diff --git "a/AdultNoteBook/Kernels/GBC/.ipynb_checkpoints/4-deep-analysis-and-90-accuracy-checkpoint.ipynb" "b/AdultNoteBook/Kernels/GBC/.ipynb_checkpoints/4-deep-analysis-and-90-accuracy-checkpoint.ipynb"
new file mode 100644--- /dev/null
+++ "b/AdultNoteBook/Kernels/GBC/.ipynb_checkpoints/4-deep-analysis-and-90-accuracy-checkpoint.ipynb"
@@ -0,0 +1,6393 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:24:44.478199Z",
+     "iopub.status.busy": "2021-07-05T16:24:44.477948Z",
+     "iopub.status.idle": "2021-07-05T16:24:44.482786Z",
+     "shell.execute_reply": "2021-07-05T16:24:44.481957Z",
+     "shell.execute_reply.started": "2021-07-05T16:24:44.478171Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "import plotly.express as px \n",
+    "import seaborn as sns\n",
+    "import warnings\n",
+    "warnings.filterwarnings('ignore')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from aif360.datasets import StandardDataset\n",
+    "from aif360.metrics import BinaryLabelDatasetMetric, ClassificationMetric\n",
+    "import matplotlib.patches as patches\n",
+    "from aif360.algorithms.preprocessing import Reweighing\n",
+    "#from packages import *\n",
+    "#from ml_fairness import *\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "\n",
+    "\n",
+    "\n",
+    "from IPython.display import Markdown, display"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:25:00.744888Z",
+     "iopub.status.busy": "2021-07-05T16:25:00.744557Z",
+     "iopub.status.idle": "2021-07-05T16:25:00.854534Z",
+     "shell.execute_reply": "2021-07-05T16:25:00.853632Z",
+     "shell.execute_reply.started": "2021-07-05T16:25:00.744839Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "df=pd.read_csv('../../Data/adult.csv')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# EDA"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:26:57.863973Z",
+     "iopub.status.busy": "2021-07-05T16:26:57.86364Z",
+     "iopub.status.idle": "2021-07-05T16:26:57.894742Z",
+     "shell.execute_reply": "2021-07-05T16:26:57.893763Z",
+     "shell.execute_reply.started": "2021-07-05T16:26:57.863943Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>age</th>\n",
+       "      <th>workclass</th>\n",
+       "      <th>fnlwgt</th>\n",
+       "      <th>education</th>\n",
+       "      <th>education.num</th>\n",
+       "      <th>marital.status</th>\n",
+       "      <th>occupation</th>\n",
+       "      <th>relationship</th>\n",
+       "      <th>race</th>\n",
+       "      <th>sex</th>\n",
+       "      <th>capital.gain</th>\n",
+       "      <th>capital.loss</th>\n",
+       "      <th>hours.per.week</th>\n",
+       "      <th>native.country</th>\n",
+       "      <th>income</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>90</td>\n",
+       "      <td>?</td>\n",
+       "      <td>77053</td>\n",
+       "      <td>HS-grad</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Widowed</td>\n",
+       "      <td>?</td>\n",
+       "      <td>Not-in-family</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4356</td>\n",
+       "      <td>40</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>82</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>132870</td>\n",
+       "      <td>HS-grad</td>\n",
+       "      <td>9</td>\n",
+       "      <td>Widowed</td>\n",
+       "      <td>Exec-managerial</td>\n",
+       "      <td>Not-in-family</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4356</td>\n",
+       "      <td>18</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>66</td>\n",
+       "      <td>?</td>\n",
+       "      <td>186061</td>\n",
+       "      <td>Some-college</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Widowed</td>\n",
+       "      <td>?</td>\n",
+       "      <td>Unmarried</td>\n",
+       "      <td>Black</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4356</td>\n",
+       "      <td>40</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>54</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>140359</td>\n",
+       "      <td>7th-8th</td>\n",
+       "      <td>4</td>\n",
+       "      <td>Divorced</td>\n",
+       "      <td>Machine-op-inspct</td>\n",
+       "      <td>Unmarried</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3900</td>\n",
+       "      <td>40</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>41</td>\n",
+       "      <td>Private</td>\n",
+       "      <td>264663</td>\n",
+       "      <td>Some-college</td>\n",
+       "      <td>10</td>\n",
+       "      <td>Separated</td>\n",
+       "      <td>Prof-specialty</td>\n",
+       "      <td>Own-child</td>\n",
+       "      <td>White</td>\n",
+       "      <td>Female</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3900</td>\n",
+       "      <td>40</td>\n",
+       "      <td>United-States</td>\n",
+       "      <td>&lt;=50K</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   age workclass  fnlwgt     education  education.num marital.status  \\\n",
+       "0   90         ?   77053       HS-grad              9        Widowed   \n",
+       "1   82   Private  132870       HS-grad              9        Widowed   \n",
+       "2   66         ?  186061  Some-college             10        Widowed   \n",
+       "3   54   Private  140359       7th-8th              4       Divorced   \n",
+       "4   41   Private  264663  Some-college             10      Separated   \n",
+       "\n",
+       "          occupation   relationship   race     sex  capital.gain  \\\n",
+       "0                  ?  Not-in-family  White  Female             0   \n",
+       "1    Exec-managerial  Not-in-family  White  Female             0   \n",
+       "2                  ?      Unmarried  Black  Female             0   \n",
+       "3  Machine-op-inspct      Unmarried  White  Female             0   \n",
+       "4     Prof-specialty      Own-child  White  Female             0   \n",
+       "\n",
+       "   capital.loss  hours.per.week native.country income  \n",
+       "0          4356              40  United-States  <=50K  \n",
+       "1          4356              18  United-States  <=50K  \n",
+       "2          4356              40  United-States  <=50K  \n",
+       "3          3900              40  United-States  <=50K  \n",
+       "4          3900              40  United-States  <=50K  "
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:27:00.834338Z",
+     "iopub.status.busy": "2021-07-05T16:27:00.834016Z",
+     "iopub.status.idle": "2021-07-05T16:27:00.839732Z",
+     "shell.execute_reply": "2021-07-05T16:27:00.838718Z",
+     "shell.execute_reply.started": "2021-07-05T16:27:00.83431Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(32561, 15)"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.shape"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Dataset has 32561 rows and 15 columns."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:27:03.81423Z",
+     "iopub.status.busy": "2021-07-05T16:27:03.813921Z",
+     "iopub.status.idle": "2021-07-05T16:27:03.864502Z",
+     "shell.execute_reply": "2021-07-05T16:27:03.863793Z",
+     "shell.execute_reply.started": "2021-07-05T16:27:03.814204Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "age                  73\n",
+       "workclass             9\n",
+       "fnlwgt            21648\n",
+       "education            16\n",
+       "education.num        16\n",
+       "marital.status        7\n",
+       "occupation           15\n",
+       "relationship          6\n",
+       "race                  5\n",
+       "sex                   2\n",
+       "capital.gain        119\n",
+       "capital.loss         92\n",
+       "hours.per.week       94\n",
+       "native.country       42\n",
+       "income                2\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.nunique()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Label column has only two categories, hence it is a problem of classification. There are no constant columns nor there are any identifier column."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:02.0687Z",
+     "iopub.status.busy": "2021-07-05T16:35:02.068292Z",
+     "iopub.status.idle": "2021-07-05T16:35:02.095924Z",
+     "shell.execute_reply": "2021-07-05T16:35:02.094689Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:02.068667Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "age               0\n",
+       "workclass         0\n",
+       "fnlwgt            0\n",
+       "education         0\n",
+       "education.num     0\n",
+       "marital.status    0\n",
+       "occupation        0\n",
+       "relationship      0\n",
+       "race              0\n",
+       "sex               0\n",
+       "capital.gain      0\n",
+       "capital.loss      0\n",
+       "hours.per.week    0\n",
+       "native.country    0\n",
+       "income            0\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.isnull().sum()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There are no null values in the dataset"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:03.73924Z",
+     "iopub.status.busy": "2021-07-05T16:35:03.738768Z",
+     "iopub.status.idle": "2021-07-05T16:35:03.745896Z",
+     "shell.execute_reply": "2021-07-05T16:35:03.745052Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:03.739209Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "age                int64\n",
+       "workclass         object\n",
+       "fnlwgt             int64\n",
+       "education         object\n",
+       "education.num      int64\n",
+       "marital.status    object\n",
+       "occupation        object\n",
+       "relationship      object\n",
+       "race              object\n",
+       "sex               object\n",
+       "capital.gain       int64\n",
+       "capital.loss       int64\n",
+       "hours.per.week     int64\n",
+       "native.country    object\n",
+       "income            object\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.dtypes"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There are 8 object type feautures rest of the features are of integer type."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:04.708192Z",
+     "iopub.status.busy": "2021-07-05T16:35:04.707812Z",
+     "iopub.status.idle": "2021-07-05T16:35:04.74255Z",
+     "shell.execute_reply": "2021-07-05T16:35:04.74148Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:04.70816Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "age                0.558743\n",
+       "fnlwgt             1.446980\n",
+       "education.num     -0.311676\n",
+       "capital.gain      11.953848\n",
+       "capital.loss       4.594629\n",
+       "hours.per.week     0.227643\n",
+       "dtype: float64"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.skew()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There is skewness present in the data which needs to be removed."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:05.649537Z",
+     "iopub.status.busy": "2021-07-05T16:35:05.648913Z",
+     "iopub.status.idle": "2021-07-05T16:35:05.661964Z",
+     "shell.execute_reply": "2021-07-05T16:35:05.661026Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:05.649498Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<=50K    24720\n",
+       ">50K      7841\n",
+       "Name: income, dtype: int64"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df['income'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Dataset is imbalanced."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:07.168945Z",
+     "iopub.status.busy": "2021-07-05T16:35:07.168374Z",
+     "iopub.status.idle": "2021-07-05T16:35:07.205495Z",
+     "shell.execute_reply": "2021-07-05T16:35:07.204571Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:07.168908Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>age</th>\n",
+       "      <th>fnlwgt</th>\n",
+       "      <th>education.num</th>\n",
+       "      <th>capital.gain</th>\n",
+       "      <th>capital.loss</th>\n",
+       "      <th>hours.per.week</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>count</th>\n",
+       "      <td>32561.000000</td>\n",
+       "      <td>3.256100e+04</td>\n",
+       "      <td>32561.000000</td>\n",
+       "      <td>32561.000000</td>\n",
+       "      <td>32561.000000</td>\n",
+       "      <td>32561.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>38.581647</td>\n",
+       "      <td>1.897784e+05</td>\n",
+       "      <td>10.080679</td>\n",
+       "      <td>1077.648844</td>\n",
+       "      <td>87.303830</td>\n",
+       "      <td>40.437456</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>13.640433</td>\n",
+       "      <td>1.055500e+05</td>\n",
+       "      <td>2.572720</td>\n",
+       "      <td>7385.292085</td>\n",
+       "      <td>402.960219</td>\n",
+       "      <td>12.347429</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>17.000000</td>\n",
+       "      <td>1.228500e+04</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>28.000000</td>\n",
+       "      <td>1.178270e+05</td>\n",
+       "      <td>9.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>40.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>37.000000</td>\n",
+       "      <td>1.783560e+05</td>\n",
+       "      <td>10.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>40.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>48.000000</td>\n",
+       "      <td>2.370510e+05</td>\n",
+       "      <td>12.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>45.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>90.000000</td>\n",
+       "      <td>1.484705e+06</td>\n",
+       "      <td>16.000000</td>\n",
+       "      <td>99999.000000</td>\n",
+       "      <td>4356.000000</td>\n",
+       "      <td>99.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                age        fnlwgt  education.num  capital.gain  capital.loss  \\\n",
+       "count  32561.000000  3.256100e+04   32561.000000  32561.000000  32561.000000   \n",
+       "mean      38.581647  1.897784e+05      10.080679   1077.648844     87.303830   \n",
+       "std       13.640433  1.055500e+05       2.572720   7385.292085    402.960219   \n",
+       "min       17.000000  1.228500e+04       1.000000      0.000000      0.000000   \n",
+       "25%       28.000000  1.178270e+05       9.000000      0.000000      0.000000   \n",
+       "50%       37.000000  1.783560e+05      10.000000      0.000000      0.000000   \n",
+       "75%       48.000000  2.370510e+05      12.000000      0.000000      0.000000   \n",
+       "max       90.000000  1.484705e+06      16.000000  99999.000000   4356.000000   \n",
+       "\n",
+       "       hours.per.week  \n",
+       "count    32561.000000  \n",
+       "mean        40.437456  \n",
+       "std         12.347429  \n",
+       "min          1.000000  \n",
+       "25%         40.000000  \n",
+       "50%         40.000000  \n",
+       "75%         45.000000  \n",
+       "max         99.000000  "
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.describe()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "All the columns are not present as they are of object type. Count of each column is 32561 showing there are no null values. Mean is very much greater than the median in capital gain and capital loss stating that there is high skewness present and data is skewed to the right side. Also there is high variance in Capital gain and Capital loss column. Min, Max, and interquartile ranges have variable difference, that means there are outliers present in the data."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Univariate Analysis"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:08.839479Z",
+     "iopub.status.busy": "2021-07-05T16:35:08.837615Z",
+     "iopub.status.idle": "2021-07-05T16:35:09.131486Z",
+     "shell.execute_reply": "2021-07-05T16:35:09.130826Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:08.839436Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<=50K    24720\n",
+       ">50K      7841\n",
+       "Name: income, dtype: int64"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x576 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(15,8))\n",
+    "plt.subplot(1,2,1)\n",
+    "df['income'].value_counts().plot.pie(autopct='%1.1f%%')\n",
+    "plt.subplot(1,2,2)\n",
+    "sns.countplot(x='income',data=df)\n",
+    "plt.ylabel('No. of People')\n",
+    "df['income'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Dataset if highly imbalanced. There is less than 25% of >50K income category while more than 75% of <=50K income."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:10.72801Z",
+     "iopub.status.busy": "2021-07-05T16:35:10.727634Z",
+     "iopub.status.idle": "2021-07-05T16:35:10.804001Z",
+     "shell.execute_reply": "2021-07-05T16:35:10.803077Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:10.727975Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "#Separating categorical and continuous variables\n",
+    "cat=[feature for feature in df.columns if df[feature].nunique()<45]\n",
+    "cont=[feature for feature in df.columns if df[feature].nunique()>45]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:11.24824Z",
+     "iopub.status.busy": "2021-07-05T16:35:11.247852Z",
+     "iopub.status.idle": "2021-07-05T16:35:11.596616Z",
+     "shell.execute_reply": "2021-07-05T16:35:11.595911Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:11.248209Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Private             22696\n",
+       "Self-emp-not-inc     2541\n",
+       "Local-gov            2093\n",
+       "?                    1836\n",
+       "State-gov            1298\n",
+       "Self-emp-inc         1116\n",
+       "Federal-gov           960\n",
+       "Without-pay            14\n",
+       "Never-worked            7\n",
+       "Name: workclass, dtype: int64"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x1080 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(15,15))\n",
+    "plt.subplot(2,1,1)\n",
+    "df['workclass'].value_counts().plot.pie(autopct='%1.1f%%')\n",
+    "plt.ylabel('')\n",
+    "plt.subplot(2,1,2)\n",
+    "sns.countplot(x='workclass',data=df)\n",
+    "plt.ylabel('No. of Individuals')\n",
+    "df['workclass'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There are 9 workclass in total including Never worked and one unknown category(?).Most individuals work in private sector and there are very few who have never worked or work without pay. There are 3 categories of govt job provided state, federal and local among which no. of people working in the local govt is highest."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:11.598122Z",
+     "iopub.status.busy": "2021-07-05T16:35:11.597716Z",
+     "iopub.status.idle": "2021-07-05T16:35:12.108023Z",
+     "shell.execute_reply": "2021-07-05T16:35:12.106821Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:11.598081Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "HS-grad         10501\n",
+       "Some-college     7291\n",
+       "Bachelors        5355\n",
+       "Masters          1723\n",
+       "Assoc-voc        1382\n",
+       "11th             1175\n",
+       "Assoc-acdm       1067\n",
+       "10th              933\n",
+       "7th-8th           646\n",
+       "Prof-school       576\n",
+       "9th               514\n",
+       "12th              433\n",
+       "Doctorate         413\n",
+       "5th-6th           333\n",
+       "1st-4th           168\n",
+       "Preschool          51\n",
+       "Name: education, dtype: int64"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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hEVHb8xKA3lYX0V7ES8WI2dq6TVbXQZ1eEoBXMuYt4PdWRNRu8X9gRERtSabrZgCXWF1Ge/Og7dmA1TUQATgHwH1WF0FE1FQMh0REbUWmqyuAv1tdRnuUKGWjp2mbs6yugwjA7zPmLZhqdRFERE3BcEhE1HY8AyDO6iLaq4dsT3usroEIgA7gtYx5C7pYXQgRUWMxHBIRtQXB6aTc7bAZUqRk7ATZts3qOogAdAfwuNVFEBE1FsMhEZHVgtNJH7W6jI7gEftTFVbXQBRyY8a8BRdaXQQRUWMwHBIRWe9ZAC6ri+gIukrh+FGye6fVdRCFPJ0xbwGPpCGidoPhkIjISpmuWwBcZHUZHcmjtieLra6BKKQngAesLoKIqKFEKWV1DUREnVNwOulWcNQwrJSCusz7pz1Zqnc/q2tpi5Tfi9zX/g/K7wNME5EDpiBu2o3I/+hv8ObugWg67Gn9kXDBnRDdOOVZf2ke8t97AEqZQCCAmDGXIGbUxVB+H/Le/SMC5QWIGTUHMaPnAAAKP/0HokdeBEdqXyvealthApicPX/OKqsLISKqD8MhEZFVMl0fg6OGLWKvmbZitvfhSVbX0RYppaB8bmj2CKiAH7mv/hJdZt8K010OZ++xAICCj/4GZ/ehiBl16h5JKuADFCCGDaa3GkefuwOp3wmGSm/+frgmXYfcV36BtO8+DG/ePpSt/QiJF//UirfZ1mwBMDp7/hyf1YUQEZ0Np5USEVmB00lbVG/JmTBQDu6zuo62SESg2SMAAMr0A2YAEEFEn3EQEYgIHGn94S8vOPNZ3QYxbMFnAz4g9ANm0XQonwcIBIDQz5xLlr6CuGnfaZ031fYNBTDP6iKIiOrDcEhE1NoyXfEAHra6jI5MBNpjtidyrK6jrVJmAEdfuAuH//EdODNGwpE+4ORrAT8qty5ERK/RtT7rL8vH0efvxJF/3gLXxKthxCTA2WsU/KV5yHn554gdeymqdq+CPaUPjJiE1npL7cF9GfMWDLS6CCKis+G0UiKi1pbpehjAPVaX0dEphcBs70OH96n0nlbX0laZ7grkvfcAupz7I9iTMgAAhZ88DrE50eXcW8/6rL+8EPnv/QnJV/8OelT8iesq4Mext36H5Kt+g5JvXkWgLB9RQ2cjst+Elnwr7cUX2fPnnG91EUREdeHIIRFRa8p0ZQC4w+oyOgMR6I/bnjhodR1tmeaMhrPHcFTvWw8AKPnmNQSqyxA/+wf1PmvEJMCW2BPuQ1tPuV6+YQGih86C5+hOaI4oJF7+fyhb816L1N8OnZcxb8Ecq4sgIqoLwyERUet6AIDD6iI6iyGSPbGn5B62uo62JFBVCtNdAQAwfR64szfAltAN5Zs+g3v/eiRe+guI1P7tgb+sAKbPE2zHXQHP4W2wJXQ72ba7AtV71iBq6CwovwcQAUSCn9NxD2fMW2DUfxsRUevj/5yIiFpLpms0gBusLqMzEYHtUduT+670/rFb/Xd3DoGKIhQs+DugTECZiBw4DZF9x+PAXy+D4UpG7iv3AgAi+09G3JQb4MnZjYqNnyDhop/AV3gIxQufO9FW7PirTkxHBYDSZa/DNfk6iGiI6DUa5esXIOe5OxE9insv1TAAwdkDj1ldCBHR6bjmkIiotWS6vgIwy+oyOhul4J3qeazwCJLSrK6FKKQIQO/s+XNKrS6EiKgmTislImoNma6LwGBoCRHY/27/5y6r6yCqoQt4tAURtUEMh0RUKxG5T0S2ishmEdkoIm1yq0ERyRaRxNDnFVbXU6tMlwbgQavL6MzGyc4JKSjKs7oOohp+mjFvQVeriyAiqonhkIjOICKTAFwCYLRSajiAcwEcsraqdm0ugGFWF9GZicD5iO2p7VbXQVRDBIA/WF0EEVFNDIdEVJs0AAVKKQ8AKKUKlFJHRWS2iGwQkSwReV5EHMCJ0bu/hEYY14rIaBH5TET2ishtxxsVkV+IyJrQaGSt3xSJSLSIvBDqY7OIXB26fkPo2hYRqXcUrq6+ROS3IrJTRL4RkddF5N7Q9T4i8qmIrBORpSISnsOqM10RAO4PS1vULJO1reMSUFpgdR1ENdycMW9BH6uLICI6juGQiGrzOYDuIrJLRP4pIjNExAngRQDXK6WGIbjb8e01njmolBoJYGnovmsATEToJ+Micj6AfgDGAxgJYIyITK+l798CKFVKDQuNWn4tIukITsucFXp2nIhcUVfxdfUlIuMAXA1gBICLAIyt8dgzAO5SSo0BcC+Af9b7u9QwdwPgTpltgAgiH7I9vbX+O4lajQ7gl1YXQUR0HMMhEZ1BKVUBYAyAWwHkA3gTwI8A7FdKHd/Y4yUANcPdh6FfswCsUkqVK6XyAXhEJA7A+aGPDQDWAxiIYIA73bkAnqxRSzGAcQAWKaXylVJ+AK+e1vfp6uprCoAPlFJupVQ5gI+A4GglgMkA3haRjQD+heDoafNkuuIB/F+z26GwmaltGhOPsiKr6yCqYW7GvAXpVhdBRAQwHBJRHZRSAaXUIqXU7wHcCeCKeh45fsq1WePz418bAATAX5RSI0MffZVSz4nIHaHpqBtDI4ThUGtfZ7lfA1BS4/6RSqlBYajjxwBcYWiHwkQE0fNt/95sdR1ENTgA3GN1EUREAMMhEdVCRAaISM1RvZEA9gLIEJG+oWvfBbC4Ec1+BuB7oVE6iEhXEUlWSj1ZI5AdBfAFggdEH68lHsBqADNEJFFEdAQPkj9b37X2BWAZgEtFxBl67RIAUEqVAdgvIteG7hcRGdGI93amTJcDwVBNbcz52tpRsajg+XLUlvwoY96CLlYXQUTEcEhEtYkG8JKIbBORzQAGI3gm1y0ITr3MQnBE8OmGNqiU+hzAawBWhJ5/B0BMLbf+CUB8aOOZTQDOUUrlhPpfCGATgHVKqQ8a25dSag2C0183A/gEwSmwx0PCjQC+H+pzK4DLG/re6vBdAKnNbINagAhcD9ie32B1HUQ1RAO4y+oiiIhEKWV1DURErUZEopVSFSISCWAJgFuVUuvD2kmmSxAMmOGYmkotwFQoGeZ5Tq9ERG0/oCCyQhGAntnz57TN81qJqFPgyCERdTbPhDadWQ/gv2EPhkFzwGDYpmmCuPttL66zug6iGroguAkYEZFlOHJIRBRuma6FAGZaXQadnamkcKjnOWcVnFFW10IUchRARvb8OT6rCyGizokjh0RE4ZTpGgoGw3ZBE5XwG+OVtVbXQVRDOpq/3pmIqMkYDomIwuuO+m+htuJ6feFgJzzVVtdBVMOPrC6AiDovhkMionDJdLkQ3KWU2gldVNI84/U1VtdBVMPsjHkLeltdBBF1TgyHREThMxcA16+1M9/Vv+hvh89jdR1EIQLgh1YXQUSdE8MhEVE4BI+v+LHVZVDj6aJS7zXeWmV1HUQ13JIxb4HN6iKIqPNhOCQiCo9ZAAZYXQQ1zff0T/oY8HOHSGorUgBcZnURRNT5MBwSEYXHjVYXQE1niNn1p8a7K62ug6gGnnlIRK2O5xwSETVXpssG4BiAeKtLoabzKf3gQM+L6QHohtW1EAFQAHpnz5+TbXUhRNR5cOSQiKj5zgWDYbtnk0CP2/UPOXpIbYUAuMXqIoioc2E4JCJqvuusLoDC4yfGe101mAGr6yAKudbqAoioc2E4JCJqjkyXHcAVVpdB4WEXf68f6B9z9JDaikEZ8xYMtroIIuo8GA6JiJrnPABxVhdB4XOP8XYqwAX51GZcY3UBRNR5MBwSETUPp5R2ME7x9Zmrf85zD6mtYDgkolbD3UqJiJoqOKU0D4DL6lIovKqVfdcgzwv9ABGrayECMCB7/pxdVhdBRB0fRw6JiJrufDAYdkgR4u1/g/71GqvrIArh6CERtQqGQyKipuOU0g7sN8YrMVbXQBTCcEhErYLhkIioKTJdDgCXWV0GtZwo8Qy6UlvK0UNqC0ZlzFvQ2+oiiKjjYzgkImoaTintBP5gezHC6hqIQvjDKCJqcQyHRERNM8fqAqjlxUr10DnaynVW10EEYLbVBRBRx8dwSETUNNOsLqApDpWaOOelSgx+sgJD/lmBx1Z6AAC/+NyNgU9UYPhTFbjyzSqUuOveyTpgKoz6VwUuea3qxLUb363C8Kcq8Ouv3Ceu/WmJB+/v8LXcm2klD9ies1ldAxGAGRnzFhhWF0FEHRvDIRFRY2W6EgEMsrqMpjA04OHzndh2RzRWfj8KT67xYVt+AOf1MbDlx1HYfHs0+nfR8JelnjrbeGyVF4MST/7zsflYABGGYPPt0VhzNIBSt0JOuYlVRwK4YmD7z1VxUjn8PG3tRqvroE4vBsBYq4sgoo6N4ZCIqPGmAmiX59+lxWgYnaYDAGIcgkFJGo6UKZzfx4ChBd/SxG46DpebtT5/uMzEgt1+/GC0/cQ1mwZU+xVMpeALALoG/G6hB3+Y6Wj5N9RK5tuetboEIgCYZXUBRNSxMRwSETVeu5xSerrsEhMbcgKY0E0/5frzG324qG/ts9fu/tSNv57rhFYjGg9K0pEUqWH0vypxaX8De4pMmAonQmhHkCDlI6drmzZbXQd1egyHRNSiGA6JiBpvutUFNFeFV+Hqt6rw6IVOxDpOJr0HlnhgaMCNw86cDvq/XT4kRwnGpJ8Z+h690ImNt0Xj55Md+O1CD/44y4EHlnhw3dtVeHadt0XfS2t5yPavjvFGqD2bnDFvQccZkieiNofhkIioMTJd0QBGWV1Gc/gCwWB44zAbrhp0MgS+uNGL/+3249WrIiBy5qzZZQcD+HCnHxmPluNb71Tj6/1+fOfd6lPu+WCHD2PSNFR4FfYWm3jr2ki8s92HKl/dG9y0F8lSMnaitnWr1XVQpxYBYJLVRRBRx8VwSETUOJMBtNv5kkopfP9DNwYl6rhn0skBiE/3+PHXZV58+K0IRNpqX075l3OdOHxPDLLvjsEb10RgVi8Dr1x18hhAX0Dh0VVe/HKKA9W+k4syAybgDbTku2o9j9ieqrS6Bur0eKQFEbUYhkMiosZp1+sNlx0K4OXNPny934+RT1dg5NMV+Hi3D3d+XI1yr8J5L1dh5NMVuO1/wRHBo+UmLn61qp5Wg55c48XcETZE2gTDUzRU+RWGPVWBMWk64pztcv+eM6RL0fjRsmuH1XVQp9bup7UTUdslSrX/qT5ERK0m07UIwAyryyDrHDSTVk73PjbR6jqo0yoDEJc9fw6/gSOisOPIIRFRQ2W67AAmWF0GWau75E8YLnt3W10HdVqxAPpYXQQRdUwMh0REDTcOgNPqIshaIpBHbU8WWF0HdWrtelMsImq7GA6JiBpuqtUFUNvQS3InDJSD+6yugzqt0VYXQEQdE8MhEVHDDbO6AGobRKA9bvtHrtV1UKfFkUMiahEMh0REDdff6gKo7egnRyb0kSMHrK6DOiWGQyJqEQyHREQN18/qAqjtEIH+uO2JQ1bXQZ1Scsa8BV2tLoKIOh6GQyKihsh0JQOIs7oMalsGy4GJPSX3sNV1UKfE0UMiCjuGQyKihuGUUjqDCIzHbE/ut7oO6pRGWl0AEXU8DIdERA3DcEi1GiF7J3ST/KNW10GdTm+rCyCijofhkIioYRgOqVYisP/d9uQeq+ugTqeX1QUQUcfDcEhE1DAMh1SnsbJrQhoKebQFtSaGQyIKO4ZDIqKGYTikOonA8bDtqZ1W10GdSreMeQsMq4sgoo6F4ZCIqD6ZLg1AH6vLoLZtkrZtfCJK8q2ugzoNHUB3q4sgoo6F4ZCIqH49ADitLoLaNhFEPGR7epvVdVCnwqmlRBRWDIdERPXjlFJqkBna5jHxKCuyug7qNDKsLoCIOhaGQyKi+nFKKTWICKL/ans2y+o6qNPgyCERhRXDIRFR/RKsLoDaj3O1daNcqCixug7qFBgOiSisGA6JiOrnsroAaj9EEPuA7bmNVtdBnUKS1QUQUcfCcEhEVL84qwug9uVibdXIaFSVWV0HdXjxVhdARB0LwyERUf04ckiNogni7re9uN7qOqjDi7O6ACLqWBgOiYjqx3BIjXaFtmx4FKorrK6DOrQ4qwsgoo6F4ZCIqH5xVhdA7Y8mqstvjZfXWl0HdWhxVhdARB0LwyERUf04ckhNcq2+eIgTnmqr66AOy5Yxb0GU1UUQUcfBcEhEVD+GQ2oSXVTSr4zX1lhdB3VocVYXQEQdB8MhEVH94qwugNqv7+hf9rfD57G6DuqwuGMpEYUNwyER0dlkuuwAnFaXQe2XLir1F8abq6yugzqsOKsLIKKOg+GQiOjsOKWUmu0W/dO+Nvi9VtdBHVK01QUQUcfBcEhEdHZxVhdA7Z8hZvrdxn85etgM1fvW4cizP8KRf/0QpSvfPuP1stXv4ei/b8fR5+/EsTd+DX9pHgDAV3gYOS/+FEefvxOeI9sBAMoM4Ngb98H0uVv1PbQQvTkPi0hARDaKyBYReVtEIsNV2Gn9ZIrIvWFqi0fEELUQhkMiorPjT+UpLG7V/5ehI+C3uo72SJkBFH3xFJKv/QPSf/BPVG5bDG/BwVPusaf0QercvyP9e08gcsBUFC96AQBQvvETxJ97K5KvyUTZ6veC1zZ8jKgh50CzdYgZ4839Xq5aKTVSKTUUgBfAbTVfFBGjme0TUTvCv/BERGfHb+YpLGwS6H6H/sE3jweummp1Le2NN2cXNEcU8t7+PWCaMOLTUL17JeyJPU7c4y/LQ/4H86HHJED5PIBSAADlrUbhgkcB0WDEJsJ0V6B69yooZSJy4NSOEBCbNXJ4mqUAhovITAB/BFAMYKCIDAIwH8BMAA4ATyql/iUiaQDeBBCL4PeUtyullorIhQD+HKqtQCk1O9T+YBFZBKAHgEeVUo8DgIjcA+B7oXv+rZR69GzXiajlMBwSEZ0dd5mksLnDeL/rU56L8mxK15SmC6CgoBSgBEpBoABRAJTVpbYp3qKDdl/RkeheNz1YYsQmmnufvSvesNl9EYGqE9MLPf4qR2y/8Ubq+bdW5n7+TJQeFWdGBKqqtYAnWjdsBkSUBHyqYsmLAWdcEpwpvfxRmulBoMrKt9ZsClpY/rCERggvAvBp6NJoAEOVUvtF5FYApUqpcSLiALBMRD4HcBWAz5RSD4iIDiBSRJIAPAtgeujZLjW6GQjgHAAxAHaKyFMAhgO4BcAEAAJglYgsRnBE9IzrSqkN4Xi/RFQ7hkMiorNjOKRmqRapWhAVmfVWbIw3z2ek3nN48+f7kg4akUdL9PTqPF18old6o/UId6QeW+1ApNep2/2GXVN23a87TL9uN/2GwwzoduXX7QjoNgQ0m2bqhhYQQ0xN05VmGApimJpmKIgNEBtECaBMwFRQylQwVehrQIWuwzQBBSjTBEwVDKomAGVCmaHPTTM4CmcqFXxNQYV+Db6uQm0gGHbNUNgN/YoavyolofahoACYEmxbCY5/DYXgfcevKe2jfevSyzXl+HHFit2oUPJstL1ved52+w8OvXUAgAYo+aZgT8LhsuKIngv/XF12cH/kXbOnH7IdfBXveQ5q/QekVidER5rvb9jSxcgpQLXPp7sKt+jm1g+jLho2oDIlNtpEcJRLq/Gh17imIxhQ2iIDuLo5z0eKiA/BWRL/BvAcgMkAViul9ofuOR/ABBG5CUAVght19QOwBsDzImID8L5SaqOIfAkgpsazl4WCJAAsALATwFgAeQBSAEwF8J5SqhIARORdANMQ/P2u7TrDIVELYjgkIjo7hkNqtKOGnvN6TMzuj6MjI/N0fShEJgDA+VvMlUa+GTdVH6tvmLjVfM57gyQcKtWurvja1s2+VRVEljiWRNjNLQ57RKmpJcaVi55apEq6FqIyvUh5U4uVllAGe0w1op1eJGgKSVLHv+UBzXAHdEdVQHdW+3WnJ2A4PX4jwu83Inx+I8Ln1yNNv+EM+I1I5Tecym9EIKA7tYDu0AOaXTN1u2Fqhs0Uw6403aGgOZWIE5BIiES05u9ndIwdulEAZ9wPxwNAZGQuPGYenHG3jz5xT+yn2Lb1aWw8mIMB3UbD7/z2gJjoZFww/hj+s/DBeH+gHBH2DLiiEhAd8GPKoDlIiEnFh6ufc948+54G1aGUaQIqEEzCKhAKzoFgUFaBUBAOQCmlan4dCug4GdBD950I5OpkID8R3FWwndDnoa9D9waDuTIVtIjm7qrjRjCg/UcpdRcAiAgAVNa4RwAsArBJKfVQzYdFZDqAOQBeDI34nV7PzQC2hD6v+f/TAPh9KFGbw7+URERnx3BI9VKAWuN0bH8tNiZvWYQzza1pAwCknX7flO2mtyhtcJeqI2v0cWqyPzl9gVE5xhN4KPBDqci2+Z2HSmJmFG7CL/SFJZO1bR6v5k1eF+soXpHi9H3tdNgOGkayR6QXQpuEiFJmfDmOpZagMK1QlXctVJ60YqikUmXEVfijIrx+l9NXmSxAVHjfr5gB3V4V0B3ugO6o9utOt9+I8IY+fH4jMuA3nH6/EWn6jQjl150IGBES0B1aQLdrAc2um5rNFvzQHUp0uxItGDyBSARHok7YcXg9SisL8IfXb8J91z2H7GPb0Dt16Ml6lMLm7OVwe6uQGJuGbl364OWFD+L6aXfjxa8eQMD0Y8qgS3Awfxc8Pjf25W5BWVUR7IYDvkDDTxgR0Y6PKta4WMe9DW612Zq75tAEUHTatasAzBCRzQC2AVgL4PcAZonIdwA8COBDAIkADiulnhWRGAA/B3AdgEUi0gvAGARHCV9FcLTx0VD7dwHog+AU1l8D+L6IzEfwt+1KAN8Nff5iLdeJqAUxHBIRnR3DIdWq5nTRnXbbAFNkMIDBZ3umdw7SypN9x3L8ZYGBlYaSo+djffGW/g+NundPVr8hUc/0u8P2cdmF9s93TSrVirwpiSg1r/YurbymYqnxazncVxeV4gU8WQ7HnpURzoLVEQ5zT5QtbluM1mtbDy2mrn6jqlVZciny0opUaddCVZ1WBH9KsdK7VMAZ5Uas3YdEDUho6HsXKM0IeKKNgKdFdvM1RfMFdEd1aOTTfaHudv7XERmfV37U/qeXr/amOKOrewYqSxZ8Ok96J2SUie7E7iPrBkbYHPD7qgNfbX7bbqqAtnDj64VXjrulKiG2q/bXD36S1it5kNk1oY9eXl0ixRV50DQNcVHJLfEWWlNLnJ/5bQBLlVIXi0gcgDIAFwPoi+D3jrcC+BjBDWp+EZqWmgzgfgBHQh/vIhikvQBuBHAJTm7wVQBgL4A3Qu2+CGB16LV/H19XKCK1XieiliNKcdE7EVGdMl06uGMphRw19Jw3YmJ2L4iOjMjT9WEQafBWl65KVfDM44GEzcNuW5wXG9VFVS7ofWXPn5ZsMQ4fWG3smdit+5ZVGb02DFkss3a+hB/EeZU9Qz9Uuc7YV26D1xwtgDZC9uy6Qf/66Ln6elcCygaLwAEERy7324xDq5zOoysinO6tDntUga53N0VSG1qf4VeexDLkpRWp4vQiVHQtVL7UYiChTNljqxDj9CJeU0gWwFZ/a+HlVwrn79sLhwg+6NUb1x/Ixl/T0tHP4QAA/D43FwMdDtwQHw8AmLFnD5IMHZOiojAxMgpdbTZk5uagt92Bgz4vMhzOwDmuxMrUiJiqPx/Jjnlo4KQDASPC5zecPr8R4fMZkQG/EWH6jQgzoEeI33Cq4KinIzTt1mZTmmGcOuVWi0Bw1LO1tz+ddcfTsxY2pwERyQDwv9BxFhCRTwFUAHgfwbWEFSKSCaDi9GmloftHArhfKXVZLW0tAnCvUmpt6OtsAFOUUkckON36AaXUuc2pn4jChyOHRERnk1kaQKYrgPBuF0/thALUWqdj+6uxMXnLI5xp1XVMF22IiTvUHgESne5i0boMHeZRgUMr8/+XPzn58ikAlq0+hIn5+Rl5k0d9Ysywf93vE7l0xZs9bkzz9IzuJVX+I8bust0bj/Xtu8nfdyb8QAQ8VRdoa9Zery+sHK3t7t7b5+/d21fR44byk+eDF2pawdoI58HlEc6yDQ6H/YhhpHgFGQjuLHkKvyGO3C7onttFutc5PKOUiq9AfkoJCtKKVHnXAuVOK4aZXKJscZWIiPQgzgggWcJ8PqghgjsTE/GH3Fxcun8frnS50M/hwD8K8jHE6USe34dq08RrJcUwROBWJn6YkIxhzgj8KucoPKYZWkencGtCAhJ0Q/9lzoHYgELs71JSEF+656wjvo1RY8ptdUB3VvsNp8evO2tOufX7jYiA34hQfiPCPD7l1h8Kn6ZmM0Ifx6fcOkJTbo+Hz9PDeXW4aq9hDoDpAC4FcJ+IDKv5Ymhn0nWhLz8EkANgbCj4GQCSRWSRUmpmHe0fn5HBdYdEbQz/QhIR1c8DINLqIqh1VItUfRIVueXN2GjPDru9f0OmizbE5G2mFwCc7kKbiIhm67v/UOWOGUWeCd8Md/ScCmD5aveeCatWXpPau8+aJRelfzT+Qllgf1dd+80HEVf38o3oMhNKKe2Ye72xu8xdVYUx75tTx75vBo9N7C55R67XF+67RFtp9JRjg0XgSjDNxAsqqxIvqDx5XINbpHqzw75veYSzaI3TiX12W3xFcB1j/esSRaQ4BknFMUja0b3uVXURblWWXIr89CJVml6IqvRCFUgpUdKlAs7oasTa/UgQhURpxNK8CZGR6Gm348NevU9cuysxCQDwdkkJro+Lw5jI4F/TWw4dRFebDek2G17q0RMAcMDrxWMF+ehtd+Bv+XnoabfjJ4lJyLDbG1pCg5w65bYsrG0DJ6bcVgV0Z5Vfd3qUaOXArLC1LyIagO5KqYUi8g2AbyEY9ssRPM8QSqkAgJGnPfpU6PkMBEcOZ4aulyN4dAURtQMMh0RE9WM47OBydD3njdiYPQuiI53HgtNFx4e7jz65SAcAp7vICQBGxOReXt8utSj3jWFX9PhJ7vBAz8kAlq829kzYt3f8jGO5/fYNH/Gp+xrjzamX47+e19V3F3+OiwebqRGjvakRgDdQbOwtX6kfrkoVUw04pJK7PuS/vutDuB4azMBkbWvWDfrXRdO0rC4xqBosEhz9dioVMd7tGTLe7QFQCgAwAXOPzbZ/ZYQzd2WE07vdbo8u1LUeKnhmXaNVOyX2gBOxB1Lqzn5GQHkTypCfWqQKT+7GCiSWKXtsJaKcPnTRTSQLUG96SzZsyPWfnP19zOdHinHqANtjBfn4SWISXikuxjWuOKTbbHg0Px9/S09vylu0jKZMm+avdtn81a7QpWYd1CgiryO4djBRRA4D+COA74qIC8Hw/rhSqkREPgLwjohcDuAupdTSBnbxIoCnRaQawKTm1EpELY9rDomI6pPpygHQ4LVb1PYpQK0LTRddFuFMrda0gS3Zn6tSFTz7eCARAMpieu5aO+aX/QHAXfLkZijP8F7Rw1aPT7p4PABs1g8sX23smQCBDpj+QYOWfpOQeHCqCAwPHFUv4Ierl2LmSAQ3CgEASLFnu21nWb6UekdIcFfIU/tHRcnl+rLt1+hL/IPlQB9DzAYlomO6nrfG6Ti4IsJZucnpsB81jDQf0PP4WQctTinlqkTBgacP2fN2lUf5fUp/fs6gJcmlSo+rRESkG3G2AJIez8+Pfbm4CN1sNvgUIAL8r1dv7Pd68IujR1EWMDEswomH07viz8eOYX11Ff6Wlo5HCvLxj67dWuWttKCkQTu2FzSngdB00HIEp3n6lVJjReRmAJ8rpY7WuGesUuqsfUnwz8afAFwbau8ppdTjIjITgFcptTx034sIjjC+05zaiSi8OHJIRFQ/7ljaARyfLvpWbLRnexinizbEpO1qD4Lb/sPhKYk/fl13jCwNuFdhf0XW+IGu8ctj7YmTa44gQjRj+/YZM12u3K1Dh30V6dA8vW7DEzO/i+dLn1F3LlqL8WMhEq3iHYO8E5MGIaCq9QMVy4zsiij4zBHHp22WIjruP4ELJv0ncAEAYKAc3HeD/vWhC/Q1USkoHixS+8h4SiCQfEllVfIlNaalVopUbHI6spdHOIvWOh2y32ZLqBLp3SIbsYhIaTSSigMBBOwaTG8AP1i2e0byFcnB2AGgy6wusJUklse/ElBHdlY4dRMm/Ao7u2L1s5uL+t+RmuR+5lhB1yrTtAFApCYoDgTws6NH8buUlLCXbIGSMLVzzmnB72YEzyc82sh2bgbQHcBApZQpIse3g52J4CY3y5tXJhG1JI4cEhHVJ9O1DcAgq8ugxgtOF43evSA6KuJY8DD6Vj28/bj7/+NfMvAIpgOAggQWzviHBhFRylPmKXnSDsBp1yKKruhxZ0BESwKALP3g8lXG7tAIIqBp/qqhw75cGxubP03keOhzFTyJn27diuETTg9nUuE7YOwq26/luwfKWUa+7fB5Zmnrt96gLywbr+1IjxBv/8a+vwAQ2Gm3Za+McOaudDr9Ox322GJN66lEujS2rbp487048OgB9Hug31nvq9pThSPPHUG/v/RD7lu5iBocBXuiHXn/PWYOvyI9d8fTB2K/e2lGVrdieNOKgcRSZYutQlSE98Q0Vke4am4F5YN2bI9tbiOnjwqKyDUITgc9guCGN5MAbAfwEoKb1NgAXKuU2lFLW6sBfFsptafGtQwAKxGM9PkInnP4fQQXZY5F8M/nLzmKSGQ9hkMiovpkur4AwK3W24Hj00Vfi43J/ybCmVytaW0i1L/yV/9eewB9jn/99YwnihAKTp7SF1Yos3gSAPSLHbNidMK5J9ZlnR4QASAxKXvdwIHfpIuoE7umFiAx53H8fPde9Jt0xm6WSgW0o1Xrjb3lAakOjKnvKIpUFB27Rl+853J9GfpIzgBNVGJT3/dRXc9dHdwttTrLYXfkGka6H+jelGmp9YXDsnVlyH07F4HyAHr+rCci+0bCW+jF4WcOQ/kVut7cFcXfFCNmZAyiB9W9maqrUhUml6AgvUiVdS1Q7rQiBJJKlR5fgcgoD1w2P5IltDFLG5A9aMf2Xs1tRET2AygGoAD8Syn1TB1HUDyslPqHiPwYwGil1A9qaasQwCMIHlqfD+AnSqndpx+FEZpWGgXgegADAXyolOrb3PdCRM3DaaVERPU7ZHUBVDe3SPUnUZFZbwani/YLTRdtM1wVKr9mMAQAzfQXm7qtCwAYzok2X9UnAIDdZesm9Y8duzLaFjcRAIYFekwGcEpALMjPGLOyOK1kxMhPl0dGlk0GgEQUpN2PX6XlIP3go+reQ4fRYxKCu04CIrrZNWqct2sU4AnkG3vKtulHq7qLid6oRS66pDwRuDLlicCVAJQaJzu332B8fewcbWN8HCoGizT8nMP0QCD1iorK1CsqKk9cK9OkdIPDcWB5RETJeqdDO2AzEquD01KbtW1o7JhYxI6JReXOShx79xh6/bIX7Al29P5V8G16jnngK/bBme7EoX8dggoopFyVAkfqqQOFpVGSUBqFhN1d686vDq+qTCpFXmg31sr0IuVLKVZaQjkcMdWIcfiQIApJEjwEviU1a61hDVND5w4mA/hCRM4YEQx5N/TrOgBX1XGPA4A7tG7xKgDPA5hWx73vK6VMANtEpEPM8SVq7xgOiYjqd9DqAuhUubqe+2Zs9O6PoqMcLbW7aLhMDq43PGXXTz3gKTf1YMbS7ANGoerTPEAlA8BXOa/2vqz7j0sktOFMbQHR73fErVt7+eSuXbct79V73WARxAFAGo72eBD39NiPXnseU/cW5EvqxFOKcehJ/iHxM/xD4qEVuLOMXWUlUu4bVfe5hCJr1MBBa3wDBwFAFKrL5+grN1ynL3aPkL09bRLo2djfj1hTuWZUu4fPqHafuOYDfNsd9l0rnM781RFO/y67La5E0zIQ3DGzUaIGRMGb74W/3A8j5uS3Ocf+ewwpV6Wg8ItCdJnRBbZEG469cwzdb+ve2C7gsUvU4ST0OpxUd4DUTOVPKMOx1GJVmFaEiq6FyptWBDOxTNlclYiO8CJON5EiQHPWauY149kTlFJHQr/mich7AOr6+3TG+YQi8hmAFABrQyOJh3EyRL4H4IWzdF1zPXfrbHJERGfFcEhEVD+GQ4spQK13OHa86oo59k2EM6VaZCBE2sUOspO3m77Trxn+ymqfPZjHRDRdM7pvN/0HkwHAHahI3lK8dNmwLtOnHL9/WKDHZAGWrzxtiumRI4Mn5+f3zB016pO1dkf12OPXe2F/30dxR98datD2f+CeqhLpMub0GsxE5zBvohPwmxXG/oql+sGKOPGrYaffV1MlImLeCpwz/q3AOQCA3nL04PX6wuw5+ipHVxQMFmnaeXY2wDbc4+0/3OPt/6PSk2cDHjSMI6sjHEeWR0RUrXKruAMBNRS1fO/iOeaBPdkOEUF1djWUT0GPPvHbhModlbDF2eBIdcD0msEYIgh+3kJMTYz8OKTlx0la1lkmfsZUqaLkEhSkF6qyrkWqOq0IgeQSZcRXwBnlhsvuR5IgGP5r0djNYs4gwfMtNaVUeejz8wHcD2AGGnA+oVLqgtMuvQ/gHAD7Q23sCl0/cU4iEbVdXHNIRFSfTNd5AD63uozOJjRddMtbsdHubcHpou0iDJ7u9PWGALBu5M+WlMb1nX78a9Ofu9tb/topi+ku7f7jtZFGzNia17boB88IiMf16rVuSddu28bWtvPoBoze9BR+gkqJGXG2WqXMu9fYVXZYK/QMkdDuqg1lwO+brm3e/i19YdFkbWtyFNyDjm+c01w3/LcKi7IDKKhSSIwSdeWMqEO7YHhybIYWcWmyefjjgj4ly0s10QViF6Ren4qo/lEAAKUUsh/KRvfbu8OINuA+6sbhfx2GCiikz01HVL+ocJTYouw+VZVcivzUIlWcXoTKroXKn1KsIAofXvXl9kea07aI9EZwhA8IBu/XlFIPiMjVAP6MUzekGauUKhCRsQAeqnHQfc324gC8CqAHgruT3qaU2iQi/QG8A8DEyQ1pThxlISIVSqm6F4MSUatgOCQiqk+mawCAutbgUBjVMl3Ukt1FwyWuQuU/84/AGQfJbx1086JjKeNm1rzmLn58F+A/sVNopOE6ekm3H8WIyCmjN2cLiJGRJftHjPy0yjB8Q2qrZxmmrnsOt0V6JOLsG/WYyqcfrlxn7CvX4TFHC87sqz5dUFp4tf7Nziv1pWqAHOqri2r0mrLvfVCN/+3yIzlKsOXHZ+aGD3b48NuFHkCgqiGe8y6P31U5Oq5kU24gZefzOf2UqbSuN3dFZN9IqIBC9sPZ6PnTntAcLb0UsNX8MGtu1r+tLoKIOg6GQyKi+mS6IgFU1nsfNVpouujO12Ojc5dGRqRUBaeLdpi1RxevNlfc/JU56fTre3tdtvRAzwtO2aTDV/XV4oBn04ya14bHz1g6KG7iGZt5bNEPrlhp7B5fW0AEzMCAgcuWJiVlTxU5cwqmAvAVLlj5Cm5O8om9z5nPn6ban2PbXbZLy63OEIVGrzE8brjs3X2D/vXR8/R1MQkoGyJS/5ERSw74EW0X3PReda3hsMKrEGUDRASbjwVw3dvV2HFnNO75zI0rBxlKdbEdvfMjd8TMn3bNWvBFWYbHZXPFn5MQ19T30AZdmDU36zOriyCijoNrDomI6pNZWoVMVyGABKtL6QjcItWfhnYXDU0XHYjgVvYdzuTtpr+260534RnByHBOGBzwbPKjxr/Nm4sXT+0VM3yDU48cVfPeoYEekwDUERA1feeOaTNzjvbfPmz4l3ZNM08JgALgXHw2cRY+Nz9SVy77L67vHhCjR51vIsJI8w3vkoZhSmn57o3G7rJKqfCPFqBRo7qbVZ9+m/19+v3K/0M44am+QFu79np9YeUYbXc3h/hqDanTexrILql7XWC0/eTPESq9Csd/rGDTgGofJMPj7zrYFsD9B/Nn7NhchU+/E4niA9UFa4PHa5RvdDiMw4aR6hVkQKTRo6NtAHdSJqKw4sghEVFDZLo2ABhpdRnt1fHpov+LjnLkdoDpog31yl/9++yBM4+MKIwfuGXTiLuGnn7dXfLMGqiKcTWvxRjxBy/q9sNEETljLWFoBHEcahkhBADR/O6hQ79e5XIdm17X+j8/dN/buGHlx7isryl6Wm33nMFnlhr7yjfphyqTJKCafZZkN8k/eq2+aO9l2nKjpxwbpMnJDViyS0xc8lpVrSOHAPDedh9+9ZUHeZUmFnw7EpO6GzhYauKm96rhCQD/usSJlzb6cOkAAzMzav+ZuFukerPDvn9FhLNwjdOp9tptXSpEeiG4QUtbpQBEZc3Nqm7KwyISAJCF4LmXfgD/AfD30NESjW3rbgDPKKWqmlJLLe3dDOBzpVSzN9whosZhOCQiaohM1wcALrO6jPZkvcO+/bXYmGMdcbpoQ9S13hAAKiNSDqya8Lszpmj63etX+KsXnTENdXTCeYv7xY6ecfp1oP6ACAAJiQfWDxq0NFVEpdd1jxc29yu4ZdXXOG+oEq3Bo+RS4t1p21WaK8XeEWfZVbPBNJiBSdq27TfoXxdO0zZ3KSypGHzZ61V6XeHwuCUH/Lh/sQdf3nRqnttTZOK+r914/EIn7v3CA29A4Y/nONA/4ewDhSZg7rXZDqyMcOasiHD6ttvt0YW61kOJ1Prf1AJHsuZmdWvqwzU3gAmdb/gagGVKqd83oa1shDaracQzulIqUMdriwDcq5Ra29haiKh5GA6JiBoi0/UEgDusLqMt8wjcn0ZFZb0ZE1291WHvZ4o0bBSqg7p4tbn85q/MybW95tcdFUumPXJG2lHK7/GUPO4GcPr5fuaVPX661a47az1qoiEBUde9pSNGfrolKqp0Sl33AEA1nBXP4bZ1KzB1ZKPOGQwoj36oYp2xv8IJrzlKwnRunbNkb3nem78zFt7Va+0Qye5liFlnIOr9WDlW/zAKiZEnN5y5/p0q/OkcB17c6MP5fQxkxGn49dduvHrVGQOxDZKn6/lrnI4DyyOclZucDvtRw0j1AT0h0tq73CzKmpt1TlMfPn130NCupWsQ3KXWAeApAGMRHFW8Rym1UIJTbx8EcCGCu44+i+B/54cA7ARQoJQ6R0RuAPDr0GsLlFL/d7xPAP8CcC6C/z+dBeBSBKcoLwfwIwBXA3gRwBGc3Cl1MIBHEDyPswDAzUqpnKa+dyKqG9ccEhE1DM86rMUxXT/2Zmz0ro+C00WHQmRc/U91DlO2m7WOigCAEfBEQ6nq06fXihgO0VNXq0Du6ZvQaF/nvBZ1QddbPCJyxnrFoYEekwSyYoWxq86AGAjYXevXXTYlLW3nyj59V/cXQZfa7ouAO/pOPDrjZvy75Cl116KNGDMetUxpPYMujkBGzORARgyk0n/Y2F26R8tz9xeFOkcrG6JComMqDBcu9/5pGgAMkIP7v6UvPHiRvjqytLBgaP8ELUJEsD4nAE8ASIg4mUkXZ/uRHq2hX4KOKp8PmgCaAFVnnDzZcMmBQNKcyqqkOZUnZ1BWilRscjqyl0c4i9Y5HbLfZkuoDE5Lbcnp0zvD2ZhSal8o/CUD+E7wkhomwTXBn4eOorgFQAaAkUopv4h0UUoVicg9AM4JHXORjmCAHAOgOPTsFUqp9wFEAVillPo5AIjINqXU/aHPXwZwiVLqHRG5E6GRQxGxAfgHgMuVUvkicj2ABwB8L5zvn4iCGA6JiBpmn9UFtBUbHfYdr8bG5C6JjEiuEhkEkUYfUdAZZBzDWaf8iTKLlOhdT79uREyO81W8e8b9pb783tkVWxb3ihlW6/TSIYHukwCcNSACQE7OgImFhd3zRo76eI3DUV1nmI9GRdwv8JeZxYjPe0L9bM0ODJ4EEfvZ3tNxKsro5huZ0A1KmVpu9VpjT5lPqgJjBGjQ8wUfP4rqvWug/D5oNgcC1WU4/ORcuKbeiLWmv9daJPX6VcKPUPDhX5WqLlOGptSgRM379Bync9oLVShxK/zxHDv+udaHN6+JxOVvVOGeiXb89FM3/Cbw1BxnQ8posCiloidXu4dOrnafuBYAAjvttr0rI5zHVjmdvh0Oe0yxpvVUIuHa2Kolj9eZimAgg1Jqh4gcANAfwRG/p5VS/tBrRbU8Ow7AIqVUPgCIyKsApgN4H0AAwH9r3HuOiPwSQCSALgC2AvjotPYGABgK4IvQzHQdAEcNiVoIwyERUcOst7oAq9SYLure6rD37ci7i4ZLfLnKswXQ62z3aKavNKCdGQ51W8YwH7QDgHnGmsQ1BZ9M6RY1YLtNs9e6CUxDA6LXG5m8etU1yRkZ65d26751tAjq3HglHsXJv8XvkvOQfOQxde++bPSe3OCdPUU0My1yrDctEvAECo295Vv0I5XpYqLf2R6LHnYuYkZfgsIFjyD9+/8843XTXYHcV36B1JseESM2GYHKEimJinPesfqV8tGDDuT8Y2Rh4V2v7x37zfeibB/t9GFUqoYZGQbW/6j1zljXAX2w19dnsNfX53ul5SeuH9X13NURzkMrIpyVmx12Z65hpPuB7k1YkxvWcBiaVhoAkBfOdk/jPr7OUEScAP6J4FrFQyKSCaC21C4AtiqlzliLS0Thx3BIRNQQmaX7OtNxFnm6nvdmTPTOj2KiHDmcLtpok7erPQhOz6uT4a+uDBi1j2Bptn7Zpm/nGeFQQRmLct/Qzk37ri803e4MDQ2IAJCdPXrasWN9Dowc9ck+w/DVup7xuGTkdX0Av+x6CN33P6Z+kZOD9EmNCjQOPcE/OG6Gf3ActELPVmN3aZGU+kYKEHP6rc7uQ+EvPVZnU5XbFiOi/2QYscHfYj0qLnjd1iVmqSTGXOaZigL5M66q+s72zYsfSP36pohDSlUNEkGtv2etKT0QSL2iojL1ioqTR6eWi5RtCE5LLV7ndOoHbEZitUjvekZqN4erJglusvM0gCeUUkpElgK4EcDXoemkPRCcxvoFgB+JyMKa00oBlCP437EAwGoAj4tIIoLTSm9AaBTyNMf/8BeISDSAawC8E7p2vD2E+k0SkUlKqRWhP/f9lVJbw/X+iegkhkMiooZbC+ACq4toKbVMFz1ruKG6Td5W93rD42y+Co/HGV/ra0bE5D5e306FWjZ1KfLkDDhctWtx96gBtU4vBRoXEKurXT1XLL8u0H/AikXJyfum1BeguuNQr4fwk1570XfXY+rekkJJGn+2+2tjJjiGeBOSgYBZpWdXfGMcqIgRnxrR0Od9RUegzAByX5sH5a1GzNjLED10NqIGz0DBh39DxaZPETfjZixav2eQNuoWTMe58VGe6oqL9VUbrtMXuUfI3p52CZwRvq0So1Ts9Gr38Ok1pqX6AN8Ou33X8ghn/uoIp3+X3eYq1bQMJRIHoCBrblZzj3mIEJGNOHmUxcsIbvoCBEf0nhKRrNBrNyulPCLybwSnl24WER+CG9I8AeAZAJ+KyNHQhjTzACzEyQ1pPji9c6VUiYg8C2ALgFwEN8M57kUAT4vI8Q1prkEwcLoQ/N71UQSnoBJRmHG3UiKihsp0/RHAb6wuI1w8AvdnUZFZb8bEVG/h7qJh9epf/fvrm1a6adjtiwsThtYZ8Nwl/9wE5a41MGnQvFf2vPuAodnOOj1zq36oQQHxuJiY/J3Dhn+h63qgb0PuB4CtGLr1CdzjLRPXqIY+Uxsp9+03dpUe0Ao8gwVI9pceQ947f6h1WmnRF0/Bk7MHKd96AMrvQe4r9yL5mkzYupycpRtwV6Dg/flIuuo+FH/1LEx3BWLHXwlH1+CM3AzJOfQtfeH+OdpKRzcpGCSC2ObU31oOGcbhdU7H51fce/T7VtdCRB0PRw6JiBqu3Z+5xemiLa9LmTpWXzAEAKe7tr08TtIdI8sC7pW1vmbCtC859rbvnNQbAnKW9X+NGUEEgPLypAErll/vGTJ04eK4uJxpIqj3eIYh2DLkKXwPa9SEDf/CHbZqiRpa3zO1UTG2Xr4xib1gKr9+tGq1WnXUDmBkbffqMYmIcMZCszsBuxOObkPhzdt/SjgsXfY6XJOvQ+W2xXB0G4LIAVOQ/94DSLn+jwCAbJXWfb7/293n49vQEfBP1zZv/pa+sGiKtiU5Cu6BDXnvVuju93frXuE/+x8eIqImYjgkImq4NfXf0vZscth3vhobk7MkMiK5ktNFW9zk7WovgHp3cHW6C886fdNwjhkZcK+sRvAMuDPkuw8Nzq3evzgtsnedo49A4wOiUrpjS9a5M7p0ObRx0ODFiZqmGnTQ+jisGjUOq7BYnbP6RfzA5RXngIY8dwZNjEC3qPEBoyvMD7SAPz1yqZ5T1VPUycAd2Xciir58CsoMQAV88ObsROy4y0804Ss6gkB5IZw9hsObtx9i2AEBlN9ba5cB6MZCc9TwhWZw8DMeZUVX6d/suEpfag6Ug311UalNei8tp9NukEVELYvTSomIGiPTdQRo3rltLa3GdFH3Voe9TyB47hi1kj+/6F/aNwenn1N4hmNJo9dvHfL90We7x1P64nJlFk2u63VNdPdVPe/O0cWod6Rym3545XJj59iGTjEFAF33lg0f8fnm6OjiqQ19BgAUoD7FnJVv4LupfrHVW9vpSv44D75N62CWlkCL74Lom2+Dyik6rOVVuF2jr0kXILJ01X9RmfUlIILo4RecEg7z35+PuOnfha1LVwQqS5D/7p9geqrgmnYjogZMaWw5GCb7dt+gf330PH1dTCJKB4vUuqtma+qPzNLdFtdARB0QwyERUWNkut4HcHl9t7W2PF3PeysmeueH0VH2HEMfCpE6jyaglvXqX/3ZtgAy6ruvNCZj17oxv+h/tnsC3h1rfZUfjz3bPakRvTdPT7lmmDRg59CmBEQASE3dtapvv1V9RJDYmOdMaIH3cPWK93Fthil6g0Yg6+Uzy4z95Zv0g5VdJKCGhKXNRnDCU32etm7rt/SFlWO0Xd2c4uvTyiUUILM0qZX7JKJOguGQiKgxMl2/AfBHq8sATkwXzV0SGZFYKTK4CeekUZgllKncp54MNGgKosfuyls2+c9nneKrlBnwlDyWD5x9WuOstG8vSXJ2n96QfpsaEG226vyRoz7Z73RWNnp3Uj8M7+v4zorPMGeQEq3W91z610x4Vi6BFtcFic+/c8brZkU5Sv/8G5h5OVCBAKKuuwmRky/abS5cV1z8xt/GQCk94YI74Og6CMoMIO+t3yHp6t9Cs7XsIF9X5Odcayzec5m23MiQ3IGaoPYtaMPnf8gsvbSpD4vI8wAuAZCnlBoauvY3AJcC8ALYC+CW0G6iIwGkK6U+Dt2XCaBCKfVQ894CEbVVbXKxNRFRG2bZukMv4PlfVOTa76SlLBmZ0f3od9JTB3wSHTWjUtOGMBi2DZO3qX0NvdfuLUtAPT+hFdF0zehZ72Hni3PfHmOqwOGG9Ds40G3iZP+AtVDwN7RWAPD5IpLWrL5q/MEDw5YqhfL6nzjJgN/+Xbw44zl8J3q6+noxlCo+/Z6ICy5F/Pwn62yj+oO3YGT0RsK/30KXvz+L8qcfgRkp/SqOLhsfPe8+M/7e+etKlr9erACzfMPHiBpyTosHQwA4gqS0R/3XTJvlfWRSH88rrhu89239MDBpUamK3KwU6j3SpAmWNfP5FwFceNq1LwAMVUoNB7ALwK9C10cCuLiZ/RFRO8JwSETUOK26Y2m+ruU/EedaekG39NVjMrr7f5WcOHaT0zGd6wjbpkk76j/f8DiB0hE8JPysjIgp9U7HDChf1Iq8j/Ia2ndTAyIAHDgwctratZeX+Hz2TY191gFP5I/w5IxncJM2Tq1YBKVOhEz7iDHQYl11PyyAqqqEUgqquhpajAvQdcCwQfm8tkCqc4zqmRjvHunMrdy9pDhy6KwGheVwUtC0FeaQIT/x3TVzhOffw4d7nq34je+WlRvNPkv9SgtXPUubVaNSSwAUnXbtc6XU8T8LKwF0ExE7gPsBXC8iG0Xk+tDrg0VkkYjsE5GfNKcWImp7OK2UiKixMl17AfRuqeY3h3YXXRwZkcTpou3Lqw/6D9hMNPhw9UXTH91rarZ616y5i/+xHfANqu++89LnftPFkdrgzWNCU0zHoJ6D72unzH79Vi5JSd0zWQT2xj8PlCG28EncvWULhk+AiDOQexTFv/5J7dNKqypR8pu7ETiYDVVVCdfvHoRj4jQEjuWgdP5vAZ8XMT/7DdyffwTHpBmwjxijtGPuDcbuMrdU+ccI4GhKjeHUXw7t/5a+8OBF+urIVBQNFkFj1wa7AbiQWVr7tqsNJCIZAP53fFrpaa99BOBNpdQrInIzgLFKqTtDr2UCOB/AOQBiAOwEkKqU8jWnHiJqO3iUBRFR4y1DGMOhF/B8HhWZ9UZsTNWW4O6iAwA07RgAskxCqcppTDAEAN3vKTft9ecy3TEkP+DZWG84XJT7xrArevwkRxMtrSH9Dw50mwigiQFRtN27J83Myem3e/iIz5WuB866uU5tYlGW8CvcP6MQCbmPq5/v3mlGTQRqr8O7ZjlsfQYg/uFnEDh6CMW/uB0Jw0ZBT0lDl7//GwDgP3IQgfw86D16ofQvvxXl942OvuXHMFK6FRt7y1fqh6tSxVSW/d3apbr3ut9/U6/7/TfBBr/3HG3Dhm/pC0snatvTIuDpL4L6fhC0qrnB8GxE5D4AfgCvnuW2BUopDwCPiOQheGxLq4/SElHLYDgkImq8TwF8tzkN5Ota/lsxMTs+jI6yHw3uLnrWHSmp7ZuyXe0H0KBQdpzhr6z22aPrv885YXDAs9GPev7d9pke15qCT3ZOSJrT4DqaFxCBiorEfiuWX+8dPHjxovguR6Y35fD4BBSm/gG/Tt1oxh29z1MZB6WcEDmlnepPP0TUDbdARGB07QE9tSsCB7OhDTo5+FXx3JOI/t6PUf3e64iYcwX0lHRUPPcEXPf9Od4/KG6Gf1AcpNiz3bazLF9KvSMEOMs81pblg2H/3Bw36nNzHAAgGcX5V+tLdl2hL0M/OdJfE1XbjqRftlQ9oVHCSwDMVmefVuap8XkA/F6SqEPhX2giosb7DICJRq7b3uyw73otNuboopPTRes9C4/aj0nbG77e8Di7t9xXHZlS732iRSVCYlZDlde7U2h2xZbxA10TlrvsiXWej3i65gZEpXT71q2zZsbHH9k8eMjCeE1T3RvbBgCk6vnpaY5C/Bb37n1U/SI/DykTjk+r1pNT4V2/GvbhoxEoKkTgUDb09K4nnvVuWgs9IQlGt55QbjcgGqBpwc9r1hrvGOSdmDQIAVWtH6xYZuyviITPHCmod9SuReUhPumpwOVJTwUuB6DUaNm94wb962Oz9A2xXVA+JDR194uW6FtELgTwSwAzlFJVNV4qR3D6KBF1ElxzSETUFJmuVQDO+o26F/B8EZoumhWcLtr1bPdT+/bag/4DRiOnlW4ddPPiYynjZjTkXr9740p/9dcTG3KvXYsouqLHnQERrVHn4W3XD69c1uQ1iEG67qsYNvzzDTExRY364ccDfzqGTZvcKC0NID5ex9y58dhXkZj7jTnNo93w456BgjyUPfh7mEUFUEoh6oZbEHHeHACAUgolv7wdrt8+CC3WBf+BfSh94D7ADCDm7l/DPnTkWfuWCt8BY3fZfi3PPUAaOfrbGqJQXXGZvnz1X2zPnY/M0mbtgCoirwOYCSARwDEAv0dwd1IHgMLQbSuVUreJSBcEfxhmA/AXAINQ4ygLEdkC4BKlVHZzaiKitoPhkIioKTJdmQh+U3WKAl3LfzsmeucH0dHGkeB00frnDFK7l1iqcv75z0CjQ8XeXpctPdDzggaFKKX8Hk/J49UA4hpyf7/Y0StHJ5zXoDBZUzgCIgCkpOxZ3a//il4iaPaB7RsxavNT+KmqkJgRzW3rrJQKaDnV6409ZQGpDoyROtY/WuSt7Plzrq//NiKipuO0UiKipvkEoXCYZbfvetUVc3RxZERShcggiDR4t0jqGKZsa/x6QwBwugsbvIOmiOEQPW21CuQ0KEzuLls/sX/suJXRtrhGBcRBoSmmzQ2Ix471HV9U1K1w5MhPVjojKk7UkJfnx4Pz81BcHIAIMGdOLK66+tSlf0opPPlkIVavqoLDoeGXv/QM/1f/DXh3z6Atz/55W1+lGc6Yn90H+5ARUAE/Sv7vDsT96VGIM6Kp5QaJ6GZ65DhveiTgCeQbe8q26UeruomJeneUbQUfW10AEXV8POeQiKhp1tyWkvTxyIzuh7/dNbX/guiomRXBw+j5/9VOaOIO02zKc053YWRj7jciJsc35v6vcl7trWo5cL4+gwLdJk71D1wPhWYdUeDzORPWrLlyYnb2iGVKoQwIHk14220JeP6F7vjHE13xwQdlOJB96gacq1dX48hhH176T3f87J5EPPZYAQDg2GffDP3r3R7nD/4wdn31y89UAkD1B2/Dee6c5gfD0zn0JP+Q+Bme87r28Y5JyDJjbUsVUBHeThpMIbgRFhFRi+I3MURETZFZai6LjMgLiNR7QDl1fD3z0KQNWJye4tjG3K/beg4FtP0Nvd8dqEjOKl6yrfGVAQMDXSeEIyACwKGDw6esXXNFmc/n2JiQYKBf/+CAaWSkhh49bSgo8J9y//JllTjv/BiICAYPdqKiwkRhoR+GAXg8JiYGlo6eELkp8rLif63yLPnS7Tz/kuaWeFZmonOYd1LyNM/sNPj7xCxVhmS1aIdnWp09f86xVu6TiDohhkMioqZ73+oCyHpJJepoYzeiOc7hKWnUSCAAaPb+Bxtz//bSlVOq/OVrGtsPEN6A6HbHdFu54toROUf7L1YKbgDIzfVhzx4PBg5ynnJvQUEASUknV74kJekoKAjgsstdeO21Ejz4YD5u/HacFL/++oQ/zc21XS7vLdVUIKe5NdbL0KL9fWOneWanD/NMStobSHAsVkB+i/cLvNsKfRARMRwSETXDFwCqrS6CrBVab9gkRsATA6Ua9WfIcE7ug+A0wwb7KueVbkqpskYVFxLOgAiI7NkzYcaGDRcfLiuTnX/IPIYf/zgRUVEN+3YkJcXAI4+k4x9PdIXDqSG/wI9ePQx9/18endbnDzOTR+9+frUos6D5ddZPxdr7+MYmzvCclx7nGxy3Ujm0NSp47l9LYDgkolbBcEhE1ERZc7OqAHxudR1krYk7zGZt+y3KLGrM/Zoe1w0Ssakxz1T5y9K2l65s1DM1hTcgAmWlcX3v/bnqP3Royp6pU6POCFSJiTry809ONc3PDyAxUT/lnuefL8Itt3TBe++V4aKLY3D7bfG6560Xxj+L7zqnqCWLoFRpOGqtlya2QPeoiZ6ZaeM801PyAmkRi5TgQBh72Jw9f86eMLZHRFQnhkMiouZ5y+oCyFo98tGjOc9rpq/RIcZwjGz0xihZxUumugNVGxr73HHhCohKKXz44YdISkqS4cO/13dL1uxtpqmdEqYmTY7CF5+XQymFbdvciIrSkJBwcprppk3VSEjQ0a2bDW6PCU0AEYHHbSIC7ugf47GZ/8LNapRaswhKVTan3kaJMNJ8w7vM9JyX3sM7qstGM9pYppo/u+DN5pYlIj8VkS0islVE7g5du1lE0mvcky0iic3ti4jaNx5lQUTUPO8BKAPQqI1FqGMIrTdsVjg0/NWVAcNZ/4016M4xI/3uFVUAGrPbqXx99JWEi7r9sFJEohrVYcjAQNcJAFZ9Y+wY3dRjLg4dOoTNmzcjOTkZTz/9NAAMmz17ultkxe7EJHe/Sy+NxYQJEVi9qgo3ffcQHE7BL36RfOJ5pRRefaUEv/lt8NqcObH4y5/zEAgAP737ZLaJRkXcvZg/sxhx+U+qn63djiETIdLgo0OaRUTM5IiR3uQIwGeWGvvK1+iHKpMkoAY1obVmhUMRGQrghwDGA/AC+FRE/gfgZgBbABxtTvtE1LGIUs2aDUNE1OkNe2nYswB+YHUd1PquXG4uu2GxOaU5baweM++bipjujT4b01P60jJlFja679Fdzl3SzzVmemOfq2mHfqRZAbEuScn71g4YsLy7iEoJZ7sAkI+ko4/h3r370WcSRCz54biUeHfadpXmSrF3uAAN2YxoXfb8OWOb1afItQAuVEp9P/T1bwF4APwOwBEERzYnAdgO4CUAlwKwAbhWKbWjOX0TUfvDaaVERM33ktUFkDWau94QABze0iZtYmJETGzSwX7ri76c6g24m3UUw8BA1wnT/IM2hGsN4nH5eb3Hrlxxja26OmZFONsFgCTkp/8J/zftQdx9OF0dXg4Lfjqu4uwDvOOTZnjOTY/0DYhdruzaenX2zYVeCUO3WwBME5EEEYkEcDGA7gDWArhRKTVSndwUqUApNRrAUwDuDUPfRNTOMBwSETVT1tysbwDstboOan3d85t2hEVNDnejz6gHAGi2/iMBacrxDdrXOa9GK6XcTeo4ZEAgfXxLBES/39ll7ZorJu3fN2qZUgj7pjLdcDjjb/jp5Pvxf3sSVP7qcLffILo4Ahkxkz3npI32Tk05EkhxLlJyxvROH4BXm9uVUmo7gAcR3DzrUwAbUfeuqsd3RV0HIKO5fRNR+8M1h0RE4fESgPutLoJaT3KJOmKY6N7cdiLchU2amikimmZk7DT9+9Ma+2ypr6BXdsWWxb1ihs1oSt/HDQikjweweqmxfSQEdgAoLS3F+++/j4qKCogIRo8ejYkTJ57yXHV1NT788EMUFRXBMAxcfvnlSE5ORmVlJd5880243W7MmjVryogRV+aMHPXJ3j/+MXv0T3+aiMTE8H3b0gd7+z2O27BVDd36BH7mKZO40WFrvBFUlNHNNzKhG5QytdzqtcaeMp9UBcYIsCB7/pywnKGolHoOwHMAICJ/BnAYwMhabvWEfg2A3yMSdUocOSQiCo//oJFnz1H7NnWryg5HO053YZM3STEipjQ5nK4p+GSqz/Rua+rzx4VGEDdCwQsAmqbh/PPPxx133IHvf//7WLNmDfLzT804S5cuRUpKCm6//XZceeWV+PTTTwEAW7ZswdixY/HDH/4QK1euhMcTnfafl4aNio5KOpCQYLTImaJDsGXIU/j+6HvU/I2RqrJZ022bRUQz0yLHeqelTvLMTC339Y35V/ialuTQrz0AXAXgNQDlAGLC1QcRdQwMh0REYZA1N+sAgEVW10GtJxzrDQHA6S5q8jfompHcB7A1KeApKH1RzhuGUqrZ00JrBsSYmBikpQUHMx0OB5KSklBWVnbK/QUFBejVqxcAIDExESUlJaioqICmafD5fPD7/dA0DaZpYtWq1TJu3I09N6y/JMfvN5odZusyBmtGPoubht2mHl/jUO6dLdVPgzh0d6BP7JdhbPG/IrINwEcA7lBKlQB4EcDTIrJRRJq0fpWIOh6GQyKi8OHGNJ1It4LwrMlyeIrjmvO87hha0NRni7w5/Q9X7VzenP6PO30EEQBKSkqQk5ODbt26nXJvSkoKtm/fDgA4cuQISkpKUFZWhmHDhmHnzp14+eWXMXXqVKxZswbDhw+HzWZDZWV87xXLr++fn99jkVLwh6Pm2kzD4nHP4cb+N6nnVhjKu6+l+qnH87nnjGzSRkW1UUpNU0oNVkqNUEp9Fbr2X6XUgOMb0iilMpRSBaHX1iqlZoarfyJqPxgOiYjC520ARVYXQS0vpVgdNkx0q//O+tl95V2as3Om4ZwwBGj6pjAr8j6a7Dd9u5v6fE01A6LX68Vbb72FCy+8EA7HqTNnp06dCo/Hg6effhqrV69GWloaNE2D0+nEt7/9bdx6661IS0vDrl27MHjwYHz44Yd46623cOjQEWPH9hkzszaft9M0tf3hqLk2AsgF+HjSC7ix59XqjW805T/cUn3VwkRofSARUWtjOCQiCpOsuVlVAMK2TojarinbwrPeEAA0ZRoAmrZlKQDRIhOgxW5o6vMKpm3Jsbd8SqmwjFQNCKSPn+juu+nNN99Uw4YNw6BBZ5777nA4cPnll+O2227DFVdcgcrKSsTHn3rs35IlSzBt2jRkZWWhR48euOKKK7B48WIAQGlp6pAVy69PLS1NXqxUy6311WDqV+HtqS/gxuSL1IdLRJnHWqqvGj7OPWfkgVboh4joDAyHRETh9Q/g5LQ66pgm7jAlnO1pyt/kcAgAhnNcswJSvvvw4NzqfUub08ZxSin8e8Er4/pFdz82aeKkWv8uuN1uBALBLLp+/Xr07NnzlNHFwsJClJWVISMjAz6fDyICEYHPd3KA1DSNiM2bLpixY/u09Uo16UiPBjPgt38HL01/DjfGzlRfLhJltuQMgb+3YNtERGclFpwBS0TUoQ17adhLAG6yug5qOa8/6D+im+garvaWTnlwk88WPaKpzysV8HpKHqsEEF/vzXXQRHdf1fPuHF2MXk1tAwBWH96Mq1+9EwOTeqMiUF3ls5kRs2fPltLS4JGFY8eOxaFDh/D+++9DRJCUlITLLrsMEREn90R5++23MWvWLCQkJKCyshJvvPEGPB4PZs6cicGDB5/Rp2F4SkaM/HRbZGTZ5ObU3lBViCx7FrevX41JYyASzh0/N+WeM3JkGNsjImoUhkMiojAb9tKw4QA2WV1Hazn83GGUbyyHEWug3wP9Tlwv/KIQhV8VQjRBzIgYpF6fWuvzylTYm7kXtngbev4seKb8oacPwX3YjZiRMUi9Jvhc3od5cHZ1InZMbMu/qbNIKVZH/vF0IGzBEABWjP/9iurI5EnNacNT9sYSFTg6vTltpEb02jw95dqhIhK2mUW79KOrl9Q4B7ElpXfdvrx377WDRRDX0n0BQBliiv6Jn2ZlYeR4hGfHz1tyzxn5YhjaISJqEk4rJSIKs6y5WZsBfGV1Ha0lfmo8Mn6eccq1iu0VKNtQhr5/7It+f+6HxIsS63y+8PNCONJPTil0H3JDs2vo96d+qN5fjUBVAL4SH6r3VlseDAFg6lYV9o1Q7N6yZk9FNiKmJDS3jdzq/cPz3Ye+aW47NfUPpI+fftoupi3l6JFBk1evusrt9USsbem+ACAW5V3m4U8z/oFby/qpHUvQvGNBchA8f5CIyDIMh0RELeNhqwtoLVEDoqBH6adcK/q6CElzkqDZgv/MGLFGrc/6inwo31SO+Ok1ZkPqgOk1oUwF5VeABuS9m4fkK5Nb7D00RrjXGwKA09OsJYcAAN3WfQigN/vohSXH3hljqsChZhdUQ2sGRK83KnXVqmvGHj40eIlSqGrp/gCgC4pSMnHf9Idx57EeKnsZmra5z6O554zkemUishTDIRFRy/gUQIsd2N3WeXO9qNxVib3378W+v+xD1b7av0fPeS0nON20RtxypjthxBjY+/u9iB0ZC+8xL5RSiMhoG+d0dytEz3C36XQXheXfY83ev9mhLqB8USvyPswPRz019Q+kj5/uG7ypNQIiAOzfP2b6+nWXHvP7bVtboz8ASEVut7/g51P+gp8fSFE5KxpxREkZgKeb07eIBEIH2m8RkbdFJLKRz78uIptF5GfNqCFbROqeJtDwdm4WkSea2w4RNR7DIRFRC8iam6UAPGJ1HVZRpkKgIoDev+2N1OtTceifh874PrlsYxmMWKPW0Jd2Yxr6/rEvEi9KRN67eUi5KgV5H+bh4JMHUbTIuqMkU4vUYT1M5xvW5HQXhWU9nuGc3A/Bc/Ka5XDVrtFFnpyw7F5aU38zbVxrBsSqqrheK5ZfNzAvL2OxUk0/C7KxeuBA70dw56Tf476d8apwTQMeeTr3nJFlzey2OnSg/VAEd0y+reaLIlL78H3wtVQA45RSw5VS3C2VqBNjOCQiajn/AdBiB3W3ZbZ4G2LHxkJEENk7EhAgUH7qTLuq3VUo21CGnT/ficNPHUbF9goc+tepA19l68vgzHDC9Jjw5nvR444eKFtbBtPT7PzTJFPDeL5hTU53YaNGeeqi6a50SERYNkNalPPGCFOZOW6/B5f851ac//wtmP3vm/Dw0ufPuPflDR/g3Ofm4oIXvoerXrkDuwqyAQBrDmfhvOdvxsUv/RD7i4L/bVOqose989zrbjNgesJRZ/00feeOaTM2bzp/j2lqe1unz6D+2DnwCdw67v/U/VnRqmxjHbdVAngozF0vBdBXRGaKyFIR+RDANhFxisgLIpIlIhtE5JzQ/Z8D6BoaeZxWsyERuTY0GrlJRJaEruki8lDo+mYRuavGI3eJyPpQHwND93cRkfdD964UkeFnu05E1mE4JCJqIVlzs3wAfm91HVaIHR2Lyu2VAABPrgcqoKDHnLouMfXaVAz8+0AMeHgAut3eDdGDotH9R91PvK78CoWfFyLp4iSY3pNh8MRaRAtM2NEyodTpKXKFqy3DMboyHO34lDd2TcEnhx26HW9+61F8/r0X8Oktz2PR/lVYf+TUmZpXDD4XX37/JXx2y/O4bcINuP/r4IzAZ9a8gf9c81dkzr4LL2/8AADw+PL/4PfT74idGRi6GQqtFBCBsrKUQcuXX9+1pCRlsVJo1T9Aw7Fp2L9wy8i71MPrnKrq9OnmT+SeMzJs03hDI4QXAcgKXRoN4KdKqf4A7gCglFLDANwA4CURcQK4DMDe0Mjj6SPGvwNwgVJqROg+ALgVQAaAkUqp4QBerXF/gVJqNICnANwbuvYHABtC9/4awR+cne06EVmE4ZCIqGW9CmCL1UW0pENPHcK+P+2DJ9eDHT/bgaLFRYibHgdvvhe779uNQ08dQrcfdAseYl7sQ/Yj2Q1qt/CrQsRNiYPm0ODs7oTyKuz+zW5EZEScsQFOa+lWgGadAVgXh6e0yecTnk53jhqF4GhUs2VXbBlX5itYFmUPDmz6TT/8ph8ip+7JE+OIOvF5lc8NCS0iNTQD1X4Pqn1u2DQD2cVHcLQ8D5N6jDo+xbRVA6IyDWfW5vNnbN82Y6NScrS1+j1uIpaPeQ7fHfx99dRqm/LsBlAO4G9haj5CRDYCWAvgIIDnQtdXK3Vih92pAF4BAKXUDgAHAPSvp91lAF4UkR8COP4X71wA/1JK+UNt1Zzr/W7o13UIBsjj/b4cuvdrAAkiEnuW60RkkTrnnxMRUfNlzc0yh7007DcA3re6lpbS/fbutV//0ZnXbfE2ZNyTccb16EHRiB4Ufcq1xAtO7mshInX201rSCtUhXaFFijAC7hgo5UZwFKdZROxRoid+owIFU8NR29c5rw2+tNuP8+f850dJ2cVHMHf0FRiVfuZB9C+ufxfPrnkLvoAPb37rUQDAnRO/g7v/9wCcNgcem3Mf/rjwn/jltB+ceKa/mTZOfFiz2LZtOASOMxptIYWFPUatWH5d6YiRny2LiiqZ0lr9HjcLX46fia/MxWrWL/8065nCMDVbrZQaWfNCKMQ36gcFIvIAgDkAEBpJvE1EJoSurRORMfU0cTzsB8DvM4naHY4cEhG1sKy5WR8AWGF1HdQ8U7eZB1qyfVFmuEICDOekqPrvahiv6Y7fVLxo72e3PI/VP34HG3N2YEf+mSdm3Dz6Kiz70Rv41czb8PiK4OzAISn98OFNT+OtGx7DgdKjSI5OgAJw+we/x08++iPyK4vQz0wbN6OVRxABIBCwu9avu3TKnt3jVyqFVt/lSIMqOgdfPdvK3S4FcCMAiEh/AD0A7Kx5g1LqvlAoHBm6r49SapVS6ncA8gF0B/AFgB8d3+RGRLo0ot+ZCE49LTvLdSKyCMMhEVHr+LXVBVDzTNipwn6+YU2a6SsNW1u2viOA8E2b3FO+fmK5r3ilyxmDyT1GYdG+VXXee/mg2fhs1zenXFNK4fHl/8FPJ8/F35e9gPtm3o4bRlyK59f9FwAsC4gAkJMzYOLqVVf7PZ6IhuwqGk5/nj1rb2sHoX8C0EQkC8CbAG5WStX3e/630OYyWwAsB7AJwL8RnLq6WUQ2Afh2PW1kAhgjIpsBzAcwt57rRGQRhkMiolaQNTdrEYI7AlI71bWF1hseZwSqw7JOEABERNNsvXaFo60KtwfVXh++znm1T5W3unhJ9lr0TTj1qMfjO5ECwFd7VyCjy6mnfbyz5VPM6j0R8RGxqPZ5oIlAE0G1z33inn5m2riZvsFZVgRErzcyefWqa8YdOjh0qVLhWa9Zj4MIBrWwUUpF13JtkVLqkhpfu5VStyilhimlRimlFoauZ4eOwKit3atC9w9VSv1UBfmVUvcopQYrpUYopZ4I3ZuhlCoIfb5WKTUz9HmRUuqK0FEZE5VSm+u5/qJS6s5w/v4QUcNwLjgRUev5NYDzcMqR79QepBeqg7pCj5bsw+at9HgcYduXBoZzSg+v78zpn41V5vbgjdWboJRK+pP5RdWNI67EuX0n46Glz2F46gCc328qXlz/Lr7JXgdDN+ByxuDvF58cKK/2ufH2lk/x6nUPAwB+OO463PT2L2HXbfjHpb87pa++ZtpY+LB2kW3bsNZcg3hcdvaoaceO9T4wctQn+wzDN6wFu/rt7Fl7Wz0EExHVR04/lJiIiFrOsJeGvYr6p2BRG3PdksA31yxTYdngpS6bht2+qDBh6MxwtukufmIr4B0SzjYv7X77mkgjdlw42zzdHi3HsoAYZAb6D1ixNDl53xQR2MLc+AoAU2bP2stvwIiozeG0UiKi1nUvAG640M6Mb+H1hgDgcBeHvQ/dMSxsm9wc99XRV7oppcK2PrI2fc20sVZNMQ3S9F07p8zctPHCfYGAvjuMDZsA7mIwJKK2iuGQiKgVZc3NygHwG6vroMbpWojeLd1HhLsw3CNUMJzjh/kCAe9jX36Dhz9bgr99uhifbal9KeLGQ0fx108X42+fLsarKzcAAPLKKvD3L5bi4c+WILugGABQ7itNO+/F76ia6wVbgvUBESgvTxqwYvn1PYqL0xYrBTMMTT43e9bedWFoh4ioRXDNIRFR6/sngJsBjLa4DmqArgUtv94QAJzuwmafcXg60SLibUbcqttmTJzgsBkImCae+HoFBqYloWfCyfWN+eWV+Hr7Xtw5azIi7TaUu4N5bOW+g7hi5BDER0Xggw3bkJE4Biv2HsDInvFxogXWo4X/DAfXIMraRbatlk0xVUp3bMk6d0aXLoc2Dhq8OFHTVLf6n6pVMbhrMRG1cRw5JCJqZVlzswIAbgPCMhJBLWzqVvNga/TjdBeF7WzCmoyICeKwBX8WHDAVTPPMP3ar9h3ElL49EWkPDl7GOIM5TBOBNxCALxCArgmqvT5sO5qHMRnd8NXRV5OUUi2+s2dfM3XsTN8QS0cQAaCoqPvIlSuud1VUxH9T/921mjd71t6CsBZFRBRmDIdERBbImpu1BsC/rK6D6jd+l2qVfysdnuLwbVVag24fMso0VeEjny9F5odfoF9K4imjhkBw5DC/vBJPfLUcj3+5DDty8gAAU/pm4Kvte/DG6k2YNagvvti2G7MG9YUmggp/cffdZetaZYpkWwmIgYAtZsP6S6bu3jVhlVJoTNBbAaC1D7wnImo0hkMiIuv8GsAxq4ugs0svbNnzDY+z+8q7oAW2EBfRbbq929Z7zp+G314yG4eKSpBTWn7KPaZSKKioxO3nTMSNE0fh7bVZqPb6EB8VgR+fMwl3zZ4Cu66jtNqNlNhovLZqI15esR6fH/hgmjdQvTncNdcmFBC3WB0QASA3t/+EVSuvUW531OoG3O4HcBs3oSGi9oDhkIjIIllzs0oA/MLqOqhu3QrUAV0hrTX60pRpAChpibZtzimJABBht6FPciJ2hkYGj3NFODE4PQW6piEhOhJJMVHIrzh1xugnW3biwqED8M3u/ZjQqzvmDB+Iz7fulq9yXotRSrXs7jQhfc3UMW0lIPp8EUlrVl81/sCB4UuVQvlZbn1k9qy9zQrQIjJARDbW+CgTkbtF5GYRSa9xX7aIJDagvdkisj7U1jci0jd0/QoRGVzjvkUiMrY5tRNR+8JwSERkoay5WS8D+NLqOqh2rbXe8DhN+YvC3WZ5dQncZtxgQN/r8wew+1g+kmOjT7lnaNcU7M0LnnpR6fEiv7wSCVGRJ17fm1eIWKcTSTFR8PpNiAg0EfgCAZT5Cnrtr8haFe6669LXTB1zTnCKaasE0vocPDBi2tq1l5f4fPZNtby8DcDvmtuHUmqnUmqkUmokgDEAqgC8h+DGVulnebQuTwG4MdTeazi5g/IVAAbX8QwRdQLcrZSIyHq3ANgMoEXWnFHTjd+p9NbsTw94KkzNBtMM4K/v/hiuqATcftGfT7nnq81vY8X2j6FpOqKdcfjOzF+gS0wKjpUcwotfPYCA6ce3pv0MvVOHIGAG8PSn98Hv98LjLUrVNT9GdE/H4PQUfLplJ7rHx2FI1xQMSE3CrmMF+Ouni6GJ4JIRgxDlsAMAlFL4cvsefHfiKADAxD7d8drKjTCVwlVjhgIA1hZ8OrV71MBtNs3eKsGij5k6Fj6sXWjbOhSCsO/y2lju6tjuK1dc17Vfv5WLUlL3TJLgzqp+AHNnz9ob7lHO2QD2AhgHYCyAV0WkGsCk0Ot3icilAGwArlVK7ailDQUgNvS5C8BREZkM4DIAM0TkNwCuDr1+rYj8E0AcgO8rpZaG+f0QURsiLbC8gYiIGmnYS8OuBfCW1XXQqV6f789prWmlALBi/O9XVEcmT/pq89s4mL8Lbm/lGeFw15ENyEgeBLvNiaVbP8Tuo5vwvfN+i/8u/ydG9pqGLjGpeGf5k/jh+ZlYtOU9OG0RmDjgQiizLMdT+u8UtNCsoXh7yu7z0uf2FBF7S7Rfm71abpsJiMdFRxfsHj7ic6Xrgbdmz9r723C3LyLPA1ivlHpCRBYBuFcptTb0WjaAh5VS/xCRHwMYrZT6QS1tTAPwPoBqAGUAJiqlykTkRQD/U0q9E7pvEYB1Sqmfi8jFAO5RSp0b7vdERG0Hp5USEbUBWXOz3gbwH6vroJO65avsmsHw3L17cPn+/bgyez+uzc4+4/6vystxRY3X11VVAQD2ez24Jns/rti/HxurqwEAfqXwvUMHUX3asRJ2b5mvuCIfWw+swuSBF9daV/+uo2C3BbNQRsoglFTmAwB0zYDX74HX74au6ajyVGDLgRUY3/98AIBosWmQyI3N+12pW7H3WL9DlTuWt1T7teljpo49J7gGsU1MMQWAiorEfiuWX18M4P5wtx0K3pcBePsst70b+nUdgIw67vkZgIuVUt0AvADgkWa2R0QdBKeVEhG1HXcCmAa0zu6YdHbTtpqHcNo3wy927454o/Z/OidGRWFWdDREBDvdbtyTcxQLevXGWyUl+FVyCrrabPhL3jE81rUb3igpxqWxsYjQTv0ZrcNTYv539Su4YuKtcPuq6q1xxY5PMLjHeADA9CGX4z8LH4Q/4MUN03+GT9e/jPNHfRuanOzDcI6u9lc39Zi++q3M/9+U9Mi+uw3N1q/FOjlNcIqprFto2zKkjYwgVimlz509a6+vBdq+CMFRw7Ptcnx8GmsAoe/zROQzACkA1gL4FYARSqnj60TfBPBpY9ojoo6LI4dERG1E1tyscgDfQfCbMLLYuF2NW28YpWkQEQBAtVKQ0HVDBG6l4FYKhgjKAgEsqqjA5bGuM9pYuW9JUkxEPHok9a+3v9W7vsDB/F2YPeI6AECXmBTcfdkjuPfKJ2A3nCipKEBqXA+89PVf8PwXf8SxkkPQHaNGAahozPtqDAXTtjj3Lb9SqlX/DPcxU8ac4xu6tY2MIP4sMzNzZwu1fQOA12t8XQ4gpr6HlFIXhDa0+QGAYgAuETn+h+w8ANsb0x4RdVwMh0REbUjW3KzlAP5idR0EpBWhd82vRQQ/OHwI12Tvx1slJbU+82V5Oebs34fbDh/Cn1KDM1JviIvHM4UF+FXOUdzaJQFPFRbg1oQEaCJnPL+7YF981oHl+N2r38YLX/4Ju45uxEtf/fmM+3YcXofPNryGH134R9j0M5f4fbT6eVwy/hYs2vIeJg+8GFdMvBWfrHsZIrZI0ZM2NuG3o8EKPIcH5VTva7nhyTq0kYD4fmZm5jMt0bCIRCEY5N6tcflFAE+HjqSIaEg7Sik/gB8C+K+IbALwXZw8UucNAL8QkQ0i0idsxRNRu8HpAUREbc8fAJwPYLzVhXRW3fLVfl2dOr33le49kGKzodDvxw8OH0Jvux1jIyNPee7cmBicGxODtVVVeLwgH89374F0mw0v9egJADjg9eKY34/edgf+L+cofErhJ4lJyLAHA94vewwsvGDEE+kAsOvoRny16S3Mnf3rU/o4VLAbbyz9O3588XzERJy5we3uo5vgikpAsqsbfH4PRAQiAq8/mJkM56RoX+WH4fqtqtWyvPcmXNXz7v26GK06RbqPmTIGPlg1xfQogDM2fwkXpVQlgITTrv0XwH9rXMqo8dpaADPraOs9BI/COP36Mpx6lMXMGq8VgGsOiTo8jhwSEbUxWXOz/AC+jeD0L7LA9C3m4dOvpdhsAIAEw8Ds6GhsdlfX+fzYyEgc9vlQ7Pefcv2xgnz8JDEJrxQX4xpXHH6elIwnCwpOvO70FMWe3hYA/G/NC9icHdzr5f2Vz8Djq8ZzX9yPv7xzK57+9Dcn7lNK4dP1r+DC0d8BAEwZNAfvLH8ST33y6xPTTzVbnxGAnPH+wslUAefSY/+tUEqZ9d8dXn3MlDGzWn8E0QRwU2ZmZmEr9klEFHYcOSQiaoOy5mbtHfbSsBsAfAz+IK/Vnb7esMo0oaAQpemoMk0sr6zC7YmnDOLggNeLHjYbRATb3G54lUKcfrKZNVVVSDYMZNjtcCsTguB/WHeN/OTwlHY5/nn/9JHonz4SAHDJuFtO3HPXJX+rs24ROeX11PiemHf1v06/RzRb772mb2+3BvxWNNmx6uxh+e5DS5IjekxvyX5q0zs0gvh1640g/iozM/OrVuiHiKhFMRwSEbVRWXOzPhv20rBfAXjQ6lo6m7RinLLeqtDvx0+OHgEQPIZiTmwspkVF442S4ODut+Li8UV5OT4oK4UhAqcIHk5LP7FBjVIKTxcW4OH0rgCAa11x+GXOUQQU8LuUlBP9GAF3DJRyQ6RFA40RMaWH17e3JbsAACw59vbYq3refVATvUeLd3aaGgFxMAQNWo/XRK9nZmb+tQXbJyJqNaKUsroGIiI6i2EvDXsNwV0KqRV0z1P7H34uYNlxIgtnPH5UiZ7e0v24S57YAuUd2tL9dI3sv2FK8hUjRWrZgacV7NOOtWRA3ABgSmZmZt1zjImI2hFOVSIiavu+j+A3odQKQucbWkYL+Epaox/dPrxV1rQeqdo1qsib0+q7lx7XO7gGcRsUwh3g8gFcyWBIRB0JwyERURuXNTerGsCVCH4zSi1s/C5ls7J/I1Bd2Sr9OMcNw8kDzlvU4pw3R5jKzGmNvmoTCojbwxgQ/QCuzczMPBCm9oiI2gSGQyKidiBrbtYBANch+E0ptaDU09Ybtjabt7JVAptoEXGiuVplRNqnvLGrCz5u0R1S69PbTBkdxoB4W2Zm5uIwtENE1KYwHBIRtRNZc7MWAbjb2io6th55ar+mkGxlDXZvaaC1+tKdE1rt+4ADFVvHlXjzl7VWf7UJU0Ccn5mZ+VzYiiIiakMYDomI2pGsuVlPgruXthir1xsCgNNd1Gp96fbBowEU1HtjmCzMeW2wUqal06ObGRDfAvDrcNdERNRWMBwSEbUzWXOz5gH4t9V1dETjLF5vCAAR7sJWq0FEM8Totq21+vOa7vh1hV+0/Bka9ehtpoye7RvW2IC4AsDczMxMbvNORB0WwyERUft0G4B3rS6io0ktRl+ra3C6C1vj0PYTbBFTklqzv73lGyeW+4pXtmaftellJjcmIO4DcHlmZqa7pesiIrISwyERUTuUNTcrAODbABZaXUtH0fOY2qcptGpQqo3TUxTdmv1pRtdBgLG7Nfv8OufVPkqp1ps/W4cGBsTDAM7LzMxs1nRYEXleRPJEZEuNa11E5AsR2R36NT50faaITK5x34sick1z+iciagiGQyKidiprbpYHwOUA1lldS0cwdat5xOoaAMDhLnG1dp+6fWCrvnd3oDJpc/Hi7a3ZZ13qCYi5AGZnZmbuC0NXLwK48LRr8wB8pZTqB+Cr0NcAMBPAZBARtTKGQyKidixrblY5gIsA7LS6lvZu3C5lWF0DANh9ZQlQqlXXtRkRkwYBaLVdUgFgR+mqKVX+stWt2WddepnJo8/1DdtxWkDMRzAY7gpHH0qpJQBOHy29HMBLoc9fAnCFiGQgOG38ZyKyUUSmhV6fLiLLRWQfRxGJqKUwHBIRtXNZc7PyAZyP4PQ3aqLUEuvXGwKApkwDQElr9ilaTAokqlXOPKzpq6OvdFdKlbZ2v7XJMJNH1QiIxQhOJW3pzXpSlFI5oc9zQ19nA3gawN+VUiOVUktDr6cBmArgEgDzW7guIuqkGA6JiDqArLlZBwHMAHDA6lrao4xctbctrDc8TpS/uLX7NJxjvK3dZ1WgPG1byYqs1u63Lhlm8qhZvqHrAJyfmZm5qTX7VsHR4rONGL+vlDKVUtsApLRSWUTUyTAcEhF1EFlzs/YhGBD3W11Le9NW1hseZwQ8Za3dp+4YMQpAeWv3u6Vk6VR3oHJ9a/dbh+LeZsrPMjMz17ZSf8dEJA0AQr/mneVeT43PpUWrIqJOi+GQiKgDyZqbdQDAdACtuvtkezdut/XnG9Zk+KqackB7s4jYIkRP3tja/QLAV0dfSVZKVVrRdw1FAM7tNn9aawVDAPgQwNzQ53MBfBD6vBz/3959h8lVlQ8c/74pJPQOAkGpUjR0kWKQJkVQQKkCRkCxYEFRwYoFFHtBadKCIqCCgoCiohQVkSoLUkVAMPQmIAGS9/fHOQvj/jbJJtmdO7P5fp5nn525c3fmvTu7d+57znvOgQXbGIckASaHkjTs9EzsuZeSIN44s31VLP0YqzYdQ6t5nnvy+SZed9TYjRdq4nWfeuHxcbc/eU2Ts+7eD2w57qgJQ9aDGRFnAFcAq0XEvRFxAGXs4Bsi4nZga14aS/hLYJc+E9JI0pDriJnZJEmDq2diz/3jJ41/PXAh8Nqm4+lkK96f/xgBKzcdR6sxUx5v62ylvUaMXmktGHEvTBvX7te+7tGLJ6ywwKtumGfkvGu1+aVvB7Ydd9SEIS3Hzsy9pvPQVv3sexvQ+nu4vM/jbV0LU9Lcw55DSRqmeib2PErpjbi46Vg6WaeNNwQYO+XRRsaURUSMGL3SP5p4bSAunnz6QpnZzpLaq4FNhzoxlKRuYXIoScNYz8Sep4AdgJ80HUun2uD2nKfpGPqa97+PjGnqtUfNu+kKTb32k88/ssI/n7rhyja93G+ALcYdNeGhNr2eJHU8k0NJGuZ6JvZMAfYEvtB0LB0nM5d+rDPWN2w19tlH5mvqtUeMXPwVxJjGlpe4+uGLJjw/bcpQry94OrDjuKMmPDXEryNJXcXkUJLmAj0Te7JnYs/hwNuAZ5uOp1OsdD//GAFLNB1HX2OnPNbIxDC9Rs6z1uNNvXaSI/8w+YzRmTlU6y5+Ddh33FETGpn0R5I6mcmhpLlKREytMwD+LSKujYhNZvN5To2IXWfxZxrvpeiZ2HMGsDlldsa53utumvbvpmPoz5gpjy/a5OuPGvuatWiwEeGx5x5Y9V9P33LFID/tc8B+446a8PFxR01oZMIfSep0JoeS5jb/zcx1MnNt4BPAl5sOqD8RMWSzSfdM7LkS2BD421C9RrfoxPGGAKOmPrsQmY0lZzFi7MIxYpHrmnp9gL88dP4mL0x7/rZBeroHKeMLTx2k55OkYcnkUNLcbCHgMYCIWCAiLq69iT0RsVPvThHx9oi4ofY2/rDl5zeLiD9HxJ2tvYgR8bGIuKr+zOf7vmgUX4uIG+tr7VG3bx4Rl0fEecDfI2L+iLigvu6NvfsNhp6JPf8CXkdZhHvulJlLPd5Z6xu2CqY92uTrjxr72kaXu0qmjb70/rOmZuYLc/hUVwMbjDtqwp8HIy5JGs5MDiXNbeatZaW3ACcCX6zbnwV2ycz1gC2Ab9Qk7lXAp4Eta2/jh1qeaxlKgrUjdfHqiNgGWJXSM7cOsH5EbNYnhrfUx9amLDXxtYhYpj62HvChzHwlsB3w78xcOzNfDfx6kH4HwIszme5C6T2d68rsVrqfO0bA4k3HMT0jpj7/RKOvP88a60I0OpPnw1PuW2Pyf//xpzl4iknAhHFHTfjXYMUkScOZyaGkuU1vWenqlOTrtIgIIIAvRcQNwO+A5YClgS2Bn2bmwwCZ2dqb84vMnJaZf6/7AmxTv64DrgVWh//XO/U64IzMnJqZDwCXAq+pj/01M3vXXOsB3hARX4mICZk56MlCz8SeaT0Tez4JvJFSejfXmHDjtMlNxzAjo6Y+2+gY1YgRo0aMGjfUs4bO1J8e+MVGU/OFO2fxx54F3jvuqAnvGHfUBCdgkqQBMjmUNNfKzCsoM1UuCexdv6+fmesADwBjZ/IUU1puR8v3L9cEdJ3MXCUzT5qFsJ5uie82Sk9iD3BERHx2Fp5nlvRM7Pk1pSfz4qF6jU6zwR2dOd6w1+jnnpoy872G1qh5N31Z0zFMY+qYy+8/++nMnDbAH/k7sOG4oyYcN5RxSdJwZHIoaa4VEasDI4FHgIWBBzPz+YjYAnhF3e33wG4RsXj9mcVm8rQXAftHxAJ1/+UiYqk++1wO7BERIyNiSWAz4K/9xLcs8Exm/ogy/f56s3OcA9Uzsed+Sq/np4A5HefV2TJzyQ4ebwgwz3NPTG06hhGjll0NRg3WpDCz7YFn7xr/4LP3/HEAu54IvGbcURMaW6dRkrpZo4PNJakB80bE9fV2ABMzc2pEnA78MiJ6KBNY3AKQmTdFxJHApRExlVIu+o7pPXlm/iYi1gCuKNWqPAXsw/+WbP4c2JgyW2gCH8/M+2uy2mo8ZTziNOB54L2zf9gD0zOxZxrwpfGTxl8CnAG8fKhfswkrl/GGHZ0cjp3S6Hw0Lxo5zxqTpz7X88qm47j8gZ9t8JZXHHzPiBjZ39/kk8CB446acFa745Kk4SQy57o5CCRJAzB+0vhFKT0xb2k6lsH2jt9OveyNV2ffiYI6yt3Lv+FP/1h5502bjiOnPfXglCdOWJzSy96o5eZb9bpNl9plnTpOuNeVwF7jjprwz+n9nCRpYCwrlST1q2diz2M9E3veCrwTeLzhcAbV+rfnmKZjmJmxzz4yb9MxAMSIBZYi5m90zcNe9z1z+7qPTpl8eb07hbJW6aaDnRhGxM4Rkf305nesiHhHRHyv6TgkdTeTQ0nSDPVM7DkJWAP4WdOxDIrMXPKJzi4pBRg75dEFmo6h16ixGzzfdAy9Lr3/rHWen/bcr4H1xx014ahxR00YirGZewF/rN8laa5hcihJmqmeiT3390zs2Q3YGbiv4XDmyMqTuX0EzGxiocaNmfL4wk3H0GvkmLXXBRpdd7F65vl87ovn3P2tHccdNeGmoXiBOpnU64ADgD3rtmUi4rK6RuqNETGhTih1ar3fExEfrvuuExF/iYgbIuLnEbFo3b5KRPwuIv4WEddGxMr9vPabIuLKiLiu7rt0b0wRcUp9nRsi4q11+34RcVtE/BXYtOV5To2IY2scd0bE5hFxckTcHBGnDsXvTdLwYHIoSRqwnok95wJrAsdSJtPpOpvdOO3+pmMYiHmee3JxOmRigIhRY2Pk0jc0HMbvgPGHnHX+1w856/yhnMl1J+DXdSmZRyJifeBtwEV1mZu1geuBdYDlMvPVmTkeOKX+/GnAoZm5FmUZmsPr9tOB72fm2sAmQH/rbP4R2Cgz1wXOBD5et38GeCIzx9fn/X1ELAN8npIUvo7yf9lqUcrEVx8GzgO+BbwKGB8R68zG70XSXMDkUJI0S3om9jzZM7HnfcAE4Oam45lV69/R+eMNAUbktFF00FjPUfNu3FRP5n3APoecdf4bDjnr/Dvb8Hp7URIz6ve9gKuA/SLic8D4zPwPcCewUkQcHRHbAU9GxMLAIpl5af35ScBmEbEgJZH8OUBmPpuZz/Tz2uOAi+qsyR+jJHMAWwPf790pMx8DXgtckpkPZeZzQN+ZWn+ZpXGhB3ggM3vqWpE3ASvM1m9G0rBncihJmi09E3v+ROk9+TTwn2ajGaAy3rDxZRkGKvKFx5qOodeIUSuOhxH3tPEl/wt8EVjtkLPOP70dL1jXMd0SODEi7qIkaLtT1ibdjJKonhoRb68J2trAJcB7KDP7zurrHVlLVa+vm44Gvld7It8NjJ2Dw5lSv09rud1736XMJPXL5FCSNNt6JvY81zOx50hgFUqp6QsNhzRDq/yb26OU23WFkVOndEzSHRExYvQq7Vou4qfAGoecdf5nDznr/Kfb9JoAuwI/zMxXZOYKmbk88E9KYvhAZv6AkgSuFxFLACMy82xKA8l6mfkE8FhETKjPty9wae1pvDcidgaIiDERMV9mfioz16nlqgAL89KY3oktcf0WOKj3Th3HeCXw+ohYPCJGA7sN8u9C0lzIliNJ0hzrmdjzIPC+8ZPGfxc4ijJuq+NMuGnaZOiensPRzz/zzAujO2bSUkbNu8mKzz1/WwIx051nz/XAhw456/zLhuj5Z2Yv4Ct9tp0NnAo8HRHPA08BbweWA06JiN6G9k/U7xOB4yJiPkrp6X51+77A8RHxBeB5SjLXt0z2c8BPI+Ix4PfAinX7EcD3I+JGYCrw+cw8p5a5XkEpP75+dg9aknpFh4x1lyQNI+Mnjd8M+BqwYdOxtPreMS/8daknOiumGblmnQ9f9sQiq2zWdBytnn38+zeQU9Ya5Kf9F2VylVMOOev8aYP83JKkAbKsVJI06Hom9lwGbETpiWlXKeIMRZeNNwQYM+XxjmvBHTlm7cFc0uJ+4IPAqoecdf5JJoaS1CzLSiVJQ6JnYk8CZ46fNP5sYB/KtPyrNxVPHW/YVcnh2CmPdlwj7qgxG6w19dm/PsucTZbyAPB14JhDzjq/v1k7JUkNMDmUJA2pnok9zwOnjJ80fhKwM3AY8Jp2xzHhxu4abwgw738fGd10DH3FiLELx4hFr8hpj208Gz8+GfgqcPwhZ53/30EOTZI0h0wOJUlt0TOxZxpwDnDO+Enjt6IkiVu36/XXvyPnbddrDZaxzz4yf9Mx9GfU2I1GP//Mr2blR24EvgP86JCzzn92aKKSJM0pk0NJUtv1TOy5GLh4/KTxG1CSxF0YwnHwkTltiSe7q9cQYOyUxxZqOob+jJhntXV55tcPQi41g92mARcA3znkrPMvblNokqQ5YHIoSWpMz8Seq4Fdx08avxJwAGXa/2UG+3VWvY/bA1Yb7OcdavNMeaIj12SMGDFyxKjlb572wj39JYf/AU4Gjj7krPP/0ebQJElzwKUsJEkdY/yk8aOAHYB3AdsBIwfjeQ+4aOql216brx+M52q337/+e1OIGNN0HH1Ne+H+25/7z49Xbdl0I/AD4NRDzjr/yYbCkiTNAXsOJUkdo2dizwvAucC54yeNHwfsX79eMSfPu14XjjfsFUx7JBm5bNNx9DVi1MtWJea5inzuKsr6hFc3HZMkac7YcyhJ6mjjJ40fAbwBmAjsCCw4Kz8fmdPOPGrqfwIWHor4htqlr/vGzVNHjV2j6ThaTAEuBH4EXHDQcVtOaTgeSdIgsedQktTR6iynFwEXjZ80fgwlUXwL8GZg8Zn9/Cvv5bZocH3FOTVy6rNPTx01J0sKDorngUuBs4CfHXTclo83G44kaSiYHEqSukbPxJ4pwPnA+eMnjR8JvJ6SKO4C9Ft6OeGmaQ/QxcnhPM8/9exzYxZp4qUfoPQQXgD85qDjtvxPuwOIiJMpvcUPZuar67bdgM8BawAbZubVdfs6wLKZeWG9/zngqcz8ervjlqRuZXIoSepKPRN7pgK/B34/ftL4DwAbUXoTtwbWoy6Nsd4/une8IcA8U56YygLj2vFSCVxLSQbPB64+6Lgtmx57cirwPeC0lm03UhoEju+z7zrABpSEVpI0G0wOJUldr2diTwJX1K9PjJ80flFgc2DrRZ5iPUriE81FOPvGTnl0KJ/+LuCPwCXAhQcdt+XkoXyxWZWZl0XECn223QwQ8dLbGRHzAF8A5o2I1wFfrg+tGRGXAC8Hvp2Z321D2JLUtUwOJUnDTs/EnseAnwM/ZyLcvPoaiwObAq8DJgDrA6MbDHHAxj776GB9Vj8H3ABcSUkI/3jQcVveO0jP3ajMfC4iPgtskJnvhxfLSlcHtqBMYnRrRBybmc83F6kkdTaTQ0nSsLfGLTc/ApxXv7h59TXmBdYC1uzz9Qo6rIdx3v8+Mjuz0TwJ3ArcDFwN/BW4fi6cWfSCzJwCTImIB4GlgWGREEvSUDA5lCTNdda45eb/UnrQrmzdfvPqa8xHmeikb9K4EnUMY7uNnfLI9JbumAbcA9xCSQRf/N5p5aENak2Gp+J1jyTNkCdJSZKqNW65+Rngmvr1optXX2MssAKwDPCylq+lgaWARft8zW7JagJPAI/Ur0fHTHniHsoEMZP7fN110HFb/nc2X2c4+g+zuAamJOl/RWbTE5FJkjS83Lz6GvMDC1FKVHMWvp5a45abpzYRcyeKiDMoEwstQVla43DgUeBoYEngceD6zNw2IhajrIc5mjIhzRq0LGURETcCO2bmXe09CknqHiaHkiRJkqRmxk9IkiRJkjqLyaEkSZIkyeRQkiRJkmRyKEmSJEnC5FCSJEmShMmhJEkCImLniMiIWL3pWCRJzTA5lCRJAHsBf6zfJUlzIZNDSZLmchGxAPA64ABgz7ptmYi4LCKuj4gbI2JCRIyMiFPr/Z6I+HDdd52I+EtE3BARP4+IRev2VSLidxHxt4i4NiJW7vO620XET1vubx4R59fbe9XXuDEivtLnZ66tz3nxkP9yJGkuYnIoSep4tdzxRy33R0XEQ72JxCw+1yIR8b7BjbDr7QT8OjNvAx6JiPWBtwEXZeY6wNrA9cA6wHKZ+erMHA+cUn/+NODQzFwL6AEOr9tPB76fmWsDmwCT+7zu74DXRsT89f4ewJkRsSzwFWDL+pqvqWWvSwI/AN5an3O3wfsVSJJMDiVJ3eBp4NURMW+9/wbgvtl8rkWAWUoOoxjOn5l7AWfW22fW+1cB+0XE54Dxmfkf4E5gpYg4OiK2A56MiIWBRTLz0vrzk4DNImJBSiL5c4DMfDYzn2l90cx8Afg18KaIGAXsAJwLvAa4JDMfqvucDmwGbARclpn/rD//6FD8MiRpbjWcP+gkScPLhZTkAUryckbvAxGxYURcERHXRcSfI2K1uv1VEfHXWhp5Q0SsChwFrFy3fa3u97GIuKru8/m6bYWIuDUiTgNuBJbvr6Sy20XEYpQeuhMj4i7gY8DuwOWUhOw+4NSIeHtmPkbpRbwEeA9w4my83pH1d3993XRmfb0tgatrEipJaoDJoSSpW5wJ7BkRY4G1gCtbHrsFmJCZ6wKfBb5Ut78H+E4tjdwAuBc4DPhHZq6TmR+LiG2AVYENKSWM60fEZvXnVwWOycxXAUvQf0llt9sV+GFmviIzV8jM5YF/UhLDBzLzB5QkcL2IWAIYkZlnA58G1svMJ4DHImJCfb59gUtrkndvROwMEBFjImK+zPxU/d2vU/e/FFgPeBcv9V7+FXh9RCwRESMpjQGXAn+h9EquWJ9zsSH7rUjSXGhU0wFIkjQQmXlDRKxASRQu7PPwwsCk2jOYwOi6/QrgUxExDjgnM2+PiL5PvU39uq7eX4CSFN4D3J2Zf6nbXyypBC4AfjNYx9awvSjj+1qdDZwKPB0RzwNPAW8HlgNOaSmx/UT9PhE4LiLmo/ye9qvb9wWOj4gvAM9Txgje2fpCmTm1jh19R30eMnNyRBwG/AEI4ILMPBcgIg4EzqkxPEgpMZYkDYLIzKZjkCRphiLiqcxcICI+C3wI2BxYHPhoZu4YEacC12bmd2sCeUlmrlB/dmVKOeoHgHdTkpPzM/PV9fFvALdl5vF9XnOF1v3qtgWAbSlJz6OZuf+QHbQkSW1mWakkqZucDHw+M3v6bF+YlyaoeUfvxohYCbgzM79LmehkLeA/wIItP3sRsH9N/IiI5SJiqb4v3F9J5aAckSRJHcKyUklS18jMe4Hv9vPQVyllpZ+mlHz22h3Yt5ZG3g98KTMfjYg/RcSNwK/quMM1gCtqyelTwD7A1D6vMb2SSkmShgXLSiVJkiRJlpVKkiRJkkwOJUmSJEmYHEqSJEmSMDmUJEmSJGFyKEmSJEnC5FCSJEmShMmhJEmSJAmTQ0mSJEkSJoeSJEmSJEwOJUmSJEmYHEqSJEmSMDmUJEmSJGFyKEmSJEnC5FCSJEmShMmhJEmSJAmTQ0mSJEkSJoeSJEmSJEwOJUmSJEmYHEqSJEmSMDmUJEmSJGFyKEmSJEnC5FCSJEmShMmhJEmSJAmTQ0mSJEkSJoeSJEmSJEwOJUmSJEmYHEqSJEmSMDmUJEmSJGFyKEmSJEnC5FCSJEmShMmhJEmSJAmTQ0mSJEkSJoeSJEmSJEwOJUmSJEmYHEqSJEmSMDmUJEmSJGFyKEmSJEnC5FCSJEmShMmhJEmSJAmTQ0mSJEkSJoeSJEmSJEwOJUmSJEmYHEqSJEmSMDmUJEmSJGFyKEmSJEnC5FCSJEmShMmhJEmSJAmTQ0mSJEkSJoeSJEmSJEwOJUmSJEmYHEqSJEmSMDmUJEmSJGFyKEmSJEnC5FCSJEmShMmhJEmSJAmTQ0mSJEkSJoeSJEmSJEwOJUmSJEmYHEqSJEmSMDmUJEmSJGFyKEmSJEnC5FCSJEmShMmhJEmSJAmTQ0mSJEkSJoeSJEmSJEwOJUmSJEmYHEqSJEmSMDmUJEmSJGFyKEmSJEnC5FCSJEmShMmhJEmSJAmTQ0mSJEkSJoeSJEmSJEwOJUmSJEmYHEqSJEmSMDmUJEmSJGFyKEmSJEnC5FCSJEmShMmhJEmSJAmTQ0mSJEkSJoeSJEmSJEwOJUmSJEmYHEqSJEmSMDmUJEmSJGFyKEmSJEnC5FCSJEmShMmhJEmSJAmTQ0mSJEkSJoeSJEmSJEwOJUmSJEmYHEqSJEmSMDmUJEmSJAGjmg6g3ZZYYolcYYUVmg5DkiRJkhpxzTXXPJyZS/bdPtclhyussAJXX31102FIkiRJUiMi4u7+tltWKkmSJEkyOZQkSZIkmRxKkiRJkjA5lCRJkiRhcihJkiRJwuRQkiRJkoTJoSRJkiQJk0NJkiRJEiaHkiRJkiRMDiVJkiRJmBxKkiRJkjA5lCRJkiRhcihJkiRJwuRQkiRJkoTJoSRJkiQJk0NJkiRJEjCq6QA6wUPH/qjpEAZkyffu03QIkiRJkoYpew4lSZIkSSaHkiRJkiSTQ0mSJEkSJoeSJEmSJEwOJUmSJEmYHEqSJEmSMDmUJEmSJGFyKEmSJEnC5FCSJEmShMmhJEmSJAmTQ0mSJEkSJoeSJEmSJIYwOYyIkyPiwYi4sWXbYhHx24i4vX5ftG6PiPhuRNwRETdExHotPzOx7n97RExs2b5+RPTUn/luRMRQHYskSZIkDXdD2XN4KrBdn22HARdn5qrAxfU+wPbAqvXrQOBYKMkkcDjwWmBD4PDehLLu866Wn+v7WpIkSZKkARqy5DAzLwMe7bN5J2BSvT0J2Lll+2lZ/AVYJCKWAbYFfpuZj2bmY8Bvge3qYwtl5l8yM4HTWp5LkiRJkjSL2j3mcOnMnFxv3w8sXW8vB/yrZb9767YZbb+3n+2SJEmSpNnQ2IQ0tccv2/FaEXFgRFwdEVc/9NBD7XhJSZIkSeoq7U4OH6glodTvD9bt9wHLt+w3rm6b0fZx/WzvV2aekJkbZOYGSy655BwfhCRJkiQNN+1ODs8DemccnQic27L97XXW0o2AJ2r56UXANhGxaJ2IZhvgovrYkxGxUZ2l9O0tzyVJkiRJmkWjhuqJI+IMYHNgiYi4lzLr6FHATyLiAOBuYPe6+4XAG4E7gGeA/QAy89GI+CJwVd3vC5nZO8nN+ygzos4L/Kp+SZIkSZJmw5Alh5m513Qe2qqffRM4aDrPczJwcj/brwZePScxSpIkSZKKxiakkSRJkiR1DpNDSZIkSZLJoSRJkiTJ5FCSJEmShMmhJEmSJAmTQ0mSJEkSJoeSJEmSJEwOJUmSJEmYHEqSJEmSMDmUJEmSJGFyKEmSJEnC5FCSJEmShMmhJEmSJAmTQ0mSJEkSJoeSJEmSJEwOJUmSJEmYHEqSJEmSMDmUJEmSJGFyKEmSJEnC5FCSJEmShMmhJEmSJAmTQ0mSJEkSJoeSJEmSJEwOJUmSJEmYHEqSJEmSMDmUJEmSJGFyKEmSJEnC5FCSJEmShMmhJEmSJAmTQ0mSJEkSJoeSJEmSJEwOJUmSJEmYHEqSJEmSMDmUJEmSJGFyKEmSJEnC5FCSJEmShMmhJEmSJAmTQ0mSJEkSJoeSJEmSJEwOJUmSJEmYHEqSJEmSMDmUJEmSJGFyKEmSJEnC5FCSJEmShMmhJEmSJAmTQ0mSJEkSJoeSJEmSJEwOJUmSJEmYHEqSJEmSMDmUJEmSJGFyKEmSJEnC5FCSJEmShMmhJEmSJAmTQ0mSJEkSJoeSJEmSJEwOJUmSJEmYHEqSJEmSMDmUJEmSJGFyKEmSJEmioeQwIj4cETdFxI0RcUZEjI2IFSPiyoi4IyLOioh56r5j6v076uMrtDzPJ+r2WyNi2yaORZIkSZKGg7YnhxGxHPBBYIPMfDUwEtgT+ArwrcxcBXgMOKD+yAHAY3X7t+p+RMSa9edeBWwHHBMRI9t5LJIkSZI0XDRVVjoKmDciRgHzAZOBLYGf1ccnATvX2zvV+9THt4qIqNvPzMwpmflP4A5gw/aEL0mSJEnDS9uTw8y8D/g6cA8lKXwCuAZ4PDNfqLvdCyxXby8H/Kv+7At1/8Vbt/fzM/8jIg6MiKsj4uqHHnpocA9IkiRJkoaBJspKF6X0+q0ILAvMTykLHTKZeUJmbpCZGyy55JJD+VKSJEmS1JWaKCvdGvhnZj6Umc8D5wCbAovUMlOAccB99fZ9wPIA9fGFgUdat/fzM5IkSZKkWdBEcngPsFFEzFfHDm4F/B34A7Br3WcicG69fV69T33895mZdfuedTbTFYFVgb+26RgkSZIkaVgZNfNdBldmXhkRPwOuBV4ArgNOAC4AzoyII+q2k+qPnAT8MCLuAB6lzFBKZt4UET+hJJYvAAdl5tS2HowkSZIkDRNtTw4BMvNw4PA+m++kn9lGM/NZYLfpPM+RwJGDHqAkSZIkzWWaWspCkiRJktRBTA4lSZIkSSaHkiRJkiSTQ0mSJEkSJoeSJEmSJEwOJUmSJEmYHEqSJEmSMDmUJEmSJGFyKEmSJEnC5FCSJEmShMmhJEmSJAmTQ0mSJEkSJoeSJEmSJEwOJUmSJEmYHEqSJEmSMDmUJEmSJGFyKEmSJEnC5FCSJEmSBIxqOgANvsnHHNp0CAOyzPu+0nQIkiRJkip7DiVJkiRJJoeSJEmSJJNDSZIkSRImh5IkSZIkTA4lSZIkSZgcSpIkSZIwOZQkSZIkYXIoSZIkScLkUJIkSZKEyaEkSZIkCZNDSZIkSRImh5IkSZIkTA4lSZIkSZgcSpIkSZIwOZQkSZIkYXIoSZIkScLkUJIkSZLELCaHEbFoRKw1VMFIkiRJkpox0+QwIi6JiIUiYjHgWuAHEfHNoQ9NkiRJktQuA+k5XDgznwTeApyWma8Fth7asCRJkiRJ7TSQ5HBURCwD7A6cP8TxSJIkSZIaMJDk8AvARcAdmXlVRKwE3D60YUmSJEmS2mnUzHbIzJ8CP225fyfw1qEMSpIkSZLUXtNNDiPiaCCn93hmfnBIIpIkSZIktd2Meg6vblsUkiRJkqRGTTc5zMxJ7QxEkiRJktScmY45jIglgUOBNYGxvdszc8shjEuSJEmS1EYDma30dOBmYEXg88BdwFVDGJMkSZIkqc0GkhwunpknAc9n5qWZuT9gr6EkSZIkDSMzLSsFnq/fJ0fEDsC/gcWGLiRJkiRJUrsNJDk8IiIWBg4BjgYWAj48pFFJkiRJktpqpslhZp5fbz4BbDG04UiSJEmSmjCQ2UpPAbLv9jr2UJIkSZI0DAykrPT8lttjgV0o4w4lSZIkScPEQMpKz269HxFnAH8csogkSZIkSW03kKUs+loVWGqwA5EkSZIkNWcgYw7/QxlzGPX7/cChQxyXJEmSJKmNBlJWumA7ApEkSZIkNWe6yWFErDejH8zMawc/HEmSJElSE2bUc/iN+n0ssAHwN0pp6VrA1cDGs/uiEbEIcCLwakqp6v7ArcBZwArAXcDumflYRATwHeCNwDPAO3oT04iYCHy6Pu0RmTlpdmOSJEmSpLnZdCekycwtMnMLYDKwXmZukJnrA+sC983h634H+HVmrg6sDdwMHAZcnJmrAhfX+wDbUybBWRU4EDgWICIWAw4HXgtsCBweEYvOYVySJEmSNFcayGylq2VmT++dzLwRWGN2XzAiFgY2A06qz/dcZj4O7AT09vxNAnaut3cCTsviL8AiEbEMsC3w28x8NDMfA34LbDe7cUmSJEnS3GwgyeENEXFiRGxev34A3DAHr7ki8BBwSkRcV597fmDpzJxc97kfWLreXg74V8vP31u3TW/7/xMRB0bE1RFx9UMPPTQHoUuSJEnS8DSQ5HA/4CbgQ/Xr73Xb7BoFrAccm5nrAk/zUgkpAJmZlLGIgyIzT6hlsRssueSSg/W0kiRJkjRsDGQpi2eBb9WvwXAvcG9mXlnv/4ySHD4QEctk5uRaNvpgffw+YPmWnx9Xt90HbN5n+yWDFKMkSZIkzVWm23MYET+p33si4oa+X7P7gpl5P/CviFitbtqK0ht5HjCxbpsInFtvnwe8PYqNgCdq+elFwDYRsWidiGabuk2SJEmSNItm1HP4ofp9xyF43Q8Ap0fEPMCdlDLVEcBPIuIA4G5g97rvhZRlLO6gLGWxH0BmPhoRXwSuqvt9ITMfHYJYJUmSJGnYm25y2DI5zFuBMzPz34P1opl5PWXtxL626mffBA6azvOcDJw8WHFJkiRJ0txqIBPSLAj8NiIuj4j3R8TSM/0JSZIkSVJXmWlymJmfz8xXUXrvlgEujYjfDXlkkiRJkqS2GUjPYa8HKesPPgIsNTThSJIkSZKaMNPkMCLeFxGXABcDiwPvysy1hjowSZIkSVL7zHSdQ8oagwfXSWQkSZIkScPQdJPDiFgoM58EvlbvL9b6uMtGSJIkSdLwMaOewx9T1ji8BkggWh5LYKUhjEuSJEmS1EYzWudwx/p9xfaFI0mSJElqwozKSteb0Q9m5rWDH44kSZIkqQkzKiv9Rv0+FtgA+BultHQt4Gpg46ENTZIkSZLULtNdyiIzt8jMLYDJwHqZuUFmrg+sC9zXrgAlSZIkSUNvpuscAqtlZk/vncy8EVhj6EKSJEmSJLXbQNY5vCEiTgR+VO/vDdwwdCFJkiRJktptIMnhfsB7gQ/V+5cBxw5ZRJIkSZKktptpcpiZzwLfql+SJEmSpGFopslhRGwKfA54Rev+mbnS0IUlSZIkSWqngZSVngR8GLgGmDq04UiShsIbf3FI0yEMyIU7f2PmO0mSpCExkOTwicz81ZBHIkmSJElqzECSwz9ExNeAc4ApvRsz89ohi0qSJEmS1FYDSQ5fW79v0LItgS0HPxxJkiRJUhMGMlvpFu0IRJIkSZLUnOkmhxHxkRn9YGZ+c/DDkSRJkiQ1YUY9hwu2LQpJkiRJUqOmmxxm5ufbGYgkSZIkqTkjmg5AkiRJktQ8k0NJkiRJ0vSTw4j4UP2+afvCkSRJkiQ1YUY9h/vV70e3IxBJkiRJUnNmNFvpzRFxO7BsRNzQsj2AzMy1hjY0SZIkSVK7zGi20r0i4mXARcCb2xeSJEmSJKndZtRzSGbeD6wdEfMAr6ybb83M54c8MkmSJElS28wwOQSIiNcDpwF3UUpKl4+IiZl52RDHJkmSJElqk5kmh8A3gW0y81aAiHglcAaw/lAGJkmSJElqn4Gsczi6NzEEyMzbgNFDF5IkSZIkqd0G0nN4dUScCPyo3t8buHroQpIkSZIktdtAksP3AgcBH6z3LweOGbKIJEmSJEltN9PkMDOnUMYdfnPow5EkSZIkNWEgYw4lSZIkScOcyaEkSZIkyeRQkiRJkjSbyWFEHDjYgUiSJEmSmjO7PYcxqFFIkiRJkho1W8lhZh4/2IFIkiRJkpoz0+QwIsZFxM8j4qGIeDAizo6Ice0ITpIkSZLUHgPpOTwFOA9YBlgW+GXdJkmSJEkaJgaSHC6Zmadk5gv161RgySGOS5IkSZLURgNJDh+JiH0iYmT92gd4ZKgDkyRJkiS1z0CSw/2B3YH7gcnArsB+QxmUJEmSJKm9Rs1sh8y8G3hzG2KRJEmSJDVkuslhRHx2Bj+XmfnFIYhHkiRJktSAGfUcPt3PtvmBA4DFAZNDSZIkSRomppscZuY3em9HxILAhyhjDc8EvjG9n5MkSZIkdZ8ZjjmMiMWAjwB7A5OA9TLzsXYEJkmSJElqnxmNOfwa8BbgBGB8Zj7VtqgkSZIkSW01o6UsDgGWBT4N/Dsinqxf/4mIJ9sTniRJkiSpHWY05nAgayBKkiRJkoYBE0BJkiRJksmhJEmSJKnB5DAiRkbEdRFxfr2/YkRcGRF3RMRZETFP3T6m3r+jPr5Cy3N8om6/NSK2behQJEmSJKnrNdlz+CHg5pb7XwG+lZmrAI8BB9TtBwCP1e3fqvsREWsCewKvArYDjomIkW2KXZIkSZKGlUaSw4gYB+wAnFjvB7Al8LO6yyRg53p7p3qf+vhWdf+dgDMzc0pm/hO4A9iwLQcgSZIkScNMUz2H3wY+Dkyr9xcHHs/MF+r9e4Hl6u3lgH8B1MefqPu/uL2fn5EkSZIkzYK2J4cRsSPwYGZe08bXPDAiro6Iqx966KF2vawkSZIkdY0meg43Bd4cEXcBZ1LKSb8DLBIRvesujgPuq7fvA5YHqI8vDDzSur2fn/kfmXlCZm6QmRssueSSg3s0kiRJkjQMtD05zMxPZOa4zFyBMqHM7zNzb+APwK51t4nAufX2efU+9fHfZ2bW7XvW2UxXBFYF/tqmw5AkSZKkYWXUzHdpm0OBMyPiCOA64KS6/STghxFxB/AoJaEkM2+KiJ8AfwdeAA7KzKntD1uSJEmSul+jyWFmXgJcUm/fST+zjWbms8Bu0/n5I4Ejhy5CSZIkSZo7NLnOoSRJkiSpQ5gcSpIkSZJMDiVJkiRJJoeSJEmSJEwOJUmSJEmYHEqSJEmSMDmUJEmSJGFyKEmSJEnC5FCSJEmShMmhJEmSJAmTQ0mSJEkSJoeSJEmSJEwOJUmSJEmYHEqSJEmSMDmUJEmSJGFyKEmSJEnC5FCSJEmShMmhJEmSJAmTQ0mSJEkSJoeSJEmSJEwOJUmSJEmYHEqSJEmSMDmUJEmSJGFyKEmSJEnC5FCSJEmShMmhJEmSJAmTQ0mSJEkSJoeSJEmSJEwOJUmSJEmYHEqSJEmSMDmUJEmSJGFyKEmSJEnC5FCSJEmShMmhJEmSJAmTQ0mSJEkSJoeSJEmSJEwOJUmSJEmYHEqSJEmSMDmUJEmSJGFyKEmSJEnC5FCSJEmShMmhJEmSJAmTQ0mSJEkSJoeSJEmSJEwOJUmSJEmYHEqSJEmSMDmUJEmSJGFyKEmSJEnC5FCSJEmShMmhJEmSJAmTQ0mSJEkSJoeSJEmSJEwOJUmSJEmYHEqSJEmSMDmUJEmSJGFyKEmSJEnC5FCSJEmShMmhJEmSJIkGksOIWD4i/hARf4+ImyLiQ3X7YhHx24i4vX5ftG6PiPhuRNwRETdExHotzzWx7n97RExs97FIkiRJ0nDRRM/hC8AhmbkmsBFwUESsCRwGXJyZqwIX1/sA2wOr1q8DgWOhJJPA4cBrgQ2Bw3sTSkmSJEnSrGl7cpiZkzPz2nr7P8DNwHLATsCkutskYOd6eyfgtCz+AiwSEcsA2wK/zcxHM/Mx4LfAdu07EkmSJEkaPhodcxgRKwDrAlcCS2fm5PrQ/cDS9fZywL9afuzeum162yVJkiRJs6ix5DAiFgDOBg7OzCdbH8vMBHIQX+vAiLg6Iq5+6KGHButpJUmSJGnYaCQ5jIjRlMTw9Mw8p25+oJaLUr8/WLffByzf8uPj6rbpbf9/MvOEzNwgMzdYcsklB+9AJEmSJGmYaGK20gBOAm7OzG+2PHQe0Dvj6ETg3Jbtb6+zlm4EPFHLTy8CtomIRetENNvUbZIkSZKkWTSqgdfcFNgX6ImI6+u2TwJHAT+JiAOAu4Hd62MXAm8E7gCeAfYDyMxHI+KLwFV1vy9k5qNtOQJJkiRJGmbanhxm5h+BmM7DW/WzfwIHTee5TgZOHrzoJEmSJGnu1OhspZIkSZKkzmByKEmSJEkyOZQkSZIkmRxKkiRJkmhmtlJJkubIDucc3XQIA3LBWz7QdAiSJA2YPYeSJEmSJJNDSZIkSZLJoSRJkiQJk0NJkiRJEiaHkiRJkiRMDiVJkiRJmBxKkiRJkjA5lCRJkiRhcihJkiRJwuRQkiRJkoTJoSRJkiQJGNV0AJIkSZ1u17OvbTqEAfnZW9drOgRJXcyeQ0mSJEmSyaEkSZIkyeRQkiRJkoTJoSRJkiQJk0NJkiRJEiaHkiRJkiRcykKSpMbt+LPTmw5hQM7fde+mQ5AkDSF7DiVJkiRJJoeSJEmSJMtKJUnSENjpZ79qOoSZOnfX7ZsOQZI6ij2HkiRJkiSTQ0mSJEmSyaEkSZIkCZNDSZIkSRJOSCM14tyTu2MShJ327/wJJSRJkjQ47DmUJEmSJJkcSpIkSZJMDiVJkiRJmBxKkiRJkjA5lCRJkiRhcihJkiRJwuRQkiRJkoTJoSRJkiQJGNV0ANLMXHX8m5oOYUBe8+5fNh2CJEmSNNvsOZQkSZIkmRxKkiRJkiwrlaT/59Cfbdd0CAPylV1/3XQIkiRpGLHnUJIkSZJkz6EkSZKkoXX/N25pOoQBedkhqzcdQqPsOZQkSZIk2XMoSZIkdZqbjnug6RAG5FXvWbrpEDSITA4lzbHjf7ht0yEMyLv3vajpECRJkjqWZaWSJEmSJJNDSZIkSZJlpZIkSRoGfnXWw02HMFPb77FE0yFIM2TPoSRJkiTJ5FCSJEmSZHIoSZIkScLkUJIkSZKEE9JIkiTNdb7y88lNhzAgh+6yTNMhSHMVew4lSZIkSSaHkiRJkqRhkBxGxHYRcWtE3BERhzUdjyRJkiR1o64ecxgRI4HvA28A7gWuiojzMvPvzUYmSZIkabh68Og/NB3CgCz1gS1maf9u7zncELgjM+/MzOeAM4GdGo5JkiRJkrpOZGbTMcy2iNgV2C4z31nv7wu8NjPf32e/A4ED693VgFvbEN4SwMNteJ128Xg633A7Jo+n8w23Y/J4Ot9wOyaPp7MNt+OB4XdMHs/se0VmLtl3Y1eXlQ5UZp4AnNDO14yIqzNzg3a+5lDyeDrfcDsmj6fzDbdj8ng633A7Jo+nsw2344Hhd0wez+Dr9rLS+4DlW+6Pq9skSZIkSbOg25PDq4BVI2LFiJgH2BM4r+GYJEmSJKnrdHVZaWa+EBHvBy4CRgInZ+ZNDYfVq61lrG3g8XS+4XZMHk/nG27H5PF0vuF2TB5PZxtuxwPD75g8nkHW1RPSSJIkSZIGR7eXlUqSJEmSBoHJoSRJkiTJ5LBJETFv0zFIkiRJEpgcNiYiFgcOjYjtmo6lSRERTcfQVyfGpJkbru9bRLwqIrZpOo45NRzen+FwDOpe/v11lr7vh++PmhARr4uIkwbzOU0OmzMvZbbYCRGxZdPBtEPviTMilouIRSJiRGZmRHTM32FERNZZmiJidESMrLc7JsYZ6e/DqVtinxP9vG/D4pgjYgywFbBvRGzddDyzq8/7s15ELN10TLOqzzFsFBEvazomDcxwuGjv8/f3zm5rMOrvnNzN70uf92PBiJin065n5gbT+31389/WbLgG2CYijhusJ/SPuAE1KbqXsk7jSsABEbFJw2ENuXrifCNwLvBJ4Hf1dzGt4dAAiIiVgIXr7Q8DpwLHRsRymTmt00/6ETFfy4fVphGxGUA3xD6nWo77fcBJwDci4q3NRjXnMnMK5f/lCmCPiHhDwyHNlpb35xDgq8CYZiOadS3H8FHgc5QGvo43nQajkU3E0pSW9+5NEbFnRCzcbRePLcfwQeBdwORmI5o1vZ/zEbF1RKwbES+v1wRd9T4ARMSqwFr19keAHwMXRMQK3fJ5OxzOCxGxaMvf1Tsj4uCI2BdevN7sur+tWRURozLzv8Argc0j4sTBeN6O/wMejurJY1vgSOAvwDLAW4Z7D2JErA18HtgLuANYClio5fFG/pGjmBc4DvhgRGwP7AKcDDxKOemP6+STfkSMB94bEUtExHuA04CPR8SVMHckiBFxIPBW4ChgNaArEyn43/+FzLwb+DlwI7B7N/UYtB5HRLwF2B3YITPviYhXRMRqzUU3MH2OYQfgLcCbMvOfEbFSJx9DRCzSklRsHRG7A2Tm1GYja48+791+wBeAdwJfBzbtxothYHtg58zs6YZzeu1lP7re3g+YBLwHOCYi1u2mi/h6rTAW+Ciwd0TsA+wIfIRyLffnlgSxY/+2uv28UN+HccDVEbFhRGxBeQ/mBd4UEV+HFxPEjv8fmR29x1XXex9bE8R1gddGxMlz+vzD8pfW6SJiNPBG4CuZ+R3Kh9UzlNKxCY0GN7SeBY4GVqcc85sz8/GWHq6mFt0cUf+x3g+8BjgAOC0zL87Mw4BfAudGxCs6pZezHwsAG1FalDcBXpOZOwL3DtcEsZ9jmR94G7A55dz2/ogYFRHLtzu2ORHxP+VK29QPvsWBY4EeYLfoghLTPsexPHA3cC2wT0R8kdKAcXREbNhgmDPU5xheDkwD7qO8B18GjqecG9ZrMMx+RcQqwGERsU5E7E859x4QEVfWC6thrc97Nz+wJLB1Zm4NPERpqNiowy/i+yZNY4AVgKX77PfKdsU0G24GtoqIScDKwGspF/IXAV+PiHW6KEEcmZnPUhoZ5gO2BS7PzNsz8zPAD4DLImLlTk20hst5oVbffRf4EbAn8LbM/DKlqmNcRHy17tep12xzpKXHdF/giIj4OKWzZX1g/Yg4YU6ef9hcKHaTzHweeATYvrbg3EkpS9gM2CXKZDXDRkSsGKUM4wVKr863gY0z886IeB3wkYhYrqHYFqWU9vb6NOUDeOP6GPWkfylwek02OuZDLCLmqxdBV1AuVNcAXkH5ECYz3wrcExG31fvD4kQZEUtQGhmIiN0iYmFgMeBqYNvM3C4zXwD2p/TKj2ou2lnTckH7XuAblJ6C31IuRE4CbgDeWZPGjtVyHPsBvwaSct57G/BHynvzV6BjL85bjuFtwFmU3tt/AvsBl1ESjJ9QGmc6zWjK73ZXYAfgtZm5LeV3flK3NZrMiqjj2evtjwMXAu+jVBYAfBH4D6Uh8DWNBDkTfZLblSJiwcy8HzgG2D8iVq0Nfm8HTowy7q2TPpvGRCl5e4LScPkyyrnshcx8mtKD+AtK7Gs12Dg8IPV6oLcRaAngp8BjwCsjYl2AzDyccp44v9OuFVp09XmhftbPV+8eA3yM0nu7ft12CyV5f3VEHNH+CNsnIiYCh1J6rdert9ekNMDsFBHfme0nz0y/hvgLiPp9ZeDV9fZKwDcp5RWjgRWB3wCvajreQT7m1wA/BL4GjAW2A+6nlG2+HfgbpQexqTg3oZT3Hgfc0vLeXEQZF7lYy75LNv177RP7ApQP2y2ADwF7AxtSWtI+CKzasu8PgRWbjnkQj30N4AzgFOBWYMH6+zgXOLbucwBwE7B60/HO4rEFsDwlgXpl3bYlpedtC8q42AOBZZqOdQDHsjVlvOTLW7aNqN93pfSErtR0nDM5hrfW92L1lm2957c9gL930v8WpfW493e8OeVC6RpKKWLvPt8BrgSWazreIf5dTAAuqOeL/evf21vqY/MBhwNLNx3nTI7hw8DFwO9qvAdQqlz+QSmP/XunXTfU8/E+lF7OT9TPpwWBPwHfadlvEco10CuajnkAx7QqcBhwNvD3um1pSkXHEcC6Lfsu0XS8/cQ/LM4LlGFJ7wM+C1xRt70TuB3YtN4fQRla0rHHMYe/gwDmqe/XjnXby+r/2jfr/XmBlWf3NbqmNb2bZWZGGavyVUqN9LKUC/nLqWUJlJK4T2fmTc1FOnhajvlzlFKy1wEfp7T0vINSBvAM8PHMvKi1lbQd6nvwaGb+udbb70s54ZClR/MDwLeA+SPi65n5WGY+1K74BuhZygngSErCsG1m3hERxwLvBkZExEWZeXNm7ttkoIMtM2+OiJsoH9Yfy8z/1DLTD1NKFc+hXHjsnpm3NBjqgLT+/df/nQcpPVSjauv77yPiSGDXzPxDRJySpQKho/Tp7RhJ+bt8JeV89+W62/y1YuDTwF5ZKic6Rj/nomcpjS47UFqloRzDJsCngN0y859tDrNfUcZDvQ54WUQsRLlIOpMyM/b6EfFwZv4xMz9Uy646ttd2dkTEmsA2mfntiFgd+AxwX2beDNwcEU8An46IMZl5BmUMfMeKiI2BiZQk9zWUC97xvJQUJvD9Tvn761XPxwsAfwCeBPao294I/CYivp2ZB2cZVnJ8Oz/7Z1VEvBZYpF6nLEi5ZjsKIDMfqOXlH6cMC8rMvJ5SIdExosyp0NXnhVo6PYpSsfFrYFFqJUBmnlg/b34QEQdl5h8ojcbDRt9rBOC5iJhMmajur5l5f0ScDvwoyiSK91EakGaLyWEbRMT6lMRwO8pFxo8pk50cmJk/j4i1gGfqhX1bk6ShUk+i7wA+kpmXR5lsZ2fKxftRmfnr1v3bnBj2ntyvrxfhPwQeBzaIiEeBSzLztoj4JOUCtqPKr+uH1XzAg8AlwHspFwqrRcTkzPxTRDxPSZyejYg7OjGRmFX9/G/8iNJaeEBEPA6cXRONHer+82cpX+pofRKqFSllV/+qF7IHUS48XqB8YPcOQu+497PPcSwNTM3MsyPiBUoZ3H6ZeUq9SLyZ0pjxQKNB99HnGF4FPJaZF0TEjsC3IuLfmXlGZj4VEdcCb+iwY3iOMp7uCErp21aZeXtE/JjSy7ldlCn3f5+ZH28y0MFWS8dXB9aKiPdk5nERcR6wdf38+VP9exxDGY98PvBUh3/eJnBvZv4H+H1EPAxsAyybmb9vNrT/r5a6T8jML1Cuc95MacDMWhb7RJQJta6oja4f7eTff0S8mTIM5l1109HAncCqtQH5zCyTa51EaWC+FxqdP2F6plBmt/0yJanqqvNCROxMacj5J6X89VfAppTE9v7MvDszj69lvN+IiE2zzCMxLPT5XNoaWI7Sw3slpfLwHRFxKmUG3ecpJfNzxORwiEXEGsBtlJ6y1SgXektSSuJ+HRHbZeYNvft34EllttQLwGcp5QuX156PZSmlmg9GxMn1A6+tIuI1lEHMH6T0XO6SmdcA18RLs13+J8oYgieAfbMMQO8IUWZS/S6lRXZpYHJmviEidqMkRQtTPpTvopRcXtOJicSs6nNy3AdYFrg6M8+qieEngafrBf2alIaJZxoKd5a0HNcHKL0ED9dGivdRxpGeHBFPU07872gqzhnp8/58jHIBu3xEHE8pyTyBksSPyczjMvOu5qKdvj7HsDXwZETcQakiOIQy8H/ezDw5Mx9uMNT/ERELZeaTWcag3QY8TCmh3L42GN0YEVMoJXwbRcQVw+ziaUSWMcbnRMQylAlQnsjM70WZAO5tZbf4Y2b+OCJ+2cTnz0DVZPZNlAvi0RGxf/2buyEiHqP0xv+10SBb1IvyeSizeG4eEaOzjNV/Y5Qxn9+mlDFeQUlONqrfO1ZELEYp359YG7jnyzLm86Sa4O4M7BwRi1DK/D7TaY2RUSbKmh94inI+uIcyZr1rzgtR5uB4N6XK5O8R8W5KL+iNlOvqRaLMTro7ZWjW6Z12DHOq5XPpYMo1wHWUhpe/UDoJVgZ+Rpkw7eDMfHJOX7OjekSGm4h4PWXQ8tKZ2UNJlM6pb9zplN//Es1FOHjqhwMRsUaUqYUXogzMHhsRO9XdrqecnHYCmpoVa1HgrMy8iHIBtXNEfDUivkmZaexyyknmnZTEqpMSw5GU5OELmXkgpaVy7Yg4NTN/Slk3c+OI+AllfMoVmfnv5iIePC0nxw9SPiieAo6KiM9S3rMjKX9XW1Fq7qd2U0NLlDLLiZQlErajNNx9n/Lh923KWMrdM/PGxoKcgZb3ZzNKA8uOlDFHK1Em2rqUUsb0+ujwNeZq78fWWSZpeJ4ybuqhWu3weUov6EKdcgxRlgi5PCJeWy/Kn6BcOJxISSI+WHedShnzdcIwvHjqnbnvYMp5YCFKmd87M/NblAvjA4GN6/4dlRi2fH72/k39l9IjMIXSQLRZRJwQZXKnTSgNLh0jiymUSWYOo/TeHl0f+yplKZ5PRcTXKMNM5s2yRE8ne4yylNU9EfEK4OcRcWJE/BL4PeXabmVKyfyvOzAx3JEygdm7KBVQb6X8bxxPd50XXqDMJ/AygMw8nvJ/cS9wPqWh4QeUydvm7bT/7cESZRK+zSnVKvtR5slYHLi79vbuTRk/ev1gvJ49h0MkSn30p4DDMvOOuvkWSvf9oZRenne09hp2s8zM2vX/KcoH8VhKS8aDwMQoUyavQVnC44OU8p+bGwj1ceBjETGNUrL3Hcpg/wOBkzJz/4j4OeWQHmsgvunKzKkRcV3L/ScpyeCfIuKbmfmRiLiTcrL8fCf1bMyuPj1SawNrUyZneS+ltXZpymxl36YkxPNl5lPNRDtwrcdVPU6ZnOlhgMzcPSIuAd6emZPaH+HA1Jbp72XmJnXT/MDD9ULx6lo9cA6l/OUc4MJOe39qb+aUlk1PA3+s5+lFKR+4GRHrZeYvI+L3nXIhGBErUJYFeJBSsv/1iLguM5+NiL9QJgHZPiJ+S1lXdrvhcF7oT72A3wN4PaUc802UNc+eyszvRCm178hxSC3ngoUp54JbgVcBB9TezxuBD1Amrtu1U3veKb2Ha1ImoDkmytjvpzLz7RHxJGVG6U2ys0qx/5+WntAnKb1UK1ImNjqdMpHgbygNkZcBXxqMnprBVCufvkSpfPpbrSyaUCttrqI0nnTFeSFLKfLplEa55SjXjs9QxnW+gpL0rgd8KsvyFsNCrYZonV3+Ccr7thNwYmb+Nkol3NsojRP/GtQAsgNm3hkuX9QZ7OrtbSg9OacBo+q23vX9zqT0EDQe8xwe78je78DLKYOE56NM834t5eS6AKU+emdKK9sESpntCk29P5SW120pLWW9j61MaWkf2fTvtZ+4X9lyex9KOUXr7I9LUFpmV213bEN83CNabu9BGa+7HGXGzovr9v3q39Nhvf9n3fRFWTZlJKUn/TLKB3jvY1+grN3UeJwzOYbfA5fW20vUc96WlEQdSovuDk3HOZ3Y56c0Eq1KmUH5YMpF+W/r+zGm7vcByjiX+ZuOuU/8LwdeX29/FjgP2ACYp26bh9J7exBdNmvvAI699fN2NKVn4VZgjbptIUo58zXA3k3HO4Dj2aD+3W1T769GmRlzrf6OuRO/6v/Tl+vtPSgNLed3S/z9HM9WwAOUpVCWaNl+GrBg0/HNIO5NgPe03F+FUob8inp/dDedFyiNJntT5ur4Zsv2X/V+zgynr97zd729ess5bR/KePLt6/29KD2I8wx2DJaVDqLMzIjYJCIOz8zfUMaoPAt8OCJGZuYtmXkipXb6l51SljSroliCMqHL8vnSYq83UabYfhdlBr/nKD09D2XmLyit2F8E3poNtHzW92dEZv6ZUuK6RkS8oT68GeXDeP52xzUjtTTk+og4EyAzf0RJBP8UZVFusrT4TaG0yg4b+VKp2OspJZe3Z5mB62WUch8oLYh/Bk7OMuaoo0XEq1tuH0LpXf8aJUk8EvhuRHwiIj5PaVC5pok4Z6aeA0YCZOaWlPGel9W/xT9Rlqk4Iso4yrdQJkzqOFl6AO+ijN34MmWa/ZsoZXvXAJ+sx/Auyqy4ndJj+EqAzLyHci4jyyQgV1GWO1i77rpKZt6Zmd/PLpi1d6D6VBRMpHze3E+5aD8wyhqAT1J64y+lVId0un9T4v9MlBkwd6GMLVqmd4feY+5gI4FlI+JTlMatD1PGhH0ZuiL+F9VrhYspnz2bUHqh542IvSlVUJ06oyf1Gufsum0k5W/rAUqpLMDy3XReyMwnMvN04J2Z+RGAKOt7LswwGx4XZZbld9XbB1E6ky6qn0OXU659Ph4RP6U0CH6/XmsPrqYz5OHwxUs9UptSpph+mNLFDWVSg+9RptTuuF6pOTzuoykXVuPq/WMpg53Xrfe3pJSYtvZ8LdXk+8T/9kbtQEkujqeU/K7Z9O+0T7zzU3pjDwROBc5oeeyLlAufd1NKeTtqrbVBOv4RlMVcpwGHtryHC1BmLbuQMltpR71vMzmmSymzrL62xr8jpSzwYkrr7tqU1tyvAas1He90jqG1x6a1Nf0XwG/q7Y0pH1zfprZ6dtJXn/PAqyllrzcDa9dti1BK4A+ntNR2zN9Y/Zt5ps/5oLWl+TOUSamOquffxs65bfhdHEjLWpmUSZs+U8+HX6dM5d4VFRW8VInzCsrM5hfUc991lESko3vdWuLfv/7ed6n3V6AL1jHscyxBy/UapWrlLF5aB7Cj1pWsMfaeF85s2da7ruEISi/bQpS5Cn4JLNp0zHNwrPvX//HxTccyBMe2B+Wa9JOUuQZGUjourqYMpxlLqTTakiFcx7E3qdEciogJlBlID6TUcE+kTAjyySgzTO5CWcKho9b0mlVRZoI7mlLL/t/aIrgPsD7lQ+0gSm/pHZTFej+WmefXntOp03veIYizb71262ObAB/MzD2jLAuxIHBHduA4jigzvD5JOSEcBzyfmXvVx3ah9KKtD3w7O3SyklnRz1g8oqy79E5K8vtE3bYQ5eR4XXb+xAYv/j1GmTnxF5T37buZOakey16U3rbDs7T6dryIeB/lomkycG5m/iUifkW5INm27jMqO6xHt0+v09soDVp3U0rNPwt8ODMvruM5rs8Omu03Iuan9AicQ+nNGJWZ+9THXhw7WcervpKyXEhPQ+EOmVp1szBlGaLPZZlxuvexMZRKkCWBqzLz9mai7F+fv7/5MvOZlsc2oyT6v6v396Icwx39P1v71fPVfFnWVVuR8v8/JTOz9lxtCvwxy1IJHb801wCuFQ7OMgZ8cUrytWBmPtjWIGdiJueF3iWQfkwZt7YOZSx7R1ZzDEQdXzy6k/4v5lTr32GUJVR2opT+viUzH6tVRycDF2TmkK/PanI4SOqF+pqZeWT9Z1yJUv73o8w8KiIW7r2w7XYRcQGlZe0tWSY++Aplhs/1Kb1db6zfr8nMS9v9ARERi2adTCYi3knpaXokM38YEctTxkgdnJkXtCumwVA/nE4AnsvMvaIs2/BUNyRHA9Hnomk7SuvYNZl5XUR8EXg7sH526MD56elzXAtRZlr9BeXDbfu6fQFKa+gbKC2Hz07vgqUT1KTqvZRYL6GsMfmJ+thlwH8zc9tOvjiMiPdTpnDfKTP/UbftS5mR9BxK4rtbdtjkGf00GD3beyFYH38lpZfjHZn5t2aiHHx9/5Zqgngi5TP2D72P16T+xuzMmRdfFBEfppzjPpuZT0eZ3Oks4KOZeW6z0fUvylqSm1MaHlYBlqcu9xRl+Y2jgIMy86rmohy4AVwrXExpLLqgk89lMKDzwi8o79sumdmREzPNrfpcI2xOqTDajtLxcjnl8/WhKJPyfYcyNOuRIY2pg//WO1o/H1S7UsasbNx78RplKucNKbNgntBMpIOntfcvIs6ijHF7U/1g+CplbNHrs4wLayK+oExYcimlJ2Z+ynIAP6S0lv0zMw+LiDUy8+ZOP9n3J8pYz69RWgdHApvnMJqhCyAiPkJ5/3ooY/H+Vd+3L1Jmul0hO2wm2YGoYwbWovSuT6NMPnFXlmmpe1t/R2fm440FOQARMYKyXuufKCVj+1ImnHk+ykLKz0UZizy4s6cNoohYhTLz4O6ZeXdE7ECZvOUKyoQ0u1HGHzYxo/KAtTQY/Tcz94mIdSilY3/vtkaUGelz8bQS8GBmPhURn6Nc8H4gMx+JiN0pk1S9rZPPEVFm734XJc5/1m3vAm5rokF1IFqS71Upa+iuDLwrM8+vj38N+Gtm/rQT42813K8V+jkvrEr5v/hRN/cYDndRxhgeSLmuvici9qBc691CWQbvgd7P2CGPpYv+3jtC3zKQPo8dSRnHtjulbOxQymLlYzPziPZFOfhaPhgWzLqOTEScQpktb4eaIH6bcqJ9OfBCtrGMtE+MH6JcgP8BODYzr4+INSkD5G/NzE+17t/OGAdDbXE+lLLezbApGasf2PNSLtr3r6UU61P+n67PzDNqL/UPuq2cJMpU4p8EduxtPKmt8BdSen/f0mR8syrKpAwfp0w2tXXddgilnOkrjQbXj34a85akjCecr25aGniOUh57anRgOez0tDQYbUxpMHp9DpP1Tfuqvb17UCYQeigzvxoR36f0wD1H+ex5V3b4ElER8SXgz1mGXMyXmc+066JvdvRT/fAmyhIPd1FmKv5Lg+HNsrnhWqHlvLBp3TSh06og9JJ6rXMCJTH8d8v23SjVeH+ilJVmO/4Wh9UsP0MtyixCJ9fW2d5tI+r3JSjdvT+p34+iXMBPpiwIO7pe/HaleiLdBjg6Ir4VEdvWHo87gXMjYmxmHgxslplTGkgMF6CMHQQ4hrL23Y6UUlcoLS+fBdaNiCOgu2ZO6xURi1JOFNsMh8QwIpaIMkYIYMPa8LIcZYwuWcYSTaaMLyQzD+2GxLD3f733/EBZ++tHmXlfPReMrsnHG+t+yzYU6gzVC8He2ztExK411t9RLgx/HhErRMSelKnGf9lMpNPX58J27SjlYg9TSkf/Dnw9M3egTDTxmvpjbT1/zYnaQ3gDZRKdtwzjxPBtlMTwLZTG132jrO96EGVWzG9Ryq06KjGczuf+UpRlEmhpbN4qIpZqW2CzoOX/533AMVlmjvweZRHuHSNipYjYNiK2bDnndaSIWJiXGoWG7bVCy3lhIcr/hYlhB+nnvDAGuKf3/B1lfgIy86eUBvPzM3Nau/4WR7XjRYaDiFiNMqD3eMpkK62TTCxPmVXoK5n5pZqoTKPMSPhZygd2x0xqMDuiTNxyAqWsb33gjRHxysx8V5RF4y+MiK0os0e2O7YVKB+0o2uPwBszc+N6+7CIuCUz/xQRt1AuIjpqEe5ZUXvT3pSZzzYdyyB5HbB7RFxbv29KKc/eNiIezszzgIco7+1Y6sQHDcY7U31amccB9wD/oiydMn/W5RCilKLf2qm9hhGxBjAxIiZRWp8/QSmFPZqyJtsXKeWXP6BMQjWxE0uWWi5sP0BJYP9E6Sk8IDN/Xx/bB9iTUvnQVReDw63BqD/1QukpSmK4O+X9extwbEScALw7O3Cytz4NE28EXqCczw4DLo6ITwJfpfztfYYyu3lHiTqcJCLeTSlN7P0fualWC32AcgybUHqtO3asdLUtsGRELMYwvlaYG84L3arPeWEzylrNNwILR8S+mfnDLMM03ktZDeBTbQ8yO2Dq1k7/ogzwvYAyrqF1+5r1+zeA9/Z5bFHKmn8dMwX6HP4O9gSOqLfnpXyI/QhYuG5br6G4tqX0YqxHmfL7QWCDlsffTekd2KLp36Ff//O+tS6HcBHwX+piz5RZb99R37fTKQ0Or2465tk4xvdTJmsZQ2koOp8y6cymlB6Qv9HBU7xTemdOopQmnUhZGwtKeey/eWlB5UXosMXha1yLttzejZIULkRZ4uBOylqG89a/t0nd+DfWcnxjm46hDcc4hjI27MfAy+u2UymTuCzTdHwzif2DlEXIjwZ+QylpfhmlPHYSdaxr03H2ibl1Car5KT2F61LGGr6f0iu1c/0fWruTz2X1GN5EGec5X/1smTzcrxXmhvNCN3/V88L11GXIKDOWn1Q/b98LXNvUecExhzPRUpt+DOXEfhtlcfvxwPaU3rSjM3Ny6/71dteMW+mr5bhXpCy6uS7lw2GfzLy+7nMh8LXM/ENDMW5DabFcglIi9hfK5BiXUkr47q37vYcyyHfT7PAZ7OYGff5HVqeU8m1NWex5n6zThEfEy+q2B7OhSY5mV0TsR53NM1+acGIjSpKyPOUC5RPZgS26veUu9f9/UUqPxkaUpOrndfsnKOv/rZGZtzUXbf/queFLwCcz8zdRZoKcDLwZeCvlQvFCSsKxBWWspOeGDlT/HiNLlc68lEaWUynv3W6Uc8ZDDYY4XTX2RYGfUnrW762lo6dTetx/QZkIaXR20AQ6EbEjZYjMLzLzbXXbocDBlET2YuBpyhJDu3Tq779Xy7XCJzLzV/WaYGfKWMMfZ508y2sFtUv9mzyKMqngk7U6cRlKw+s7KcuO/CIzb2oivo6uDW9aLTU4tJaz3U85mfdQ1lC6sn7fnpKQAP9bjtStiSG8eGH4ZuA0yiD/KykfyO+JiM3rRf3LKCUybRcRW1PGC+wNrEhpzfw7pdRoAvDuOrZrH0pL7es92XeGlsTww5TxHr/OzImU0sufRsTImlztmJnXdWFiGJSyt08BS0fEIRFxJ6WB5XDK9NRv69TEMKuImEiZXfWLwFWU3vn1ATLzy8BHm4t0plajLG7/0VqGfS3wAOUYvpRlPcA/A/+h9Dp5bugAreNwImI+qLMvlMRwArAG8BXK5+6uwKGdlpj0GUs0hrI23mjqOLfa+HUapWHlucx8qsMSw/kpPYMHA89FxI8Bskw0tStljbzvU8YcT6lfHSvKWoU/BA6sieH8lN7md1MahvaJiDFeK2go9TPGcDKl6u2TEXEUpSLi3cCymfnxzDyyqcQQHHM4M6sDq1LWxPtCRFxEGUN0HrWlOSK+S7kQHFYiYjxlvOS7ey9io6yTszWlBe5h4MhsbuH1kZQPqZvq2IE7KbNxXV/rtI+hjA/dAdgy6wyr6gy1ZXpvypiPhwAy84CIOJFSwr1cfbzjRVmc9uneHsKaWE2mlGPeTek1eB/wEeA3WdbU68hZCfsk7rsB78kyzvXLwKeBnWtFxF8y81tNxjoTZ1DWmv0XsF+UGSHPqh/Qr68XjJtSenY7KrmYm/X5+xsXEa1rAJ4CfCwzfx5lLc2sSX7H6FMVsS8wb2aeEBF/As6IiO1rcrg4sEqUGYuntjYqN63+vvenrJl3DnBcRJyRmXtl5p8AIuKjlIbY/TLzyQbDHYhHgOeBZaJMHPhTytjPOyil5ltQ1mzcEa8VNAT6nBdeSfl7fJTSwLIR5Xr165SqxGUaCvN/WFY6A3UQ/FrAROA+4HtZJ5Ooj29C6U08ODN/20yUQyMiNgQ+lJl7R58ptmtpz+jaFd7oFM/x0qRA21F6NrfPsmj6YpTE/r4cZusADge1fGflzPxYvUCKrJM21ZPn473lpZ0sIrYAjqTMrvpQ/VvsLclevm57tmW/nTv9uGrZ2ymURdQfijKz6vMRsTSlDOZu4MsdeGG+FkBm3hBlxsQvUy7Cz6JMmvEt4J+Ukp1VKT2Iw2aR+OEiunANwL6iLLmxH7BXb9l1RBxGKVn8OWWB612zw9fRhH7XzFuD0oP408y8pdnoBibK4uE/p5Twfo6yJMABlOFBxwALAPd7raChFBEfo3SwjKSUZx+bL81Ouitloqq3ZQcM1bDnsI+oY+wy84l6QfQ3yvpRjwELRMTXKa3++1EuOD423BLDKoEFI2LJ3pb1KDNJrgmc2lt20fSHdNaZ0TLz11Fmrds+Inoy81FKKawaNp2LuXspU4UvnpmP1P32oFyAnNf2IGdD7YXanFJqviKwfkT8Lssi8BsDz2Xmv6KspfV2Sit7xyWG/bw/SamQWJVSNt5bHj+CUm62QAcmhotTBvbfV3ud7qaU9X6HEvePKT23x2Xmp6POwNhUvJqhVShVKf+Ml9YVnpQdugYg/L+egWUos6q+GXgsyjIvG1Imrvsdpbz0+9mBs6v2JzMfiTJT6dci4lYgKEtW3d9waAOWmX+r1SpbZuaJdfMPIuI3lCqwqxsMT8NUn/PCG4CtMnPbeq36auD+KEt5bUaZo2C/TkgMwTGH/VkZuLulPvhnwOWUC42xwIcoF089lKnQz++nlrjrZeZVlAv4kyJizygLcU4C7s7OXZbjb5Spmzu6VXlu0ufkuE9EfCgiDqLMdLcU8M6I2L2WYH2OMp1zV6jHdQTlIvCXlMWgn4uy7MsZvFRu/jdK+WJHrb8G/+/9WTDKUhsPAWcCm0XEmrUXdB9KlURkB66XVRsYtqaUI69F6Zk5jTLea8nMPJNSIvf2iFiQstSQGjadz84ZrgHYdINkX33+h5bIMjndVZTxa8cAr6+7HgFcl5mXdUti2CtfWjNvYcqaeV2TGPbKzL9n5vd670fEWymVBQ83F5WGqz7nhSUpVSsXRcTnKPN47FE7N15J6UXcPTtoHgLLSvtRSxSPoUyh/5fMPLxu34pSTvEA8PlO+5AaDC1lmgtQSi32pnxYL09pvb2o0QBnIiJ+Anw8M+9qOha9pJaKHUyZQfJQymx9f6aM91iJ0pre5BjWAWspGx1FmZTpQsoYgp9k5lci4oPALZn5m0YDnQV1DNH6lOTqA5Syl50p43D+DGxDKYntuHUMW9Vz9MmUiWd2pYyL+hdlCZExAI4p6gx9Lp5a1wD8F2U2zLPoswZg1lklO1FEHEKZp+AwSnXRbpQxxvfWRORNlAblruuxjjJr8U+AQzqxkWtW1AaJ/SgTau2WDU76oeGnt8Gr5dz2LuAgyvXPpynnubdk5jO1oXxXyuR7T/f/jM0wOZyOepFxEWVsXba0cG4JTO70i6SBaLnIXYnS2/ZA/YNditLy+ZHMPLvuO6bTSsladcM4lLlVbWg4CTg5My+KiEUovdDXZebn6j7zZhfMENfngnaRzHy83l6K0jP1yyyz+hEdONlEf+oH1FsoCeAfKCWlEylLw2xIWRvw5m5pcKmJxleAjTPzqYhYMevYNXWe2piyD2UYwGqUSUKOpyzzcCulZf2dnXwRXy8A96UkGw/UUrGslQQHUZKR/TqpZ2BWRcTYzHy26TjmVL2Wez1ljGFXjJlU94iWJexqHvEFyvjiyRFxBGXCmVvr7vsCe3biuc0xh9ORmRdHWcrhtojYuJZVQGnRHBZqYrgzpQXtbuDJWgs9AfhCb2JYdex4D+i8UqO5WUSsSinXmQ+4PjMfjbKUw0oRsUBmPl4vCI+t95/qhsQQ/qc18BBgm4hYjtJTdRxlEo3jI2KpzDwkO3Qpmzo+b1q+NH3+aOAdlJbN+6nrm1HWZTu/gRDnSGZeWNvyroqITfOlSU1sQOog9SJ9UWAnSkt66xqAN1PG4XTcGoAAEbF0n/LqlSllzMtFxN6Uscg3RsSplOqCd3RDVcSMDIfEEF48h1/SdBwafuq4wv2jzFVyOzCVMk/HLsAxWca77wssSynR3q1TGyhMDmegXmRMBW6KiNU77QNqTkXEKpQLwm0oE03sQlkr8K7eY+0tM/WiSgMRETtQ1sW7m1KWvEZEbEvpid4LuDkirgE2oFz4dWQC1VefHsPtgd0p49peSSl5IzO/GWWWwq/UsUcdN5al9qp9DrgrIu7IzE8C3wVeQVn25c21t+1twMERcXG3JO6t6rl7NPC7iNiAulxe03HN7fok6P2uARgRvWsA/oQObJSMssbv3yPiO5Ty8eMpcxBsT+khnAScDaxNWcvs8Dq2SNIwVYejfYGypuZSlOuD0ynX1vtExEOZ+dPM/GHdf0QnnxdMDmeilsHtTznRX9JwOINtDKV0bC/K+KJ9M3NKRIyPiOsz84VO/uNVZ6knx88AH87MS+u2z1HWBd2akgy+k7KWz6LA+7qhNbqfgeUPU8osHwOujDJF/UURcVVmXh4RO2UHzqxY359PUpbUuBs4pLecNyLupSzX89Yoy0DcTKke6LrEsFdmnluTW89hHaDP/1FXrgFYPUUZh3s/5f9lXUo59pFZl6aoFTlbUJZ8cYyrNIxFWTrtQmCnzPxlRLycMl56wcw8vXYy7R1lWagf1x/rtPPa/zA5HIDMvAC6vyypZYxh79iBOyg9BjtSurfvqL08X6SMQXLNHw1Iy8nxzVnWIhubmc9m5udqsvEryiySv6f0KD6THT7j3QwGln8MmCciVqP0st8YEWdRT/Ydmhj2vj9vrUnThpSE/ev1IvyDlAvcCZSle3bPzLsbC3iQZOZTTcegouX/6MU1AOv2T0TEE8BfIqJ1DcCOrCqo5a9/pUx69EZKFcGewEH12Lau9/fJugyUpOGrDp15E/DViLg0M++pCeGydZcLKZ0xb46I8+pQmo7OJZyQZi5Tx1HuSrmQPYDywbYFpTfkFspMkh/vxrFGalYtKT0K2DzL2lgvTmIUEZdSehSvbTTIWTCTgeXfBeYFbqLMVHow8Ibs4Elb6vtzBGV84dcpvR8nUkrgbsjMd9b9FsuyTqg0x/r0GC5DKbXal7J28Jt5aQ3AZSjlpfdmhy710NLAOg9ljOHBlBlKT6YsXbEsZcbfd2QXTz4jadbVISffpUxmuSywd2/1TZSJ+UZk5pMNhjhgJodzgZYPtKUoPTiHAQcC81NmiVuTkiDOA1yWmb/t9l5SNaOeHL8HbJCZj9Uyiucj4lzgU90yKUPvwHLKGoW9A8tPoRzDMXWfAymTTawIfLW3pKyT1dLSC4FPZuZRddsClNLfPezp0GDqkxgukZkPR8RXKNUqVwH/rV+LUmYk7fhlHmpFwWhKCf1KlCVgDsvMX0TEisATNq5Ic6eI2JrSUPSyOoa6K2Zi78vkcC4RERtRpqTfMDOPqNtOo4zv2Ld2i3f0AFl1h34SxLdTyjHfVMcUdbR+Bpa/jNLbsRylMeXkzPxpy/6jM/P5JmKdHTXx/R7w2iwzx+5HmWl1W8dHaSjEMFwDsJaVXwp8PzO/2HQ8kjpDvQb6OrBFN1zz9Mcxh8NYS4/hxsBPgWspywnclpk/ycy317FS50XE5pTeEWmOZOav6tibyyLiGEoJ2QHdcJKczYHlHTk2anpqZcDBwB/r+7MncKCJoYZCHau7E2Vc+yNR1gD8Uf7/NQC76vMnM2+tk1GtEBHzZeYzTcckqXn1Gmge4NfRpbNlmxwOYzUxnEAZ17EHcAVlnOFWETE1M8/OzD0iYq1OHfyv7lRPjiMpC8Ovmx24yGt/huPA8v506/ujzhdz1xqAf6FM3iZJL8ouny3bstJhqqXX8IvAhyilo+dGWbR7e8oH9HlZ1pKShkS3tqgPp4HlM9Kt7486U9Q1AIEX1wCsCeH2lLG5k4AplKWhDgee7taLp17+D0kabkwOh5mWpHDJ3sklIuLDwETKMgP3RMQ4yoLXf3ZGNal/w2VgudQu9bPlTOCXwFbAnZQlUm7I/10D8HBgGydAkqTOY3I4DNVejw8DDwL/AL5MWcdsd8r6ZXe2LjMgqX/DYWC51E4R8U3K5E17Uz5zdqNMfNa6BuB+ljJLUmcyORwGImJZYExm/rOW9ZxPGeS/IPAaYJXM3DcivgZsA7wWmNKNY6WkdouInSg9HV05sFxqB9cAlKThweSwy9Vk8Gzg85Q1DFcDDsrM/SJiBOUD+QjgpMy8PCLW6Ib12KROEhELZOZTTcchdTLXAJSk7jei6QA0+yJiBeBnwDfr0hT/Ae4BJkTErpk5LTPvpSwyvHr9sVubiVbqXiaG0sxl8RzwI8qYw9Mz8xf1sX+aGEpS53Mpi+62BXBxZp5UewnXBV4B/Bj4aEQsDNwGbEIp86HbZ4aTJHU21wCUpO5lctjd7gTeGRHbUtYxnBdYizK+Ywxl8fE7gMMz84rGopQkzW1cA1CSupBjDrtYRMwHHAi8g5IEfge4kdJ7+Hbgs73lcL2TBTQUqiRpLmOvoSR1H5PDYSAiFmsdyxERmwNfAt4K3G9SKEmSJGlmLCsdBnoTw4gYDbyBsq7hJzNzcqOBSZIkSeoazlY6TNTEcEPgI8CnM/OChkOSJEmS1EUsKx1GaoK4eGbe7xhDSZIkSbPC5FCSJEmSZFmpJEmSJMnkUJIkSZKEyaEkSZIkCZNDSZIkSRImh5IkzbKIeEdEfG+Qn3PniFiz5f4XImLrwXwNSZJmxORQkqTOsDPwYnKYmZ/NzN81F44kaW5jcihJUh8RsU9E/DUiro+I4yNiZETsFxG3RcRfgU1b9j01InZtuf9Uy+1DI6InIv4WEUfVbe+KiKvqtrMjYr6I2AR4M/C1+portz5vRGwVEdfV5zo5IsbU7XdFxOcj4tr62Opt+hVJkoYhk0NJklpExBrAHsCmmbkOMBXYB/g8JSl8HS09fDN4nu2BnYDXZubawFfrQ+dk5mvqtpuBAzLzz8B5wMcyc53M/EfL84wFTgX2yMzxwCjgvS0v9XBmrgccC3x0tg9ckjTXMzmUJOl/bQWsD1wVEdfX+x8GLsnMhzLzOeCsATzP1sApmfkMQGY+Wre/OiIuj4geYG/gVTN5ntWAf2bmbfX+JGCzlsfPqd+vAVYYQFySJPXL5FCSpP8VwKTag7dOZq4GfG4G+79A/TyNiBHAPDN5/lOB99dewM8DY+cw3in1+1RKr6IkSbPF5FCSpP91MbBrRCwFEBGLAdcBr4+IxSNiNLBby/53UXoaoYwbHF1v/xbYLyLma3kegAWByfV59m55nv/Ux/q6FVghIlap9/cFLp39w5MkqX8mh5IktcjMvwOfBn4TETdQkrxlKL2HVwB/oowV7PUDSuL4N2Bj4On6PL+mjCO8upan9o4H/AxwZX2eW1qe50zgY3XimZVb4nkW2A/4aS1FnQYcN4iHLEkSAJGZTccgSZIkSWqYPYeSJEmSJJNDSZIkSZLJoSRJkiQJk0NJkiRJEiaHkiRJkiRMDiVJkiRJmBxKkiRJkjA5lCRJkiQB/wd3GP4lHUGU9wAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 1080x1080 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(15,15))\n",
+    "plt.subplot(2,1,1)\n",
+    "df['education'].value_counts().plot.pie(autopct='%1.1f%%')\n",
+    "plt.ylabel('')\n",
+    "plt.subplot(2,1,2)\n",
+    "sns.countplot(x='education',data=df)\n",
+    "plt.xticks(rotation=45)\n",
+    "plt.ylabel('No. of Individuals')\n",
+    "df['education'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Most of the people are high school graduate. There are few who have done masters and doctorate. The no. of people who went through just the preschool or 1st to 4th is the least."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:12.109985Z",
+     "iopub.status.busy": "2021-07-05T16:35:12.109649Z",
+     "iopub.status.idle": "2021-07-05T16:35:12.558681Z",
+     "shell.execute_reply": "2021-07-05T16:35:12.557565Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:12.109951Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "9     10501\n",
+       "10     7291\n",
+       "13     5355\n",
+       "14     1723\n",
+       "11     1382\n",
+       "7      1175\n",
+       "12     1067\n",
+       "6       933\n",
+       "4       646\n",
+       "15      576\n",
+       "5       514\n",
+       "8       433\n",
+       "16      413\n",
+       "3       333\n",
+       "2       168\n",
+       "1        51\n",
+       "Name: education.num, dtype: int64"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x1080 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(15,15))\n",
+    "plt.subplot(2,1,1)\n",
+    "df['education.num'].value_counts().plot.pie(autopct='%1.1f%%')\n",
+    "plt.ylabel('')\n",
+    "plt.subplot(2,1,2)\n",
+    "sns.countplot(x='education.num',data=df)\n",
+    "plt.ylabel('No. of Individuals')\n",
+    "df['education.num'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Majority of individuals lie in the 9th 10th category of education no. which is a liitle higher than the median education number. People with least and highest educations are very few."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:12.560435Z",
+     "iopub.status.busy": "2021-07-05T16:35:12.560166Z",
+     "iopub.status.idle": "2021-07-05T16:35:12.869875Z",
+     "shell.execute_reply": "2021-07-05T16:35:12.868971Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:12.560409Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Married-civ-spouse       14976\n",
+       "Never-married            10683\n",
+       "Divorced                  4443\n",
+       "Separated                 1025\n",
+       "Widowed                    993\n",
+       "Married-spouse-absent      418\n",
+       "Married-AF-spouse           23\n",
+       "Name: marital.status, dtype: int64"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x1080 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(15,15))\n",
+    "plt.subplot(2,1,1)\n",
+    "df['marital.status'].value_counts().plot.pie(autopct='%1.1f%%')\n",
+    "plt.ylabel('')\n",
+    "plt.subplot(2,1,2)\n",
+    "sns.countplot(x='marital.status',data=df)\n",
+    "plt.ylabel('No. of Individuals')\n",
+    "df['marital.status'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Majority of people are married to a civialian spouse or Never married. Least people are married to armed forces. From the above maritial status data we can see that there are less young people in the workforce as compared to young ones."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:12.871334Z",
+     "iopub.status.busy": "2021-07-05T16:35:12.871082Z",
+     "iopub.status.idle": "2021-07-05T16:35:13.433357Z",
+     "shell.execute_reply": "2021-07-05T16:35:13.432594Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:12.871308Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Prof-specialty       4140\n",
+       "Craft-repair         4099\n",
+       "Exec-managerial      4066\n",
+       "Adm-clerical         3770\n",
+       "Sales                3650\n",
+       "Other-service        3295\n",
+       "Machine-op-inspct    2002\n",
+       "?                    1843\n",
+       "Transport-moving     1597\n",
+       "Handlers-cleaners    1370\n",
+       "Farming-fishing       994\n",
+       "Tech-support          928\n",
+       "Protective-serv       649\n",
+       "Priv-house-serv       149\n",
+       "Armed-Forces            9\n",
+       "Name: occupation, dtype: int64"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1440x1080 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(20,15))\n",
+    "plt.subplot(2,1,1)\n",
+    "df['occupation'].value_counts().plot.pie(autopct='%1.1f%%')\n",
+    "plt.ylabel('')\n",
+    "plt.subplot(2,1,2)\n",
+    "sns.countplot(x='occupation',data=df)\n",
+    "plt.xticks(rotation=45)\n",
+    "plt.ylabel('No. of Individuals')\n",
+    "df['occupation'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can observe over here that prof-speciality has the highest number for people than any other occupation. followed by craft repair persons. Minimum occupation category is the armed forces with only 9 people in it. There is an unknown category of occupation too."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:13.434688Z",
+     "iopub.status.busy": "2021-07-05T16:35:13.434305Z",
+     "iopub.status.idle": "2021-07-05T16:35:13.709834Z",
+     "shell.execute_reply": "2021-07-05T16:35:13.709127Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:13.434658Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Husband           13193\n",
+       "Not-in-family      8305\n",
+       "Own-child          5068\n",
+       "Unmarried          3446\n",
+       "Wife               1568\n",
+       "Other-relative      981\n",
+       "Name: relationship, dtype: int64"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1440x576 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(20,8))\n",
+    "plt.subplot(1,2,1)\n",
+    "df['relationship'].value_counts().plot.pie(autopct='%1.1f%%')\n",
+    "plt.ylabel('')\n",
+    "plt.subplot(1,2,2)\n",
+    "sns.countplot(x='relationship',data=df)\n",
+    "plt.ylabel('No. of Individuals')\n",
+    "df['relationship'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There are much more husband working than their wives. There are 25% individuals working who fall in not in family category."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:14.808243Z",
+     "iopub.status.busy": "2021-07-05T16:35:14.807932Z",
+     "iopub.status.idle": "2021-07-05T16:35:15.255826Z",
+     "shell.execute_reply": "2021-07-05T16:35:15.255091Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:14.808215Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "White                 27816\n",
+       "Black                  3124\n",
+       "Asian-Pac-Islander     1039\n",
+       "Amer-Indian-Eskimo      311\n",
+       "Other                   271\n",
+       "Name: race, dtype: int64"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1440x576 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(20,8))\n",
+    "plt.subplot(1,2,1)\n",
+    "df['race'].value_counts().plot.pie(autopct='%1.1f%%')\n",
+    "plt.subplot(1,2,2)\n",
+    "sns.countplot(x='race',data=df)\n",
+    "plt.xticks(rotation=45)\n",
+    "plt.ylabel('No. of Individuals')\n",
+    "df['race'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "SInce this is from european countries, most of the individuals working here are white. There is also an other category where minory races are present."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:15.348302Z",
+     "iopub.status.busy": "2021-07-05T16:35:15.347799Z",
+     "iopub.status.idle": "2021-07-05T16:35:15.540302Z",
+     "shell.execute_reply": "2021-07-05T16:35:15.539609Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:15.34827Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Male      21790\n",
+       "Female    10771\n",
+       "Name: sex, dtype: int64"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x504 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(15,7))\n",
+    "plt.subplot(1,2,1)\n",
+    "df['sex'].value_counts().plot.pie(autopct='%1.1f%%')\n",
+    "plt.subplot(1,2,2)\n",
+    "sns.countplot(x='sex',data=df)\n",
+    "plt.ylabel('No. of Individuals')\n",
+    "df['sex'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There is more than double the number of men working than the no. of women."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:15.542072Z",
+     "iopub.status.busy": "2021-07-05T16:35:15.541542Z",
+     "iopub.status.idle": "2021-07-05T16:35:16.01881Z",
+     "shell.execute_reply": "2021-07-05T16:35:16.017828Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:15.542025Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "United-States                 29170\n",
+       "Mexico                          643\n",
+       "?                               583\n",
+       "Philippines                     198\n",
+       "Germany                         137\n",
+       "Canada                          121\n",
+       "Puerto-Rico                     114\n",
+       "El-Salvador                     106\n",
+       "India                           100\n",
+       "Cuba                             95\n",
+       "England                          90\n",
+       "Jamaica                          81\n",
+       "South                            80\n",
+       "China                            75\n",
+       "Italy                            73\n",
+       "Dominican-Republic               70\n",
+       "Vietnam                          67\n",
+       "Guatemala                        64\n",
+       "Japan                            62\n",
+       "Poland                           60\n",
+       "Columbia                         59\n",
+       "Taiwan                           51\n",
+       "Haiti                            44\n",
+       "Iran                             43\n",
+       "Portugal                         37\n",
+       "Nicaragua                        34\n",
+       "Peru                             31\n",
+       "France                           29\n",
+       "Greece                           29\n",
+       "Ecuador                          28\n",
+       "Ireland                          24\n",
+       "Hong                             20\n",
+       "Cambodia                         19\n",
+       "Trinadad&Tobago                  19\n",
+       "Laos                             18\n",
+       "Thailand                         18\n",
+       "Yugoslavia                       16\n",
+       "Outlying-US(Guam-USVI-etc)       14\n",
+       "Honduras                         13\n",
+       "Hungary                          13\n",
+       "Scotland                         12\n",
+       "Holand-Netherlands                1\n",
+       "Name: native.country, dtype: int64"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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GbKojSZIkSVoJWwwOkzw+yeeAY4CrAY82U6kkSZIkrS9bXOcQ2AU4pKpOmXFdJEmSJEkrZLF1DrevqvOBl3bbO4w/XlU/m3HdJEmSJEnLZLGew3fR1jg8ESggY48VcL0Z1kuSJEmStIwWW+fw3t3P3ZavOpIkSZKklbDYsNK9FnthVZ00fHUkSZIkSSthsWGlL+t+bgfsA3yVNrR0T2ADcJvZVk2SJEmStFw2u5RFVe1XVfsBPwL2qqp9qmpv4BbAD5argpIkSZKk2dviOofAjarqtNFGVX0N+NPZVUmSJEmStNyWEhyemuSNSe7U3d4AnLqlFyU5LMk5Sb42tu/QJD9Ickp3u9fYY/+Q5KwkZya5+9j+e3T7zkryrLH9uyX5Srf/PUm2XfrbliRJkiSNW0pweCBwOnBwd/t6t29L3gLcY4H9r6iqm3e3IwGS7AH8NfBn3Wv+K8nWSbYGXgPcE9gDeGj3XIB/68q6AfBz4KAl1EmSJEmStIDFEtIAUFW/A17R3Zasqo5LsusSn74/cHhVXQh8J8lZwK26x86qqm8DJDkc2D/JN4A7A3/TPeetwKHAayepoyRJkiSp2WLPYZLbJTk6yf8m+fboNsXvfGKSU7thp1ft9l0b+P7Yc87u9m1u/9WAX1TVRfP2b+49PCbJhiQbzj333CmqLkmSJEnr01KGlb4JeDlwe+CWY7c+XgtcH7g5LQvqyxZ99kCq6vVdttV9dtxxx+X4lZIkSZK0pmxxWCnwy6r6xBC/rKp+MrrfJbb5WLf5A2CXsafuzMblMhbafx5wlSTbdL2H48+XJEmSJE1oKT2Hn03y0iS3SbLX6NbnlyW55tjm/YFRJtMjgL9OctkkuwG7A8cDJwC7d5lJt6UlrTmiqgr4LPCg7vUHAB/pUydJkiRJ0tJ6Dm/d/dxnbF/REsJsVpJ3A3cCrp7kbOB5wJ2S3Lx7/XeBxwJU1elJ3kvLhHoR8ISqurgr54nAUcDWwGFVdXr3K54JHJ7kRcDJtOGvkiRJkqQelpKtdL8+BVfVQxfYvdkArqr+GfjnBfYfCRy5wP5vszGjqSRJkiRpCpsNDpM8dbEXVtXLh6+OJEmSJGklLNZzeKVlq4UkSZIkaUVtNjisqucvZ0UkSZIkSStnKdlKJUmSJEnrnMGhJEmSJGnzwWGSg7uft1u+6kiSJEmSVsJiPYcHdj9fvRwVkSRJkiStnMWylX4jyTeBayU5dWx/gKqqPWdbNUmSJEnSclksW+lDk/wJcBRw3+WrkiRJkiRpuS3Wc0hV/Ri4WZJtgRt2u8+sqj/MvGaSJEmSpGWzaHAIkOSOwNuA79KGlO6S5ICqOm7GdZMkSZIkLZMtBofAy4G7VdWZAEluCLwb2HuWFZMkSZIkLZ+lrHN4mVFgCFBV/wtcZnZVkiRJkiQtt6X0HG5I8kbgHd32w4ANs6uSJEmSJGm5LSU4/HvgCcCTu+3PA/81sxpJkiRJkpbdFoPDqrqQNu/w5bOvjiRJkiRpJSxlzqEkSZIkaZ0zOJQkSZIkGRxKkiRJknoGh0keM3RFJEmSJEkrp2/PYQathSRJkiRpRfUKDqvqv4euiCRJkiRp5WwxOEyyc5IPJTk3yTlJPpBk5+WonCRJkiRpeSyl5/DNwBHANYFrAR/t9kmSJEmS1omlBIc7VtWbq+qi7vYWYMcZ10uSJEmStIyWEhyel+ThSbbubg8Hzpt1xSRJkiRJy2cpweGjgAcDPwZ+BDwIOHCWlZIkSZIkLa9ttvSEqvoecN9lqIskSZIkaYVsNjhM8txFXldV9cIZ1EeSJEmStAIW6zn89QL7rgAcBFwNMDiUJEmSpHVis8FhVb1sdD/JlYCDaXMNDwdetrnXSZIkSZLWnkXnHCbZAXgq8DDgrcBeVfXz5aiYJEmSJGn5LDbn8KXAA4DXAzetql8tW60kSZIkSctqsaUsngZcC/hH4IdJzu9uFyQ5f3mqJ0mSJElaDovNOVzKGoiSJEmSpHXAAFCSJEmSZHAoSZIkSTI4lCRJkiRhcChJkiRJwuBQkiRJkoTBoSRJkiQJg0NJkiRJEgaHkiRJkiQMDiVJkiRJGBxKkiRJkjA4lCRJkiRhcChJkiRJwuBQkiRJkoTBoSRJkiQJg0NJkiRJEgaHkiRJkiQMDiVJkiRJGBxKkiRJkjA4lCRJkiRhcChJkiRJwuBQkiRJkoTBoSRJkiQJg0NJkiRJEgaHkiRJkiQMDiVJkiRJGBxKkiRJkjA4lCRJkiQxw+AwyWFJzknytbF9OyQ5Osk3u59X7fYnyX8kOSvJqUn2GnvNAd3zv5nkgLH9eyc5rXvNfyTJrN6LJEmSJK13s+w5fAtwj3n7ngUcU1W7A8d02wD3BHbvbo8BXgstmASeB9wauBXwvFFA2T3n0WOvm/+7JEmSJElLNLPgsKqOA342b/f+wFu7+28F7je2/23VfBm4SpJrAncHjq6qn1XVz4GjgXt0j21fVV+uqgLeNlaWJEmSJGlCyz3ncKeq+lF3/8fATt39awPfH3ve2d2+xfafvcD+BSV5TJINSTace+65070DSZIkSVqHViwhTdfjV8v0u15fVftU1T477rjjcvxKSZIkSVpTljs4/Ek3JJTu5znd/h8Au4w9b+du32L7d15gvyRJkiSph+UODo8ARhlHDwA+Mrb/kV3W0n2BX3bDT48C7pbkql0imrsBR3WPnZ9k3y5L6SPHypIkSZIkTWibWRWc5N3AnYCrJzmblnX0X4H3JjkI+B7w4O7pRwL3As4CfgMcCFBVP0vyQuCE7nkvqKpRkpvH0zKiXg74RHeTJEmSJPUws+Cwqh66mYfussBzC3jCZso5DDhsgf0bgJtMU0dJkiRJUrNiCWkkSZIkSauHwaEkSZIkyeBQkiRJkmRwKEmSJEnC4FCSJEmShMGhJEmSJAmDQ0mSJEkSBoeSJEmSJAwOJUmSJEkYHEqSJEmSMDiUJEmSJGFwKEmSJEnC4FCSJEmShMGhJEmSJAmDQ0mSJEkSBoeSJEmSJAwOJUmSJEkYHEqSJEmSMDiUJEmSJGFwKEmSJEnC4FCSJEmShMGhJEmSJAmDQ0mSJEkSBoeSJEmSJAwOJUmSJEkYHEqSJEmSMDiUJEmSJGFwKEmSJEnC4FCSJEmShMGhJEmSJAmDQ0mSJEkSBoeSJEmSJAwOJUmSJEkYHEqSJEmSMDiUJEmSJGFwKEmSJEnC4FCSJEmShMGhJEmSJAmDQ0mSJEkSBoeSJEmSJAwOJUmSJEkYHEqSJEmSMDiUJEmSJGFwKEmSJEnC4FCSJEmShMGhJEmSJAmDQ0mSJEkSBoeSJEmSJAwOJUmSJEkYHEqSJEmSMDiUJEmSJGFwKEmSJEnC4FCSJEmShMGhJEmSJAmDQ0mSJEkSBoeSJEmSJAwOJUmSJEkYHEqSJEmSMDiUJEmSJGFwKEmSJEnC4FCSJEmShMGhJEmSJIkVCg6TfDfJaUlOSbKh27dDkqOTfLP7edVuf5L8R5KzkpyaZK+xcg7onv/NJAesxHuRJEmSpPVgJXsO96uqm1fVPt32s4Bjqmp34JhuG+CewO7d7THAa6EFk8DzgFsDtwKeNwooJUmSJEmTWU3DSvcH3trdfytwv7H9b6vmy8BVklwTuDtwdFX9rKp+DhwN3GOZ6yxJkiRJ68JKBYcFfCrJiUke0+3bqap+1N3/MbBTd//awPfHXnt2t29z+zeR5DFJNiTZcO655w71HiRJkiRp3dhmhX7v7avqB0muARyd5IzxB6uqktRQv6yqXg+8HmCfffYZrFxJkiRJWi9WpOewqn7Q/TwH+BBtzuBPuuGidD/P6Z7+A2CXsZfv3O3b3H5JkiRJ0oSWPThMcoUkVxrdB+4GfA04AhhlHD0A+Eh3/wjgkV3W0n2BX3bDT48C7pbkql0imrt1+yRJkiRJE1qJYaU7AR9KMvr976qqTyY5AXhvkoOA7wEP7p5/JHAv4CzgN8CBAFX1syQvBE7onveCqvrZ8r0NSZIkSVo/lj04rKpvAzdbYP95wF0W2F/AEzZT1mHAYUPXUZIkSZIubVbTUhaSJEmSpBVicChJkiRJMjiUJEmSJBkcSpIkSZIwOJQkSZIkYXAoSZIkScLgUJIkSZKEwaEkSZIkCYNDSZIkSRIGh5IkSZIkDA4lSZIkSRgcSpIkSZIwOJQkSZIkYXAoSZIkScLgUJIkSZKEwaEkSZIkCYNDSZIkSRIGh5IkSZIkDA4lSZIkSRgcSpIkSZIwOJQkSZIkYXAoSZIkScLgUJIkSZKEwaEkSZIkCYNDSZIkSRIGh5IkSZIkDA4lSZIkSRgcSpIkSZIwOJQkSZIkYXAoSZIkScLgUJIkSZKEwaEkSZIkCYNDSZIkSRIGh5IkSZIkDA4lSZIkSRgcSpIkSZIwOJQkSZIkYXAoSZIkScLgUJIkSZKEwaEkSZIkCYNDSZIkSRIGh5IkSZIkDA4lSZIkSRgcSpIkSZIwOJQkSZIkYXAoSZIkScLgUJIkSZKEwaEkSZIkCYNDSZIkSRIGh5IkSZIkDA4lSZIkSRgcSpIkSZIwOJQkSZIkYXAoSZIkScLgUJIkSZKEwaEkSZIkCdhmpSughf3ktS/u/dqd/v7ZA9ZEkiRJ0qWBweFAzn3d66Z6/Y6Pe9xANZEkSZKkyTmsVJIkSZJkcChJkiRJMjiUJEmSJGFwKEmSJEliHQSHSe6R5MwkZyV51krXR5IkSZLWojWdrTTJ1sBrgLsCZwMnJDmiqr6+sjWTNu/Dh91zqtff71GfGKgm0nTu9aH+S+4AHHl/l92RJGk1WdPBIXAr4Kyq+jZAksOB/QGDwxn65n/uP9Xrd3/iR+Zsn/S6+0xV3l6P++hUr9+So950r6lef/eDjhyoJsvjTW+721SvP+iRn5qz/Z/vvPtU5T3xYUdN9fot+Yf33WOq1//LX31yoJosj3t9uP8AiyPv968D1mRTf/nBV071+o8/4JBB6rFW3fv975vq9R970F8NVBMBPPgDZ0z1+vc+8MYD1WRh//6hH0/1+v93/z8ZqCZrz5ffcs5Ur9/3b68xUE2k4aWqVroOvSV5EHCPqvq7bvsRwK2r6onznvcY4DHd5o2AM5dQ/NWBnw5Y3dVc3mqum+VZnuWt3fJWc90sz/Isb+2Wt5rrZnmWt1bKu25V7Th/51rvOVySqno98PpJXpNkQ1XtM1QdVnN5q7lulmd5lrd2y1vNdbM8y7O8tVveaq6b5VneWi9vrSek+QGwy9j2zt0+SZIkSdIE1npweAKwe5LdkmwL/DVwxArXSZIkSZLWnDU9rLSqLkryROAoYGvgsKo6faDiJxqGusbLW811szzLs7y1W95qrpvlWZ7lrd3yVnPdLM/y1nR5azohjSRJkiRpGGt9WKkkSZIkaQAGh5IkSZIkg0NJkiRJ0hpPSLMaJdkBeBzwO+CNVXX+CldJQJKtgZ0Y+8xX1f+tXI1mq8vee8Nu88yq+sNK1keSpPUsyU2APYDtRvuq6m0rVyOtNkn2WuzxqjppueqyGBPSjElyO+CUqvp1kocDewGvqqrvTVDGZ4H/AS4L3AO4T1V9e8A67gTcsts8vqrOGars9SrJk4DnAT8B/tjtrqrac+VqNdcQn72xsu4EvBX4LhDaWqAHVNVxU9bxGsw96a2a4DrJ9YGzq+rC7v3vCbytqn7Rs7wrA4cCd+h2HQu8oKp+OWE5T13s8ap6eZ/6rWbd9+0dVfXzgcq7aVWdNlBZt6P9X69LaygK7VhwvSnKfMACu38JnNbn+DzksWAtGPqCOskjF9o/ZZlXBXZnbh17HU+TXAH4bVX9sdveCtiuqn4zYTl3rqrPbObzR1V9sEfdtgaeXFWvmPS1i5R5H+Djo/c7UJmDnouGKC/J84A70T7LRwL3BL5QVQ/qWaetaeewh/V5/WbKvDzwNOA6VfXoJLsDN6qqj/Uoa3fgX9j0uzvxsXTo8+Sszrvj390kNwRuDHxiksb3LkaA9jfbB/gq7Ty0J7Chqm7Ts2770K5XrgX8FvgacHTf87A9h3O9FrhZkpvRvkBvBN4G3HGCMq5WVc8GSPIp4Ngkv+jK+7uqenDfyiV5MPBS4HO0D9Orkzy9qt7fo6wb0t7vTlV1kyR7Avetqhf1KGsf4DlsesHVO/hKsiPwTDY98Ny5R3EH0w6A5/Wtz3wD1w+G+eyNvAy4W1Wd2dX1hsC7gb37VCzJfbsyrwWcQ/s/fwP4sz7ldWU+APg34Bq0z8voM7N9zyI/AOyT5Aa0FM4fAd4F3KtneYfRDq6j7+sjgDcDC16ILeJK3c8b0Rp1Ruuw3gc4vmfdRp+/RwO7Mrc3/FETlnMasNkWwp7f4Z2AE5KcRPs7HlXTtUL+V5LLAm8B3jlpgD7Pm4CnACcCF09RzriDgNsAo5P+nbryd0vygqp6+4TlDXksGOxYleSjLP5ZuW+Pui14QU17v33dcuz+dsBdgJP6lpnk72jnkJ2BU4B9aQ3AfY/1xwB/Afyq27488CngthOWc0fgM7RjyXwFTBwcVtXFSR4KDBYcAg8BXpnkA7Tlxs7oW9DQ56KBy3sQcDPg5Ko6sGvIf0efesEl/4vrJtm2qn7ft5x53kw7No0CkB8A7wMmDg67sp5H+6zsBxxI/6lqQ58nr7Tlp/RyHHCHrrHoU7S11h8CLDmAr6r9AJJ8ENhr1PDZNZIdOmmFkhwIPAn4Du1/eybtuHd74JlJvgb808QNHlXlrbsBJ3U/nwscNL5vgjK+COw6th3g2rQTwDWnrN9XgWuMbe8IfLVnWccCt6IdyEb7vtazrDOB+wK70Q6u1wWuO+V7/RTtousbtJPgYcC/9Szrs8A2A39WBqvfUJ+9sbJOXcq+CT93Vxt9VmgngjdN+fc7C/jTAf8fo7/f04EndfdPnqK8U5ayb4LyjgOuNLZ9JeC4Kcr7Ei24fjDwwNGtRzmj7+tLuttNu9u/Av86Rf0C3B04vPtfvxi4/hTljVqpz6IF/XftWc5XhvrMjZV5FK2RbbS9U7dvhz7H1CGPBd1rBzlWda+9I/Aq4D20C7f7dP+PV/Ss22m0C8qvjv3tjh74/3MV4JNTvP402sXWKd32jYEPTlHeKUvZN0F5uy1l3wTlvQL4T1ovxF6j25T/g+2BxwJfpgXWjxk/Hk5QzqDnoiHLo43kgnaBvn13DDxjyr/b22gByD8BTx3dpihvQ/fz5PG/Qc+yTux+njZ/3xT1G/Q8OfRt7Nj8JOAZ3f1TepZ1+lL2LaGcJwCXW+TxmwN3mbRcew7nuiDJP9B6Ce7QDfe4zIRlPArYdrRR7b/zg25zomEjC9iq5g5TOo/+LTWXr6rjk4zvu6hnWedW1RFbftpErlZVb0pycFUdS+uBPaFnWd8GPpfk48CFo5013ZC+IesHw3z2RjYkeSMbWy0fBmyYom5/qKrzkmyVZKuq+mySV05RHsBPquobU5Yx7g9di/cBbGxJ7/v3A/htkttX1RfgkqF+v52ivJ2A8dbf33f7+rp8VT1zitcDUN1QxSR3rapbjD30rK7n71k9y60kPwZ+TDuuXBV4f5Kjq+oZPcr7ZpJ/pH2O/wO4RdrB69k12fC5zyZ5Ka1XZfxYMM08j12q6idj2+d0+36WpM9c39Gx4OHAn095LICBjlXda0nysqraZ+yhjybpe3wZDdG6KMn2dH+7nmVtzq9pDZd9/a6qfpeEJJetqjOS3Gia+iTZa/SZS7I30x1bPkAL4Ma9n54jRWgXkwAvGNtX9O8pparOT/J+4HLAIcD9gacn+Y+qevUERQ19LhqyvA1JrgK8gRYg/ooWCE/jW91tK4bpDft9ksvRjQDopmNcuPhLNuvC7tj0zSRPpF3nXnHK+g16nkyyHa1h7M+YO2piohE2c4vMbWjXVAd1+7buWdapC1ynnTppIVX1mi08fsrkVXNY6XwPAf4GeFRV/TjJdWjDOJesuqF8M/LJJEfRhghCq+8nepb10+7AMDpIPAj4Uc+yntd9yI9h7gXXxMNaxowuqn6U5C+BH9Ja4vv4v+62LWOB+5SGrB8M8Nkb8/e01qQnd9ufB/5rirr9IskVaa1670xyDu2Ca2Jj82M2JHkP8GGG+cwcSEsE9c9V9Z0kuwGTDucb9/fAW9PmHgL8HPjbKcp7G3B8kg912/ejzQvt62NJ7lVVR05RxrgkuV1VfbHbuC09G56SHAw8EvgpbUjk06vqD6MLCWCi4LAb8n4g8JfA0bR53CcluRbt4muSz8ytu5/jwc1UF760hqeP0YZnQevF/Vza/JRf9ChvdCw4aIBjAQx/rLpCkutVN5e++65doWdZg19Qzxv+uhVtyOp7pyjy7K6OHwaOTvJzYJr5n4cA70vyQ1rv0p/Q/ucTSXJj2kXvlTN33uH2jF0IT6q6YW9DSbI/7dh5A9px8FZVdU7a/LevA5MEh4Odi4Yur6oe3919XZJPAttX1cQX+/PKfD5AV0eq6leLv2KLngd8EtglyTuB29H/vHYwbUTck4EX0o6hB0xZv6HPk28HzqCNYnkBLQCbplH6EOAfgA9V1elJrsfG6QSTOpB2nXFwt30cbUpBL0neChxcXZ6Fbujry/oGwiakmSfJdYHdq+rT3cFr66q6YKXrNdKdBG7fbX6+qj602PMXKed6tLlZt6Vd+H4HeHhVfbdHWe+gDbU5nbkJX/q2zpDk3rSgZhfayWN74Pkz6KHsZRb1W62fve4i93e0C5mHAVemzf2aeA5nkjcv8vBUn5lZ6HozqAGyDnc9BKPv7nFVdfIUZV1AuyC/kHbxP9Wcza5uh9H+t6EdEx7Vp0ctyfNpc4s2uYBO8qeT9hgnOZY2V/B9VfXbeY89oiaf0zeorgfzgbQLLWhTCz5Qq+TkOvSxKsk9aOeOb9M+K9cFHltVR01Zz10Z4II6yR3HNi8CvldVZ09T5ryyr0wbptp7HliSy9DmV0HPbNJd0HU/2pSO8f/lBcDhVfWlnnW7Mi2I+PNuV69kXGPlvYV2PNgkgU+Su1TVMROUNdi5aOjyktwf+Mzo79Q1KNypqj7cp25dGTehBTijxpyfAo+sqtOnKPNqtHmzAb5cVT/tW9YsDHyePLmqbpHk1Kras/vefb6q9p2yjkMF64MZvdct7Vtyeavk/LUqJHk0bSz8DlV1/bRsTK+rqruscNWAS1pof1RVv+u2L0eb6/LdKcq8Am24au8gJMmZVTXNMJuZSkvI8Aw2HVowTW/BoIb87GXhJCO/pA3Je1HfE+mQxnupFtu3hHJmkVCFJC8GXjKvFe5pVfWPfcrrylj1y6mMekr7XgiOlbNq32vXezb/WPCCzb9ieSXZlxbE/SltpMPWwK+q6sqLvnAZpSUIunG3eUZVTTQ0LcmNu+GZC6Z17zvMt/vcfXrI3q+u53YTk36eM4Psol25t6mqaYcvjpf3AVoyrlGPzSOAm1XVpMm4ZvL/WK2SnFJVN5+3r/fFeff6LwHPqarPdtt3Al5cVZMmLxqVN3UAm+SVVXVINpOgqnokpppX/mDnjiTHV9WtkhwHPJ42zeH46pmdOslNab2bO9CC63PpGaxn08zZQL9sr115X6X9L3/ebe8AHFtVN+1TnsNK53oCLUnLV+CSeS7XWNkqzfE+5mY0u7jbd8uFn755A1/8finJHlX19R6v3Vz9BsnG2HknLYHCvWlDDw+gfan71OsZVfWSJK9m4QPjkxd42VIM+dn7BO2z8a5u+69pwz9+TMv4uFB2u010vVOLBV59M4tCu/idf2G40L4tuXf38wndz1Ev0sNZpO5LcM/qsg4DVNXPk9wL6BUcZu5yKhfT9fTR0lf3kmHT61+W1vu1K7BNurnIfYKmtPknhzJv6RgmfK+LBP69syEneR3tu7Afbcjrg5gia2xX5tCZd/+T9p19H2346yPZuGZpn/pdj5ZE5ja0/8f/AE+p6ZZY2puNx+abJaEmWyriabTj+8sWeKz3MN9qGR7/mOTK0zZwjPl4V6fQvmu70ZKwTZrR8o4MmF10dC4C/iZtvvXcAvufi65fVQ8c235+klP6FDTU/yPJF6rq9mPnpIz/nPS7tsi5bZrv7kLD8Ke9xr7CKDAEqKrRcPW+nldjo82q6hdpGYM/PEEZo3Psv09RjwXN4Dz5+u48+U+03vUr0hJ99fXftIRA48H6G5g80zAMnzn7ZcD/JBlNb/grWiK4XgwO57qwqn4/ujBKsg3TXWAObZvxoSxdXfvOoRvy4ndf4JQk36ENc5t6KQvaUgSfBz7N9F+cIZPHjIbETZPgZSFDfvb+oqrGg6zTkpxUVXulrZu2JFV1pa4uL6TNR307G4ffXLNPxdImc98W2DFz1yLanh4Tu2vzCVWemSkSqgBbpyWfuLAr/3K0tUv7OpgBl1PJ8On1P0LrXT6R/gkKRg5hmPd67y0/ZWK37YYXnVpVz0/yMvrP2x55CW0e5GAJlqrqrCRbV9XFwJuTnEyb69LHu4DX0JKAQAs8383G+ZcTSfJ24Pq0z93o2FxMsFREVT26+zmLHqVf0Y55RzM2f6xvsDS/5b3r7Xz8Zp6+WDnP634e2KceC5jVuWjoZFxT/z+q6vbdz0GWKBiqnHk2JHk57bsGrcHyxCnL/HaSf2Juo+c0jTpTB7BVNXpPV6OtXznt+WLcoOfJqnpjd/dYoPdatmOGDNZ/WVXTnnsuUVVvS0sMNroGeMA0HTYGh3Mdm+TZwOWS3JV2AvjoCtdp3LlJ7lvdXJG0OQd9x4sPefF7j56vW8wg2Rg7gyVkqKqPdj+nmSS9kCE/e1snuVVVHQ+Q5JZsDLz6ZKS9b1XdbGz7td0Qhj4tcNvSWu+2YW72tfNpvTh9JQMlVOm8EzgmG+dIHsh0E+O/Twu+hnIwbcTAl6tqv7TkFL1bCYGdq2qo7/Eg77Vms+j76CL3N2kJbc6jZ0PHmKEz7/6ma/Q7JclLaA0z03yWL19z52W+I8nTpyhvH2CPqv5zUjY3tHKk7xDLzgfpscbfUlVLhjRxYJ2BF+ae4bloPBlXgJ8xXTKuQf8fXXB+e1qDxBdqijlpY2Veg7kjMPoMY3wSrYfqPd320Wwc0dLXo4Dns/Hv9/luX19DBrD3AV7RDdl8D20ebt+M9yODnic38537JW3JjVN6FDlksD5o5uwkb6+qR9CSPM3fN3l5Uxzf1520bHoHAXejHRSPqqo3rGytNkrLLvpO2oKtoX2RHllVZ/Uo65m0L/f4xe8R3TCVvvUb4gA7KutFwJdqgGyMGTAhw+bG2Y/0HW+/0GcPeGOfC7AuGDyMFoSFFnj9HS1h0F9W1USZ+9LmPbyGtmZdAQ8FnlA95z10ZV53yIv/DJhQZazMe9IW0Ia29lrvhBtJ3kRLQDHIcipJTqiqW3bDvW5dVRcmOb2q+i4G/Xrg1dUtyDuNGbzXhebg/brP0K/uxP5q2v/1NbTP8xuqqvdQoySvomWc/DADZN5NS0z1E9p7fQrtM/1fkx7n0+acADyT9n0YfX8fAly1qnr1RHbDlp5cVX2zWzPW6HIN2kiCz3Tb+9GO+1P1GneNndepAbKHz7vA3Io29P1qVXX3Cct53mKPV5eZclJpUzCeScvKOtic+gyYjGsoSZ5LGy43+m7dj5ao6kU9y7svbTjetWjLqFwX+Ebf4+hq1/Vy/RPwF92uo2l5CPpmH78McE/aMeX2tPPk301Rv6HPHe+iNWaNGtrvTVsuYlfa52ai691uiOrzGUsKCRxa3Ty/CctaKMtp9f3ejkaHjW1vTVuDco9e5RkcbtQNO3zVlvattAyUKSkt69wlB4m+F7+zOMBmwGyMSbarLonPtLIxE94DaBeEozVqHkrrQXjKEL9nCBkuuciutDlLt6NdXH4ROKSmS4T0WRaeszntBc0g73lom7swnOKC8EO0Bp1DaMNIfg5cpqru1bO8r9NSzU89NHwG73UDC8zB6xvcjJV7WWC7Ab4fC2XgreoxP7o7ob+tqh42TZ26sr7DxnlZC9Wvb+KDz9LWwjueuRdwEzeMJfkUcMAo0ExyTeAtkwZe88q8D20+1LZVtVuSm9OybfZtuBv/PF8EfJeWjXaQc8q0ur/he4D/x9ic+klH3gzdszlW7u7Av7Bp8Drx5y/JmbTkOONJ+U6pngnxuhEwd6YlzblFkv1oWdsP2sJLx8sYPEHLrBqhZ6ELEO9BOx/9eVVdfYqyhj53HAfca3St3F07f5xW3xP7Bk6rSdqauM+mrSH6GzYe738PvL53I6DB4UbzI+9u38k1RbapISR5eFW9Y3MH7ykO2oMsnTDEAXaWkpxFa4n/fHf7wgAXhBtq7kLQC+6boLz5matGF+d9L+BWe0bG8QWat6MlQ7moeiyQ3pU3J6HKaP+k7zmbJj645CGmSzIyMxkgvX53LNjEkL27fY2+V+nSkXf7eh2X0xZFfjxjw9KA166WC31on0Hgzn3/l7OWuUtFXKLafO5Jy/pGVf3p2PZWwOnj+3qUeSLtfPS50Wckydeq6iZ9yxxSNiYI2pf2GZwqQVCSE6tq73nfjxOqaqJEdWMX5jeiDVkfjay5Dy3D45Lnq88r9wu0JCOv6Mo6kJYhfeLe+q5h4v61MZHeVYAPTtHbMjq2fBW4RVX9MclXa+40ii2VsXdVnTjw92ImjdBJbkhrRNiVuefJif9+3ciahwB3Aj5HW0v0UzX90NLBJDkDuGl1S8V01wlfraob9zmHZODM90NepyX5l2kbTMc55xBIy/T1N8BuScaHGl6JNt5+pY0mvA42iTpjSyfQkgtcG3gdG4fRTeIPVXVekq2SbFVVn03yyp71GjzFeVXdIC0d+R1oC2m/Jskval7a6QkNuRA0DJi5KgNnZOwuqA9i04NY77kPtXFS+8gXk0yTNXKQhCo1cOKDkSFPKl3v0ulVdeOujIkvPuarjYl95gwN72PoEyjDzsF7G20duNHC239Dmz/yVz3LI8nOXXmjdQ4/T1uMuO/aet+mfR+OYG4Cj76NgI9caH9Nll10/HVTf97GHJPkKFqCHGgXm5+essw/VNUvkzkdpn/c3JO3ZDO9OKOlgf67R8PCoAmCGGhOfW1ccP04YK9RQ3GSQ2m9LX1drqqOSZLuOHNoF8AvOTjMxuzgvwROT0tuU8BdmS7b8C+63qTjgHcmOYex79xSjM5lQ34vRmUledm8BuePdiMp+nof7TrvjUyf6O+RtB7rx9ZASWlmcO54J/CVJB/ptu8DvCtteG2fZC1DZr4fOnP2c9ISDu5WVS9MsgtwzepyT0zK4LD5Eu2C4+rMTa19AW188oqqqv/ufm7StZ7+2UqHXDph6gPsmKfSgtbBUpx3F2+3owWHN6PNvftCz/qNPAX4XJI5C0FPUd6QmauGzsj4duAM4O7AC2jZSqdKwJGN86GgXejvTev96mvIhCqb6Fqon1BV/9yziMFOKtXSw5+Z5Do10NqB2czQcCZP1w8DvtfOI2ifkSfSvne70FrU+7jJvKFEn00bUjuNN9Mu+EcB5sO7fXftWd63uttWDNMgON6DtB2tAfAkJsguOi4DzgGtqiemrb02WnD99TWWar+n05P8DS0x1+7Ak2nn+L6+DezI3AD2AtryIm+gfT4nMXSCoBelDad/Ghvn1E8zvWEn2pC0kd93+/q6sOsR/mbaMjc/oM2Hn8QoIDoRGP98fG6KegHsD/yO9vd6GO0c1LfnZrDhs2OGboS+qKpeO8XrL1FVmyyfMoBBzx1dkPQJNjbcPa6qRp+lPkP3h8x8P/R12mtojWB3Bl5IyxL8GnosdQdAVXlbIzfagXDXse1b0rrI+5T1le7nyd3PbYBTe5Z1BdoFwja0L/OTaV+iFf+bdfX7Iy0I3n/gci9LCzZvBlx2yrL+FXgpbS2yvUa3Kf+3X6Zd7F8WOGuKuo0+I6d2Py9Dy5I5zfv9Du2i6zvAN4FPAbeforzX04aPTPs/3aUr62O0JD5XoAVN5wKvmqLcE8f/ht39E6Yo7zjaBeoxtOFfR9ASSvUt76u01OSj//V+wJtWyXs9eCn7lljWO4B9x7ZvTZvjN81n5pSl7FstN+AqtCHIfV+/gTY/9eTuuH8g8C9TlLcTrUX/3sA1Bnh/lwf+GTihu72INre0b3mbfHZH+2g9+EstZ4fu9m+0JXZ2pTXCPGOav98MPh/P6Y4Hh3a3U4BnT1HeLWnB4M60RpMPjn8HV8ONFlCP/j879CzjC7SGl1O7/+uhtLmu09TrHsD/0a79jqXNd737FOUdShtWf80B3u++3ffrV7QGhIuB86d8v0OfO66z0G2K8r7c/TyKNgrtFsC3epY19HXaSd3Pk8f29YoPqsqew3FDtojOyL8An0zyH7RhoPeknZj7ODYDLZ1QczNdDZZWO205gl2ZOza+T2v3LWhzjP4mybNowcixVfWmKas47ULQ40ZDisaHkPTqKQU+1vV0vZTWQ1C0Fu6+RsOWfpHkJsCPaVkGe6uq3aZ5/QJuD/xtpl9r8220k/AHaCfmDbSLo5tW1Y+nqN9gy6l0/mmK1y5ksKHhDP9eD6DN0Rr3twvsW4q9gS8lGfW4Xgc4M8lp9F+b9bxuOM+oZ+mhtCUyesmMkjWN+TVTrvlVA63DmOTBtOPU52jf2VcneXpVvb9HWdvRehtuAJwG3KaGmf90xfFe+m6Kwqjna5J5oScyN0HQ+EiTYsK/39hQywVV/3Ud/znJJ9mYkfHAmmK5iKoa9az8iv7XKwCkZR5/IZvOze91jZbksbTsk7+jNSKPFl3v8/2YevjsfFX1ya5H8sbdrjNquiGcB3Q/x3uq+77f/2SBRGFT1A2GP3d8nI3fkcsBuwFn0m9EDCzcS39Iz7IWuk5746KvWNwfuiknBZcM0e0/nL6LLsXssuINKcmdaOmHf0qbQN3rgjXDLp3wAFpr6DW6sqZO3pHNLLTc94TXDXu9PW1o6cO7whZMwrES9ZuVDJCRMW3B9Q8Ae9Jafq8IPLeqXjdFmZehrac1Gk72Odr8nT9s9kWLlzdIQpXMS0aQ5GxaS2Pvg2xXzmDLqcxCkk/T0sL/C214/TnALavHciVDvddsnAt++668kSsBf6yqiedHb+5zMjLp52WszFfTev2LNoTxydVzyG+GT9Y0PmduK9qwt/dW1bN6lnccLcv1G2kNRT8C/rYmSOIxVtZXgbtW1Tnd9o60xGZ9ynoP7eLy87SG0+9W1SGTlrNAufeizdP6Fu3cthutMfVzwKOr6pXT/o6e9TpgbPP5tKQvl6gp1z/MQEtTDTlnMy253ANoKfqnvnhN8k1aI0Lf9aLHy/oS7Vj1ftrSLD8A/rV6ZlIdK/cmbDpUtW8j9GAyYKKwsTJnep5My2Xx+JpiuY0Fyjxk2mPAQNdpD6MNed+L1knzIOAfq+p9vcozONxoFh/2IaWt0fVg2py8PWnj5J9WVb0mi2egtaC6A/Z9asCFoJN8gykXWh4rawOty/5LdBlL+1wEzqJ+mUEm2qyNjIxvpA1PHV3APAK4eNqD9rQXNN3F6p3Y2Lr/2fHtqlrRBFXZNIvqJQ8xXQv6FWit52Hj3Jt3VlXvHrBpdUHXbrSAdTyQuYA27Kh3r9BQF77LJcnxVXWrCV9zA9qQzfERQhfR/sc/qqpv9azLdWmNB5dhinUYu7JOq6qbjm1vRRsKddNFXrbFspJsQ8uwuWBisx5lX5aNvTdnTnMszcAJgroyB7tOyabzj69D67Hqu4bqq9h0zub5tOPY9jXBIt1dr/pdpm2sGyvvk8ADquo3A5R1S9o87avQejevDLykqr48RZnPo51/9gCOpDV6fKGqHjRFmYMEm0M2Ei2n+cecAcr7v6q6zgTPX3S+fPVcH7cr+8a0oc0BjpnmmtxhpXMNmRVvFq4G3Kqqfgv8T3dgeyM9Mol1J4CX0obP7pbp1oL6yZCBYedrtBTOvRdaHnPPqpomIcZChqrf4JloGTgjYwZaJmKeW847iXymC8x6WeCCpm9ClSvThn+NpzocZcidePjN0EO/auAsqmPlDjY0PC1pwpPY9PMy0bGla8D5Hq1HbhADfk5mNqwvwyVreiXwD1V12rzyb9o9dp8+9RtrWPstrcdqGp/MptlKj+xZ1iWjDqrqoszNVjqt3WlLPGzH9FMIBk0Q1Bmylf+FtPlkc5ammqK829bcZTU+mm6pjSSnT1jWM4AjkxzLAIuk04byfinJV+aVN/F3d8jhs2MeRMtpcHJVHZhkJzYuazGxzQWb9PvsPYI29Wo8UdgDe9ZrVsfS8Ub3rWi9aj/sU9Ziv2bC5y923C3anNxequoM4Iwkj5n2mtzgcK4hs+INrtpCq5dLcqOqOrM7SffNiPc8WrbSz3Vln9Jd1PWxoRvS82HmHmAn/pCPDUG5EvD1tOUNei20POqVAx6x0IXCFCcUaEPvpqpf9/zNZqKdwtAZGQdZJmKei5Ncf9R7kbb21zSptQe5oKmqXaeow0KmSTs+czPqifwwbWmWjzLdEgKzqNuQF77j/9tNhvVNYXxu2kW0pE191ozdaX5gCFBVpyXZddLC0s3L3Nzj1WO+ZlU9vWtJH81vmyZb6c2SnN/dD20+/flM36s+5AU1VfWkeeVfBTi8T1kzMuT8Yxhuzia0REO/ogXVfTO1j/tv2hDQ05jiWAWQZB9aMp/RfEig3/dizG+rrb14UZLtaQ1au0xR3mDB5sCNRLM6T443pl5E60j5wMC/Y6KGmaoaquFgMY+jJdbrzeBwrvtV1atow6tGa/4cTL/EB4NLch/g3xmmt2+htaD6tj5uD/yGNn9xvKw+LSBH0IZCfX7e/jsweS/dLHrlRg4dsrAMuzDySUn2HQ1nSXJrpjv4zmKZiKfTgtbR+9uV6Vpbh76guUSSQ6vq0D6vrXnzftLmvlJVvxqgalObUU/k76rqP6YtZEZ1G+xzMv6/7eadDJKMq4ZL1nSVRR67XI/y7t2zHlvyJVrD0B9p2Q97qaqtB6vRXIP23izg17Th0xOZ13hy+XmBce9gmGGXpoKWvOMLSebM2eyGsk/6nblWVd1kirrMd5mqWnBKRw/vpJ3Xpg40x2zoGg/eQGs0+hXt2qCvqYPNGTUSvbUr+69q3hy5JL3XoAW+vpnyJpqHt4WGyomOpZnBVKLN1GsqBodzDZkVbxYOZdPevr5Z54ZcC+qNVfXF8R1Jbre5J2/B/iw8FOpnwItpPRJLMqNeuVHZgy1425l6YeSxg/Zl2DQj4xlT1O1LSW66UC/EpLp5Gd+vltVtd1rGvvvRlrLoPayU4S9oxt2XKRsDunkeb6dlXkuSc4FHVtWkw6pmYt5QxpELql+CoFd1vS2fYm6v+kmbf8myGX1OPs+wn5Mh5kYPPRdlQ5JHV9WcTMVpCaZOnLR+Yz0Fo3mHu1fVp9Pmrve6lujq8lxa780oW+kLquqwPuXNyKC9N5mboGVrWnb0905azqyGmNPOwb9lgLX/AKrqyMzNuDk+Z/OVExZ3ZJK7VdWn+tZnnk8keQxtlMP4sarP3PJza+AEY1X1+O7u69KmEW1fVdOsvT1EsDmrRiJow3znB24L7VvW8gb+rs2y02Kk15SBcSakgcWy4m1PS5IxcVa8WUjy5araN2OTzzOWPGfCsi5PGwIx6u07CnhR9Zhon+Skmjfxf6F9SyzrhHnzE8Yf6zWROC1By0G0eUXjk7Af1aOsWSUE2eT/mHmZM5dQxuCZGLtyv05LDz/tMhEkOQn4i6r6WZI/pw2nehJwc+BPq+dE+8wwoUoGSPaQlsnuOVX12W77TsCLq0c20FlI8l3aBe/PaX/Dq9CSDPyElpFxycFEkn+hDdH/Fhtb0KuGW4qht+64N/qcPJx2jH9nz4vB8XJ7He/mlfHm7u41gNvSAiaA/YAvVdVEF2VdD9eHaEP3Rv+/fWgjT+5f/TNdP5qWFG2Hqrp+d+H/uj7nySRn0uaknddtX432XqfK8DikJP8FPJvWYPc02gX1KX2HhyW549jmRcD3qursqSs6kK5H4z1V9YMByxxkWaru/HsF2nnoD0x/3v3OArureixcn+QutGVsjmHK6TVjZf75Qvur6rgeZYU2Cuj73fauTBFsdufcUcPJDWnB/yf6NCgmuSdwL1rCxfeMPbQ9LfHfpMm4Bi1vNdtcD+RI355Iew6bL9GGLF6dlqxg5ALagqarxSC9fWlroXy8qvajBYi9JLkN7SJmx3kf0O1pLaJ9XGWRx/oMhYLWY3MGcHdaC+jDaEkoJjbD1tpPpK3BeDgt+HwIrZV0h+73bvHidV7L/s1oQ3GhZWedplfunlO8dr6tx97LQ2hzjD4AfCDJKX0LrRmttdkZIuPhFUaBIUBVfa47ua4WRwPvr6qjAJLcjZZc4M3AfzFBDzYt8dH1qmrS+UQzs5lGndHQm+d2Q96eU1XH9Cxz6mF9o2AjyadoFzA/6ravCbxlkrK68n4C3DZtXuVoKN7Hq+ozi7xsKZ5AG8Hyle73fDMt+2sf59HOsyMXMMUakUPrLqj/pap+wUC9N1V1bJI/of0Ni9aIsppcCfhUN1rnPcD7us9SL9nMsk/0mLM59Pl3wCHc0KZF3Jg2cueSRjGmSDDC3PUIt6N9Zk6kx/rHVVVJjgRu2m1/d4p6QRulc4ckV6WNEjmBdk5/WI+yfkib+nJf5o5quIDWg73S5Q1uwE6LmVyTGhyyaVa8rvXyz4Ff1TCL6A7lSbRg7kLakMOjaAkWJlJVFyf5Y5Ir1xTrqtBaoK9I+xyNf0DPp83T6GOwoVBJtun+fzeoqr9Ksn9VvTXJu9h0TuNKe3D387Hz9v81E2bJTJsn+2g2npTekeT1VfXqRV62WaOgM/PS//e09dj/5S60HoiRiY9HYxfoYe7F/7QtylemDSW9Q7d9LG1+b9/vy7fTlqJ5e7f9cKDPfNJZ2beqHj3aqKpPJfn3qnpsWrbaSXyN1shzzpAVnMZiF5VdY9lNaHOGljyfaYYNRbuMAsPOT2hDw3vpGiU+u8UnLt2FVfX7dPPV05aNmGgI0lhj4lnAV5J8pCtjf1ZRg+wMLqhX/VDaatMwnp9kT9rF/rFJzq6qv+hZ5D4MtyzVYD1pXXmXB55KW9LrMV2j+42q6mM9irvl0D3eVTVneGCSXZh8KO64k5LcsjZmVp1Gquo3SQ6iLWXzkr4NvF3j9Ve7a7MAN+weOrNPT2RVfTXJ14C710BzwWdgqE6LIwf6f85hcAgk+RjwrKr6WtdKexKt1eH63UX1K1e0gp1qa/E8hyl6+8b8CjgtydGMzbmpCVIGV5t3d2ySt1TV95JcvqZfL+gQ4ENpC3puMhRqwrKOp/X6jA4uv0ib+/Vj2tCtVWPgFsyDgFuPetOS/BttXkGv4DADpv+nNWocm+SntHktn+9+xw1oGVEnMsML9MNoQc4oaH8ErRetb/biR9GSXH2QdhH8+W7favGjJM9kY9bEhwA/6QKnSZMrXIWWTvsEpsjku1yq6mLahUmv78cMHJNNl3f49ArWZ75jkzyblg30rrQ1VT86YRmj7+23mNtz9pEB6je0IS+oofUG3WL+UFraMWc1OYd2rjyP6c6XQy5LNVhPWufN3etHw/t/QJuP1ic4/FKSPapqmszgW3I2bY5qX7cGHt5NI/g1U0wRoXWs34YW1IyyKU+bFOq2tB7l73Z12yXJAX2C/64TZJck266mUSxjhuq0eH3aPPrDgXcP9fkzOGx2q6qvdfcPBI6uqkcmuRLwRaZrqZlakkUnOfe86PogG3uWRi16fTMcXSvJJ2i9iNfphjQ+tjZOpl6yGQ2Fen039OEfadlQrwj80xTlDS6bLlz/edo8nj6LLYe5y0JczHTZqwZL/19V/5zkGOCawKfGWpO3ovWMT6wLYE6vqhtv8clLd/2qGl+z6fl9WkW7/+vjaHM2TwOe1qcldBn8DW0phg9321/s9m3NxgB5qYZa0mFZVZfAaqVV1RPTktOMhoVPs7zDLDwT+Dva5/mxtOUd3jhJATWDJGEzdGvgYUm+x/QX1LD6h9I+nvad35EWKD16ygvOQZZ96l4zdE/a9avqIWl5J+h6wvqeK/elrZE99dz8kcxd/28r2tz8iRN7ZeNSInfvW5cFHEJL7vKhqjo9LTnitCMUXg7crarOBEiby/hu2lqvfXwH+GJ3DT3eCTJERtBpDdJp0V2T3Yg2yuz9Sf5A+5sdPs1IB4PDZvxi7S60TE5U1QVJhkpJPI3bAN+n/cO/whQX+kn2p01Kfk23fTztJFC0k34fr6QddI6AS7r0Fxz+sVQDDYW6xtjwpVHygNd0P1fTfC8YYOH6rgf3b2mtoV9JMrqgvB8TZHldwKDLRFS3xMa8ff87RXkXJzlz7AQ4hN8muX1VfQEuyb772x7lvJV2fPk8be7mn9JOqqtKVf2UzQfnZy21nC5Q/++BA/VLnWpJLKaZqzQT8xpi3rCl5y+hvFmsDTe0IS+oYTNDaUfnqlVw4boLcEhVnTJQeYcOVM5Cpu1J+31att0CSHJ9+q/lO/RyTzB3CaqLaD1DX9zckxfxYWCvboTXB+Y1fPYyNnLsikmuWG3ZrV6L1Y+5zCgw7H7H/ya5zBTljUYmbMVss4P2Meq0+Cc2dlo8t09B3d9sNBz8ZrRA8ZgkP66qXisHGBw230/yJNqBZi/gkwDdQWOaD+ZQ/oS22P0oq+rHaQeJPmnwn0H74IxsS2uVuSItqOiVMriqvj+vwW2aBc2HsjXtfS0UTK+2NL1DLFy/J7SLiySfY+PC0gdW1clT1G2Wy0QM5aq0hE3HM7eFsO9QxscBb0ubewgti+cBPcrZo7oMu0neRBvqvOp0LbT/j00zCk40XGtGgfqlStdr+G+0VuQw5fzZIc3g/zuLteEGVcPOuYbND6Vd0YvXbFzO5qXztoHeyzsMuuzTUD1pYw6lXe/tkuSdwO3oud7uDD4nAO+nrRt7cVf21j2n74xfA/Vd/mxugclNaY3aQy7PtCHJG9m4jujDmGKN5tEIhayy9YUBqmo02uJYhvufbEU7b+xE6wDpPe/f4LA5iDYh9C+Ah1TLTAZtmMCbN/ei5dIdGD4JfDItOcRDgc8leX5V/eeExW1bXSrjzhe6g/7P0j974vfTUlVX18pzMD2zgQ7sR1XVe32mZTbEwvWXT3ILNp4IvtD9TJK9asJ15rp5gDux6bpX16XnENAZGnqY8PlVdbO0dc2oqvOT9JkXesmohKq6qP+IpZl7H/A62vDAaRt2hg7UL21eAtynqlbDMXQhQ/5/B18bbmgZds71+AXrEHP0h3Qim59iMlFStHGZm9V3W1qD+697NnYM1ZMGXJJ460TatV6Ag7tRFBMb+nPSOYZ2XToKai5Hyww66RJItZn70/hv4Kk1d3mmNzB53cb9PS0b8qgH8vO0bNm9ZO76wqTlOlgV6wt31/IPZNMG2YmvWZPcgRYX3I/W0HY48JSaIuGk6xxuRpI/qZ7rQM1C90H6S9oHYFdaN/RhNeFaREnOqqobbOaxb1XV9XvU7erAq2gHsdAOXgfXAGvMTSMDrE+3XJJ8A7gRML5w/Zm0E+CS5i10J+ET2ExP6aS9QGmJmv6hqk6bt/+mtDX6pl5odUiZuzD35WnLZlywpddtpqyF1u48saommvuQ5GI2XkCHdnL/DauoNwj6vbdFyrrjQvuH7EFYz5J8se9QoOUw5P83M1gbbmhJvkpLeDJnznVVHbSFl26uvNvQhvlfsaqmmqO/1nTz+fanZUd+1iqozzE1b33OhfYtsaxBPyddmadU1c23tG8J5YzOQ+PnIJjiPJQF1mFeaN+EZV6BeT2lwGX7NqJkFa8vnLYszi9pjTKXNMhW1cs2+6KFy/k+bbWFw4H3VtUgWcLtOdy8IxlmfbOpJXkbLTnLkcDza2PynD6+koWXingsPYe8dS1tfda2mbWJD/AraIj5CmdNGgBuwU7zA0OAqjotbQHdVSNjC3PT1tS6Nq0nbKLPQJIb01p6r9wN7xvZnh5Dhapq2uxty+WjaYkoPsTci/SJh5JVW8dtk0B9uKquexuSvIc2T2jVBUwDB/mzWBtuaIPOuWYGc/SH1s2F2p2566/1Wi5iXLXeiA8neR6w5OAwyWks3OPVK+lLWqKwywNX797rqEF1e9q5o4+hPycAvx4f9ZNkb3rMfZ/ReWgWyzMN1VM6sprXF965qoa47rt9ja1xDZd8f39RU/T+GRxu3moa//VwWqvPwcCTx4am9Wn1eQrt4Pw3bByrvzdwWVqX9JIleUa1tW3G5wFcoiZYFmMW+s6RWE5Jtq+q85mbve4SK/werrLIY5dbrkos0VALc98IuDftvY/3jF5AWztyvRrNpxxPFd9rKNlQgfql2Pa0lv27je1b8YBp3vDAOQ/Rvxd88LXhZmDwOde1OufoA4zWYTwY2Jm2cP2+tKWQejU8zmtk24q2NNWkWbjv3ed3L+KxtMRg16L13Iz+GecDk07VGRl9Tj7PcHPzDwHel+SHXR3/hLk5I1bS+PJMMMzyTNuNzwusql91jYt9reb1hb+U5KYLNcBP6IAk762qM7oRhp8EbgZclORvqqrXMkgGh5s3dSa2oVTVVgOWdQ5tqYg7s3EsfN+lIh7Xddv3njAs3kU78Y3me4xfMUx6cb7ZbLNJrtZjmO+GzfQy/x0b16BcLaZemBugqj7SDad9ZlW9eOA6rlo17DqbQwXql0pV1SshxqzVbNYUXY614aY1f871lWk5CvparXP0Rw4Gbgl8uar260ZTTHMsHG9ku4i2ht3+kxQw3jOSZKeufgDH9xlGV1WvAl6V5ElVNdT6pvelBb0H04KQ7WnBU29VdUL39x81oPRaFH4WqurnTJ+ddL75PaX70C9L+MiqW184yddooyS2AQ5M8m2mW/rkIbTlxmBjI++OwA1p2dJ7BYfOOWTTrFzzrYUeqJWQ5BDaB/OawHtpk8OnyYqpASX5Fi2z7TuAt9TcbKhLef1OtGGGv2djMLgPLanA/VfZnNyXAL8AHklLlvN44OtV9Zye5R1fVbcaroar06j3v7v/V1X1vrHHXlxVz+5R5leq6tajOb9doH5Sj5PepVKSnWlL2ozmHX6eNof77JWr1Wx0c62vT1uPbJC14YaWlojqR9WtOZuWxXyn6rmGWBaeo//k1XKdkeSEqrpl2rqut66qC5OcXlXTJFYZqm4PpmVT/Rztb3cH4OlV9f4pyrwJsAdzh9C+bYLXL9SjPmrk/R0tM+1zquqYCcoc/Lg8tCQfZdP3/UtaZ8F/V481mpPckjZ37ofdrmvSkkRO1BidTdcXPmy1BNVJfk7Lsrug+UNEl1DeydXl1kjyAdr60f/dbW+SO2HJ5RocQtqipaNem+vQ0taHNrTs/wZuVV93uvlFf93dLkfrDXt3VX1zRSu2BiRZ9ItbE2YYXaD8pwD/TlvOYsknvHll7Eeb8wptjbM+vcwzlZbC+SDaULwARwFv7DvmPskraPOg3sPcjIxT/T9Wm/GTx/wTSd8Ty9CB+qVNkqNpx9DxoVAPq6q7rlytZqM7d2xi0gukWUqyAbhtVf2+294W+GJV3XLxVy65/KsCj6+qfx6ivGmlrY97IG1I451p10OXqap7TVjOgtNNRvpMO0lL+nLXUW9hkh1pCWB6JUHp5j7eiRYcHklbi/YLVfWgPuUtUP7WtHPnO6vqJlt6/tjrBj8uDy3Jq2g9VO/udj2ENiy3gO2r6hETlHVL4PtV9eOuN/2xwAOArwPPnbThpJuzPb6+8Her6pBJypiVof9/Sb4M/B3wE1oSw72r6jvdY2dUzzWHDQ7HJHkD8KGqOrLbvidwv6p67MrWbO1IW0rhMGDPGU2CXleSfHaRh6smSDCT5FPAo2vjekv70oYVvBS4W1U9eKrKXops5v8y0f9jLZjX6njJ/YW2JyhzPFAHOKo2rumkLchAGQrXksxbG65W0RqZm/l/TJyVMckutCV3rkUbkXE4bcjbI2mNqQcPU+PhpGWmvTLwyVFwPMFrx9eFfT7wvPHHq+qtPepzWnXrxnbbWwFfHd83aXm0+VknV1u6aCfgHUM3xCR57Kg3Z4nPH/y4PLRRD/NC+ybtaU5yEvAXVfWztORMh9MaFm8O/Omkwfr456QbuXL8agioAZKcDbx8c49X1WYf20x5+wJvoQXqr6yqF3b77wU8oqoe2qeezjmca9+quiTpRFV9omsF1yK6L989aT2Hd6EN+Th0Bau0ZlTVfgMWd42xwPAvaUHhfarqf9Oy0a5bSW5H+8xdl3ZcGw1P67U218D/l9VssfWvJmo5TLI/LQPba4A3pCWm2RHYO8kvphn6dSlzXpKHs7FF/qHAii4LNCuZzdpwQzs3yX2rW4+x+5z3WQvvbbQFrz9Ay069gZbwZc/VMEQ/LfHHH0bD75LciJax/XuTBoYwN/hLckifYHABn0xyFHN7q46corzfVtUfk1yUtqbtOcAu01ZyvkkCw9FLNnN/oe2VcsUk1xk15CS5DnDF7rFJPy9bj/UOPgR4fVV9APhAN7x5Uqt5feGtaX+nQSpVbW3sTXoHu06u3t8Ng8O5fpjkH2lztKBNPv/hIs+/VEtyV9qFy71oy2AcDjymqqbN0HWpkeTOVfWZzM3odomaLH39hV1r7S60VrdbVNUPu5PeaknfPCtvoiWMmLNmUF9dC/KLgWtV1T2T7AHcpqreNG3Zq8zNkpxPO1FdrrtPtz3p0h3PYG4mvW1pmZCvCLwZMDhcmkfR5hy+gnYh+CXaML/16IW0bJhz1oZb4TrN9zha9sn/pH0vvk/r7ZvUDlV1aHf/qCR/RRsu/MdFXrOcPknr8f9mkhvQMpS+E7h3klvVdOsSThXQdPXZqaqe3p0rb989NKpjXxuSXIWWgPBE2hIK/zNNXQcy5HF5Vp4GfCEtt0GA3YDHpy0VMWlDwNZJtqmqi2gdDI8Ze6xPnHKzeX+zy439PatWdn3hH1WPhe43J8lT5+0qWuPVF0bDS/swOJzrobShDx+i/YGP6/ZpYf9AmxvztGqZqzS5OwKfYW5Gt5FJ09c/jLZ21O+BlwCHpWWT3Z9VlH13Rn5ZVZ8YsLy30AKa0Ty5/6XNP1xXweHAQ7+3rarvj21/oWsN/llWz9pSq17X+3/fla7HMpnF2nCDqqpvAfumLVNAjaXan1Tmrql3Hm091XTlrnRCmqvWxjwBB9CGuj6pm2N5IhOsSzgDr6Rdb4waTD8IkOSm3WMLnT+3qKoe3919Xdqi5NtX1anTVnZaa2FKTlUdmWR3NvZanVkbk9C8csLi3g0cm+SntOykn4dLGgV+2aNuq/nvN3Q35kJZpHcFnpPk0Ko6vE+hzjlcQJIr2PultS4t2c1daPMpeqUzXu2yMaHPg2nDNT7I3IXDeyWQGZs7MT73Y13P+5pWkrOq6gabeexbVXX95a7TWjKLBB6rXZJP09bX/Rfg6rRhfbesqr6LXg8mycOr6h0LtMwDveYGfZeWwn6hi8PeQ+CHkuTU6rLEJvki8NKq+nC33WeO5XgWz8vT1u6EHr03C81vG3tszjzECev45wvtr6rj+pR3aZJkwd7z6p/4bl9adtJPja6/k9wQuGLf8/hqlGSH5WgISluF4dN951raczgmbe2hN9KGQV0nyc2Ax461LkkzkbZ46QNpLT6XfC+nGX7QHVDXzUF1M142b3ufsftFz4WbaestXa0rY3TimrgF81LmK1l4XczH0oada3Hj68VuksBjPRkNE2TTNQSvSxsSvxqMersHWd+xqnYdopwZOjXJvwM/oC0B8CmAbtjlxGrYdTEXq8Plpij36WP3t6Otz3oi/c8blybjwfp2tIbok2hzayfWzZ2bv+9/+1Vt9VquEQJdcp/evZT2HI5J8hXgQcARY70FX6sJUhBLfXRDWn7JvDlzVTU/+FmsjIXWW7rECo+zn6kk16uqb29p3wTl7UWb93UT4Gu0xCoPWg1DjlartIyTH6b13I4aJfYGLkvL+vyTFaramrNaMhLOSpKPAf9QVafN239T4MVV1WuY4FrTDfs6dKXrAZC2fuPBtN6bw6rqq93+2wLXr6q3L/b6Gdft3cBnFmh4+jva0hYPGej37ELL+PjAIcq7NOkaEQ6vqnusdF3EaAmyf6qeGdYNDsdk3uLN3b6Jh1NIkxqyESLJC4Ef0dZJC61F/ppV9dwhyl+NssDaQUlOrKq9pyhzG+BGtL/hmbVKFtFd7ZLcmY3ZJlflupir3UKf5/VkVsMEh5RkseNlVZcyfsrfsar/z0n2Wg1D+roEYR+izacfLYi+Dy3p1f1roGyvXU/L6VW1xxDlXZqkrU/4taq60UrX5dIkbTmW+YHcDrRkmo+sqjP6lOuw0rm+37WSVfdBP5iWVluatS8luen8lvSe7juvQeO1aYsHr7vgMMmNaYHIledlfN2eKbK6LTCfYq8kvedTXJp0waABoRZzlUUem2aY4JAWyjtwBVpGz6vRMq1Oa1Xl2F/AG2nLWayobtTBbbvekFEj6senbXiaN893K+AWrP+pGFNJciTwBOA/2Pi32xr4U+B9K1WvS7F7z9su4Lxp86YYHM71OOBVwLVp4+4/BTjfUDMz1uqzDXBgkm/ThuWNJu3v2aPYXyd5GG1pkaJl3F2vCZZuRDs4XoW5GesuAB690AuWaND5FNKWzE/gMS8V+0qnXx/ahs3MT/07NvYMrajxIf1JrkRrLD6Qdlxd8nD/Leg9smGZrKrgtao+C3x2wCJH83wLuAh4V1V9acDy16M3A0fRlqs4ntabexFtPcyzV7Jil0Zddus5kjwGeP005TqsdEyS21XVF7e0TxpKkusu9vhCX/wllLkrrZHjdrST3heBQ6rquz2quCYkuU1VzWx9KudTSMNZrmGC0+oy/j2VNjT/rcCrasplm5LsSGu42pW5ycceNU25s5DkfqOMpetJkv2BnavqNd328bR55QU8o6pck3UR3bIu/wTcgzZ95ZK1OifN4qvhDTFc3Z7DuV7NpkMoFtonDeUntB7rGwCnAW+qthBsb10QuP/0VVtTzktyDG2h5Jsk2ZM2vPZFA5X/a9oiv5KmNKthgkNK8lLgAbQW+JvWFOsbzvMR2jpun2Ys+dhKG1sWaNz/jfavhrmHA3oG8Ndj29vSenGvSOsZMzhc3O9p58TL0rL5/nHxp2uZTd3jb88hrdcBuC1wCPCKsYe2p7VimpBGM5HkPcAfaBcL96QNzTh4yjK3o82L+TPG5t2txpbpoSQ5lpaW/L+HyDSc5KPMnYuyB/DeqlrJhaAlLZMkf6QN8b+IuQkfphrmu1rXS02y2HDN6pv1cDWanxApyX9W1RO7+1+uqn1XrnarW5J7AC8HjgBeUFW/2cJLtMyS7DztEF97DpttaS1G2zB3TaPzaUtbSLOyxygzX5I3Mcx6cG8HzgDuDryANiRqvSdWunxVHT9vWZ9pemD/fV45zqeQLkWqaqsZFf2xJPeqqiNnVH4vVbXfStdhGV11fGMUGHZ2XOa6rDXPAf6qqk5f6Ypoo27qyyPphquProWq6sl9yjM4BKrqWODYJG/pM8dLmsIlyyNU1UVTrFk67gZV9VdJ9q+qtyZ5F61ncj37aZLrs3HR+gfRlvOYSNfrOugwX0kaczDw7CQX0o7/qyLhUJJnVNVLuvt/VVXvG3vsxVX17JWr3eC+spmESI9lmAbadauq7rDSddCCjgS+TLtumXqYr8NKgSSvrKpD5g0lu0RV3XcFqqVLgSQXszGTaGhp3H/DFBcMSY6vqlslOY6WbffHwPFVdb2Bqr3qJLkebW7QbYGfA98BHj5pEp5ZDPOVpNVuPInF/IQWq309xkkluQbwYdqw4dFcyr1pc+ju182JldaMob+j9hw2b+9+/vuiz5IGVlVbz6DY1ye5Ki2b2BG0IdPrbo3DcVX1beAvklwB2KqqLuhZ1CyG+UrSJbrj8+7MnRN+3MrVCJibxGL+EJZVtaTFtKrqHFpCpDvT5ubDKkuIJE3o7UkeDXyM1ugBQFX9rE9hBodAVZ3Y/Tx2pesiTauq3tjdPRZYt72FsOBi9aP9AH0WrZ/FMF9JAi5Zy/FgYGfgFGBf4H+AlU74Upu5v9D2utAFgwaEWg9+D7yUNid09H0tel4DOqx0TJLbAYcC16UFzqOhfev6AlvrQ5KnLvb4elx/KMmrN/PQfYFrV9VEDWCzGOYrSSNJTgNuCXy5qm6e5MbAi6vqAStcr9Gxb/y4R7e9XVVdZqXqJmlxSb4N3KqqfjpEefYczvUm4Cm0RXlXzfpD0hKNMu3eiHbxcUS3fR/W6fDIqnrS6H5aN9/DgGfSJmb/c4/yZjHMV5JGfldVv0tCkstW1RlJbrTSlfLYJ61pZ7GxQWdqBodz/bKqPrHSlZD6qKrnA3SJaPYazbtLcijw8RWs2kwl2Qb4W+D/0YLCB1XVmStaKUla2Nld2vkPA0cn+TlglnRJ0/g1cEq3Xun4nMNeS1k4rHRMkn8FtgY+yNw/7kmbfZG0yiQ5E9izqi7sti8LnFpVK946PbQkT6DN3zkG+LdJs5NK0kpJckfgysAnq+r3K10fSWtTkgMW2l9Vb+1VnsHhRl3EDRsnc47mGa30RHFpyZI8B3gw8KFu1/2A91bVi1esUjOS5I/AOcC5zE2aMPru7rkiFZOkBSTZFzh9bGTH9sCfVtVXVrZmktQYHDInkccoNWHRLja/UFXfWZlaSf0l2Ru4fbd5XFWdvJL1mZUk113s8apyuJakVSPJybRh/9VtbwVsWE/rCEpaXkl2B/4F2IO5S+T0SqjpnMPmSgvsuy7wnCSHVtXhy10haRpVdWKS79MdJJJcp6r+b4WrNbiFgr8k966qj61EfSRpC1JjrfJV9cdu3rQk9fVm4HnAK4D9gAOBrfoWZs/hIpLsAHzaFj2tJUnuC7wMuBZtyOV1gDOq6s8WfeE6keQkv7OSVqMkHwQ+B7y22/V4YL+qut9K1UnS2pbkxKraO8lpVXXT8X19yusdVV4aVNXP2DjUVForXkhbWPl/q2o34C9oWTwvLfzOSlqtHgfcFvgBcDZwa+AxK1ojSWvdhd0Q9W8meWKS+wNX7FuYQxkWkWQ/4OcrXQ9pQn+oqvOSbJVkq6r6bJJXrnSlltFjV7oCkrSQqjoH+OuVroekdeVg4PLAk2kdBHcGFsxguhQGh0CS05ib6RBgB+CHwCOXv0bSVH6R5IrAccA7k5xDWwNn3UnygM3s3xmgqj64vDWSpE0leUZVvSTJq9n0eqP3emSSVFUndHd/RZtvOBWDw+be87YLOK+q1uUFtda9/YHfAU8BHkZbR+sFK1qj2blP9/MatKFan+m29wO+RFuzVJJW2je6nxtWtBaS1p1uKb6FGp16LcVnQhpJa16STwEHVNWPuu1rAm+pqruvbM0kSZJmp1u+bGQ74IHARVX1jD7l2XMorTPdUMt/o/WmhY0Lwm+/ohWbrV1GgWHnJ7QsrZK0aiS5IfD/gF0Zuwbr28IvSVV14rxdX0xyfN/yDA6l9eclwH2q6htbfOb6cUySo4B3d9sPAT69gvWRpIW8D3gd8Ebg4hWui6R1oFt6b2QrYG/alKJ+5TmsVFpfknyxqm630vVYbl2P6R26zeOq6kMrWR9Jmm+atcckaSFJvkObcxjgIuA7wAuq6gu9yjM4lNaXJK8C/gT4MHDhaL+ZOyVpZSU5FDgH+BBzj88/W6k6SdI4g0NpnUny5gV2V1U9atkrs0wupfMsJa0xXQv/fFVV11v2ykha05JsD+xUVd/stv8KuFz38FFV9ZNe5RocSlrrkpzFpW+epSRJupRK8nrgS1X1lm77LOATtADxoqp6XJ9yTUgjrROX8kWWf2JgKGm1SnLnqvpMN8phEw77l9TDLYHHjm1fUFVPAkjSa74hGBxK68mleZHlDUneg/MsJa1OdwQ+A9xngccK8FglaVLb1NwhoI8Yu3+VvoU6rFRaR5JsDfxbVf2/la7Lcro0zrOUJEmXXkm+Cty9qn48b/+1gU9U1Z59yrXnUFonkmxTVRcludQtY1FVB650HSRpS5JcBXgksCtj12DrfNi/pNl4KfDRJE8DTu727QX8e/dYLwaH0vpxPO2gcEqSI2iLLf969OB6HmKZZDvgIODPgO1G++05lLTKHAl8GTgN+OMK10XSGlZV70jyU+BFtOufAk4HnltVn+hbrsGhtP5sB5wH3JmNi6Ku9zktbwfOAO4OvAB4GBvnYErSarFdVT11pSshaX2oqk8CnxyyTOccSutEkrOBl7MxGMzYw1VVL1+Rii2DJCdX1S2SnFpVeya5DPD5qtp3pesmSSNJngL8CvgYc5Nn/WzFKiVpTUryj8B/be74keTOwOWr6mOTlGvPobR+bA1ckblB4ch6bwX6Q/fzF0luAvwYuMYK1keSFvJ72lyg57DxuFzA9VasRpLWqtNocw5/B5wEnEsbPbY7cHPg08CLJy3UnkNpnUhyUlXttdL1WAlJ/g74ALAn8GZakPzcqnrdilZMksYk+TZwq6r66UrXRdL6kGR34HbANYHf0qbVHFdVv+1VnsGhtD6MhlaudD0kSQtL8ingflX1m5Wui6T1J8lVgV/UFAGew0ql9eMuK12B5ZZk0cQO63mepaQ16de0jNKfZe6cQ5eykDSRJM8F3ltVZyS5LPAJ2nDSi5L8TVV9uk+5BofSOnEpTWhwpZWugCRN4MPdTZKm9RDghd39A4CtgB2BGwJvpc05nJjBoaQ1q6qev9J1kKSlqqq3JtmWdvEGcGZV/WGx10jSZvx+bPjo3YF3V9XFwDeS9I7xthqkapK0gpLsnORDSc7pbh9IsvNK10uSxiW5E/BN4DXAfwH/m+TPV7JOktasC5PcJMmOwH7Ap8Yeu3zfQg0OJa0HbwaOAK7V3T7a7ZOk1eRlwN2q6o5V9ee01v5XrHCdJK1NhwDvB84AXlFV3wFIci/g5L6Fmq1U0pqX5JSquvmW9knSSkpyalXtuaV9krRSnHMoaT04L8nDgXd32w8FzlvB+kjSQjYkeSPwjm77YcCGFayPpDVqgYztBfwU+MKoF7FXufYcSlrrklwXeDVwG9rB8UvAk6vq/1a0YpI0pks3/wTg9t2uzwP/VVUXbv5VkrSpJM9bYPcOtOHqh1bV4b3KNTiUJElaHl3yCKrq3JWui6T1J8kOwKeraq8+r3dYqaQ1K8mraT2FC3JhaUmrQZIAzwOeSJcMMMnFwKur6gUrWTdJ60tV/aw75vRitlJJa9kG4MTudt+x+6ObJK0GTwFuB9yyqnaoqh2AWwO3S/KUla2apPUkyX7Az3u/3mGlktaDJCdX1S1Wuh6SNF+Sk4G7VtVP5+3fEfiUxy5Jk0pyGpuOntoB+CHwyKo6o0+5DiuVtF7Y0iVptbrM/MAQ2rzDJJdZiQpJWvPuPW+7gPOq6tfTFGpwKEmSNFu/7/mYJC2oqr43f1+SxwCvn6Zch5VKWrOSXMDGHsPLA78ZPQRUVW2/IhWTpDFd8pmFWvMDbFdV9h5KmlqSk/pmKR2x51DSmlVVV1rpOkjSllTV1itdB0mXCr2zlF5SgD2HkiRJkrS2Jdm5qs6eqgyDQ0mSJElae5I8dYHdvwROrKpTJi7P4FCSJEmS1p4k7wL2AT7a7bo3cCqwK/C+qnrJROUZHEqSJEnS2pPkOOBeVfWrbvuKwMeBe9B6D/eYpLythq+iJEmSJGkZXAO4cGz7D8BOVfXbefuXxGylkiRJkrQ2vRP4SpKPdNv3Ad6V5ArA1yctzGGlkiRJkrRGJbklcNtu84tVtaF3WQaHkiRJkrQ2Jdka2ImxUaFV9X99ynJYqSRJkiStQUmeBDwP+AlwMRCggD17lWfPoSRJkiStPUnOAm5dVecNUZ7ZSiVJkiRpbfo+bdH7QTisVJIkSZLWpm8Dn0vyccaWrqiql/cpzOBQkiRJktam/+tu23a3qTjnUJIkSZJkz6EkSZIkrSVJXllVhyT5KC076RxVdd8+5RocSpIkSdLa8vbu578PWajBoSRJkiStIVV1Ynd3e+DjVfXHIcp1KQtJkiRJWpseAnwzyUuS3HjawkxII0mSJElrVJLtgYcCB9LmH74ZeHdVXTBpWfYcSpIkSdIaVVXnA+8HDgeuCdwfOCnJkyYty55DSZIkSVqDktyX1mN4A+BtwFur6pwklwe+XlW7TlKeCWkkSZIkaW16IPCKqjpufGdV/SbJQZMWZs+hJEmSJMmeQ0mSJElaS5JcQEs+s8lDQFXV9r3KtedQkiRJkmS2UkmSJElag5K8fSn7lsrgUJIkSZLWpj8b30iyDbB338IMDiVJkiRpDUnyD928wz2TnN/dLgB+Anykd7nOOZQkSZKktSfJv1TVPwxWnsGhJEmSJK09Sf58of3z1z1ccnkGh5IkSZK09iT56NjmdsCtgBOr6s59ynOdQ0mSJElag6rqPuPbSXYBXtm3PBPSSJIkSdL6cDbwp31fbM+hJEmSJK1BSV4NjOYJbgXcAjipb3kGh5IkSZK0Nn0d2Lq7/wvg3VX1xb6FGRxKkiRJ0hrSLXb/YuBRwP91u68DHJbk+Kr6Q59ynXMoSZIkSWvLS4EdgN2qaq+q2gu4HnAV4N/7FupSFpIkSZK0hiT5JnDDmhfMJdkaOKOqdu9Trj2HkiRJkrS21PzAsNt5MRsT1EzM4FCSJEmS1pavJ3nk/J1JHg6c0bdQh5VKkiRJ0hqS5NrAB4HfAid2u/cBLgfcv6p+0Ktcg0NJkiRJWnuS3Bn4s27z61V1zFTlGRxKkiRJkpxzKEmSJEkyOJQkSZIkGRxKkrSJJPdLssfY9guS/MVK1mkpktw8yb1Wuh6SpLXJ4FCSpE3dD7gkOKyq51bVp1euOkt2c2DB4DDJNstbFUnSWmNwKEla95LsmuQbSd6Q5PQkn0pyuSSPTnJCkq8m+UCSyye5LXBf4KVJTkly/SRvSfKgJPdI8r6xcu+U5GPd/bsl+Z8kJyV5X5IrLlCPnZJ8qPt9X+1+F0memuRr3e2QsTp/bey1/y/Jod39zyX5tyTHJ/nfJHdIsi3wAuAhXb0fkuTQJG9P8kXg7UmOS3LzsTK/kORmw//FJUlrkcGhJOnSYnfgNVX1Z8AvgAcCH6yqW1bVzYBvAAdV1ZeAI4CnV9XNq+pbY2V8Grh1kit02w8BDk9ydeAfgb+oqr2ADcBTF6jDfwDHdr9vL+D0JHsDBwK3BvYFHp3kFkt4P9tU1a2AQ4DnVdXvgecC7+nq/Z7ueXt09Xoo8CbgbwGS3BDYrqq+uoTfJUm6FDA4lCRdWnynqk7p7p8I7ArcJMnnk5wGPIyNa0UtqKouAj4J3KcbpvmXwEdoQd0ewBeTnAIcAFx3gSLuDLy2K+viqvolcHvgQ1X166r6FW1R4zss4f18cN572Zwjquq33f33AfdOchngUcBblvB7JEmXEs4/kCRdWlw4dv9i4HK04Oh+VfXVJH8L3GkJ5RwOPBH4GbChqi5IEuDornduKBcxtxF3u3mPj97PxSx+Pv/16E5V/SbJ0cD+wIOBvQeopyRpnbDnUJJ0aXYl4EddT9rDxvZf0D22kGNpQ0IfTQsUAb4M3C7JDQCSXKEbtjnfMcDfd8/ZOsmVgc8D9+vmO14BuH+37yfANZJcLcllgXsv4f0sVu+RN9KGt55QVT9fQpmSpEsJg0NJ0qXZPwFfAb4InDG2/3Dg6UlOTnL98RdU1cXAx4B7dj+pqnNpc/neneRU4H+AG8Mly2Dct3v5wcB+3TDWE4E9quokWg/m8V1d3lhVJ1fVH2gJZo4Hjp5Xv835LLDHKCHNQk+oqhOB84E3L6E8SdKlSKpqpesgSZKWSZJrAZ8DblxVf1zh6kiSVhF7DiVJupRI8kha7+RzDAwlSfPZcyhJkiRJsudQkiRJkmRwKEmSJEnC4FCSJEmShMGhJEmSJAmDQ0mSJEkSBoeSJEmSJOD/A9izANkmzHa5AAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 1080x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(15,8))\n",
+    "sns.countplot(x='native.country',data=df)\n",
+    "plt.xticks(rotation=90)\n",
+    "plt.ylabel('No. of Individuals')\n",
+    "df['native.country'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Majority of the people working belong from U.S. whereas there are people who come to U.S. from their own countries but there no. is very low. Second highest no. of people belong from Mexico as it is a neighboring country."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:16.020665Z",
+     "iopub.status.busy": "2021-07-05T16:35:16.020406Z",
+     "iopub.status.idle": "2021-07-05T16:35:16.5138Z",
+     "shell.execute_reply": "2021-07-05T16:35:16.512712Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:16.02064Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Minimum 17\n",
+      "Maximum 90\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 576x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(8,6))\n",
+    "sns.histplot(df['age'],kde=True,color='r')\n",
+    "plt.ylabel('No. of Individuals')\n",
+    "print('Minimum',df['age'].min())\n",
+    "print('Maximum',df['age'].max())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Minimum age of a working individual is 17 and highest is 90 which is way far retirement, but majority of the people working are in the age 25 to 45. Data is skewed to the right side."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:16.515521Z",
+     "iopub.status.busy": "2021-07-05T16:35:16.515168Z",
+     "iopub.status.idle": "2021-07-05T16:35:17.18091Z",
+     "shell.execute_reply": "2021-07-05T16:35:17.179988Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:16.51549Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Minimum 12285\n",
+      "Maximum 1484705\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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73/1uvv/979Pf3z+wz913383SpUtpaGgY86x5B1PLXkQk+kYNe3f/kbsf7+6fDl5vdPeLsl9aYWptbaWqqoqqqioALr30Upqbm3nkkdTKvq+++irPPPMMf/VXfzUpx0u37Hfs2DEp3yciIlPPsNPlmtmNwLAXg939s1mpqIC5O9u2bePwww8f2PaBD3yAOXPm8L3vfY/zzjuPu+++GzNjxYoV3HPPPRM+plr2IiLRN9Lc+GtzVoUAqcDdv38/8+bNG9hWVlbGJz/5Sb7+9a/zjW98g3vuuYczzjiDQw45ZFKOWVZWRmlpqcJeRCTChg17d78jl4UIA2vSDw57gC9+8YusX7+eL3zhCwBcddVVEx6Fn2Zm1NbWKuxFRCJs1FXvzKwO+CKwBChPb3f3s7JYV0Hau3cvZWVlVFZWvml7TU0NDz/8MA899BD33HMPL7zwAn/6058mPDgvTWEvIhJtmYzGvxtYDywEGoHXgWeyWFPBGmlNejPjoosu4sYbb2TmzJmTFvSgsBcRibpMwn6Wu98G9Lr7b9z9k4Ba9VkwUthnk8JeRCTaMgn73uDnNjM738xOAGZmsaaCpbAXEZFsGPWaPXCDmc0A/gG4EagGrslqVQUomUzS09MTWtjv2LEDd8fMcn58ERHJrlHD3t3TU+TuAc7MbjmFK5FI4O5Mnz4958eura2lr6+Pzs5Oqqurc358ERHJrkxG4/+AISbXCa7dyyTp7OwEeMtI/FyYOTN1Vaajo0NhLyISQZl04w9e/KYc+BDQOsy+Mk5dXV0AobXsIRX2CxcuzPnxRUQkuzLpxn9w8Gszuxf4n6xVVKDSYR/WNXvQlLkiIlGVScv+YIuAOZNdSKHr6uqiqKhoYK56SM2VH4/HB17PnTs3K8dW2IuIRFsm1+w7SV2zt+BnnNSMejKJurq6iMVibxoNn0gkWLVqFfX19XR1dbFy5cqsHFthLyISbZl041flopBC19nZOWQXfiwWG1juNltmzJgBKOxFRKJqpCVuTxzpg+7+x8kvJz8kk8mB7vW5c+dSVJTJ3EQj6+rqYvbs2RP+nvEoKSmhpqZGa9qLiETUSC37bwY/y4FlwPOkuvKPJ7X87anZLW3qisfjNDY2ArBy5cq3rFI3Vu5OV1fXm9axz7X6+nra29tDO76IiGTPSEvcnglgZg8BJ7r7n4PXbwOuz0l1U9hk3g+/a9cu+vv7Q7ntLj0IsLa2lra2tpwfX0REsi+T0fjHpIMewN1fMLPFWayp4KQvCYQxoU56EKBa9SIi0ZVJ2K8zs1uBfw9efwxYl72SCs+2bduAcCbUgdQgwOrqajZu3BjK8UVEJLsyGVl2OfAi8Lng0RRsk0mSbtmHMaFOWiwWY+/evezbty+0GkREJDsyufVuH/Ct4CFZkA77sFr2g4/d1tYW6kBBERGZfMO27M3sgeDnn81s3cGPiRzUzK4xsxfN7AUzu9fMys1soZk9bWYbzOx+MysL9p0WvN4QvL9gIseeirZv305FRQXFxcWh1ZDuVRg8Y5+IiETDSC37zwU/PziZBzSzBuCzwBJ37wl+qfgocB7wLXe/z8xuAa4Abg5+7nL3o8zso8C/AH89mTWFJX2/fmtrKxUVFaHWMrhlLyIi0TJsy97dtwVPLwJ63X3z4McEj1sCVJhZCTAd2AacBfw4eP8O4MLg+YrgNcH7Z9vgOWXzWPp+/T//+c+UlZWFWota9iIi0ZXJAL0q4FEz+62ZfcbM6idyQHdvAf4VaCYV8nuAZ4Hd7t4X7LYVaAieNwBbgs/2BfvPOvh7zexKM1trZmu3b98+kRJzqrKykgMHDrxpAZwwpHsW1LIXEYmeUcPe3RvdfSlwNXAI8Bsz++V4D2hmtaRa6wuBeUAMWD7e7xtU52p3X+buy+rq6ib6dTm1b9++0Lvx01PmKuxFRKJnLEvctpNa8a6DiS1x+z5gk7tvh4EZ+k4DasysJGi9Hwq0BPu3APOBrUG3/4yghkhIJpPs27dv1Jb94OVu3T0rtdTV1akbX0QkgjJZ4vbTwEeAOuBHwKfcvWkCx2wGTjGz6UAPcDapufYfBz4M3AdcBvw02H9N8Pr3wfuPebbSLgT79+8HGLVln57pDrJ3P/7s2bPVshcRiaBMWvbzgf/t7s9NxgHd/Wkz+zHwR6AP+BOwGvgv4D4zuyHYdlvwkduAu8xsA7CT1Mj9yOju7gbI6Jp9tifdqauro6lpIr/HiYjIVDTSErfV7r4X+Ebweubg991953gP6u4rgZUHbd4IvHOIffcBF4/3WFNdT08PkFnYZ1tdXZ1a9iIiETRSy/4eUvfYPws4qeVt0xw4Iot1FYyxtOyzra6ujs7OTrq7u0OdzU9ERCbXSEvcfjD4uTB35RSedMs+7NH4AHPmpMZdtrW1sXCh/thFRKJipG78E0f6oLv/cfLLKTxTqRt/9uzZQGpiHYW9iEh0jNSN/83gZzmwDHieVFf+8aRGz5+a3dIKQ09PD6WlpaHOi582uGUvIiLRMdJ0uWe6+5mkZrk7MZiw5iTgBN64B14mqLu7e0p04bv7wP3727ZtG2VvERHJJ5lMl3uMu/85/cLdXwAWZ6+kwtLT0zMluvATiQR33nknAK+99lrI1YiIyGTK5D77dWZ2K/DvweuPARNa4lbe0NPTMyVa9gBVVVWUl5fT3t4edikiIjKJMmnZXw68SGrJ288BTcE2mQTd3d1TomWfVllZqWv2IiIRM2rLPpjU5lvBQyaRu0+JRXAGq6qqoqVFQzJERKIkk7nxTwOuBw4fvL+7a1KdCerq6qK/v39KteyrqqrYsmVL2GWIiMgkyuSa/W3ANaRm0uvPbjmFpaMjtXjfVGrZV1dXs2vXLs2iJyISIZlcs9/j7j9393Z370g/sl5ZAUiH/VRq2VdWVgKodS8iEiGZhP3jZvYNMzvVzE5MP7JeWQGYimFfVVUFQHNzc8iViIjIZMmkG//k4OeyQdscOGvyyyksO3emFg6cSmFfXV0NqGUvIhIlmYzGPzMXhRSidNhPpWv2lZWVmJnCXkQkQkZaCOfzI33Q3VdNfjmFpaOjg+LiYkpKMulgyY3i4mLmzJmjbnwRkQgZKWWqclZFgero6GD69OmYWdilvMm8efPUshcRiZCR1rNvzGUhhWjHjh1T8va2efPmsWHDhrDLEBGRSZLJaHzJkqkc9lu2bBlYBU9ERPKbwj5EUznsu7u7BwYQiohIfhs27M3sc8HP03JXTuFwdzo6OqbUSPy0hoYGQLffiYhExUgt+/TKdjfmopBCs3fvXg4cODBlW/agsBcRiYqRRuOvN7NXgXlmNnj9egPc3Y/PbmnRll4zfiqGfbplr9vvRESiYaTR+JeY2VzgEeCC3JVUGKZy2M+ePZvS0lK17EVEImLE2VzcPQ683czKgKODzS+7e2/WK4u4qRz2RUVFzJ8/n82bN4ddioiITIJM1rM/HbgTeJ1UF/58M7vM3Z/Icm2RNpXDHuCII45g48aNYZchIiKTIJNb71YB57j76e7+XuADwLeyW1b0pcN+Ko7GBzjyyCN57bXXwi5DREQmQSZhX+ruL6dfuPsrQGn2SioMbW1t1NTUUFxcHHYpQzryyCPp6OigqamJZDIZdjkiIjIBmYT9WjO71czOCB7fB9Zmu7Coa29vZ9asWWGXMax0bddddx3xeDzkakREZCIyWW7t74Crgc8Gr38LfDdrFRWI9vZ2Zs+eHXYZw1qwYAEA+/fvD7cQERGZsEzWs99P6rq9lrQ9iLsPtHrnzp1LUVHmsw+3t7ezcOHCbJU2YYcffjgAe/bsCbkSERGZKM2NPwGJRIJVq1bR2Ng45q7uqdqyT/8Cs2fPHiorK9m9e3fYJYmIyARl0o0vI4jFYlRWVo7pM319fXR0dEzJsE//AgNQVVWlsBcRiQC17EOwY8cOgCkZ9pD6BSYWi1FdXa2wFxGJgHGFvZldOZGDmlmNmf3YzF4ys/VmdqqZzTSzR83s1eBnbbCvmdl3zGyDma0zsxMncuypIH2P/VQN+7Tq6moSiQSJRCLsUkREZALG27K3CR7328B/u/uxwNuB9cC1wK/cfRHwq+A1wLnAouBxJXDzBI8dunwJ+xkzZgBo2lwRkTw3rrB39++N94BmNgN4L3Bb8F0H3H03sAK4I9jtDuDC4PkK4E5PeQqoMbNDxnv8qSAd9lP5PntItewBXn/99XALERGRCRk17M3sUDN72My2m1m7mT1oZodO4JgLge3AD8zsT8GEPTGg3t23BfvEgfrgeQMwePm1rcG2vNXW1gZM/Za9wl5EJBoyadn/AFgDHALMA/4j2DZeJcCJwM3ufgKQ4I0uewDc3QEfy5ea2ZVmttbM1m7fvn0C5WVfe3s7JSUlA93kU1VZWRnTp09X2IuI5LlMwr7O3X/g7n3B44dA3QSOuRXY6u5PB69/TCr829Ld88HP9uD9FmD+oM8fGmx7E3df7e7L3H1ZXd1Eysu+trY25syZg9lEhz5kX01NjRbEERHJc5mEfYeZXWpmxcHjUqBjvAd09ziwxcyOCTadDTSR6j24LNh2GfDT4Pka4OPBqPxTgD2Duvvz0pYtW5g/f/7oO04BM2fO5NVXXw27DBERmYBMwv6TwEdIXUffBnwYuHyCx/174G4zWwe8A/hn4GvA+83sVeB9wWuAnwEbgQ3A94FPT/DYodu8eTOHHXZY2GVkZNasWXR0dDDVL42IiMjwMpkbfzNwwWQe1N2fA5YN8dbZQ+zrpBbiiQR3p7m5mRUrVoRdSkbSdwysX7+eqX55REREhjZs2JvZ/xvhc+7uX8lCPZHX3t7O/v3786plD9DU1MR73/vekKsREZHxGKllP9S0aTHgCmAWoLAfh+bmZuCNVeWmusrKSiorK3nxxRfDLkVERMZp2LB392+mn5tZFfA5Utfq7wO+OdznZGTp2ejypWVvZixatIimpqawSxERkXEacYBeMF/9DcA6gvvj3f2L7t4+0udkePnWsgc4+uijFfYiInls2LA3s28AzwCdwHHufr2778pZZRG1efNmKisrqampCbuUjB199NHE43F27twZdikiIjIOI7Xs/4HUjHnXAa1mtjd4dJrZ3tyUFz3Nzc0cfvjheTGhTtrRRx8NpEbki4hI/hk27N29yN0r3L3K3asHParcvTqXRUbJ5s2b86oL392pra0F4IUXXgi5GhERGY/xLnEr49Tc3Jw3g/MAEokE99xzDyUlJTzzzDNhlyMiIuMw6qQ6Mrre3l56e3tJJpPE43EA5s6dS1HRm3+XSiQSdHR05FXLHlK3382aNYuXX3457FJERGQc1LKfIHfn3nvv5bOf/SzxeJzGxkYaGxsHQn+w9Ej8fGrZp9XV1fHCCy+QmtBQRETyicJ+gnbu3MmOHTtYs2YNL7zwwsAkNENJ32Ofby17gPr6enbv3j1wDiIikj8U9hO0adMmAKqqqli1atWI++Zzy76+vh6AZ599NuRKRERkrBT2E7Rp0yYaGhq46qqreOSRR2hraxt239dff53i4mIAkslkrkqcFLNnz6akpERhLyKShxT2E7B792527drFokWLuOKKK6ipqWHt2rXD7v/SSy9RUVHBDTfcMOQ1/amspKSEY445RmEvIpKHFPYTkO7CX7RoEdXV1Zx//vls2rSJ/v7+Ifd/7rnnqK+vJxaLEY/HicfjeTXg7fjjj+fZZ5/Nq5pFRERhPyGvv/46c+bMoaqqCoD3ve99HDhwgK1bt75l3+3bt7Np0ybmzZtHIpFg1apVrFq1ikRiqMUFp6bjjjuOjo6OgbEHIiKSHxT24+Tu7Nq1a2DgGsB73vMeiouL2bhx41v2f+qppwA45JBDAIjFYsRisdwUO0mOP/54QIP0RETyjcJ+nA4cOEBfXx/Tp08f2FZRUcFhhx3Gxo0b39LV/eSTT1JSUvKmXw7yzeLFiykpKRlxXIKIiEw9CvtxSne/Dw57gCOOOII9e/bw2muvvWn773//e972trdRWlqasxonW3l5OUuXLlXLXkQkzyjsx6mrqwvgLV3xRxxxBAC//OUvB7b19vbyzDPPcNJJJ+WuwCx517vexZNPPklvb2/YpYiISIYU9uM0XMu+qqqKuro6HnzwwYGu/HXr1tHd3R2JsD/rrLPo6upS615EJI8o7MdpuLAHOOmkk2hqauKnP/0pkOrCB1i2bFnuCpxk7k48HufYY48F4LHHHgu5IhERyZTCfpy6urooKSkZ8hr8sccey8KFC1m5ciV79+7lnnvuoaGhgYaGhhAqnRzp2wVvvPFGlixZorAXEckjCvtxSiQSTJ8+HTN7y3tFRUV8/vOfZ926dSxevJg//OEPfPWrXw2hyskVi8WorKzkXe96F7/73e/Yt29f2CWJiEgGFPbj1NXVNWQXftqKFStYvHgxnZ2d/Od//ieXXXZZDqvLrtNOO419+/YNzB0gIiJTW0nYBeSrRCLBzJkzh32/uLiYxx9/nP7+fubNm5fDyrLvlFNOoaioiMcee4wzzjgj7HJERGQUatmPU7obH94YvHbwXPf19fWRC3qA6upqli1b9qbbC0VEZOpSy34curq66O3tHbjHPj14Dd64rh11559/Ptdffz0tLS15PfBQRKQQqGU/DunlaQdfs8/Hue4n4q//+q9xd370ox+FXYqIiIxCYT8O7e3twND32BeKY445hne84x3cf//9YZciIiKjUNiPQ1tbG1DYYZ9MJjn33HN56qmn2LRpU9jliIjICBT245AO+0Lqtj9YPB4fCPnbb7895GpERGQkCvtxaGtrG3b2vKEkk0laW1vfMlo/Hw2+8+CQQw6hvr6en/zkJ2GXJSIiI9Bo/HFob28nFosNOXveYMlkciAYb7nlFrq7u/O+N+DgOw+WLFnC448/zrPPPhuJhX5ERKJILftxaGtry+j2ung8TmNjI6tWrcLM8j7o0wbfebBkyRIqKir43ve+N9CD0draSjKZDLlKERFJCy3szazYzP5kZv8ZvF5oZk+b2QYzu9/MyoLt04LXG4L3F4RVc1pbW1vGwV1ZWRmZkB/KtGnTuPDCC7nnnnt45ZVXaGxspLGxceD2RBERCV+YLfvPAesHvf4X4FvufhSwC7gi2H4FsCvY/q1gv1Bt3769oEfiH+zSSy8lkUjw0EMPUVlZWRCTComI5JNQwt7MDgXOB24NXhtwFvDjYJc7gAuD5yuC1wTvn22jXSzPot7eXjo7O6moqAirhCnF3amvr+e4447jBz/4gbrvRUSmoLBa9v8GfAFIJ8MsYLe79wWvtwLpOVgbgC0Awft7gv3fxMyuNLO1ZrZ2+/btWSt89+7dAJSXlw+7z3Bz5UdRIpHgW9/6FvX19WzYsEH33IuITEE5D3sz+yDQ7u7PTub3uvtqd1/m7svq6uom86vfZNeuXcDIYZ8esb5q1SoSiUTWapkqYrEYf/EXf0FpaSlNTU1hlyMiIgcJ49a704ALzOw8oByoBr4N1JhZSdB6PxRoCfZvAeYDW82sBJgBdOS+7JSdO3cCI4c9FN6EO2VlZSxatIiXX36Znp6esMsREZFBct6yd/cvufuh7r4A+CjwmLt/DHgc+HCw22XAT4Pna4LXBO8/5iH2jafDftq0aWGVMGUtXryY/v5+te5FRKaYqXSf/ReBz5vZBlLX5G8Ltt8GzAq2fx64NqT6gDfCXgP03mrWrFnU19ezbt26yI9VEBHJJ6GGvbv/2t0/GDzf6O7vdPej3P1id98fbN8XvD4qeH9jmDVncs2+kC1evJhdu3bx+9//PuxSREQkMJVa9nlB3fgjO+KII5g2bRp33XVX2KWIiEhAYT9GO3fupKqqiqIi/acbSklJCUuXLuXnP//5wOqAIiISLiXWGO3atYuampqwy5jSjj/+eHp7e/nBD34QdikiIoLCfsx27typsB/FzJkzOfXUU1m9erVm1BMRmQIU9mO0c+dOZsyYEXYZU5q7c8EFF7Bp0yYeeeSRsMsRESl4CvsxUst+dIlEgueff57y8nK+853vhF2OiEjBU9iPka7ZZ6a6uprjjjuORx99lJaWltE/ICIiWaOwHwN3V8t+DI477jj6+/u57bbbRt9ZRESyRmE/Bl1dXfT19SnsM1RTU8MZZ5zB6tWrOXDgwKj7J5NJWltbaW1t1cA+EZFJpLAfg/TseQr7zH3qU5+ipaWFf/3Xfx01xOPxOI2NjTQ2NhKPx3NYpYhItCnsxyA9e57CPnOnn346p556KjfccAPXXXfdqCFeWVlJZWVljqoTESkMCvsxSIe9br3LnJnxpS99iZ6eHl5++eWwyxERKUgK+zFQy35s3J14PE5DQwNHHXUUa9eu1ch8EZEQlIRdQD7p6OgAoLe3V0u4ZiCRSLBq1SoAli1bRnNzM5/5zGd48sknKS4uDrk6EZHCoZb9GDQ3NwNwxx13kEgkQq4mP8RiMWKxGNXV1Zx11ln84Q9/4Nprr9VoexGRHFLYj8Hu3bspLi6muro67FLy0mGHHcaCBQv45je/qZn1RERySGE/Bnv27KG8vBwzC7uUvHXmmWcyf/58rrnmGm688cawyxERKQgK+zHYtWsX5eXlYZeR10pLS7nwwgv5wAc+wGc/+9mBBXNERCR7FPZjsHv3boX9JCgpKWH16tV84xvf4LHHHmPp0qV897vf1aBHEZEsUdiPwZ49e5g2bVrYZeQ9d2fHjh38zd/8DU1NTbz3ve/l6quv5vLLL6e3tzfs8kREIkdhPwZq2U+O9C15119/PTt27ODWW29l1apV/PKXv+SJJ54IuzwRkcjRffZjsHv3burr68MuIxJisRgAq1atIhaLsXLlSl566SVWr17NkUceGXJ1IiLRopZ9hg4cOEAikVDLfpKl78OPx+N84hOfYObMmTzyyCPs2bMn7NJERCJDYZ+h9Ox5FRUVIVcSPelu/ZtuuonTTz+dRCLBzTffrKVuRUQmibrxM5QOe7XssyPdrR+LxZg3bx633XYbPT09NDY2Mm/evJCrExHJb2rZZ0gt+9xZunQp3d3dtLe3h12KiEgkKOwzlF7xTi377Dv88MOJxWI899xzYZciIhIJCvsMqRs/d4qKili6dCnNzc28+uqrYZcjIpL3FPYZUjd+bh1zzDEUFRXxwAMPhF2KiEjeU9hnqKOjg2nTplFSojGNuVBRUcGCBQt46KGH6O/vD7scEZG8prDPUEdHB7W1tVrxLocWL15MPB7n17/+ddiliIjkNYV9htJhL7lzxBFHUFVVxV133RV2KSIieU1hn6GOjg5qamrCLqOglJaWcv755/Pggw/S3d0ddjkiInlLYZ8htezDcdFFF9HV1cWDDz4YdikiInkr52FvZvPN7HEzazKzF83sc8H2mWb2qJm9GvysDbabmX3HzDaY2TozOzHXNYPCPiynnHIKRx11FKtXrw67FBGRvBVGy74P+Ad3XwKcAlxtZkuAa4Ffufsi4FfBa4BzgUXB40rg5lwX7O7s3LlTYZ9j7k57ezsf/ehH+Z//+R9efPHFsEsSEclLOQ97d9/m7n8MnncC64EGYAVwR7DbHcCFwfMVwJ2e8hRQY2aH5LLmvXv30tfXp7DPsfQCOZs3b6asrEytexGRcQr1mr2ZLQBOAJ4G6t19W/BWHEgvHN8AbBn0sa3BtoO/60ozW2tma7dv3z6pdaYn1FHY514sFqOuro5zzz2XO++8k56enrBLEhHJO6GFvZlVAg8C/9vd9w5+z90d8LF8n7uvdvdl7r6srq5uEitV2E8Fl156Kbt37+amm27S0rciImMUStibWSmpoL/b3R8KNrelu+eDn+klz1qA+YM+fmiwLWcU9uE79dRTOf744/nyl7/MypUricfjYZckIpI3whiNb8BtwHp3XzXorTXAZcHzy4CfDtr+8WBU/inAnkHd/TmhsA+fmXHNNdfQ2dnJli1bRv+AiIgMCGOi99OAvwX+bGbPBdv+L/A14AEzuwLYDHwkeO9nwHnABqAbuDyn1fLG8rYK+3C4O/F4nOOOO445c+bw1FNP0dfXF3ZZIiJ5I+dh7+7/Aww3wfzZQ+zvwNVZLWoU6Zb9jBkzwiyjYKVH5QO84x3v4Be/+AUPPvgg11xzTciViYjkB82gl4H0VLla8S48sViMWCzG4Ycfzty5c/na177G3r17R/+giIgo7DPR0dHBrFmzwi5DSF27P+uss2hvb+eGG24IuxwRkbygsM+Awn5qqa+v54ILLuDf/u3fWL9+fdjliIhMeQr7DCjsp5ZEIkFJSQlmxuWXX6577kVERqGwz4DCfuqZPXs2Z555Jk8//TQ33nhj2OWIiExpCvsMKOynpsWLF/Oe97yHa6+9lpdeeinsckREpiyF/SgOHDhAZ2enwn4K6u7upq6uDnfnQx/6EF1dXWGXJCIyJeleslEUFxezbt06hf0UNXv2bD74wQ/y8MMPc9lll/Gd73yH1NQMUFRUxNy5cykq0u+0IlLYFPajKC4u5rjjjgOgtbU15GpkKIcffjj/9E//xFe+8hU2b97MscceC6TuzV+5ciXz5s0LuUIRkXCpySORcNVVV3HxxRfz7LPP0tLSQiwWo7KyMuyyRESmBIW9RIKZ8fWvf53DDjuM3/zmN2zdujXskkREpgyFvURGWVkZf/mXf0ltbS2PPvoo27dvD7skEZEpQWEvkTJt2jSWL19OWVkZDz/8sMZZiIigsJcISC+BG4/HcXcqKytZvnw5Bw4c4IorrmDfvn1hlygiEiqNxpe8N3gJ3FgsBsCsWbNYvnw5a9as4XOf+xwrV64c2F+344lIoVHYSySkQ36wo446iquvvpqbbrqJV155hRNPPJGuri7djiciBUfNG4m0L3zhC5x66qn89re/pbu7W7fjiUhBUthLpJWUlHDzzTdTXl7OAw88wP79+8MuSUQk5xT2ElnpgXv9/f2cf/757N69m//+7/8emE5XRKRQKOwlstID91atWkVNTQ3vf//7ee2117jlllvCLk1EJKcU9hJpsVhsYPDeySefzNFHH80///M/8+tf/zrcwkREckhhLwXDzDjnnHNYuHAhF154IU8//XTYJYmI5ITCXgpKWVkZ9957L7NmzeKcc87hySefDLskEZGsU9hLQXF3iouLue+++5g5cyZnnXUWt956a9hliYhklcJeCkp60N63v/1tTjrpJGbNmsWnPvUpLrnkEnbv3h12eSIiWaGwl4KTHrQ3a9YszjvvPJYuXcr999/Psccey1133UUymQy7RBGRSaWwl4JWVFTEaaedxgUXXEBPTw8f//jHOeuss3j++efDLk1EZNIo7EWA+vp6Lr74Yk4//XSee+45TjjhBC6++GKeeeYZtfRFJO8p7EUCxcXFHHPMMbz//e/n2GOP5aGHHuKUU07hYx/7GC+++GLY5YmIjJtWvRM5yMyZM3nPe97DO97xDpqamnj44Ye57777OOGEE7jooou4+OKLOfLII2lraxto9RcVFWnpXBGZshT2IsOoqqri5JNP5qijjmLTpk1s3LiR6667juuuu46GhgYqKiqora1lzpw5zJs3j+uvv15L54rIlKSwFxnFrFmzmDVrFieddBJ9fX0cddRR/O53v+M3v/kNGzZsAKC8vJx9+/Zx1VVX8a53vQszG/K7kskk8XgcQD0BIpIzCnuRDJkZNTU1LF++nOXLl3PXXXcRj8eJx+Ns27aNBx54gLvuuouFCxdyySWXcO6553LyySdTWlo68B3xeJzGxkYAVq5cqZ4AEckJi+Jyn8uWLfO1a9dO2velW2PxeJx///d/J5FITNp3Z+KQQw5h27ZtOT3mWBVSjek///QCO2m7d++mvb2d/fv38/TTT5NMJikvL+ewww5j3rx5lJaWYma0tLRQWlrK2WefzbJly3j3u99NQ0PDsL0BIiKZMLNn3X3ZUO/lTcvezJYD3waKgVvd/Wu5Ona6NZZIJN7yD7wUnuH+DtTU1FBTU0MikaChoYH29nZ27drF3Llz2b59O1u2bOHAgQMkk0kOHDjAc889N/DZGTNmsGjRIo4++mgaGhpYtGgRM2bM4MCBA0ybNo3p06cTi8U4/PDDqaurY+/evYAuBYhIZvIi7M2sGLgJeD+wFXjGzNa4e1OuaqisrMzVoSTPpWfomzlzJpDqCZgzZw7vfOc7B/Zxd3p6eti9ezfxeJw9e/bQ3NzMiy++SE9Pz6jHqKiooKqqihNOOIFFixaxZMkSFi5cSCwWo7a2ltmzZwOpXqne3l7i8Ti9vb309/cDqQWBysvLmT9/PhUVFUybNo2ioqI3jScAMh5foLEIIlNbXoQ98E5gg7tvBDCz+4AVQM7CXmS8huoJMDOmT5/O9OnT33Td/pBDDmHLli10dHTQ29tLWVkZvb299PX10dfXRyKRoKenh/3799PZ2cnvfvc7fvGLXzAZl+OKioowM4qLi6msrKS0tJTu7m6Ki4uZN28eNTU1xGIxKisrKS4upqioiOLiYoqLi9m/fz9NTU2YGW9/+9upqqqiuLiY6upqamtrmTlzJkceeSTTp08f+FxRURHJZJLt27eTTCZJJpOYGTNnzqS0tJSysjKmTZv2pkdJSQnuPvDo7+8nHo/j7tTX12NmA/8tzGzgkT43Mxs4VvqR/o5kMsns2bMHakt/brjnB3/vUM8HS9ecTCYHfvb39w/8QrZt2zaSySR1dXWUlpYO/Lcd/Bjqew+WPv8oXqLNN5lcmsvV5bt8CfsGYMug11uBk3NZQFdXV86v1ad1dnaGduxMqcbJ0dnZyf79+8fUk1RRUcGHPvQhWltbufvuu+nq6qK3txd44x+S8vLygSACBoJm3759bwq94uLigcsM/f39VFRUkEwm6ejoIB6P09/fj7sPfP/g4E1/7/r169+yvVAN/uVjsqR7TRTq+e8nP/kJK1asyMmx8iXsR2VmVwJXBi+7zOzlCX7lbGDHBL9jqoryuUG0z2/Ic4vIMr2R+3MbFMSTdm5TcPrmyP25DZLVc7vwwgsn+ysPH+6NfAn7FmD+oNeHBtsGuPtqYPVkHdDM1g43qjHfRfncINrnp3PLTzq3/BSlc8uXUTTPAIvMbKGZlQEfBdaEXJOIiEheyIuWvbv3mdlngEdI3Xp3u7trZRIREZEM5EXYA7j7z4Cf5fCQk3ZJYAqK8rlBtM9P55afdG75KTLnFskZ9EREROQN+XLNXkRERMap4MPezJab2ctmtsHMrh3i/Wlmdn/w/tNmtiCEMsclg3P7vJk1mdk6M/uVmQ1728ZUM9q5DdrvIjNzM8ubEbWZnJuZfST4s3vRzO7JdY0TkcHfy8PM7HEz+1Pwd/O8MOocKzO73czazeyFYd43M/tOcN7rzOzEXNc4Xhmc28eCc/qzmT1pZm/PdY3jNdq5DdrvL8ysz8w+nKvaJtXgyS8K7UFqsN9rwBFAGfA8sOSgfT4N3BI8/yhwf9h1T+K5nQlMD57/XZTOLdivCngCeApYFnbdk/jntgj4E1AbvJ4Tdt2TfH6rgb8Lni8BXg+77gzP7b3AicALw7x/HvBzwIBTgKfDrnkSz+1dg/4+nhulcwv2KQYeIzVu7MNh1zyeR6G37Aem4XX3A0B6Gt7BVgB3BM9/DJxt+bE82ajn5u6Pu3t38PIpUvMX5INM/twAvgL8C7Avl8VNUCbn9ingJnffBeDu7TmucSIyOT8HqoPnM4DWHNY3bu7+BLBzhF1WAHd6ylNAjZkdkpvqJma0c3P3J9N/H8mvf0sy+XMD+HvgQSCf/l97k0IP+6Gm4W0Ybh937wP2ALNyUt3EZHJug11BqtWRD0Y9t6CLdL67/1cuC5sEmfy5HQ0cbWa/M7OnghUh80Um53c9cKmZbSXVkvr73JSWdWP9fzJf5dO/JaMyswbgQ8DNYdcyEXlz651kj5ldCiwDTg+7lslgZkXAKuATIZeSLSWkuvLPINWCesLMjnP33WEWNYkuAX7o7t80s1OBu8zsbe4+5eaJlTczszNJhf27w65lEv0b8EV3T+ZHp+7QCj3sR52Gd9A+W82shFS3YkduypuQTM4NM3sf8E/A6e6+P0e1TdRo51YFvA34dfA/51xgjZld4O5rc1bl+GTy57aV1DXRXmCTmb1CKvyfyU2JE5LJ+V0BLAdw99+bWTmpOcrztgs1kNH/k/nKzI4HbgXOdfd8+DcyU8uA+4J/S2YD55lZn7v/JNSqxqjQu/EzmYZ3DXBZ8PzDwGMejNiY4kY9NzM7AfgecEGeXfcd8dzcfY+7z3b3Be6+gNQ1xHwIesjs7+RPSLXqMbPZpLr1N+awxonI5PyagbMBzGwxUA5sz2mV2bEG+HgwKv8UYI+7bwu7qMlgZocBDwF/6+6vhF3PZHL3hYP+Lfkx8Ol8C3oo8Ja9DzMNr5l9GVjr7muA20h1I24gNYjjo+FVnLkMz+0bQCXwo+C31mZ3vyC0ojOU4bnlpQzP7RHgHDNrAvqB/5MvLakMz+8fgO+b2TWkBut9Ih9+wTaze0n9EjY7GG+wEigFcPdbSI0/OA/YAHQDl4dT6dhlcG7/j9RYpu8G/5b0eZ4sIJPBuUWCZtATERGJuELvxhcREYk8hb2IiEjEKexFREQiTmEvIiIScQp7ERGREGW6GM+g/ce8EJbCXkTewsw+a2brzezuEfbpmoTjfMLM5k30e0Ty3A8JJpIajZktAr4EnObuS4H/ncnnFPYiMpRPA+93949l+TifABT2UtCGWozHzI40s/82s2fN7Ldmdmzw1rgWwlLYi8ibmNktpJag/bmZ7Qm6GH9tZhvN7LND7H+TmV0QPH/YzG4Pnn/SzL4aPP//LLWG/f+Y2b1m9o/BuuDLgLvN7Dkzq8jdWYpMeauBv3f3k4B/BL4bbB/XQlgFPYOeiLyVu/+v4B+QM4HPAOcEz6uAl83s5mBe/rTfAu8hNR1sA5BetvU9pOYU/wvgIuDtpGYm+yPwrLv/OJhN7x/zZCpjkZwws0rgXbwxuynAtODnuBbCUsteREbzX+6+3913kFqMpv6g938LvMfMlgBNQFuwTvupwJPAacBP3X2fu3cC/5HD2kXyURGw293fMeixOHhvK7DG3XvdfROQXghr1C8UERnJ4NUQ+zmoR9DdW4AaUgOMniAV/h8BuoJwF5ExcPe9pFa0vBggWDzp7cHbP2EcC2Ep7EVkMjxFalRwOuz/MfgJ8DvgL82sPOie/OCgz3WSujwgUrCCxXh+DxxjZlvN7ArgY8AVZvY88CKwItj9EaAjWAjrcTJcCEvX7EVkMvwWOMfdN5jZZmBmsA13f8bM1gDrgDbgz8Ce4HM/BG4xsx7gVHfvyXnlIiFz90uGeestg++CFSA/HzwyplXvRCTrzKzS3bvMbDqp1v+V7v7HsOsSKRRq2YtILqwOBvCVA3co6EVySy17ERGRiNMAPRERkYhT2IuIiEScwl5ERCTiFPYiIiIRp7AXERGJOIW9iIhIxP3/mjJ9LgR3TW4AAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 576x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(8,6))\n",
+    "sns.histplot(df['fnlwgt'],kde=True,color='k')\n",
+    "plt.ylabel('No. of Individuals')\n",
+    "print('Minimum',df['fnlwgt'].min())\n",
+    "print('Maximum',df['fnlwgt'].max())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "It is assigned by combination of features and has the peak wt as 0.2*1e6. Data does not follow normal distribution and data is rigt skewed."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:17.182335Z",
+     "iopub.status.busy": "2021-07-05T16:35:17.182055Z",
+     "iopub.status.idle": "2021-07-05T16:35:17.609944Z",
+     "shell.execute_reply": "2021-07-05T16:35:17.609082Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:17.182307Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Minimum 0\n",
+      "Maximum 99999\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x864 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(15,12))\n",
+    "sns.distplot(df['capital.gain'],color='m', kde_kws={\"color\": \"k\"})\n",
+    "print('Minimum',df['capital.gain'].min())\n",
+    "print('Maximum',df['capital.gain'].max())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Minimum capital gain is 0 while the range goes on to 99999 but most of the people are with the gain of 1000. Data is highly skewed with a very long tail due to presence of large outliers. Outliers here are very few people belonging to elite class who have very large capital gains."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:19.026256Z",
+     "iopub.status.busy": "2021-07-05T16:35:19.025814Z",
+     "iopub.status.idle": "2021-07-05T16:35:19.455618Z",
+     "shell.execute_reply": "2021-07-05T16:35:19.454778Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:19.02621Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Minimum 0\n",
+      "Maximum 4356\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x864 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(15,12))\n",
+    "sns.distplot(df['capital.loss'],color='g', kde_kws={\"color\": \"k\"})\n",
+    "print('Minimum',df['capital.loss'].min())\n",
+    "print('Maximum',df['capital.loss'].max())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Minimum capital loss is 0 while the range goes on above 4000 but most of the people are with the loss of 1000. There is also a slight peak seen near 2000. Data is highly skewed with a long tail to the right side."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:19.457101Z",
+     "iopub.status.busy": "2021-07-05T16:35:19.456823Z",
+     "iopub.status.idle": "2021-07-05T16:35:19.900891Z",
+     "shell.execute_reply": "2021-07-05T16:35:19.900079Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:19.457072Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Minimum 1\n",
+      "Maximum 99\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x864 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(15,12))\n",
+    "sns.distplot(df['hours.per.week'],color='b', kde_kws={\"color\": \"k\"})\n",
+    "print('Minimum',df['hours.per.week'].min())\n",
+    "print('Maximum',df['hours.per.week'].max())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Most of the people work 40 hours a day where there is a high chance that they belong to private sector. There are people working as low ass 1 hour a week and as high as 99 hours a week which undoubtfully might belong from the armed forces. Data shows less skewness compared to the other features in the dataframe."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:19.902487Z",
+     "iopub.status.busy": "2021-07-05T16:35:19.902231Z",
+     "iopub.status.idle": "2021-07-05T16:35:20.562454Z",
+     "shell.execute_reply": "2021-07-05T16:35:20.561464Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:19.90246Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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KurpGzfa5kj4taXXergeGqevN/P0tMZBBkxDIaIaDkj5su10q/reYilFt7bGE3XXrr3Lx/9zaVTzQ6Om65f+r4t9n1ZTr+tgotuefJf12Ppd8UW5Dejt8T7p43vXqoV4MVIVAxoRLKT0v6U5J/2j7WUnbJd0u6RHbh1X8+5+y51Q89vHfJN2R77AoOyRpYe2inor/Vfbntp9Rg9Gq7U7bu/LsF1U85esFSX8r6RsqHqv4AxWj4qMqHq9Y/4sAqBRPe8Oksn27pB+nlD7R5HbelVL6cR6Ff13S+1LxDGQgDM6FYbp43Pb5Ki4o3kEYIyJGyAAQBOeQASAIAhkAgiCQASAIAhkAgiCQASCI/wfXXq3svYhl7wAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 432x288 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "for i in cont:\n",
+    "    sns.boxplot(df[i])\n",
+    "    plt.figure()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There are outliers in all the features, while capital gain and capital loss have very vast no. of outliers."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Bivariate Analysis"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:21.406007Z",
+     "iopub.status.busy": "2021-07-05T16:35:21.405672Z",
+     "iopub.status.idle": "2021-07-05T16:35:21.681042Z",
+     "shell.execute_reply": "2021-07-05T16:35:21.679969Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:21.405972Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='income', ylabel='workclass'>"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 576x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(8,6))\n",
+    "sns.stripplot(x='income',y='workclass',data=df)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There are individuals belonging from every workclass who earn >50k except for never worked and without pay, and even there no. is low in the <=50k category."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:21.683039Z",
+     "iopub.status.busy": "2021-07-05T16:35:21.682645Z",
+     "iopub.status.idle": "2021-07-05T16:35:21.997883Z",
+     "shell.execute_reply": "2021-07-05T16:35:21.996728Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:21.682998Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='income', ylabel='education'>"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 576x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(8,6))\n",
+    "sns.stripplot(x='income',y='education',data=df)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There is no individual who has done preschool and earns >50k salary while there are few who earn 50k even after going through 1st-4th and 5th-6th in the education criteria. It is also to be noticed that there are doctorates and prof who earn <=50k even with such high education. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:22.868263Z",
+     "iopub.status.busy": "2021-07-05T16:35:22.867933Z",
+     "iopub.status.idle": "2021-07-05T16:35:23.135283Z",
+     "shell.execute_reply": "2021-07-05T16:35:23.13435Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:22.868234Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='income', ylabel='education.num'>"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 576x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(8,6))\n",
+    "sns.stripplot(x='income',y='education.num',data=df)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "It is clearly seen that as the education no. increases chances of earning >50K salary also increases"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:23.458951Z",
+     "iopub.status.busy": "2021-07-05T16:35:23.458638Z",
+     "iopub.status.idle": "2021-07-05T16:35:23.729032Z",
+     "shell.execute_reply": "2021-07-05T16:35:23.728157Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:23.458923Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='income', ylabel='marital.status'>"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 576x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(8,6))\n",
+    "sns.stripplot(x='income',y='marital.status',data=df)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There are less no. of individual who are married armed forces spouse, thats why the no. is less in both the categories while people with married spouse absent are less in >50k category income comparatively."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:23.730509Z",
+     "iopub.status.busy": "2021-07-05T16:35:23.730264Z",
+     "iopub.status.idle": "2021-07-05T16:35:24.040631Z",
+     "shell.execute_reply": "2021-07-05T16:35:24.039822Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:23.730485Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='income', ylabel='occupation'>"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 576x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(8,6))\n",
+    "sns.stripplot(x='income',y='occupation',data=df)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There are very few people with income greater than armed forces and private house service while all the other categories of people are distributed evenly in both the income categories."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:24.498212Z",
+     "iopub.status.busy": "2021-07-05T16:35:24.49781Z",
+     "iopub.status.idle": "2021-07-05T16:35:24.936832Z",
+     "shell.execute_reply": "2021-07-05T16:35:24.936038Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:24.498182Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='income', ylabel='native.country'>"
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 576x1080 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(8,15))\n",
+    "sns.stripplot(x='income',y='native.country',data=df)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The grapghs shows people belonging to diff countries have less chances of earning >50k which is wrong, this is because no. of individuals belonging from other countries other than U.S are very low nut it is to be noticed that there are more people in the category <=50k than >50k."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:25.058221Z",
+     "iopub.status.busy": "2021-07-05T16:35:25.057755Z",
+     "iopub.status.idle": "2021-07-05T16:35:25.198488Z",
+     "shell.execute_reply": "2021-07-05T16:35:25.197591Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:25.058192Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='income', ylabel='age'>"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(6,8))\n",
+    "sns.boxenplot(x='income',y='age',data=df,palette=\"Dark2\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "People with higher mean age earn >50k while there are individuals earning <=50k even wat very high age."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:25.20009Z",
+     "iopub.status.busy": "2021-07-05T16:35:25.199802Z",
+     "iopub.status.idle": "2021-07-05T16:35:25.345288Z",
+     "shell.execute_reply": "2021-07-05T16:35:25.344678Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:25.200063Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='income', ylabel='fnlwgt'>"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(6,8))\n",
+    "sns.boxenplot(x='income',y='fnlwgt',data=df,palette=\"Dark2_r\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "People are equally divided with respect to fnlwgt in the income category while it is seen that as the fnlwt is high indiduals fall into <=50k income category."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:25.346871Z",
+     "iopub.status.busy": "2021-07-05T16:35:25.346494Z",
+     "iopub.status.idle": "2021-07-05T16:35:25.475057Z",
+     "shell.execute_reply": "2021-07-05T16:35:25.474403Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:25.34682Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='income', ylabel='capital.gain'>"
+      ]
+     },
+     "execution_count": 37,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(6,8))\n",
+    "sns.boxenplot(x='income',y='capital.gain',data=df,palette=\"crest\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "As the capital gain increases more people fall into >50k salary while mean of both categories remain cloase to zero capital.gain"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:26.988346Z",
+     "iopub.status.busy": "2021-07-05T16:35:26.987809Z",
+     "iopub.status.idle": "2021-07-05T16:35:27.116512Z",
+     "shell.execute_reply": "2021-07-05T16:35:27.115855Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:26.988304Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='income', ylabel='capital.loss'>"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(6,8))\n",
+    "sns.boxenplot(x='income',y='capital.loss',data=df,palette=\"ocean\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There is more density in the >50k income category with increase in capital loss while mean of both categories remain cloase to zero capital.gain"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:27.117918Z",
+     "iopub.status.busy": "2021-07-05T16:35:27.11754Z",
+     "iopub.status.idle": "2021-07-05T16:35:27.252839Z",
+     "shell.execute_reply": "2021-07-05T16:35:27.252061Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:27.11788Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='income', ylabel='hours.per.week'>"
+      ]
+     },
+     "execution_count": 39,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(6,8))\n",
+    "sns.boxenplot(x='income',y='hours.per.week',data=df,palette=\"rocket\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "People earning >50K income work mean hours per week greater than tose earning <50K while people from both the categories work from min to max hours per week."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:28.189107Z",
+     "iopub.status.busy": "2021-07-05T16:35:28.188736Z",
+     "iopub.status.idle": "2021-07-05T16:35:32.34294Z",
+     "shell.execute_reply": "2021-07-05T16:35:32.341965Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:28.189074Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x3960 with 10 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#age vs Categorical features\n",
+    "fig,ax=plt.subplots(5,2,figsize=(15,55))\n",
+    "r=0\n",
+    "c=0\n",
+    "for i,n in enumerate(cat):\n",
+    "    if i%2==0 and i>0:\n",
+    "        r+=1\n",
+    "        c=0\n",
+    "    graph=sns.stripplot(x=n,y='age',data=df,ax=ax[r,c])\n",
+    "    if n=='native.country' or n=='occupation' or n=='education':\n",
+    "        graph.set_xticklabels(graph.get_xticklabels(),rotation = 90)\n",
+    "    else:\n",
+    "        graph.set_xticklabels(graph.get_xticklabels(),rotation = 45)\n",
+    "    if n!='education.num':\n",
+    "        graph.set(xlabel=None)\n",
+    "    c+=1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Individuals working in the government secctor have atmost age 70 to 80 with few outliers which must be the retirement age for them. There are no individuals who do not work after age of 30. There are no individuals of age >70 belonging to the pre school education category while Doctorates and proffessors appear from late 20's as they have to study for more years to get to that level of education. Same is the case with education num, as the education number increases age also is increased. There are no people after the age of 50 in the married to armed forces category with just a few outliers. Widowed category has seen increase as the age age seem to increase, there are very few widows at an early age. There are less people with high age from other races than the white race. There are more no. of working men at higher age than women. There are very few people belonging from other countries with high age."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:32.344504Z",
+     "iopub.status.busy": "2021-07-05T16:35:32.344245Z",
+     "iopub.status.idle": "2021-07-05T16:35:37.530194Z",
+     "shell.execute_reply": "2021-07-05T16:35:37.529145Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:32.344477Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x3960 with 10 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#Hours per week vs categorical Feature\n",
+    "fig,ax=plt.subplots(5,2,figsize=(15,55))\n",
+    "r=0\n",
+    "c=0\n",
+    "for i,n in enumerate(cat):\n",
+    "    if i%2==0 and i>0:\n",
+    "        r+=1\n",
+    "        c=0\n",
+    "    graph=sns.violinplot(x=n,y='hours.per.week',data=df,ax=ax[r,c])\n",
+    "    if n=='native.country' or n=='occupation' or n=='education':\n",
+    "        graph.set_xticklabels(graph.get_xticklabels(),rotation = 90)\n",
+    "    else:\n",
+    "        graph.set_xticklabels(graph.get_xticklabels(),rotation = 45)\n",
+    "    if n!='education.num':\n",
+    "        graph.set(xlabel=None)\n",
+    "    c+=1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Govt employees do not work more than 80 hours a week that also with rare cases. It is seen that people with less education worl more no. hours of the week which is quite logical. No armed force person works more than 60 hours a week while farmers and transport movers has working hours mean higher than other occupation. More no, of individuals who have relationship as own child have high density for working only 20 hous a week. Female works for less no. of hours as compared to men."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:37.532653Z",
+     "iopub.status.busy": "2021-07-05T16:35:37.53205Z",
+     "iopub.status.idle": "2021-07-05T16:35:40.685546Z",
+     "shell.execute_reply": "2021-07-05T16:35:40.684966Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:37.532609Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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kEgAAAAAQG8klAAAAACA2kksAAAAAQGwklwAAAACA2EguAQAAAACxkVwCAAAAAGIjuQQAAAAAxEZyCQAAAACIjeQSAAAAABAbySUAAAAAIDaSSwAAAABAbCSXAAAAAIDYSC4BAAAAALGRXAIAAAAAYiO5BAAAAADERnIJAAAAAIiN5BIAAAAAEBvJJQAAAAAgNpJLAAAAAEBsJJcAAAAAgNhILgEAAAAAsZFcAgAAAABiI7kEAAAAAMRGcgkAAAAAiI3kEgAAAAAQG8klAAAAACA2kksAAAAAQGwklwAAAACA2EguAQAAAACxkVwCAAAAAGIjuQQAAAAAxEZyCQAAAACIjeQSAAAAABAbySUAAAAAIDaSSwAAAABAbCSXAAAAAIDYSC4BAAAAALGRXAIAAAAAYsskuTSzjc3sF2b2NzP7q5l90sw2NbM5ZvaP6N9Not81M7vczNrMbL6Z7VbUT1P0+/8ws6ai24eb2RPR31xuZpbF/xMAgNXFMRIAkFdZVS5/IOk37v5hSbtI+quk0yXd5+47SrovaktSg6Qdo6/jJF0lSWa2qaSzJX1C0h6Szi4cbKPfObbo7/avwP8JAIAkcIwEAORSxZNLM9tI0khJ10qSu7/j7v+RdIik5ujXmiV9Pvr+EEk3ePCgpI3NbEtJYyTNcfcl7v6qpDmS9o9+tqG7P+juLumGor4AAKhaHCMBAHmWReVye0mvSLrezB41s2vMbH1JW7j7v6PfeVHSFtH3W0t6tujvn4tu6+n257q4HQCAascxEgCQW1kkl7WSdpN0lbvvKulNrRzeI0mKrqZ62oGY2XFmNs/M5r3yyitp3x0AAKtSFcdIjo8AgDWRRXL5nKTn3P3PUfsXCgfSl6LhOor+fTn6+fOSti36+22i23q6fZsubn8Pd7/a3Ue4+4jNNtss1n8KAIAEVMUxkuMjAGBNVDy5dPcXJT1rZh+KbtpX0l8k3SGpsJpdk6Tbo+/vkPTVaEW8PSW9Fg0Nmi2p3sw2iRYpqJc0O/rZ62a2Z7QC3leL+gIAoGpxjAQA5FltRvc7QdIMM1tL0kJJRykkureY2dGSFkk6LPrdeyQdIKlN0rLod+XuS8zsPEkPR793rrsvib7/hqSfSVpX0qzoCwCAPOAYCQDIJQtTNzBixAifN29e1mEAAFJmZq3uPiLrOPKC4yMA9B9xj5FZ7XMJAAAAAOhDSC4BAAAAALGRXAIAAAAAYiO5BAAAAADERnIJAAAAAIiN5BIAAAAAEBvJJQAAAAAgNpJLAAAAAEBsJJcAAAAAgNhILgEAAAAAsZFcAgAAAABiI7kEAAAAAMRGcgkAAAAAiI3kEgAAAAAQG8klAAAAACC22t78kpl9UNIpkoYU/427j0opLgAAqh7HRwAAVupVcinpVkk/lvRTSe+mFw4AALnC8REAgEhvk8sV7n5VqpEAAJA/HB8BAIj0ds7lnWb2DTPb0sw2LXylGhkAANWP4yMAAJHeVi6bon9PKbrNJe2QbDgAAOQKx0cAACK9Si7dffu0AwEAIG84PgIAsFKPyaWZjXL3uWb2ha5+7u6/SicsAACqF8dHAADea1WVy89KmivpoC5+5pI4eAIA+iOOjwAAlOkxuXT3s6N/j6pMOAAAVD+OjwAAvFdvF/SRmR0o6WOS1inc5u7nphEUAAB5wfERAICgV1uRmNmPJX1Z0gRJJulLkoakGBcAAFWP4yMAACv1dp/LT7n7VyW96u7nSPqkpA+mFxYAALnA8REAgEhvk8u3on+XmdlWkpZL2jKdkAAAyA2OjwAARHo75/IuM9tY0vckPaKwEt41aQUFAEBOcHwEACDSq+TS3c+Lvv2lmd0laR13fy29sAAAqH4cHwEAWKlXyWVXm0Sb2WuSnnD3lxOPCgCAHOD4CADASr0dFnu0wiIF90ftvSW1StrezM5195+nEBsAANWO4yMAAJHeJpe1kj7i7i9JkpltIekGSZ+Q9IAkDp4AgP6I4yMAAJHerha7beHAGXk5um2Jwsp4AAD0RxwfAQCI9LZy+dtooYJbo/YXo9vWl/SfNAIDACAHOD4CABDpbXJ5gqQvSPp01L5B0i/d3SXtk0ZgAADkAMdHAAAivd2KxCX9MvoCAADi+AgAQLHezrl8DzO7OslAAADoCzg+AgD6qzVOLiX9JLEoAADoOzg+AgD6pTVOLt29NclAAADoCzg+AgD6qx7nXJrZnZK8u5+7+8GJRwQAQJXj+AgAwHutakGfiysSBQAA+cLxEQCAMj0ml+7+u0oFAgBAXnB8BADgvXq1FYmZ7SjpAkkflbRO4XZ33yGluAAAqHocHwEAWKm3C/pcL+kqSSsUNoW+QdL/phUUAAA5wfERAIBIb5PLdd39Pknm7ovcfaqkA9MLCwCAXOD4CABApFfDYiW9bWY1kv5hZidKel7SoPTCAgAgFzg+AgAQ6W3lcqKk9SSdJGm4pP+R9NW0ggIAICc4PgIAEOltcrmduy919+fc/Sh3/6Kk96cZGAAAOcDxEQCASG+TyzN6eRsAAP0Jx0cAACI9zrk0swZJB0ja2swuL/rRhgor4wEA0O9wfAQA4L1WtaDPC5LmSTpYUmvR7W9I+lZaQQEAUOU4PgIAUKbH5NLdH5f0uJnNcHeuxAIAII6PAAB0ZVXDYm9x98MkPWpmXv5zd985tcgAAKhSHB8BAHivVQ2LnRj9+7m0AwEAIEc4PgIAUKbH1WLd/d/Rv4skvS1pF0k7S3o7ug0AgH6H4yMAAO/Vq61IzOwYSQ9J+oKkQyU9aGbj0wwMAIBqx/ERAICVVjUstuAUSbu6e7skmVmdpP+TdF1agQEAkAMcHwEAiPSqcimpXWF59YI3otsAAOjPOD4CABDpbeWyTdKfzex2SS7pEEnzzexkSXL376cUHwAA1YzjIwAAkd4ml09HXwW3R/9ukGw4AADkCsdHAAAivUou3f2ctAMBACBvOD4CALBSr5JLM9tM0qmSPiZpncLt7j4qpbgAAKh6HB8BAFiptwv6zJD0N0nbSzpH0jOSHk4pJgAA8oLjIwAAkd4ml3Xufq2k5e7+O3cfL4mrsgCA/o7jIwAAkd4u6LM8+vffZnagpBckbZpOSAAA5AbHRwAAIr1NLs83s40kfVvSFZI2lPTNtIICACAnOD4CABDp7bDYL0kyd1/g7vtIGi1pbHphAQCQCxwfAQCI9Da53Nnd/1NouPsSSbumEhEAAPnB8REAgEhvk8saM9uk0DCzTdX7IbUAAPRVHB8BAIj09gB4iaQ/mdmtUftLkr6bTkgAAOQGx0cAACK9Si7d/QYzm6eVy6t/wd3/kl5YAABUP46PAACs1OuhO9HBkgMmAABFOD4CABD0ds4lAAAAAADdIrkEAAAAAMRGcgkAAAAAiI3kEgAAAAAQG8klAAAAACA2kst+bvHixZowYYLa29uzDgUVxnMPAOgv2tvbNWnSJC1ZsiTrUICKyeJ1T3LZzzU3N2v+/Plqbm7OOhRUGM89AKC/mDlzphYsWKAZM2ZkHQpQMVm87kku+7HFixdr1qxZcnfNmjWLClY/wnMPAOgv2tvb1dLSIndXS0sL1Uv0C1m97kku+7Hm5ma5uySpo6ODClY/wnMPAOgvZs6cqY6ODknhmEf1Ev1BVq97kst+bM6cOVq+fLkkafny5Wppack4IlQKzz0AoL+YO3euVqxYIUlasWKF5s6dm3FEQPqyet2TXPZjo0eP1sCBAyVJAwcOVH19fcYRoVJ47gEA/cWoUaNUW1srSaqtrdWoUaMyjghIX1ave5LLfqypqUlmJkmqqalRU1NTxhGhUnjuAQD9RWNjo2pqwilvTU2Nxo0bl3FEQPqyet1nllya2QAze9TM7ora25vZn82szcxuNrO1otvXjtpt0c+3K+rjjOj2v5vZmKLb949uazOz0yv+n8uJwYMHq6GhQWamhoYG1dXVZR0SKoTnHqhuHCOB5NTV1am+vl5mpvr6em266aZZhwSkLqvXfZaVy4mS/lrUvkjSpe4+VNKrko6Obj9a0qvR7ZdGvycz+6ikwyV9TNL+kn4UHYwHSLpSUoOkj0o6IvpddKGpqUk777wzlat+iOceqGocI4EENTY2atiwYVQt0a9k8brPJLk0s20kHSjpmqhtkkZJ+kX0K82SPh99f0jUVvTzfaPfP0TSTe7+trv/U1KbpD2irzZ3X+ju70i6KfpddGHw4MG64oorqFz1Qzz3QHXiGAkkr66uThdffDFVS/QrWbzus6pcXibpVEkdUbtO0n/cfUXUfk7S1tH3W0t6VpKin78W/X7n7WV/093t72Fmx5nZPDOb98orr8T8LwEAkIjLlPExkuMjAGBNVDy5NLPPSXrZ3Vsrfd/l3P1qdx/h7iM222yzrMMBAPRz1XKM5PgIAFgTtRnc516SDjazAyStI2lDST+QtLGZ1UZXXreR9Hz0+89L2lbSc2ZWK2kjSe1FtxcU/013twMAUM04RgIAcqvilUt3P8Pdt3H37RQWG5jr7uMk3S/p0OjXmiTdHn1/R9RW9PO57u7R7YdHK+VtL2lHSQ9JeljSjtHKemtF93FHBf5rAADEwjESAJBnWVQuu3OapJvM7HxJj0q6Nrr9Wkk/N7M2SUsUDoRy9yfN7BZJf5G0QtIJ7v6uJJnZiZJmSxog6Tp3f7Ki/xMAAJLFMRIAUPUsXODEiBEjfN68eVmHAQBImZm1uvuIrOPIC46PANB/xD1GZrnPJQAAAACgjyC5BAAAAADERnIJAAAAAIiN5BIAAAAAEBvJJQAAAAAgNpJLAAAAAEBsJJcAAAAAgNhILgEAAAAAsZFcAgAAAABiI7kEAAAAAMRGcgkAAAAAiI3kEgAAAAAQG8klAAAAACA2kksAAAAAQGwklwAAAACA2EguAQAAAACxkVwCAAAAAGIjuQQAAAAAxEZymZKnnnpKDQ0NamtryzqUHuUlTiRv8eLFmjBhgtrb27MOBUAf0draqoaGBj366KOp9N/e3q5JkyZpyZIlqfSftrzHDwCrQnKZkvPPP19vvvmmzj333KxD6VFe4kTympubNX/+fDU3N2cdCoA+Ytq0aero6ND555+fSv8zZ87UggULNGPGjFT6T1ve4weAVSG5TMFTTz2lZ555RpL0zDPPVG1VMC9xInmLFy/WrFmz5O6aNWsW1UsAsbW2tmrp0qWSpKVLlyZevWxvb1dLS4vcXS0tLbmr/uU9fgDoDZLLFJRfsa3WqmBe4kTympub5e6SpI6ODqqXAGKbNm1aSTvp6uXMmTPV0dEhKXxu5a36l/f4AaA3SC5TUKgGdteuFnmJE8mbM2eOli9fLklavny5WlpaMo4IQN4VqpbdteOaO3euVqxYIUlasWKF5s6dm2j/act7/ADQGySXKdhuu+16bFeLvMSJ5I0ePVoDBw6UJA0cOFD19fUZRwQg7wYNGtRjO65Ro0aptrZWklRbW6tRo0Yl2n/a8h4/APQGyWUKpkyZUtI+66yzMoqkZ3mJE8lramqSmUmSampq1NTUlHFEAPJu8uTJJe3yY0xcjY2NqqkJpy01NTUaN25cov2nLe/xA0BvkFym4IMf/GBnFXC77bbT0KFDsw2oG3mJE8kbPHiwGhoaZGZqaGhQXV1d1iEByLnhw4d3VisHDRqkXXfdNdH+6+rqVF9fLzNTfX29Nt1000T7T1ve4weA3iC5TMmUKVO0/vrrV301MC9xInlNTU3aeeedqVoCSMzkyZNVU1OTeNWyoLGxUcOGDctt1S/v8QPAqlhhxcj+bsSIET5v3ryswwAApMzMWt19RNZx5AXHRwDoP+IeI6lcAgAAAABiI7kEAAAAAMRGcgkAAAAAiI3kEgAAAAAQG8klAAAAACA2kksAAAAAQGwklwAAAACA2EguAQAAAACxkVwCAAAAAGIjuQQAAAAAxEZyCQAAAACIjeQSAAAAABAbySUAAAAAIDaSSwAAAABAbCSXAAAAAIDYSC4BAAAAALGRXAIAAAAAYiO5BAAAAADERnIJAAAAAIiN5DIlixcv1oQJE9Te3p51KD068MADNXLkSB100EFZh4IKu+222zRy5EjdcccdWYfSo7zECUBqbW1VQ0ODHn300VT6b2tr09ixY7Vw4cJU+s+z9vZ2TZo0SUuWLEml/5tuukljxozRrbfemkr/Z5xxhsaMGaMpU6ak0v8ll1yiMWPG6LLLLkul/zxL+7WD/oXkMiXNzc2aP3++mpubsw6lR2+88YYk6bXXXss4ElRa4QB7ySWXZBvIKuQlTgDStGnT1NHRofPPPz+V/qdPn65ly5bpwgsvTKX/PJs5c6YWLFigGTNmpNL/9ddfL0m65pprUun/kUcekSQ9/PDDqfTf0tIiSZo1a1Yq/edZ2q8d9C8klylYvHixZs2aJXfXrFmzqrZ6eeCBB5a0qV72H7fddpvcXZLk7lVbFcxLnABC1XLp0qWSpKVLlyZevWxra9OiRYskSYsWLaJ6WaS9vV0tLS1yd7W0tCRegbrppptK2klXL88444ySdtLVy/KLk1QvV0r7tYP+h+QyBc3NzZ0nxB0dHVVbvSxULQuoXvYf5QfWaq0K5iVOAKFqWSzp6uX06dNL2lQvV5o5c6Y6OjokhfOOpCtQhaplQdLVy0LVsiDp6mWhallA9XKltF876H9ILlMwZ84cLV++XJK0fPny93yoAVkrXPzorl0t8hInAHVWLbtrx1WoWnbX7s/mzp2rFStWSJJWrFihuXPnZhwR8oLXDpJGcpmC0aNHa+DAgZKkgQMHqr6+PuOIgFJm1mO7WuQlTgDSoEGDemzHNWTIkB7b/dmoUaNUW1srSaqtrdWoUaMyjgh5wWsHSSO5TEFTU1PnSXBNTY2ampoyjqhrG2ywQUl7o402yigSVNo3v/nNkva3v/3tbAJZhbzECUCaPHlySTvpeXOnnnpqSfv0009PtP88a2xsVE1NOKWrqanRuHHjEu3/qKOOKmkfc8wxifa/2267lbR33333RPsvv8jf0NCQaP95lvZrB/0PyWUKBg8erIaGBpmZGhoaVFdXl3VIXbr77rtL2nfeeWdGkaDSxo4d23kBxMx08MEHZxxR1/ISJwBp+PDhndXKQYMGadddd020/6FDh3ZWK4cMGaIddtgh0f7zrK6uTvX19TIz1dfXa9NNN020/8MPP7yk/aUvfSnR/i+44IKSdtLzdcsvTJZfuOzP0n7toP8huUxJU1OTdt5556qtWhYUqpdULfufwsG12quBeYkTQKhe1tTUpLZX4amnnqr11luPqmUXGhsbNWzYsNQqT4XqZdJVy4JC9TLpqmVBoXpJ1fK90n7toH8xFsgIRowY4fPmzcs6DABAysys1d1HZB1HXnB8BID+I+4xksolAAAAACA2kksAAAAAQGwkl/3cvffeq5EjR+r+++/POpRVeuihh7T33nurtbU161D6hKeeekoNDQ1qa2vLOpQe5SVOAOlrb2/XpEmTtGTJkqxDqTqtra1qaGjQo48+msv+035u29raNHbsWC1cuDCV/tPE6x55QnKZkrycEH/3u9+VJJ177rkZR7JqU6dOVUdHh84888ysQ+kTzj//fL355ptV/9xPnTpVb775ps4666ysQwGQsZkzZ2rBggWaMWNG1qFUnWnTpqmjoyPxlVYLzj//fHV0dKR2zLjuuuv0xBNP6Nprr02l/+nTp2vZsmW68MILU+k/TWm/7vOceKP6kFymJA8n7vfee6/effddSdK7775b1dXLhx56SEuXLpUkLV26lOplTE899ZSeeeYZSdIzzzxTtRdBnnrqKT333HOSpOeee65q4wSQvvb2drW0tMjd1dLSQhWnSGtra8kxMunqYmtrq5YtWyZJWrZsWeL9t7e3a+7cuZKkuXPnJv7ctrW1adGiRZKkRYsW5SqJqsTrPs+JN6oPyWUK8nLiXqhaFlRzIjx16tSSNtXLeMqvbFfrc1/+vFO9BPqvmTNnqqOjQ5LU0dFB9bLItGnTStpJVy/TPmZcd911Jc9t0tXL6dOnl7TzlESl/brPc+KN6kRymYK8nLgXqpbdtatJ4Ypsd22snsLFj+7a1aJQteyuDaD/mDt3rlasWCFJWrFiRWelC+kfIwtVy+7acZWPnEp6JFUheequXc3Sft3nOfFGdSK5TEFeTtzzZNCgQT22sXq22267HtvVwsx6bAPoP0aNGqXa2lpJUm1trUaNGpVxRNUj78fItD/rhwwZ0mO7mqX9us9z4o3qRHKZgrycuA8fPrykvfvuu2cUyaqVD48877zzsgmkj5gyZUpJu1qHm372s58tae+9997ZBAIgc42NjaqpCactNTU1GjduXMYRVY/JkyeXtMs/4+P6xCc+UdLec889E+2//LN9n332SbT/U089taR9+umnJ9p/mtJ+3ec58UZ1IrlMQV5O3L/zne+UtMsPTtVkjz326LwSO2jQoPckxlg9H/zgBzsvemy33XYaOnRotgF146STTuq8gm1mOumkkzKOCEBW6urqVF9fLzNTfX29Nt1006xDqhrDhw8vOUbuuuuuifY/ceLEHttxjR8/viSBGj9+fKL9Dx06tDNpGjJkiHbYYYdE+09T2q/7PCfeqE4klynIy4n74MGDO5O03XffXXV1dRlH1LOpU6eqpqaGqmVCpkyZovXXX79qL35I4TVaqF7uvffeVf8aBZCuxsZGDRs2jKplFyZPnqyamprEq5ZSSHAK1cs999wz8QSnrq6uc7jnvvvum8qFg1NPPVXrrbdeLpOnNF/3eU68UZ3M3bOOoSqMGDHC582bl1h/Tz31lCZOnKgrrriiapNLSVq8eLHOOeccTZ06lRN3VCVeo0iambW6+4is48iLpI+PyKf29nZdcMEFmjx5cirJX9r9o3ttbW065ZRTdMkll5BcIvYxkuQywsETAPoHksvVw/ERAPqPuMdIhsUCAAAAAGIjuQQAAAAAxEZyCQAAAACIjeQSAAAAABAbySXQTy1evFgTJkxQe3t71qEA6CPa29s1adIkLVmyJOtQAAAZILkE+qnm5mbNnz9fzc3NWYcCoI+YOXOmFixYoBkzZmQdCgAgAySXQD+0ePFizZo1S+6uWbNmUb0EEFt7e7taWlrk7mppaaF6CQD9EMkl0A81NzersMdtR0cH1UsAsc2cOVMdHR2SwucK1UsA6H9ILoF+aM6cOVq+fLkkafny5Wppack4IgB5N3fuXK1YsUKStGLFCs2dOzfjiAAAlUZyCfRDo0eP1sCBAyVJAwcOVH19fcYRAci7UaNGqba2VpJUW1urUaNGZRwRAKDSSC6BfqipqUlmJkmqqalRU1NTxhEByLvGxkbV1ITTipqaGo0bNy7jiAAAlUZyCfRDgwcPVkNDg8xMDQ0NqquryzokADlXV1en+vp6mZnq6+u16aabZh0SAKDCarMOAEA2mpqa9Mwzz1C1BJCYxsZGLVq0iKolAPRTJJdAPzV48GBdccUVWYcBoA+pq6vTxRdfnHUYAICMMCw2JQ899JD23ntvtba2Zh1Kj44//niNHDlSJ5xwQtahrNLixYs1YcKEqt+TMS9x/uQnP9HIkSN17bXXZh1Kjy677DKNHDlSP/zhD7MOZZXy8r4H0tLa2qqGhgY9+uijqfR/5ZVXasyYMfrxj3+cSv9pa29v16RJk1LZA/S6667TmDFjUtta6s4779SYMWN0zz33pNJ/2s/t/fffrzFjxuiBBx5Ipf80pfm6AZJW8eTSzLY1s/vN7C9m9qSZTYxu39TM5pjZP6J/N4luNzO73MzazGy+me1W1FdT9Pv/MLOmotuHm9kT0d9cboWVSypo6tSp6ujo0Jlnnlnpu14tf/3rXyVJTzzxRMaRrFpzc7Pmz59f9Xsy5iXOwh501R7nr371K0nSLbfcknEkq5aX9z2qV96PkdOmTVNHR4fOP//8pLoscccdd0iSbrvttlT6T9vMmTO1YMGCVPYAvfnmmzvvIw1XXnmlJOnyyy9Ppf+0n9tCRf2iiy5Kpf80pfm6AZKWReVyhaRvu/tHJe0p6QQz+6ik0yXd5+47SrovaktSg6Qdo6/jJF0lhQOtpLMlfULSHpLOLhxso985tujv9q/A/6vTQw89pKVLl0qSli5dWrVVjOOPP76kXc3Vy8WLF2vWrFlyd82aNatqq4J5ifMnP/lJSbtaq5eXXXZZSbuaq5d5ed+j6uX2GNna2lryHki6ellIbgryVr1sb29XS0uL3F0tLS2JVqGuu+66knbSFw3vvPNOubskyd0Tr16m/dzef//9JXuw5ql6mebrBkhDxZNLd/+3uz8Sff+GpL9K2lrSIZIKn4bNkj4ffX+IpBs8eFDSxma2paQxkua4+xJ3f1XSHEn7Rz/b0N0f9PBJeENRXxUxderUkna1VjEKVcuCaq5eNjc3dx7YOjo6qrbalpc4y69+VmuchaplQTVXL/Pyvkd1y/Mxctq0aSXtpKuXhcpWQd6qlzNnzlRHR4ekcHxIsgpVqFoW31eSypO/pKuXaT+35fOA81S9TPN1A6Qh0zmXZradpF0l/VnSFu7+7+hHL0raIvp+a0nPFv3Zc9FtPd3+XBe3d3X/x5nZPDOb98orr8T7zxQpXLntro3VN2fOHC1fvlyStHz5crW0tGQcUdfyEieSx/seScvyGLkmx0feAz2bO3duSfVs7ty5GUfUe4WLpt21q13hce+uXc3y/LpB/5RZcmlmgyT9UtI33f314p9FV1NT/+Ry96vdfYS7j9hss80S63fQoEE9trH6Ro8erYEDB0qSBg4cqPr6+owj6lpe4kTyeN8jSVkfI9fk+Mh7oGejRo1SbW1YpL+2tlajRo3KOKLeK5+Wm8FSFrEUHvfu2tUsz68b9E+ZJJdmNlDhoDnD3Qvj3l6Khuso+vfl6PbnJW1b9OfbRLf1dPs2XdxeMeXD484777xK3n2vfeQjHylp77TTThlFsmpNTU2dB7Oampqq3ZsxL3GW70FXrXF+4QtfKGkfdthhGUWyanl536P65fUYOXny5JL2lClTkui208EHH1zSHjt2bKL9p62xsVE1NeG0q6amJtG9QL/85S+/576SVL4mw0knnZRo/2k/t5MmTSppn3baaYn2n6Y0XzdAGrJYLdYkXSvpr+7+/aIf3SGpcIbbJOn2otu/Gq2It6ek16KhQbMl1ZvZJtEiBfWSZkc/e93M9ozu66tFfVXEHnvs0XnFdtCgQRo+fHgl777Xyhd1KZ9TUU0GDx6shoYGmZkaGhpUV1eXdUhdykuc5Ys5HX300RlF0rNvfvObJe0TTzwxm0B6IS/ve1S3PB8jhw8fXvIe2HXXXZPotlN5gvO1r30t0f7TVldXp/r6epmZ6uvrtemmmybW9/jx40vaSV8wPOiggzovnJqZDjjggET7T/u53WeffTRgwABJ0oABAzRy5MhE+09Tmq8brBrbwKy+LCqXe0n6iqRRZvZY9HWApAsljTazf0jaL2pL0j2SFkpqk/RTSd+QJHdfIuk8SQ9HX+dGtyn6nWuiv3la0qxK/MeKTZ06VTU1NVVfvShUL6u5alnQ1NSknXfeuWqrbAV5iXPHHXeUJH3oQx/KOJKebb/99pKkD3zgAxlHsmp5ed+jquX6GDl58mTV1NQkXrUsKFS48la1LGhsbNSwYcNSqT4VqpdJVy0LCglg0lXLgrSf25133lmS9PGPfzyV/tOU5usGPWMbmNVneZuUnZYRI0b4vHnzsg4DqIjFixfr8MMP1zvvvKO1115bN910U1VWWfMSJ/LFzFrdfUTWceQFx0fkXXt7u4488ki98847WmuttdTc3EwFEKvUX183cY+Rma4WCyAbedkyJS9xAgCqF9t5YE3wulkzJJdAP5SXLVPyEicAoHqxnQfWBK+bNUNyCfRDedkyJS9xAgCqF9t5YE3wulkzJJdAP5SXLVPyEicAoHqxnQfWBK+bNUNyCfRDedkyJS9xAgCqF9t5YE3wulkztVkHACAbTU1NeuaZZ6q+GpiXOAEA1auxsVGLFi2i+oTVwutm9bEVSYSl1gGgf2ArktXD8REA+g+2IgEAAAAAZI7kEgAAAAAQG8llP/fQQw9p7733Vmtra9ahoMIWL16sCRMmqL29PetQepSXOKV8xQqk4f7779eYMWP0wAMPZB0Kcqa9vV2TJk3SkiVLctk/gIDksp+bOnWqOjo6dOaZZ2YdCiqsublZ8+fPV3Nzc9ah9CgvcUr5ihVIw8UXXyxJuuiiizKOBHkzc+ZMLViwQDNmzMhl/wACkst+7KGHHtLSpUslSUuXLqV62Y8sXrxYs2bNkrtr1qxZVVtpy0ucUr5iBdJw//33a8WKFZKkFStWUL1Er7W3t6ulpUXurpaWlsSri2n3D2Alkst+bOrUqSVtqpf9R3NzsworRXd0dFRtpS0vcUr5ihVIQ6FqWUD1Er01c+ZMdXR0SAqfn0lXF9PuH8BKJJcpuffeezVy5Ejdf//9WYfSrULVsrt2tRk/frxGjhyp4447LutQenT22Wdr5MiROu+887IOpVtz5szR8uXLJUnLly9XS0tLxhF1LS9xSvmKFUhDoWrZXTsJY8aM6fxCqcbGRo0ZM0b/8z//k0r/aT72c+fOLal6z507N1f9p23atGkaM2ZMahdszjjjDI0ZM0ZTpkxJpf88a2tr09ixY7Vw4cKsQ8kNksuUTJs2TZKqOsEYNGhQj+1q09bWJkn629/+lnEkPStcUJgzZ07GkXRv9OjRJe36+vqMIulZXuKU8hUrkIba2toe20hXYSj+K6+8knEkq2/UqFE9tqu9/7T97ne/k6TUkuJHHnlEkvTwww+n0n+eTZ8+XcuWLdOFF16YdSi5QXKZgnvvvbfkClm1Vi/zVLkcP358Sbtaq5dnn312SbtaLy7cddddPbarxe23317S/vWvf51NIL1QPmf5scceyyYQICNpVy7LK2ZUL1dqbGwsaSddvUz7sU/7mJSXY15XCsWKgqSrl2eccUZJm+rlSm1tbVq0aJEkadGiRVQve4nkMgXlHwTVmmDkSaFqWVCt1cvyCwnVWr189913S9ppDF/rb5577rmS9jPPPJNNIACqVlrbYZQvIJbH6mWepbnNSaFqWZB09bJQtSygernS9OnTS9pUL3uH5DIFlZh3AgAA8oXtMPomnte+qVC17K6NrpFcpoB5JwAAoBjbYfRN7e3tmj17ttxds2fP5nntQ4YMGdJjG10juUzB5MmTS9ps8RHfhhtuWNLeeOONswlkFfbZZ5+SdvkiL9XCzHpsY/WVX0QaOHBgRpEAqEZpbodRV1dX0t5ss80S6xs9mzlzZsk6G0lXL9dbb72S9vrrr59o/zU1panAgAEDEu0/z0499dSS9umnn55RJPlCcpmCj3/84yXtnXfeOZtA+pDCFg8Fb7/9dkaR9OzAAw8saR9wwAEZRdKz8sSnWhOh8n3zLr300owiWbXy4e/lr1kA/Vua22Gce+65PbbjOuqoo0raxxxzTKL959l9993Xucexu+u+++5LtP9ly5aVtN98881E+y9c8CgoX5OhPxs6dGhntXLIkCHaYYcdMo4oH0guU1C+eTqbqce3xRZb9NiuFlOnTi1pV2vVujzxqdZEKC+Pp5S/rX0AVNaoUaM6RzjU1tYmuh1G2guPXH/99SXta665JtH+82zzzTfvsR1X2scWjl09O/XUU7XeeutRtVwNJJcpKN88ffbs2RlF0ne89NJLPbarRV62dylcZe2uXS3y8nhKLOQFoGeNjY2dQxBramo0bty4xPpm4ZHsvPjiiz2240r72HLiiSeWtCdOnJho/3k3dOhQ3XbbbVQtVwPJZQryUmXLk/r6+s55gWbG/mYx5WXOZZ4Wxyp/Te6///4ZRQKgGtXV1XUey+rr67Xpppsm1jcLj2Qn7Wkm++23X4/tuBYsWFDSfvzxxxPtH/0PyWUK8lJly5OmpqbOD+yBAweqqakp44jyrfzgt9Zaa2UUSc/KFxao5oUGeI0CWJXGxkYNGzYs0aqllP7CI3mZp5+FtEfYNDY2lhxbkn7tlM/9TXofTfQ/JJcpoMqWvMGDB6uhoUFmpgMOOOA9K+NVi7zMXWhoaOixXS3Kq3/VGqcUXqMHHHCAzEwHHnhg1b5GgbSkPdIgTyMZulNXV6eLL7440aqllP7CI+XnMXk7r0nz2Jx21biurk5jxozpPJ9M+rWT5lxg9E8klynISwVjk002KWlX+8lwU1OTdt5556p9PKX3LkBz3nnnZRPIKjQ1NZUcTKr1MS2Os5rfSwV5eI0CaZk0aVJJ+7TTTstV/3mX5sIjjY2NnSNHBgwYkHj1bLfdditp77777on2X75F3JQpUxLruxLbVaRV8S70ndZcYPRPJJcpyEuV7fbbby9p33bbbRlF0juDBw/WFVdcUbWPpyTtsccenVdEBw0apOHDh2ccUdcGDx6sAw88UGamz33uc1X7mBbHmYdqYB5eo0Ba9tlnn5KLViNHjsxV/3mX5sIjdXV1nec1DQ0NiVfPLrjggpL2+eefn2j/w4cPLzk277rrron1XYntKtKqeBf6TmsuMPonksuU5KWCUahecjKcnKlTp6qmpqZqq5YFeXmN5iVOACuri2lVFdPuH91Ls3omraxeJl21LJg8ebJqamoSrVoW5H27irSfW/QvVq1bEFTaiBEjfN68eVmHUXFPPfWUJk6cqCuuuEJDhw7NOhwASJ2Ztbr7iKzjyItqOj62t7frggsu0OTJk6mw9DE8t0B1iHuMpHLZz51//vl68803de6552YdCgAAPZo5c6YWLFigGTNmZB0KEsZzC/QNJJf92FNPPaVnnnlGkvTMM8+ora0t24AAAOhGe3u7Wlpa5O5qaWnRkiVLsg4JCeG5BfoOkst+rHzCPNVLAEC1mjlzpjo6OiRJHR0dVLj6EJ5boO8guezHClXL7toAAFSLuXPnasWKFZKkFStWsNl7H8JzC/QdJJcpeeihh7T33nurtbU161C6td122/XYrjZ5eEylMNy4oaGh6ocZn3322Ro5cmTVr2p77733auTIkbr//vuzDmWV8hQrkIYrr7xSY8aM0Y9//OPE+y7f3D2Nzd7b29s1adKkXA7LbG1tVUNDgx599NHc9V+J5/aSSy7RmDFjdNlllyXed9rSfm7b2to0duxYLVy4MJX+0b+wWmwk6dXwDjjgAC1dulSDBg3SPffck1i/SXrqqad0zDHHdLavu+66ql4xNg+PqSR99atf1TPPPKPttttON9xwQ9bhdKt4j7gHHnggw0h6NmrUKK1YsUK1tbVVfzU7T7H2Z6wWu3pW5/g4ZsyYzu9nz56daBzt7e1qbGzsbN94442Jryp6xRVX6O6779aBBx6oCRMmJNp32r74xS92HiN/+ctf5qr/Sjy3ab4205b2c3vcccdp0aJFGjJkiK6++urE+0e+sFpsFXrooYe0dOlSSdLSpUurttJWnFhK0vjx4zOKZNXy8pjmZZGks88+u6RdrdXLe++9t2SoVDVXBPMUK5CGK6+8sqSddPXyZz/7WUk76Yt3eV5UprW1teQYmXSFK+3+jz/++JL21772tUT7v+SSS0raeapepv3Yt7W1adGiRZKkRYsWUb1EbCSXKZg6dWpJ+8wzz8wmkD4kL49pXhZJKk985syZk1EkPZs2bVpJu1qTYClfsQJpuOOOO0rat912W6L9t7S0lLRnzZqVaP95XlSm/POn/FhU7f2/8cYbJe3XXnst0f7Tfu2kKe3Hfvr06SXtCy+8MNH+0f+QXKagcIWpuzZWX14eUxZJSlahEthdu5rkKVYA75XnRWXSPkbm5RjcF6X92Beqlt21gdVFcpmCQYMG9djG6svLY5q3RZKqXW1tbY/tapKnWAG816hRozrft7W1taksKpOWtI+ReTkG90VpP/ZDhgzpsQ2sLpLLFJQP4WR4XHx5eUynTJlS0j7rrLMyiqRn++yzT0l79OjRGUXSs8mTJ5e0q3U4tJSvWIE0HHzwwSXtsWPHJtp/fX19SbuhoSHR/hsbG1VTE06LampqNG7cuET7l9Jbjbb886f8WFTt/W+wwQYl7Y022ijR/tN+7aS5ynDaj/2pp55a0j799NMT7T/v8ryCdFZILlOwxx57lLSHDx+eUSQ9+9WvflXSTnp+TJL22GOPzqt1gwYNqtrH9IMf/GDJle9qXX23fBXEb3zjGxlF0rP99tuvpF2eFFeT97///SXtbbfdNqNIgGwcfvjhJe3DDjss0f6//e1vl7S/+c1vJtp/XV2d6uvrZWaqr69PfLVSKczrXLBgQeLzOYcPH15yjNx1111z1f9PfvKTknbSi0EdcsghJe3yCyFxpfW8SuGxLz6vSPqxHzp0aMlzu8MOOyTaf96l+dz2VSSXKShP0soXOagWJ510Ukl74sSJGUXSO1OnTlVNTU3VVi2lsFps8Zydal0t9rvf/W6P7Wrx1FNPlbSr9fGU8rOYE5CW8oVHkv5cufPOO0vaaWxJ1djYqGHDhqVWtUxzNdrJkyerpqYm8cpWJfpP+7VTft6Q5Odz2s9re3t7STuN/t9++21J0ttvv02FrkieV5DOEsllCsqXuC5fArtaPPfccyXtf/3rXxlF0juvv/66Ojo69Prrr2cdSrfykmCUb+WS5B6vScrL4ymxmBOwYMGCHttxlW91cvnllyfavxSqlxdffHFqVcs0V6Pdbrvt9LGPfSy1OXPDhw/XrFmzEq+cSem/dl588cWS9r///e/E+k77eZ05c2bJReu89Z9neV5BOksklylw9x7bWDOFK5vVXLkkwUhWnh5PFnMC0pX3Y2vaq9EyfC8baT+v5f2l0X/hveTuuVolOW15XkE6SySXyIW8bFC/5ZZb9tiuFmbWY7tabLPNNj22q8lHPvKRkvZOO+2UUSQAqlGaq9EyfK9n66yzTo/tONJeZbh8DmTScyLLj1Ucu1bK8wrSWSK5TMHaa6/dYxurL68b1Fdr0rbWWmuVtKv1NVq+INKOO+6YUSSrVr4pd/n8MAD9W5qr0TJ8r2f//e9/e2zHkfYqw08++WSP7bjSHpKcZ5VYQbovIrlMQWFidHdtrL68bFBfPo/jhRdeyCiSnpW/JpM80CbpoYceKmn/+c9/zigSAIgnzdVoGb6XnbRXGU57OPibb77ZY7s/q8QK0n0RyWUK2Gw4eXnZoD4v8+7y8hot33+zfK8yAEhSW1ubxo4dq4ULF6bSf0NDg9Zdd10deOCBifZbPlwvjeF7l1xyicaMGfOeRQshbbbZZnJ3ve9970u877SnsVTifCDPe0UOGzZM7q5ddtkl61Byg+QyBVOnTi1p52UIZzXLywb15Uu0n3XWWRlF0rO8vEabmpp6bFeT8j04yxNjoK/bc889S9p77bVXov2Xz7lOYy/ZadOmadmyZaltzzRr1iy99dZbuvvuuxPtt6GhoaSddPIqSS0tLZLeOwUgCZtvvnlJO+kkrfzCZPnjFdf1118vSbrmmmsS7VeSTjjhhJJ2+TZycZWfX6Wx1Uzai021traqoaFBjz76aOJ9F1alvvTSSxPvu68iuUzB3//+95J2+V59WH3XXXddSbvwQV5typO2at06ozw5T2tftLjKN2Uvb1eT8kWm5syZk1EkQDYefPDBkvYf//jHRPsv3z7r2WefTbT/trY2Pf/88533lXT1Ms1Fd9Lcx1F675ZqSVcvX3755ZJ2+dYhcRUS44IkE+S0918t3yos6a3DbrzxxpL2TTfdlGj/lVhsatq0aero6HjP9mVxtba2atmyZZKkZcuWpZK89kUklyn46U9/WtK+6qqrMoqk7yg/qajWLSnyEudbb71V0q7WORbvvPNOSZv5ywDSUr5wXNLVyzQX3UlzH0cp3eQs7374wx+WtH/wgx8k2n/aF22eeOKJkvZjjz2WaP9pLzbV2tqqpUuXSpKWLl2aaAKYp722qwnJJQAA6PcKVcuC8ouFcbHoDvqjtF/35ReFkqxeFqqW3bXRNZJLAADQ76W9cAp75qE/Svt1X6hadtdG5ZFcpmC99dYraa+//voZRQIAAHrj05/+dEn7M5/5TKL9p7ln3oABA0raSa+onpcV27NQvrrqBhtskFEk1SntvSLTXO32E5/4REm7fNEydI3kMgXlexAVxppjzRU+mLprV4vyrUeGDh2aTSCrUH5FvlofzxEjRpS0+WAHkJavf/3rPbbjSnPPvPIFfZJe2KR8rlnS/efZu+++W9JOeh/uE088saQ9ceLERPtPW9p7Rab5+JT3lbfHPivVeUaZc+WLpZS3sfrKE/RqTdjL90EaNmxYRpH0LC8XQMrnQC1atCijSAD0da+++mpJ+z//+U/i99HY2Khhw4YlXr0ZPnx4Z/WytrZWu+66a6L9l184HTJkSKL951na53zlCwM+/fTTifZfCWm97iVpwYIFJe3HH388sb7r6uo6q5d77rln4olxX0VyCSSofPuJ8hX2sHrKVzxMegVEAChIe7VYKZysXnzxxamcpJ533nmqqalJpao4c+bMzuR1wIABqe1XiPcqXwAn6QVxKjHkOc3XfdqPz8SJE7XTTjtRtVwNJJfIhU9+8pMl7aQ3507K6NGjSyaul2/cjL6rfM5TeRtAdUt7tdi0DR8+XLNmzUq8aimFE/bC8M93332XlW6LpP3ZP2rUqJI5i0kviDNp0qSS9mmnnZZo/2lLe8GgNBPjvorkMgXbbrttj22svlNOOaWkXf5hWC2amppKltxuamrKOKKu5eU1uuWWW5a0t9pqq4wiWbXyxT9GjhyZUSRANtKeG3/UUUeVtI855phE+097tVgpbCg/adKkVDaST7PvtE/g11577R7bcaW5MMs+++xT0k76sWlsbCzZJzLpoaXl8eft2NXY2Nj5XjWzVIbepqmtrU1jx47VwoULsw4lMSSXKSgvnZ988skZRdJ3lB8sy+fGYPWcffbZJe1zzjkno0h6duyxx5a0jz/++IwiWbU33nijxzbQ16277rol7fKV0+N69tlnS9rlc9HiSnu1WEm66qqr9MQTT+hHP/pR4n3PnDlTCxYsSGXIatorfo4ZM6akfcABByTaf3kCte+++ybW9/jx43tsx5X2XOD29vaSdhoXJ9JUV1fXeeF5q622yl2Fcfr06Vq2bJkuvPDCrENJDMllCm688caSNnMT4ps8eXJJ+/TTT88okp5NnTq1xzZWz6WXXlrSvvjiizOKZNVaW1tL2vPmzcsoEiAbb775Zkk76f3m7r333h7bcaW9Wmx7e7t+//vfS5J+//vfJ3oS397ernvuuUfurnvuuSfxBCHtFT/vuOOOkvZtt92WaP9pHkvmz59f0i5fYCau73znOyXt8vOhuCox1zhN7e3teuGFFySFdRnylBy3tbV1LlS4aNGiPlO9JLlMASeZyXv55Zd7bFeL8oNMkquWJal8TkX5sONqQTUQQF9x1VVXlbSTrF7OnDmzZOhk3IvaV111lU455ZSSrz/+8Y8aMGCAnn766ZLby/9f1ejtt9/usR1HeaJ60UUXJda39N5KZdIjt8qT4aST47TNnDmzcwX8JF775dIctjp9+vSSdl+pXpJcAv1Q+TCY8jb6tsWLF2vChAk870CR6667rqR97bXXJtp/oWrZXTuO8pXJ01ip/J133tHaa6+tgQMHJt53npXva5n0Ppfo2dy5c0vWukh6salp06Zp2bJlqVR0y7dXS2O7tTTnYncn+fWGAQBVrbm5WfPnz1dzczNzwoHI/fff/552tY7qKLd8+fIe26urqyHBhcfie9/7Xqy++5ra2tqShDKNrTzQvVGjRuk3v/mNVqxYkfhiU21tbZ2rSD/33HNauHChdthhh8T633rrrUtWqd5mm20S67ugeC72hAkTEu+/K1QuAaAfWbx4sWbNmiV316xZs6heApHC0Lru2nFtttlmJe3NN988sb7Tjh3d++IXv1jSPuywwzKKpHqlWT1Lc7XYtOejlieTSSeX7e3tamlpkburpaWlYtVLkksA6Eeam5tL5qc0NzdnHBFQHcpXuy1vx1Ve0UpyP8RKbKOCrt19990l7fLFiZDuKslprhab9t635WuyPPzww4n2n/Rc7N4iuQRQtThhSt6cOXM6h8wtX748lblZQB6Vr3Zb3o7r3//+d4/tOMoT1SQTV/SsfFXkpFdJzrs0V0ku9F9IAl944YVcrRab9jlO2vNRu0NyCaBqrbPOOj22sfpGjx7duSDHwIEDVV9fn3FEQHVI+0Qvzf7XWmutHttAVtJcJVkK1blCArV8+fJcbf83fPjwkvaIESMS7X/UqFGdIyaSno/aE5JLAFXrrbfe6rGN1dfU1NR5UltTU6OmpqaMIwKqQ9rzFtPsf9myZT22+7vyIcmseFs5aa6SLEn33Xdfj+040h4RkPZqsY2NjaqpCaleTU1NovNRe0JyCQD9yODBg9XQ0CAzU0NDg+rq6rIOCagKac+5RHYGDx7cYxv5tdFGG5W0N95448T63meffUraSVf+XnzxxZJ2kkPlpTAftb6+Xmam+vr6ROej9oTkEkDVWnvttXtsY800NTVp5513pmoJFFlvvfVK2uuvv35Gkay+8pVnk1yJti9I+yQe3dt6661L2kmviJrmczt27NiS9he+8IXE+q6UxsZGDRs2rGJVS4nkEkAVe/vtt3tsA0BSyrflWbx4cUaRrL7yWPMUO/q2yZMnl7S/853vZBTJ6ps1a1ZJu3xl4Dyoq6vTxRdfXLGqpURyCQD9TnNzs+bPn882JEAfwT6XqFZDhw7trF5us8022mGHHRLtP83KaPnqqpVabTXvSC6BBJWv/LX77rtnFAnQtcWLF2vWrFlyd82aNes91RoA+VNYtKO7NpClE044QTU1NTrxxBNT6btYkvfxqU99qsc2ula76l8B0Fu77babWltbO9tJLysNxNXc3NxZ1ejo6FBzc7NOPvnkjKMCEMc+++yje++9t7O9uguPXHXVVVq4cGGPv/P0009Lkk455ZRV9rfDDjvo61//+mrFUEnsmVxZ//d//yd31x/+8Aftuuuuifbd1dDVpO+jgNdN75BcAgm65pprSto//vGPdcQRR2QUDfBec+bM0fLlyyWFPcFaWlpILoGcGz9+vObOnauOjg7V1NRo/Pjxq/X3Cxcu1IK/zde6PSwe/XY00vbpV+b32NdbORgMwbDhymlvb1dLS4vcXS0tLRo3blyi8//S3Orkj3/8Y0n7D3/4gyZNmpRY/30VySWQIOa9oNqNHj1a99xzj5YvX66BAweqvr4+65AAxFRXV6dRo0bp3nvv1b777rtGJ+/r1kk7fi5+ZeYfd3Hcw0ozZ85UR0eHpDBaZsaMGZowYULGUfXO5ptvXrL3JKsw9w6D8oEElQ+ZYAhFPDyeyWtqaup8HGtqatiOBOgjxo8fr5122mm1q5aIp3wLm/J2fzd37lytWLFCkrRixYrEF8Wpra3tsR3Hyy+/3GMbXSO5BBJUvifSl770pYwi6Rt22223knb5gklYfYMHD1ZDQ4PMTA0NDaqr62EcHIDcyGLLgaRssMEGJe2NNtoo0f7T3MP03Xff7bEd1/ve976S9lZbbZVo/9ttt11Je/vtt0+0/1GjRnUmfLW1tas9H3hVColrd+049tprrx7bcZW/V/vK8ZjkErmQlwpWS0tLSfuee+7JKJK+oXwz5BdeeCGjSFZt4MCBJe211loro0hWrampSTvvvDNVS6DIgAEDemzHVb7ISPnFs/7sjTfeKGm/9tprifZfvkfyf//738T6Lk/+yttxlT8Wr776aqL9l1fjXnrppUT7b2xs7Fy9uKamRuPGjUu0/yFDhvTYTlLS555vvfVWSXvZsmWJ9p8VkkvkQl7mMi5durTHNlZPeTJZzcllYZGcgnfeeSejSFZt8ODBuuKKK/rMVVIgCXk5znSnvb1dkyZN0pIlS7IOpeqkWV1M+zhVnoCUt+MqryQmXVmsq6tTfX29zEz19fWJV9ZPPfXUkvbpp5+eWN9/+MMfStpJLhYkpf/cZoXkErkwaNCgHtvVIi9x5qUSnJc4AeRf2ntFPvrooyXtRx55JNH+Z86cqQULFmjGjBmJ9ouepTkssxIaGxtL2klXFgv3MWzYsFT6Hjp0aGe1csiQIdphhx0S6zvN+Zx9GcklcqF8q4Te7LOVhalTp5a0zzvvvGwCWYW8XKH/7Gc/W9Lee++9swkEQJ9X/vmyzz77ZBPIGijf7oHqZeWkfTz9xCc+UdLec889E+2/fJjtf/7zn0T7l9KfD3zqqadqvfXWS7RqKTEabU312eTSzPY3s7+bWZuZJftqQ8U9/vjjJe3yK8DVYo899uisVg4aNKhqF6DJy+p2J510Ume10sx00kknZRwR0DdwjHyv8ePHl8wNS3rV1TSrIF1t94CVKjkvL2kTJ07ssR3X9OnTS9oXXnhhov1XwtChQ3XbbbclWrWU0h891Vcro30yuTSzAZKulNQg6aOSjjCzj2YbFeIoXyhn9uzZGUWyalOnTlVNTU3VVi2l9y5uUN6uFoMHD+6sXu69997MEQQSwDGya4W9IiWt8V6RPUlz2G3a2z2k7aijjippH3PMMYn2n+a8vLTV1dV1Vi/33HPPxF+Xxfs4dtXuz9KuSvfVqT99MrmUtIekNndf6O7vSLpJ0iEZx4QYtthiix7b1WSPPfbQb3/726qtWkr5+kA76aSTtMsuu1R91TJPjyn6PY6R3Uhzr8gtt9yyx3YcaW/3kLbDDz+8pJ30Nl5pzsurxGf/xIkTtdNOOyVetZTyXdVNW9rraKy99to9tvPKqnWuVRxmdqik/d39mKj9FUmfcPcTu/ubESNG+Lx58yRJl19+uWbNmtXjfSxbtiz2FQwzW+VwxIaGhm5PqisVp7TqWHuKU1p1rMT5Xn3huc9LnFLfee7zEqeU3XNvZq3uPiL2HefU6h4jC8fHq666SnPmzCn5WW+fw66eo9GjR+vrX/96Z7u8/9V5fayq/zixd9X/qmJfnf7X5LFJuv9x48Zpcfti1UQ7KnWskNTbt6ZJNUWj+TqWS4PrBncOzeWxr67+eV/x2HfVf3HfcY+RfWNw7xoys+MkHSdJ73//+zOOBgCA6sDxsX/ZcMMNS7ZBeLvj7c45nKtSU1OjtQcWVVwGhv4A9E99tXL5SUlT3X1M1D5Dktz9gu7+prhymYQTTzxR8+fP1y677KIrrrgisX6TdNttt+nSSy/tbE+aNEkHH3xwhhF1b/HixTr88MP1zjvvaK211tLNN9/M/LuYvvvd72r27Nnaf//9NXny5KzD6RMK76lqfi+ByuXqHiN7e3xsa2vTCSec0Nm+6qqrEh1+2N7ernHjxsndZWaaOXNmaqtPpqG9vV1NTU1avny51lprLTU3Nycaf3t7uy644AJNnjw5V49LX3DnnXfqhz/8oSZOnKgDDjgg63BWW1tbm0455RRdcskliS+Kk3etra2aMmWKpk2bpl133TXRvtP+zFxTcY+RfXXO5cOSdjSz7c1sLUmHS7qjkgFMnTpVu+yyy3u2pqgmY8eOLVmJs5pPhgcPHqyGhgaZmQ444AASywQcf/zx2mWXXXT88cdnHUqfMXbsWD3wwANV/V4ClNIxcujQoZ3zCLfccsvET5Lq6up04IEHysx04IEH5i6Bqqur05gxY1LbTD7t7R7QvYMOOkizZ8/OZWIppbfaal8wfPhwzZo1K/HEUkp3LnCW+mRy6e4rJJ0oabakv0q6xd2frGQMgwcP1hVXXFH1SdA3v/lNSdK3v/3tbAPphaamJu28885qamrKOpQ+IS+vUQDJSvMYOWXKFK233no666yzkujuPdLcjL0S8h4/gGSltUdnlvrksNg1kfSwWABAdervw2JXF8dHAOg/GBYLAAAAAMgcySUAAAAAIDaSSwAAAABAbCSXAAAAAIDYSC4BAAAAALGRXAIAAAAAYiO5BAAAAADERnIJAAAAAIiN5BIAAAAAEBvJJQAAAAAgNpJLAAAAAEBsJJcAAAAAgNhILgEAAAAAsZFcAgAAAABiI7kEAAAAAMRGcgkAAAAAiI3kEgAAAAAQG8klAAAAACA2c/esY6gKZvaKpEUJdztY0uKE+0xDXuKU8hMrcSYrL3FK+Ym1P8c5xN03S7jPPmsNjo9pv7boP5u+6T+7vuk/2/7zHPua9B/rGElymSIzm+fuI7KOY1XyEqeUn1iJM1l5iVPKT6zEibSk/ZzRfzZ90392fdN/tv3nOfZK9F+OYbEAAAAAgNhILgEAAAAAsZFcpuvqrAPopbzEKeUnVuJMVl7ilPITK3EiLWk/Z/SfTd/0n13f9J9t/3mOvRL9l2DOJQAAAAAgNiqXAAAAAIDYSC4BAAAAALGRXCbMzNbNOgYAAAAAqDSSywSZ2f6S7jSzs8zsY1nHg1JmlqvXu5ltmnUMfZWZWdYxoPLMbF8z+3LWcQAA0FfVZh1AX2Fmn5F0qaTvSnq/pCMkTck0qJjMzLwPrPhkZrtJesbdl2QdS2+Z2RBJx5vZdyW95e4dWce0ugqvHzN7v6R2d3+zCmLZ1t2frbbXtZltLmmJu6/IOpbVYWYflNTh7m1Zx9JLNZJuNLN33P22rIPpC8zs5J5+7u7fT+h+PijpKklbuPswM9tZ0sHufn5C/e8laaqkIQrnRibJ3X2HJPpPk5ltIWmapK3cvcHMPirpk+5+bcx+r5DU7Welu58Up/+i+/mSpN+4+xtmNkXSbpLOd/dHEup/oqTrJb0h6RpJu0o63d1bkug/TdHrfDsVna+7+68S6nuOpC+5+3+i9iaSbnL3MUn0j55Fn2mnaOVnjiTJ3UdlFlRCSC6Ts66kqe5+s5ntLunnZnaZwgljbhOD6PvDJW0l6a+S/uDub2Qa3Gows1pJ4yQtknS5mdXk5PnYQNK+kn7t7g/lMdGPkrmDJB0j6QxJf8k4lgZJx5rZ6e7+VFaxlIsuJJwm6WRJuUkuzWwDSSdK+rWktmp+b0WjFtzd55jZCQqfz0e4+51Zx9YHbBD9+yFJu0u6I2ofJOmhBO/npwonYj+RJHefb2YzJSWSXEq6VtK3JLVKejehPivlZwrJ03ei9lOSblb4P8UxL+bf99aZ7n6rmX1a0n6SvqdwIeETCfU/3t1/YGZjJG0i6SuSfi4pseTSzAZI2kKlScK/YvZ5naSdJT0pqfDZ6pISSS4lDS4klpLk7q9GFzoTk2YCZWZfkHSRpM0VLgYVLghtGLfvsvtJ/LmN3CrpxwqfbYl95pjZGyq9KGRRO5XHpyskl8n5vaRB0fd/kfR3RYllXhMDSTKzr0n6qqRLJN0i6ejo31xw9xVmtkDhpEfV/nyY2caS3nD3BWZ2vaSzzewod38549BWm5l9XKGSf4y7Z5ZYRrEMVxhZML6aEsvIC5J2knS6QuUkF6Iqw7OSpprZn7OsTK9KIek1s29J2kHSbyTNNLOj3T03n2fVyN3PkSQze0DSboWLj2Y2VdLdCd7VetGFtuLbkrwY85q7z0qwvxIpnwgPdvdbzOwMqfO4F/tk1d2bi9tmNii6fWncvssUYj1Q0tXufreZJXXRQAqPtSQdIOnn7v5kklMjzGyCpLMlvaTSJHDnmF3v6e4fjdlHTzrM7P2FRCm60Jn0uVEqCVRkuqSD3P2vCffbKcXnVpJWuPtVCfRTwt03WPVvpYvkMiHu/pakt6Lv3zSz9STNlHR4VDWp2oSmK9EH70aSPinpYEkNkv4s6ZdZxtVbZjZM0ubuPlfhCuXRZvZtd7+kWp8HMxsq6aTwrX1H0o2StpW0paSXq7ky1I0hkh4tVF4V9tXtMLOB7r68wrF8WNK97v5/xbFUOIYShTm17r7EzI6VdJqZfdjd/5ZlXKtiZh+QtKO7/8bdvxdd6d5T0n3V/Bo1sx0lHSvpc+6+0MxGS/qlmf3X3e9YxZ9j1baQ9E5R+53otqQsjl57hQufh0r6d9xOo2kTknS/mX1PoSr0duHnSQ3NVLonwm+aWZ1WPjZ7Snotqc6j4+nPJW0amvaKpK+6+5MJ3cXzZvYTSaMlXWRmayvZNUFazaxF0vaSzohGXST5OTVR0ofcvT3BPiXpT2b20RQvzn5H0h/M7HcKCfhnJB2X8H2kkkBFXkozsYwk/tzayvU07jSzb0i6TaWfOYlN4TKzXRSeV0l6wN3nJ9V3T0guE1aURH5R0t5m9kV3/2W1JjTFooPT+tFVrF0l/UOhCnudpLUljY4S5ZMVXqSVGjKzWqIhDCMVTtavknSXwrCMMdGcgv9Uy/NReL1Ew/b+pZBQflHSnQrDnEZKqpP0tWo9aS/o4gLKC5LWMrNtJL0QJZZ7SdrezG5099SGnnURyzOSvmRmH4wql25hnvRW7n5zWnF0F5ukrRUqqc+a2W8VKjzvKFTV/latF6PMbB2F+eS7m9mRCiMaNlQYvnZfNb1Gu3gMl0h6QuF1qWiI7JWSfm1mB6ZZteonbpD0kJkV5rJ+XlJz97++2k6QdLWkD5vZ85L+Kel/Euj3krL2iKLvXVJS85/SPBE+WWE48gfM7I+SNpP0pQT7v1rSye5+vySZ2d4KlahPJdT/YZL2l3Sxu//HzLZUOGbHFn3enqXwmCx092XRuc5RSfQfeVYJJvNFblBIMF9USD4K1e4kqmZy999EF1f2jG76prsvTqLvNBOoaBSAJM0zs5sVpmYU953UsGEpnee2VSuHqUqlr3VXOA+IzcJc42O1chj1DDO72t2vSKL/Hu+7Cs9f+gwL25KcJelyd499hTVNUXKzm6SvKVRgt5D0dYUP4EMVkpvHLEy8P1PSF7yKFvEoStKGSnoz+lpf4f/wPoUhDDWSTnH332UX6XtZWGX485L+K+lmd/9TdNvWClfNtpI03N0XZRdl75jZvpI+IGmxu/8qGtr7nKT5kl5WWEzhaHd/oAKxfEZhIYR/ufvvogsNTyvMR/q3wnykE9z992nHEsVTeI2u4+7/NbOPSPqgwsntJZL2kjRc0r7u/kIlYuqNorg3l7TU3ZdFt5+vsEBGo6RtFBaGmJthqJ2KE8vCZ4K7/9vMblVYIOur0c/GSfq0pB9Ue8U4DywMP/901HzA3R9N4T7Wl1TjCc/9N7Md3H3hqm5bg34LJ8KfVTgW/VoJnwhHlb53Fea9msK0nBp3f7vHP+x9/4+7+y6rum0N+x4g6Ul3/3Dcvnq4jyfcfacU+i0sZvUxhcf+bpU+t7EWszKzNoULB0+oqNKa5LmAmR2scBFbkn7r7ncl1O8/VZpAFXOPsVBWdF7RHXf38Wvad9F9pPrcRvexjrv/d1W3xeh/vsLCXm9G7fUl/SmpixM9oXKZInd/y8y+U01X87sTVZXmS9pY0lhJ33D3djO7WiFZmBRV/TaT1FhNiaVUsnjMFIUk5jVJv3D3s6I31DkK8y3WyzDM9zCzPST9SNI3FIYeH2ZmH3H366KfPyhpo2pOLAtDIaP/y7UK1YrxZvZhSccrHBwPVBhm/a00E0szG+Du75rZSEkzJP2vpCvM7CsKF3qOUrjg8I6ksyqVWEqdr9FDJH01unJ+pcLV3McUHp83Je2ocFGkakRxHyxpsqT/mNlj7n66u08xs4EKi7Z8RdJQSXOroepalFhOUBgJ8FR0An6YQnXtVoU5NPtJ2s/dn8ss2D7E3VstzMNdR5KsaD5XXFa2Km0oSOk1Sa3u/lgCd/ELhQusxW5VuOATx0FF3y+TVF/UTmpxlj+5+24KC79IkszsEb33/7OmFprZmQpDY6VQMY6VdBdEn9d/T/K10oVHzGx3d3844X4Lc9v+FX2tFX1JycxdfMVTHLJvZhcqrEcxI7ppopl9yt0nx+3b3beP7qPLBCpm30dF/ezl7n8s63uvOH0XSfu5laT/03vfo13dtqZMpfNc31XXyX7iqFz2c+UngtFQt/dL+rikq9x9TnT7RxWunL1WjVXYqKpyj8KCQy9L2kWhCnuVu8+OfmdTD/PbMj/5LaoGHS3pI+4+KRq+82WFSvExXrSKWzWysPjQCndfGiWWX1aoVtxuYSjsryXd4e7nFn4/GvKU+ONvZpu4+6vR98MUktp73H1WNITrDklHRtXUtRUWB3m1kq8FC0vK/6+kIyV9RGE14Efc/YdFSfGuaVR74jCzfSR9X+HizOEKKzle7u4nF/3O7tHvHFQtr1sLqwOfIukQhblFe7j7qGiUxucVhvM+SMUyGdEFiEsURlq8rHAc+Zu7J7Lns4WVYUcoTBmQpM8pjIjYTtKt7j59Dfv9sEJ1YrpKh6dtqDDSJan4uzwRLr9tNft8n8IIl/9VGEFQOHHcUNKPk6oGRheWz9HKqvTvFVbHfzWh/h9QmIrzkMJFNkmSux+cUP9/U7hw90zUf6LDS83sS+5+66puW4N+f6Rwwf9OpTDsMyoofNxXLng2QGGdhMQqW2b2SHTho8fbqq3vov4Sf27L3rfjin6U9Pv2ZElNChexTeFY+DN3vyyJ/ntC5bIfKxs6tp/CELd73P1lC2O1J5rZywov+KHu3tNQhMxESdm7CleFF0Qn6W8qzAcZKmm2tHKMf9aJZWQThTlgT0saV5RU3GRmRymc7KzxSUfaLCyIcIzCHNGlCsNGDpL0opmt7e7PRVW6OWa2mbtPkPS6lPzjb2EFw+PNbGZ05XuUwnP/nJn9wd1/G534zjWzY6Kq8NtpxNJNfIX32XaS/uFhgZBHzOw5ST80sz8WJZSPlf1NNXhHYZGH4QpVwD0UFsIZJGmCh6F3aynMDa7IVdFy0WdA+fP5mqTLFC447aYwp0sKw4SSnJOD4DyFuVv3uvuu0UWJJOZEFmyjsBrtUkkys7MVhqqNVJjDtEbJpcJn1+cUTuKLq4xvKMxXSsoVem9FoqvbVscYhYtV2yhc3Cl4Q2GkQSKiJPKk6HPfPfnVYs9MuL9yae/beIZClXtVt62udRWOVWlUuws2VjgXkcLookQUJVDrmtmuKr3wEWsEmZl9UuEYv1nZiIYNJQ2I03cX0nhui9+3FxfdvlTJvm+/b2FNh08rvG6OqtTFa5LLfqwosTxRYbuROxWG7I3ysCfUuwqLyqyrcMWj6liYT7Wtu99vZs9I+omZHevur0eJ8YeyjXClomrlCEm3WNgW4R5Jf5B0iIWNsJ9RWB02kUn1afGwDcUNkmrN7Dh3v9rMVkgaL+nPZvYnd3/ewoqc20V/k9bw8OUKcznXjmK53MzeVqhyfMLM/i9KMEdp5bCWSvqownC1xyWtsLCX24Me5oHep3CAeVRa+Z7MMrEsep2ur1CZ/mN0Rfs6hbmJj5jZzxSuiG6tMDzuBYUN7ROpZKyBdTys2C0zG6+wLdR8hSHaf3H3vaKfHSmp3sIcrNczirWvWu5hKkWNhaHy91vY6zkpm6uoeqPwvt/Cw/STNZ5b6O63S7rdzD7p7n+KG2S5NE+EPWwV0mzRwoFx+uqJme2ksLjMplF7saQmd1+QRP/RZ+EWirYMk/SQJ7j9lrsvij53d3T3681sM63cOm6NRaMjDpC0tZldXvSjDZXANjkeDf9M0QWSHjWz+xWSv5EKW2IloTiBukQrk8vXFT+BWkvh+avVyuGrhb4Pjdm3pHSfW3dvNrM/SPqCwo4A7yrMk56ZwnHpXYXE0pXsCsk9Irns56Ihg42S9lFYjW9tSU+Y2fBouN59Cot4PJtdlKWKTn4/ozBUZ1CUIJ8vaYKk31tYvOUkhfl1VSGKuTC08C8KQyI+r5DAf05h6N7rCsON/p5VnKtSePyjCvcRkvY0s3fd/VoLi1idIekSM/uduz8v6fk044kqZ29bWDjjM1EsP7GwHdCXFFas/a27/7Y4/jRjKnqN7qiw1Put7n6cmT2hsLXPbmb2uMJFm/9NM5bVFcV9sMKFgo3MbLqkBxWStU9bGFY8XGEBn4XR3/wzq3jNbAeFizWHe5gLvo7C6sS/NbNTJZ1lZmMVtqM5TNJXSCxT8Z+omv2AwqqEL6toiGMCZihcuLo9ah+ksFfp+gqfp2skev1MkfRC9P68VGELrr8qDIt9JlbUFTgRdvdfmtmBCiNe1im6/dwk+pf0E713tdirldBqsWZ2mMJw+98qJCFXmNkp7v6LhPo/W+Fi44cUjrcDFT53487Pe0HSPIXP9Nai29+Q9K017dTMrlAP8/rc/aQ17busnxujylYhqT/N3V9MqO/ULnx4WJTxd2b2M09vPYoXFJ7TRJ9bSTKzkxTO+R5QeF0+qpBkPmhm3yicq8RlK1eL/aXC++p/jdVikTYLG+b+V+FFV6+wb9V+ZvZzhQToQx5zpby0REOuLlXYdH68wgfBzZL+pLDC6n8l/dXdW7KKsVg0bG8LhSG633L3uWb2ZUmXKwxVuMfMNpI00N0XVyIBSoqZHa6wj9Jj7v5TM/uawkn8oZ7gfk29iGM9hX3SDpA0L4rlNIUTilM9oSXWVyOegxWqe39RWEjoV+5+UpSQ76swBOln7p7kRvOxmdnHFTa9PknhpGO4wknfCwrDa/aXNM2rYG/IoiR+msJw6MMVFkd6x91/Gv3OF7RyrthPPf190fqlKMl7S2FV7nEKr+8Znuz+cCO0MiH4oyewHZaF+X43KsT7PwrJxy0Kx8Rx7p7IViSW4oI1ZvZjhaGG+yiM4jhUofp3dEL9p7ZabKEvha3OXo7amykMr06q/8cU5nQ+4u67RrfN9+TmXCa6d7OZNUXf7qUw8qWwXdaXFEZifC2h+7lTYT/2OzxaUTRNZjY3ifdTVEy4KTpX+oDCe3YnhZXgj3H3J+LeR9F9Jb4vd3QR6+MepnCtpzAdbW8ze7+k2wuv0QTuJ7PVYuXufPXDL4UFe64rap+tsC2DFK503KUwhCTzWMviLlwQmS5pcvT9AIXhHXMljcg6xh5ir1XYG+zDkgZEt01RuLr/6eL/Xx6+JK1d9P0BCvOHvhG1t6lwLAOjf9dTqAb+qCiW7TJ4bNaVdK+ksVF7fYVKyGVFv7NJtT3nCpuMXy/pl0W3HaKw0MaQqL1hNcRdfP+ShijMC/2jwvDd7yisBLunwgnatlk/tn35K/oMvr8C9/NphYtxUli5fPsE+ny06Pt/dfezGP1vJOlCSX9TmNvWHn0WXChp44Qel/ll/w6S9PsEH/fbFOZFbhd9TZF0W4L9P1HWrim/LWb/D0X/PhL9u37hsUrrS9KsBPp4UFJtUXugwpSKpGL8bHSsXKSwWvKhClMMEnlNln09oTCsfX7cx15h65rC93cXHWf3VrjolET8GyqcV/5cYYeE4p/9KGbfTyg6f1JYf2Ne0c8WJPj8PlH8fCqMakjsfdXTV43Q51lQ/lz/RdLHzOyMqL1E0i7RcIzjJB3r7v+oZJy94dE7RGHhk+2jq8HvuvsZCm/S/7GVm/dWmxqFYcdHFt32W4Vq68/NbEjR/69qmNm60fwDmdkuFvbglLu/bWbbm9n33f0eheFBO5nZtl7BrR0szO9abmbbKyzeMlfhcd0tiuWZSsVS5L8Km7y/KEkerhyeoLBFyyXRba9G/1bTc75UUpukjaOhpPIwJ+2vWrnwyBvR7ZnGXbh/MztGYWXi/1W4KHaEwlyWvRSGL52n5JaORxfc/V1JHdHoi1REQxtPUxh2L60c2hhXh5l90MKKx+tF1dHCfP4kFge5RdKrkvZ2903dvU6hwvif6GdJKGz1sMzMtlKYj7plQn1LYXTQZgoLyfwq+j72XoJFfmNms83sSAvzou9WWI8gKbeY2U8UPteOVbjwd03cTs1st26+hitcwI9rE4Ukp2BQdFsi3P137v4NSTsoDH0+TGGl5yQ8o5BIHqYwhP2gqO/C93EUT+nb3N1vkyQPw0k36PIvVt/1CqP6finpcDP7ZTQlRAoXLeO4RtLDZvZThfO/K6XOin2So72uV5hKMNXMpipcrLg2wf67xbDYfsDMBvnKFfa2URgy9rKZ7aaQSE5ROIjWK1TVbvIEhxWkwcx2UZhP+aDCm9Ml/VChcnWXu1+YYWzbSdrA3Z8oGra3lru/Y2aDFYa4LFQ44ThIYQXOYyRd6e5PZxV3dyzsSXW2wgnRQElHuPtTFvZqvEWhYnF+9Ltbeopb1RQ9nnsoDBeap7DibofC/IXb3X2ahbmfG7r7S2nF0kVsNV60aJGFfeG+IukTHrY92Uthju2nFaru91cqtp4UPaaF/Uo3Ufhc2FIhOf6twrDBL7v7QxmG+h5mNkahSjnO3Z81s7UUtqFplNTgYeubAVHygxRZmAu5q6Q5Kt1OIpH5YWkNbTSzfRWqNx0Ko3a+pbCV1YYKF1lv7+HPe9P/3929y4XlevrZat7HmQojR/ZVOFF1hSHgZ8Xtu1LM7ItaOeT594WEIcH+Ryuc45ik2R5tsxazz3cl/U5dr5K9p7uvG7P/oxSm/hQvuHOOu/8sTr9l97GuwnnIlxUuIN7lYXX3JPoeq/B+utjd7zCzhe6+QwL9fldhMblzFaZCLFOoro+S9EV3/1wC9/GYu3+8qP0dhRFaB0ua4zG3OzGzjylsSbbAU9wOK7rQUfy+qshqsSSXfZiZmcJwseskNSis2nWZpOck/UbhA+tKSTck8UGblsLJb/T9Wu7+TvT9sZI+oDAvrE7hQ+bjCv/n6VlVVszsGwrJWL27P24r9zD8gMIk7hsV5gZuKuk+hVUQfyhpjIcFcKqOhQUcblEYUrFvdNsISVtFB42SxCrlWPaVdJXCRYWtFCqVz0l6ySs8xzZ6Tr9UuJgRjRAY4NEcDTObrFBJm63w+jxY4UrubzyhSftrwsJ2MW9H328cJWG17r4i+tzYUiFBO1zhCvTV7t5Syee5m7iLPwsGKszt+6Gkb7r7NdHtAyRNU1go4QCFFW9JLlNmK+eJlfCwsEcS/T/k7ntYtI9dmvOHoouArybxujGzFoVKWXPhYpeFlVGPVJhnuF/M/msUEpn/i9prKwyFey1W4KX38UFJkxSGxHZWjTyh+ahpM7OL3P20Vd22Bv0uUBiS+Z5RXmb2rLtvG6f/qJ/3SfpE1PyzJ7TgTtT3LQpbS/1G4aL375L+fI/ep+cpnKsNd/dtEur3SIUCwwcURoQ9qzCC5aIkXvtm9ldJHyu7YHykwl64g9x9SNz7qIToeLiFSt+3qcz9LlE+TpavvvOllRcPNlE4ydpBYf7HWIVlj7+uMIzsMYWhBZnH3E38m0b/1kT/DlW4Or6TQqVyS4U3zwGSFih8IGQd+zcVhhJ+PGoPVth4+syy3xsePRc7ZR1zd49/9P2GCge4axQ2LC/cvkmFY/qQpBZJe0XtvRWuXjYW/U7F5gIqXD19W9LZZbfvoHAFWAoL4IxW2MT7M9H77QMZPq81ChWacQqVoJmSNop+tq3C3LBdos+N0yRdpHASXE2vx021cu7nV1Q076bo/1iXdcx8Jfr8T1IYurcwev3+SWGf1TTu6+oE+9okeg8V5lwuiY4NFyX1+akE5oauov/Ho/OFPaJj1nCFRCFuv28orJpb/vWGpNcTjP+RLm6LPedSYY7ih7r52ecT6H9s4bM5am+cRL9F/Y1RtP5D2l/RMeVrlbivhOKdLmm/Lm7fX2G/6sxj7MX/YYLCtnZPauW811TnGhe+qFz2UWVX+DdXGI53icLKUQvM7MMK48b3VVj4Yiev8GqavWFhft/JComZFDacvVTSs+7+3aLf21BhT7uzvEqG9JrZKQrzUo5QOGB+2MPcxOKhiBtJWt/dX8gw1G5FQ4kOVIj/VoUTo/MU5jVcopBEf8tTHApbFEutwmN5jqRb3P306PYjFRKlAzzhVd1WEU+hIr2tpD8rDEM7O3ot3izpD2Wv0Y8qLOj0DXd/vFJxdiWK8UWF4Yt7eRjmPEhhO59n3P2y6Pc2V5grOkDShZ785umrzcwmKQx/GqLwGnxM4er1OEk3uvvN3f810mJhBcTyE4rXFIaun+8JrBqbxtDGbu7nEY857K2X93OUu1+fQD8XKyTbv/IUTurMrNXdhyfdb9rM7OuSCnMKi6ecbKCw8Mv/pHjfsZ/b8qGZ0W2PekKriZb1m/pr3symuvvUlPq+2t2PS6PvLu4rkfdt2sysTWFaTmIrdvf6vkku+5ZoSJuKEstjFK7u7mJhA+fvSBrlpcM1t/YqHI5pZnsqnIyPU7gCs4XCUvHrF5KZ8mFylUwuymItJIsfU1js4A8ehhh+U+Eq++GFpLc45mpmYfPvGxWS+88pJJaPSLpTYX7PRySd5+53pRhD4XEdLOktd3/TwlYeDZIecPdrLMy/vVhhTmDFtj6J4iu8h7ZTOLn7ibtPNbO9vWxfzSihq610jGXxds6vVNin7mCFE//Lo58P8WjfsKJhsoMVPlIqfoAqFw2JnqYw//czCivZLlBY0e8whcTjaElv5uE91pdY2A/1XYVKuBSGVK+ncBHj0+4edxGPijGz37j7/hW4n3+5+/sT6OcNhRVQ31XYDsYU3rMb9viHq+63sDjeSQqLsdymMFJDCneQ2GeZmX1aYYX666PPnA085v650cXbTRRW/Ty96EdvpP05nMRza13MKTazJ9x9p3jRdXlfqSStZfeRWgJbqQtC0X0l8r5Nm5ndrzDqaEWl77t21b+CnBlQeCFFJ2JHKVQt5e7fNzOXNNvM9nf3x6Lbqy6xjGysUKUapDCX8jB3f93CokT/lt6zYmXF30AF0Qn7gQobQf9R0gVmNsHdLzOzDkmzzOxgd38kRye9IyRd7+6/MrN7FKqGDQoLPh1pZlu4+0tpJsvR4zpW0lmSXjKzu939iig5OtnMPq9wFfp7lUraihK0T0ra3Mxedvc/RRdD/mxmb7v7BdHvds5RdPfXKxFfT6K4d1MYUj5JYf7IX8xs0+iK8kZm9mF3/1vhc6TKRjQMUBi1sEzhc+wNhRELf1BYOfTWaqiu9lP7lZ3cPWEr50eucYUoeo67+nxJJIHqSpKJpYW95rr8kcIF09jcPakVMsu1Kjz2hQVrTim+W4WKYGwWVgIeoTDt4XpJaym8n/fq6e9WxcPcu9fMbIqkFz2scL63pJ3N7AZ3/0/MuNN+bueZ2fcVrSaqMIqkNYF+u1KJ/Za7WvgoKUmtciupMu/btESFJClMIfitmd2t0otC3087BpLLPiQaMjTewobE/1C4ivlRhav5P5Ekd7/UwupgvzSzj0haXg3JjoWNZPd097lRUiyF/cCuVRha9SkPi47USzrAzM4qP1nP8v9hZjspDCkcrbDi2hcknWVm33X3y6NkKK0TgLQ8K+mQQrIh6XoLQ1CHS3rYo8UpUhqGVUjgBioMgZygsLruvVGFunChZH+FFdDuKv67pOMpFsXVoLA41qWSZprZse4+08J2Bk+a2QbuPtkzXPymBxtJalKYy3O5mX1KUquFhSM+q1BpryoWVtrdRmELpWVRleNBd/8/M5sjabC7z1fRARQVN8DM9vBoReHovVDYymONL/ylmDiVsLBozSkKw62TXLRmC4W5ba+W36Wk/4vZ98rOzA5WWE1Ukn6bxIgSd98+bh+9NFbRSsDR/b5gZkk+77+UNMLC9jJXS7pdocJ+QMx+035uJyjsL1oY6j9HIcFMhIXtu/7t7v919ynRueEWnuD2XWa2l7v/MWoO7+K2RKQw0qAi79uUFN47/4q+1oq+Kobkso+wMDfxXIXhYZsrnHTPkHSiwt6Pr7j7ryTJw1YNP/Zo1dUqsVzSURaWex6sMPH7YTO7RtIHJW1bNPxxSjVUgQrMbBcPw4y/qrDY0FkKMV8gaYaZfdVXzmGryiGxRcncngpXj3+vsILc7pK+aGb3KgyL3UDJ7sPUpSiW0QpzggcpTKB/ycxGKlyJW9fdv2thFPjnzOwId7+xEo+thSGw5yos3z5E0kuSvmtmG7r7j81smMLiPVXFwsq2L7r7/Wa2QtKp0fP+AzPbWWF12Jnu/odsI+3yfVJYDOlWhWGwh0qqN7NnFT7rLqp8lChzjKTrLMzdNYV52kdbWC3ygjXt1Faxb3GCIxZulfRjhakYSa4ufJfC6pKPlf/AzH6bxB2Y2YUKn9UzopsmRifwZ/TwZ6vT/wmSZhQqfRa2KzrC3X+URP8K26N5dMGwsMJokjo8DPH/gqQrotEvSWzJkOpz62F/5NNX+Ytr7lZJnypqvxvdtnuC93GFoj2Siy62dt4WR4oXhKQKvG/T4u7nZB0Dcy77gOjgu1jSIe5+p5m9X2GlqxlR+3CF+S83u/uN0d9UTZJTlNh8XGHj5HnufnD0sw8rXD06XGHuzvUetr6oivijoZG3SNrXw6IoJyusvHu6mR2gMMf1OHd/MtNAe8HM9lHYtuZ+heGvhygMfRqlMLT6TUlXufsvU4yh8FoYJulnCkOMhynM8/yFuz8XvSb+FN3+jsL8u997ZfbXXDsaWvV+Se9TeDyGm9lhkm6S9BV3n1H8N2nFtDos7Ek6VeGE/7vuvszMPqswMuDnCsOKl2UYYpfM7CBJa7v7L8zs55IWu/u3ots/qTCf6gp3/0umgaKThXluhSGJSfT3T5UOzSzmnsC+edH95HLRGqlzCN/HCyfvFrYfeNQT2qbFUl5YxsIiXTsqjPy5QGEhvJnufkVC/f9ZYaTJdyQd5O7/NLMF7j4sif7TYmabSTpV0sckrVO4PaHkqbvn9XF33yWBvj+pkLh+U2GET8GGCit7J3EfjytcEGpV0QUhd09r6HCuRKN6vlR2Uegmdx+T9n1TuewD3H1JdLI13cx+5+7/srC571bRr9yjsA/QIWZ2l7u/UUUnvYWT9lpJbQor1/7QzK5x92Pc/W9m9o+oulI4sa+Kk3Yz21HS9yV9292fim5+TGE47IUK/5dv5SSx/KBC5aHJ3R8ws+MVNhaf6O4XRRXkAe7+cpqPf/Ra+JTCPpanuvtsMztU4SD1BTO7LXpNbF1Ihszs1jRfD0Wv0YMkHWhmp0XvsV0VqmhSGHoyS2FPyM7/S1ox9UbZ87REYTGOgyRNMrNL3f13ZvZrherwNQobUWeq6LE2hZOpyZJ2tLAR9GmSfmBhsaQ7Jd1pGS7iha65+2tmdpfCImBJ9Jfq0MyiyuidFvYoTm3RmpRtrJWjSjZKuO8BxZ8nUfKa2DA7d7/YwkiV1xVGzpzlya4EfJSkrylcWPunheGgP0+w/7TMUBgS+zmF+JskvZJg/69YWAviDkkys0MUChVJWEth1FGtSqcEva4w8iQJK9z9qoT66os286J5xe7+qoUV4FNH5bIPsTAP7HKFDdu3kjTO3d+KfjZIYZ/IahpOWjiRHK1wxfIJd/+5hXH/sxT25rlLYS7jgZJe9iqaw2Zha4nCRPvR0bCbzRSGlBwk6XZ3/01mAfZSlNhPVKgO3ybpguh5OUbhhP7r7n5vBePZWGFu3cPufkh021iFCvZTCo/5Cg+rtFbkQkNU1S1cSJgb3baHwpyY/yoM2Tza3f9YDRc/yt5bH1dYtfMyhWrfvgorS96lsArkOe7+p4xC7ZKZDXX3NjPbWuHK94cU5pF/XGEu8NGVfP6xepKsapX1m/i8wkpVRtNkYQXtCxVGnZjCY3SGu9+UUP/fUxh6+JPopuMVFtb6dhL9o2uFaroVrRprZg+7eyLDVi1MlZihsF+zFD5bv+LuT3f/V6t9H0N85QrkNQpDTWOdh1oFVzHOMzNrVagS/ytqD5F0m1dimyWOy32Lme2nsMn8+6Iq07qFBLMamdkYhSETkyT9QGHC+sWSXlConG0k6X/d/bbMgowUnbDvKGldhU2xt1PYquNdSd8sr6Lk5eTXwjYZX1XYL/D3Hs3PNbPjJP3V3X/f09/HvO/C47qTpIEKFxVqFTb9neXuJ0a/d6ikv3gGQyDN7FSF5euvKqqgr6VQUf2IpKfdvaXScfXEwrDXqxVWXG5SqK5eqrDIytEKm1p/P6oCVoWoYrmVwgqwv5P0T4UFvd5QWODrSwoLWnzQq2BrFHTNzK5z9/EJ91k+r/AIhQtQkxPqfx13/++qbqtWZralVs6Ve8jdX0yw7xpJxymMxpHCcfoad09kbqqFuZAXKawXYdGXe0IrAUfH7AsUFjgsHl5a1RcOzOxBd9/TzGYrFA5eUJge8oGE72eQJHkKK22b2UyFquu7kh5WGBb7A3f/Xow+c39BqBIsrMVytcKx1BQugh/n7rNTv+8cnPdiNUUVzIsl7ePuiS7PnCQLK8RerbBv3fsUkst5Ch8a50XDVzZw9zeyTtKKEqCDFU7WFygsPPQdhXl/X1OoDh3nGewpFIeZreXu71gYj98kaVuFk7ZErnr3MoZDJJ0h6aHo/s9QmGP7oKT/S/pEdXWZ2XcV5tIeW3TbTgpzAN+z52o1MLOLJLW7+/So/QNJ73f3sVF7Yw8rMFfFe6vsto8ozDP6vEIS/KTCxZsXLSycVDUjMFDKwgrPwyQ9n+Txx9KfV/ieffK6uq0amdl97r7vqm5L6L42lbSNh9WZk+qzTWEu5F+T6rOs/z9IOlvh4tpBCsNka9z9rDTuLylm9jmFxfW2VVgEZ0OFkSZ3JNT/RgqPS2E0wO8knesJzZeO7uMxd/+4mY1TWMTndEmtSbxv835BqBIs7Bm7Z9R80Cu0tVhNJe4EleXusxTmKv3GzGqiakDmzGx9C8vTy8xGKVQoTlBYKOYchX2uTlOYX3CcmW3k7m9I2c1fi6pT0bf2gSjefRSWMt9GUpu7L1CYVN6hMHwvNyzsw/iOhTkohyvsLbZY0ictbE1RiRi2Uhheuq/CsNctJL3qYa7AnpJGmdnHoqvnlYjHon93M7PPmNnHFBbI2tXMzop+9mmF18C2hb/LOrHs4n3+tKQ6C8OM5e4TJQ2KhsZIoSKY9RY+xfO4PhL9OyA6ybxDoVryoMICU9+LEgr2sawiZvbj6D1SOFl9XNINkh6NhmsmaeOi7xOZV2hm77Mwp3ddM9s1et/vZmE/xPWSuI+0mNk6UbI32Mw2MbNNo6/ttHKoYxL381sz2zC6r1ZJPzWzS1f1d6vhpbQSy8i67n6fQkFlkYc9fQ9M8f4S4e53uftr7r7A3fdx9+FJJZaR6xRGhRwWfb2usM9okgZGF5w+L+mO8tFdMXW1JUi1bxNSMRa28Hormj6wsaTJRcf/VLGgTx/l7rdHVy6rYo5iNGTnfZLONrPXFTZxP9ZXzqtaX6Fsv4GkRyXdmOTVszURnZT/2sxOdfeHzOxNhc3aj1f4oDzE3V+P3sB/lnSSV+GKmwVF1dc9FIYHzZP0tJl1KKx0eru7LzazqyRtkuSwqi5iqSl6bdYoLObUpDDU7aseth3Zx8O2GUMrWQ2OHqMDFeb6PqpwEeQhhT3R7jSzD0n6sKQJHu3plyULc2bfjeLeXWHxruck3aew4u8oC3MvNlQYdrZcyj4ZLo7Bwvzeg83sKx4WhPm0pD087Gd6vMKiZA8nNQwPifqMu38t+v4oSU+5++eji1OzJN2Y0P1coJCwFs8rTGKbhjGSjlS4WFi8ufjrChdpq9nxCnOSt1JI+goXmF6X9MME72ej6Fh3jKQb3P1s636T+V6zMBxWkuaZ2c2Sfq3SuXO/insfkbeji5P/MLMTJT2vsNhMbqRURf+Au3+xqH2OmT2W8H38RGGhu8clPRAlN7HO7aLPlq0VXRDSytf9hqryC0IVdpWkXSxs43eywurwNyjsZ50qkss+LI3x82vCwtYRtyksL36DwofNbe7+YJRk/CUatvJbSZtKOjnJITdrKhoy+GtJV0YH1QUKy6UPU1gsaaGFeW0/Upg0/VT3vWUvSj72VfjA+ZOkcZLmKiQiZ3o0ZzCqGP4njRii6u9Sd3+p6OYXFIZCf1vhcWyL4rzYzL7k7m1pxNJDjOsqVFK/6WFF1fcpbItykMKchY0lreNhxdish5S+T+GgcZGFvSpvVKiofkrh+T1Hodr+FUUXd9z9hYzC7VJ0ceZQScdEieVOCp8T35Q690bLfM41ulW8X/JohX3yFA1hTuxO3P1GC/vLFeYVnpbQBbCNFOab7+EpbrOUBnf/gcIKyhM8oW07ulEbXSA+TGEqSFIOKvp+maT6orZLSiq5nKiQdJwk6TyF7bWaEuq7UtIYgfaWmX3ao72NC5WuJO/A3S9XmC+q6D7+pfD5HkdXF4RcoQpb7ReEKmlFdN53iKQr3f1aMzu6EndMcolURcNzfiHpYnf/k5m9qPDB8NOoIjg9+tVzJNVJWt/dk9jcOJaipGGOpL0UNtb+ssK8h3MkNZrZWwon8KdVe2IpSVHF7TRJR3lY1XRvhYPsu4XEMs1kKbpi+WeFE4qXotsGeFj18y6Fq5nfiSoTJylsRVKRxLIQR9TsUDhhLgzJftHMrpQ0yt3fUVidTtHPsq7+/UdhQaHvKlQrDvOwlcxXFKoAh7p7k4Whx+tFiXvWCXHxUNj1FT4PhkjaX2FLlFqFDdr/nHWs6JX/WJgb9rzCZ+XRUmdFfd2k7sTCitFzfeW2CRub2efd/dcxuz5PoQL6tIVl+m/1Cs1LSlCHRXOoJcnC/Pkj3P1HCfV/rsIq9H9w94fNbAeF1ZtjcfejYkfWu/t5OPp2qUJ1PY/uTqHPr0tqtjCc3RS2sjkyhfvpFCU7ZyqcU61pH80KcX/R3X9pZp+RtIfCjgNVtbBext4wszMULi5/JqreD6zEHbOgD1JlZkcpLMIw0cJl7F0UhuaNUKgOnSlpkcLVpgOraVhpNDTyIoVK66cU5lOOVbgC+mlJmykcbB+o9pPg6ETvCIXE+BZ3Pz26/UiFBPmAhOdCdBVDoUL1G0l7K+xltjyax3OIwh6hIxVWlXsyGhKb6uNqYa7pkqhiVlsYfhsd/A6VVB8N0f28wknzYZL+m/VzbWEOyzoeFrvaVNL3FIaaT5U0O0rY/0dhAYv/8QqsDtcbZYnlFpJed/e3zOwUhcrqXe5+f/Tz4qHTqFIW9si9XOH5u8zdfxbdPkbh/ZPIdhXW9Ybvj3rMLU/M7FFJwxVWQv2ypIMVhpjeKOlXHs37r2ZpPTaVYmbNCnsq/ydqbyLpEo+5kJuZ9Tg/0d0PjtN/2qLj0789WqAmGlWzhbs/k/D9bChJnuBCaT0MmzaF1b7XjtH3Q+6+R/T9MQqjc36tUPm+090vXNO++5JoZFOjwpSS35vZ+yXt7e5xK8erROUSaVso6ZjoROPLCleyP64w3OVphUVk3pH0w2pKLCN7K+z5OMPMfiLpRIW5iePdveSqW9bJRlcKJ/IWVgt7y8MeoiskNZjZMe5+jcKcwnEKc11T2RvKzDZQmFf5hEKFrVFhvuLy6MPvTwrDch+N4ulUgcf1A5IeMbPto2HQa7n7O+5+noXFnB40s2sUruae5FWwrU909XE/hauSH1CoXJ6ssI/l5xS2cHnO3f83uqDzTnd9VVpRYvkthf/Demb2G4WK5dck7W9m63tYyILEMgeiURv7d3H7bIVqV1K6WtAriXMYj15rLZJaogs3DQoX4y5WuIhY7QaUXbgZoLCJfeIsnbl/O/t7N3tPIjH+pMLejTcqjJqpisUNV8OtChe2C96Nbktqn8uJCgv4vKEwmmw3SacnVP3bQmFUyqvld6v4i+4UV9+OV7iI9YqZXaywABzJpTpHXf1SYTqXFBZrrMgUE5JLpO1hhQ/DixQWbfmBwtzF7RUOfhdI6vAq2BKhC4V9DGd4WFH1LoXE6KZoGMabXsULjESJ5VhJZ0l6yczudvcrouTk5Kgat4Gk73lKmw5HieVFkh6RdKdCgvm2pA2ioVUbKmw7879p3P+quPu9Fla0bDWzEdFJzdru/ra7n2lm/1CYk3q/u2e+Cp2ZbaYwN+kthRPf90maFFVev6GQpJ1mZhd7WBXx59HfVc17y8y+pHDyvr/C/N/93P2iKImfIGlPM5tbhReb0AUzu0JhvlOX3P2khO5qnpl9X9KVUfsEhQpjXCUJRzSC4w5Jd1jYLisPfiPp5ugiqBROuH+T0n2lkaDVmNkm7v6q1LndSRLnp+9TmAd8hMKx+26FxQKfTKDvSqj1MBVDkhSdhyR50WC8u/8guvhfpzB88ucKF1riukvSIHd/rPwHFuZOx1ETVbdrFEZgviJJ7v5mdAEdkszsWIUV1zdVuJC+tcLOBolvUVSO5BKpik4QLzOzG4oTGAurV31a0kCPFnfJ8uS3qMr3aYWVa19X2P/pPjP7jrt/V+EN+idJP01y+EjSiv4vAxXmVE5QuHp4r5kN9LACpyuc3P/ewzLVqSQg0bDNhxRWJ1uqMHdnQ4XhmxsrzG+6Lrr/TIZBuvtvLKwgOM/Mdi+8TqMLCCMUFp/KfGhclFh+XeFK8x8VXou7KCzKsJW7vxANc75ZYcnxiYXhVNWSWEaWKVSwT5G0ncIqvFIYbn6BwnBfEsv8mFf0/TkKn5tpKEyjuFkhmZ2jkGDG9eXufpCj1+FpCgnl16P2HIULTbFEnyE/MLO93P2P0c1pzP27RNKfzOxWheT1UIXPiFiii7+/UdiWbW2FJPO3ZnaOuye5mm5aXjGzg33lPONDFKpPSSlcKDhAYRXgJ6PRLrG5e7cLx7h7Y8zuN9LK1ZHdzLZ093+b2SDlrzqdphMU5qL+WZLc/R8W5pWnjjmXqKgo4RmtcBI52d3TOFCtEQuLUpwj6WqFE5mzFKqsv1YYrvlpSScUkrFqZmajFa5ObaEwzOUlM9tRYUXeH7n7d82sUWEY5Z3untR2AcUxdCaLFjZQPkDhQP+/CkOjT5L0d0k3u/s/k77/1WVmDQorqu1gYd+++yUd7+6Zr1RqYc7sGZIGKJw0fkvhhOxDko6VdE80DHZjSYMVFsZ6PKNwuxRViJ9QSCivlPSQu38p+tnxChcgxjsbYOdWpeb5FU4m076fPIkqWh9SSLz/7gnMobdoLmdKQ2HL7+tjCntIS2Hhpr8k1O/aCntaHqHw2XOHpOvc/fkk+k9TNO1hhlbuWfqspK+4+9MJ9X991Pf2ChcqB0j6rbsPT6L/SotGGmxRDecT1cDM/uzunyh8LkfnEY+4+85p3zeVS1RMlFjuoTA/bErWiaWFhSi2d/fZ0RWvYxWG6+2nsHLpg1E1aLjCvJt13P2pahpiWKyoYjlMIXn/o6T3SzrCzH4RXbXaV+EK8c8Urm6vkPT7lGLpMLOhkv6tMOflJYVFcTxKhH6o8Fq4Oen7XxPuPsvMTrCwCvBrko5z919n/XxH97/CzGYrbIlSp7B9y9clTVOYxzwuGg1wrKR9vApWXO7CRyQ1uvtBZra/pOFm9kmFoedHSjqcxDL3KvU+uVtSqslOnlhY+btZYT9Bk7StmTW5+wMxu/5rNDVgKytdoMUUPscTO0mNqmavSFpHkszs/e7+rzh9mtkNCluH3SPpHHdfED/SyomSyD2j85M0tpc7WuFC70J3XxYNR87rarqFkQYkliv9zswmK+wHOlrSNxSmJ6WOyiUqKkow6zxMNM7spD1KLH8tabq7/8zCKmxXSfqLwlXOY6NE8vOS/lltVaDumNmnFP4fp0ZJ86EKJ+/PKAzvfNbM1isM90rzOYgqgecpHNiHS/qiwqqwDZJ+5+7Xm9kG1TDktJiZjZK0sbv/qgoSy20V5gpd4+7tFlYwvkBhM+SNFE7EzlFI3HaTtMjd78sq3p5Y2HbkIkk/dvcFZnZR9KPNFd6Hf80uOiShEhWu6H4qUiHNCzNrVbhw8/eo/UGFuYWxK1AWFl2brbCKbgl3XxS3/+g+DlYYibGVwlZPQyT91d0/FrPfDklvRs3iz/FCcrxhnP7TZmGLkLMVVlGXpN9JOtfdX0uo/70kPeZhruL/KBxDfpDU84psRUOcj1FYRdcU3sfXVOKchuQS/Y6ZfVRhqMlUd7/dwgI36ytUgs6UNNLdH40+eH8iaVyOksuNFRLkh939kOi2sQqrtj2lMBxxhYetKhJNnCzspbi2QiL7QYVq5aGSvhD9O9rDHMwvR7d9y91fSOr+k5Z1YhnFcL5CdfcehWGx7QrJZp3C1i2fVFg57wIv2puvGmKP4hivkAT/xt3/ambnStrGi7YYsKItYJA/ZvaGVp64r6cwp1ZK8QTezL7hye3hmHtmNr+8itjVbTHvYy2Fz3UpoWG3RX0/rrA+wL3R8L19FLZQqsiG79XKwkqfCxSq0lJYcGcXd/9CQv3PVxgOu7PCqJhrFPZK/mwS/SM7FlaMftLdP5zF/TMsFv3Rpgof0LdH7VkKcwF/HP3segsLCxwu6YxqTiyLhsLupJBkPKmw7PR8M/uhu5/o7rdFHzR/cfe3C3+bcGL5YUm/VFio5xVJHQqrzu2osDfkEVFiuZe732xmv/VoIadqlXHFspBwna2QSO6kMOT1HwpzZAZG3z8rqSn6nc7kMsMRAeVJ7WMKW/h81Mz+n737j6+6rP8//nyNoSlkylAzLdCQMlFTkEyTlGI4f6aZ5kxXWqYfJcuQlC8ZIqGilvkjs9KaBdlPP/5cDhulfawUNBHTaBnkz3RDTcSMudf3j+t98JwjjLH3+733eZ897rcbN3adbdeunXN2rvN6v67rda2UNFfSrWY22d84e7NiKy5jw9z9rf31sywUXNvZ3b9tocDVUPZXSQrFyL6vsJ9dCsdLLerh6zeKmX1Y0g1KftltwZpoZUaNhb36C83s8oT6zrN3u/vHi9rnm9mfE+y/K3r/cITCcXDXmdmADuirRZRA+GsSy8v7guASA467/97MDjGzxxXO2vw/d/9m9OlzohfvlxSKCvyhUrJA61I0MZwr6T5J74w+HqtwRuP17n6Su/8irTGY2UhJv5D0DXf/eXTb8wqVygZL2tXdV5nZBEnTzOyUSs5YZi1ahnZ0tMTwXjP7rkKxmyckrVEoenGIpPe6+6FmtiyFvTgbrfjvxMyaFPaCdrr7SVFW+0pJl0jaSdL+ZtbqkexGjbwws68pVG9+j0LF5MEKwdR+WY6rQpym8HpbOPblHklJZna/oXCWYMmyW4V5JgkvRvsK75Y0z8ye0xvLWQeyV83sQ+7+e2ntMtYkz1p+2czOVciI7h+t4iIuqB5bSXrEQsX+tX9P7v6mJe5J40mEAclD8ZbPKWQs6yXJzN7i7v9x9xvLvrZi3/xGb9qnKFSG/YzCm68XPJwbuo+kP1uowveop3fMx4GSfhNd9axRKBAwUmHp8ZGSjjCzNQpB70wCyw3aXNIoSUeZ2fUKGeEjFDLPrdHFjyGS9jOz3dz94eyG+mZmdqpC5uQcSfdEQefPJH3czMYrXNC5uZL/rlCRjpS0p8KZufJQbK3fsqaVzN1fM7MfSfqRR2f+JWxwIbCMft4yC/UTknKEQtD0JYXXjrcpHFs10J0mqTnae2mSVioUP0vKsQrbLD7joQ7GBIW5BdXhq1n9YIJLDFju/pso67fMzD7o7h152P9lpedB1khqV1gaeZykEz0cO3JgtLRoVD/8Po9L+qyFg5iPVchY7aGwefy1aFyPKhw901LJmeBK4O6Pm9k0hT1I31U4WuQVSV8zs2fc/WEz+4ykYe7enuVYpVDVUSFD+YqZ1UnaX9LHJH1C4TDuXxZduLlPIcMObKz/Ris1CtnxAf8mOCrY8TWFpec10W2vS7rS3ZMMzhanuezW3QtZlW4zu13h9WTAzxHu/mdJe5jZFlE70fO1o4ByoaRGM/uxQqXVy5P8Geh/ZvYWSacqXKR+WNJ1/f2+tqY/fxhQadz9DoWJ+REz26qSA0sze7eZbVuWgXxaoZjGlyWd5u7tFo4b+UY/BZaSdL+knytUAt1CYTnWfgp7dH6nUCDgbALL3nP3/7p7Iau+s0JV2K0knRc9B1ZWSGC5raLnnpkNdfdOhT23cxSKSB3p4SDz/4muigN99TMzu1bSltGqk7skfS/jMWXtSwqvtXu7+zB3HybpAwqrGr6U4M85VaFQ3Beif39RyKrFYmb7mNlvzexXZranmS1VKGDzLwvHFQ1oZnZmFFi+rDCnP2Bm9Qn0O9rMvmZmjylsV/inQoHPA939yrj9I3PNCqvYHlaozn9Zfw+AarGAJAtHPLzi7r/NeizrYmYjJC2WdJi7/yG6bVC0afsQhWzRjpIWKkz+09z9tn4e4zB3X1nUPkDS1xUyWM8QVPZNlA0cI+mLCgHb+9x9eZZjKoiWQTcqlLD/h6SrJE1TOB5leLTX9hiFJbIfp/gK4rBwVtvasvruviDjIWXKzB5UqMLdUXb71pJaPYHjWizFqpNmtkjSdIVlsN+V1ODuf7RQIO4nSYw/z8zsIXffI1oVdKqkGQpLn2Md92PhiJZ7JJ1cuEhpZo+7+06xB43MmdnD7r5b9HGtpPviPmc2FstiAUnufrtUOUc4rMMOCtVXtzCzCyWd5+5rLBx6vI2knyqchVUr6fRoSWy//i6FwDLaizNJ4TzG6eyxjCfKBv5O4UDk91dCYGlmO0uqcfe/mtk8hQJYDZJOcfeLo4sht5vZEwpLc5oILBGXuy8wsz8peu9SfkFrABpcHlhKkrs/n9SeSE+36mStu7dKkpnNcvc/Rj/zsbDid8Ar3AkHS7rB3R+xZO6YoxSq4S80s19LurHoZyH/1h4T5O5dWfwtEVwCRSotsIwKVtQoLG/4ukKWaEoUWL5d0h8kfdXdH5T0YPH3ZvG7RG9oxiuczTijELQjnsI+22gPTqYXQaJM6l8ldZjZ+QpHiXxXIfswysw+7+7/Y2ZjFOaYDnd/MouxonqY2ecVMuL/UTjqyBS2BAzkbMt/+/i5jZVW1cniLR7lVVArai7OyGIza1VYlXRu9H4gdmE+d/9fSf8b7Vs+QmFVzDZmdo2kmwoBP3JrDzMr7M81SZtF7dTOHi7HsligQkUTycUK1RFvVVgSM1rSzxSWv24haS93vz6zQa5DFGDWRcUCKjUTjBjMbKLCnrczFc7g3ErSKoU3tHXR537o7v/JbJCoKmb2N0kfXFembqCKives68gOk/QWd08ke2nhnMs3cfffxey3MH5TKAS3uvApJTj+vLI3qq8/7qEC/DBJO7j7khR+1lYKW1iOdfePJN0/BhaCS6CCmdmnFc44vFPSbxQCypkKh9P/vLBMqayCLJC6aP/bFQqVgbdVqG77SYXM9TOS9nP3l7IbIapJtHzvKHdfvcEvRiIqoerkQGbhXMs/R5W4P6Wwt/1b7r4i46EBPSK4BCpQcbBoZscr7Ln4tUIp+PcrFO35q6SfspcNWYmKSX1T0j7uvjK6+j1Y0uaVsDcU1cPM9pT0A0l/UjjiSJLk7l/IbFBVzsx+qrB/6x6FPdUr3P3MbEc1cJjZEoWLd7tL+qGk7ytUX19nJhmoFOy5BCpMtJS028xGKWSAfiLpX5JOVlgv/2Mzu0phX+NPMxwqBjh3vz2qPPhHC2fFdmY9JlStayW1KWTQWKXRP95XVHXyOnFGbX/rcne3cB73Ve5+nZmdnPWggA0huAQqTDSZNEi6QNIdksZK+rjCXrYGMxvs7j8ws1Pd/eUsxwpE55duIukuMxvL8mykZLC7n5X1IAaYzKtODnAvm9m5kk6QtH+0B5P37ah4NVkPAIBkZu8wsx0teI9CZdhjJP1bIagc7O4/ldQi6SAzeweBJSqFu98saX8CS6SoxcxOMbPtzGxY4V/Wg6pye5jZv6N/L0vavfBxUTVKpOdYhSXgn3H3ZyV9SNKQbIcEbBh7LoGMRQdG/1KhUE+LpO0kHSrpLwrZy+Pc/e9mtp+7/5+Zbevu/8pswADQz8xsXXvLnYPfUc2ivcaNCpVc/yHpV+5+ZbajAnpGcAlkyMxGSrpN0jfd/broti0lLVIojLKru68yswmSpikcUv90RsMFAAApMrPRko6L/nUo1FaY6u4jMh0Y0Eus3QaydaCk30Qb9QtnWo2UNE/SkZKOMLM1ks6VNJPAEsBAFJ2fe5qkCdFNv5V0rbuvWe83Afn0mEKF3kPdvV2SzOxL2Q4J6D2CSyBbj0v6rJlNVthfsZlC6fE7FfZaHCfpUUnTo8Ip5iw3ADDwXKOwmuPbUfuE6LbPZjYiIB1HKZwZvDA63/VGSVRTQm6wLBbIkJltLukUSZ+W1C7pW5KWKmQvj5d0XuHQcAJLAAOVmT3k7nts6DagWpjZEElHKFxknijpBkk3uXtrpgMDNoBqsUCG3H21u18uaaK7H+3u97j7C5LeJumDkra0qP47gSWAAex1M3t3oWFmO0l6PcPxAKly91fcfb67HyZpB0kPSvpKxsMCNojMJVBBon1FkyRdqLAU9vaMhwQAmTOzj0j6gcJWAims7viMuy/MbFAAgDchcwlUiCiwHC/pLEkzCCwBDHRmtreZvd3dfyNpZ0m/ktQtqVXSQ5kODgDwJmQugQoSBZh17v4seywBDHRm9oCkj7r7yuhIphslTVGorL2Lux+d5fgAAKUILgEAQEUqLtpjZldLet7dZ0btP7v7+zMcHgCgDMtiAQBApRpkZoVj0z4iqa3ocxynBgAVhhdmAABQqX4i6Xdm1iHpVYXD5WVmoyS9lOXAAABvxrJYAABQscxsH0nbSWp191ei20ZLGuruD2Q6OABACYJLAAAAAEBs7LkEAAAAAMRGcAkAAAAAiI3gEgAAAAAQG8ElAAAAACA2gksAAAAAQGwElwAAAACA2AguAQAAAACxEVwCAAAAAGIjuAQAAAAAxEZwCQAAAACIjeASAAAAABAbwSUAAAAAIDaCSwAAAABAbASXAAAAAIDYCC4BAAAAALERXAIAAAAAYiO4BAAAAADERnAJAAAAAIiN4BIAAAAAEBvBJQAAAAAgNoJLAAAAAEBsBJcAAAAAgNgILgEAAAAAsRFcAgAAAABiI7gEAAAAAMRGcAkAAAAAiK026wFUiuHDh/vIkSOzHgYAIGWLFy/ucPetsx5HXjA/AsDAEXeOJLiMjBw5UosWLcp6GACAlJnZiqzHkCfMjwAwcMSdI1kWCwAAAACIjeASAAAAABAbwSUAAAAAIDaCSwAAAABAbASXAAAAAIDYCC4BAAAAALERXAIAAAAAYiO4BAAAAADERnAJAAAAAIiN4BIAAAAAEBvBJQAAAAAgNoJLAAAAAEBsBJcAAAAAgNgILgEAAAAAsRFcAgAAAABiI7gEAAAAAMRGcAkAAAAAiI3gEgAAAAAQW2rBpZldb2bPmdnSotuGmdkCM/tb9P9W0e1mZleYWbuZLTGzvYq+pyn6+r+ZWVPR7WPN7OHoe64wM+vpZ6A6dHZ2aurUqVq5cmUq/be3t+vII4/U448/nkr/eXb00Udr8uTJOuaYY1Lp/8wzz9TkyZN11llnJd532s+btPufPHny2n9p+PSnP63JkyfrpJNOSqX/NMd/7rnnavLkyZoxY0bifaeJOXLdOjo6NGXKFHV2dmY9lESdc845mjBhQu6epxuybNkyNTQ0qL29PeuhJO6ss87ShAkTNG3atKyHkqgJEyas/VdNqvW1I4/SzFz+UNJBZbedI+k37r6zpN9EbUlqkLRz9O8USddIYRKU9DVJH5A0XtLXiibCayR9ruj7DtrAz0AVmD9/vpYuXap58+al0v/cuXO1evVqXXTRRan0n2cvv/yyJOmll15Kpf/HHntMkvTII48k3nfaz5u0+0/bM888I0l66qmnMh7JxnvggQckSffff3/GI9loPxRz5Js0NzdryZIlam5uznooibr33nslSXfffXfGI0nW7Nmz9corr2jWrFlZDyVxixYtkiT98Y9/zHgk6I1qfe3Io9SCS3e/W1L5ZfwjJBUe9WZJHyu6/QYP/ihpSzPbTtJkSQvcfaW7vyBpgaSDos9t4e5/dHeXdENZX+v6Gci5zs5Otba2yt3V2tqaeJaovb1dK1askCStWLGC7GWRo48+uqSddPbyzDPPLGknmb1M+3mTdv/l2b6ks3+f/vSnS9pJZy/THP+5555b0s5TVog58s06OjrU0tIid1dLS0vVZCDOOac0fs/T87Qny5Yt0/LlyyVJy5cvr6rsZfkcVC3Zy/JsZbVkL6v1tSOv+nvP5bbu/kz08bOSto0+3l7SE0Vf92R0W0+3P7mO23v6Gci5+fPnq7u7W5LU3d2deJZo7ty5JW2yl28oZC0Lks5eFrKWBUlmL9N+3qTdf9oKWcuCPGUvC1nLghxmL8sN6DmyublZIRYOf0vVkoEoZC0LqiV7OXv27JJ2NWUvC1nLArKXla1aXzvyKrOCPtHVVM/yZ5jZKWa2yMwWPf/882kOBQloa2tTV1eXJKmrq0ttbW2J9l/IWq6vjXxK+3mTdv8YmLKeI7OYHxcsWKA1a9ZIktasWaPW1tZ++bnom0LWcn1toL/w2lFZ+ju4/Fe0XEfR/89Ftz8l6Z1FX7dDdFtPt++wjtt7+hlv4u7fdfdx7j5u66237vMvhf4xceJE1dbWSpJqa2s1ceLERPsfMWJEj23kU9rPm7T7x4BSMXNkFvPjpEmTNHjwYEnS4MGDVV9f3y8/F30zcuTIHttAf+G1o7L0d3B5i6RCNbsmSTcX3X5iVBFvH0kvRct27pRUb2ZbRUUK6iXdGX3u32a2T1QB78Syvtb1M5BzjY2NqqkJT9mamhodf/zxifZfvqeifJ/MQPbWt761pP22t70t0f7f+973lrR33XXXxPpO+3mTdv9p22677Ura22+//Xq+svLstddeJe299947o5EkZkDPkU1NTYqK2qqmpkZNTU0b+I582HfffUva1bLPrXzv6HnnnZfRSJI3bty4kvY+++yT0UjQG9X62pFXaR5F8hNJf5D0HjN70sxOlnSRpElm9jdJH43aknSHpMcltUv6nqT/kSR3XynpAkn3R/9mRbcp+prvR9/zd0kt0e3r+xnIubq6OtXX18vMVF9fr2HDhiXa/6hRo9ZmK0eMGKGddtop0f7z7Be/+EVJ+2c/+1mi/X/rW98qaX/jG99IrO+0nzdp93/nnXf22I7rhz/8YUn7+uuvT7T/NMd/4YUXlrTL94BVMubINxs+fLgaGhpkZmpoaFBdXV3WQ0pE+f79PD1PezJ69Oi12cqRI0dq1KhR2Q4oQeVzUHlNhrwq3+9bLft/q/W1I69q0+rY3Y9bz6c+so6vdUmnr6ef6yW96d2Ouy+SNGYdt3eu62egOjQ2NmrFihWpZYemTZums88+m6zlOrz1rW/Vyy+/nHjWsuC9732vHnvssUSzlgVpP2/S7j9t2223nZ555plcZS0L9tprLz3wwAO5y1oyR65bU1OTli9fXnWZh3333Vf33ntv1WQtC2bMmKEzzzyzqrKWBePGjdOiRYvIWuZEtb525JEVqisNdOPGjfPy6mAAgOpjZovdfdyGvxIS8yMADCRx58jMqsUCAAAAAKoHwSUAAAAAIDaCSwAAAABAbASXAAAAAIDYCC4BAAAAALERXAIAAAAAYiO4BAAAAADERnAJAAAAAIiN4BIAAAAAEBvBJQAAAAAgNoJLAAAAAEBsBJcAAAAAgNgILgEAAAAAsRFcAgAAAABiI7gEAAAAAMRGcAkAAAAAiI3gEgAAAAAQG8ElAAAAACA2gksAAAAAQGwElwAAAACA2AguAQAAAACxEVwCAAAAAGIjuAQAAAAAxEZwCQAAAACIjeASAAAAABAbwSUAAAAAIDaCSwAAAABAbASXAAAAAIDYCC4BAAAAALERXAIAAAAAYiO4BAAAAADERnAJAAAAAIiN4BIAAAAAEBvBJQAAAAAgNoJLAAAAAEBsBJcAAAAAgNgILgEAAAAAsRFcAgAAAABiI7gEAAAAAMRGcAkAAAAAiI3gEgAAAAAQG8ElAAAAACA2gksAAAAAQGwElwAAAACA2AguAQAAAACxEVwCAAAAAGIjuAQAAAAAxEZwCQAAAACIjeASAAAAABAbwSUAAAAAIDaCSwAAAABAbASXAAAAAIDYCC4BAAAAALERXAIAAAAAYiO4BAAAAADERnAJAAAAAIiN4BIAAAAAEBvBJQAAAAAgNoJLAAAAAEBsBJcAAAAAgNgILgEAAAAAsRFcAgAAAABiI7gEAAAAAMRGcAkAAAAAiI3gEgAAAAAQG8ElAAAAACA2gksAAAAAQGwElwAAAACA2AguAQAAAACxEVwCAAAAAGIjuAQAAAAAxEZwCQAAAACIjeASAAAAABAbwSUAAAAAIDaCSwAAAABAbASXAAAAAIDYCC4BAAAAALERXAIAAAAAYiO4BAAAAADERnAJAAAAAIiN4BIAAAAAEBvBJQAAAAAgNoJLAAAAAEBsBJcAAAAAgNgyCS7N7Etm9oiZLTWzn5jZW8xsRzP7k5m1m9lPzWyT6Gs3jdrt0edHFvVzbnT7X81sctHtB0W3tZvZORn8igAA9AlzJAAgr/o9uDSz7SV9QdI4dx8jaZCkT0q6WNI33X2UpBcknRx9y8mSXohu/2b0dTKz90Xft6ukgyR928wGmdkgSVdLapD0PknHRV8LAEBFY44EAORZVstiayVtZma1kjaX9IykiZJ+EX2+WdLHoo+PiNqKPv8RM7Po9hvd/TV3/4ekdknjo3/t7v64u/9X0o3R1wIAkAfMkQCAXOr34NLdn5J0qaR/KkyYL0laLOlFd++KvuxJSdtHH28v6Ynoe7uir68rvr3se9Z3+5uY2SlmtsjMFj3//PPxfzkAAGKolDmS+REA0BdZLIvdSuEq6Y6S3iFpiMKSnX7n7t9193HuPm7rrbfOYggAAKxVKXMk8yMAoC+yWBb7UUn/cPfn3X2NpF9J2k/SltESIEnaQdJT0cdPSXqnJEWff5ukzuLby75nfbcDAFDpmCMBALmVRXD5T0n7mNnm0b6Qj0j6i6SFko6OvqZJ0s3Rx7dEbUWfb3N3j27/ZFQpb0dJO0u6T9L9knaOKuttolDQ4JZ++L0AAIiLORIAkFu1G/6SZLn7n8zsF5IekNQl6UFJ35V0u6QbzWx2dNt10bdcJ+lHZtYuaaXCRCh3f8TMfqYw6XZJOt3dX5ckMztD0p0KVfaud/dH+uv3AwCgr5gjAQB5ZuECJ8aNG+eLFi3KehgAgJSZ2WJ3H5f1OPKC+REABo64c2RWR5EAAAAAAKoIwSUAAAAAIDaCSwAAAABAbASXAAAAAIDYCC4BAAAAALERXAIAAAAAYiO4BAAAAADERnAJAAAAAIiN4BIAAAAAEBvBJQAAAAAgNoJLAAAAAEBsBJcAAAAAgNgILgEAAAAAsRFcAgAAAABiI7gEAAAAAMRGcAkAAAAAiI3gEgAAAAAQG8ElAAAAACA2gksAAAAAQGwElwAAAACA2AguAQAAAACxEVwCAAAAAGIjuAQAAAAAxEZwCQAAAACIjeASAAAAABAbwSUAAAAAIDaCSwAAAABAbASXAAAAAIDYCC4BAAAAALERXAIAAAAAYiO4BAAAAADERnAJAAAAAIiN4BIAAAAAEBvBJQAAAAAgNoJLAAAAAEBsBJcAAAAAgNgILgEAAAAAsRFcAgAAAABiI7gEAAAAAMRGcAkAAAAAiI3gEgAAAAAQG8ElAAAAACA2gksAAAAAQGwElwAAAACA2AguAQAAAACxEVwCAAAAAGIjuAQAAAAAxEZwCQAAAACIjeASAAAAABAbwSUAAAAAIDaCSwAAAABAbASXAAAAAIDYCC4BAAAAALERXAIAAAAAYiO4BAAAAADERnAJAAAAAIiN4BIAAAAAEBvBJQAAAAAgNoJLAAAAAEBsBJcAAAAAgNgILgEAAAAAsRFcAgAAAABiI7gEAAAAAMRGcAkAAAAAiI3gEgAAAAAQG8ElAAAAACA2gksAAAAAQGwElwAAAACA2AguAQAAAACxEVwCAAAAAGIjuAQAAAAAxEZwCQAAAACIjeASAAAAABAbwSUAAAAAIDaCSwAAAABAbASXAAAAAIDYCC4BAAAAALERXAIAAAAAYiO4BAAAAADERnAJAAAAAIiN4BIAAAAAEBvBJQAAAAAgNoJLAAAAAEBsBJcAAAAAgNgILgEAAAAAsWUSXJrZlmb2CzN7zMweNbMPmtkwM1tgZn+L/t8q+lozsyvMrN3MlpjZXkX9NEVf/zczayq6fayZPRx9zxVmZln8ngAAbCzmSABAXmWVufyWpF+7+3sl7SHpUUnnSPqNu+8s6TdRW5IaJO0c/TtF0jWSZGbDJH1N0gckjZf0tcJkG33N54q+76B++J0AAEgCcyQAIJf6Pbg0s7dJmiDpOkly9/+6+4uSjpDUHH1Zs6SPRR8fIekGD/4oaUsz207SZEkL3H2lu78gaYGkg6LPbeHuf3R3l3RDUV8AAFQs5kgAQJ5lkbncUdLzkn5gZg+a2ffNbIikbd39mehrnpW0bfTx9pKeKPr+J6Pberr9yXXc/iZmdoqZLTKzRc8//3zMXwsAgNgqYo5kfgQA9EUWwWWtpL0kXePue0p6RW8s75EkRVdTPe2BuPt33X2cu4/beuut0/5xAABsSEXMkcyPAIC+yCK4fFLSk+7+p6j9C4WJ9F/Rch1F/z8Xff4pSe8s+v4dott6un2HddwOAEClY44EAORWvweX7v6spCfM7D3RTR+R9BdJt0gqVLNrknRz9PEtkk6MKuLtI+mlaGnQnZLqzWyrqEhBvaQ7o8/928z2iSrgnVjUFwAAFYs5EgCQZ7UZ/dwpkuaZ2SaSHpf0GYVA92dmdrKkFZKOib72DkkHS2qXtDr6Wrn7SjO7QNL90dfNcveV0cf/I+mHkjaT1BL9AwAgD5gjAQC5ZGHrBsaNG+eLFi3KehgAgJSZ2WJ3H5f1OPKC+REABo64c2RW51wCAAAAAKoIwSUAAAAAIDaCSwAAAABAbASXAAAAAIDYCC4BAAAAALERXAIAAAAAYiO4BAAAAADERnAJAAAAAIiN4BIAAAAAEBvBJQAAAAAgNoJLAAAAAEBsBJcAAAAAgNgILgEAAAAAsRFcAgAAAABiI7gEAAAAAMRW25svMrPRks6WNKL4e9x9YkrjAgCg4jE/AgDwhl4Fl5J+Luk7kr4n6fX0hgMAQK4wPwIAEOltcNnl7tekOhIAAPKH+REAgEhv91zeamb/Y2bbmdmwwr9URwYAQOVjfgQAINLbzGVT9P/ZRbe5pJ2SHQ4AALnC/AgAQKRXwaW775j2QAAAyBvmRwAA3tBjcGlmE929zcyOWtfn3f1X6QwLAIDKxfwIAMCbbShz+WFJbZIOW8fnXBKTJwBgIGJ+BACgTI/Bpbt/Lfr/M/0zHAAAKh/zIwAAb9bbgj4ys0Mk7SrpLYXb3H1WGoMCACAvmB8BAAh6dRSJmX1H0rGSpkgySZ+QNCLFcQEAUPGYHwEAeENvz7nc191PlPSCu58v6YOSRqc3LAAAcoH5EQCASG+Dy1ej/1eb2TskrZG0XTpDAgAgN5gfAQCI9HbP5W1mtqWkSyQ9oFAJ7/tpDQoAgJxgfgQAINKr4NLdL4g+/KWZ3SbpLe7+UnrDAgCg8jE/AgDwhl4Fl+s6JNrMXpL0sLs/l/ioAADIAeZHAADe0NtlsScrFClYGLUPkLRY0o5mNsvdf5TC2AAAqHTMjwAARHobXNZK2sXd/yVJZratpBskfUDS3ZKYPAEAAxHzIwAAkd5Wi31nYeKMPBfdtlKhMh4AAAMR8yMAAJHeZi5/GxUq+HnU/nh02xBJL6YxMAAAcoD5EQCASG+Dy9MlHSXpQ1H7Bkm/dHeXdGAaAwMAIAeYHwEAiPT2KBKX9MvoHwAAEPMjAADFervn8k3M7LtJDgQAgGrA/AgAGKj6HFxKujaxUQAAUD2YHwEAA1Kfg0t3X5zkQAAAqAbMjwCAgarHPZdmdqskX9/n3f3wxEcEAECFY34EAODNNlTQ59J+GQUAAPnC/AgAQJkeg0t3/11/DQQAgLxgfgQA4M16dRSJme0s6UJJ75P0lsLt7r5TSuMCAKDiMT8CAPCG3hb0+YGkayR1KRwKfYOkH6c1KAAAcoL5EQCASG+Dy83c/TeSzN1XuPtMSYekNywAAHKB+REAgEivlsVKes3MaiT9zczOkPSUpKHpDQsAgFxgfgQAINLbzOWZkjaX9AVJYyV9StKJaQ0KAICcYH4EACDS2+BypLuvcvcn3f0z7v5xSe9Kc2AAAOQA8yMAAJHeBpfn9vI2AAAGEuZHAAAiPe65NLMGSQdL2t7Mrij61BYKlfEAABhwmB8BAHizDRX0eVrSIkmHS1pcdPvLkr6U1qAAAKhwzI8AAJTpMbh094ckPWRm89ydK7EAAIj5EQCAddnQstifufsxkh40My//vLvvntrIAACoUMyPAAC82YaWxZ4Z/X9o2gMBACBHmB8BACjTY7VYd38m+n+FpNck7SFpd0mvRbcBADDgMD8CAPBmvTqKxMw+K+k+SUdJOlrSH83spDQHBgBApWN+BADgDRtaFltwtqQ93b1TksysTtK9kq5Pa2AAAOQA8yMAAJFeZS4ldSqUVy94OboNAICBjPkRAIBIbzOX7ZL+ZGY3S3JJR0haYmZnSZK7fyOl8QEAUMmYHwEAiPQ2uPx79K/g5uj/tyY7HAAAcoX5EQCASK+CS3c/P+2BAACQN8yPAAC8oVfBpZltLWmapF0lvaVwu7tPTGlcAABUPOZHAADe0NuCPvMkPSZpR0nnS1ou6f6UxgQAQF4wPwIAEOltcFnn7tdJWuPuv3P3kyRxVRYAMNAxPwIAEOltQZ810f/PmNkhkp6WNCydIQEAkBvMjwAARHobXM42s7dJ+rKkKyVtIemLaQ0KAICcYH4EACDS22Wxn5Bk7r7U3Q+UNEnSkekNCwCAXGB+BAAg0tvgcnd3f7HQcPeVkvZMZUQAAOQH8yMAAJHeBpc1ZrZVoWFmw9T7JbUAAFQr5kcAACK9nQAvk/QHM/t51P6EpK+nMyQAAHKD+REAgEivgkt3v8HMFumN8upHuftf0hsWAACVj/kRAIA39HrpTjRZMmECAFCE+REAgKC3ey4BAAAAAFgvgksAAAAAQGwElwAAAACA2AguAQAAAACxEVwCAAAAAGIjuOyDzs5OTZ06VStXrsx6KAAQG69pADAwLFu2TA0NDWpvb896KKhSBJd9MH/+fC1dulTz5s3LeigAEBuvaQAwMMyePVuvvPKKZs2alfVQUKUILjdSZ2enWltb5e5qbW3lSj+AXOM1DQAGhmXLlmn58uWSpOXLl5O9RCoILjfS/Pnz1d3dLUnq7u7mSj+AXOM1DQAGhtmzZ5e0yV4iDQSXG6mtrU1dXV2SpK6uLrW1tWU8IgDoO17TAGBgKGQt19cGkkBwuZEmTpyo2tpaSVJtba0mTpyY8YgAoO94TQOAgWHkyJE9toEkZBZcmtkgM3vQzG6L2jua2Z/MrN3Mfmpmm0S3bxq126PPjyzq49zo9r+a2eSi2w+Kbms3s3OSHHdjY6NqasLdVlNTo+OPPz7J7gGgX/GaVpnyOkcCqFwzZswoaZ933nkZjQTVLMvM5ZmSHi1qXyzpm+4+StILkk6Obj9Z0gvR7d+Mvk5m9j5Jn5S0q6SDJH07mowHSbpaUoOk90k6LvraRNTV1am+vl5mpvr6eg0bNiyprgGg3/GaVrFyOUcCqFyjR49em60cOXKkRo0ale2AUJUyCS7NbAdJh0j6ftQ2SRMl/SL6kmZJH4s+PiJqK/r8R6KvP0LSje7+mrv/Q1K7pPHRv3Z3f9zd/yvpxuhrE9PY2KgxY8ZwhR9AVeA1rbLkfY4EULlmzJihIUOGkLVEamoz+rmXS5om6a1Ru07Si+7eFbWflLR99PH2kp6QJHfvMrOXoq/fXtIfi/os/p4nym7/QJKDr6ur06WXXppklwCQGV7TKs7lyvEcCaByjR49Wi0tLVkPA1Ws3zOXZnaopOfcfXF//+x1jOUUM1tkZouef/75rIcDABjgKmWOZH4EAPRFFsti95N0uJktV1iOM1HStyRtaWaFTOoOkp6KPn5K0jslKfr82yR1Ft9e9j3ru/1N3P277j7O3cdtvfXW8X8zAADiqYg5kvkRANAX/R5cuvu57r6Du49UKDbQ5u7HS1oo6ejoy5ok3Rx9fEvUVvT5Nnf36PZPRpXydpS0s6T7JN0vaeeost4m0c+4pR9+NQAAYmGOBADkWVZ7LtflK5JuNLPZkh6UdF10+3WSfmRm7ZJWKkyEcvdHzOxnkv4iqUvS6e7+uiSZ2RmS7pQ0SNL17v5Iv/4mAAAkizkSAFDxLFzgxLhx43zRokVZDwMAkDIzW+zu47IeR14wPwLAwBF3jszynEsAAAAAQJUguAQAAAAAxEZwCQAAAACIjeASAAAAABAbwSUAAAAAIDaCSwAAAABAbASXAAAAAIDYCC4BAAAAALERXAIAAAAAYiO4BAAAAADERnAJAAAAAIiN4BIAAAAAEBvBJQAAAAAgNoJLAAAAAEBsBJcAAAAAgNgILgEAAAAAsRFcAgAAAABiI7gEAAAAAMRGcAkU6ezs1NSpU7Vy5cqsh1JxFi9erIaGBj344IOp9M99D6BadXR0aMqUKers7Mx6KOilu+66SxMmTNDChQuzHgqQKwSXQJH58+dr6dKlmjdvXtZDqThz5sxRd3e3Zs+enUr/3PcAqlVzc7OWLFmi5ubmrIeCXpozZ44k6YILLsh4JEC+EFwCkc7OTrW2tsrd1draSgatyOLFi7Vq1SpJ0qpVqxLPXnLfA6hWHR0damlpkburpaWF7GUO3HXXXerq6pIkdXV1kb0ENgLBJRCZP3++uru7JUnd3d1k0IoUruAWJJ295L4HUK2am5vl7pLC6xvZy8pXPueRvQR6j+ASiLS1tZVcqWxra8t4RJWjkLVcXzsu7nsA1WrBggVas2aNJGnNmjVqbW3NeETYkMJ8tL42gPUjuAQiEydOVG1trSSptrZWEydOzHhElWPo0KE9tuPivgdQrSZNmqTBgwdLkgYPHqz6+vqMR4QNKcxH62sDWD+CSyDS2NiomprwJ1FTU6Pjjz8+4xFVjunTp5e0Z8yYkWj/3PcAqlVTU5PMTFJ4fWtqasp4RNiQ8jnvq1/9akYjAfKH4BKI1NXVqb6+Xmam+vp6DRs2LOshVYyxY8euzVYOHTpUe+65Z6L9c98DqFbDhw9XQ0ODzEwNDQ2qq6vLekjYgI9+9KMlq2kOPPDAjEcE5AfBJVCksbFRY8aMIXO2DtOnT1dNTU3iWcsC7nsA1aqpqUm77747WcscKWQvyVoCG8cKFcwGunHjxvmiRYuyHgYAIGVmttjdx2U9jrxgfgSAgSPuHEnmEgAAAAAQG8ElAAAAACA2gksAAAAAQGwElwAAAACA2AguAQAAAACxEVwCAAAAAGIjuAQAAAAAxEZwCQAAAACIjeASAAAAABAbwSUAAAAAIDaCSwAAAABAbASXAAAAAIDYCC4BAAAAALERXAIAAAAAYiO4BAAAAADERnAJAAAAAIiN4BIAAAAAEBvBJQAAAAAgNoJLAAAAAEBsBJcAAAAAgNgILgH0yuLFi9XQ0KAHH3wwlf7b29t15JFH6vHHH0+8787OTk2dOlUrV65MvO/+cO6552ry5MmaMWNGKv1fdtllmjx5si6//PJU+r/xxhs1efJk/fznP0+877w/tijV0dGhKVOmqLOzM+uhJOqMM87QhAkT9MUvfjHroSTqvvvu0wEHHKDFixdnPZTEnXTSSZowYYJOOeWUrIeCXli2bJkaGhrU3t6e9VAGPIJLAL0yZ84cdXd3a/bs2an0P3fuXK1evVoXXXRR4n3Pnz9fS5cu1bx58xLvuz888MADkqT7778/lf5bW1slSS0tLan0/4Mf/ECS9P3vfz/xvvP+2KJUc3OzlixZoubm5qyHkqglS5ZIeuNvuVrMnDlT3d3d+upXv5r1UBJXCFIee+yxjEeC3pg9e7ZeeeUVzZo1K+uhDHgElwA2aPHixVq1apUkadWqVYlnL9vb27VixQpJ0ooVKxLNXnZ2dqq1tVXurtbW1txluM4999ySdtLZy8suu6yknXT28sYbbyxpJ5m9zPtji1IdHR1qaWmRu6ulpaVqspdnnHFGSbtaspf33XdfybxQTdnLk046qaRN9rKyLVu2TMuXL5ckLV++nOxlxgguAWzQnDlzStpJZy/nzp1b0k4yezl//nx1d3dLkrq7u3OX4SrPdCSdvSxkLQuSzl4WspYFSWYv8/7YolRzc7PcXVJ4PKsle1nIWhZUS/Zy5syZJe1qyl6WBydkLytb+XsSspfZIrgEsEGFq9Pra8dVyFqurx1HW1uburq6JEldXV1qa2tLrG9ki8e2uixYsEBr1qyRJK1Zs+ZNFz5QWdKeF4DeKmQt19dG/yK4BLBBQ4cO7bEd14gRI3psxzFx4kTV1tZKkmprazVx4sTE+ka2eGyry6RJkzR48GBJ0uDBg1VfX5/xiNCTtOcFoLdGjhzZYxv9i+ASwAZNnz69pJ30vr9p06aVtM8555zE+m5sbFRNTXipq6mp0fHHH59Y3/1hr732KmnvvffeifZf/ga+oaEh0f4/85nPlLQ/+9nPJtZ33h9blGpqapKZSQqPZ1NTU8YjSsbuu+9e0i7/m86r8mWxF1xwQTYDScGoUaNK2u9973szGgl6o/w9yXnnnZfRSCARXALohbFjx669Kj106FDtueeeifY/atSotdnKESNGaKeddkqs77q6OtXX18vMVF9fr2HDhiXWd3+48MILS9pJ73f98pe/XNJOutjIJz/5yZL2Jz7xicT6zvtji1LDhw9XQ0ODzEwNDQ2qq6vLekiJuOqqq0raaR3509/Gjx9fMi+MHTs24xEl5/rrry9pf/e7381oJOiN0aNHr81Wjhw58k0XB9C/CC4B9Mr06dNVU1OT2lmL06ZN0+abb55o1rKgsbFRY8aMyW1mq5DpSDprWVDIXiadtSwoZC+TzFoW5P2xRammpibtvvvuVZO1LChkL6sla1kwc+ZM1dTUVFXWsqAQoJC1zIcZM2ZoyJAhZC0rgBUqsw1048aN80WLFmU9DABAysxssbuPy3ocecH8CAADR9w5kswlAAAAACA2gksAAAAAQGwElwAqQmdnp6ZOnaqVK1dmPZSNlvbY0+6/vb1dRx55pB5//PFU+l+8eLEaGhr04IMP5qpv9L+Ojg5NmTJFnZ2dWQ8lUZdffrkmTJjwpuI+eVetjxfyh+di5SC4BFAR5s+fr6VLl2revHmJ95128JTm2KVQufDhhx/Wddddl0r/c+fO1erVq3XRRRel0v/s2bPV3d2tWbNmJd73nDlz1N3dnXgVXWTjkksu0UMPPaRLLrkk66Ek6le/+pUk6Wc/+1nGI0lWc3OzlixZoubm5qyHkjiClXyp5udi3hBcAshcZ2enWltb5e5qbW1NPEOXZvCU9tg7OzvV1tYmSWpra0u8//b2dq1YsUKStGLFisQD8MWLF2v16tWSpNWrVyeaYVy8eLFWrVolSVq1ahXZy5zr6OjQH/7wB0nSvffeWzVv6suPHqmW7GVHR4daWlrk7mppaamax6uAYCU/qv25mDcElwAyN3/+fHV3d0uSuru7E80Aph08pTl2KWQti/tPOns5d+7cknbSAXh5RjHJ7OWcOXN6/FnIl/JsZbVkLwtZy4JqyV42NzercOJAd3d3VQVhBCv5Us3PxTwiuASQuba2NnV1dUmSurq61mbqkpB28JTm2CVp4cKFPbbjKgTe62vHVcharq8dRyFrub428qWQtSy49957MxoJemPBggVas2aNJGnNmjVqbW3NeETJIVjJl2p+LuYRwSWAzE2cOFG1tbWSpNraWk2cODGxvtMOntIcuySZWY/tuEaMGNFju5INHTq0xzaA9EyaNEmDBw+WJA0ePFj19fUZjyg5BCv5Us3PxTwiuASQucbGRtXUhJejmpoaHX/88Yn1nXbwlObYJemAAw4oaR944IGJ9j9t2rSS9jnnnJNo/x/4wAdK2vvss09ifU+fPr2kPWPGjMT6Rv8bMmRIj+28Ouqoo0raxxxzTEYjSVZTU9Pai101NTVqamrKeETJIVjJl2p+LuYRwSWAzNXV1am+vl5mpvr6eg0bNiyxvtMOntIcuySddNJJJcHrSSedlGj/o0aNWhtwjxgxQjvttFOi/Z955pk9tuMYO3bs2mzl0KFDteeeeybWN/rf+eefX9Kulj20X/ziF0vaZ5xxRjYDSdjw4cPV0NAgM1NDQ4Pq6uqyHlJiCFbypZqfi3lEcAmgIjQ2NmrMmDGJZ/7SDp6k9MYuheC1sNT2Ix/5SOLBqxQC8M033zzxwFsK4y9kL/fZZ5/Exz99+nTV1NSQtawC48ePX5utHDJkiMaOHZvxiJJTyF5WS9ayoKmpSbvvvnvVBV8EK/lTrc/FPLLChuWBbty4cb5o0aKshwEgBe3t7Tr77LN12WWXpRJcpq2zs1MXXnihpk+fnkpwmbZKG7+ZLXb3cVmPIy/6c3687777NG3aNF122WVVFVwifzo6OnT++edr5syZBJcYUOLOkQSXEYJLABgYCC43DvMjAAwccedIlsUCAAAAAGIjuAQAAAAAxEZwCQAAAACIjeASAAAAABAbwSWAXuns7NTUqVO1cuXKrIcCAAD6oKOjQ1OmTFFnZ2fWQ0GVIrgE0Cvz58/X0qVLNW/evKyHAgAA+qC5uVlLlixRc3Nz1kNBlSK4BLBBnZ2dam1tlburtbWV7CUAADnT0dGhlpYWubtaWlrIXiIVBJcANmj+/Pnq7u6WJHV3d5O9BAAgZ5qbm1U43767u5vsJVJBcAlgg9ra2tTV1SVJ6urqUltbW8YjAgAAG2PBggVas2aNJGnNmjVqbW3NeESoRgSXADZo4sSJqq2tlSTV1tZq4sSJGY8IAABsjEmTJmnw4MGSpMGDB6u+vj7jEaEaEVwC2KDGxkbV1ISXi5qaGh1//PEZjwgAAGyMpqYmmZmkMJc3NTVlPCJUI4JLABtUV1en+vp6mZnq6+s1bNiwrIcEAAA2wvDhw9XQ0CAzU0NDg+rq6rIeEqpQbdYDAJAPjY2NWrFiBVlLAAByqqmpScuXLydridSQuQSKdHZ2aurUqRy1sQ7Lly/XI488ohUrVqTS/9VXX63JkyfrO9/5Tir9pynt503a983ChQs1efJk3X333an0f+utt2ry5Mm64447Eu/7+uuv1+TJk6l6CAC9cNRRR+mhhx7SkUcemfVQUKX6Pbg0s3ea2UIz+4uZPWJmZ0a3DzOzBWb2t+j/raLbzcyuMLN2M1tiZnsV9dUUff3fzKyp6PaxZvZw9D1XWGGBObAB8+fP19KlSzlqYx3mzJmj7u5uzZ49O5X+b7nlFknSTTfdlEr/aUr7eZP2fXPppZdKki6++OJU+r/66qslSVdccUXiff/0pz+VFB6DasAcCQDIsywyl12Svuzu75O0j6TTzex9ks6R9Bt331nSb6K2JDVI2jn6d4qka6Qw0Ur6mqQPSBov6WuFyTb6ms8Vfd9B/fB7Iec6OzvV2toqd1drayvZyyKLFy/WqlWrJEmrVq3Sgw8+mGj/heCjIE/Zy7SfN2nfNwsXLiw5Zibp7OWtt9669lw1d080e3n99deXtKske8kcCSAVEyZM6LENJKHfg0t3f8bdH4g+flnSo5K2l3SEpMI7g2ZJH4s+PkLSDR78UdKWZradpMmSFrj7Snd/QdICSQdFn9vC3f/o4R3NDUV9Aes1f/58dXd3SwqHC5O9fMOcOXNK2klnLwuZuYI8ZS/Tft6kfd8UspYFSWcvy4PjJLOXhaxlQTVkL5kjAQB5lumeSzMbKWlPSX+StK27PxN96llJ20Yfby/piaJvezK6rafbn1zH7UCP2traSjI4bW1tGY+ochSylutrD2R5f94Uxr6+dlyFrOX62lg/5kgAQN5kFlya2VBJv5T0RXf/d/Hnoqupqb8DMbNTzGyRmS16/vnn0/5xqHATJ05UbW0ooFxbW6uJEydmPKLKMXTo0B7bA1nenzeFsa+vHVf5dj629/VO1nMk8yMAoC8yCS7NbLDCpDnP3X8V3fyvaLmOov+fi25/StI7i759h+i2nm7fYR23v4m7f9fdx7n7uK233jreL4Xca2xsVE1N+JOoqanhyI0i06dPL2nPmDEj0f4PP/zwknaeqtil/bxJ+76ZOnVqSfsrX/lKov2ffvrpJe0vfOELifV97LHHlrQbGxsT6ztLlTBHMj8CAPoii2qxJuk6SY+6+zeKPnWLpEI1uyZJNxfdfmJUEW8fSS9FS4PulFRvZltFRQrqJd0Zfe7fZrZP9LNOLOoLWK+6ujrV19fLzFRfX69hw4ZlPaSKMXbs2LXZyqFDh2rPPfdMtP/yAOTUU09NtP80pf28Sfu+OfDAA0syr0kXeDjssMPWZivNTAcffHBifZ900kkl7Wo4t405EkBaygu2pXX8FAa2LDKX+0k6QdJEM/tz9O9gSRdJmmRmf5P00agtSXdIelxSu6TvSfofSXL3lZIukHR/9G9WdJuir/l+9D1/l9TSH78Y8q+xsVFjxozJZdYy7bMWp0+frpqamsSzlgWFDF2espYFaT9v0r5vCgFreSCblEK/SWYtCwrZy2rJWmqAz5HLli1TQ0OD2tvbsx4KAKAPjOIKwbhx43zRokVZDwPosyuvvFK33367DjnkEE2ZMiXr4SBHBtpzx8wWu/u4rMeRF/05P5544olavny5Ro4cqRtuuKFffiYA4A1x58hMq8UCSAZndKKveO6gUixbtkzLly+XJC1fvpzsJQDkEMElUAU4oxN9xXMHlaL8/NxZs2ZlNBIAQF8RXAJVIO9nLSI7PHdQKQpZy/W1AQCVj+ASqAJ5P2sR2eG5g0oxcuTIHtsAgMpHcAlUAc7oRF/x3EGlKK9Efd5552U0EgBAXxFcAlWAMzrRVzx3UClGjx69Nls5cuRIjRo1KtsBAQA2GsElUCXyfEYnssVzB5VixowZGjJkCFlLAMgpzrmMcM4lAAwMnHO5cZgfAWDg4JxLAAAAAEDmCC4BAAAAALERXALolYULF2ry5Mm6++67sx7KgNPZ2ampU6dq5cqVuewf6K277rpLEyZM0MKFC7MeCga4ZcuWqaGhQe3t7VkPBcgVgksAvXLppZdKki6++OKMRzLwzJ8/X0uXLtW8efNy2T/QW3PmzJEkXXDBBRmPBAPd7Nmz9corr2jWrFlZDwXIFYJLABu0cOFCdXV1SZK6urrIXvajzs5Otba2yt3V2tqaeHYx7f6B3rrrrrtKXmfIXiIry5Yt0/LlyyVJy5cvJ3sJbASCSwAbVMhaFpC97D/z589Xd3e3JKm7uzvx7GLa/QO9VchaFpC9RFZmz55d0iZ7CfQewSVQJdrb23XkkUfq8ccfT7zvQjZhfe0kTJ48ee2/pJ177rmaPHmyZsyYkXjfUnhTPHny5FSC7ra2tpJsTltbW676l9J9bBsbGzV58mR96lOfSrxv9K/+eJ3JCntJ86WQtVxfO88mTJiw9h+QBoJLoErMnTtXq1ev1kUXXZR437W1tT22K90DDzwgSbr//vtT6f93v/udJKUSmE2cOLHHdqX3n7bOzk5J0vPPP5/xSBBX3l9nesJe0nwZOXJkj20A60dwCVSB9vZ2rVixQpK0YsWKxLOXaWcUyjNaSWa4zj333JJ20tnL8qV8SWcvb7vtth7bld5/mo9tY2NjSZvsZb5NmTKlpP3FL34xm4EkjL2k+VM+T5x33nkZjSRZ5dlKspdIA8ElUCTNIxnS7Hvu3Lkl7TSyl3lVyFoWJJ29LGQtC9LIXmLdClnLArKX+VZ+UaxaiqhU817Sjo4OTZky5U1/i3k3evRoDR48WJI0ePBgjRo1KuMRAflBcAkUSfNIhuuvv14PP/ywrrvuusT7LmQt19cGgEq3YMGCknZra2tGI0lWNe8lveSSS/TQQw/pkksuyXooiVuzZk3J/6hs1XqhI48ILoFImkcydHZ2rs1otbW1JZ69HDFiRI9tAKh0kyZNkplJksxM9fX1GY8IPeno6NAf/vAHSdK9995bVW/qzzjjjJJ2tSzRrmbNzc1asmSJmpubsx7KgEdwCUTSPJLh+uuvL+k76ezltGnTStrnnHNOov3nWU1N6cvcoEGDEu1/s80267GN9LztbW8raW+11VYZjQRJOOyww+TukiR31+GHH57xiNCT8mxlNWUvlyxZUtIu316BytLR0aGWlha5u1paWqrqQkceEVwCkTSPZCgv4JB0QYdRo0atzVaOGDFCO+20U6L951khqC94/fXXE+3/1Vdf7bGN9Gy55ZYl7S222CKbgSARt956a0nm8pZbbsl4ROhJIWtZcO+992Y0EvTW3Xff3WM7r5qbm9fO9a+//jrZy4wRXAKRiRMnri19X1tbm+iRDIU3TOtrJ2HatGnafPPNyVqWGTp0aI/tuPrjscW6sde4uixYsKAkc1ktey4BpGvBggUlyQFeO7JFcAlEGhsb1y6hrKmp0fHHH59Y32PHji1pjxs3LrG+C0aNGqWbbrqJrGWZ8r0zZ555ZqL9f+hDHypp77///on2j/Vjr3F1mTRpUkmFTvZcVrYhQ4b02EZluvvuu9f+qxbl8y5HrGSL4BKI1NXVqb6+fm0hiWHDhiXW95NPPtlju9KV71ssb1dy/0uXLi1pP/TQQ4n1LUmnnXZayVK+0047LdH+05b2wfXvec97Stq77LJLYn2z17i6NDU1rf1bqqmpUVNTU8YjQk/OP//8kvbs2bMzGgmASkJwCRRpbGzUmDFjEs1aStJTTz1V0s5bcFm+b7G8Xcn9l++dTfocyrq6urXZy/333z/RixL9Ie1jEp544omSdpJLV9lrXF2GDx+uhoYGmZkaGhpUV1eX9ZDQg/Hjx6/NVg4ZMuRNK3SA/nLPPfeUtKspK5tHBJdAkbq6Ol166aWJBwh5X76XdnYrzf7T3EtbcNppp2m33XbLXdZSSn9P6sSJE0uWmyd9/7PXuLo0NTVp9913r6qsZdqvn1k6//zzVVNTQ9YSmZo0aVLJPM+S+mwRXAL9IO/L96ZOnVrS/spXvpKb/tPcS1uQ1kUJSdprr71K2nvvvXei/U+fPr2kPWPGjET7b2xsLJn0k77/2WtcXYYPH64rr7yyqrKW5X9jX/3qVzMaSfLGjx+v3/72t1WXteSYo3xpampaO88PGjSoqi5O5RHBJdAP8r5878ADDywJEJLeLJ9m/2nupe0PF154YUk76QzB2LFj12Yrhw4dqj333DPR/vN+/wNxffSjHy15fTvwwAMzHhE25NZbby1p33zzzRmNBL3BkvrKQnAJ9JO8L98rZBeTzlr2R/9p7aXtL4XsZdJZy4Lp06erpqYm8axlQd7vfyCuQvaymrKW1a6QvSRrmQ/VuKQ+r6xwptRAN27cOF+0aFHWwwAGrM7OTl144YWaPn062a0y3DfJMrPF7p78eUBVivkxvo6ODp1//vmaOXMmWZWc4DHDQBV3jiRzCaAizJ8/X0uXLtW8efOyHkrF4b4B8q25uVlLlixRc3Nz1kNBL/GYAX1DcAkgc52dnWptbZW7q7W1VStXrsx6SBWD+wbIt46ODrW0tMjd1dLSos7OzqyHhA3gMQP6juASQObmz5+/9mzL7u5uMnRFuG+AfGtublZhC1J3dzeZsBzgMQP6juASQOba2trU1dUlSerq6lJbW1vGI6oc3DdAvi1YsEBr1qyRJK1Zs0atra0ZjwgbwmMG9B3BJRLV2dmpqVOnsnSvCl199dWaPHmyvvOd7yTe98SJE3tsx9Xe3q4jjzxSjz/+eKL9FixevFgNDQ168MEHE+877ftGki677DJNnjxZl19+eeJ9S+neP2n2jf5333336YADDtDixYuzHkpiJk2aVNKupgPely1bpoaGBrW3t2c9lERV82N27LHHasKECWpsbMx6KInq6OjQlClTWMJcAQgukSgKj1SvW265RZJ00003Jd53+SSX9JEVc+fO1erVq3XRRRcl2m/BnDlz1N3dnfgZlFL6942ktVflW1paEu9bSvf+SbNv9L+ZM2equ7u7qo7sKD8aoZqOSpg9e7ZeeeUVzZo1K+uhJKqaH7NnnnlGkvTkk09mPJJkUYCpchBcIjEUHqleV199dUk76ezlD3/4w5L2DTfckFjf7e3tWrFihSRpxYoViWcvFy9erFWrVkmSVq1alXgG7fOf/3xJ+9RTT020/8suu6yknXT2Ms37J+37Hv3rvvvuK3k8qyV7OXPmzJL2BRdckM1AErZs2TItX75ckrR8+fKqyl6ecMIJJe0TTzwxo5Ek69hjjy1pV0v2kgJMlYXgEomh8Ej1KmQtC5LOXpbvZ0kygzZ37tySdtLZyzlz5pS0k86gvfzyyyXtl156KdH+07zvpXTvn7Tve/Sv8iCsWrKXS5YsKWk/8MADGY0kWeV/b9WUvXzllVdK2uWvw3lVyFoWVEv2kgJMlYXgEomh8AgqUSFrub52XIVMy/raA12a9w/3fXXh8cyXQtZyfW2gv1CAqbIQXCIxEydOVG1trSSptrY2lcIjaUuzIFHaxY4oprRuI0aM6LEd19ChQ3tsD3Rp3j/c99WFxzNfRo4c2WMb6C+TJk3S4MGDJUmDBw+uqgJMeURwicQ0NjaqpiY8pWpqalIpPJK2NAsSpV3sKM3+y1+oGxoactP/tGnTStrnnHNOYn1L0vTp00vaM2bMSLT/IUOGlLTf+ta3Jtr/PvvsU9Leb7/9Eu0/zfsn7fse/ata9yaWB12jRo3KZiAJK/97O++88zIaSfI222yzknb563BebbfddiXtHXbYIaORJKupqUlmJim8/6ymAkx5RHCJxNTV1am+vl5mpvr6eg0bNizrIW2UNAsSpV3sKO3+n3766ZL2E088kWj/o0eP7rEdx1ZbbbV20jEzbbnllon1Lb35jWPSmdEdd9wx1f7Ll7IlXfBo7NixazNQQ4cO1Z577pmLvtH/xo8fX/J4jh07NuMRJaOjo6Ok/eyzz2Y0kmSNHj167evfyJEjqyZolt58wbP8aJK8Wr16dUm7fG9pXg0fPlwNDQ0yMzU0NKiuri7rIQ1oBJdIVGNjo8aMGZPbrGVaBYnSLnaUdv9Lly7tsR1XeTXaK664IrG+58+fX5JRT+O+HzRokCRp0KBBubvvy9/olhd8SML06dNVU1OTSmYxzb7R/2bOnKmampqqyVpK1b2XdMaMGRoyZEhVZS2lsIevWLXs4SsvCPfCCy9kNJLkNTU1affddydrWQEILpGouro6XXrppbnLWkrpFiRKu9hR3ospFaq8ra8dR1tbm15//XVJ0uuvv57KfZ9m/9Vg7NixamlpSSWzOHLkSO26666JZ3SBpFTzXtIXX3xRr776auJVrLNWnqlkDx/QewSXQCTNgkRpFztKu//CstL1tSu5//L7Io37Ps3+077vy/fglLcrXdp7mdG/Zs6cqe7u7qo5hkSq3r2kUnU+XpLelP0iG1b5mpubtWTJEo4hqQAEl0AkzYJEaRc7Srv/8qxQ+T7AuMaMGVPS3mOPPXLRtyRtvfXWJe23v/3tifa/+eabl7STznqU72/dZZddEu0/TWnvNUb/uu+++9YuGV21apUWL16c8YiSUX7Wbnk7r6r18ZKkY489tsd2Xr3tbW8raW+11VYZjSRZHR0damlpkburpaVFnZ2dWQ9pQCO4BCJpFiRKu9hR2v2nXfTl4YcfLmn/+c9/Tqzvq666qqT9rW99K7G+JemHP/xhSfu6665LtP+0D/P+3e9+V9LO07Le+fPnlyxJJnuZb+UZvmrJhj333HMl7TT2NWehWh8vSWvPTCz473//m9FIknXrrbeWtG+++eaMRpKs5ubmtdtpuru7yV5mjOCywuT9rML29nYdeeSRiQcf/aWhoUGbbbaZDjnkkMT73nrrreXuiWe2CsaMGSN3Tzwzl3dpF9NIc79otbjssss0efJkXX755Yn2y37X6lLNhW+qEY8XKsWCBQvWXhBYs2ZN1RRgyiuCywqT9/1Dc+fO1erVq3XRRRdlPZQ+aWlp0auvvqrbb7898b5/8IMfSJK+//3vJ9639EaGLunMXN6lXUwj7T2R1aAw0be0tCTa77777ttjG/lSzYVvqhGPFyrFpEmTNHjwYEnS4MGDKcCUMYLLCtIf+4cWL16shoYGPfjgg4n33d7erhUrVkiSVqxYkbvsZZr3f/lSlDvuuCOxvqXwuBbvfUnj8c2r4cOHl7S32WabRPtPez9q3l122WUl7SSzlw899FBJe8mSJYn1jf5XrYVvCkcVra+dV9X6eFWzCRMm9NjOq6amprUXdmtqaqquAFNHR4emTJmSm72kBJcVJO2zCiVpzpw56u7u1uzZsxPvu7xIQd6yl2ne/2nv+5szZ05JO43HN6/S3i+adv95V748Kcns5fPPP1/SLt/bhnwZP3782uzX0KFDNXbs2IxHlIzC0u31tfNqp512KmmPHDkym4FgwBs+fLgaGhpkZmpoaFBdXV3WQ0pU3irhElxWkLTPKkw7u1XIWq6vXenyfFYke18AVIPjjjtOknTCCSdkPBJsSHNzc0mV8ry88e0Nlvzmz/777y8z04c//OGsh5KoPFbCJbisIGmfVZh2divvL8Zp3/9pKox7fW0AyIOf/OQnkqQf/ehHGY8EG7JgwYKS1T7VVESlcKF5fW1Unquuukrd3d1VV3cij5VwCS4rSNpnFaad3cr7i3Ha93+aqnVPD4CBo5rPTaxG+++/f0m7WvbvSdKmm25a0t5ss80yGgl6Y9myZWu3qCxfvlzt7e3ZDihBeayES3BZQdI+qzDtzOJHP/rRHtuVLs37P+3M4qRJk3psIz1kjXuW5hvQvK+WQKlqPjexGr322ms9tvPspZdeKmm/8MILGY0EvVG+Em/WrFkZjSR5eayES3BZYRobGzVmzJhUsmZnnHFGSfvMM89MtP/yYwA+9KEPJdp/f0jr/k87q9vY2FiypDdPWde8O/XUU0vap59+ekYjqUyf/OQnS9qFPXVJmD59ekl7xowZifWN/sfe8Xy5++67S9q/+93vMhoJBrrywnrl7TzLYyVcgssKU1dXp0svvTTxrKUkLV26tKRdXsY/rmuvvbakfc011yTaf39I6/5P+yzEuro6HXTQQTIzHXTQQak8f7Bu5ZPY3//+92wGUqFaWlrWPt/NLNEzZMeOHVtSXXTPPfdMrG8APSvsA1tfG+gv5ZWKq6lycR4r4RJcDiDl1U+Troaa92qxaeqPSTjNrHeebbfddj2240r77yrv2tra1j7f3T3x+2f69Omqqakhawn0s0KNgvW1gf5S/vp/3nnnZTSSdDQ1NWn33XfPRdZSIrgcUNKuhsr+p/UbMWJEj+0kpJn1zrO0J53yv6M8VRmW0t8zmvbrztixY9XS0kLWsgqwfzlfqrmgD0Xy8mX06NFrs5UjR47UqFGjsh1QwoYPH64rr7wyF1lLieByQGlsbCxZnpa3fYWS1N7eriOPPDK1g+o7Ozs1depUrVy5MtF+p02bVtI+55xzEu0/beUBa9IvcO95z3tK2rvssktifY8aNapkM3z5wd9xNTQ0lLQPOeSQRPsv37xf/vPiSnvPaNpVmNP6m0X/q9Y39OWvZ7vuumtGI0lWeUXV8naevf/97y9p77XXXtkMJGHbbLNNSTvplTxZmjFjhoYMGVJ1Wcs8IrgcQOrq6vSOd7xDkvSOd7wj8QxXf1SLnTt3rlavXq2LLroo8b6lsE/04Ycf1re//e1E+y2/ipZ0gJO28jfuSR/iW142fNmyZYn13dnZWVLGO+kg5Kabbipp//KXv0y0/wcffLCknfTxDOV7rx944IFE+0+7Cvb111+vhx9+WNddd12i/aL/HXTQQSXtpC+kZOWxxx4raf/lL3/JaCTJquaCPuWPUXnNirx6/vnnS9rPPvtsRiNJ3ujRo9XS0lJ1Wcs8IrgcQDo7O/X0009Lkp555pnE32Q3NjaWtJPOULS3t6/dx7lixYrEs5ednZ265557JEn33HNPovfPwoULS9rlk3IS0s7qpun111/vsR3HnDlzStpf//rXE+tbku66664e23GVvxl47rnnEu2/8JxfXzsJae0H7uzsXHt/33XXXWQvc658P1Fe9hdtSLUWvtl22217bOdZtf5u1fpclMJF6YaGhqo64zKvCC77IK/LsObPn7/2haS7u1vz5s1LtP/yc6BefPHFRPufO3duSTvp7GV5ddsks5eXXnppSfviiy9OrO+COXPmaPXq1YkHT3lXfsW5Wq5AV6prrrlGZ599dsm/KVOm6Omnn9aFF1649rYkqklff/31JW2yl0D/eeqpp3ps51k1H21RrWbPnq1XXnmlqs64zCuCyz6YP3++li5dmnhwlra2tra1+yC7uroSr9qYdvCXdjXaNDM4ae9HbW9vXzuxP/nkk7nMXqJ6/ec//9F//vOfxPtNO2uM/nXFFVf02EZlKWw3WF8b6C/Lli1bewFg+fLlZC8zRim2jdTZ2anW1la5u1pbW3X88cfnpjrnxIkT1dLSotdff12DBg1KvGpj2sHf5ptvrtWrV5e082LQoEElSz2TLlSxrqWfZHGQhdNOO+1Nt5199tmSpEsuuaS/h4Mc+e1vf1vSXrhwoc4///xsBgMgN2bPnl3SnjVrlm644YaMRgMylxtp/vz56u7ulpTO0tI0l9w2NjaWnDeX9P6n8mAv6eDvtdde67Ed19Zbb13SLq+qFkf5BvPRo0cn1rf05uVITz75ZKL9AwAAVCKWMVcWgsuNlPbS0rSqlfaH8mVvSS+DKxyjsr520v0n6a9//WtJ+9FHH03tZ6F/pf28xPpxiHt1GTJkSI9tAFiXwhmX62ujfzETb6Q0DwRPs1qpVFrQx90Tz7oWMrrra8d1wAEHlLQPPPDARPsvr8KZdFXONJVnWZPMuqJn1Vx9r9Kl/ZqD/pVm1WgA1WvGjBklbc66zBbB5UZK80DwNKuVSiHrWhxcJp11TVt5IP+Rj3wko5FUnvJzJ5M+hxIA0vbhD3+4pF1+QREA1mX06NFrL6pvs802nHWZMYLLjZTmgeBpnze322679diudN/85jdL2t/4xjcyGknlYWkm+qqwEqNg8ODBGY1k47GMEgAgSS+//HLJ/8gOwWUfpHUgeNrSPu+v/E1qeTuutA+Tz7O0lwyjeg0fPrzHdiVL+4gf9K91VYsFgA2577779Oqrr0qSXn31VS1evDjjEQ1sBJd9UFdXp0svvTTxI0i23377kvYOO+yQaP+vvPJKj+24eKOXnSOPPLKkfdRRR2U0EuTNs88+W9J+5plnMhrJxisPhMsrPiNf0q4IDqA6le+x/H//7/9lNJJ0dHR0aMqUKbnZ8kRwWUGmT59e0k76j2Po0KE9tpFfLS0tJe3bb789o5EA/ac8EH766aczGgkw8FCtGZWi+Az0dbXzrrm5WUuWLFFzc3PWQ+kVXgkqyKhRo9ZmL3fYYQfttNNOifZ/xhlnlLTPPPPMRPtHdsqLM+WtWBPQF1TqBbJTvlKAlQNA8jo6OtTS0iJ3V0tLSy6yl8luikNsp59+umbMmPGmQDAJixYtKmn/6U9/0oQJExL/Oeh/++67r+66666SNpC2a665Ro8//vgGv+7vf/+7JOnss8/u8et22mknnXbaab3++TU1NSXHVZA5AfrPv/71rx7bQH8ZO3ZsyT7LvffeO8PRJKu5uXnthdPu7m41NzfrrLPOynhUPWMmrjD33nuv3F2///3vE++b7NbAQbVY9IfHH39c7X/5m/77xOoe/23SVatNump7/Jr2v/ytV4FqsfLCVUmeOwwAyIdNNtmkpJ2nqucbsmDBAq1Zs0aStGbNGrW2tmY8og0jc1lBOjs71draKndXa2urjj/++ESLBuV9CZmZlYyZAOoN//d//1fS/v3vf6+pU6dmNBoMJO966/Y6d+8psfu58P4rN/p7TjrpJLW1tam7u1s1NTU66aSTYo8DAJAvf/jDH0ra9957b0YjSd6kSZN0xx13aM2aNRo8eLDq6+uzHtIGkbmsIPPnz1d3d7ekkPqeN29exiOqLHkPjtNUODx4fW2gGtXV1a3NVn7kIx9JvII3AABZampqWptMqampUVNTU8Yj2jCCywrS1ta29viOrq6uxJetbr755j22kZ7NNtusx3Zc7H3BQHXSSSdpt912I2sJ9LNNN920xzbQX7bddtse23k2fPhwNTQ0yMzU0NCgurq6rIe0QQSXFWTixImqrQ0rlWtraxPfP5T2OZdpK89KJP0HNmjQoB7bcfz3v//tsR1XNb+wxvXud7+7pL3zzjsn2j9vsLKV1rnDAHq25ZZblrS32mqrbAaCAa+8mFuS798qQVNTk3bfffdcZC0lgsuK0tjYuPYPpKamRscff3yi/Y8YMaLHdlxpBmfSm4PhVatWJdr/LrvsUtJ+3/vel1jfxRUt19WO69lnn+2xPZCVn4X41FNPJdo/B79nq7OzU1OnTtXKlSuzHgowoJSvkGHeQVaq/czj4cOH68orr8xF1lIiuKwodXV1qq+vl5mpvr4+8Svx06ZNK2mfc845ifaf9p7ItN/EP/bYYyXtRx99NLG+y4sPJV2MqLwyWjVVSourfAVA0isCCqsN1teudHk/CH3+/PlaunQpe9SBfvaWt7ylxzbQX0aOHNljG/0rX+8iBoDGxkaNGTMm8aylJI0aNWpttnLEiBHaaaedEu0/729SC/td19eOI+3AuzyLm3RWN8/Kz/z80Ic+lGj/aWfs01a+lC1Py0vLK2yTvQT6z3/+858e20B/mTFjRkn7vPPOy2gkkAguK07a+4emTZumzTffPPGspSQdcMABJe3yM+gqXdrZxTTleexpu/baa0va11xzTaL9T5o0qcd2pevs7Cxpd3R0ZDSSjUeFbQDovfKLn3lbabM+o0ePXputHDlypEaNGpXtgAa4qg0uzewgM/urmbWbWfKRVE6NGjVKN910U+JZSylUbSzeM5p09ca0M0R5XlrKMS3rt2LFih7bcTU2NpYU4kp61UH54dDl7bjS3oudprQrbFcz5kjENWTIkB7bqDwXX3xxSfuSSy7JaCTJmzFjhoYMGULWsgJUZXBpZoMkXS2pQdL7JB1nZslVZ8E6pX3m3Lhx40rae++9d6L9T5gwocd2HGlnFocOHdpjeyBLO3iqq6vTQQcdJDPTQQcdlPjzfubMmSXtWbNmJdp/2nux05R2he1qValzJCsw8uX8888vac+ePTujkaC3xo8fv/bCfG1trcaOHZvxiJIzevRotbS0kLWsAFaNGQ4z+6Ckme4+OWqfK0nufuH6vmfcuHF+8skna8GCBSW3r169uldZIDN707mRkyZN0mmnnba2fc0111RV/73tuzf9xxn7uvrP+r5Ju3/u++rtP0+P7fHHH6+VHSu1ae0b2dQ1r69Rt3dvsO8aq9HgQW+sDnit678aNnxYydLWtO57M1vs7uPW861Vb2PnyHHjxvmiRYtKbrviiivU0tLSq5+3Mc+5jbGux3h9Ghoa9IUvfGGDX1cJv5eU7e9Wrb+XxHOxL3guVu9jtr7fK+4cWZWZS0nbS3qiqP1kdFsJMzvFzBaZ2aLnn3++3wYHANVgiy220GZDNlPNpoPW/tMgk2p68W+QlXzfZkM20xZbbJH1rzRQbHCOZH4EAPRFtWYuj5Z0kLt/NmqfIOkD7n7G+r5nXVdmUVlOOeWUkv1yI0aM0He/+93E+r/yyiv161//Wl1dXaqtrdVBBx2kKVOmJNb/rbfeqquuukpnnnmmDj744MT6LVi8eLFmzJihOXPmaM8990y07/6472+77ba17UMPPTTR+769vV1nn322LrvsslT2GyM7nZ2duvDCCzV9+vReL0kmc7lxc2R/zY+XXXaZbrnlFrm7zExHHHGEzjrrrNR/btpOPPFELV++fG175MiRuuGGG7IbEDbo4IMPLqm6PnToUN1xxx0ZjgjoP2Qu1+0pSe8sau8Q3YYcS3tvWGNjY0lBoqQLsxx22GG68847UwksJWns2LFqaWlJPLCU+ue+LxSq2WSTTRK/79MsZIVspV1hu0pV5BzZ1NS0tpDa4MGD1dTUlPGIksExCflTvtf9ggsuyGYgQA5Va3B5v6SdzWxHM9tE0icl3ZLxmBBT2ud01tXVqb6+Xmam+vp63qwW4b4HqkpFzpHDhw9XQ0ODzEwHH3yw6urqsh5SIjgmIX/Gjx+/tjDe0KFDq6rwDZC2qgwu3b1L0hmS7pT0qKSfufsj2Y4KSUjznE4pZNDGjBmTeOasGnDfA9WhkufIpqYm7b777lWTtSzgmIT8mTlzpmpqashaAhupKvdc9gV7LgFgYBjoey43FvMjAAwc7LkEAAAAAGSO4BIAAAAAEBvBJQAAAAAgNoJLAAAAAEBsBJcAAAAAgNgILgEAAAAAsRFcAgAAAABiI7gEAAAAAMRGcAkAAAAAiI3gEgAAAAAQG8ElAAAAACA2gksAAAAAQGwElwAAAACA2AguAQAAAACxEVwCAAAAAGIjuAQAAAAAxEZwCQAAAACIjeASAAAAABCbuXvWY6gIZva8pBUb8S3DJXWkNJw0+6b/bPvP89jz3n+ex07/yfY9wt23TmksVacP82NcaT8Xs8LvlT/V+rvxe+VPf/5useZIgss+MrNF7j4ub33Tf7b953nsee8/z2On/+z6Rv+r1seT3yt/qvV34/fKnzz9biyLBQAAAADERnAJAAAAAIiN4LLvvpvTvuk/2/7zPPa895/nsdN/dn2j/1Xr48nvlT/V+rvxe+VPbn439lwCAAAAAGIjcwkAAAAAiI3gEokyM8t6DH1hZkNS7v/teb1vAKCS8doKAJWD4HIjmdmglPodZWbjzGzTlPrf1cw+bGZ1KfT9ITM7QZLc3dOY6M3sMDM7M+l+o76PkHSxmW2TUv+TJd0k6Z0p9b+PmZ0Q/b9Jwn3vHD0va9J67gNJIMAYeMxsBym9eScrZrajmY3KehxpYj5Btaum16SNRXDZS2Y2WpLc/fWkXxTN7FBJv5J0iaQfFn5Wgv03SPqJpC9JusHM3p5QvzVmNlTStZLONbNTpbUTfWLPLTOrl3SBpL8k1WdR3x+WdLGkm939uRT6r4/6307Sl1Po/3CFTd4flTRV0ogE+/6YpF9IOlfSNyR9Pu0Mb9HPzu2Lctpjz9t9Y2abpdz/26XwupPmz0FliR7388xsilQ9AaaZDZP0BUmfMrN3Zz2eNJjZ1grzSSoXXCuVmX3QzC7PehyVIMn3iJXIzN4iaWL08fvMbGLGQ+pXVf3gJiUK/v5sZvOlZANMM9tXIahscvcDJb0g6Zwk+o76P0DStyR91t0/Jum/ksYk0be7d7v7KknNkq6TtK+ZfanwuSR+RnT//EjSKe6+wMzeZmYjzGzzJPqXNFbS96O+32Fmk8zsA2b2trgdm9lHJX1b0vGSdpa0i5lNiNtvUf91kk6X1OjuTZL+Len9ZrZN9MIWt+/PSzrO3T8uaYmkz0g6y8zeGnPo6/p5H4gy63tLyb5RNLMtkuinh/73irL346Xkg5zoDclBZjYppf4bzOzEJPss6nuypDPiPh976L9B0hXVnuXBOq2SdJek95rZSVL+A0wzM3dfKelGSUMkHWtm22c8rDTsGf37uJm9I+vB9KPHJE0ys9lZD6Q/Ff4mzez9ZnaAmb0rqfeIFWxzSXuY2W8U/p6XZzuc3it6vN4XrV7b6NcggssNiDI1Z0j6oqT/mtmPpcQzmBe7+4PRx1+TNMySWx77L0mfd/f7oiu9H1B4s3etmR2d0ETcpbDks1nSeDP7hpldaEHc51inpDWStosCnv+VdI1ChjeJ8XcVffwLSScpPN5Xm9lWMfseJOlEd39E4Y3CXyXtKiWWfeqStJnCm6stJB0g6URJl0uaETPL2CVpqKRCVuh6hRfH4ZIOjdHvm0QBwo8VgvDpZnZd9DNjv1E0s6Mk3RMFr4m/3kUXnq6TdIqkqWb2+YT7P1jSdxSugH4xylQXPhf7ORS9zpwq6VoLy8MTEz2ucyXd7+7/KftcEmMfr3DffMfd28s+x9xW5aILm0MlbSmpycyaottzG2AWXTjaVeEi8MmSTqq2DKa7t0paJGl3SZ+MMplVq/BeyN1fkPRVSSeb2dVZj6u/RH+TBymsoNtP0lIz+1DGw0pVdJHoCUl7S/qHuz8uSWZWm+nAeiF6vI5QeG/zBYVtYx/cmD6YgDfA3V9RCDjmKyw7fEtxgJnAj/iTwpLYwh6ETRWWNm4R3RZrj6S7P+ruC6PmyZK+HWUw/yDpaIVgIa6bJT3r7r9RmDBOlbSFB7GuTrn7XyUdIumbkh5SeBwOlfRrSR+XFDcAXCjpc2Z2o6TvuftxCgH+Kknj43Ts7ne6+73RpPKipNslfc3Mdksi++TuL0m6QmHZaqukH7j7YZK+L2kHSX3O5kR9z1N4Y3OCmX1d0msKS5M/GnfsBdFzvknSLHc/Jfr4vWb2i2gcfX6jaGYjJZ0l6TmFJeF7Jfmm08z2lDRH0qfd/URJP5f03gT730vSLEmnuvs0SQ9Gt28jJfMm2t1fk3Sbwt/w5YU36HGDMzN7n0LW/mp3/62Z1ZnZe8xst6TGLmm0pB+7e5uFVQeHFDKw7t5NgFndzOwzChd9fyBpsaR9zOxzUr4DzOiizJmSGiWdrxA8V1UGM7po9mmFi6PHSDqhmjOYhfdCZvZFSScobJX5uJl9O9uRpS8KrN8haYqkgyX9XiHo+mvR11TNa3XZ687tCu9T283su2Y21N27zCyJ992psbBc/UsK7/WWSxop6bGNSahVzQOaJnd/2t1XuXuHwlLBzQoBpoUlcX1+Q+nur7v7v6OmSXpR0kp3f97Mjpc02xLas+TuX3f32dHHP1QIYJPY8/CqpPdEE/upki6S9K6ksjju/pBCQHmRu38vWo57vUJg+a6YfT+scNHgA5J2jG57XCHrmMjV1EKA7e6/VtgfeWhCWV25+y8UXgDuURR8uHubpLcq/v7Ln0hqkXSgpM3c/VPufq2kbS2hpabRBZoHi9r/dvf9op9xbXRbXwPxbkn/z90nKQTF50kaW37lMMab0M0ULtY8FLUflLSfmb0zoTe2tZLOcPc/WNiHdZKkz0m6zMyulOItkTWzwdGHz0n6pcLFphlmdrGkb27MRLIOmyk8d7qjK9Y/VQiUv5HE2CNPStoymghvk7S/pC9EF4oSW5qPyhK9dtZK2klhTrhL4SLPIklHFQeYGQ5zoxW9Zrxd0iPu/oK73yDpNwp/m2eY2Y6ZDTAhZralwnaOL0QXcy9WeCyPsZSK6mUtes5uIelwSZe5++UKv/OBZnZNpoNLSeH5HAXWTytcyP+Uwjaww6P3uMeZ2dbV9FodXdhqiObR0919gUISoFvSpWb2EUlzKvy5XivpEUmflHSUwgX0FyR9IPr73SCCy43k7p0KAeYaM3tM4U3TqoT67oqW+jxhZhcqZF2+7e6vxu27/M2umX1c0raSno7bd/TC8YTCco+z3H2WQgGYO+L2XfQz/uLuVxXa0fi3lvRMAt23KGQrP2VmJ5vZyQr7Qf6QQN/lHlLIxNYk9YIa/dG3KVwJrbewdHJHhX2Scfp9yd3nKezXPUuSoszQMEmxsvZWWrTqKUlfMbPiCwVHSqozs1372re7/1PSn6OPZ0m6X+Fx3jP6urVZtD72f69CUFbIwD6tsAz9pWiC2Xljx17W/32S7o8uQhwn6dwoM32OpDEW9lPH6X9NdNMSSUe5+2KF4lxfklTbl5UZRX0vVsh87yrpaoUl559UCJB3MbP944w98oLCxbETFTKY57j7OEkjzOwLfekflal4/orerHZJWqFQFGaH6MLvrxSWye7R2zdAWSublwvbGO6RVBNlMOXud0hapnDB5t/Kv5ej/8dKkrvfJOkfCgFnk6VUMb+/reM5+29Jf1P0OLv7aoX3kp83s69kM8p0mJlFc+ABZvaJ6DEdo/Ba/XF3/7uFlTkzFLJiVcPMxim8/12mcMHk5+6+QuHi6hpJV0m6xVMoINlXheeqme0drZB4UmHP6HSF93/tFmqIfEthJcWGuTv/+vBP4Q3Ys5J2S7BPk7SJpL9L+qeknVMY96YKy2MfkTQmwX7fKWlsUbsmpfvdFN6g/kXSrgn3vZfCFfDLknxc1/FzfiZpZMJ9bqmwNv53ku6UtEcK4y7c77HuG4Us9GpJNxbddoHCBYp3Fd12o6Txfez7J0W3bVL08VcVllZfpBBUbZPA2GsK/ytcqNhCYenTLZK2ijv+6PZNy9rXSdo3xn0/v+i2rRSurB4TPb4zFPY6H5vAfTNe0pFlX/dDSfvEGHvxY3uqpMcVJuwto9umSfpMUs97/mX7T5IVfdyosA3gYwp7mc5VWH69k6TDFJahbZv1mPvwO35eYVXLVyQ1SDpbYSvIeQrZnj8Uvzbm6V/h8VPYpvFehfcgn5A0W9LE6HNjJd0q6b1ZjzfJ3zn6+MOSPqQwR39aIYP37uhzhyvUkBiV9ZhTuA8+prCa56CovYPChZMrJF2pcKH98KzHmfDvvFv0enRa0W33lc2J25U/RyrhX/S68w9JH4jaRygEk83R8/YRSYf1tr/CHz02goVCLz+T9GV3j5UdWk//n1YogvFICn0PljRJ0t897GdMun/zFJ9U0RWWDyvs8XwsrZ+ThrTvm+hnvFXhRSvxK9xmNkLSYC8rnrKRfQxRyPb9StK+CkHTcdHnLlCYbL+tsBf4eEmHuPs/+th3rbt/Kvrcph72F8rMfquwX2+yh2XRfR17cf+DFILL+ZJekvR+hWJOvT4+ZwP913rI1hSKFJ0r6WgPV0ST6P8ihQtmje7+SwtH9DzV28d6HX1v4u6N0ec282j1RbTi4JwExl7c/+cUlg22KATKxygEtLl6fUDPLJxzfKTCm53TFd6U36+wp+kjklxhGflD6+2kAkWrQT4n6bMKFwa/qfD+YleFFQu1ki7dmNeqSmPhWKtpCheCXlJYabOzwlz+vKQPSpriYetI1TCz/1G4OLBA4ULYTgoX78YobCfaQ9Kh7v63zAaZgmgbx88Vaig8rXDhfnuFi98HSnqbpL962PKR+vui/mKhOvrZCs/zrxfmODN7RNJydz/EQg2OiloGHK2yulnSp9z9gei93lYKK0HGKyR1HnL3u3r7eBFc9pGZvcXLKiAm2HfV/LEB5Sxs7v+3pLcoVPtcUxRgHqmw52ispMvdfWnMvv9TCKCiz49WWMr+6b68Ce1F//+rELge2ZeLNz31H10YOkUhg9y0sffNevr/r7s3RktvR7n7sr6+/qyj79fc/fiizzcpVGL+TEJjL37efEhhMvyApB+lceEM2bFwnvKl7n6qhfOUP+7ukwoXjaJlsIVtJRWtaMmgKeztn6GwyuF9Cm/GD3H3/5rZEHd/pfjCWB5ZqHT7fYViLqdJOlahYuhbJW0jaZykv3nYBpBrZraNR8sdLRR8+7rCha+TJH3S3T8UfW5Hhderzo25yJYHFvaWrpZ0r6S7FbbRuKJMmLtfkOHwElX0t7ybwsWCFxS2a52nsFe61d2fiL52Xw9baSpC8Txv4ei9mQoXArZWqF/wL0nz3P3nfemfPZd9lFZgGfVNYImq5W8ukLWJmf0k+vQySXe4+2f7EoCso+/i4lvvVwhcJ/U1u7GB/ndWWFZ6dF+Dm576l/RuhSzGsX25b9bT/6Zm9uPoSurmZrZLX19/1tH3W4rum10UnduX4NiLnzf/lvSAu88gsKwu0XNylcJRYHcrLH+tjz79KTMb7+4v5imwjJpbR6sRlissc29y90lRYPllhaX1yltgaWabFH28qaRXFIotnagQaB0f/d6j3P2v7j6vSgLLd0k6xd4owPi0wjms5yqsyPlI9HUnKBRtfKAKA8udFCocj9Qb1YB/7O4nK9wH77CEClRWgiiwbFBYsXSUpIcVinLeoBCgHR49L1RJgaW0dux7m9l1Hk4H+LvCaol7FI4+u1dhmW+fEFwCyIy/USDrP2b2V4WlGUkc8VPcd6H41s8ltUfBSdL9L1PY7/Ut34ilsBvR/18Vshs/7e1S1Y3sv3D/vNzzd/Wp78LjepNHZ30l2H/hefMrhaU7yLlCcYno43cpnO+6h8KbHkm6NnpjdIKkL0tK5O+5PxRlCr6kcJbyFgpL6J6QdKOZbWlmxyospfxddiPtm2h7wMfN7CALBVu+rrDSYBuFoygKxUHqJV0TLb+rFqsV9hOOMrNjFAo9fkLhglp9lGFvVFgCXTUBVpmhCvfDqZLk7qd7OCrqUIVicbd7AgUqK0X0+jRDIXBervBa1OVhefd8hQCzkpNF7ZL2NLPL3P0qd/+0u98qaReFAnz39Pzt61fxh3kCqG7u3mFmSxQ2lE9y9ydT7Dt2deQN9P+vlPt/NuX+07zvk6js3FP/iY0d2SkKwLZz93+a2UsK+2wL5/dOjZZYj5L0iaQuWPQXC0eMfVLSMR72xt9t4TidPRUuknQp7Nd+NMNh9om7v25m9ykExoMkfdjdl0cZ5/9I+nR0MejLkqZVQ+aukI2OXo/2Vig0tY9CNeOPS/qjmV2mUMjogwpbMhJ9Hc+ame3p7g+6+xIz61Yo5nOShWOhHlG4sPD/3P22LMeZghcUTkXYR+Fs2o9Hz4NDFfZP3++hmn9FMbM6SS+7+wsWqsDeFGUwT46W+M5ROHt8QZ9/BiswAWTJUiyQlWbf9J9d3/3RP7ITLTWbqfAm5wGFgihfcPdWM9tWYV/Q80lfzElD2d6mIQoBh7l7s5ltEQWYheWkQxUyH7k8ciTKOm+pUHxre0nnu/v86HMHKgTQxFDnBwABAABJREFUb5N0j29EcZBKVfbYflZhL+klCtVhP6hQxfoJhSKKm0tqc/e/ZzTcVFjYr/9jhWXek6Lb9lA4euNFSRdK+qe7r66Wx9vMxipkn+9T2Fe6q6Rh7r7GzD6gcBTJSZW2RSN6rN4h6UcKhcN+HS3Dr1PYI3qPu0+xcLzTk3EeL4JLAJmzdAtkpdY3/WfXd3/0j2yY2T4K+5akUH1xnEKFzS94VCAjD8qCj0K1UEna3d0PKvq6oxWqZ+ayImzRm+7NPZzfWAgwfiDpB+5+pYViai/l4YJAb5Q9th+UNFXhLOJlZraDwnnW4yTdXG0Zu6LHe3AUUA1VCKi2lfSx6HPnKiyvnONVVLnbwjniX5d0urvfHT3Wt0n6P4VzTJskzXT3mzMcZonyINHMPqUwzm9IWuju/zGz8xX2RTck8XixLBZA5tIMENIOPug/m777o3/0LzObqJDxulXhTMvPKlRfrlWoNvlzhb1MuVAUfOyrUIjoCHfvMrPfWChGNVXSZIXzLQ/ObqR9VxRoHCHpsxaqWl/h7neY2Rclfc/M3qNwpMGpClUoc60ssJyssEd2pKQPmtnjUdbnVoX9ppPM7HeSVuU5a1cserzrJR1iZl0KZ1KfF/37PzO7WOFIqNOqLLB8t6T/p3De43ILheq2UchYf1Fh3/+XPewzrYgsbdHf54clHSDpKYUaCB0KF+62ih7D3RSOZ1uWyM+tgN8dAAAMMOu4on6kwhmxuymchdgh6S/RXq7ZytkxM9Ey0R0UzuQcLulz7v5wFID9VKHK8Q4KGdlECoFlIVrGPFuhsMlMhaW//+PuN5rZrgpB5c3ufld2o0xetH/2MIWKsJ9V2Ff5C0l/it7QbyfpVXd/MbtRJi9aWfAThX2Ghyo8jx9y9x9F+0uHSrrNQ3GY3FrH61OdpO9J+odC4cHRkt6lUBH3G9mMcsOiCyCXKFyce5vCWaNHK1SgP1ThHNJvuvtNif1MgksAANCfyrI/Bym86Vki6RmF4PLbChnLf7h7brJ668pYREUyvippocKb7sLZd4MkbVpYSponRRmRzRSOhnlW4ainLynswbtY0tnufr1FB8dXSjYnCRYKoZykcBbg7WY2TKFyaJdC5v331fK7FhQ95qdJ2t7dZ0QXSo5TyLx/KsrMF86fze3jXXjORh/vrJCV7FRY6vslhQJj/6dQbGycpK9X6u8aLXn9q7+x//lzCsu2j1V4vr7Fw5m6iT1eHEUCAAD6RZTNk6KjY8zsdEmXKhRA+aGk49z9HoWKk7+QtI2ZbVf0fRWtKGA+xcyuM7NrFYLkryocTXCImY2Mvvb1PAaWUskZfz9VKAbyN4Xjgaa6+/cVAulpZrZN4U16pb757o3C86/oefhuSSMk7WNmw919pcIZj29TWOq8aSYDTUHhdy56/B5X+L13c/c17n6DwvLQsdHXvVb29bliZlsrHCsjM/uQpJsUzqL9mqSt3P3j7t6ikPG7WNKDlfS7ruO18q0K2cqCOxSyzZtGr0GvSMk+Xuy5BCqImX1a0jh3PyPBPj8maVlh2ZWZzZJ0d7UtUQKQC7soLHXtNrN3KGQ8Do32ME2UdLKZPenut5rZRZIudvdVmY54I0Wv4ycr7EHbWWGJ70EKhUAulPSamd3g7omc6ZsFMxujkME5p/D4mNnfJe1voZLzawpHqjyX4TATUZbRGSXpb+5+rZk9J+koSRPMbKGHox3OlrRZtewHL8pW7q+wb3aJwnL1uyQdHmVsn5E0TNLK7EaaqKGSNjWzeQrVjz+uEIwdoHBx6BWFo2b+n6SvRpnrisnSRo/XPgoXOp5VWKp+p5ld4O5fVViKv4vCY5ZKZWqCS6D6fUyhmtlfJMndz8t0NAAGnOhq+iBJN5vZH939BHd/2sxWSTrAzH4cFcLYWeGMvF8XrqhXunW8sXyHpGvc/U6FN3VPKyzz3VfhCIC/5jywfKvCvLK7whEbMrNaSYsUlgj+j6Sz3P2+rMaYpKJs9BRJR1s4y/MJSVdKGqyw1/QtZnZHtL8yl0fJrEtRMZhrJd0iaZrCxZLCBZ850ccXuPvfshllstz9H2Y2V9JnJE2U9G93f8bMFiocM7Nz9Fp1vLs/VymBZdGFgH0Uiiy1KbwWPaRQEO02C0WJ9pD0FXdfntZYWBYL9CMz+5SZ3Wdmfzaza81skJl9xsyWRRPWfkVf+0MLJeoL7VVFH3/FzB42s4eiq/sys8+Z2f3Rbb80s80tVCk8XNIl0c98d3G/ZvYRM3sw6ut6M9s0un25mZ1vZg9En3vvOn6XA8zst2b2CzN7zMzmFS0dWm5mw6OPx5nZb6OPZ5pZs5ndY2YrzOwoM5sb/YxfW9i/AaD61Lh7l7vvrFBVs1AA4zcK2b3Ca99KhcxI5m/Weqso+DjcwrEMaxTONix8/leSlkoa6u4L3f3pbEbad8VL7dz9ZYU9Zz+WdKKZvd/duyTNU6iaeUCUec7FUubeMLPjFCqgHqFQyOUYhUz0LxSWAE9QKPJSVSwcITNdYbnzNIXgcpCkbne/UuH9xafc/Zd5f7zLnuN/k3S5pD9I+qaZbenuz0p6VNJeFvZkPhd9bUW8VkWB5UclfU5he8FJkk5QOMbp4wqvsecoVLu9Lc3Hi+AS6CcWylYfK2k/d3+/wkT0KYV9GvspXBF7Xy/6aVCY4D7g7ntImht96lfuvnd026OSTnb3exWuNp7t7u/3ogOczewtCnucjnX33RRWMpxW9KM63H0vhUqHU9cznD0V3ky8T+EMt/3W83XF3q1wNfBwhTcnC6Of/6rCJnMAVaaQqbNQvOc2SaeZ2YXu/l2FJZRfMLP/VXgje1UUrOTN5xSWoF0maXczu8bMtjWzwhu8XK4WK8qINJjZRWY2Q2H+mqtwtMHJZjY2unjwurs/JVXOm+6+KLpQaoWLrgoB5ackDVHYf7ePwjLnHyvMsS9nMdaklQUd71ZYPnmcmQ1y9wcl/V7SCWZW5+6d7v68lP/HO3qOH2RmZ5nZV6Lg8TSFC16/MbNCsHZTYR9xBdpVIeO6fdTukPQtSbtG+2P/6e6PS+k+XgSXQP/5iMKG9/vN7M9R+0uSfuvuz7v7fxWKI2zIRxUOpl4tSR4KCUjSmCgj+LCk4xVeZHryHoVKjIVzjZoVrr4W/Cr6f7HCGV7rcp+7Pxm90P65h68r1uLuayQ9rHAF9NfR7Q/38vsB5ETxagQzO0bS1QpLRBsUlhhe7O6zJJ0R3X6Yuz+UyWDjm6Kwz2moQuDxLkkXKBS6OdHdc3nGY/Sm+1CF36VNYXnvLxSC5asUlkV+zsJy2dwrW+Y4xN1fc/efKCx3/ZDCc/Q3kl6UtIWkYdUUWEaP98Fm9jkPhWu+qvAYfyX6sqcldUvaJKtxJi36nQ+RdJGk+xXObJ0f/c1OV9i7eJrCOZa/rpQsbdFFkP3MbB93/5ZC1eLvm9nI6Hm8uaQ9zOyt/TXuXF5FA3LKJDW7+7lrbwjFdo5az9d3KboAZGY12vAL+Q8lfczdH7JQUOKAeMPVa9H/r2v9rxWvFX1c/HVrx65wkPSbvsdDQY81RZN4dw8/B0DOWCj6coBCACKFpa4/jC5oLbNQifFhMxvq7qcrFAapeGY2TtJ/3H2pmX1G0nJJjykU+dhE0knufrmZHaHwOw9x99zuw4uW+k5SuGj5PoXg+UFJ/6uwiuYbkraslgCraJnzmZI+bmYtkv7o7gstnNt5spk9L6lO0mmFzF01iIKswxVWVBXqM7QpvH/5cvScLuyxzMXfa2+Y2dskNUlqVFim/7Sk95rZne4+2cw+q/B33C5VTpa2sKJA4aLdp6Pb5kTvGdvN7CqFSr7f7M+/TzKXQP/5jcKV+m0kyUKVtQclfdjM6qIr/J8o+vrlikp7KywhLWQAFkj6jJltXtSPFMpNPxP1c3xRPy9Hnyv3V0kjzWxU1D5B0u/6/uuVKB77xxPqE0BOWCgccYKkBWa2q5m9XdILko4xs00kKcoKzJd0cLR8tCKyAT2Jxv5uSR3Ra+3Lkk5XyOp9UuGw8hPNbNeiZaK5CyzL9p+tkjRL4QLgdIU3sV9RyNr9WtJLXgXFXKI35IWPd1PIUl6scIHgODN7v8KZjocpLD08M6/Z6PWxcG7pCQpB1l1mNkFh68tDCs/tByXdG2U013XsRS65+0sKf8fdCkueGyR9WNIkM7vJ3Z8pBJaVxMy2V1iafay7321me0dbD76usJLi8woX9H5l/VjTgiwB0E/c/S/RXpXWaBJbo/BiNlNh0/iLCktLC76nUFnxIYUJvHAW0a+jSW6Rmf1X4cyi6QpLV/4k6fno/0JAeaOk75nZFyStLRDk7v+Jrrr/3EKlv/slfaen3yG6Yn+qu392A7/u+ZKuM7MLJP12A18LoPoMUtiTfbTCqobhCsVAbpf0kJmdGn1+G0nj85L9KWxfMLP3SPqZpM9KulnhmIarFS7+vUPS3pIeyWqccUUZkQMV9m7VuPsN0T79hxTmmL0Vzv/7eXSf5Fq0HLQ7+niiQkXNP3k4ZuIvCkfmnK6wJWWymb3Fq+S4kTKusNroTEnbKmTjPyxpuLtPi94rHGNmZ0i6ulIyeElw9+eLLvrXKOyTvljhb7pSPSepRaHC9qcVLnytlrSHu19sZltIutXM3uvu/+ivQVkVPS8AAECGzGxHSSvd/aXoTfrPFJbF/kdhWdlXozemOyucGXiuuy/JbsS9Y+GIlOGSNpP0gLu/aOFMw/0kzXH3+6I3cvsrrByZ7dHZwnlStOfugwo1AL6j8Pv8VqHSZLNCBvpwSU3ufkdWY02DmZ2scBHkzwqZyz3cvcPM3qVQ0OddCmd7rs5ulMkqesxrou0q71Eornevu/8xupg9S+H3N4Vg888eqqfmUtHvbJJq3X1NtPz7PQqZ2tUKx+18MloOnflxI2a2mbu/WnZbrUKW9YMKq+PaFP5eJ7j7KdHXfFnSrUX1NdIfK8ElAACIy8KxBT9VWHL/RXd/1sxOVKgO/RuF/Xr/lXSZu//bzDbJQ9YrKvRxgUIWp/AG9FBJyySdqlCcbY67/yGzQSbIzPZW2H92t7v/zEK11N8qZEjmSHqvpEE5Lry0Tma2v8Kqm2OigPIahQzmxzycZ7iDpFfc/YVMB5owi6q+mlmtu3cVgszoc4cqLLuc7u63ZjvS+IqCyq3c/YWi33mkwlE6n5K0qUJhrppK+ZuOAv4vSZpZCOoLr5/RioLu6OMPKqygmJHlhR/2XAIAgCQ8rrAUdD9JF5vZwQoFvB5XqLR5i8KS0S+Z2SCFrQEVLdq/9FVJX3L3I919kqTrJN0qaZS7X66wbO7iaNtANRivsAx0FzN7q7u/prC8eT9Jm7r70ioMLDdTWAa5g8K+Srn7aZIekPRbM9vaQ2X0agsst5P0o2jZZFcUQD9qZh+IMvFHSfqKV8m5pUUFcJrNbKZCVditFLLVt7n7P9z9MXf/UwUFlu+V9COF6vxrs8VRMDlCocr2uywcd/d5See7+x1ZPl5kLgEAQJ9FSwbf4u7LzGy4QiGJGklPKix/naCQzfycwnm4nXkohBLtv+qQdLiHQ8fX7rOL3pieoJDZ2kShcNmv3f2JrMbbV0XZnJ0kPevuq83sKIWjF+ZIuk/S7goZkY/6G8df5da6ljlGQcaRCsH13e4+P7r9G5KucPfl/T7QFBT/7hYKDJ4r6SfR0u4fKwQxV0Sf39TdX6uEZaFJMLPxkq5XuFjydYXK9p9XOE7m8ehrKuZ3NbN3KCx1/UG0h7JWYUn6rxWWKN8m6U53vygKJodHe0cz/R0o6AMAAPrEzIYoZPY2sVBV8X/N7HGFPZatCpnKXRT2Ab3o7lOyG+3GcfeVZnaYpIvM7A/R0sFNPZx7ONPMPixptLs/YGbXu/vrWY+5L4qyORdIajGzvRSOGHmnwpLIfypUK59VbYGlme3i7o9GS0FfMLM7oy/bP3qsf+DuZ2U43MQUPXfdzLZ396ei5b5PSrrSzPaV9NVC4RczGxRlrSvm6I0EvFPhLMsto4+PjfZPF6ruV9rvuqNCgaF/RhfxrpX0oIfqr0MUKhYvkdaO+/mijzNDcAkAAPrE3V8xs68q7Ku8Klpm166wF7Hd3Reb2UmSTpH0kwyH2iceqoV2S7rPzMZFAchgd1+jsNR3TfR1uQoso4zIpgrHRo1WyOIcrbAMcrhCJvpbZvaCwmN5qbv/bzajTVZRYPlZSYeb2QkeClDtr7CftEWhYuoeZraF5/AomXJmtq2kT5jZ9QqV5C8yM5c0xd0vM7OtJZ3o7j8oLKfM23N6XYqy8tu4+3MKF0puUDhy5IAoy3eopIlmNsMrrFCTu/9flFH/qKQZkv7P3adHn3tF0hKpsrKtEnsuAQBADO7+bLSE8HCF4GRPhYvXl5nZu6MlsF/3Cjwnrjc8nOl3hsLxT1t5qCx5oqS3S6r45b3loj1cCySNkzRE4Y32jxSWMB8jqdHdV5nZvu5+g0Khky+b2QerYd+dJJnZfgrB9P9EgeVuCpVwn3P3JxWqHH+tGgLLyBqFx3yowsWEqQpHBF1kZt+OvmakFILvSgpU+qoosDxM0v9Gmb/HFZaU3ilpRFQA5+uSFlZKYGlm21s4J1iS5O63KRzhdL+kB6OtByUq7fFizyUAAEhEVBBksqS9FPbsfVnStxS9Z81ybHFFS0fnKhTQOEHSKe6+NNtRbRwLVTFvk/RNd78uum1LSYsUlr7uGgWWEyR9RdJnoqWTp0m63d3/mc3I4ylbCjtE4Xf7hELl4u+b2Z6SNnH3P1VaFiiuaHnr69HHV0Y3X+buy83sfQpZsekKZ86OlvS4R9Vi887MDpB0paST3P3+aM/ivgoVn5sULg7d4O43V8LjbqGI0h0K58t+ReFYp7uizzVIOkihavXPoosgFYngEgAAJMbMBissK7xM4U3sXzMeUmKiJXS/krSnuz+S9Xg2lpl9RtL73f1MM6uR9H6FjNUeCsVsLlbIcp2rcOzBzRkNNTFlgeW2kv7t7q9aOKf07QpVQhdGn69RFVwIKSjK3n1AoXLzkwrLK/8r6ceF/XpRcL0mbxdL1qXs8T5OYd/3nxSOQjpR4Vik6xWKdRWW9mceWBaY2RUKFz6uVjhr9TFJF7v7MxYqUp8i6W8KRaZey26k60dwCQAA0EtmtnmlLKHbWFERojmSZkk6VtJmCoHlnQpvZP8l6VFJbe7eUrT/LvdvFs3sSwpZus0VlkZ+X2E/6RaS7omWH1adaFno+ZK+7O4LowB7hqLjgdz9T2VfXzGBVl9Fy56fUCjcM00hU3mtpFcUqld/190fzGyA6xAVleqO9q1/WSE7eZ+ZtSnsk12q8Di+X9Jj7v5YdqPtGXsuAQAAeimvgWXkfkk/V8hQbqGwxHc/hSInv5N0jLufXQgsq2j/3SckNUg6TNIyhSNVOhUCzDWS9jGzzTMcYiosHDXyBUmfiwLL2mgP9AWStlYo8rNF8fdUw+OtsHy0TdLTCtnKQ9z9+5IWS/qgpEEZjm2dipYir1YoqjU6am8r6aeSno3+v7eSA0uJzCUAAMCAYmbDvOhYkWhv2tcVluM9UyUBxlpmdoikVZL2UahsfGhUmGlHSc8pVMftzHKMaYiO2PiVQlXYhwv7L6NAulbSDu7+l2xHmZwoeO6KPj5fYan3Ye6+IlrSPkfhuJWKXu5t4TigWxW2F8xx98ui29/pOThLl8wlAADAAFIILM1ssJkdrFB0aY67P11NgaWZHWdmYxQOnL9B0jh3nxwFlp9XCKhfr9LA0hSWgf5R0jgz2y4KLPeT9B1JNVUWWI6VNL1QTdXdvybpfyX93MzerrDc++RC8Z7sRhqY2XAze3/ZbYMkyd0fkPQ9SfM8HBUzOBpzxRbxKcY5lwAAAANMVHhpvKSzJM1w99szHlIadlE4WuUwMztI0tjo+Il9JX1a0ifd/T9ZDjAJUUC1g7v/ufhmd3/NzO6TdKCkejN7WNJJkr7g7i/2/0hT9ZJCVtrN7NvRBYNvKyyFvl3SPu7+dyn7pb9REHmWpK3M7Dp3XxSN63ULZ9BOlPR3SR+zHJ61SuYSAABggHH3NZLuk/Qpd7+1ErI5KbhY0gozG+PuZ0i6W9LHJI1R2F+au4q/5YoClc9H1UQlhT18UfGeGkk3SrpJ0qsKx8vckclgE1R4vprZ7tEy0lUKy2DHSzrd7P+zd+dxVpb1/8ffn2FwQTQFzNxCEW1TSsUlU74yyuBkqZhLjdXk0uqaEiJpmpopPyvDzDTDxoK0zdSMBATTLBfQUmzRkSSXShlcUjSB+fz+uO4znHOEcZh7m/uc1/PxmAdznZk513W4zzn3+dyf6/pcNlShEvIsSZ+Nnu+5i9Yyr5L0ZUkuaUKUXZeZbSbpbknru/uPJP1Z0i65DbaPWHMJAACAmmBmx0l6i6Tfuvtfzex8hazecWW/0702r8jKthoxha0rnpf0E3dfFAUqD0r6mrt/P9eBpiRaS3uhpIclbSnpF5JmSLpaYbuVZoU9LmflNsi1sLCX7NkKlWz/KOn/SeqStL27/zL6nUI+TwkuAQAAUEjVW2dEWayTJK2StEzSVIXiKF9199vW9DdF18tApdYe8yaSfi3pLHe/28zeobB/5aUKW81sLmlwf1xXamY7KQTCH1GoDlvaGqZ879GGsgqyhcK0WAAAABROecBkZm1m9jlJO0RZynMljVQItEZI2q+W9u0siQKVKxQC6g9IekFhD9NVZYFlQy095kiXpP9K+qckufvfFdZY7uHur7r7P/tjYBlpVLjwsdTdn5L0FYV9Zs83sz2kiq1JCofgEgAAAIUVBZUnKEyPvMHMjooq335EoTLq5ZKur8EAS6rxQKWkbI3ltma2obu/LGmBpJ9GxamksIZxRFl11X6hbOwbR2P9h6SHJDWZ2TB3f1Yh67qJwrEsNKrFAgAAoDDM7O2SOt39lahwy34KhXqOlDRb0i/MbAN3f83d71MoXFQTytZZbizpNVUGKne4+7NmNl1Sq2ogUJEqHnOLpMskLYgCtknRr/zJzH4g6dOSTusvxXtKorEfqpBRXinpR5IeU6gKu5+ZLZL0WUmnlyraFhlrLgEAAFAIUQXUKZKelPQ9d3/ZzC6TtKGktypsPfKqmZ0uaYG735nfaNOxhkDlXZLeKWmFpPJApWYeu5ntKekYhbWKT0r6qKSDJR0U/euSnnX3O/Ia49qY2V4KU5c/KOmHCpVtj1bYImYXherFv3D33+Y1xiQRXAIAAKAQzKxBISu3m0LW7jsKGayvShoWBZtHSZos6SPu/o/cBpuCegtUJMnMNlDY93Gpu7/XzAZEe0JeIemeaNuOfsPMtpe0p7vfELU/KWmApH8prAX+uLs/bmZD3H2ZmQ109xW1UnSJabEAAADo18xsR0kN7v53M5sh6UVJLZI+4+6XmNlwSbea2ZMKhXzaaiGwrA5UFCrCXqEQXG8m6eRo2uWf3H1erQQqZVNht3f3f5jZWEl/NLMz3f2S6NeWSXp7jsNcm8GS/mFmm7v7cwqZ1skKx+sod38iugBysJl9VmHblJopNEVwCQAAgH4rWlf5d0lLzeyrCtuMXK2wn+VIM/usu38h2oy+UauL29SCugxUosDyw5K+amafcveHoi1X/mhm75b0U0mHSjoz14FWiYLih82sUdLdZjZTIbv+WYW1v5ub2TaSzlHYRuW1HIebCqbFAgAAoF8zsyZJcyWdqjD9czOFKaGvSxoa/eyHtfRhvSx71yjpbkmlQGWGQkGYmyWtL+lKhUDl17kNNmFmtrfCBYRWd19kZlu4+3+iYk73S+qQdLS7P1WaJpvrgFVxvD4kaVtJf5I0TaEI0SxJX1LIqg+U9AN3v6XoGeY1IbgEAABAv2dm4xQ+rL9X0hYK1TY/KmlPhfVsH3D3F/MbYXLqPVAxsw8oVAC+R+HxH6mwp+VXFIr3zJd0ubtPzWuMa2Jmu0uaKmmKu99rZu9X2H/zUnefEf1Oaa1lzRyvcgSXAAAAKAQzO1jStyTtHX1A30whwBrk7k/kOriE1XOgYma7SPqYpAMUguolkg6UdL+73xpNgb5R0t6SlvWHx25m20o6WdL/ufteZbfvJald0tXu/s1aO1bVCC4BAABQGNF+h9+W9H5378x7PGmol0DFzIZJ2sbd/xS1Tepec7mRpBXu/noUTM5QKGB0Z/S767n76zkNvYKZHSTpM5JuUFhf+Wt3/2bZz9+vUJDq7pyGmJmGvAcAAAAA9Ja7l6aFzo22JqkpUaDybUkLJb0S7dkpSXL3eyUdK+neqF3kwHKApNMlfdbMRkvh8USB5ZYKW6wMjgr5XCfpK+5+ZykAVdjXM3dmNkrSREnnRFV9vyNpBzM7qfQ77v7HeggsJYJLAAAAFIy73yRpP3fvynssSaqXQCXKuK6S9GWFNZQTouykoqnOd0sa6O7LJD2jsDfkTeWZ2v4QWJvZpgrrft+lqFKvpDkKBaZ2N7PT8hlZftiKBAAAAIXj7i/nPYYk9RCouKRDzOw0d78sn9Elqyww3E+hMNE7FILo/yepS9JEd/9l9Lsda/i73FQFuC+Y2Q8lvU3SyWb2DXdfYmZzJQ2Q9Ncch5oL1lwCAAAAOaheM2lmOynsY/mypFKgsrGk8ZL+6u6P5DTUxEWP9ReSPiJpuaSzJb0k6cfu/lD0O/1im5GSsiq+4yW9T9Krkr4nabikExRmhX7X3f9hZg21llnvDabFAgAAABkrD1TM7EwzO0XSE5K+rhC0nGRm27v7fyX9spYCy0ijpGWSlrr7UwrbjOwr6Xwz20OS+lNgKXUXGvqQwjH6i0JgPENhm5SrJK0n6VQz20Ah41x3CC4BAACAjNVboFIqxGNmG5vZQEn/kPSQpCYzG+buz0qaLmkThaCzXzCzt0f7bpamLh+lUGxoPYVYqkvSryQ9LelySd9z99f6wxTePDAtFgAAAMiAmb1d0rbufncUqEyTdIGkUZJOUyhes4mkwyRtK6nR3f+Wy2BTYGaHKgRmKyX9SGF96TsVKr8uUtjG4/TSdiN5ioLhjSX9XdKLCtugzDGzrSRtKunHkj4U/fr9Cusrx9VrUFlCcAkAAACkiECle4/OKyR9UNIPFdaVHi1prKRdJO0s6Rfu/tu8xrgmZvZ1SaMVAuBr3P2XZvYuSae6++eirVLGKexteW+eY+0PqBYLAAAApCgKEl+KKouOlvRFM9s4ClTeIuk+d38mClSmKwQqhQ4szWx7SXtGW6pIoSLsFZJ2k7SZQoDtZvYnd59nZgPdfUV1kaM8lMYSNe9QuAAwS9Knotm9cyTtaGbfVZgm+zECy4A1lwAAAEBKovWFJXdI6lCoMPpxMztc0lNaHaj8UtKdNRKoDJb0DzPbPGo/qbDVyvkKwdjjZnaUpG9F60pXSflvN2Jm75T0AzMbG900W9JbJO0t6TpJxytkWg9XmNp7sLvPyWOs/RHTYgEAAIAURIHKFEnXuvv8aHrsDIWqsPdJ+rSkr0l6RNK7JXXVQmBZVgm3UdLdkmZK+o7CY39M0s2S1pd0paSz3P3XuQ22SpQ9vkPSgwoXAbokzZX0MUntkvZXWBt6mbv/KpdB9mNMiwUAAADS8VZJH5f0HjMrBSpnKQQq90raUNJFqqFApSyw/JBCUaLTFAoXLZX0BUlfkjRJ0kBJU9z91/1hKmyJu98ZBZi3KRRY2kfS9ZK2lnS7pJ9JMoWMM6oQXAIAAAApqMdAJQosd5f0RYXg8d5oD8/vRj8/S5LMbIi7L+tPgWWJu/8+mrJ8mUIl35skHSRpE3dfaWY/dfeVeY6xv2JaLAAAAJAiMxuv1YHKrgqByt3ufruZNdZSoGJm20o6WdL/ufteZbfvpTCt9Gp3/2Z/DCqrmdnBki6VtLe7v1hV6AdrQHAJAAAApKweAhUzO0jSZyTdoLAu8dfu/s2yn79fUoO7353TENdZ9JjaJb3T3Z/Pezz9HcElAAAAkIFaDlTMbJSkbyrs//hINK30AEl/dffv5Du6eKILA6+4+x15j6W/YysSAAAAIAPu/ltJx0l6b95jSZKZbaqwzci7JL0e3TxHocrq7mZ2Wj4jS4a73+rud0TVftEDMpcAAABAxoqw5rAn1eM3s50kTZb0sqRvuPsSM9tY0niF7OUjOQ0VGSK4BAAAANBrZduNjJf0PkmvKuwJOVzSCQqzI7/r7v8wswZ378pvtMgS02IBAAAA9FrZPpZfl/QXSR+RNEPSPyVdJWk9Saea2QaSyGTVEYJLAAAAAD0ys7eb2Qei7zeVdJSkoxUCyQZJXZJ+JelpSZdL+p67v1bkqb9Yd0yLBQAAALBGURGbjSX9XdKLkk529zlmtpWkTSX9WNKHol+/X9JfJY0jqKxPZC4BAAAArJEHL0n6oaQnJX3RzA5392cUprzeF30/UtJ0SV8msKxfjXkPAAAAAED/Y2YD3X1F1LxDIVM5S9Knol055kja0cy+qzBN9mPufm8OQ0U/wbRYAAAAABXM7J2Spki61t3nR9NjZ0h6QtJ9kj4t6WuSHpH0bkldBJYgcwkAAACg2lslfVzSe8zsewoFe86S9DFJ90raUNJFki5z91/lNUj0LwSXAAAAACq4+51mNkbSbZKekbSPpOslbS3pdkk/k2SSnsptkOh3mBYLAAAAYI3MbLykyySNkrSrpIMk3e3ut5tZo7uvzHN86F8ILgEAAACslZkdLOlSSXu7+4tVhX6AbkyLBQAAALBW7n6rma2S9KiZvdPdn897TOifyFwCAAAAeFNRBvMVd78j77GgfyK4BAAAANBrZmZOEIE1ILgEAAAAAMTWkPcAAAAAAADFR3AJAAAAAIiN4BIAAAAAEBvBJQAAAAAgNoJLAAAAAEBsBJcAAAAAgNgILgEAAAAAsTXmPYD+YtiwYb7ddtvlPQwAQMoWLly41N03z3scRcH5EQDqR9xzJMFlZLvtttOCBQvyHgYAIGVmtiTvMRQJ50cAqB9xz5FMiwUAAAAAxEZwCQAAAACIjeASAAAAABAbwSUAAAAAIDaCSwAAAABAbASXAAAAAIDYCC4BAAAAALERXAIAAAAAYiO4BAAAAADERnAJAAAAAIiN4BIAAAAAEBvBJQAAAAAgNoJLAAAAAEBsBJcAAAAAgNgILgEAAAAAsRFcAgAAAABiI7gEAAAAAMRGcNlH8+fP1/jx43XnnXem1sf48eO7v9LS2dmpiRMnatmyZan1IWXzWDo6OjRhwgQtXrw4tT6uv/56jR8/Xj/72c9S60OSrrjiCo0fP17f+973Uusji2Of1fPrsMMO0/jx43X44Yen2k8Waum4AHEdeuihGjNmjCZMmJD3UDI3d+5cjRkzRvPnz897KLl49NFH1dLSoo6OjryHgoyNGTOm+6veTJ48WWPGjNHZZ5+d91D6LLXg0symm9mzZrao7LYhZjbHzB6L/t0sut3MbJqZdZjZQ2a2W9nftEW//5iZtZXdvruZPRz9zTQzs576SNqll14qSbrkkkvSuPvMzJw5U4sWLdKMGTPyHkpsU6dO1fLly3XxxRen1se1114rSbrmmmtS60OSbr75ZknSjTfemFofWRz7rJ5fr776qiTplVdeSbWfLNTSccHa1fo5MinPP/+8pHBBpN5cdNFFkqQLLrgg55Hk48ILL9Qrr7yi888/P++hAJn5wx/+IEmpJq/Slmbm8oeSDqq6bbKk2919R0m3R21JapG0Y/T1GUlXSuEkKOlcSXtJ2lPSuWUnwislfbrs7w56kz4SM3/+fK1cuVKStHLlylSeANUZvjQyfp2dnZo9e7bcXbNnz04ti5HFY+no6NCSJUskSUuWLEkle3n99ddXtNPKXl5xxRUV7TSyl1kc+6yeX4cddlhFu8jZy1o6LnhTP1SNniOTcuihh1a06yl7OXfu3IrPGfWWvXz00Uf1xBNPSJKeeOIJspd1pDpbWU/Zy8mTK9+Oi5q9TC24dPc7JVV/ajlUUnv0fbukw8puv86DeyRtamZbShovaY67L3P35yXNkXRQ9LNN3P0ed3dJ11Xd15r6SEwpa1lS1OzlzJkz1dXVJUnq6uoqdBZj6tSpFe00spelrGVJWtnLUtayJI3sZRbHPqvnVylrWVLk7GUtHRf0rJbPkUkpZS1L6il7WcpaltRb9vLCCy+saJO9RD0oZS1Lipq9zHrN5Rbu/q/o+39L2iL6fmtJT5b93lPRbT3d/tQabu+pjzcws8+Y2QIzW/Dcc8/1+kGUriaurV0U8+bNq7gyOm/evJxH1HelrOXa2qiUxbGvpedXVjguda/fnCP7en5EMmrlc0ZflbKWa2sD6L9yK+gTXU31PPtw96vdfbS7j9588817fb+NjY09touiqampe+yNjY1qamrKeUR9N3z48B7bqJTFsa+l51dWOC4oyfsc2dfzI5JRK58z+mq77bbrsQ2g/8o6uPxPNF1H0b/PRrc/LWnbst/bJrqtp9u3WcPtPfWRmIkTJ1a0zzzzzKS7yERra6saGsJToKGhQcccc0zOI+q7SZMmVbSr560n4dhjj61on3DCCYn3IUmHHHJIRTuNdUZZHPusnl8bbrhhRXujjTZKpZ8s1NJxQZ/UxDkyKZttVllraOjQoTmNJHtTpkypaJ9zzjk5jSQf1WvNvvKVr+Q0EiA7++yzT0W7qOtNsw4ub5ZUqmbXJummsts/GVXE21vSi9G0ndskNZvZZlGRgmZJt0U/e8nM9o4q4H2y6r7W1Edixo4dW3HlP42Df9ttt/XYTsLQoUPV3NwsM1Nzc7OGDBmSeB9SNo9l5MiR3dnK4cOHa8SIEYn38dGPfrSifeSRRybehySdeOKJFe3Pfe5zifeRxbHP6vn1q1/9qqL9y1/+MpV+slBLxwV9UhPnyKTcdFPl0NKsnt3fHHjggRWfM8aOHZvziLK10047dWcrt9tuO40cOTLfASEz1esMi7rusC+q64VUrz0uijS3IvmJpD9KeoeZPWVmx0u6WNI4M3tM0oFRW5J+I2mxpA5J35f0BUly92WSLpB0f/R1fnSbot+5JvqbxyXNim5fWx+JKmUvi5q1LGltbdXOO+9cE9mLSZMmadCgQalkLUtK2cu0spYlpexlmtURszj2WT2/StnLImctS2rpuGDtav0cmZRS9rKespYlpexlvWUtS84++2xttNFGZC1RV0rZy6JmLSXJwpILjB492hcsWJD3MAAAKTOzhe4+Ou9xFAXnRwCoH3HPkbkV9AEAAAAA1A6CSwAAAABAbASXAAAAAIDYCC4BAAAAALERXAIAAAAAYiO4BAAAAADERnAJAAAAAIiN4BIAAAAAEBvBJQAAAAAgNoJLAAAAAEBsBJcAAAAAgNgILgEAAAAAsRFcAgAAAABiI7gEAAAAAMRGcAkAAAAAiI3gEgAAAAAQG8ElAAAAACA2gksAAAAAQGwElwAAAACA2AguAQAAAACxEVwCAAAAAGIjuAQAAAAAxEZwCQAAAACIjeASAAAAABAbwSUAAAAAIDaCSwAAAABAbASXAAAAAIDYCC4BAAAAALERXAIAAAAAYiO4BAAAAADERnAJAAAAAIiN4BIAAAAAEBvBJQAAAAAgNoJLAAAAAEBsBJcAAAAAgNgILgEAAAAAsRFcAgAAAABiI7gEAAAAAMRGcAkAAAAAiI3gEgAAAAAQG8ElAAAAACA2gksAAAAAQGwElwAAAACA2AguAQAAAACxEVwCAAAAAGIjuAQAAAAAxEZwCQAAAACIjeASAAAAABAbwSUAAAAAIDaCSwAAAABAbASXAAAAAIDYCC4BAAAAALERXAIAAAAAYiO4BAAAAADERnAJAAAAAIiN4BIAAAAAEBvBJQAAAAAgNoJLAAAAAEBsBJcAAAAAgNgILgEAAAAAsRFcAgAAAABiI7gEAAAAAMRGcAkAAAAAiI3gEgAAAAAQG8ElAAAAACA2gksAAAAAQGwElwAAAACA2AguAQAAAACxEVwCAAAAAGIjuAQAAAAAxEZwCQAAAACIjeASAAAAABAbwSUAAAAAIDaCSwAAAABAbASXAAAAAIDYCC4BAAAAALERXAIAAAAAYiO4BAAAAADERnAJAAAAAIiN4BIAAAAAEBvBJQAAAAAgNoJLAAAAAEBsBJcAAAAAgNgILgEAAAAAsRFcAgAAAABiyyW4NLMvmtkjZrbIzH5iZhuY2fZmdq+ZdZjZDWa2XvS760ftjujn25Xdz1nR7X83s/Fltx8U3dZhZpNzeIgAAPQJ50gAQFFlHlya2daSTpE02t13ljRA0kclXSLpW+4+UtLzko6P/uR4Sc9Ht38r+j2Z2bujv3uPpIMkfdfMBpjZAElXSGqR9G5JH4t+FwCAfo1zJACgyPKaFtsoaUMza5Q0SNK/JDVJ+nn083ZJh0XfHxq1Ff38ADOz6Pbr3f1/7v4PSR2S9oy+Otx9sbu/Lun66HcBACgCzpEAgELKPLh096clXSrpnwonzBclLZT0gruvjH7tKUlbR99vLenJ6G9XRr8/tPz2qr9Z2+1vYGafMbMFZrbgueeei//gAACIob+cIzk/AgD6Io9psZspXCXdXtJWkjZSmLKTOXe/2t1Hu/vozTffPI8hAADQrb+cIzk/AgD6Io9psQdK+oe7P+fuKyT9UtIHJG0aTQGSpG0kPR19/7SkbSUp+vlbJHWW3171N2u7HQCA/o5zJACgsPIILv8paW8zGxStCzlA0l8kzZd0RPQ7bZJuir6/OWor+vk8d/fo9o9GlfK2l7SjpPsk3S9px6iy3noKBQ1uzuBxAQAQF+dIAEBhNb75ryTL3e81s59LekDSSkkPSrpa0q2SrjezC6PbfhD9yQ8k/cjMOiQtUzgRyt0fMbOfKpx0V0o60d1XSZKZnSTpNoUqe9Pd/ZGsHh8AAH3FORIAUGQWLnBi9OjRvmDBgryHAQBImZktdPfReY+jKDg/AkD9iHuOzGsrEgAAAABADSG4BAAAAADERnAJAAAAAIiN4BIAAAAAEBvBJQAAAAAgNoJLAAAAAEBsBJcAAAAAgNgILgEAAAAAsRFcAgAAAABiI7gEAAAAAMRGcAkAAAAAiI3gEgAAAAAQG8ElAAAAACA2gksAAAAAQGwElwAAAACA2AguAQAAAACxEVwCAAAAAGIjuAQAAAAAxEZwCQAAAACIjeASAAAAABAbwSUAAAAAIDaCSwAAAABAbASXAAAAAIDYCC4BAAAAALERXAIAAAAAYiO4BAAAAADERnAJAAAAAIiN4BIAAAAAEBvBJQAAAAAgNoJLAAAAAEBsBJcAAAAAgNgILgEAAAAAsRFcAgAAAABiI7gEAAAAAMRGcAkAAAAAiI3gEgAAAAAQG8ElAAAAACA2gksAAAAAQGwElwAAAACA2AguAQAAAACxEVwCAAAAAGIjuAQAAAAAxEZwCQAAAACIjeASAAAAABAbwSUAAAAAIDaCSwAAAABAbASXAAAAAIDYCC4BAAAAALERXAIAAAAAYiO4BAAAAADERnAJAAAAAIiN4BIAAAAAEBvBJQAAAAAgNoJLAAAAAEBsBJcAAAAAgNgILgEAAAAAsRFcAgAAAABiI7gEAAAAAMRGcAkAAAAAiI3gEgAAAAAQG8ElAAAAACA2gksAAAAAQGwElwAAAACA2AguAQAAAACxEVwCAAAAAGIjuAQAAAAAxEZwCQAAAACIjeASAAAAABAbwSUAAAAAIDaCSwAAAABAbASXAAAAAIDYCC4BAAAAALERXAIAAAAAYiO4BAAAAADERnAJAAAAAIiN4BIAAAAAEBvBJQAAAAAgNoJLAAAAAEBsBJcAAAAAgNgILgEAAAAAsRFcAgAAAABiI7gEAAAAAMRGcAkAAAAAiI3gEgAAAAAQWy7BpZltamY/N7O/mdlfzez9ZjbEzOaY2WPRv5tFv2tmNs3MOszsITPbrex+2qLff8zM2spu393MHo7+ZpqZWR6PEwCAdcU5EgBQVHllLr8t6bfu/k5J75X0V0mTJd3u7jtKuj1qS1KLpB2jr89IulKSzGyIpHMl7SVpT0nnlk620e98uuzvDsrgMQEAkATOkQCAQso8uDSzt0gaI+kHkuTur7v7C5IOldQe/Vq7pMOi7w+VdJ0H90ja1My2lDRe0hx3X+buz0uaI+mg6GebuPs97u6Sriu7LwAA+i3OkQCAIssjc7m9pOckXWtmD5rZNWa2kaQt3P1f0e/8W9IW0fdbS3qy7O+fim7r6fan1nA7AAD9HedIAEBh5RFcNkraTdKV7r6rpFe0enqPJCm6muppD8TMPmNmC8xswXPPPZd2dwAAvJl+cY7k/AgA6Is8gsunJD3l7vdG7Z8rnEj/E03XUfTvs9HPn5a0bdnfbxPd1tPt26zh9jdw96vdfbS7j958881jPSgAABLQL86RnB8BAH2ReXDp7v+W9KSZvSO66QBJf5F0s6RSNbs2STdF398s6ZNRRby9Jb0YTQ26TVKzmW0WFSlolnRb9LOXzGzvqALeJ8vuCwCAfotzJACgyBpz6vdkSTPMbD1JiyUdqxDo/tTMjpe0RNJR0e/+RtIHJXVIWh79rtx9mZldIOn+6PfOd/dl0fdfkPRDSRtKmhV9AQBQBJwjAQCFZGHpBkaPHu0LFizIexgAgJSZ2UJ3H533OIqC8yMA1I+458i89rkEAAAAANQQgksAAAAAQGwElwAAAACA2AguAQAAAACxEVwCAAAAAGIjuAQAAAAAxEZwCQAAAACIjeASAAAAABAbwSUAAAAAIDaCSwAAAABAbASXAAAAAIDYCC4BAAAAALERXAIAAAAAYiO4BAAAAADERnAJAAAAAIitsTe/ZGY7SfqSpOHlf+PuTSmNCwCAfo/zIwAAq/UquJT0M0nfk/R9SavSGw4AAIXC+REAgEhvg8uV7n5lqiMBAKB4OD8CABDp7ZrLW8zsC2a2pZkNKX2lOjIAAPo/zo8AAER6m7lsi/79UtltLmlEssMBAKBQOD8CABDpVXDp7tunPRAAAIqG8yMAAKv1GFyaWZO7zzOzw9f0c3f/ZTrDAgCg/+L8CADAG71Z5vL/JM2T9OE1/MwlcfIEANQjzo8AAFTpMbh093Ojf4/NZjgAAPR/nB8BAHij3hb0kZkdLOk9kjYo3ebu56cxKAAAioLzIwAAQa+2IjGz70k6WtLJkkzSkZKGpzguAAD6Pc6PAACs1tt9Lvdx909Ket7dvyrp/ZJ2Sm9YAAAUAudHAAAivQ0uX43+XW5mW0laIWnLdIYEAEBhcH4EACDS2zWXvzazTSX9P0kPKFTCuyatQQEAUBCcHwEAiPQquHT3C6Jvf2Fmv5a0gbu/mN6wAADo/zg/AgCwWq+CyzVtEm1mL0p62N2fTXxUAAAUAOdHAABW6+202OMVihTMj9r7S1ooaXszO9/df5TC2AAA6O84PwIAEOltcNko6V3u/h9JMrMtJF0naS9Jd0ri5AkAqEecHwEAiPS2Wuy2pRNn5NnotmUKlfEAAKhHnB8BAIj0NnN5R1So4GdR+yPRbRtJeiGNgQEAUACcHwEAiPQ2uDxR0uGS9o3a10n6hbu7pLFpDAwAgALg/AgAQKS3W5G4pF9EXwAAQJwfAQAo19s1l29gZlcnORAAAGoB50cAQL3qc3Ap6arERgEAQO3g/AgAqEt9Di7dfWGSAwEAoBZwfgQA1Kse11ya2S2SfG0/d/dDEh8RAAD9HOdHAADe6M0K+lyaySgAACgWzo8AAFTpMbh0999lNRAAAIqC8yMAAG/Uq61IzGxHSV+X9G5JG5Rud/cRKY0LAIB+j/MjAACr9bagz7WSrpS0UmFT6Osk/TitQQEAUBCcHwEAiPQ2uNzQ3W+XZO6+xN3Pk3RwesMCAKAQOD8CABDp1bRYSf8zswZJj5nZSZKeljQ4vWEBAFAInB8BAIj0NnN5qqRBkk6RtLukj0v6ZFqDAgCgIDg/AgAQ6W1wuZ27v+zuT7n7se7+EUlvT3NgAAAUAOdHAAAivQ0uz+rlbQAA1BPOjwAARHpcc2lmLZI+KGlrM5tW9qNNFCrjAQBQdzg/AgDwRm9W0OcZSQskHSJpYdnt/5X0xbQGBQBAP8f5EQCAKj0Gl+7+Z0l/NrMZ7s6VWAAAxPkRAIA1ebNpsT9196MkPWhmXv1zdx+V2sgAAOinOD8CAPBGbzYt9tTo3w+lPRAAAAqE8yMAAFV6rBbr7v+K/l0i6X+S3itplKT/RbcBAFB3OD8CAPBGvdqKxMxOkHSfpMMlHSHpHjM7Ls2BAQDQ33F+BABgtTebFlvyJUm7ununJJnZUEl/kDQ9rYEBAFAAnB8BAIj0KnMpqVOhvHrJf6PbAACoZ5wfAQCI9DZz2SHpXjO7SZJLOlTSQ2Z2uiS5+zdTGh8AAP0Z50cAACK9DS4fj75Kbor+3TjZ4QAAUCicHwEAiPQquHT3r6Y9EAAAiobzIwAAq/UquDSzzSVNkvQeSRuUbnf3ppTGBQBAv8f5EQCA1Xpb0GeGpL9J2l7SVyU9Ien+lMYEAEBRcH4EACDS2+ByqLv/QNIKd/+dux8niauyAIB6x/kRAIBIbwv6rIj+/ZeZHSzpGUlD0hkSAACFwfkRAIBIb4PLC83sLZLOkHS5pE0knZbWoAAAKAjOjwAARHo7LfZISebui9x9rKRxkiakNywAAAqB8yMAAJHeBpej3P2FUsPdl0naNZURAQBQHJwfAQCI9Da4bDCzzUoNMxui3k+pBQCgVnF+BAAg0tsT4Dck/dHMfha1j5T0tXSGBABAYXB+BAAg0qvg0t2vM7MFWl1e/XB3/0t6wwIAoP/j/AgAwGq9nroTnSw5YQIAUIbzIwAAQW/XXAIAAAAAsFYElwAAAACA2AguAQAAAACxEVwCAAAAAGIjuAQAAAAAxEZwCQC90NHRoQkTJmjx4sV5DwUAUMOWLl2qk08+WZ2dnXkPJRf1/viLjuASAHph6tSpWr58uS6++OK8hwIAqGHt7e166KGH1N7envdQclHvj7/oCC4B4E10dHRoyZIlkqQlS5aQvQQApGLp0qWaNWuW3F2zZs2qu+xdvT/+WkBwCQBvYurUqRVtspcAgDS0t7fL3SVJXV1ddZe9q/fHXwsILgHgTZSylmtrAwCQhDlz5mjFihWSpBUrVmj27Nk5jyhb9f74awHBJQC8ieHDh/fYBgAgCePGjdPAgQMlSQMHDlRzc3POI8pWvT/+WkBwCQBvYtKkSRXtyZMn5zQSAEAta2trk5lJkhoaGtTW1pbziLJV74+/FuQWXJrZADN70Mx+HbW3N7N7zazDzG4ws/Wi29eP2h3Rz7cru4+zotv/bmbjy24/KLqtw8z4FAgglpEjR3ZnK4cPH64RI0bkPCLUOs6RQH0aNmyYWlpaZGZqaWnR0KFD8x5Spur98deCPDOXp0r6a1n7EknfcveRkp6XdHx0+/GSno9u/1b0ezKzd0v6qKT3SDpI0nejk/EASVdIapH0bkkfi34XAPps0qRJGjRoEFlLZIVzJFCn2traNGrUqLrN2tX74y+6XIJLM9tG0sGSronaJqlJ0s+jX2mXdFj0/aFRW9HPD4h+/1BJ17v7/9z9H5I6JO0ZfXW4+2J3f13S9dHvAkCfjRw5UjfeeCNZS6SOcyRQ34YNG6bLL7+8brN29f74iy6vzOVlkiZJ6oraQyW94O4ro/ZTkraOvt9a0pOSFP38xej3u2+v+pu13f4GZvYZM1tgZguee+65mA8JAIBEXKacz5GcHwEAfZF5cGlmH5L0rLsvzLrvau5+tbuPdvfRm2++ed7DAQDUuf5yjuT8CADoi8Yc+vyApEPM7IOSNpC0iaRvS9rUzBqjK6/bSHo6+v2nJW0r6Skza5T0FkmdZbeXlP/N2m4HAKA/4xwJACiszDOX7n6Wu2/j7tspFBuY5+7HSJov6Yjo19ok3RR9f3PUVvTzee7u0e0fjSrlbS9pR0n3Sbpf0o5RZb31oj5uzuChAQAQC+dIAECR5ZG5XJszJV1vZhdKelDSD6LbfyDpR2bWIWmZwolQ7v6Imf1U0l8krZR0oruvkiQzO0nSbZIGSJru7o9k+kgAAEgW50gAQL9n4QInRo8e7QsWLMh7GACAlJnZQncfnfc4ioLzIwDUj7jnyDz3uQQAAAAA1AiCSwAAAABAbASXAAAAAIDYCC4BAAAAALERXAIAAAAAYiO4BAAAAADERnAJAAAAAIiN4BIAAAAAEBvBJQAAAAAgNoJLAAAAAEBsBJcAAAAAgNgILgEAAAAAsRFcAgAAAABiI7gEAAAAAMRGcAkAAAAAiI3gEgAAAAAQG8ElAAAAACA2gksAAAAAQGwEl33U0dGhCRMmaPHixan10dnZqYkTJ2rZsmWp9VFL+P8CeofXCopi6dKlOvnkk9XZ2Zn3UJCx++67T/vvv78WLlyY91Ayx/MeRUZw2UdTp07V8uXLdfHFF6fWx8yZM7Vo0SLNmDEjtT5qCf9fQO/wWkFRtLe366GHHlJ7e3veQ0HGzjvvPHV1demcc87JeyiZ43mPIiO47IOOjg4tWbJEkrRkyZJUspednZ2aPXu23F2zZ88mw/Am+P8CeofXCopi6dKlmjVrltxds2bNIotTR+677z69/PLLkqSXX365rrKXPO9RdASXfTB16tSKdhrZy5kzZ6qrq0uS1NXVRYbhTfD/BfQOrxUURXt7u9xdUniuksWpH+edd15Fu56ylzzvUXQEl31QylqurZ2EefPmaeXKlZKklStXat68eYn3UUv4/wJ6h9cKimLOnDlasWKFJGnFihWaPXt2ziNCVkpZy7W1axnPexQdwWUfDB8+vMd2EpqamtTY2ChJamxsVFNTU+J91BL+v4De4bWCohg3bpwGDhwoSRo4cKCam5tzHhGyMnjw4B7btYznPYqO4LIPJk2aVNGePHly4n20traqoSEcnoaGBh1zzDGJ91FL+P8CeofXCoqira1NZiYpPFfb2tpyHhGyUj0t9oILLshnIDngeY+iI7jsg5EjR3ZnK4cPH64RI0Yk3sfQoUPV3NwsM1Nzc7OGDBmSeB+1hP8voHd4raAohg0bppaWFpmZWlpaNHTo0LyHhIzsueee3dnKwYMHa/fdd895RNnheY+iI7jso0mTJmnQoEGpZC1LWltbtfPOO5NZ6CX+v4De4bWComhra9OoUaPI3tSh8847Tw0NDXWVtSzheY8is1JFqno3evRoX7BgQd7DAACkzMwWuvvovMdRFJwfAaB+xD1HkrkEAAAAAMRGcAkAAAAAiI3gEgAAAAAQG8ElAAAAACA2gksAAAAAQGwElwAAAACA2AguAQAAAACxEVwCAAAAAGIjuAQAAAAAxEZwCQAAAACIjeASAAAAABAbwSUAAAAAIDaCSwAAAABAbASXAAAAAIDYCC4BAAAAALERXAIAAAAAYiO4BAAAAADERnAJAAAAAIiN4BIAAAAAEBvBZR91dnZq4sSJWrZsWWp9nHXWWRo/frzOPvvs1PrIyvTp0zV+/Hi1t7en1kcWxyQrCxcuVEtLix588MG8h1II8+fP1/jx43XnnXcWug9J6ujo0IQJE7R48eJU+wGK4MADD9SYMWM0bty4vIeSublz52rMmDGaP39+3kPJxdKlS3XyySers7Mz76Fkrp4fO4qP4LKPZs6cqUWLFmnGjBmp9fHAAw9Iku6///7U+sjKDTfcICn8v6Uli2OSlYsuukhdXV268MIL8x5KIVx66aWSpEsuuaTQfUjS1KlTtXz5cl188cWp9gMUweuvvy5J+t///pfzSLJ30UUXSZIuuOCCnEeSj/b2dj300EOpXpTur+r5saP4CC77oLOzU7Nnz5a7a/bs2alkys4666yKdpGzl9OnT69op/FmmcUxycrChQv18ssvS5JefvllspdvYv78+Vq5cqUkaeXKlalkFrPoQwpZyyVLlkiSlixZQvYSde3AAw+saNdT9nLu3LkV7zn1lr1cunSpZs2aJXfXrFmz6iqDV8+PHbWB4LIPZs6cqa6uLklSV1dXKpmyUtaypMjZy1LWsiSN7GUWxyQrpavVJWQve1bKKJakkVnMog8pZC3Lkb1EPStlLUvqKXtZfR6ot+xle3u73F1SOKfXUwavnh87agPBZR/Mmzev4orivHnzch4RaumYlLKWa2ujUum4r61dlD4kdWct19YGUB+yes/pr+bMmaMVK1ZIklasWKHZs2fnPKLs1PNjR20guOyDpqYmNTY2SpIaGxvV1NSU84hQS8dk8ODBPbZRqXTc19YuSh+SNHz48B7bAOpDVu85/dW4ceM0cOBASdLAgQPV3Nyc84iyU8+PHbWB4LIPWltb1dAQ/usaGhp0zDHHJN7HbrvtVtHeY489Eu8jK0cffXRFu7W1NfE+sjgmWZkyZUpFu8jrbbMwceLEivaZZ55ZyD4kadKkSRXtyZMnp9IPUATrrbdeRXv99dfPaSTZqz4PnHPOOTmNJB9tbW0yM0nhnN7W1pbziLJTz48dtYHgsg+GDh2q5uZmmZmam5s1ZMiQxPv4+te/XtEu8rq74447rqKdxhtlFsckK7vvvnt3tnLw4MHaddddcx5R/zZ27NiKrPWYMWMK2YckjRw5sjtbOXz4cI0YMSKVfoAimDt3bkV7zpw5OY0kewceeGDFe87YsWNzHlG2hg0bppaWFpmZWlpaNHTo0LyHlJl6fuyoDQSXfdTa2qqdd9451QxZKXtZ5KxlSSl7mUbWsiSLY5KVKVOmqKGhgaxlL5Uyi2llFLPqQwrZy0GDBpG1BLQ6e1lPWcuSUvay3rKWJW1tbRo1alRdZu7q+bGj+KxUkarejR492hcsWJD3MAAAKTOzhe4+Ou9xFAXnRwCoH3HPkWQuAQAAAACxEVwCAAAAAGIjuAQAAAAAxEZw2UcdHR2aMGGCFi9eXOg+sjJ9+nSNHz9e7e3teQ8lls7OTk2cOFHLli3LeygoU0uvFawbXpO1be7cuRozZozmz5+f91AyN3nyZI0ZM4bCbgAKheCyj6ZOnarly5fr4osvLnQfWbnhhhskSTNnzsx5JPHMnDlTixYt0owZM/IeCsrU0msF64bXZG276KKLJEkXXHBBziPJ3h/+8AdJ0p133pnzSACg9wgu+6Cjo0NLliyRJC1ZsiSVbEkWfWRl+vTpFe2iZi87Ozs1e/Zsubtmz55NpqSfqKXXCtYNr8naNnfuXK1cuVKStHLlyrrKXlZvRUT2EkBREFz2wdSpUyvaaWRLsugjK6WsZUlRs5czZ85UV1eXJKmrq4tMST9RS68VrBtek7WtlLUsqafsZSlrWUL2EkBREFz2QSlLsrZ2UfrAupk3b17FVfR58+blPCJIvFbqGa/J2lY6tmtrAwD6H4LLPhg+fHiP7aL0gXXT1NSkxsZGSVJjY6OamppyHhEkXiv1jNdkbSsd27W1AQD9D8FlH0yaNKmiXb02oih9ZOXoo4+uaLe2tuY0knhaW1vV0BBeMg0NDTrmmGNyHhGk2nqtYN3wmqxtU6ZMqWifc845OY0ke/vss09Fe8yYMTmNBADWDcFlH4wcObI7OzJ8+HCNGDGikH1k5bjjjqtot7W15TSSeIYOHarm5maZmZqbmzVkyJC8hwTV1msF64bXZG078MADKzLTY8eOzXlE2aleO37hhRfmNBIAWDcEl300adIkDRo0KNUsSRZ9ZKWUvSxq1rKktbVVO++8MxmSfqaWXitYN7wma1spe1lPWcuSUvaSrCWAIjF3z3sM/cLo0aN9wYIFeQ8DAJAyM1vo7qPzHkdRcH4EgPoR9xxJ5hIAAAAAEBvBJQAAAAAgNoJLAAAAAEBsBJcAAAAAgNgILgEAAAAAsRFcAkAvdHZ2auLEiVq2bFneQwEAADVo6dKlOvnkk9XZ2Zn3UPqM4BIAemHmzJlatGiRZsyYkfdQAABADWpvb9dDDz2k9vb2vIfSZwSXAPAmOjs7NXv2bLm7Zs+eTfYSAAAkaunSpZo1a5bcXbNmzSps9pLgEgDexMyZM9XV1SVJ6urqInsJAAAS1d7eLneXFD5rFDV7SXAJAG9i3rx5WrlypSRp5cqVmjdvXs4jAgAAtWTOnDlasWKFJGnFihWaPXt2ziPqG4JLAHgTTU1NamxslCQ1Njaqqakp5xEBAIBaMm7cOA0cOFCSNHDgQDU3N+c8or4huASAN9Ha2qqGhvB22dDQoGOOOSbnEQEAgFrS1tYmM5MUPmu0tbXlPKK+IbgEgDcxdOhQNTc3y8zU3NysIUOG5D0kAABQQ4YNG6aWlhaZmVpaWjR06NC8h9QnjXkPAACKoLW1VUuWLCFrCQAAUtHW1qYnnniisFlLicxlny1cuFAtLS168MEHU+vj3HPP1fjx43X++een1kdWJk6cqPHjx+vMM8/MeyixZHHcse5uueUWjR8/Xr/5zW9S6+P555/X448/rhdeeCG1PgAAqHf777+/xowZo7Fjx+Y9lMzddddd+vOf/6y7774776H0WebBpZlta2bzzewvZvaImZ0a3T7EzOaY2WPRv5tFt5uZTTOzDjN7yMx2K7uvtuj3HzOztrLbdzezh6O/mWalCcwJuuiii9TV1aULL7ww6bvuds8990hSoZ9gJQ8//LAk6U9/+lO+A4kpi+OOdXfFFVdIkqZNm5ZaH1OnTtXy5ct18cUXp9YHUCvnSADoq9LWX6tWrcp5JNm77LLLJEnf+MY38h1IDHlkLldKOsPd3y1pb0knmtm7JU2WdLu77yjp9qgtSS2Sdoy+PiPpSimcaCWdK2kvSXtKOrd0so1+59Nlf3dQkg9g4cKFevnllyVJL7/8cipZrHPPPbeiXeTs5cSJEyvaRc1eZnHcse5uueWW7n2h3D2V7GVHR4eWLFkiSVqyZIkWL16ceB9ApPDnSADoq/3337+iXU/ZyxtvvLHi88zNN9+c84j6JvPg0t3/5e4PRN//V9JfJW0t6VBJpd1C2yUdFn1/qKTrPLhH0qZmtqWk8ZLmuPsyd39e0hxJB0U/28Td7/FwhK4ru69EXHTRRRXtNLJYpaxlSZGzl6WsZUlRs5dZHHesu1LWsiSN7OXUqVMr2mQvkZZaOEcCQF+VspYl9ZS9LGUtS4qavcx1zaWZbSdpV0n3StrC3f8V/ejfkraIvt9a0pNlf/ZUdFtPtz+1htvX1P9nzGyBmS147rnnej3uUvZqbW3UJo57/1S6yre2dhJKWcu1tYE05HmO7Ov5EQDQN1l8nslCbsGlmQ2W9AtJp7n7S+U/i66mpv4/6u5Xu/todx+9+eab9/rvBg8e3GMbtYnj3j9VLxdLY/nY8OHDe2wDScv7HNnX8yMAoG+y+DyThVyCSzMbqHDSnOHuv4xu/k80XUfRv89Gtz8taduyP98muq2n27dZw+2JmTJlSkX77LPPTvLuJUl77713RfsDH/hA4n1kZZdddqlov+9978tnIDFlcdyx7k488cSK9imnnJJ4H5MmTapoT548eS2/CcRX9HMkAPRVQ0NlaDJgwICcRpK90047raJ9xhln5DOQmPKoFmuSfiDpr+7+zbIf3SypVM2uTdJNZbd/MqqIt7ekF6OpQbdJajazzaIiBc2Sbot+9pKZ7R319cmy+0rE7rvv3p21Gjx4sHbdddck716S9NWvfrWi/ZWvfCXxPrJy6aWXVrQvueSSnEYSTxbHHevuwx/+cEX7gx/8YOJ9jBw5sjtbOXz4cI0YMSLxPgCpNs6RSXr00UfV0tKijo6OvIcCIAN33HFHRXv+/Pn5DCQHEyZM6M5WmpkOOeSQnEfUN3lkLj8g6ROSmszsT9HXByVdLGmcmT0m6cCoLUm/kbRYUoek70v6giS5+zJJF0i6P/o6P7pN0e9cE/3N45JmJf0gpkyZooaGhlSzV6XsZZGzliVDhgyRJA0dOjTnkcSTxXHHutt5550lSaNGjUqtj0mTJmnQoEFkLZG2mjhHJuXCCy/UK6+8UuiK6QDWTSl7WU9Zy5JS9rKoWUtJsqIuFk3a6NGjfcGCBXkPoyZ1dnbqU5/6lF5//XWtt956am9v7w42gbh4fmFdmdlCdx+d9ziKIq/z46OPPqoTTjihuz19+nSNHDky83EAQD2Je47MtVos6sPMmTO7S0t3dXVpxowZOY8ItYTnF1Cbqrd7InsJAP0fwSVSN2/ePK1cuVKStHLlSs2bNy/nEaGW8PwCatMTTzzRYxsA0P8QXCJ1TU1NamxslCQ1Njaqqakp5xGhlvD8AmrTdttt12MbAND/EFwida2trd2LsxsaGnTMMcfkPCLUEp5fQG2qLpxW5KrpAFAvCC6RuqFDh6q5uVlmpubmZoqtIFE8v4DatNNOO3VnK7fbbjuK+QBAARBcIhOtra3aeeedySohFTy/gNp09tlna6ONNiJrCQAFwVYkEbYiAYD6wFYk64bzIwDUD7YiAQAAAADkjuASAAAAABAbwSUAAAAAIDaCy36so6NDEyZM0OLFi/MeCiJZHZPOzk5NnDhRy5YtK3QfABDHjTfeqDFjxujmm2/OeyhAZpYuXaqTTz5ZnZ2deQ8FWGcEl/3Y1KlTtXz5cl188cV5DwWRrI7JzJkztWjRIs2YMaPQfQBAHJdddpkk6Rvf+Ea+AwEy1N7eroceekjt7e15DwVYZwSX/VRHR4eWLFkiSVqyZAnZy34gq2PS2dmp2bNny901e/bsVDKLWfQBAHHceOONKlW0d3eyl6gLS5cu1axZs+TumjVrFtlLFA7BZR/Nnz9f48eP15133pnK/U+dOrWinVamLKupkePHj+/+KqqsjsnMmTP1+uuvS5Jef/31VDKLWfQh1dbzK+3XfMn111+v8ePH62c/+1lqfUyfPl3jx4/nqjj6tVLWsqTespdMCa5P7e3t6urqkiStWrWqLt+nx4wZ0/1Vb2rhsRNc9tGll14qSbrkkktSuf9Shmxt7aQwNbL3sjom8+bN67FdlD6k2np+pf2aL7n22mslSddcc01qfdxwww2SwvEB+qvqfbjrbV9upgTXpzlz5mjlypWSpJUrV2r27Nk5jwhYNwSXfTB//vyKF37amYy0ZDU1sjqbVNTs5aabblrR3myzzVLpZ9WqVT22k7DRRhtVtAcPHpx4H7X0/MrqNX/99ddXtNPIXk6fPr2iXY9XxVEMZtZju5YxJbh+7bfffhXtImew+qL68dbT46+Vx05w2QelDEZJ2pmMtMycObN76kVXV1dNZJfS9MILL1S0n3/++VT6+d///tdjOwnPPfdcRfvZZ59NvI9aen5l9ZovZS1L0shelrKWJWQv0V+ddtppFe0zzjgjn4HkoN6nBAMoLoLLPihlMNbWLop58+ZVZGPSmhqJ+lRLz69aec0DRTJhwoSK9iGHHJLTSLJX71OCJem+++7T/vvvr4ULF+Y9lEzdddddFe2izo5D/SK47IPGxsYe20XR1NTUPc3IzNTU1JTziPq3ep6i1RdNTU3dr43GxsZCP79q5TUPoBg430jnnHOOurq6NGXKlLyHkqlx48ZpwIABkqQBAwaoubk55xEB64bgsg8mTpxY0T7zzDNzGkk8LS0tFWs6Dj744JxH1L99+MMfrmgfdthhqfSz4YYbVrSr10cmYZdddqlov+9970u8j9bWVjU0hLeYhoYGHXPMMYn3kZWsXvPVHyJaWloS7+Poo4+uaLe2tibeB5CE6szlEUcckdNIslf92I888sicRpKP++67T6+++qok6dVXX62r7GVbW1vFZ7O2tracRwSsG4LLPhg1alRFe+edd85pJPHMmjWrInN566235jyieNLe9qK6YtusWbNS6ad0Qi155ZVXEu/jpZdeqminsX506NCham5ulpmpublZQ4YMSbwPSTrppJMq2qeeemrifYwdO7YiC5vWIvvq6VB33HFH4n0cd9xxFW0+uKC/qt7fL4214f1V9fnllltuyWkk+TjnnHMq2vWWvaxn1dOA62lacK08doLLPqgugFHUQiXz5s2ruDpW5DVxUvrbXrz22ms9toskq21VWltbtfPOO6eatbziiisq2tOmTUuln1L2Ms2ZCtUXFqrbSdlhhx0kSTvuuGMq9w8gnqzeC/qren787e3tFbN+qOiNoiG47IPbb7+9x3ZR1NKauKy2vagVw4cP77GdlKFDh+rSSy9NLWspZVf4YuzYsbrtttsKWxq8pLOzU08++aSkcFGB1woA9B/scxkydqWvelMLj53gsg/e+ta39tguilpaE1dL216Ujsna2kmYNGlSRXvy5MmJ94F1V/1essUWWyTeRy29VoBaVf3af9vb3pbTSPJRz49/3LhxGjhwoCRp4MCBFPRB4RBc9kH1uo+irgPJak1cFmpp24vSB/+1tZMwcuTI7mzl8OHDNWLEiMT7wLo799xzK9rnnXde4n3U0msFqFVf+9rXKtoXXXRRTiPJRz0//ra2tu56GA0NDayLR+EQXPbBAQccUFEI54ADDsh5RH2XxZq4LGQxxXfw4ME9tovWz6RJkzRo0KDCZy1raZuQkSNHdmcvt9hii1SC/lqaDg/Uqp122qk7e/e2t71NI0eOzHlE2arnxz9s2DC1tLTIzNTS0qKhQ4fmPSRgnRBc9kFra2v3h7OBAwemEphVbxZdXZY8KVmsiTv22GMr2ieccELifWQxxbe6Wt3ZZ5+deB9Z9jNy5EjdeOONhc9a1srWQCXnnnuuBg0alErWUqqt6fCobeuvv35Fe4MNNshpJPn42te+po022qiusnbl6vnxt7W1adSoUWQtUUgEl30wdOhQjR8/PtXppCeeeGJF+3Of+1zifWTlox/9aEU7jf26spjiu/vuu3dnEQcPHqxdd9018T6y7KdWZLVNSFbSDvpraTo8atucOXMq2vVW2GSnnXbSrFmz6iprV66eH/+wYcN0+eWXk7VEIRFc9lEW00lL2cu0spZZKmUv08halmRxTKZMmaKGhobUsolZ91MrstgmpJbUynR41L5S9rLespYAUFSWVtn+ohk9erQvWLAg72HUrM7OTn3961/XlClTyJT0Av9fQHrMbKG7j857HEWR5/nx0Ucf1amnnqrLL7+8LjNYAJC1uOdIMpfIxMyZM7Vo0SK2Pegl/r8AQLrwwgv1yiuv6Pzzz897KACAXiC4ROo6Ozs1e/Zsubtmz57Npu1vgv8vAAhZyyeeeEKS9MQTT6ijoyPfAQEA3hTBJVLHpu3rhv8vAAhZy3JkLwGg/yO4ROrYtH3d8P8FAOrOWq6tDQDofwgu+2jhwoVqaWnRgw8+mFof8+fP1/jx43XnnXem1kcWmpqaKvbVK/Km7Z2dnZo4cWKqU1Wz+v/q6OjQhAkTtHjx4lTuP0tZvB6zOPYAVttuu+16bAOoTa2trRozZow++clP5j2UzC1dulQnn3yyOjs78x5KnxFc9tFFF12krq6uN0zbSdLFF18sKWwknJYsPjC3trZWTPNMa/uDLB7LlVdeqYcffljf/e53U+sjq/+viy66SMuXL0/1+ZWV8847T11dXfrKV76SWh9ZHHsAq1VvxZTm67s/evTRR9XS0lK3a03nzp2rMWPGaP78+XkPJXP1fuyfeuopSfU5W6G9vV0PPfSQ2tvb8x5KnxFc9sHChQv18ssvS5JefvnlVLIl1W+maWUvs6hK+vzzz1e0X3jhhVT6SfuxdHZ26q677pIk3XXXXakFsVn8f3V0dOjpp5+WFN7Ei5y9XLhwoV5//XVJ0uuvv57K6zGrYw9gtZ122qmiXW9bkdR7pdyLLrpIknTBBRfkPJLs1fOxb21trWjXU/Zy6dKlmjVrltxds2bNKmz2kuCyD0pveCVpZC9LWcuSNLJLWVUlPeWUUyraJ510UuJ9ZPFYrrzyyop2Whms6hNpGieX6udwkbOX5513XkU7jexGVscewGpjxozpsV3L6r1S7ty5cytqD9RT9rLej30pa1lST9nL9vZ2ubukMHOtqNlLgss+KGUt19Yuiqyqkq5atarHdhKyeCylzNXa2kn597//XdH+17/+lXgfpaxlSfWbeZGUspZraychq2MPABKVcqsvgNZT9rLej309mzNnjlasWCFJWrFihWbPnp3ziPqG4LIPBg8e3GO7KGqpKmktPZYsmFmPbQBAfuq9Um7pfL62di2r92Nfz8aNG6eBAwdKkgYOHKjm5uacR9Q3BJd9MGXKlIp2ddGBomhqatKAAQMkSQMGDCh0FdempiY1NjZKkhobG1N5LFtvvXVFe5tttkm8D0nacsste2wnYd99961o77fffon3IdVOhdWsjj0ASFTKLZ3P19auZfV+7KvPr/X0+Nva2rq/N7OKdpEQXPbB7rvvXtHeddddE++junBBdWGDJLS2tnbP7Xb31KqSVr8xjBgxIvE+WltbK7bvSOOxnHjiiRXtNNaOStLJJ59c0T711FMT7+Pzn/98j+2kZFEwqvo4pPH/VX1B6ctf/nLifQBAybhx4yraLS0tOY0kH9Xvueecc05OI8levVdJnjlzZkX7uuuuy2kk2Rs2bFj3xeytttpKQ4cOzXlEfUNw2Qe33HJLRfs3v/lN4n2UMoolRZ62WB0opxFcDh06VM3NzTIzNTc3a8iQIYn3UT3Vdu7cuYn3IUk33XRTRfvGG29MpZ/yYDwNWRWM2mqrrSraaWR6R44c2f2Gv80226TyHAZQqbpKetH3fF4X1157bUX7+9//fk4jyceBBx5YMRtp7NixOY8oOzvttFP3Rfntttuu7qokH3rooRXtCRMm5DSS7C1dulTPPPOMJOmZZ56hWmw9ueKKKyra06ZNS7yPv//97z22kzBz5szuoNXMUssuVVd5S6vqW0tLizbccEMdfPDBqdx/Vo/j3nvv7bGdhCyOfVYFo7Ko3ixJn/jEJyQp9WkqHR0dmjBhQqG3hwEQTz2vOSw59thjJUmf/vSncx5J9s4++2xttNFGdZe1lN64HVtRA6y+KK8W6+5Ui60npQO/tnZRzJs3r7ty66pVq1IrgpNV8ZhZs2bp1Vdf1a233prK/ddSEZwsjn1WRZayqt78k5/8RJL04x//OJX7L5k6daqWL1/+hu2IANSPel5zWDJnzhxJ4dxeb3baaSfNmjWr7rKW9Y5qsSi8ffbZp8d2UtZbb72K9vrrr594H1lMwdxhhx0q2mm96VdPia5uJyGLY59FkSVJ3ZXV1tZOQkdHh5YsWSJJWrJkSWpZxaz6AYqgnve53HPPPSvaaZ2f+6t63+sR9YlqsXWsOjhKI1jKQ1qZuOXLl1e0X3nllcT7yGIK5qOPPlrRTmOqspTNvqDV0jj2WRRZktR9lW9t7SRMnTq1op1WVjGrfgD0b3/4wx8q2vW03lRir8d6ttlmm1W0i1rUpi/a2tq6P481NDRQLbae/O9//+uxXRTVJ6+77747p5HEl8UUzFqZDi1lc+yzKLKUlVI2cW3tovUDAP1Zve/1uHTpUp188sl1td6wJKuihv3RsGHD1NLSIjNTS0tLYQNrgss+GDx4cI/toqieplj0fS57aqNSVv9fO++8s9xd733ve1O5/6wMHz68x3bR+pk+fbrGjx9f2GIBAGpbve/1eNVVV+nPf/6zrrrqqryHgozddNNNcnf96le/ynsofUZw2QfV+y9V70mUhN12262ivcceeyTeR2tra0U7rWmL1Rvivv3tb0+8j+o9wNKoGLvzzjtXtEeNGpV4H5J09NFHV7Srj1MSsjr2pUrK3/rWt1K5f2l1RcGSE044IfE+Jk2aVNGePHly4n1k2c8NN9wg6Y37iQHoHw4//PCK9lFHHZXTSPJRz3s9Ll26tLuY0ezZs+sye4liI7jsg8cee6yincZC8wceeKCiff/99yfex0MPPVTRXrRoUeJ9SNJTTz1V0f7nP/+ZeB/V28FcdtllifdR/f9T/f+XlNIH/5I0AoDrr7++ov3Tn/408T4WLlzYvd52+fLlevDBBxPvQ3rjfnDXXHNN4n08+eSTFe3q53RS/vrXv1a0//a3vyXex/Tp0yvaZC/RX2VR3Ky/ql5r//rrr+c0EmTtqquuqqghUW/Zy3ou5FUrj53gsg+y+DCbhUsvvbSifckll+Q0kviy2Be0ltx8880V7TTWNNRSQYasXivf+c53Ktrf/va3E+8ji4sXAOKpXndW5ClyfVFL5491NXfu3Ip2KYsJFAXBZR1jk2akqbpKcHW7SHitANnbaqutemyjdtV7QR+gyAguAQBAv7N06dIe26hdpT2S19auZVxUQdERXAIAgH6ntO6spMjbP2Hd1PNsES6qoOgILgGkorQR8NraANCT6j2kX3vttZxGAmSntD+0FM6b48ePz3lEwLohuASQik996lMV7eOPPz6fgRTIDjvsUNHecccdE++DoB8A+q+2tjYNHDhQkjRw4EC1tbXlPCJk5a1vfWtFe8stt8xpJPEQXKImDB48uMc2svfcc89VtP/973+n0k8Wxz6r9T//+te/KtpPP/104n3U8/YOANDfDRs2TC0tLTIzffCDH9TQoUPzHhIy8vOf/7yiXV3dvSgILuvYoEGDemwnpXQFrmS99dZLvI8pU6ZUtKs3YC6Svfbaq6K99957J95HFtmrefPm9dhOShbHPqv1P01NTWpoCG/LDQ0NampqSryP/fffv6I9duzYxPsAgDhGjRpV0X7ve9+b00jy0dbWplGjRpG1rEOl7GVRs5YSwWWfbL311hXtbbbZJvE+svjwf8opp1S0v/jFLybehyR99atfrWinsV/V7rvv3p1Namxs1K677pp4H1lNJzz11FN7bCdh3333rWjvt99+iffR1NRUcUzSCJSkcOzLpXHshw8f3mM7Ka2trRX/Z8ccc0zifRx33HEVAexxxx2XeB8A4hk2bFhFu3q6XK0777zzemzXumHDhunyyy8na1mHfv7zn+vOO+8sbNZSIrjskxNPPLGifdJJJyXex5577lnRrs5mJWHBggUV7XvvvTfxPiTpnnvuSb2fzs5OrVq1SpK0atUqLVu2LPE+hgwZUtEu8pv+5z//+R7bSWhtba04JmkESpK0cOHCivaDDz6YeB+TJk2qaE+ePDnxPqTwnNp2220lSdtuu+0bnnNJ9bHHHntICu8zafQBJKE6oNpiiy1yGkn2Xn755Yr2Sy+9lNNI8jFs2DBtt912kqQRI0YU+nyLdfOud72ror3LLrvkNJJ8TJgwQWPGjNERRxyR91D6jOCyD/7whz9UtH//+98n3sfGG2/cYzsJ8+fP77GdlJtvvrmifeONNybex8yZM7vL1Lu7ZsyYkXgfnZ2dFe20yoPPnDmzop3GY6k+UacVxJQfk7SCmIsuuqiifeGFFybex8iRI7vXJg4YMEAjRoxIvI+Sxx9/vOLfNCxZsqTiX6A/yuo9tz+qroxbj5Vy//Of/0h641p01La//e1vFe1FixblNJJ8lN73nn322ZxH0ncEl30we/bsHttJmDt3bkV7zpw5ifdRyiqtrV0k1f8/afx/Va8VTWPtqCT9+te/7rGdhLPOOquincY6xVtuuaWi/Zvf/CbxPqQ3XuGvbieho6OjIgu7ePHixPuQpOnTp1e029vbE++jo6Oju7jSv/71r9QeCxAXlY3r13333adXX31VkvTqq6++YYZKrVu6dKlOPvnkN1xgqQfV+9nW0/62EyZMqGgXNXtJcNkHr7/+eo9tZG/FihU9tpNQS8f9gQceqGjff//9ifdxxRVXVLSnTZuWeB9Zqc6Ofu1rX0uln+o1FtVZ7CRk9Viy0tnZqYkTJ6YyFR75yqqQFvqfr3zlKxXtL3/5yzmNJB/Tpk3Tn//850KfN7Huqi8mFDV7SXCJmtDV1dVjG9mrpauP1VuCPPXUUzmNJL5aeixSCMAXLVqUyvRxAPlYvnx5j+1atnTpUt1xxx2SwnKlesxeotgILgEAhdTZ2anZs2fL3TV79myylwAKrzpbSfYSRUNwCQAopJkzZ3bPUujq6iJ7CaDwSlnLkrSKLQJpIbgEABTSvHnzutfhrVy5UvPmzct5RAAA1DeCSwCoIwMHDuyxXSRNTU1qbGyUJDU2NqqpqSnnEQHJ2HLLLSvaW2+9dU4jQdZK72lrawP9HcElANSRLCorZ6W1tbV7ewoz0zHHHJPziIBkVO/tWF2IC7WLKskoOoJLAEAhDR06VG9961slSVtssYWGDBmS84gAIJ7Se9ra2kB/R3AJACikzs5OPfPMM5KkZ555hmqxAArvpZde6rEN9HcElwCAQpo+fXr3/qldXV36wQ9+kPOIACCe1157rcc20N8RXAIACqm6RD8l+wEAyBfBJQCgkErFfNbWBgAA2SK4BAAU0v7771/RHjt2bD4DAQAAkgguAaCurL/++j22i6R6X8sDDjggp5EAAACJ4BIA6sr//ve/HttFctVVV1W0r7zyypxGAgAAJIJLAEBBLVmypMc2AABFUSt1BAguAaCObLTRRj22i2T48OE9tgEAKIr/+7//q2hX1xUoCoLLOjZs2LCK9uabb57TSOIbMGBARbuxsTGnkRTDpptuWtHebLPNEu9jhx12qGjvuOOOifdRa7I4LieffHJF+7TTTku8j6xMmjSpoj158uScRgIAydhiiy0q2m9729tyGgmy9vGPf7yi/YlPfCKnkcRDcFnHpk2b1mO7SFatWlXRXrlyZU4jKYaXXnqpov3iiy8m3sfpp5/eYxtv9MILL1S0n3/++cT7WLBgQUX73nvvTbyPrFQH39XBOYqt+qJhdRuoRYccckhFe8KECTmNBFm75ZZbuqfCmpluvvnmnEfUNwSX/RQn1fqVxbF39x7bSZg1a1ZF+9Zbb028j6xkNf0yi/UW8+fP77FdJDNnzqxoz5gxI6eRIA3VFw2r20Atmj59ekX76quvzmkkyNqcOXO6P4+5u2bPnp3ziPqG4LKfete73lXRfs973pN4HzNnzqy4QsIHs/6henpy9RSZJDQ0NPTYTkL1m2JR3yQl6bOf/WxF+/Of/3wq/ey7774V7f322y/xPmqlYIAk3X777T22AaBo6v2iyoYbbljRHjRoUE4jyd64ceM0cOBASdLAgQPV3Nyc84j6pmaDSzM7yMz+bmYdZla4hTh//etfK9qPPPJI4n3cfvvtFVdI+GDWP/z73/+uaD/zzDOJ91G92Xz1foFJWLFiRY/tIvnDH/5Q0f7973+fSj+f//znKy74pBHEVhcIqH4uFMlb3/rWHttYu6KfIwHUpssvv7yi/Z3vfCenkWSvra2t+zNAQ0OD2trach5R39RkcGlmAyRdIalF0rslfczM3p3vqNZNFtkFPpjVr+o1HIcffnjifWQx9TYr8+bN67GdlKFDh3ZnL/fbbz8NGTIk8T6OO+647kx1Q0ODjjvuuMT7yMqzzz7bYxtrVgvnSAC1aaeddurOXg4aNEgjR47MeUTZGTZsmFpaWmRmamlp0dChQ/MeUp/UZHApaU9JHe6+2N1fl3S9pENzHtM6ySK7kNUHsw022KCiXT3lAdmbNWtWRYYsjfWQ1RV706rgm8V6yKampu7xNzY2ppLpLfn85z+vXXbZJbWpt0OHDu0e/wEHHJBKAJuVAw44oOJ5fMABB+Q8osIo/DkSqFVZnTv7s8svv1wbbbRRXWUtS9ra2jRq1KjCZi0lyYqcTVgbMztC0kHufkLU/oSkvdz9pLX9zejRo/3444/XnDlzKm5fvnz5OmVczOwN88PHjRtX8UHxyiuvjNVPf+4jq36K2EdW/RS1j6z6KWIfWfXTn/tIsh8zW+juo3t1RzVoXc+Ro0eP9uoqw1KoMF5duKsn6/qcj2Nt7zFr09LSolNOOaXXv7+uj13K7vGv62OX0n/8HPvaOPb1/Nil+nnexz1H1mrmslfM7DNmtsDMFjz33HN5DwcAgH6B8yMAoE/cvea+JL1f0m1l7bMkndXT3+y+++6+Lk4//XRvbm72iRMnrtPfrYulS5f6GWec4Z2dnan1MW3aNB8/frxPmzYttT7c3RcsWOAHHXSQP/DAA6nc/2OPPebNzc3dX48//ngh+3APx72lpcWbm5u9paUlleO/dOlS/9CHPuTNzc3+oQ99KLXn2Lx587y5udl/97vfpXL/JY899pgfdthhqR0T92xej1h3fTkukhZ4PzhX5fW1rufIdT0/Jmn8+PG+3377+UEHHZTbGPLwy1/+0vfbb7/ur5tuuinvIWXqueeeq3j8S5cuzXtImZozZ47vt99+Pm/evLyHgjoU9xxZq5nL+yXtaGbbm9l6kj4qKdGdSKdMmaJddtlFZ511VpJ3W2Ho0KG69NJLU10T1draqp133lnHHHNMan1I0u67765Zs2Zp1113TeX+R44c2b3Wbvjw4RoxYkQh+5DCcS9f0J3G8R86dKiam5tlZmpubk7tOTZ27FjddtttGjNmTCr3XzJy5EjdeOONqR0TKZvXI9Ydx6VPUj9HJmXatGnaaKON3lBBstZNmDChYj3xIYcckvOIsjVs2DAdeuihMjMddthhhS1s0lcHHnig7rzzzkJX80b9qsng0t1XSjpJ0m2S/irpp+6e6F4etfKBplYehyRNmjRJgwYN0uTJ6VXVz6IPKZugP6sLCwD6lyzOkUnZaaedNGvWrLqqGFly2mmnSZLOOOOMfAeSk1oobALUo5os6NMXaytYAACoLfVe0GddcX4EgPpBQR8AAAAAQO4ILgEAAAAAsRFcAgAAAABiI7gEAAAAAMRGcAkAAAAAiI3gEgAAAAAQG8ElAAAAACA2gksAAAAAQGwElwAAAACA2AguAQAAAACxEVwCAAAAAGIjuAQAAAAAxEZwCQAAAACIjeASAAAAABAbwSUAAAAAIDaCSwAAAABAbASXAAAAAIDYCC4BAAAAALGZu+c9hn7BzJ6TtGQd/2yYpKUpDKcW+8iqn1rpI6t+aqWPrPrhsfS/PvrSz3B33zytwdSaPp4fk5TV86g/qufHLtX346/nxy7V9+PP+7HHOkcSXMZgZgvcfTR99J9+aqWPrPqplT6y6ofH0v/6yLIf5KOej289P3apvh9/PT92qb4ff9EfO9NiAQAAAACxEVwCAAAAAGIjuIznavrod/3USh9Z9VMrfWTVD4+l//WRZT/IRz0f33p+7FJ9P/56fuxSfT/+Qj921lwCAAAAAGIjcwkAAAAAiI3gEgAAAAAQG8ElAAAACs/MrPxfANlrzHsARWBmQyR9TtJrkq5x95dyHhJqjJkNkHSKu38r5X5OX8PNL0pa6O5/SrPvNJlZg6TBRXxtmtmP3P0Tb3YbAPSWmY2StMjdu/IeS8aGS3rCKShSN8xsS0mvu3tn3mNJk5lZUZ7XZC575xeSBkvaWtIfzWxEzuOJzcxO7c1tCfSz0MxONLPNkr7v6P7NzD5uZl+J2m83sz0Tuu/Te/pKoo8Sd18l6WNJ3udajFa4ULJ19PVZSQdJ+r6ZTUqqEzPbKAr4ZGY7mdkhZjYwqfuP7nemmW1iZhtJWiTpL2b2pST7iPq5xcxurvr6kZmdamYbJNDFe6r6GyBp9wTu9w3MbJqZ7ZPGfa+hr82iD7hp3f9DZjbFzHZIqw/UJjPbzswG5T2OtERZu0sl/Sp6P6l50WeBwZIeMLNzym/PcVj9Qvn/QdLn4bxFgeWlkg4xs2F5jydJ1c/dUmBZhOc0wWXvDHX3Ke5+hqTTJf3OzB42s2Yz+2lSnZjZf83spTV8/dfMks7ItK3htk8l3IckHS1pK0n3m9n1ZjY+4RfGdyW9X6sDs/9KuiKh+974Tb6SdreZfcfM9jOz3UpfCfexjaTd3P2M6Pm8u6S3ShqjZI//nZI2MLOtJc2W9AlJP0zw/iXp3VGm8jBJsyRtH/WTtMWSXpb0/ejrJYXn2U5Ru0/M7Cwz+6+kUeWvdUnPSrop/rDXaKGks83scTO71MxGJ3nnZnZHFPAPkfSAwkWLbybZR5kPS1op6admdr+ZTTSzt6fUF2qEmW0uaaKkIXmPJQ1mNsCDZkmbSrqyCB9GE9Dg7i9L2k3SyWb2BSl8IK+Tx79WZUHJcZKmmtkJZrZLzsNKhLv/SyEB9H5J46MLDDWh7Lgda2YXmNkXzOydRcheMi22d/5rZtu5+xPuflv0AWYrSc9LejipTtw9jYClgpl9TFKrpO3N7OayH20saVnS/bl7h6QvR1cSPyRpuqRVZnatpG+7e9w+93L33czswai/581svZj3qei+vprE/ayD90X/nl8+DElNCfbxVkn/K2uvkLSFu79qZv9by9/0hbn7cjM7XtJ33X2qmf0pwfuXpIHRVdjDJH3H3VeYWRpvuvu4+x5l7VvM7H5338PMHunrnbr7183sEoWp9sfFH2av+myX1B4Ffx+RdImZvd3dd0yoi7e4+0tmdoKk69z9XDN7KKH7ruDuSyRNVfiwtKOkcyRdIqkuMjXos6UKszZOUwgya0o0C0ZmdrSkDklHSNrKzD5chA+lfWFmVnrckraVdIukb5rZQHf/dq0+7nURvSd/StKZkq5XyPYl9vk1D9Fxd0nrK1zs/aCkRjP7dZGnyFqY6feSu68ys1MUPuNcJmmKwizKv+U3ut4huOyd4yR1ByzRk/npqLk8rU7N7K2Suqfdufs/E7jbP0j6l6Rhkr5Rdvt/JaXyITCaGneswgv/F5JmSNpX0jytDqj6akU07ad0hWdzSYmuMYmmPh6vMH2x/HgkGhC4+9gk728tZki618xKmbEPS5ppYWrpXxLsx8zs/ZKOUfi/k5L/0H+VpCck/VnSnWY2XCGrmLTBUQD2TylMvVZ4g5ek1+Pcsbt3mdkeb/6biRsp6Z0K65P+muD9NkbTlI6S9OUE73eNomN+dPS1SlJiU7tRfGa2obu/Gn2/taRN3P2vZnaSpAvM7N3unuT7Xr9gZuMlXaBwnp2sEEzcqPAhtaaUBRgys08qfAA/WtJ8Sd+KAsxL8xxj3sysUdK7JH1c0gcUgpMrop9t5O6v5Di8Pouy0kcqXCQ6WGFGXrNCAuNXUSa7UMzsEIXX6enRjMXtJB0g6URJL0j6RvSZdKC7/zenYb4pgstecPe/Z9lf9OT6hkJ29Fmt/gD4np7+rjeiq/1LzOwYSc+4+2tRnxsqTJl8Im4f5cxsocIL4geSJrt7KTt2r5l9IIEupimcNN9qZl9TuEp7dgL3W+5HCm/G4xWyiscowQ/kZvZxd/+xrWUdp7snNq3Q3S8ws99KKq27+5y7L4i+PyapfiSdKuksSTe6+yMW1inPT/D+5e7TFI5/yRIzSyNAP0PS783scUmmMP32C1FA3p7A/T9gZnu4+/0J3FePzGyqpAmSHlf4wHmBu7+QYBfnS7pN0t3ufn903B9L8P67mdm9kgZK+qmkI919cRr9oJjMbGNJd1hYjz9H0pckvdfMfibpdwqzNrZRshfVclEeYEVelHSHuz8btZuiqfC/kfThsixfoZnZuyQdbmaXRp8tBkn6nrv/WdKfzexvkuaYWVeS59EisVCD4lFJSyT9TNLz7j4u+tlp0e035jbA+IYrnG/+rTAT51hJ50oaZGa/KEoGM5q6PVhh6d33JG0h6RWFqe33SPq3pJYooP6UQoLrt7kMthdYc9k/XSBpb0mPuvv2Clct7km4j5+qMsO3SuGNJ2lHuvsB7j6zFFia2faS5O6Hx71zd5+hkK34ukJG9jB3T/pxjHT3cyS9Ek0rPFjSXgne/0bRv1mt7XxA4VjfKOnZpNepRZnkQ9z9EHe/RJLcfbG7n5JwP1uY2Q/MbFbUfrfWvJY4Fnf/jaQdFabRnSrpHe5+q7u/4u6XJdDFXgqFwh63UKTm4TSmkkYnr/9Ker+7H+TuP0w4sJS7/8zdR7n756P2Ynf/SJJ9SN3VgX/p7ru5+8UEligXZSxL6++/IWl3dz9N0hcV1pcfJulQSV83s23zGmcSqjJ360cXip+W9E4z27nsV6+R9DaFWUu1YiuFzM4Xo+UwL6ssOxtdOP2NpDMsFBirq7WXZraVpC8oHPcHFS46/CD62dEKM8qSnLmSquh9v/R9aSbU/ZI2jWbIyd2vVUiS7KZwAakoSpnIqyV9RtJ8d1+hUKtipaRfRYFlm0KmNpWLtkkhc9k/rXD3TjNrMLMGd59vZpcl3Eeju3dP6XP31y2htYpVfq7wIq++LZFqmGa2t6RH3L00xWMTM9vL3e9N4v4jpTeoF6KT9b8V1i4mwt2viv5NfY2nmZ2scFXvPwoXFExhSnFiVT2jdQL7JnV/PfihpGu1evrlo5JuUHTyTNjuCh9iGhWyH3L36xK67/EJ3U+PohPTUe5+QVp9mNlOkq5UWMe7c3TCP8TdL0yyn2g68ZEKayyBbhbWE59vZme7+3Qze03Sj83sJHefZWafVVjm0qXwun67pCfXkP3r96oCy9MV3se3VQiiZ0i6xsx+JGlzhdkqH3b3/+Q13qRYKHT3LoXZFw0KszFOcvdvmtlhZjZPYRrh/ylcUNvN3Z/PbcAZqX4Ou/szZvaypPPc/aNR1n5c9BoYKOnj7t7v1++VeLStjoXCRFua2RPuPsPMjpB0pJntqrBloCR93QuyNVn0uXJ/Sd+JbtpV0q1mto2k30v6tqQzzeyDCktajnD3x/MYa29Zwd5L64KZzVW4+vZ1hauMz0raw90T20LAzOZIutzdb47ahyrss3hAQvf/ToVpvFMVpiOVbCLpS+4ee4pv1M+DCieO0gm2QdICd0+syqqFhfC/kLSLQkAzWNJX3P17SfUR9ZP62k4z61AogpTqVBEzu1KhaMbPFKZ2SJLc/ZcJ9lEqqvOgu+8a3fYnd39fUn1E9/kjSTtI+pNCQC6FWC2xTKyZvVfSflHzrmhaV+LMrF2h+FEqU3DN7HcKr/eryo7JInffuee/7FNfFysUZ7lBlc+xxAuToViibORASVu7+11m9lFJF0n6vLvfVvZ7kyS9M8n32DxE0+RaFdbQz5W0xN0/bmYfUZjG/25J33T3RfmNMjlm9j6FC6TrufsSM9tfoWL8w+7+HTP7fwqfNd4t6UR3T6WeRH9iZtu6+5PR9+9T2Pf591H7Oknt7n67hWqqm0l6uYgBt5kdpXCB/JuSLo6+v0YhC/t/Csd9clGe6xa20vqMwoXyBkkbKtRyaVZ4/l7u7ovM7C0Kj+1Vd1+a13h7i8xl/3SowtWXLyqsg3uLKiuIJuFzkmaYWWnbjiclfTLB+3+HQnXYTRVOeCX/lfTpBPupvlLXZWHxemLc/Zro2zslpbnHaaprOyNPKkyNSdsGkjpVWenWJSUWXEp6xcyGanUxp72VzmMbrbDtSSpX4izsL/tprf6/+bGZXe3ul6fQ3V6SjjGzJQoBmSkEykllrge5+31Vs89WJnTf1Y6O/j2x7DZXuq9R9GPRTJ8ud3/SzCYr7H33JXe/PnpOTjOz09x9VvQn/5DUbGWFf4ogynRs5+6/jm7aSGGt1skKU0NPiC60zvFQvblwWdmeuPufogz1D81snrtfEk15/ZiFYk2Toxk0g9w9taKL/UH0uDeRdIWZfUKhcF6bpJ3M7C8KVWE7FAKV2z0UuSlcoRtJMrMDJLUo1Iq4K7qY+UeFmXjTJF1lZoO9WIV8BihkKl9SmCX3NklfUUhobCzpc2Y2w93/qGw+uyWCzGWdi65iKa0Xo5m9P3pRpMLMfinpDoWpeFJYXzDW3Q9LsI+LJE0trU+zUCb6DHdPtHBQKQNnZg+5+ygL22zc5e57J9jHDxQC/1tVtiWJF7DYQTQ16nJJO0tapDD164ikr1JHU4lO8bCfVuIsrK98v0cV+ywUCvpjggFfeV/D13S7h0JfSdz/LEknSfqZhy2CjpB0vLu3JHH/wNqUAigz28rdn4lu+7ykwyV91d1/H334/prCUo3nFbIDTxYlyyFJ0XlhnMJas43c/YkokP6YwtYSn4wusp6qMHvky5JWFj24rA6Qo6BqX4WA+l53/4aZ/Z/ChboHoimyNRVUr0npgoqFtbb7Sto2mg7+NoXCMA8p7AH5fkkHlbKZRVD2mi49xlMULir+WtLVHpaP7ahwEX6Ku0/NdcDrwELtkWXu/qKZNSnUQfmOQtZyiMLMxUEK59MNFB5fktvFpYrMZT9iZr93930tbKRe/oZYyi5skmBfQxWmE+wryc3s95LOT2q6pJldrtUZpY9V/zzBKYWfU6gYenbU3+0KUwyS1OLuU0oND3tpflDJV6VNdW1n5J/R13oq214naZbB2jt3fyD6MPEOhdfI3z0sgE/aMEl/MbP7VBmQH5LQ/ZtWT7eVVq+FTVw0hWxfSTu6+7UWtu5JctPpExUKErzTzJ5WyAx9PMH772ZmgxSyNW93989EHzLeUZbNQR2JPoQepFCqf4FCpeoro4zll83sEnf/kZnNLZtWNmutd9gPRR+yV0j6TTT19yvRBZ3LFNYddkra3Mw+rBBkHZHSe2KmzGxjj7ZdMLOPK+xr+LS7/9bMuhS2bVjl7peZ2SqFTF33JvS1ysyGlC0D2EqhqOEPLWy/clU0hfQdClmxbRVmLhVC1YWB7SQtdvdpZvaspIMk7Wtmv3P3x6LPG4WJZ6Lx3iDp79FMinkW1kw3KXyG3URhecmlChfQVxQpsJQKdDDqgbvvG/2bRoXQatcrTPMsVXI8RuHJfmBC97/gzX8lPg+l1j+acjcDzGx9X13tdkOFk1vSro6youdIulnhQ/85SXbgGRQNinxf0dq7qN+HzGympNjBpZmtrcrwThYK7SQ59VaSzkv4/qpdq7A1z40KQeWhSqcokczsXIVpvu+I+h0o6ccKe5/F5qFq64FR9rXB092H61pJC7V6W52nFdb4ElzWkbLsxjCFCxmfV5jN0GRmm0UB5noKgdifFS7aFU70OEsFTT6pMFPjToVlFC8rVJX/oUJmdgtJR3mBirWsTXTRaKqZnaWwL/Z5Cu+PXzSz7aPj6wpFnFZ4VNyvThxsoYjNYoXiPHtHs0V+FF2IuFIhm/2wmX3f3QszrbIUWEbTnD8SXdz9h7t/L8reHyZpfTO7zYtXLXyxpEcU1oheYmY3KFy4XqxwIeBWhTWkpyhsF1a4iyQEl/2MhfLKj7j7O1PuakuvrBp5oYXS1InwsGVHasxskrtPLc+QVvWf5LYXMyTdbmbXRu1jlcz+hhV89drO3ynhdWNmdpm7n2Zmt2jN/19JZeFK0lx79+Eefpb0uk65+++SvL813P83zewORbMIJB3r7g+m1N0EhfUdD0R9P2NhP8BEZDWFPLKDux9dmhnh7svN6murAXRnLPdX2O9upbvfaWZ3KdQQ2D3K4nzbzG70AhYwKSn7sL2/pOMUgsmBCu+rR0a/c0T0O0Vbd7ZWUWZqiULxln9IOjy6WDlHoW6ERwHHlxUuMNWNKBN/psJ+rbtFt/0xyu7+MLoofln064WonFrOwn7sRysEkj+UtI+Zvc3dz4su8o9V2GqmECxs+7aBuz9qYY/RkxWK+GyrsN3ZmOjfTyusr+wsYmApEVz2Ox4Wof/dzN7u7v9MsavZFiro/TRqH6Gw+Xmioml3ZyosJi+vgNq01j/qnVKhm9QzpB6KBTykcDKXwpWkNP6vhipclf2AQpBxV9RXElOVfxT9e2kC99UbSy1UQSt9IDpCYcpObO5+bBL382aynKZefr9KaUps5PXow3jpuGz0Zn+wjrKaQi5Jr0cfMEqPZQeVTVtGfTCzDyh88GyX9Akz+0u09qo9ynDsbmbbpHw+TU359EALBU0+I+nf7r5K0qpoWmyXpDYz29Tdf6Ky6slFFV0oMg8Fmk4zsy8pzLC618z+6u4LouBjlpmtLLs4W9PKMvUNUSb7OwoXF84xs8+7+2vufk8UYH7PzH7o7i8UIUgpe2ymMDvMJB2lUAl5Q4WZT2ea2fkKy7o2LspFlOhce46k9aILXb8ys8UKxTtnK0xrfpfCc/wFdz85v9HGR0GffsjM7lTILtynyhL7iWWXog/MG2n1+q6Gsr4S++BsZrMVpttOVFgf2SbpOXc/M6H7383dH0jivvIWXYm9U2GaohTeZPZ396SmKpemlN6a9vx9MxuhsPZuH4XCGf9QmLbzRML9HKw3bt2SdGXlVJnZVxQ+HPxC4bV4mEJBnET3hoz6mqhwZXScQsGA4yTN9IQq00YXYfaomkK+wBPaeqiqr3EKQeu7FU7OH5D0KXe/I+m+0D+Z2TsUngOz3H2mhbXq8yX9vyjAlJlt7e6FzGhVBZbHKexx95rC/pzflvR7D3tUD1NYr3WXp1R4LEtVj7tNCrOhzOyrCu/35yvM8FoVTQt9yfv5vn9JqPp/2UfSf9394aj9a0mvRLM52hQqzy9097SqdSfOzAZEx7R8GdLGkqZLOiZ6rt+kcKH6bC/AlhzlLBRZalLYou9rCmuDPyfpIndfaGZbKFw8+om7d+Q30vgILvshC0VK3iDt6XlpMLOF7r67RRVQo9vud/c9Err/+Qqlm38u6QZPsOpf1pkrW8N+gGb2sLvvkmAf1yq8ud2pEPT/Ns2Tj6W49s7MvqdQTW2swj5XR0i6z92PT6GvAQrrmLpneySVCTGzv0t6r7u/FrU3lPQnd39HEve/hv7GKVTJNEm3ufucBO/7TIVpy+VTyG/2lKr4Rdn+vRUeyz1F+7CBvinLcByuMIXs3wofNp82s3dLelChQuxFuQ40IVEgcZ5Ctc+uKMgaprDG+I/u/r+yTFbNsLDe7liFCriPRLd9XWHZyCUK75M19Zh7w8zOUFibv0yhiNMl0VTLXytksd8laUKSn4fSZGZ7u/s90fdfVJgl1qFQ9fc6C1uq/D+FtcWfl/Qxd/9PbgOOyUKl+0skzVG4KPoWharqj9fK67gh7wHgjaIg8glJA6Pv71e0RiopZvaB0pQ4M/u4mX0zmg+etFKlun+ZWWnx+ZCk7tzdxyoEF88p7HH0sJklMgXPywosufsmZV8bpzAlUoqmKptZQ/R1lBKeqhxNKR2p8KHkY5IeN7PEpxOZ2fpm1irpVIXCC1+JMnRJ2sfdPynpeQ+Fit4vaaeE+5CZnaywYfcchYX2tyrZojHPqCzzqqgSYoL33y16zc9z9y8pFF3aMJo6mMR9m6RS0aZ3RV8XpBhYfkDSa+5+q8J+ulNsLVutoPgsEjW3klQq3vU1hfL9E8xsS3f/i8L6s/vzGWlyooe8g0J2dkNJpXP0+QrvScdJ2lMKezznMsiUWNjHcqzCGstHzGwDSXL3sxSqnp6usOa05pnZZtEFTpnZoZLGufsYSX+XtJ+kU8xsB3f/kKQLJP1fUQLLyGQz+7OZ7adwzL+jMHPvVDOboFCo6xMKF5JOL3JgKYVK9woXTTolPaWw1vIQC3vT1kTGj8xlP2Rmn1ZIjQ9x9x0sVEv7nrsf8CZ/ui59PCTpvZJGKaxXuUahutwas6Yx+vmQwtrBbRVKKm+icEX55iT7ifraRdIkSUe7eyLbbFh2BZbKpyp3KbzBDFAKU5WjvgYqlPM+VtIYdx+W1H1H9/9bhQXpC1W2zYa7fyPBPu51973M7B6FveyWSVrk7iOT6iPqp0PSXp7QNj1ruP9fSdpDIXh1hSmr9ymcdBItTmVmCxU+jGwm6fcKa5Zfd/djErr/RDPtb9JX+XvYtQoVJBN/D0P/YmYtkr4qaa7Ce+W5ClUXD1PYZmmmr97nsnD7HK5pzBb2wTtJ0q8kzXb3f0fnpi9J+qG7F7ICbk+iD9q/kPRzd59Rdvv73P1PZjY0rffk/iS66H+NpIs9bFnxDkmvK1T2/4hCwPVjSf9V2E7uvtwGu47Ks3Rmdp1CNnayhyq3MrO9FV7rH1GYnbLS3V/Na7xJiz6HbSDpG5K+4e5/z3lIiaGgT/90osLVyHul7mppSe93uDKaVnSopO+4+w/MLPHphL56z7kXFa5IJcrM3qVQTewjCleBbpB0RlL379kVWMpkC5rog9nRkvaXdIeiiwopdLWNux+Uwv2W+7WZbaqwfmFhdFsaRR2eVHj+puXG6KvkjhT7Mg9VVY+XdKWHist/SvD+HzCzPdw9i6xR+XvYFWm9hyFfFvaE2zuaHvcBhaJkRyhUgz1C0paSPqvweWaCyrJZRQ4sLayb20aheN2vFS42HquwL/XtUQB9cW6DTVGUoTaF9bPblqZNWihC+HEz+2Q9BJZSWH5hoR7DGRb28vxd9P+zi8L73pMWlgeNUNjKohCi53opsNzA3T9pZjMkTVbYI1sKsw9eVtgvu+bW1HrYg3aFkt+bPXcEl/3T/zwsXJYkmVmjkk+V/9fCvlEflzQmukqY2BQTy26rkOkKe3aOL12tTsFmkh6xsM9SKgWWpO4T6jGStnf3Cyxskr1lwlciP6kQgH/W0y3q8wcz28WjYgNJMrM9JD3p0VY6ZjZYYS+vv0n6VoL9nB59u1jSHWZ2q8qqkbr7N5Pox0OhivUkvVPhtfJ3d389ifteAzOz9ys8z0qB2IAE738vScdY2DrgFa1enzwqwT5KUn0PQ/4sVBu/XtIJFgp7vEUhoNxGIcN/rEIFxqsUAswFvnpT+cIpCyxPU8jEXqewtOADCmsuV0n6oqQVZvYzDxVja1FDdGH3ToX3qrPMbKXC/rwfLfIx7q3SFHAP/p+ZrZD0ZQt7Of/OonWIZranpBaFGVuFWXNe9lw/XdJ2ZvYldz/GzH5tZosUXttbK8xMoQp4wRBc9k+/M7MpCuuhxkn6gqRbEu7jaIXyzsdHU2zerrBgOimpbxUSTQv6h7t/O60+IuekfP8l31WY5tWksG7iZUlXKEyZTIS7f8xCRbJx0bnrPnd/Nqn7L7OvpE+Z2T8UTgxJBhlXKUwJkpmNUbh6f7LCBttXK3z4TEIpk/zP6Gu96CtRFrbquErS4wr/T9ub2WfdfVbSfSl8UD1L0o3ROqYRCtmBpIxP8L7eTNrvYcjfFgqvua0VKipfIelZhdkpZ3jY0+8fCuvI35XGxaysRdMed1Z4jztV4T1hgML0wLMVMrcdtRBYrm3achRY7q9wHrkiunlbSY+neBG536jKYO8i6TF3v8zMnpd0toWtpEpTYccoFDwqXGbPzD6rMNvgqNLFbnf/kJlNV5i593VJH3T3p3IcJvqANZf9UHQF/niVVXSUdE3RpvhkwcJm2QekmOkp9TNc0o7uPtfMBkka4AlXQDWzB9x9NzN70N13jW77s7u/N8E+jlT4cHKHwnNrP0lfcvefJ9VH1M8aC6u4+5IE7rv7/8TMrlDY2ua8qP0nd39f3D566LtB0mB3T2xDajP7m6QPeVR63EIBj1s95XW+FjajTnytlpm9V+F5JYWtEf6cdB9r6PNDZVPwUUPM7HpF02A9bDcyWGHGyp2SFikUt/mMu/8tx2H2WXWAZWbrK8yW2VkhmDxA4ULK2QrTY8+shc8CVQHUMQrF2G5UKFLzFoU14V9y9xvXfi+1zUK13MMVLtJv7O6fN7NTFbL233L32y3aviPXgfaSRWssy/69QtLdCtWdmxXWTt8ZBdJXSPq2uz+a55jRN1SL7Yc8bBr8fXc/0t2PiL5P9GRiZoeb2WNm9qKZvWRm/zWzxD4wl/Uzx8K6uFJ7MzNLsgLqPyTdbWbnmNnppa8E779UYOnnCtklKVxF/1WSfURWRNnY0gl3c4VMZpLOVtiHsM1DpdU9lUJm1t2XRIHkqwqPp/SVhAHRVHEpfPCaV/azxGdjmNlMM9vEQqXVRZL+YmFD76T81yv3tFqscEU6bb9J+g6jDz4zJL01+vqxhWq7aSvU3qZ4c9F7oRSmu7dLmmqhIubLCjMUmhXezy4vamApVUwPPMpCAbydoos+GypkrFYpZC7nKBT9KHxgKVU87o8qzDx5m8LxPEJhm5Vmd7+xND20HpQ/1ihze5SkDyl85niLJEUzteZLOsnMBhUlsJQqKhq/P/p3gcK059IayzmSdoh+90QCy+JiWmw/ZGYP640fxF9UeCFe6MksZJ8q6cPu/tc3/c14Nnf3F0oNd3/eki1O9Hj01aDV0xiTlkWBJUmapnDl9q1m9jWFk2wi26qUaaiaBtupFC4ymdkhChXQtlKYxjZcYar0exK4+58oTB1fqhC83hX1OVLpFN55t7u/FF1dn6VQcGChkpuCucDMfiPppwqv+yMl3W9hD7/SdgtpSOND2/EKlXVfkSQzu0TSHxUqRaepbj6A1ovSh+ayWQnnKazl3ieaQXK/pFXu/vLaplf2Z1WZuyMUtlS5S9Lr0QXY2yX9wMKWHHso7HFZ6C0YqlnY0/uLkg5x9/+Y2acU1pe6kt3uqRDKng8jFCrHz1AIvoZJOiT62R7u/g0zm+7uy3MbbB9EM3/WlzTLzL7t7udYKFa03N2XRee8Y61OKgHXMoLL/mmWwsL9mVH7owqbxf9bYduQDyfQx38yCCwlaZWVVVqNpksm9iHAw/6Giq7gpfVGm3qBpehN9x8KW6kcoPBh+bAUjtFvow8uP4naRys835J2gcLm9nPdfVczG6tQeCU2d/+amd2uUCVydtmHygaFK+BJG2ihZPhhCpWVV0RrXpKygcKedaUtNJ5TyFp8WOF5llZw+f0U7tNUtvVM9H0Wgd9nM+gDGagKugZGr7f13f08M3td0kMWioV1V8YseGC5paTtFNYrL1EIJg6RtFThotxeCrUFYi8p6E+iAGpDhQuQX5B0rrv/0My6JH1Qq4sW1dT+nWtS9XxoU1hWcIXCfo/Pu/tu0c8+J2lfM/uMuz+f24DXUdnjG+jur5rZOxUuFK3n7mea2XpmdpzC1jpHEFgWH8Fl/3Rg6c0k8rCtXo+XyAd0hWzJDQrTO8srYCb9QfbLkn5vZr/T6jV+iZVdtlD58geSBkt6e7Te67Pu/oWk+lAGBZZK6w+itZapTfFy9y+Z2UcUrg5L0tUprWlZ4e6dZtYQra+Yb2aXJXXn7n7PGm5LawrNVZKekPRnSXdGF0gSm0Lu7scmdV+9YWb7Kqwf/m409Xqwu/8jobu/VtK9ZlZ6Th2m8PpMnIW1z2dIeru7f9rCfsDvYO1lMZV9ADVFF++iwHI7SV8zs3Pd/SILaxK3V4G2XShXFUhMVNii632SnnD3xRb2CJakUyT9yFPYEzoPVY97lMJF828pfB74nJmd6O5XeNhyZoXC2ruaDyylN0wR3lVhqvefzexShUrYn1G4ePppSZ8qSsYymk30nLu/aGbNkoaZ2Wx3f8ZC1feHzWylu3/ZzDoVZtN19HyvKAIK+vRDZvZnSZ/2aAuK6EV4jbu/18qKvcTs49o13Ozuflzc+15DX8MUsliSdI8nWC7bzO5VmD56s68ugrPI3XdOsI9MCixFJ5I/Svpl2lfizWwTlV1c8oRLu5vZXIXA4mJJQxWmxu7h7vsk2U9ezKzR3VcmdF/Xas3b9aTxWjxX0miFIGwnM9tK0s/c/QNv8qfr0sduClUepVDQ58Gk7ruqnxsUpid/0t13joLNP3iKBZ2QLjM7UGGd2W8U3guXRt//zt0vqvrdwk2FLWdmBytcqPyUpM8pnMdaPVRx3kKhavgd7v6v/EaZPAtr19dTWEf78yiYPEghcPqju1+a6wBzZGbXKVQJPtLd7zaztynsZ/kpSc9I+qG7P5LjEHvNzDaT9BWFfRzPUyhM9CFJP1O4cPCchUrpv5Z0mrtPy2usSB7BZT8UBZPTFbJxppAlOUHSI5IOdvef5ji8dWLWvXfjCHc/38J2AW/zhPZuNLN73X0vS7HCalbM7L8K6yxWSnpNq7fv2CTBPj6rUNL+NYViQaU+RiTVR9TPRgrrIRsUjv9bJM0o0nQXM/u4u//Y1lIgyhPa5zLKJJdsoFCa/RlPbi/Y8r7+pHBl/IGy18tDHnOLGDP7obt/Kvq+zd3b4461F30ucPfRtfDar2elCzVmtrdCJmu2whrDeQqFS1701ZWUG2ohmxVldKYqrIE/LLrtHEkfkdQWZa1q4rGWizJzRyqsV39GYUnGp939DxbW6R+lsLThhSJfOOiNtV0cMbPvSxqhsCwmi8JuiSo9ruiz30EKFxqXe1jOcoSkQyXdrLDco1nS/pKmu/vf8xozkse02H7I3e+XtIuZlaqDlRcpiRVYmtkkd59qZpdrzdmSpD/Qlu/deL5CFcxfKLm9G580s30kuYV1cadq9R6bsdiaCyt1i/uBfA33l1ZBonITJe2cZPZ4Tdz9FVu9fUt7lFUa8GZ/188Miv5N9bi4+y/K22b2E4Uy/Gl4PTrxl6ZhbZTQ/ZYHdKcqZCXS9rqZbajV1ZV3EJttF4aZbe3uT0eB5Y4KBcAucfdfmdkHFC5KuaRbo9+3ogZbawgUn1ZY936CmX3O3b/n7hdEr8crLVQKXZHDUNPWpVAcr12hSvkMSYeZ2QKFGUG3e1QMrNaVTYXdSmHNfYO7r4im+F8p6edmdlTV578iGKBwgdzcfVY0S2qSma1SuKjQpbCmuE3SOyWNS3BZBvoJgst+Kpoy8x5JG1hUSMbdkyi3Xwq8FiRwX72xl0d7N0rd1WKT3Ij+c5K+rVCq+2mFq94nJnTfH0roftaZmZ3nUZXEhD0uKfX1Gha2b/mMpCEKpcW3lvQ9hWJFRbFD9O9f3P1nGfa7o8I2Hmn4qZldJWnT6Bgdp2QK++SRZThX0m8lbWtmMxTWEX8qh3Ggb6aa2dfdfZHC82elpBPN7NZoSmCXQqGm9cxsWpGDjlJgaaFYy0aSnnL3n0Xn9mYz+6y7X+Xuk81smKe8b3MWzGwbhdkrqyS9Q+EY36JQ0Xs3hQvMW0n6mMJSkHtUZxeHoudDk6TPeSh0s4+kPT3sZ3mTpGvN7CNFyeJGS6AWmNme7v5sFDifolBpfzNJUyR9XeHi6TskPU1gWZuYFtsPmdn3FLImYyVdo7AW4z53Pz6l/lLZTD2673sl7SPp/ijI3FyhwmfsdaNZMbPtJf3L3V+L2htK2sLdn0ixzwe8sqhTUve7q6KiK6os5JRoxjqafrmnpHvLpiw+7O67JNlPmqLM9ShJC9M4FmX9/FeVwdm/JZ1VndFMsL9xKls/7O5zErjPZyVdH93n0dH33dKY4hv1O1RhPbcp4fXcSF+Usfyqu7ea2bYKa7NeU1iDtSL6sP1SFIAWjpltXJraaGZHSbpQoUDYJyS1u/u3omnxRyqcF6cXfS2pJJnZoQpbNj2rcIFxD4WgYrDCMp+/SZoraaCkSyRdXG/TIi1UR91NoXjP381sL4XiZ5Pc/TfR72zl7s/kOc51ZWYfVjjWH1W48P9Ld78iysYfonCx4cICZmSxDshc9k/7uPuoaC3UV83sG0pnu4iS3yi8yaWhtHfjFpbC3o1mNlXhhP2qQhZjlKQvuvuPk+pDYQF6eSGaVdFtSU3tXZO0tm+4SmEt08MK01PSkvr2LRn4raTnJQ02s/LqsImuhc1oOrQkKVo/ekMSAWWVL5V9n8msiGjq5J/c/VYLVbSnWNg7raa2bKhxHZL2MrN2d2+LzhFnSrrawnYLf8h5fH1mZjtJarVQpGV7SWMUCvYsMLNZkn4WxZGXmdlKSfdJxdtWpZqFbaf+n0JGcrHCevvrFJYX3Kowg2VTSde7+6mSMq2WnZfytYjRMd5XYaZFaQ/gwZJOd/fZpXXIRQssJcndb7FQ7fchSVPc/YroR3cp7HG5n0JBJ9Qwgsv+6dXo3+XRtIJOhT390pLaPnTuPsPMFmr1dMik925sdvdJZjZBYbuIwyXdKSnJ4LKxfJpSFDQl/uZoZh9w97uj5u5ruC0JA919jQVqEvY7S3n7lrS5+5ckfcnMbnL3Q9PqpyxIeiUKknaTlFaQtLGk2Wa2TNINCpViY2/M7mso4JPmjIjIlZLea2H7odMVrvpfp9X7haIfs9UVl3cwswfM7Cfu/rHoguGXFabNFTJjGdlMoVL2EQoVmodLui+awfEXMztS0lwzW1H2AbwW7CNpmrsvNLMNoqUwH5d0k6RHJY1TKNw0ysyGeoGKvPVVVTb67ZKWuPtxZrZc0i0W9m29vfT7nlAl8ry4+2/NbLyky83sSnd/0d1XSbrNzO7ygmylgr5ryHsAWKNfm9mmClf/HlAImn7S0x/ElMZm6uVKxVwaFDZNTlLpAsnBCh+U05hq8ZyFSnaSuqf8pDH9rnQFs3uNTvltCZllZp8xsy3NbEjpK+E+pDAl6jmFDOlnFbLjiWWss1QeWJpZGutwr1S4kPRehX0bH1cIkhLn7l919/corEveUuEiwNw0+lI45mn6/+zdeZhcZZX48e/JAgiRNYiKjMFfQMcFFwLiFsOSSERFcWNRWkTBEQGXcUZlixCcccEFxn1tHBRXBJcIkUV0HAcTFNwxYhQQlQREgwoJOb8/3lvQ3SSdTm5V36rq7+d58qTfW9X3nlSq+61zz7usqT6wHQy8v/qAPm5VYI1dRKxrMa97KnTVsPNdI+LLmflr4LheHQrbkpn/R7nJeX/Ktiq/oKye+Zgqsf4ZZerLN9d/lt4RrWEq8BBgevX1nRExOTN/R6lQvgS4GXgN8PyJkFjCsMV7XgO8PyLeExGvzszXAP9DuemweaNBtlk1OuZ1lH/b9kOOm1hOAFYuu1BmnlF9+aWI+BqwRSeSprh3P7qMiCdk5tUduMaplPkkX6JUSD8ZEV/IzIVtusTXIuIXlGrvv1RzOv/RpnO3vAo4LyL+i/JvuIEyZ6YtIuJJlLu9O8bwbS+2pv0rrB5W/f3mIceSsvR521TJ8Ufp/I2L8XY6ZV+udlpTDZc6GPivzPx4RHRkfvUQf6LM7VxJ5xYP6tiIiMpfI+LNlA+ss6PsRzu1w9fURoqILYDHRcTPKFMJpgCLM/PuKIu+vJkyfG6fiLg2Ih6XmT9qMORNVs0R/afMPB9Kglkl1vMpw8UfT7nxdlZEXNVP8wyHVOa+CLwpIvasqpetldz/RLkpu0X22d6dYxH3brVyEPAVysJOZOZRUVYI/zawTz/MuW3JslrsZpQK/axyqD/+bRqdyWWXqjqpGVT/RxFBZratmjEk6ftydajdSV/LEcBj897FcP4T+BFlnmRtWVbXewdlL7S7q2EmbR3CWN1J3yciplXtVe08P+UD8TTK//XQystfKEOq2iYzd23n+UaKcd6+pQGdSJjGLUmKiFdTPuDsSJk3/MqqgtIJnb6x8GLgcODozPxDlD1039nha2rjbUap0P0rZbj/4Zm5thqd803g462bp33w+2E74G0RcXdWK0xn2cMRSn/7acoN3RMp8+3ubijOTvo+pRr34ipRWgKsjYinUl6fifq58/6UrdleQPl/fw1ARMyohoM/CHp/zu1ImXlhRFyaPbqNkDaNq8V2oYj4NGUbhB9xb+eT2cYVFyPilwxP+u5Hmff18HZdozrv5cDzMvPPVXtbyuph+7XzOtW5P5KZx7T7vCOu8bXMbOvQyOoX7/4R8fnMfFE7z72B67b99Yqyt+V6dWge4biJssT6VW0+5wMpSdIPMvM7VZI0p503k4Zc6z8oC/r8qM3nHXVodWbe2s7rqbdUN0u/AFwKvCEzb6kqek/KzO9Wzxm5F2RPioj5lBVQz8zMz7UqURHxL5R/75H9PtcwInYGXkHZZuN/gbsoSdVhmXlNk7GNt9b7OiKeRlmp/Y+Z+ZTqseOB3SmLEPb0PEtpqIl6B6nbzQIe2eE7WL8HtuDeIaSbU/aJbLfbgZ9GxGJKRWsuZQz+2dD2LQpmtfFc67NzB875oOrD12OibBUyrDrWieHKlba/Xq3kMdazfUu7rzceIuKQEe2HUN7XP87MP9U9f7Xozburcz8rM79Gm+dcRsTWmfkXqsreyGSwDcnfUsrPd1AWrLit+npb4HeU1TLbKoZv4bIZpdq7KjO3afe1tPGGJFWbA9dQEo1jgNdFxOcy85qIuLZ6bl8klnDPUMAAzqxGHH2ueug24K5qDmLfJpYAmXlTNaLoMuAZwK2Um8x9Mwx4faoK5B+rhPIwylzibwHfo6ycPykinkkZPfIyYMDEUv3G5LI7/QR4IGXie6eMV9J3QfWn5Yo2nZdq+OA+ee9y9bU/6I/BDztwzlOBUygLIbx7xGNJ+VDWCZ18vZrYvqVTjgaeBFxetedQkqldI+L0zPx0G6/ViTmdAJ8BnsXwJLCl9pzb1nDriPgocEHeu0/bfOC5dc49yjXvGUJefZg/mLLnpRo2JLE8kLKg1x8oH67fQlkp9HlR9r17UUS8oN/m4GXmNyLibsqWKv+PsqfwocBRWVbN7HuZ+XfK9hPfaTqW8RJlr9Y3At+NiC0pC7RdAFxEWafh45S+5FWU+acv6/WFq6R1cVhsF6qGkj6Osu/V0I3un7O+79mEawyM9niuY2uBNlxzO2CXzLy2jef8YWY+vl3na1JEnDJkMadOXeOFrblAox1rw3V+lJmPG3Hsmsx8bDuvMx4i4mLgyKy27IiInSiVxcOAKzPz0W28Vk+/n6Nss/CYDR3r4PV7+vXrdUMXI4myUNlHKTfOVgEfocw5ez9wPPBY4IuZ+eX1nK7nVSNRXkzpx8/P9m7DpS5TjdB5FaU4sCuwIO/dduZkysJVX4+y73PPbzkirY+Vy+60oNMXyMzBahWv3atDv8zM1e2+TkRcATyH8l5bCvwpIv4n27fX4qUR8XzKPM6O3CmJsv3EGZR9yqZQqj6ZmVu38zqZeUaVgO9GGbLcOn5lGy/zZkoFcUPH6rolIp6TmRdBR7dvGQ+75PC9IP9UHbs1ymbR7XRsm883TGt+74aO1fD7iDiZe/eZPYIyBL/tRgxXnkQZ5t3ulaI1RlFW6n5ulP0qV1H2ePx6Zl5QPb43ZZjkt4B3Ufbc/cfQhLTfZOYP6cxoF3WRai2JzTLzTxFxGWW00T7ACyLi7Zn5hYhYC3w4Il5VTX2Q+pbJZRfKzG93+hrVkKRByh6aAewSEQNtTmQAtsnMv0TEK4BzM/O01jybNjmWsoH63RHxdzqT+L0XOIQyx65jH4Kq1+hEyvDYH1E6p/+lDcNiq+GJzwR2bg19rmwNdOLuaUe3bxlnV0TZEqiVgD+/OrYV8Od2XCCGrA4dEY8A2r069BaU/WanVzcwWsNit6a984gPA06jDAVL4Eru3f6m3Z495Os1lN9lbV0pWhvlKcATgc0j4pOURH/f1oPVIj6XAverhobeXR3vy8RSE8rjgSdXv1s3pxQI7gAeATw/ykr8X6puRnZqdW6pa5hcdqGI2Ac4B/hnykIVk4E72pwwnQXMa02wj4jdgc9SlopvpynVBPcXASe1+dzD5l110A3AT8bhQ9CJlDmJ38/Mfask421tOvfvKfusPYdSQW75K2Wj47bKzm/fMp6OoySUT6na5wJfqt4P+673u8Yo1rM6NO1d1OdY4LXAgyn//63k8i/Af7XrItXCQCdGxFaZeUe7zrueax3VyfNrbKoFau4Gvkrpq+ZQhpF/MCJeEBE/oCxc8iDgAMr8X6nnVYu7rQLWUkZO7A28IjNXRtm7cqA6fr+IGGyN5JH6nXMuu1BELKFM/v8C5RfTkcDumfnmUb9x465xbY7YU2xdx9pwnRdS5tx8NzNfHREPA96Zmc9v0/mDMvRu12pY6S7Ag7KN20VExF6UYbHfZvgc2JGL79S9zg8yc6+I+BHwxMy8MyJ+mpmPatP5JwOfzszD23G+jbhu27dv6ScR8XM6vzp061rHZ+Y5HTz/k4GPAdMy858i4rHAsZn56g5c6yGUm3CtpP87wImZeWO7r6V1i4iHU7acuIQy//jOapTEfMoNuY9ExJmU6vguwLsz8+vNRSy1RzXV482UG7fbAbOBMylTWj6XmUurzyf/DtwPOCvLit1S37Ny2aUyc9mQO8KfjIgfUn6RtcuSiPgYw+dGLWnj+QGoFor5wpD29ZQqULt8gHLXcD9KAriKsmBEO1clPbM67xaUSnKn3FjN3fgKsDgibgPati9kZt4dEbtExGaZeVe7zjsGndi+ZdxUc/veDjyAUvFr99Dr8VgdumVtRGyb9+47ux1l77kPtOn876FsPXARQJbtJma36dwjfZJSBXth1X5JdWxuh66n+3ogZUXM5wCfb908pIz22DEiXpaZJwFExP0z86/9PMdSE0NE7Et5nx9GGY5/f8pnqW2B3wAvi4ibKX3GLyg3XkwsNWFYuexCEXElZfjQxyhLuN9MWbK6bSttRtl77DjgqdWh7wAfyMw71/9dta95dWY+oRPnHLpKZLtXJY2In7RzRdAxXvPpwDbAN9uZCEbEuZTh1hdR5oQA7a/CjrjmJzLz5Z06f6dFxDLg2e1e6TEivkoZ/np/Orw69JBrrmsV37atsBoR/5eZT+zkz+OQa63r33KfY+qsiHgqZfucJ1JuHG4HPA+4EZhJmX/2CYDsk70sNbFFxEnA7Zn5XxGxRbUw1T9RbqT/jjLK6QWUefRzMnN5Y8FKDbBy2Z1eSpm78hrKfLhdaG+1jyqJfDfw7oh4UI7PPmOx4adstNXVcM/W8vc7UiqZ7fSNiJiXmZe0+bz3qP4NP83M1mIunVrU6dfVn0mUpGY8vCEi9sg2bkEzzv7Y7sSy8q4OnHNDJg+tHFXvu3ZW42+ohsZmREylzCPu1PYLKyPiJZS54lCqCH29OX03yszvRtks/ovAk6vq5NeAxwDHAL8xqVQ/GPK78yHA1OrwndUos99FxNGUz1WXAlcDfzCx1ERk5VKdqiiemJnvi4inZOb/VMcWZubJbb7OEZR9xJ5AWf32BcDJ2cZ9GyPir8BWlKrSajq0FUlEXAgcn5m/a+d513Otji60E+vYggZo5xY04yYi3kcZ/vcVhlcW27I/X0TsCtycmf+o2vcDdurEh5KIeCdlS50PV4eOBW7IzDe06fzTgfdRRl4EZS7eiZnZ9qQvIh5KmXP5JMrNpe8BJ4zHz4/uKyKeSfn/2Kta2OmeD+MOhVU/iYj9gTcBb6rmVk6iFAR2oqwuf1Rm/rXBEKVGmVx2oRinfRWHXK9tw+KGnPNHmfm4TiSu67jWI4D9Ka/TpR2qMnVcNRz68ZThkUOHrLZteGREPBr4NLB9dWgFZWXHn7brGtV1fpiZj4+yvcouWW1B0+4Fo8ZDlG0VRsp2DfWtFvB6cmv4c5T9Z/8nM9s5b7h1rUmUhLK1r+Vi4GPV3G6plog4kLLK8cMz87am45E6Ico2VG+kbO/0+cxcUh1/EfAvwCG+/zWRmVx2oWqOV8f3VRxyvVe3cUGP1jk/S1np9sGUYZj3PET5YN62JKMa2rcTQ4Z5t6N6ERGjJsWZeXXda1TXmcmI+CtPo1S0Pt6O61TX+h5wUmZeXrXnAG/LzCe36xrVeX8MzKNUk0/KzB/0anLZaeuZO9iReYrVue8H/FNW2xC1+dy7AsdT7dnZOt6h+aM7Aq9cx7V6dn5vP4iIgyhbZ13RdCxSp0TEzpSVkvej7Ed9F2Xk1GGZeU2TsUlNc85ldxqXfRWrhRh2y8wPVB/UpmXmb9px7sw8LCIeCFxMGR7ZERFxPGXT9j9S9ggMyhC5diQxZ1V/b0FJlK+pzr8HZWXdJ7XhGlCG0bw5M3889GBE3ErZ57JtySWwVSuxBMjMK6q7sO32Vsr//XerxPJhwK86cJ2OiYh/y8x3RMQ5VHN6h8rME9p0qVsi4jlZ7YEWZYn7FW069zAR8RzKKoebAbtGxOOA09uY/H2F8n79Ku2f+zzShZSFyL7FvfuDqmFZbTXiUFj1s8y8KSLeAVxGWSH7VuB5nbhpJ/Uak8vu9G+URWQ6tq9iRJxGSZgeTlm+fyplKe2njPZ9GyMz/wA8thrmt3t1+JeZubpd16AsGPLwTszpysx9ASLiy8ATWslfNbR0QRsvtdPIxLK6/o8jYkYbrwNwfUScQhkaC2X7huvbeYGqkrzL0Cpltn8LmvHQGl7d9i16RngVcF5EvJ+SxN5I2du2E06jbPR9BUBm/qiqNrbLPzLz7DaebzRbZua/j9O1tJFMLNXvMvPvlBtc32k6FqmbmFx2p/HYV/F5lPl9VwNk5u8jou2rh1ZbapxL2QsqgF0iYiAzr2zTJW4Abm/Tudbn4UOTv8z8SUT8cxvPv+0oj92vjdcBeDmlqthajOY71bG2ybKf5mGUPQ97VmZ+tfp7sMPX+TWwT6cXWaqszszbI4Yt3NzOJOB91Y2rSxh+Y6wtQ8hH+FpEPDMzv9GBc0uSpE1gctmdHpyd31fxrmoVv9aWBJ0YGgllWe55raEiEbE7ZeuAPeucNCJaq45eD1wREV+nQ1Ve4NqI+BilsgtwBGWIbLssiYhXZuZHhx6sFsNZ2sbrUC0ycEJEbAOs7eCKdv8TEf8FfI7hixN1IsnoqIiYBZzEvQtsAdCu+aMRsRNl+PODM3N+RDwSeFI759oO8dOIOJyyJcluwAmUVVbb5TGUrZT2495hsVm126JavTkpN6veEhF3Amta1+rUwmeSJGnDXNCnC1Xj+L+Vnd1X8V+B3YC5wH9Qqlefycxz2nyd+yzi0o6FXarqyPpkZp5e5/wjrrUFZQW4p1E+0C4Fds3Mo9t0/p2ACygLArSSyVmUqvXzquHFbRERe1E2NG9VqW8HXp6ZbU1iI+LydRzOzGxbkjFeIuKXlJUBf8yQeYSZ+ds2nX8RZWj6SZn52IiYAvwwMx/TjvOPuNaWlER5XnXoYuCMLPvetuP8y4BHtla+lSRJE4vJZRcasa9ix+7IR8RcyofMAC7OzMXtPH91jU9SFtsYWvWb3MZtHF6YI/a0XNexNlzn8cDhwIso1dIvZeZ/tfka+wKtivVPM/Oydp6/usa1wHGZ+Z2q/VTgA67iun4R8d3MfGoHzjslM9dExA8yc6+hWwKtawXZNl2zoz8vEfEV4JjM/FM7zrcR112QmQvG85qSJOm+TC7VURGxOXAc0Ppw/h1KMtOuSsl99tFs196a1RDew6o/KyhDPP81Mx9a99xNWdeepp3Yi3Sch3p2VJQNsw8DLmX40Osvr/ebxnbeqzPzCRFxBWWxo8VVex/g7Zn59DrnH+2aGzpW4/xXUFZT/gHDX6uOrRhdXbfj++lKkqQNc85ll+vUHfmIOAR4O/AASuWytf9k26qj1aqh12TmIyhzL9smIuYDzwR2joihq1Nuzb3V3rp+QUmGn5WZy6rrvq5N527KtyPiw5R5rwm8mDJn9QnQ1jmRn6Ia6lm1r6Mk5z2XXAJHAY+grKg8dB5hreSS8jMH8HrgIuD/RcT/ADtS9ktrm3H6eYGyGm0TYsNPkSRJnWblsst16o58NTfq2Zn58w0+ud51LgSOz8zftfm8jwUeR0mQF1aH11D2u7yiWrim7jWeCxxK2Z7lm8D5wMcys51bN4yr9cyFbGnbnMjxHOrZaRHxy8x8eAfOeyP33nSZBGxOSZLuBO5u89ZDrZ+X04FThzz0V+DyNv28TKYM535E3XON8XqHAF/PzDsjYlJmdnpfTUmStAFWLrtfp+7I/7HTiWVlO8oKlVcxfNXQusPkfkaZv7kZ926l8U+UatnXap4bgMz8CvCVaiXdg4HXAg+IiA8CF3RywaVOae3dOQ7uiIgdqLa5qIZ6dnrLmE75XkQ8MjN/1ubzTgamcd+f8S3bfB0y8xrgmoj4THW9tu87W21B88uI+Kd230xaj2cD74mIK4HPRcQ3M7OdVVhJkrSRrFx2uU7dkY+I9wEPBL5CG+eRreM665w3lpnfrnne91A+mL++tZ1GRGwNvAv4e2aeWOf8o1x3O+CFwIszc/9OXKOTIuJESgL+V+CjwBOAN7U7Ua6G2Z5DWaDoJ1RDPTPz2nZeZzxExM+B/wf8hvKz0hpCXnfF43GfJ7iufWeBgWzTvrNVovd4YOjNpMzMg9tx/nVcbyownzK8+6mUeauv6MS1JEnShplcdqGIGAROzMw/V+3tgLPatcJqdc5PruNwtnEV1y2AVwEzKVs4fLydVYWI+BWwe454A1dD836Rmbu161r9JCKuqba7eAbl/+dk4NMdGno9BXg4JYlpW4VsPEVEULaguc+2I3W3IlnX4kqdFhFLgcNzxL6zmVlr39kh5x96M6n12h2amY9qx/nXc82pwIGUubGzM3N6p64lSZJG57DY7rRHK7GEsvF9tRVG22TmUe083zoMAqspC+LMBx4JtLOamCMTy+rg3RHhHZP1aw3BfCZwbmb+tEqg2nPyMg9uXXaPiLZXxjstMzMi3t+JPSeBJirfU1uJJUBmXlclZ22Rmd8esm3PCynV3g+16/xDVYsUvRiYA1wBfIyyVZAkSWqIyWV3mhQR27UW2YiI7WnT/1VE/FtmviMizqGaDzdUZp7QjutQNlJ/THXNj1OGybXTzyLiyMw8d+jBiHgJZZVXrdvSiLgE2BV4c0Tcn3tXQG2HZ4/yWDtWWG3C1RGxV2b+oJ0nzcxb23m+MVoaER9j+L6zS+qedD3b9kSH5/geWV3n2HZtbSRJkupxWGwXiogjgbcArY3NXwicmZmfbsO5n52ZX42IgXU9npmDda9RXWfYfLJ2zy+LiJ0picrfgaXV4VnA/YDnZeZN7bpWP4mISZRVQ6/PzD9Xi+7s3ItzIcdLRPyCMrz7t5R5hG2Zc9mETu07GxFrq3MdPWTbnusz82F1zitJknqLyWWXqjadb20LcVkHVqrsqIi4m3sX9AhK0vc32ryfZkTsB7Tmc/0sMy9tx3n7WZWYP5Qh1fA2Lujy+tEeb+f2GuMlIh66ruN151yOt05uFTKe2/ZExHcz86kR8VeGj75o+169kiRp4zgstnttD9yRmZ+MiB0jYtfM/E27Tl4NY/tXYAbDk4y27HOYmZPbcZ4xXOcy4LLxuFY/iIi3U+ap/Qy4uzqcQFuSS+D+1d8PB/YCLqraz6b9Q6PHRSuJjIgHAFs0HM4m6+RWIeO5bU9mPrX6+/4beq4kSRpfVi67UEScRhni+fDM3D0iHgx8ITOf0sZrXENZaGMp9yYZZObS9X6Tel5E/JKyYFRH56hVW1IcNGSbmPtTNryf3cnrdkJEPAc4C3gw8CdK1ffnnVwBtVPWs1VIO/adXde1OrZtTyersJIkadNZuexOz6N8ALwaIDN/X304b6c1mfnBNp9T3e96YCpD9jbtkJ2Au4a076qO9aIzgH2Ab2Xm4yNiX+AlDce0qU4ZrwtVC5J9pPrT7nN3rAorSZI2nclld7qr2gIhAaqhZm1RrTwL8NWIeDVwAUMSjYZWsNT4+Rvwo4i4lOH/7+1aJbjlXOCqiLigaj+Xsj1NL1qdmSsjYlJETMrMyyPivU0HtTE6ve9sQ7YDfhoRHa/CSpKksTG57E6fj4gPA9tGxCuBl1P2cGuHpZQ5dq29Dd845LEEXN2xv13EvfMgOyYzz4yIb3LvqqRHZeYPO33dDvlzREyjzEs9LyL+xJBkpkd0et/ZJoxbFVaSJI2Ncy67VETMBeZRksCLM3NxwyFJG6WaF7cTwxeM6pkhjK0hl9XIgb8Dkyj7Qm4DnJeZKxsNcCNExI+H7Ds7BbiqnVsDjac+rcJKktQXTC67UEQcnZkfH9KeDJycmW9t4zWOo3xA/nPV3g44LDM/0K5rqPtExG7Af1AqV/esfNru/Qgj4njgNOCPlAWjem5vyKF7s0bElzLz+U3HtKk6ve/seIqIzzG8CvvbzOz1KqwkSX3B5LILRcRngG2BoylbknwK+HZm/msbr/GjzHzciGM/zMzHt+sa6j4R8V1K0vceyvYgRwGTMvPUNl9nGfDEXqrujTT056HXfzbGa9/Z8dBPVVhJkvqNcy67UGYeHhEvpgz5ugM4PDP/p82XmRwRkdXdhao6ulmbr6Huc7/MvLT6v/8tsCAilgJtTS6BG4Db23zO8Zbr+brnjNe+s+NkdeuLzFwTEaM9V5IkjSOTyy5UDV08EfgS8M/AS6vKyd/aeJlvAp+rFg4COLY6pv52Z0RMAn4VEa8BbgKmdeA61wNXRMTXGb4q7bs7cK1OeWxE/IWq0ld9DT1Y7eszjx3xf3G/If9P/r9IktQgh8V2oYj4BXBcq8IEvB54eTs3ba8SjGOB1ubmi4GPZebd7bqGuk9E7AX8nDLs+gxga+Cdmfn9Nl/ntHUdb+e8YUmSJHUXk8suFBFbZ+ZfRhzbPTOvayom9b5q6PPb2zl3V5IkSWqZ1HQAuldE/BtAZv4lIl444uGXtflau0XEFyPiZxFxfetPO6+h7hERU6qq9FM3+OT2XG/HiHhnRHwjIi5r/RmPa0uSJKkZJpfd5dAhX795xGMHtvlanwQ+CKwB9gXOBf67zddQ97iq+vuHEXFRRLw0Ig5p/enA9c4DfgHsCrwVWA78oAPXkSRJUpcwuewusZ6v19Wu636ZeSllaPRvM3MBcFCbr6HuswWwEtgPeBZlO5JndeA6O1R7ta7OzG9n5sura0qSJKlPuVpsdxlt64N2T44dr1VD1R0eEBGvB35CeS8NvVnRiYnXre0ibo6Ig4DfU/ZslSRJUp8yuewuo219sEWbr3UisCVwAmXV0P2AgTZfQ91jMuXmwboq4J1ILhdGxDbAG4BzKKvSvq4D15EkSVKXcLVYaQKIiKsz8wlNxyFJkqT+ZeVygomIi0Z7PDOfM16xaFy1e87uui8ScQ6jVEIz84TxiEOSJEnjz+Ry4nkScAPwWeD/GKekQ43bf5yus2TI128FThun60qSJKlhDoudYCJiMjAXOAzYA/g68NnM/GmjganvRMQPM/PxTcchSZKk8eFWJBNMZt6dmd/MzAFgH2AZcEW1YqzUTt65kiRJmkAcFjsBRcTmlD0tDwNmAGcDFzQZkyRJkqTe5rDYCSYizgUeDXwDOD8zf9JwSOojEfFX7q1Ybgn8rfUQkJm5dSOBSZIkqeNMLieYiFgL3FE1h/7n++FfkiRJ0iYzuZQkSZIk1eaCPpIkSZKk2lzQpzJ9+vScMWNG02FIkjps6dKlKzJzx6bj6BX2j5I0cdTtI00uKzNmzGDJkiUbfqIkqadFxG+bjqGX2D9K0sRRt490WKwkSZIkqTaTS0mSJElSbSaXkiRJkqTaTC4lSZIkSbWZXEqSJEmSajO5lCRJkiTVZnIpSZIkSarN5FKSJEmSVJvJpSRJkiSpNpNLSZIkSVJtJpeSJEmSpNpMLiVJkiRJtZlcSpIkSZJqM7mUJEmSJNVmcilJkiRJqs3kUpIkSZJUm8mlJEmSJKk2k0tJkiRJUm0dSy4j4hMR8aeI+MmQY9tHxOKI+FX193bV8YiIsyNiWURcGxFPGPI9A9XzfxURA0OO7xkRP66+5+yIiNGu0Ytmz559zx9t2Ic//GFmz57Nxz/+8aZD6QmnnXYas2fP5owzzmg6lJ5w3XXXMX/+fJYtW9Z0KOoD9pHakIMPPpg5c+bwvOc9r+lQpHE1Z86ce/6o93Sycvkp4MARx94EXJqZuwGXVm2A+cBu1Z9jgA9C6QSB04AnAnsDpw3pCD8IvHLI9x24gWuoz5133nkADA4ONhxJb7j88ssBWLx4ccOR9IaFCxdyxx13cPrppzcdivrDp7CP1Chuv/12AG677baGI5GksetYcpmZVwK3jjh8MND65D8IPHfI8XOz+D6wbUQ8CHgGsDgzb83M24DFwIHVY1tn5vczM4FzR5xrXdfoKSOrlVYvR/fhD394WNvq5ehOO+20YW2rl6O77rrrWL58OQDLly+3eqna7CM1moMPPnhY2+qlJoqR1Uqrl71nvOdc7pSZN1df/wHYqfp6Z+CGIc+7sTo22vEb13F8tGuoj7Wqli1WL0fXqlq2WL0c3cKFC4e1rV6qQ+wjBdxbtWyxeimpVzS2oE91NzWbvEZEHBMRSyJiyS233NLJUCT1sFbVcn1tqd2a7iPtHyVJm2K8k8s/VsN1qP7+U3X8JmCXIc97SHVstOMPWcfx0a5xH5n5kcyclZmzdtxxx03+R0nqbzNmzBi1LbVJ1/SR9o+SpE0x3snlRUBrNbsB4MIhx4+sVsTbB7i9GrZzMTAvIrarFimYB1xcPfaXiNinWgHvyBHnWtc11MeOOOKIYe2BgYH1PFMA++6777D23LlzG4qkN5x88snD2qeeempDkajP2UcKgG222WZYe7vtXNRXUm/o5FYknwX+F3h4RNwYEUcD/wnMjYhfAQdUbYBvANcDy4CPAq8GyMxbgTOAH1R/Tq+OUT3nY9X3/BpYVB1f3zV6ypVXXjlqW8Mde+yxw9pHH310Q5H0hre+9a3D2qecckpDkfSG3Xff/Z5q5YwZM5g5c2azAann2UdqNBdeODznv+CCCxqKRBpfV1xxxahtdb8pnTpxZh62nof2X8dzEzhuPef5BPCJdRxfAjx6HcdXrusa6n9HHHEE5513nlXLMdp33325/PLLrVqO0cknn8yJJ55o1VJtYR+pDdlmm224/fbbrVpK6ilR+izNmjUrlyxZ0nQYkqQOi4ilmTmr6Th6hf2jJE0cdfvIxlaLlSRJkiT1D5NLSZIkSVJtJpeSJEmSpNpMLiVJkiRJtZlcSpIkSZJqM7mUJEmSJNVmcilJkiRJqs3kUpIkSZJUm8mlJEmSJKk2k0tJkiRJUm0ml5IkSZKk2kwuJUmSJEm1mVxKkiRJkmozuZQkSZIk1WZyKUmSJEmqzeRSkiRJklSbyaUkSZIkqTaTS0mSJElSbSaXkiRJkqTaTC4lSZIkSbWZXEqSJEmSajO5lCRJkiTVZnIpSZIkSarN5FKSJEmSVJvJpSRJkiSpNpNLSZIkSVJtJpeSJEmSpNpMLiVJkiRJtZlcSpIkSZJqM7mUJEmSJNVmcilJkiRJqs3kUpIkSZJUm8mlJEmSJKk2k0tJkiRJUm0ml5IkSZKk2kwuJUmSJEm1mVxKkiRJkmozuZQkSZIk1WZyKUmSJEmqzeRSkiRJklSbyaUkSZIkqTaTS0mSJElSbSaXkiRJkqTaTC4lSZIkSbWZXEqSJEmSajO5lCRJkiTVZnIpSZIkSarN5FKSJEmSVJvJpSRJkiSpNpNLSZIkSVJtJpeSJEmSpNpMLiVJkiRJtZlcSpIkSZJqM7mUJEmSJNVmcilJkiRJqs3kUpIkSZJUm8mlJEmSJKk2k0tJkiRJUm0ml5IkSZKk2kwuJUmSJEm1mVxKkiRJkmozuZQkSZIk1WZyKUmSJEmqzeRSkiRJklSbyaUkSZIkqTaTS0mSJElSbSaXkiRJkqTaTC4lSZIkSbWZXEqSJEmSajO5lCRJkiTVZnIpSZIkSarN5FKSJEmSVJvJpSRJkiSpNpNLSZIkSVJtJpeSJEmSpNpMLiVJkiRJtZlcSpIkSZJqM7mUJEmSJNVmcilJkiRJqs3kUpIkSZJUm8mlJEmSJKk2k0tJkiRJUm0ml5IkSZKk2kwuJUmSJEm1NZJcRsTrIuKnEfGTiPhsRGwREbtGxP9FxLKI+FxEbFY9d/Oqvax6fMaQ87y5Ov7LiHjGkOMHVseWRcSbGvgnSpK0SewjJUm9atyTy4jYGTgBmJWZjwYmA4cCbwfek5kzgduAo6tvORq4rTr+nup5RMQjq+97FHAg8IGImBwRk4H3A/OBRwKHVc+VJKmr2UdKknpZU8NipwD3i4gpwJbAzcB+wBerxweB51ZfH1y1qR7fPyKiOn5+Zt6Zmb8BlgF7V3+WZeb1mXkXcH71XEmSeoF9pCSpJ417cpmZNwHvAn5H6TBvB5YCf87MNdXTbgR2rr7eGbih+t411fN3GHp8xPes77gkSV3NPlKS1MuaGBa7HeUu6a7Ag4GtKEN2xl1EHBMRSyJiyS233NJECJIk3aNb+kj7R0nSpmhiWOwBwG8y85bMXA18GXgKsG01BAjgIcBN1dc3AbsAVI9vA6wcenzE96zv+H1k5kcyc1Zmztpxxx3b8W+TJKmOrugj7R8lSZuiieTyd8A+EbFlNS9kf+BnwOXAC6rnDAAXVl9fVLWpHr8sM7M6fmi1Ut6uwG7AVcAPgN2qlfU2oyxocNE4/LskSarLPlKS1LOmbPgp7ZWZ/xcRXwSuBtYAPwQ+AnwdOD8iFlbHPl59y8eBT0fEMuBWSkdIZv40Ij5P6XTXAMdl5t0AEfEa4GLKKnufyMyfjte/T5KkTWUfKUnqZVFucGrWrFm5ZMmSpsOQJHVYRCzNzFlNx9Er7B8laeKo20c2tRWJJEmSJKmPmFxKkiRJkmozuZQkSZIk1WZyKUmSJEmqzeRSkiRJklSbyaUkSZIkqTaTS0mSJElSbSaXkiRJkqTaTC4lSZIkSbWZXEqSJEmSajO5lCRJkiTVZnIpSZIkSarN5FKSJEmSVJvJpSRJkiSpNpNLSZIkSVJtJpeSJEmSpNpMLiVJkiRJtZlcSpIkSZJqM7mUJEmSJNVmcilJkiRJqs3kUpIkSZJUm8mlJEmSJKk2k0tJkiRJUm0ml5IkSZKk2kwuJUmSJEm1mVxKkiRJkmozuZQkSZIk1WZyKUmSJEmqzeRSkiRJklSbyaUkSZIkqTaTS0mSJElSbSaXkiRJkqTaTC4lSZIkSbWZXEqSJEmSajO5lCRJkiTVZnIpSZIkSarN5FKSJEmSVJvJpSRJkiSpNpNLSZIkSVJtJpeSJEmSpNpMLiVJkiRJtZlcSpIkSZJqM7mUJEmSJNVmcilJkiRJqs3kUpIkSZJUm8mlJEmSJKk2k0tJkiRJUm0ml5IkSZKk2kwuJUmSJEm1mVxKkiRJkmozuZQkSZIk1WZyKUmSJEmqzeRSkiRJklSbyaUkSZIkqTaTS0mSJElSbSaXkiRJkqTaTC4lSZIkSbWZXEqSJEmSajO5lCRJkiTVZnIpSZIkSarN5FKSJEmSVJvJpSRJkiSpNpNLSZIkSVJtJpeSJEmSpNpMLiVJkiRJtZlcSpIkSZJqM7mUJEmSJNVmcilJkiRJqs3kUpIkSZJUm8mlJEmSJKk2k0tJkiRJUm0ml5IkSZKk2kwuJUmSJEm1mVxKkiRJkmozuZQkSZIk1WZyKUmSJEmqzeRSkiRJklSbyaUkSZIkqTaTS0mSJElSbSaXkiRJkqTaTC4lSZIkSbWZXEqSJEmSajO5lCRJkiTVZnIpSZIkSarN5FKSJEmSVFsjyWVEbBsRX4yIX0TEzyPiSRGxfUQsjohfVX9vVz03IuLsiFgWEddGxBOGnGegev6vImJgyPE9I+LH1fecHRHRxL9TkqSNZR8pSepVTVUu3wd8MzMfATwW+DnwJuDSzNwNuLRqA8wHdqv+HAN8ECAitgdOA54I7A2c1upsq+e8csj3HTgO/yZJktrBPlKS1JPGPbmMiG2A2cDHATLzrsz8M3AwMFg9bRB4bvX1wcC5WXwf2DYiHgQ8A1icmbdm5m3AYuDA6rGtM/P7mZnAuUPOJUlS17KPlCT1siYql7sCtwCfjIgfRsTHImIrYKfMvLl6zh+AnaqvdwZuGPL9N1bHRjt+4zqO30dEHBMRSyJiyS233FLznyVJUm1d0UfaP0qSNkUTyeUU4AnABzPz8cAd3Du8B4Dqbmp2OpDM/EhmzsrMWTvuuGOnLydJ0oZ0RR9p/yhJ2hRNJJc3Ajdm5v9V7S9SOtI/VsN1qP7+U/X4TcAuQ77/IdWx0Y4/ZB3HJUnqdvaRkqSeNe7JZWb+AbghIh5eHdof+BlwEdBazW4AuLD6+iLgyGpFvH2A26uhQRcD8yJiu2qRgnnAxdVjf4mIfaoV8I4cci5JkrqWfaQkqZdNaei6xwPnRcRmwPXAUZRE9/MRcTTwW+BF1XO/ATwTWAb8rXoumXlrRJwB/KB63umZeWv19auBTwH3AxZVfyRJ6gX2kZKknhRl6oZmzZqVS5YsaToMSVKHRcTSzJzVdBy9wv5RkiaOun1kU/tcSpIkSZL6iMmlJEmSJKk2k0tJkiRJUm0ml5IkSZKk2kwuJUmSJEm1mVxKkiRJkmozuZQkSZIk1WZyKUmSJEmqzeRSkiRJklSbyaUkSZIkqTaTS0mSJElSbSaXkiRJkqTaTC4lSZIkSbWZXEqSJEmSajO5lCRJkiTVNmUsT4qI3YE3Ag8d+j2ZuV+H4pIkqevZP0qSdK8xJZfAF4APAR8F7u5cOJIk9RT7R0mSKmNNLtdk5gc7GokkSb3H/lGSpMpY51x+NSJeHREPiojtW386GpkkSd3P/lGSpMpYK5cD1d9vHHIsgYe1NxxJknqK/aMkSZUxJZeZuWunA5EkqdfYP0qSdK9Rk8uI2C8zL4uIQ9b1eGZ+uTNhSZLUvewfJUm6rw1VLp8OXAY8ex2PJWDnKUmaiOwfJUkaYdTkMjNPq/4+anzCkSSp+9k/SpJ0X2Nd0IeIOAh4FLBF61hmnt6JoCRJ6hX2j5IkFWPaiiQiPgS8GDgeCOCFwEM7GJckSV3P/lGSpHuNdZ/LJ2fmkcBtmflW4EnA7p0LS5KknmD/KElSZazJ5d+rv/8WEQ8GVgMP6kxIkiT1DPtHSZIqY51z+bWI2BZ4J3A1ZSW8j3UqKEmSeoT9oyRJlTEll5l5RvXllyLia8AWmXl758KSJKn72T9KknSvMSWX69okOiJuB36cmX9qe1SSJPUA+0dJku411mGxR1MWKbi8as8BlgK7RsTpmfnpDsQmSVK3s3+UJKky1uRyCvDPmflHgIjYCTgXeCJwJWDnKUmaiOwfJUmqjHW12F1aHWflT9WxWykr40mSNBHZP0qSVBlr5fKKaqGCL1Tt51fHtgL+3InAJEnqAfaPkiRVxppcHgccAjy1ap8LfCkzE9i3E4FJktQD7B8lSaqMdSuSBL5U/ZEkSdg/SpI01FjnXN5HRHyknYFIktQP7B8lSRPVJieXwIfbFoUkSf3D/lGSNCFtcnKZmUvbGYgkSf3A/lGSNFGNOucyIr4K5Poez8zntD0iSZK6nP2jJEn3taEFfd41LlFIktRb7B8lSRph1OQyM789XoFIktQr7B8lSbqvMW1FEhG7Af8BPBLYonU8Mx/WobgkSep69o+SJN1rrAv6fBL4ILCGsin0ucB/dyooSZJ6hP2jJEmVsSaX98vMS4HIzN9m5gLgoM6FJUlST7B/lCSpMqZhscCdETEJ+FVEvAa4CZjWubAkSeoJ9o+SJFXGWrk8EdgSOAHYE3gJcGSngpIkqUfYP0qSVBlrcjkjM1dl5o2ZeVRmPh/4p04GJklSD7B/lCSpMtbk8s1jPCZJ0kRi/yhJUmXUOZcRMR94JrBzRJw95KGtKSvjSZI04dg/SpJ0Xxta0Of3wBLgOcDSIcf/CryuU0FJktTl7B8lSRph1OQyM68BromI8zLTO7GSJGH/KEnSumxoWOznM/NFwA8jIkc+npl7dCwySZK6lP2jJEn3taFhsSdWfz+r04FIktRD7B8lSRph1NViM/Pm6u/fAncCjwX2AO6sjkmSNOHYP0qSdF9j2ookIl4BXAUcArwA+H5EvLyTgUmS1O3sHyVJuteGhsW2vBF4fGauBIiIHYDvAZ/oVGCSJPUA+0dJkipjqlwCKynLq7f8tTomSdJEZv8oSVJlrJXLZcD/RcSFQAIHA9dGxOsBMvPdHYpPkqRuZv8oSVJlrMnlr6s/LRdWf9+/veFIktRT7B8lSaqMKbnMzLd2OhBJknqN/aMkSfcaU3IZETsC/wY8CtiidTwz9+tQXJIkdT37R0mS7jXWBX3OA34B7Aq8FVgO/KBDMUmS1CvsHyVJqow1udwhMz8OrM7Mb2fmywHvykqSJjr7R0mSKmNd0Gd19ffNEXEQ8Htg+86EJElSz7B/lCSpMtbkcmFEbAO8ATgH2Bp4baeCkiSpR9g/SpJUGeuw2BcCkZk/ycx9gbnA8zoXliRJPcH+UZKkyliTyz0y88+tRmbeCjy+IxFJktQ77B8lSaqMNbmcFBHbtRoRsT1jH1IrSVK/sn+UJKky1g7wLOB/I+ILVfuFwJmdCUmSpJ5h/yhJUmVMyWVmnhsRS7h3efVDMvNnnQtLkqTuZ/8oSdK9xjx0p+os7TAlSRrC/lGSpGKscy4lSZIkSVovk0tJkiRJUm0ml5IkSZKk2kwuJUmSJEm1mVxKkiRJkmozuexi1113HfPnz2fZsmVNhyJJkiR13LJlyzjooIP8/NujTC672MKFC7njjjs4/fTTmw5FkiRJ6rjW59+FCxc2HYo2gclll7ruuutYvnw5AMuXL/fujSRJkvrasmXL/Pzb40wuu9TIuzVWLyVJktTPRn7+tXrZe0wuu1Trrs362pIkSVI/8fNv7zO57FIzZswYtS1JkiT1Ez//9j6Tyy518sknD2ufeuqpDUUiSZIkdd7Iz78j2+p+jSWXETE5In4YEV+r2rtGxP9FxLKI+FxEbFYd37xqL6senzHkHG+ujv8yIp4x5PiB1bFlEfGmcf/HtcHuu+9+z92aGTNmMHPmzGYDkiSNG/tISRPRzJkz/fzb45qsXJ4I/HxI++3AezJzJnAbcHR1/Gjgtur4e6rnERGPBA4FHgUcCHyg6ownA+8H5gOPBA6rnttzTj75ZLbaaiurlpI08dhHSpqQWp9/rVr2pkaSy4h4CHAQ8LGqHcB+wBerpwwCz62+PrhqUz2+f/X8g4HzM/POzPwNsAzYu/qzLDOvz8y7gPOr5/ac3XffnUWLFnnXRpImEPtISRPZzJkz+frXv+7n3x7VVOXyvcC/AWur9g7AnzNzTdW+Edi5+npn4AaA6vHbq+ffc3zE96zv+H1ExDERsSQiltxyyy01/0mSJLXFe2m4j7R/lCRtinFPLiPiWcCfMnPpeF97pMz8SGbOysxZO+64Y9PhSJImuG7pI+0fJUmbYkoD13wK8JyIeCawBbA18D5g24iYUt15fQhwU/X8m4BdgBsjYgqwDbByyPGWod+zvuOSJHUz+0hJUs8a98plZr45Mx+SmTMoiw1clplHAJcDL6ieNgBcWH19UdWmevyyzMzq+KHVSnm7ArsBVwE/AHarVtbbrLrGRePwT5MkqRb7SElSL2uicrk+/w6cHxELgR8CH6+Ofxz4dEQsA26ldIRk5k8j4vPAz4A1wHGZeTdARLwGuBiYDHwiM386rv8SSZLayz5SktT1otzg1KxZs3LJkiVNhyFJ6rCIWJqZs5qOo1fYP0rSxFG3j2xyn0tJkiRJUp8wuZQkSZIk1WZyKUmSJEmqzeRSkiRJklSbyaUkSZIkqTaTS0mSJElSbSaXkiRJkqTaTC4lSZIkSbWZXEqSJEmSajO5lCRJkiTVZnIpSZIkSarN5FKSJEmSVJvJpSRJkiSpNpNLSZIkSVJtJpeSJEmSpNpMLiVJkiRJtZlcSpIkSZJqM7mUJEmSJNVmctnFvvWtbzF79mwuv/zypkPpCStWrOD4449n5cqVTYciSVIty5Yt46CDDmLZsmVNhyKNqyVLlrDffvuxdOnSpkPRJjC57GJve9vbADjjjDMajqQ3DA4Ocu211zI4ONh0KJIk1bJw4ULuuOMOFi5c2HQo0rhasGABa9eu5bTTTms6FG0Ck8su9a1vfYs1a9YAsGbNGquXG7BixQoWLVpEZrJo0SKrl5KknrVs2TKWL18OwPLly61easJYsmQJq1atAmDVqlVWL3uQyWWXalUtW6xejm5wcJDMBGDt2rVWLyVJPWtktdLqpSaKBQsWDGtbvew9JpddqlW1XF9bwy1evJjVq1cDsHr1ai655JKGI5IkadO0qpbra0v9qlW1XF9b3c/ksktNmTJl1LaGmzt3LlOnTgVg6tSpzJs3r+GIJEnaNDNmzBi1LfWradOmjdpW9zO57FJvectbhrVPOeWUhiLpDQMDA0QEAJMmTWJgYKDhiCRJ2jQnn3zyqG2pX40cFvvWt761mUC0yUwuu9QBBxxwT7VyypQp7Lvvvg1H1N2mT5/O/PnziQjmz5/PDjvs0HRIkiRtkpkzZ95TrZwxYwYzZ85sNiBpnMyaNeueauW0adPYc889G45IG8vksou1qpdWLcdmYGCAPfbYw6qlJKnnnXzyyWy11VZWLTXhLFiwgEmTJlm17FHRWmFzops1a1YuWbKk6TAkSR0WEUszc1bTcfQK+0dJmjjq9pFWLiVJkiRJtZlcSpIkSZJqM7mUJEmSJNVmcilJkiRJqs3kUpIkSZJUm8mlJEmSJKk2k0tJkiRJUm0ml5IkSZKk2kwuJUmSJEm1mVxKkiRJkmozuZQkSZIk1WZyKUmSJEmqzeRSkiRJklSbyaUkSZIkqTaTS0mSJElSbSaXkiRJkqTaTC4lSZIkSbWZXEqSJEmSajO5lCRJkiTVZnLZxfbdd19mz57Nfvvt13QoPWHFihUcf/zxrFy5sulQeoKvlzrJ95dUz3nnncecOXM4//zzmw5FGlfz5s1jzpw5POMZz2g6FG0Ck8sudvfddwOwZs2ahiPpDYODg1x77bUMDg42HUpP8PVSJ/n+kur56Ec/CsCHPvShhiORxtddd90FwJ133tlwJNoUJpddat999x3Wtno5uhUrVrBo0SIyk0WLFlkt2QBfL3WS7y+pnvPOO29Y2+qlJop58+YNa1u97D0ml12qVbVssXo5usHBQTITgLVr11ot2QBfL3WS7y+pnlbVssXqpSaKVtWyxepl7zG5VF9YvHgxq1evBmD16tVccsklDUfU3Xy91Em+vyRJmphMLtUX5s6dy9SpUwGYOnXqfYZVaDhfL3WS7y9JkiYmk8suNXny5GHtKVOmNBRJbxgYGCAiAJg0aRIDAwMNR9TdfL3USb6/pHpe+cpXDmu/6lWvaigSaXxtttlmw9qbb755Q5FoU5lcdqnLL798WPuyyy5rKJLeMH36dObPn09EMH/+fHbYYYemQ+pqvl7qJN9fUj1HHHHEsPahhx7aUCTS+Bo5jeLiiy9uKBJtKpPLLtaqXlq1HJuBgQH22GMPqyRj5OulTvL9JdXTql5atdRE06peWrXsTdFa0W+imzVrVi5ZsqTpMCRJHRYRSzNzVtNx9Ar7R0maOOr2kVYuJUmSJEm1mVxKkiRJkmozuexip512GrNnz+aMM85oOpSesGLFCo4//nhWrlzZdCiSJNVy4YUXMmfOHL761a82HYo0rs477zzmzJnD+eef33Qo2gQml12stWLs4sWLG46kNwwODnLttdcyODjYdCiSJNXynve8B4Czzjqr4Uik8fXRj34UgA996EMNR6JNYXLZpU477bRhbauXo1uxYgWLFi0iM1m0aJHVS0lSz7rwwguHta1eaqI477zzhrWtXvYek8suNXKfS6uXoxscHKS18vHatWutXkqSelaratli9VITRatq2WL1sveYXKovLF68mNWrVwOwevXq+2zCK0mSJKmzTC7VF+bOncvUqVMBmDp1KvPmzWs4IkmSJGliMbnsERHRdAhdbWBg4J7XaNKkSQwMDDQckSRJm2b77bcf1t5hhx0aikQaX9tuu+2w9nbbbddMINpkJpdd6tRTTx3WXrBgQTOB9Ijp06czf/58IoL58+fbEUuSetY73vGOYe23v/3tDUUija93vetdw9rvfOc7G4pEm8rksksdcMAB93wdEey7774NRtMbBgYG2GOPPaxaSpJ62syZM++pXu6www7MnDmz4Yik8TFz5sx7qpfbbbed7/0eZHLZxVrVS6uWYzN9+nTOOeccq5aSpJ73jne8g6222sqqpSacd73rXWy11VZWLXtUtLZvmOhmzZqVS5YsaToMSVKHRcTSzJzVdBy9wv5RkiaOun2klUtJkiRJUm0ml5IkSZKk2kwuJUmSJEm1mVxKkiRJkmozuexiK1as4Pjjj2flypVNhyJJksbRypUrOeGEE/wMIKmnmFx2scHBQa699loGBwebDkWSJI2jwcFBfvzjH3Puuec2HYokjZnJZZdasWIFixYtIjNZtGiRdy4lSZogVq5cyTe/+U0yk29+85t+BpDUM0wuu9Tg4CCtPUjXrl1r9VKSpAlicHCQtWvXAnD33XdbvZTUM0wuu9TixYtZvXo1AKtXr+aSSy5pOCJJkjQevvWtb7FmzRoA1qxZw+LFixuOSJLGxuSyS82dO5epU6cCMHXqVObNm9dwRJIkaTwccMABTJkyBYApU6Ywd+7chiOSpLExuexSAwMDRAQAkyZNYmBgoOGIJEnSeBgYGGDSpPIRbfLkyRx55JENRyRJY2Ny2aWmT5/O/PnziQjmz5/PDjvs0HRIkiRpHOywww4ceOCBRAQHHnignwEk9YwpTQeg9RsYGGD58uVWLSVJmmBanwGsWkrqJVYuu9ghhxzCNddcwyGHHNJ0KD3hqquuYs6cOSxdurTpUCRJquW73/0u1157Ld/73veaDkUaV/vttx9z5sxh//33bzoUbYJxTy4jYpeIuDwifhYRP42IE6vj20fE4oj4VfX3dtXxiIizI2JZRFwbEU8Ycq6B6vm/ioiBIcf3jIgfV99zdrQmL/ao1pYkGt2CBQtYu3Ytp5xyStOhSNImsY9Uy3vf+14A3v3udzcbiDTOhm7Do97TROVyDfCGzHwksA9wXEQ8EngTcGlm7gZcWrUB5gO7VX+OAT4IpaMFTgOeCOwNnNbqbKvnvHLI9x04Dv+utpo9e/aw9tOf/vSGIukNV111FatWrQJg1apVVi8l9Sr7SHHhhRfec2M5M/nqV7/acETS+Nhvv/2Gta1e9p5xTy4z8+bMvLr6+q/Az4GdgYOBweppg8Bzq68PBs7N4vvAthHxIOAZwOLMvDUzbwMWAwdWj22dmd/P8pv53CHn6llWL0e3YMGCYW2rl5J6kX2k4N6qZYvVS00Urapli9XL3tPonMuImAE8Hvg/YKfMvLl66A/ATtXXOwM3DPm2G6tjox2/cR3H1cdaVcv1tSWp19hHTlwjbyh7g1lSr2gsuYyIacCXgNdm5l+GPlbdTe34b9KIOCYilkTEkltuuaXTl1MHTZs2bdS2JPWSpvtI+8dmjZwG67RYSb2ikeQyIqZSOs3zMvPL1eE/VsN1qP7+U3X8JmCXId/+kOrYaMcfso7j95GZH8nMWZk5a8cdd6z3j+owO5bRjRwWe8YZZzQTiCTV1A19ZC/1j/3ota997bD261//+mYCkcbZpEnDU5PJkyc3FIk2VROrxQbwceDnmTl0EsFFQGs1uwHgwiHHj6xWxNsHuL0aGnQxMC8itqsWKZgHXFw99peI2Ke61pFDztUzrrzyymHtb3/72w1F0hv23nvve6qV06ZNY88992w4IknaePaRAjj44IPvuakcETz72c9uOCJpfFx22WXD2pdeemlDkWhTNVG5fArwUmC/iPhR9eeZwH8CcyPiV8ABVRvgG8D1wDLgo8CrATLzVuAM4AfVn9OrY1TP+Vj1Pb8GFo3HP0zNWrBgAZMmTbJqKamX2UcKuLd6adVSE5Wj9npTOEm8mDVrVi5ZsqTpMIY58sgjWb58OTNmzODcc89tOhxJ6gsRsTQzZzUdR6/oxv5RUv962cteds/n30996lNNhzPh1O0jG10tVut33XXXsXz5cgCWL1/OsmXLmg1IkiRJ6qBly5b5+bfHmVx2qYULFw5rn3766Q1FIkmSJHXeyM+/I9vqfiaXXap112Z9bUmSJKmf+Pm395lcdqkZM2aM2pYkSZL6iZ9/e5/JZZc6+eSTh7VPPfXUhiKRJEmSOm/k59+RbXU/k8sutfvuu99zt2bGjBnMnDmz2YAkSZKkDpo5c6aff3ucyWUXO/nkk9lqq62sWkqSJGlCaH3+tWrZm6Y0HYDWb/fdd2fRIve2liRJ0sQwc+ZMvv71rzcdhjaRlUtJkiRJUm0ml5IkSZKk2kwuu9inP/1pZs+ezWc/+9mmQ5EkSePosssuY86cOVx++eVNhyKNq2XLlnHQQQexbNmypkPRJjC57GIf/ehHAfjgBz/YcCSSJGk8ve1tbwPgzDPPbDgSaXwtXLiQO+64g4ULFzYdijaByWWX+vSnPz2sbfVSkqSJ4bLLLmPNmjUArFmzxuqlJoxly5axfPlyAJYvX271sgeZXHapVtWyxeqlJEkTQ6tq2WL1UhPFyGql1cveY3KpvnH44Ycze/ZsjjzyyKZD6QlvetObmD17tvtIqSOuuuoq5syZw9KlS5sOReo5rarl+tpSv2pVLdfXVvczuVTfuPHGGwF/EY3V9773PQCuvPLKhiNRP1qwYAFr167llFNOaToUqedMmTJl1LbUr2bMmDFqW93P5FJ94fDDDx/Wtno5uje96U3D2lYv1U5XXXUVq1atAmDVqlVWL6WNZOVSE5WVy95ncqm+0KpatvjLaHStqmWL1Uu104IFC4a1rV5KkjQxmFxKktqqVbVcX1uSJPUnk0tJUlttueWWo7YlSVJ/MrmUJqDp06cPaz/gAQ9oKBL1o3/+538e1n7Uox7VUCSSJGk8mVxKE9Btt902rL1y5cqGIlE/+tGPfjSsffXVVzcTiCRJGlcml9IEFBGjtqU6fH9JkjQxmVxKE9Bee+01rL333ns3FIn60VOf+tRh7ac97WkNRSJJksaTyaX6wuabbz6svcUWWzQUSW8YuXXLDTfc0FAk6kcjfx5HtiVJUn8yuVRfuPPOO4e1//GPfzQUSW8YmUyaXKqdvvOd7wxru4+qJEkTg8ml+sK0adNGbWu4GTNmjNqW6pg7dy5TpkwBYMqUKcybN6/hiCRJ0ngwuexS22233bD2Djvs0FAkvWHBggXD2meccUYzgfSIk08+eVj71FNPbSgS9aOBgQEmTSrdy+TJkxkYGGg4Iqm3HHLIIcPaL3zhCxuKRBpfI7dGe9CDHtRQJNpUJpdd6sILLxzWvuCCCxqKpDfsvffe91Qrp02bxp577tlwRN1t9913v6daOWPGDGbOnNlsQOor06dPZ/78+UQE8+fP9+aYtJFOOOGEYe3jjjuuoUik8fX5z39+WPuzn/1sQ5FoU5lcdrFW9dIPZmOzYMECJk2aZNVyjE4++WS22morq5bqiIGBAfbYYw+rltImalUvrVpqomlVL61a9qbIzKZj6AqzZs3KJUuWNB3GMNdddx0nnngi55xzjpUlSWqTiFiambOajqNXdGP/KKl/LVu2jBNPPJH3ve99fv5tQN0+0splF1u4cCF33HEHp59+etOhSJIkSR3X+vy7cOHCpkPRJjC57FLXXXcdy5cvB2D58uUsW7as2YAkSZKkDlq2bJmff3ucyWWXGnm3xuqlJEmS+tnIz79WL3uPyWWXat21WV9bkiRJ6id+/u19Jpddyk3uN94FF1zA7Nmzueiii5oOpSesWLGC448/npUrVzYdiiRphBNOOIE5c+bw+te/vulQpHHj59/eZ3LZpdzkfuO9973vBeCss85qNpAeMTg4yLXXXsvg4GDToUiSRrj22msBuPrqqxuORBo/Iz//jmyr+5lcdqlXvOIVw9ovf/nLG4qkN1xwwQW0ttXJTKuXG7BixQoWLVpEZrJo0SKrl5LURU444YRhbauXmihGfv4d2Vb3M7lUX2hVLVusXo5ucHDwnmR87dq1Vi8lqYu0qpYtVi8l9QqTS/WFVqK0vraGW7x4MatXrwZg9erVXHLJJQ1HJEmSpF5ncqm+EBGjtjXc3LlzmTp1KgBTp05l3rx5DUckSZKkXmdyqb7w2te+dlj7DW94QzOB9IiBgYF7EvBJkyYxMDDQcESSpJY99thjWPsJT3hCQ5FI0sYxuexS97///Ye1t9lmm4Yi6Q0777zzqG0NN336dObPn09EMH/+fHbYYYemQ5IkVY488shh7SOOOKKhSKTx5eff3mdy2aX++te/DmvffvvtDUXSGxYsWDCsfcoppzQTSA8ZGBhgjz32sGopSV1mZJ922mmnNROINM78/Nv7TC7VF1atWjVqW/d16623smzZMm677bamQ5EkDWGfJqlXmVyqL0ybNm3Utu5r4cKF3HHHHZx++ulNhyJJGsI+TVKvMrlUXzj44IOHtZ///Oc3FElvuO6661i+fDkAy5cvZ9myZc0GJEm6x9133z2s7fZaknqFyaX6wuc+97lh7fPOO6+hSHrDwoULh7WtXkpS9/j73/8+rH3HHXc0FIkkbRyTS/WFNWvWjNrWcK2q5frauq+rrrqKOXPmsHTp0qZD6QnXXXcd8+fPtyouSdIEYnKpvjBlypRR2xpuxowZo7Z1XwsWLGDt2rWuRDxGzumVJGniMblUX3BfpI0zffr0Ye0HPvCBDUXSG6666qp7VmtctWqV1csNcE6vJEkTk8ml+sLI7TRWrlzZUCS9YcmSJcPa3//+9xuKpDe4j+rGcU6vJEkTk8mlJG2Ae85tHOf0SpI0MZlcStIGOKd347hHnyRJE5PJpSRtwOTJk0dta7g777xz1LYkSepPJpeStAEHHnjgsPb8+fMbiqQ3jNzw3Q3gJUmaGEwupQloZHL07Gc/u6FIesPAwMA9Q2GnTp3KwMBAwxF1N/edlSRpYjK5lCagN7/5zcPab3zjGxuKpDdMnz6dgw46iIjgoIMOYocddmg6pK7mnEtJkiYmk0tpgmpVL61ajs3AwAB77LGHVcsxGLl1yxlnnNFMIJIkaVy55KE0Qb35zW++TwVT6zd9+nTOOeecpsPoCXvvvTfTpk1j1apVTJs2jT333LPpkCRJ0jiwcqm+MPLD61577dVQJL1jxYoVHH/88axcubLpUHqCr9fGWbBgAZMmTbJqKW0Ctz+S1KtMLtUXZs+ePaz99Kc/vaFIesfZZ5/NNddcw9lnn910KD1hcHCQa6+9lsHBwaZD6Ql77703V1xxhVVLaROYXErqVSaX6gvvfe97h7XPOuusZgLpEStWrOCKK64A4PLLL7catwErVqxg0aJFZCaLFi3y9ZLUUf/4xz9GbUtStzK5VF9wX72NM7JaafVydIODg/e8p9auXWv1cgwcRixJ0sRjcilNQK2qZcvll1/eTCA9YvHixaxevRqA1atXc8kllzQcUfdzGLEkSROPyaUkbcDcuXOZNKn8upw0aRLz5s1rOKLu5jBiSZImJpNLSdqAgYEB1q5dC5Rhse51ObrBwcF7Xq+7777b6qUkSROEyaUkbcD1118/rL18+fJmAukRixcvZs2aNQCsWbPGYcSSJE0QJpeStAELFiwY1j7llFOaCaRHPO1pTxvWHrlVkCRJ6k8ml5K0AatWrRq1reHuvPPOUduSJKk/mVxKE9D06dNHbWs4NzTfON/5zneGta+88sqGIpEkSePJ5FKagP72t7+N2tZwkydPHrWt4dx3VpKkicnkUpqATC43zoEHHjisPX/+/IYi6Q2bbbbZqG1JktSfTC4laQMGBgbuGQo7depUtyLZgH/84x+jtiVJUn8yuZSkDZg+fToHHXQQEcFBBx3EDjvs0HRIkiRJXcdVKSRpDAYGBli+fLlVS0mSpPUwuZSkMZg+fTrnnHNO02H0hIgYtohPRDQYjSRJGi8Oi5UktdXTn/70Ye05c+Y0E4gkSRpXJpeSpLZ6yUteMqz90pe+tKFIJEnSeDK5lCagkcMUHba4YStWrOD4449n5cqVTYfS9b761a8Oa1900UUNRSJJksaTyaU0Ae2zzz7D2k960pMaiqR3DA4Ocu211zI4ONh0KF1v8eLFw9qXXHJJQ5FIkqTxZHIpTUCbb775qG0Nt2LFChYtWkRmsmjRIquXG/C0pz1tWHv27NkNRSJJksaTyaU0AX3nO98Z1r7yyisbiqQ3DA4OsnbtWgDuvvtuq5eSJEnrYHIpTUDOudw4ixcvZs2aNQCsWbPGYZ4b4M0LSZImJpNL9YWpU6eO2tZw+++//7D2AQcc0FAkvcFhnhtn7ty5TJlStlGeMmUK8+bNazgiSZI0Hvo2uYyIAyPilxGxLCLe1HQ86qzVq1eP2tZwxx57LJMmlR//SZMmceyxxzYckfrJwMDAPe+vyZMnMzAw0HBEGsk+UpLUCX2ZXEbEZOD9wHzgkcBhEfHIZqOSusf06dOZO3cuAPPmzWOHHXZoOKLu5jDPjTN9+nTmz59PRDB//nzfX13GPlKS1CmRmU3H0HYR8SRgQWY+o2q/GSAz/2N93zNr1qxcsmTJfY6fffbZLFq0aJNj+dvf/kZTr3FEsOWWW27S986fP58TTjhhk763zmvm67VxfL02Tq++XrDpr5mv1zrPvTQzZ23yyXvcxvaR6+sfN9Y555zDN7/5zdrnabcm3+e9rO7PaKcceOCBHH/88U2HMYzv/f4xEd73dfvIvqxcAjsDNwxp31gdGyYijomIJRGx5JZbbhm34CRJatAG+0j7R0nSpujXyuULgAMz8xVV+6XAEzPzNev7nnbdmW2XAw88kL/97W/3tLfccsuuvOvVLZ75zGeyatWqe9rTpk3jG9/4RoMRqd+cddZZXHTRRRx88MG8/vWvbzoc1WDlcuP6yG7rHyeCAw444J4VqqEsjPWtb32rwYik8XHYYYdx880339N+8IMfzGc+85kGI5p4rFyu203ALkPaD6mO9YzTTz99WPvMM89sKJLesGDBgmHtM844o5lA1LcGBgbYY489XJxG/aDn+8h+95a3vGVY+6STTmooEml8jfz8NvLzsLpfvyaXPwB2i4hdI2Iz4FDgooZj2ih77733PWO6t9xyS/bcc8+GI+pue++9N9OmTQNK1dLXS+02ffp0zjnnHBenUT/o+T6y3+23337DtvPZd999G45IGh8zZ87kQQ96EFCqljNnzmw4Im2svkwuM3MN8BrgYuDnwOcz86fNRrXxTj/9dCZNmmTVcowWLFjApEmTrFpK0ij6pY/sd63qpVVLTTRnnHEGW221lVXLHtWXcy43hXNKJGlimOhzLjeW/aMkTRzOuZQkSZIkNc7kUpIkSZJUm8mlJEmSJKk2k0tJkiRJUm0ml5IkSZKk2kwuJUmSJEm1mVxKkiRJkmozuZQkSZIk1WZyKUmSJEmqzeRSkiRJklSbyaUkSZIkqTaTS0mSJElSbSaXkiRJkqTaTC4lSZIkSbWZXEqSJEmSajO5lCRJkiTVZnIpSZIkSarN5FKSJEmSVFtkZtMxdIWIuAX4bdNxrMN0YEXTQfQQX6+N4+u1cXy9Nk63vl4Pzcwdmw6iV3Rx/zgRdOvPkNRpvvebU6uPNLnschGxJDNnNR1Hr/D12ji+XhvH12vj+HpJ9fgzpInK937vclisJEmSJKk2k0tJkiRJUm0ml93vI00H0GN8vTaOr9fG8fXaOL5eUj3+DGmi8r3fo5xzKUmSJEmqzcqlJEmSJKk2k0tJkiRJUm0ml5LGRUTE0L/7Rb/9eyRJkjaVyWUP80Pt2EXE9k3HMJFFROS9E7x3bjSYNmv9uyLiwRHh71RJkjRh+UGoh4xMJod8qDXJHCEithjy9XOB11Zf+1o1YMh79ZXARRGxeT/9X0TEAPAfwNSmY5nI+uk9JW2I73f1u6HvcW/e9o4pTQegsRla+YmIFwLbA9cDSzPz1kaD6zIR8SjgXyPibZn5K+BBwMrq4cnAmsaCm8Ai4kDgCOA5mXln1VH0/HLVEfFy4AnA2zLzzqbjmciG/I48DNgL+Cnw48y8qtHApDYb8ZngecCWwO+AqzPzjkaDk9pgxHv81cADI2Jz4IzMXNVsdBqNdwF6xJAfsNcDrwbuBywE5jUZVzfKzJ8CmwMnRcRDgAcCd1SPmViOkxF3HCcDDwZmAQcAZObaXrzzvo65o0+l/Ey2HvemXYMi4hjgzcAvgD2BoyNifrNRSe015DPBG4ATgIcC/wnMbTIuqd2qG7gvoux7eTxwbLMRaUNMLnvAkA+z2wOPzcx9KRWf24AvRMQWETHhh+NFMQkgMw+nJJSvA+4P7BURh0bESyPieRExq8lY+92IO467UP4PPgUcB7woIp4F5QNSLyWYI+aO/hNAZr4c+ADw1YjYLDPXmGA2o3rdHw4ck5kfAd4G/Ah4ckRM6aX3mrQurfUDqv7uQcDjq88Eq4HbKb+H7ucQQvWqiHhcRDyi+nywGbAH8C/AfOBK4H2+v7ub/zldLCJ2hHs+gO9RDX9dGxFfpdydfFZm3g28ANitwVAb1/rQX1XDjoiIZ2bmccBmwPMpw2EfS6mc7Qs4lLhDRiSW/wa8H/gipXP4NvAZ4BUR8Xy49w58Lxjy73oN8P6IeE9EvDozXwP8D3BVRGxuhXx8rGMe+hrKdI/XV4n+jcD/AnsDW/bSe00aakgyuTQi5lXv5X9Uj30eeDpwcPWZ4GBg1+ailTZNlUw+k5JA/nNm3kWZ1vQO4CDg2dXv+VOqiqa6kMlld9svIr4SEccCb4uIbYDvAzsA76gqJAOUIWATevz5kA/9JwInUuaekJnHAxdS5ll+KDNPBF6Xmdc3FWu/G/J/cRCwf2Y+h/L+fHJmLge+CnyNUsGc1mvVpIh4DmWIzmGUO6qPA8jMo4CfUxJoF9sYB0PnnEXEMRGxHaWKfD1wavW0Xaq/7e/Us6qbpzdTpsOcHREHZOZtwDXADGBBZq6OiKOAk6kST6mXVMnkIHAp5XPvLsB3gMcAZ1EKLC8Angd8r7FANarwRm73iYhHAzdl5m0RsQR4FLB7Zt4QEXsAzwKeDfya8sH2xdU8wwktIh4IfAw4OjP/WFWQ7qwe+wzwV8qwzLutYLRfNdT4ZVUVr7XIxHTK4lP7Uu6q3xkRuwI3AFtl5u2NBbyJIuII4G7KvOfDKCMI7oqIGZm5PCIeVH0IVIeMqI4PUOac/Z5yh/tzwF3AkZShy1tShsle01C4Ui2tG1VD3vMvA04BjqL8Lj2Ksv7Cj4EnAy/yM4F6yYgpJ0TETpS5lY8FjqG8vw8F1gLbAsdn5k8aCFVjYHLZZapO5AzK3fc/A68E9qd8SH9aZt5dLY7yUGBr4JbMvKmhcBu1jl9GW1KqYu/MzG8OOf6wzLw+InbKzD82EetEUN1hPA9Ykpmvj4inUBaYWEVJLO+KiNcBs4FDe21l1YiYVA27fhrwSeCPmfmU6rHjgd0pVXGHxHbQiMRya+DlwPmZ+YeIOI1yM+MCSgV5OrA6M//cVLxSHSPe7zsAf64+BwxQEsyXZub/RsRelBtev8nMGxoMWdooI97jjwNWAH+kTHH4d+DRlEXzbqX8fl+bmSuaiVZjYXLZpSJib8rdyAVVFe4LwK6ZOasaljc1M7/UbJTNGfHLaBtgUlXpPZmykM/izPxJlC0JXgAclZl/aTDkvjXi/2I+8E7gc5l5RkS8hzLf9YfAFpR5l4f1wl31an7TH6uE8jDKHKZvAUspSfMkytCdHSmVswHvpHZWK8Gvvn4j5Wd7J+DDmfkf1fFTgUcAH8zM7zQWrNRGUVaF3RPYCjg1M6+pRlGcQrmptajRAKWaqpu0RwDfBR4CDFAWr/x3ypzi4zLzl81FqLEyuewSQz80Ve0tKdWRvwBvysyVEXEhsDNlkZoXZ+bPm4m2WSOSmdcDT6MMfXsf5YP/SZQVI/9I2evuBb2QzPS66sP+UyjzXZ8OXESZ93Y0ZWj3ZsD7M/NnjQU5RlUV9o2UTm5L4A2UatgxwEspQ9GeRJn3sQJ4T2b+uJloJ56IeCrwb8DrKfNeTwXOzsxPVI//OzCYmX9oLkqpPSLiVZR53nOBJZT5lKdl5iXVoibHU373/t0pH+oVEbFdNW+4tX/7aykrwp4KHELpZ59RPf144LPVIm3qciaXXSAi7peZf6++ngusyczLo2wv8lHKYjRvrCpzs4FfT9ShsENFxL9QOtxnURLx51OS7i9GxGMp862uyczfNRjmhBBlefyLgCMy87dVcvbfwMWZ+bbqOVMzc3WTcY5VRNwPeBVlj9RdKSMIflZ1gCcDb8nMr0e15YhDYTsrIh4J7J2Zn6q+fh8lqT88M7P6vfkfwCcy8wNNxiq1S+tGajUi59OUPm4OZWG/oygVy69FxNaOzFEviYh5lK2i3lLdJHkCcDPwHMr7/NnANyl7lu+XmS5Q1UNcPa9hEfEIYDAi7h8RhwPvBf4jIt5J+VD7SiCAD1ZzBq+cqIllRDwmIi4csgrn3ykTvI+lTPKeD3wmIo7KzGsy86smlp2xjpVQgzJ8ZcuqfRNwPvCvEXFGdazrE7CI2DYiHlDd7LkM+ANl2OULqgWivgCcDnw4Ip6VmWtMLDureq9tT9m/72FV5ftcyvyyAyNiy8xcDJwGHBYR26zj/Sn1hBHv3a0AMnMh5Xfs/Mx8TnXDbhXw3Or9b2KpXvNwylzKf42IZ2fm1ZTRZk8A3latyfBdytojD2gsSm0SN/puUET8P+C5lDmCnwQmZ+ajImI6ZYz50ZTVT19FSTon+s2A31BW6fw88MKqirELcCDwyqpidgmwMCK+BPzVIULtt47J97+qhm1fBJwfEfMz8/cR8XfK+/bT0DP7WT4eeHKULS02BxZQfj4fATw/Ir6QmV+KiNVA1w/v7XVDpgt8N8q+v6dFxI8z810RsQXw4vK0+HZVSb48M//WbNTSphvyu/VYYHZE/CAz30up1N8ZEa8EbqesFn+G73f1qM8CD6Na7bi6SfK56ubK0yPiyZSh3i/OzFuaDFQbb6InK02bCuxHqY58DXhqROxerYL1fsr/z4nAQzPzuJyg2xtExPRqbP4qSqXyroj4cpXk3ECpku0dEa+m7G+3V2b+pUeSmZ4yIrF8NWUe4rnVRPyPUlaL/Z+IOBt4K3BeZv6msYDHKCIeEhHbUirgsyhbjHwjM1dSOsHrq+NHRsSUzLwo3Su144Ys3vNsys3QLwIPjYgTM/OjwJWUm3BPqZ7vB231pIiYNOTrpwGvoPw+fUm1SNU0SsV+P+AtlDmXv20iVmlTRMQeUbbTg7Ly613AI4EPAkdExL6UobJTKVuQvM7Esjc557IBUfb5uzUzb69+mL4IvIYyTOBRlPmVy6vK5lGUhSr+1FzEzYmIZ1KqR8spFbKTImIa8CFgy8w8JCKOpqyi9zTKHCwXVumwiDiEsrjEaZR91Z4M3Aa8gzKsZSvghsz8dWNBjlFEHAy8mbJP4naUrVLOpKxu+7nMXFrdTf13ylDMsxyG1lnV/JsZmfnlKFsvXQY8k7KQyTMo86x/npnnRMSRwLcy8/fNRSy1R7VY1dbA1pl5fkTsBpxN+Rn4NPAnYLvqxpfUE6Jso3MLpRjwOuC3lFXk30dZr2E7ykqxH6pGoUzOzLubilf1mFyOs4jYnbLJ9y+B12bZm+0oyuqan6AkSI8GTsqyN+OUiTqnKyIOpCye8k7KL6I3UDZD/3tEbAZ8irL40ZHV87fJzNubineiqBbvuYKyTcfc6tgzKXfU/w78V/bIfqLVzZ0PUyqVy4H7UxYiupoyDPthlIViHgDMAK7MzFubiHWiqCo4L6bMN39fZl4YEd8HDqmGW29Gea8dDvxvZn6wwXClWkaMBnkFZZ/rH1HWXHh+Zv40Ih5G+b30tdYCaVKviYj9KNt5LQRWA/9MSTavycz/rj4LH0ip2q9y9FnvMrkcZ1FWl/wUJZm8jJJo3p8yNOBqyjLjbwS2oXy4unsi/oBVCcwKSud6QZR9Py+kDMOcnJnHVh8yv0zZVPolQztptc+6Xtfq/+MzwMfz3v0FD6YMHX1vr9xVj4iTgNsz878iYovM/EdE/BPwBcqWKt+m7KU4A5iTmcsbC3YCaL3XqiHKBwIvocxH34tSJZ+cmX+r5l8+nvKhpCduZEijiYhnAAdT9tC9lTKa6YmUG80/i4gZlM8DNzQXpVRPROxPKaQ8gdK3Hk6Zd/lyyjoHZOZfGwtQbWFyOU6qD6xbZOZ11YI9x1PmVP02+xgAAKRaSURBVN4I7EapWP6a8gM2tXruhB5rHhEHUe5wvQx4F/A9ygJHXwR+k5mHRsRWwDYOieuMEXfVD6PM+/ltlqXDH0+ZK/GVzPzP6jlbZeYdzUU8NkOSmA9SKrALqqGvkzLz7oh4NPBuypzn7YA/OMeys0a813aiDP97MXAcZU7lVyirxq4A/kYZxeDy9OpJQ34HTaL0+Z+nbBx/DOVG806Uvm8uZfP4XzQVq9RO1UintwNPysxVEbFrL6zNoLFztdhxUCVApwCbRcQFmfmViLieMn/oEuDBlOEBh1KqcK8GJvydm2rc/d2UcflvGZLA7A9cGBE7VBWyrk9metgk4O6IeA1lPsS7ga9FxDFZVut9FfC5iLgrM9/dC4klDFu59ovAmyJiz2puZUbZX/bPwF+AGzPz503FORFUSf3QVTJfCzyPMsdyEWWRpb9SqsifoLwntzWxVK+Ke1dBBtgxM/8YES8CPkD5PXtDNWVmkLLoyaqmYpXaLTO/Uf3a/0FEPKWVWDr6rH+YXI6DzLwjIk6hzBP6r4h4ELCMssXIsupD7cspdyw/22CoXSczv1kNF/qviPhQZv4ZeCFlYZW7Gg2uj0XEEzPz/6oq3uMoH/ZbwxSvAU6NsnH32RHxAnr3Zsj3gf8BXlx1bEuAtVGWQd8Bf0eOh/u1Vnmt5twcStlq6I5qeOzFlPk5r6eMWLiIshWD1JOGrIJ8HHBQdbP5OsqIpnOBN0bEWZl5c0S8z4VN1G+qBHMq8K2ImFUOmVj2C4fFjrNqFcS3A4spQ722AY7OzF+PuJupISJiPmVhnw9QPny+OjN/0mxU/SsivgbskpmPrdo7AXsDb8jMORFxKGXO5Ysz8wsNhlpbROxMWUBgP+B/KTctXgAclpnXNBlbv4uIZwGvBp4P3EkZAnsDZWGox1DmnX+UUmHeC/i+c87UqyLigZn5h+rrwyg3lF9KmWc5pZrqsS3lJvMPgZP9TKB+FhHTsmwzpz7iPpfjLDOvpmwvspIy33I28Jxq3oWZ/npk5iLgTcB7gX8xseyM6n1IZj4L+HW1SifVoilbUyruUBKwz1IWoOppmXkTZQuVk4E1lMU0nmdi2VnViIRTKAtA/b36EP07ygfu11JWiH4jZVGTNZn5BRNL9apqDYGLqsWooAz3fiNwEGU16pdUx7ekjM55v4ml+p2JZX+yctmQajjAFsBZlH3zftlwSD0hIrZMN0rviPWsCnsh8IDMfFJEPIqyeff9KHuyPttFbrQpIuLplFVgX5GZl0XZ+/e4zPzXalXMmzPzzoiYS9ma4XmZeXODIUubLMq2WicBZ2bmN6tjz6KM/rgqMw+ojr2S8rv1TTlBtyCT1PtMLiWNXKnzdZQFU06r2l+lrMg7u1r1+GnADzLzuuYiVq+KiMnA2yj7+L2cMrf1M8DnM/N91XOmVo8dCwxk5o8bCleqZci2WodUi/nNpIySeC2lcv9IyrYjc4F/AQ7PzJ82FK4k1WZyKeke1aqwhwIvGbqnY0R8FnhMZj66qdjUP6oP3KcAmwFzgA9l5jlDHt8CeATwF6vj6nXVkNgzKFuLvAf4Wma+p5pf+QbKavFrgbeaWErqdSaX0gQWEftQ9pp6T7UlxKco2z38jnIn/SmUitLXqwTzLe5HpTpaC5dVCea/UZLIN2Tmr6vHXwm8CHhmZq5uMFSpbaqhsd+g2lZrxGiRACY7FFZSPzC5lCawiHgiJaH8UGa+LyLOAPagLCpxOWXT+kmZ+frmolS/iYjJ1TY32wOnUqo251BuZvwLZdGua5uMUWq3ag7xOcATM/P2iNgsM91SS1JfMbmUJriI2Av4IGV1wk9GxJ7ATdUm3s+n7L12MGWIor8wVEtVpYmqerkVZQ/Lt1GGBj4MeH5m/qzJGKVOqbbVei9lxMitDYcjSW1ncimpVcH8APCpzDwnIqZQtsx5HWVDe+cBaaONGPo3Bbh7SPvJlPfcAdXTXw18NjN/1Uiw0jiJiIOB0wA3j5fUd0wupQmulQBUFcz/Av67SjD/BbjMbXK0KUYklq+lDLf+G2UY7F+AxcC7MvPrI58v9Ts3j5fUr0wupQlixIf91qIqrblvM4A7gZ2BzwGnZ+Zgg+GqT0TEvsBCymqZ84EnAvsDZOYd1TBZTCwlSep9k5oOQFLnjUgsXwg8r0ow746IOcCXge0ycwllpc4rGwtWfSMingOcCHwkM7+ZmScC3wcuAbZqPc/EUpKk/mByKU0AQxLL1wAnAddWlcstgecDZ7YWUcnMpW43ok3RqkIO8Vtga2CfiNgGIDNfC/wEOD8i7IMkSeojDouVJoDqQ/+DgI8Dx2TmDdUH+wTun5l/aQ2RbTRQ9awR1fEnAn/IzN9GxK7ARyjVyo9m5p+r5+yUmX9sLGBJktR2U5oOQFJnDP2wXy3YcwuwCpgZETe3NuyOiP8XET91vzXVMSSxfANl65rlEXEjZV+/Yygrw94vIt6bmX8xsZQkqf84JEnqQyOqSNtHxP0zczVlmOIsShWTiDgUeCOwZWPBqqdFxHYRMbn6+rnAMzJzNrAWmAv8O/AP4ATgcXhTU5KkvuWwWKnPjEgsTwCeAfwRuJgyNPEcYDNgDfAY4PDM/HFD4aqHRcRMygJQ787Mf1R7V94MPJNSvTwJeCdwE/AW4KZWxVySJPUf7yBLfWTovMmIeCXlg/+LgP8EzgZOy8yXRMRjgRnAmzLzd03Fq94VEdtm5rKIeB/wyIjYGriyWijqscCrMvP6iPg5pXL5dxNLSZL6m8ml1CciYi5wVERcB/wUWE6pHr0U2AZ4DvDZiNgmM98OXNNUrOpt1SI9r42IxZn5tYh4ETAduBv4TvW0z0fExyj7Wj4vM//UULiSJGmcOOdS6gMR8QzgPyh7CP4FeBnl5lFr3tsJmfl/wFXAYRGxwzq2jZDG6g7gT8BTq6GwbwF+AxwREXtn5jHAN4C9gIHM/G1zoUqSpPFi5VLqcRGxO/Al4AWZ+c2I2AGYSVmk505KsrlbRMynJAVzM3NlYwGr52Xmn6rVh58IPAo4A3gbcDLwsojYIjNPjYip1UJSkiRpArByKfW4zLwOuAh4dUTcr0octwV2zMy/AddS5l0eC5ydmbc0Fqz6QkQcA7wC+CRwF3A48GTgTMrNjOdV70UTS0mSJhBXi5V62IgFfD4N7Aj8nFK5fGFm/qN67H7A5Mxc1Viw6gsRsTllxeGLqvmWOwP/Avwz8C7K0OwdMnNFg2FKkqQGWLmUelhm3t3aYzAzXwpcD7wEeFm1NcQW1WN/N7HUpoiIYf1EZt4J3AC8MCIekJk3AR8DHg08G9jCxFKSpInJ5FLqcVWCObX6+tXAl4FPRcQOrcqltCmqPVPXVl/Pi4gjqvfa+ZQFfQYiYjrwCOBXlGHXf28uYkmS1CSHxUo9JCImtT7sDzk2uUow9wJmZuZnI+IrlJVin5/+kGsjVUllDmkfA7wO+DXwAOCFwMOB+ZRFfaYAR2fmjxsIV5IkdQmTS6kHRcR+wE3Aqsy8KSJmUxZXOTYzv1U958GZ+fsm41RvqqreK6uvnwq8ATgqM/8cEe+hVCpfnZm/iYh/orwPb20wZEmS1AUcFiv1gKF7UkbEUcC5lG0fTomIxwD/AF6fmd+KiCkAJpbaFBHxYOC/I+I51aGDKQtEzQXIzNcBPwW+FBEzMvN3JpaSJAlMLqWe0BqiGBGHAbsCjwcWANcBbwTuyMwLq8VX7m4qTvWFOyjzdo+OiCcDp1btJ0TEHIDM/FfgG4BDXyRJ0j0cFiv1gNYcuIi4Ftg2M/+pOv5w4FnAU4DTM/NHDYapPhER2wDPo+yPeibwE8rQ2KnAZZm5uMHwJElSl7JyKXWpoUNhKR/qycw9gFsi4vNV+5eUCtJllNU7pU3Wes9l5u3ABcDngZMo24y8C9gMeEpEbNlYkJIkqWtZuZS60NDVOiPiFcAM4ObMfH917AfArzPz0Ko9NTNXNxWveteI99oDM/MPQyrl21Mq4y8AzgKupuxjeUuDIUuSpC5l5VLqQkM+7L8aeBnwVeA/IuJdEbFlZu4FzIqIT1XPN7HUJhnyXnsV8M7q/ZURsTfwVODrlOr4ccAaE0tJkrQ+JpdSF4mIp0bEA6uvdwb2B54LzAJ+CDwSOCciNs/MmcBbm4pV/aPabuQQ4ITM/FtEPAH4CvCPakuSzwCvzMy/NximJEnqciaXUnd5AjClqh7dBLwc2B14QWY+HXgtcDhwfDV08TfNhapeNWJrmx2Bw4CHAo+tDj8QOCwzLwHIzL9U8zAlSZLWa0rTAUiCiJiUmWsz8+yI+GfgOxGxb2Yur7YXISK2oOw3+FXgc63hjNLGGDHH8n6ZeUtEnAqsBvaLiD9m5jeqxydRRs76XpMkSRvkgj5Sw0Z82J+emSsi4l3A0yhbQdwC/AewB7ATcEhm/qKxgNUXIuL1lOHWDwbOAG6kVMr/Bnw9M5c0GJ4kSepBJpdSl4iIN1DmVL42M/8aEW/n3jmXf6QMmf1DZv62uSjVDyLiSOAlwEGUBXtuz8wXRsRjgWMoiea7M/POBsOUJEk9xuRS6gIR8UrgpZS5lX9qbS0SEW8Bjgb2zczfNRul+kVEHA0sBeYC+wEHA2uALYHpwN8y031TJUnSRnHOpdSAiNgpM/845ND/A84FHhIRLwH2j4irMvOtEbE5MLmRQNXzhg67HmIbygqwP8zM+dXzTgAeBrwhM+8e5zAlSVIfMLmUxllEPAL4WUS8D/hFZn4Y+DEwHzgKGAQ+D+xVbTlyWnPRqtcNmc/7CmAL4FfAe4FnAndGxC7V18cALzSxlCRJm8qtSKTxtwr4HvAH4PkR8SHKkMQzM/MpmfkR4HbgyZQKk7TRRmw3cgDwOmA7yg2M1wAHUvqAUyg3Nl6UmT9vIFRJktQnrFxK4ywzb4yIqygL9DyTsiLsocBxEfEa4ICq/VLnvWlTjFiB+BHADOCozLwqIvYG/pUy5/5l1XO2zMy/NRWvJEnqD1YupXE0pJr0JiApi6f8nrJ5/c+AhcARwNGZ+dNGglRPG5FYnkgZZr0AOCgipgBLgHcCcyPipOrb/t5ErJIkqb+4Wqw0zqoEcyplOOLDgD2BN2XmVyJiV8q2ELc2GaN6X0Q8l7LdyOGUCvlxwIeAC6qnPI6ytc3vm4hPkiT1H4fFSuOsqirdFRH/DXwbeH9mfqV67DdNxqbeNXQF4ojYmjLc+pGZeRfwlWrV4X+hLOrz2cy8urloJUlSP3JYrNSQzPwlZXjs5IjYsul41LuqeZU3R8R7IuIVmfkXyhDrH0fE+wEy83OU7W4OBbZqLlpJktSvTC6lZn2fsrCPVMfQFYhfHBGfBHYH3g/8JSLeC5CZ5wKHZ+ZfmwpUkiT1L5NLqUGZ+QvgUFfqVB2ZeSPQWoF4PrAYeCnwn8D1wOyIeHP19FWNBClJkvqeyaXUMBNL1THKCsRPAK4GngPcAXwJ7pnzK0mS1HYu6CNJPSwzc0iC+SvgLMoKxK9zBWJJkjSe3IpEkvpERDyce1cgPqPpeCRJ0sTisFhJ6hOuQCxJkppkcilJ/cUViCVJUiMcFitJfSYitnShKEmSNN5MLiVJkiRJtTksVpIkSZJUm8mlJEmSJKk2k0tJkiRJUm0ml5IkSZKk2kwuJUmSJEm1mVxKkiRJkmozuZQkSZIk1WZyKUmSJEmqzeRSkiRJklSbyaUkSZIkqTaTS0mSJElSbSaXkiRJkqTaTC4lSZIkSbWZXEqSJEmSajO5lCRJkiTVZnIpSZIkSarN5FKSJEmSVNuUpgPoFtOnT88ZM2Y0HYYkqcOWLl26IjN3bDqOXmH/KEkTR90+0uSyMmPGDJYsWdJ0GJKkDouI3zYdQy+xf5SkiaNuH+mwWEmSJElSbSaXkiRJkqTaTC4lSZIkSbWZXEqSJEmSajO5lCRJkiTVZnIpSZIkSarN5FKSJEmSVJvJpSRJkiSpNpNLSZIkSVJtJpeSJEmSpNpMLiVJkiRJtZlcSpIkSZJqM7mUJEmSJNVmcilJkiRJqs3kUpIkSZJUm8mlJEmSJKk2k0tJkiRJUm0ml+swb968e/6szyc+8QnmzZvH4ODgep+zcuVK3vCGN3Drrbd2IsxNMpaYli5dyoEHHsgPf/jDWudpVzzd+Dp2E1+fDfM1kiSpN8yZM+eeP+o9HUsuI+ITEfGniPjJkGPbR8TiiPhV9fd21fGIiLMjYllEXBsRTxjyPQPV838VEQNDju8ZET+uvufsiIjRrtFu559/PgDnnXfeep9z3nnn8ZOf/GTU54y3scR05plnsnbtWs4444xa52lXPN34OnYTX58N8zVSt+n3PlKSNDF1snL5KeDAEcfeBFyambsBl1ZtgPnAbtWfY4APQukEgdOAJwJ7A6cN6Qg/CLxyyPcduIFrjMnIauW6qpef+MQnhrXXVb1cuXIll1xyCZnJxRdf3BUVk7HEtHTpUlatWgXAqlWr1lm9bNe/bSzn6cbXsZv4+myYr5G61KfowT5SkjppZLXS6mXv6VhymZlXAiM/xR0MtDKxQeC5Q46fm8X3gW0j4kHAM4DFmXlrZt4GLAYOrB7bOjO/n5kJnDviXOu6Rtu0qpYt66qGnHfeeaxduxaAtWvXdkXFZCwxnXnmmcPa66petuvfNpbzdOPr2E18fTbM10jdqJ/7SEnSxDXecy53ysybq6//AOxUfb0zcMOQ591YHRvt+I3rOD7aNe4jIo6JiCURseSWW27ZhH/O+l122WWsWbMGgDVr1nDppZe29fybYiwxtaqW62uP9TztiqcbX8du4uuzYb5G6iFd00d2sn+UJPWvxhb0qe6mZpPXyMyPZOaszJy14447tvXa++23H1OmTAFgypQp7L///m09/6YYS0zTpk0btT3W87Qrnm58HbuJr8+G+RqpFzXdR3ayf5Qk9a/xTi7/WA3Xofr7T9Xxm4BdhjzvIdWx0Y4/ZB3HR7tG2xx66KHD2kccccR9nnPEEUcwaVJ5eSdNmrTO54y3scR00kknDWufcsopm3SedsXTja9jN/H12TBfI/WQvugjJUkT13gnlxcBrdXsBoALhxw/sloRbx/g9mrYzsXAvIjYrlqkYB5wcfXYXyJin2oFvCNHnGtd1xiTSy65ZNQ2wMtf/vJh7YGBgfs8Z4cddmDevHlEBM94xjPYfvvtNyaMjhhLTHvuuec91cpp06bx+Mc/fpPO0654uvF17Ca+Phvma6Qe0vV9pCR10hVXXDFqW92vk1uRfBb4X+DhEXFjRBwN/CcwNyJ+BRxQtQG+AVwPLAM+CrwaIDNvBc4AflD9Ob06RvWcj1Xf82tgUXV8fddoq1b1crQqyBFHHMGjH/3orqqUjCWmk046iUmTJq2zarkx52lXPN34OnYTX58N8zVSt+n3PlKSNDFFmXKhWbNm5ZIlS5oOQ5LUYRGxNDNnNR1Hr7B/lKSJo24f2diCPpIkSZKk/mFyKUmSJEmqzeRSkiRJklSbyaUkSZIkqTaTS0mSJElSbSaXkiRJkqTaTC4lSZIkSbWZXEqSJEmSajO5lCRJkiTVZnIpSZIkSarN5FKSJEmSVJvJpSRJkiSpNpNLSZIkSVJtJpeSJEmSpNpMLiVJkiRJtZlcSpIkSZJqM7mUJEmSJNVmcilJkiRJqs3kUpIkSZJUm8mlJEmSJKk2k0tJkiRJUm0ml5IkSZKk2kwuJUmSJEm1mVxKkiRJkmozuZQkSZIk1WZyKUmSJEmqzeRSkiRJklSbyaUkSZIkqTaTS0mSJElSbSaXkiRJkqTaTC4lSZIkSbWZXEqSJEmSajO5lCRJkiTVZnIpSZIkSarN5FKSJEmSVJvJpSRJkiSpNpNLSZIkSVJtJpeSJEmSpNpMLiVJkiRJtZlcSpIkSZJqM7mUJEmSJNVmcilJkiRJqs3kUpIkSZJUm8mlJEmSJKk2k0tJkiRJUm0ml5IkSZKk2kwuJUmSJEm1mVxKkiRJkmozuZQkSZIk1WZyKUmSJEmqzeRSkiRJklSbyaUkSZIkqTaTS0mSJElSbSaXkiRJkqTaTC4lSZIk/f/27jxOjqrq//j3JGELiJgICIIJGFwQUCAogkIWSNhB3NBReDCgPCiL8ijwgIICYlSUxQWRoICjKIIgEpJAws6PJWELKDyMSGRfhn0RSHJ+f9xbM9XVW810Ty/Tn/frNa+Zqq6uvr1N1alz77lAzQguAQAAAAA1I7gEAAAAANSM4BIAAAAAUDOCSwAAAABAzQguAQAAAAA1I7gEAAAAANSM4BIAAAAAUDOCSwAAAABAzQguAQAAAAA1I7gEAAAAANSM4BIAAAAAUDOCSwAAAABAzQguAQAAAAA1I7gEAAAAANSM4BIAAAAAUDOCSwAAAABAzQguAQAAAAA1I7gEAAAAANSM4BIAAAAAUDOCSwAAAABAzQguAQAAAAA1I7gEAAAAANSM4BIAAAAAUDOCSwAAAABAzQguAQAAAAA1I7gEAAAAANSM4BIAAAAAUDOCSwAAAABAzQguAQAAAAA1I7gEAAAAANSsKcGlmX3dzO41s3vM7A9mtrKZbWBmt5hZj5n90cxWjNuuFJd74u3jU/s5Oq6/38ymp9bvFNf1mNlRTXiKAAAMCsdIAEC7anhwaWbvlHSopInuvomkkZL2kTRT0k/dfYKk5yTNiHeZIem5uP6ncTuZ2cbxfh+QtJOkX5jZSDMbKennknaWtLGkz8VtAQBoaRwjAQDtrFndYkdJWsXMRkkaLelxSVMk/Tnefq6kveLfe8ZlxdunmpnF9Re4++vu/i9JPZI+HH963P1Bd39D0gVxWwAA2gHHSABAW2p4cOnuj0r6saR/KxwwX5C0SNLz7r40bvaIpHfGv98p6eF436Vx+7Hp9Zn7lFtfxMy+bGYLzWzh008/XfuTAwCgBq1yjOT4CAAYjGZ0i32bwlXSDSStK2lVhS47DefuZ7n7RHefuOaaazajCQAA9GmVYyTHRwDAYDSjW+wOkv7l7k+7+5uSLpa0raQ1YhcgSVpP0qPx70clrS9J8fa3SupNr8/cp9x6AABaHcdIAEDbakZw+W9JW5vZ6DguZKqkv0u6WtKn4jb7Sbo0/v3XuKx4+wJ397h+n1gpbwNJG0m6VdJtkjaKlfVWVCho8NcGPC8AAGrFMRIA0LZGVd+kvtz9FjP7s6TbJS2VdIeksyRdLukCMzsxrpsV7zJL0vlm1iPpWYUDodz9XjP7k8JBd6mkr7r7Mkkys69JmqtQZe8cd7+3Uc8PAIDB4hgJAGhnFi5wYuLEib5w4cJmNwMAMMTMbJG7T2x2O9oFx0cA6By1HiObNRUJAAAAAGAYIbgEAAAAANSM4BIAAAAAUDOCSwAAAABAzQguAQAAAAA1I7gEAAAAANSM4BIAAAAAUDOCSwAAAABAzQguAQAAAAA1I7gEAAAAANSM4BIAAAAAUDOCSwAAAABAzQguAQAAAAA1I7gEAAAAANSM4BIAAAAAUDOCSwAAAABAzQguAQAAAAA1I7gEAAAAANSM4BIAAAAAUDOCSwAAAABAzQguAQAAAAA1I7gEAAAAANSM4BIAAAAAUDOCSwAAAABAzQguAQAAAAA1I7gEAAAAANSM4BIAAAAAUDOCSwAAAABAzQguAQAAAAA1I7gEAAAAANSM4BIAAAAAUDOCSwAAAABAzQguAQAAAAA1I7gEAAAAANSM4BIAAAAAUDOCSwAAAABAzQguAQAAAAA1I7gEAAAAANSM4BIAAAAAUDOCSwAAAABAzQguAQAAAAA1I7gEAAAAANSM4BIAAAAAUDOCSwAAAABAzQguAQAAAAA1I7gEAAAAANSM4BIAAAAAUDOCSwAAAABAzQguAQAAAAA1I7gEAAAAANSM4BIAAAAAUDOCSwAAAABAzQguAQAAAAA1I7gEAAAAANSM4BIAAAAAUDOCSwAAAABAzQguAQAAAAA1I7gEAAAAANSM4BIAAAAAUDOCSwAAAABAzQguAQAAAAA1I7gEAAAAANSM4BIAAAAAUDOCSwAAAABAzQguAQAAAAA1I7gEAAAAANSM4BIAAAAAUDOCSwAAAABAzQguAQAAAAA1I7gEAAAAANSM4BIAAAAAUDOCSwAAAABAzQguAQAAAAA1I7gEAAAAANSM4BIAAAAAUDOCSwAAAABAzQguAQAAAAA1I7gEAAAAANSM4BIAAAAAUDOCSwAAAABAzQguAQAAAAA1I7gEAAAAANSM4BIAAAAAUDOCSwAAAABAzZoSXJrZGmb2ZzO7z8z+YWYfNbMxZnalmT0Qf78tbmtmdrqZ9ZjZ3Wa2RWo/+8XtHzCz/VLrtzSzxfE+p5uZNeN5AgAwUBwjAQDtqlmZy9MkzXH390n6oKR/SDpK0nx330jS/LgsSTtL2ij+fFnSLyXJzMZIOk7SRyR9WNJxycE2bnNg6n47NeA5AQBQDxwjAQBtqeHBpZm9VdJ2kmZJkru/4e7PS9pT0rlxs3Ml7RX/3lPSeR7cLGkNM1tH0nRJV7r7s+7+nKQrJe0Ub1vd3W92d5d0XmpfAAC0LI6RAIB21ozM5QaSnpb0GzO7w8zONrNVJa3t7o/HbZ6QtHb8+52SHk7d/5G4rtL6R0qsBwCg1XGMBAC0rWYEl6MkbSHpl+6+uaRX1N+9R5IUr6b6UDfEzL5sZgvNbOHTTz891A8HAEA1LXGM5PgIABiMZgSXj0h6xN1vict/VjiQPhm76yj+fire/qik9VP3Xy+uq7R+vRLri7j7We4+0d0nrrnmmjU9KQAA6qAljpEcHwEAg9Hw4NLdn5D0sJm9N66aKunvkv4qKalmt5+kS+Pff5W0b6yIt7WkF2LXoLmSppnZ22KRgmmS5sbbXjSzrWMFvH1T+wIAoGVxjAQAtLNRTXrcQyR1m9mKkh6UtL9CoPsnM5shaYmkz8RtZ0vaRVKPpFfjtnL3Z83sBEm3xe2+5+7Pxr8PlvRbSatIuiL+AADQDjhGAgDakoWhG5g4caIvXLiw2c0AAAwxM1vk7hOb3Y52wfERADpHrcfIZs1zCQAAAAAYRgguAQAAAAA1I7gEAAAAANSM4BIAAAAAUDOCSwAAAABAzQguAQAAAAA1I7gEAAAAANSM4BIAAAAAUDOCSwAAAABAzQguAQAAAAA1I7gEAAAAANSM4BIAAAAAUDOCSwAAAABAzQguAQAAAAA1I7gEAAAAANSM4BIAAAAAULNReTYys/dI+qakcen7uPuUIWoXAAAtj+MjAAD9cgWXki6UdKakX0taNnTNAQCgrXB8BAAgyhtcLnX3Xw5pSwAAaD8cHwEAiPKOubzMzA42s3XMbEzyM6QtAwCg9XF8BAAgypu53C/+/mZqnUvasL7NAQCgrXB8BAAgyhVcuvsGQ90QAADaDcdHAAD6VQwuzWyKuy8ws71L3e7uFw9NswAAaF0cHwEAKFYtc7m9pAWSdi9xm0vi4AkA6EQcHwEAyKgYXLr7cfH3/o1pDgAArY/jIwAAxfIW9JGZ7SrpA5JWTta5+/eGolEAALQLjo8AAAS5piIxszMlfVbSIZJM0qcljRvCdgEA0PI4PgIA0C/vPJfbuPu+kp5z9+9K+qik9wxdswAAaAscHwEAiPIGl6/F36+a2bqS3pS0ztA0CQCAtsHxEQCAKO+Yy7+Z2RqSfiTpdoVKeGcPVaMAAGgTHB8BAIhyBZfufkL88yIz+5ukld39haFrFgAArY/jIwAA/XIFl6UmiTazFyQtdven6t4qAADaAMdHAAD65e0WO0OhSMHVcXmSpEWSNjCz77n7+UPQNgAAWh3HRwAAorzB5ShJ73f3JyXJzNaWdJ6kj0i6ThIHTwBAJ+L4CABAlLda7PrJgTN6Kq57VqEyHgAAnYjjIwAAUd7M5TWxUMGFcfmTcd2qkp4fioYBANAGOD4CABDlDS6/KmlvSR+Ly+dJusjdXdLkoWgYAABtgOMjAABR3qlIXNJF8QcAAIjjIwAAaXnHXBYxs7Pq2RAAAIYDjo8AgE416OBS0q/q1goAAIYPjo8AgI406ODS3RfVsyEAAAwHHB8BAJ2q4phLM7tMkpe73d33qHuLAABocRwfAQAoVq2gz48b0goAANoLx0cAADIqBpfufm2jGgIAQLvg+AgAQLFcU5GY2UaSTpa0saSVk/XuvuEQtQsAgJbH8REAgH55C/r8RtIvJS1VmBT6PEm/G6pGAQDQJjg+AgAQ5Q0uV3H3+ZLM3Ze4+/GSdh26ZgEA0BY4PgIAEOXqFivpdTMbIekBM/uapEclrTZ0zQIAoC1wfAQAIMqbuTxM0mhJh0raUtIXJO07VI0CAKBNcHwEACDKG1yOd/eX3f0Rd9/f3T8p6V1D2TAAANoAx0cAAKK8weXROdcBANBJOD4CABBVHHNpZjtL2kXSO83s9NRNqytUxgMAoONwfAQAoFi1gj6PSVooaQ9Ji1LrX5L09aFqFAAALY7jIwAAGRWDS3e/S9JdZtbt7lyJBQBAHB8BACilWrfYP7n7ZyTdYWaevd3dNxuylgEA0KI4PgIAUKxat9jD4u/dhrohAAC0EY6PAABkVKwW6+6Px99LJL0u6YOSNpP0elwHAEDH4fgIAECxXFORmNkBkm6VtLekT0m62cy+NJQNAwCg1XF8BACgX7VusYlvStrc3XslyczGSrpJ0jlD1TAAANoAx0cAAKJcmUtJvQrl1RMvxXUAAHQyjo8AAER5M5c9km4xs0sluaQ9Jd1tZt+QJHf/yRC1DwCAVsbxEQCAKG9w+c/4k7g0/n5LfZsDAEBb4fgIAECUK7h09+8OdUMAAGg3HB8BAOiXK7g0szUlfUvSByStnKx39ylD1C4AAFoex0cAAPrlLejTLek+SRtI+q6khyTdNkRtAgCgXXB8BAAgyhtcjnX3WZLedPdr3f1LkrgqCwDodBwfAQCI8hb0eTP+ftzMdpX0mKQxQ9MkAADaBsdHAACivMHliWb2VklHSDpD0uqSDh+qRgEA0CY4PgIAEOXtFvtpSebu97j7ZEk7SvrE0DULAIC2wPERAIAob3C5mbs/nyy4+7OSNh+SFgEA0D44PgIAEOUNLkeY2duSBTMbo/xdagEAGK44PgIAEOU9AJ4i6f+Z2YVx+dOSThqaJgEA0DY4PgIAEOUKLt39PDNbqP7y6nu7+9+HrlkAALQ+jo8AAPTL3XUnHiw5YAIAkMLxEQCAIO+YSwAAAAAAyiK4BAAAAADUjOASAAAAAFAzgksAAAAAQM0ILkvo7e3VEUccoWeffbYl9gMAADpLT0+Pdt11V/X09DS7KQCQG8FlCd3d3brnnnvU3d3dEvsBAACd5cQTT9Qrr7yiE088sdlNAYDcCC4zent7NW/ePLm75s6dO+isY732AwAAOktPT48eeughSdJDDz1E9hJA2yC4zOju7tby5cslScuXLx901rFe+wEAAJ0lm60kewmgXRBcZixYsEBLly6VJC1dulTz589v6n4AAEBnSbKW5ZYBoFURXGZMmTJFo0aNkiSNGjVKU6dObep+AABAZxk/fnzFZQBoVQSXGV1dXRoxIrwsI0aMUFdXV1P3AwAAOsuxxx5bcRkAWlXTgkszG2lmd5jZ3+LyBmZ2i5n1mNkfzWzFuH6luNwTbx+f2sfRcf39ZjY9tX6nuK7HzI4aSLvGjh2radOmycw0ffp0jRkzZlDPr177AQB0nlY9RqIxJkyY0JetHD9+vCZMmNDcBgFATs3MXB4m6R+p5ZmSfuruEyQ9J2lGXD9D0nNx/U/jdjKzjSXtI+kDknaS9It4MB4p6eeSdpa0saTPxW1z6+rq0iabbFJztrFe+wEAdJyWPUaiMY499lituuqqZC0BtJWmBJdmtp6kXSWdHZdN0hRJf46bnCtpr/j3nnFZ8fapcfs9JV3g7q+7+78k9Uj6cPzpcfcH3f0NSRfEbXMbO3asTjnllJqzjfXaDwCgc7T6MRKNMWHCBF1++eVkLQG0lWZlLk+V9C1Jy+PyWEnPu/vSuPyIpHfGv98p6WFJire/ELfvW5+5T7n1AAC0g1PFMRIA0IYaHlya2W6SnnL3RY1+7BJt+bKZLTSzhU8//XSzmwMA6HCtcozk+AgAGIxmZC63lbSHmT2k0B1niqTTJK1hZqPiNutJejT+/aik9SUp3v5WSb3p9Zn7lFtfxN3PcveJ7j5xzTXXrP2ZAQBQm5Y4RnJ8BAAMRsODS3c/2t3Xc/fxCsUGFrh7l6SrJX0qbrafpEvj33+Ny4q3L3B3j+v3iZXyNpC0kaRbJd0maaNYWW/F+Bh/bcBTAwCgJhwjAQDtbFT1TRrmSEkXmNmJku6QNCuunyXpfDPrkfSswoFQ7n6vmf1J0t8lLZX0VXdfJklm9jVJcyWNlHSOu9/b0GcCAEB9cYwEALQ8Cxc4MXHiRF+4cGGzmwEAGGJmtsjdJza7He2C4yMAdI5aj5HNnOcSAAAAADBMEFwCAAAAAGpGcAkAAAAAqBnBJQAAAACgZgSXAAAAAICaEVwCAAAAAGpGcAkAAAAAqBnBJQAAAACgZgSXAAAAAICaEVwCAAAAAGpGcAkAAAAAqBnBJQAAAACgZgSXAAAAAICaEVwCAAAAAGpGcAkAAAAAqBnBJQAAAACgZgSXAAAAAICaEVwCAAAAAGpGcFnCZZddpmnTpmn27NnNbgoAAOhAl156qSZNmqTLLrus2U0BgNwILkv42c9+Jkk67bTTmtwSAADQiU499VRJ0k9+8pPmNgQABoDgMuOyyy6Tu0uS3J3sJQAAaKhLL7204FyE7CWAdkFwmZFkLRNkLwEAQCMlWcsE2UsA7YLgMiO5UlhuGQAAYChxLgKgXRFcZphZxWUAAIChxLkIgHZFcJnxta99rWD5sMMOa1JLAABAJzr88MMLlr/xjW80pyEAMEAElxm777573xVCM9Muu+zS5BYBAIBOsueeexaci+y+++5NbhEA5ENwWUKSvSRrCQAAmiHJXpK1BNBOjEHiwcSJE33hwoXNbgYAYIiZ2SJ3n9jsdrQLjo8A0DlqPUaSuQQAAAAA1IzgEgAAAABQM4JLAAAAAEDNCC4BAAAAADUjuAQAAAAA1IzgEgAAAABQM4JLAAAAAEDNCC4BAAAAADUjuAQAAAAA1IzgEgAAAABQM4JLAAAAAEDNCC4BAAAAADUjuAQAAAAA1IzgEgAAAABQM4JLAAAAAEDNCC4BAAAAADUjuAQAAAAA1IzgEgAAAABQM4JLAAAAAEDNCC4BAAAAADUjuCxhl1120bRp07TrrruW3aa3t1dHHHGEnn322Qa2rHV08vOv13Pv5NcQAACglEmTJmnSpEmaPHlys5uCQSC4LGHp0qWSpDfffLPsNt3d3brnnnvU3d3dqGa1lE5+/vV67p38GgIAAFTi7s1uAgaB4DJjl112KVgulb3s7e3VvHnz5O6aO3dux2WeOvn51+u5d/JrCAAAUMqkSZMKlsleth+Cy4wka5kolb3s7u7W8uXLJUnLly/vuMxTJz//ej33Tn4NAQAA8iB72X4ILgdhwYIFfUHo0qVLNX/+/Ca3qLE6+fnX67l38msIAACA4YngchCmTJmiUaNGSZJGjRqlqVOnNrlFjdXJz79ez72TX0MAAAAMTwSXGckJf2KFFVYo2qarq0sjRoSXbsSIEerq6mpI21pFJz//ej33Tn4NAQAA8jCzZjcBA0RwmTF79uyC5csvv7xom7Fjx2ratGkyM02fPl1jxoxpVPNaQic//3o9905+DQEAAEq55pprCpavvvrq5jQEgzaq+iadZ9SoUVq6dGnJrGWiq6tLS5Ys6diMUyc//3o9905+DQEAACoha9mejCpMwcSJE33hwoXNbgYAYIiZ2SJ3n9jsdrQLjo8A0DlqPUbSLRYAAAAAUDOCSwAAAABAzQguSzj44IM1bdo0fe1rX2t2UwAAAICOccABB2jSpEk66KCDmt0UDALBZQk9PT2SpP/7v/9rcksAAACAzpGch993331NbgkGg+Ay4+CDDy5YJnsJAAAADL0DDjigYJnsZfshuMxIrpYkyF4CAAAAQy97Hk72sv0QXAIAAAAAakZwCQAAAACoGcFlxoQJEwqW3/Oe9zSpJQAAAEDnyJ6Hv+9972tSSzBYBJcZv/jFLwqWf/aznzWpJQAAAEDnOPvsswuWzzzzzCa1BINFcFlCctWErCUAAADQOMl5OFnL9jSq2Q1oRdnsJQAAAIChl81eor2QuQQAAAAA1IzgEgAAAABQM4JLAAAAAEDNCC4BAAAAADUjuAQAAAAA1IzgsoTe3l4dccQRevbZZ5vdFAAA0IF6e3t16KGHqre3t9lNAYDcCC5L6O7u1j333KPu7u5mNwUAAHSgc889V4sXL9Z5553X7KYAQG4Elxm9vb2aN2+e3F1z584lewkAABqqt7dXc+bMkbtrzpw5ZC8BtA2Cy4zu7m4tX75ckrR8+XKylwAAoKHOPffcvnORZcuWkb0E0DYILjMWLFigpUuXSpKWLl2q+fPnN7lFAACgk1x11VUF5yJXXnllk1sEAPkQXGZMmTJFo0aNkiSNGjVKU6dObXKLAABAJ9lhhx0KzkV23HHHJrcIAPIhuMzo6urSiBHhZRkxYoS6urqa3CIAANBJ9ttvv75zkZEjR2rfffdtcosAIB+Cy4yxY8dq2rRpMjNNnz5dY8aMaXaTAABABxk7dqx22mknmZl22mknjR07ttlNAoBcRjW7Aa2oq6tLS5YsIWsJAACaYr/99tNDDz1E1hJAWyFzWUJXV5cWL15cMbjs7e3VEUccwVQlw0y93lc+H8NTq72vrdYeAPUzduxYnX766WQt0XEmTZrU94P20/Dg0szWN7OrzezvZnavmR0W148xsyvN7IH4+21xvZnZ6WbWY2Z3m9kWqX3tF7d/wMz2S63f0swWx/ucbmY2kDamy3+X093drXvuuYepSoaZer2vfD6Gp1Z7X1utPahdOxwjAQAopxmZy6WSjnD3jSVtLemrZraxpKMkzXf3jSTNj8uStLOkjeLPlyX9UgoHWknHSfqIpA9LOi452MZtDkzdb6e8jdtpp8JNd95556Jtent7NW/ePLm75s6dS9ZgmKjX+8rnY3hqtfe11dqDumnpYyQADKVstpLsZftpeHDp7o+7++3x75ck/UPSOyXtKencuNm5kvaKf+8p6TwPbpa0hpmtI2m6pCvd/Vl3f07SlZJ2iret7u43u7tLOi+1r6qSrGWiVPayu7u7b7vly5eTNRgm6vW+8vkYnlrtfW219qA+Wv0YCQBAJU0dc2lm4yVtLukWSWu7++PxpickrR3/fqekh1N3eySuq7T+kRLrSz3+l81soZktfPrpp3O3e8GCBQWTG8+fPz/3fdG66vW+8vkYnlrtfW219qD+mnmMHOzxEQDQ2ZoWXJrZapIuknS4u7+Yvi1eTfWhboO7n+XuE9194pprrpn7flOmTCmY3Hjq1KlD1UQ0UL3eVz4fw1Orva+t1h7UV7OPkYM9PgIAOltTgkszW0HhoNnt7hfH1U/G7jqKv5+K6x+VtH7q7uvFdZXWr1difS7JpMWJkSNHFm3T1dXVt92IESOYsmSYqNf7yudjeGq197XV2oP6aeVjJAAAlTSjWqxJmiXpH+7+k9RNf5WUVLPbT9KlqfX7xop4W0t6IXYNmitpmpm9LRYpmCZpbrztRTPbOj7Wvql9VTVnzpyC5SuuuKJom7Fjx2ratGkyM02fPl1jxozJu3u0sHq9r3w+hqdWe19brT2oj1Y/RgLAULrmmmsqLqP1jWrCY24r6YuSFpvZnXHd/0r6gaQ/mdkMSUskfSbeNlvSLpJ6JL0qaX9JcvdnzewESbfF7b7n7km5xIMl/VbSKpKuiD911dXVpSVLlpAtGGbq9b7y+RieWu19bbX2oC6GxTESANCZLAzdwMSJE33hwoXq6enRwQcf3Lf+zDPP1IYbbtjElgEA6snMFrn7xGa3o10kx0cAGGo9PT064IAD+pbPPvtsTZgwoYkt6jy1HiObWi22Fc2cObNg+eSTT25SSwAAAIDOceKJJ1ZcRusjuMxYsmRJxWUAAAAA9ffQQw9VXEbrI7jMGDduXMVlAAAAAPU3fvz4istofQSXGUceeWTB8tFHH92klgAAAACd49hjj624jNZHcJkxYcKEvmzluHHjKOYDAAAANMCECRP6spXjx4+nmE8bIrgs4cgjj9To0aPJWgIAAAANdOyxx2rVVVcla9mmmjHPZcubMGGCLrnkkmY3AwAAAOgoEyZM0OWXX97sZmCQyFwCAAAAAGpGcAkAAAAAqBnBJQAAAACgZgSXJVx99dWaNm2arrvuumY3BcNYT0+P9tprLz344IPNbgoAAEBL6O7u1qRJk3TBBRc0uykYBILLEn70ox9Jkn7wgx80uSUYzmbOnKlXX31VJ598crObAgAA0BJ+/etfS5LOPPPMJrcEg0FwmXH11Vdr6dKlkqSlS5eSvcSQ6Onp0ZIlSyRJS5YsIXsJAAA6Xnd3d8Ey2cv2Q3CZkWQtE2QvMRRmzpxZsEz2EgAAdLoka5kge9l+CC4zkqxlueXEBRdcoGnTpunCCy+s+TF7e3t1xBFH6Nlnn61pm3ppZHsWLVqknXbaSXfccUdN2zRSnjG51V6fJGtZbjnvfiTGbjZSI7+HebRaewAAQGcjuMwYNWpUxeXEOeecI6n4CstgdHd365577inqCjDQbeqlke056aSTtHz5cp1wwgk1bdNIecbkVnt9xo0bV3E5734kxm42UiO/h3m0WnsAAEBnI7jMyJO5zPb/riV72dvbq3nz5sndNXfu3JIZiDzb1Esj27No0SK9/PLLkqSXX365ZGYyzzaNlGdMbp7X5/Of/3zB8he/+MVB7Yexm43TyO9hO7YHAACA4HIQkqxlopbsZXd3t5YvXy5JWr58eckMRHd3t5YtWyZJWrZs2ZBmKfK2p9o2eZx00kkFy6Uyk3m2aaQ8Y3LzvF+///3vC5bPP//8kvup9jozdrNx6vW5H67tAQAAILhssgULFhRkwubPn19ym3SwUmobqT7jr/K2p9o2eSQZyXLLebdppDyZ7TzvV54xl3le57xjN1G7en3uh2t7AAAACC6bbMqUKX3jOkeNGqWpU6cWbbPNNtsULG+77bYl91WP8Vd52pNnmzxWW221ist5t2mkPGNy87xfecZc5nmd847dRO3q9bkfru0BAAAguByEffbZp2C5q6tr0Pvq6urSiBHhbRgxYsSg91Wv8Vd52lOvNh9zzDEFy9/+9rcHtU0jffOb3yxYPuqoowa1nyOPPLJg+eijjy7aJs/rnGc/rardKp3W63M/XNsDAABAcDkI2a6ZL7744qD3NXbsWE2bNk1mpunTp2vMmDFF29x0000FyzfeeGPRNvUaf5WnPXm2yWPLLbfsy0Suttpq2nzzzQe1TSNNnjy5IFu03XbbFW2T5/2aMGFCX5Zx3Lhx2nDDDYu2yfM659lPq2q3Sqf1+twP1/YAAAAQXA5CdmzTVVddVdP+urq6tMkmm5TNPOTp/lbP8VfV2pN3mzyOOeYYjRgxomJGMs82jZRkL8tlLfN2VzzyyCM1evToitnGPK9znv20mnatdFqvz329tFp7AABAZzN3b3YbWsLEiRN94cKFmjZtWtFt8+bNK1g+8MADCwqnjBs3ri7zXZbT29ur/fbbT2+88YZWXHFFnXfeeUVZitNPP11z5szR0qVLNWrUKO2888465JBDhqxNKC/P+9Xp+LyimcxskbtPbHY72kVyfASAoTZp0qSidddcc03D29HJaj1GkrkchKeeeqricr3l6f7G+KvWQXfF6qh0CgAAMPwQXA7C1KlTZWaSJDPTDjvsMOSPWa37GwFNa6G7YmVUOgUAABh+CC4zVllllYLlVVddtWibrq6uvhPjFVZYoSEBxNixY3XKKadUDBoJaFpHnverk5FpBwAAWSuttFLB8sorr9yklmCwCC4zLr300oLlv/zlL0XbjB07VtOnT2+5LCEBDdoFmXYAAJA1d+7cguU5c+Y0qSUYrOIZ4KFVVllFr732WsmsZaKrq0tLliwh4wIMEt8hAACQtdJKK+n1118na9mmyFyWcMopp2j06NE65ZRTym5DlhCoDd8hAACQ9fOf/1yrrrqqfvaznzW7KRgEgssSZs6cqVdffVUnn3xys5sCAAAAdIwTTzxRr7zyik488cRmNwWDQHCZ0dPT0zeH5ZIlS/Tggw82uUUAAADA8NfT06OHHnpIkvTQQw+pp6enuQ3CgBFcZsycObNgmewlAAAAMPSy2Uqyl+2H4DIjyVqWWwYAAABQf0nWstwyWh/BZca4ceMqLgMAAAy17u5uTZo0SRdccEGzmwI0zPjx4ysuo/URXGYceeSRBctHH330kD9mb2+vjjjiCD377LND/lgAAKD1/frXv5YknXnmmU1uCdA4xx57bMVltD6Cy4wTTjih4vJQ6O7u1j333KPu7u4hfywAANDasucDZC/RKbIXU84+++wmtQSDRXCZ8fjjjxcsP/roo0P6eL29vZo3b57cXXPnziV7CQBAh0uylgmyl+gUCxcuLFi++eabm9QSDBbBZZN1d3dr+fLlkqTly5eTvQQAAADQlggum2zBggVaunSpJGnp0qWaP39+k1sEAAAAAANHcDlI9SrCM2XKFI0aNUqSNGrUKE2dOrUezQOGDAWo2gvvF9B+DjzwwILlgw46qEktAYCBIbgcpHoV4enq6tKIEeFtGDFihLq6uurRPGDIUICqvfB+Ae0ney6wzz77NKklADAwBJeDUM8iPGPHjtW0adNkZpo+fbrGjBlTx5YC9UUBqvbC+wW0ryR7SdYSQDshuByEehfh6erq0iabbELWEi2PAlTthfcLaF9dXV265ppryFoCaCsEl4OQtwhP3rFOY8eO1SmnnELWchip1zi3VhsvRwGq9lLv/1UAAACVEFwOQt4iPIx16lz1eu9b7TM0ZcoUmZkkycwoQNXi+F8FAAAaieByEPIU4WGsU+eq13vfip+hXXbZRe4uSXJ37brrrk1uESrhfxUAAGgkgstBGDt2rLbbbjtJ0vbbb1+yOytjnTpXvd77VvwMzZ49uyBzefnllze5RagkT8GwVvycAQgXfg499FD19vY2uykAkBvB5SDdc889Bb+zmjE2rZHj/Hp6erTXXnvpwQcfrOmx6rWfPPI8r3q8hvUa55Z3P418DRcsWFCQuWTM5dCp1/e5WsEwxtECrencc8/V4sWLdd555zW7KQCQG8HlIPT29uqJJ56QJD3++OMlT/6aMTatkeP8Zs6cqVdffVUnn3xyTY9Vr/3kMWvWLC1evFizZs0qu009XsO849yqtSfvZ6iRr2He54ba1ev7XK1gGO8p0Hp6e3t12WWXyd112WWXkb0E0DYILgfhf/7nfyouS40fm5Z33FS1bEhvb6/mzJkjd9cVV1xRcruenh4tWbJEkrRkyZJBZ8zqtZ88ent7+zIyV111VcnnVa+xZ11dXQVBYblxbgsWLJAkzZ8/v+Rj5fkMNfI1lPI9t+GsUVVVGzkOMs+4TACNde655/b9/1++fDnZSwBtg+ByEB599NGC5UceeaRom9mzZxcsD/XYtLzjpqplQ7q7uwu6yJXabubMmQXLg82Y1Ws/ecyaNasgUCuVLazX2LOxY8dq3XXXlSStu+66JTNGs2bNKnisUu3JM76xka+hlO+5DWeNqqrayHGQecZlAmisK664omA5e04BAK2K4HKIXHXVVQXLV1555ZA+Xp5xU3myIXnanWTKyi3nVa/95JFkCROlXp96jT3r7e3tuwDx2GOPlXydr7766ortS9ZVG9/YyNdQCs/tsccek1S+S/hw1chsYqPHQVYblwmgsd58882KywDQqgguh0gyhqnccr3lGTeVJxvSyHavttpqFZfrKQnSyi1L9Rt71t3drWXLlkkqn/1NMpLllvO2Z9y4cRWX6627u7ugq1YnVRZtZDax0eMgq43LBAAAyIPgcoi8/PLLFZfrLc+4qTzZkEa2O2lLueV6Sl6bcstS/caezZ8/vyDjmM0GS9KkSZMKlidPnjyo9hx55JEFy0cfffSg2pxXJ1cWbeRzZxwkAABoRwSXg5Anu9fojFKecVP1yoTVK7u5ww47FCzvuOOOg9pPHtngbcqUKUXb1Gvs2VprrVVxWZJmzJhREDzMmDFjUO2ZMGFC33s0btw4bbjhhoNqc16dXFm0kc+dcZAAAKAdEVwOwje/+c2C5aOOOqpom0ZnlKTq46bqlQnL8/zztneFFVaQJK2wwgpDmp3JE8wlbap17NlTTz1VcVkKwUMS4E6dOrVs8JCnPUceeaRGjx7dsM9Yp2bUGv3cGQcJAADaDcHlIEyePLkgg7HddtsVbdPojJJUfdxUvTJheZ5/3vZOnz5dZqaddtppSLMzeYO5eow9mzp1akGV12yGNjFjxgxtuummZQPdvO2ZMGGCLrnkkoZ9xjo1o9bo5844SAAA0G4ILgcpyd5Vyto1MqOUV70yYXmef73aUy95grl66Orq6gu+K2Vk2zV46OSMWic/90bN8QkAANqXlaqa2YkmTpzoCxcu1LRp04pumzdvXhNahHZ2+umn6/LLL9duu+2mQw45pNnNAWo2nD7TZrbI3Sc2ux3tIjk+onGyRd8k6Zprrml4O4BG47PffLUeI8lcDlJPT4/22msvPfjgg2W3Gc5X+uv13Br5GuV5rHq1p5MzXJ1uOH7vBzLH53B8/gCAxlhjjTUKlt/2trc1pyEYNILLQZo5c6ZeffVVnXzyyWW36e7u1j333FN1PrxGBj155HmsvM+tmlmzZmnx4sWaNWtWTfvJI0+b6/W88nR5bbX3HfVRr89QKxnIHJ/D8fkDABrjhRdeKFh+/vnnm9MQDBrB5SD09PRoyZIlkqQlS5aUzF4O5Ep/I4OePKo91kCeWyW9vb1asGCBpDA35FAGUHnaXK/nlVe93vdWDEBbsU2N0OjPUL1Ue7/yzvHZrs8fANAassP1GL7XfgguB2HmzJkFy6Wyl93d3Vq2bJkkadmyZRUDtblz58rdNWfOnKYHPXnaM5AsRiWzZs0q2E+57GU9ApU870e9nlce9Qx2G50pqldmezgGoI38DNVTtfcr7xyfeZ//cHzvAQAAweWgJFnLcstSuNKfDmbKXenv7u4uyAg0O+jJ0568WYxqrr766qL9lmtTrcFTnvejXs8rjzzvaZ5tmpEpqldmezh2n2zkZ6he8rxfeef4zPv8h+N7DwAACC4HZc011yxYXmuttYq22WabbQqWt91225L7mj9/fl/K39111VVXFW3TyBPWPO3Jm8WoJpkLstyyVL/gKc/7Ua/nlUee9zTPNo3OlOV5P1o1KK6Hahm3Rn6G6iXP+5V3js88z79d33sAAFAdweUgvPLKKwXLL7/88qD3lQ1MSwWqjTxhzdOevFmMarLlpidPnly0TSODp3o9rzzyvKd5tml0pizP+9HooLiRXSyrZdzyfoZaqVto3s9QngrIeZ5/3iEDAACg/RBcDsKrr75acVmSbrzxxoLlG264oeS+nnrqqYrLUmODnieffLLispQ/i1HN3nvvXbD8yU9+smibegVPN910U8Fy9v2R6ve88sjznubZptGZsjzvR6OD4kZ1scyTccv7GWqlMal5P0N5KiDnef55hwwAAID2Q3A5RFZbbbWC5be85S0lt5s6dWpfd1Az0w477FC0TSODnrXXXrvicqIe8zjOnj274LlffvnlRdvUK3jKu596zU9ZLTDI856OHTtW2223nSRp++23L7lNIy88SPlex0YGxXm7WDaqKJRU/TPU29urOXPmyN11xRVXlG1Tnml66jGdTb0/Q9Wef94hAwAAoP0QXA6Rp59+umC5VEZSCidiyUn2CiusUPaEbJdddtEqq6yiXXfdtb4NzciTSZWk5557Tv/85z9rmn9owYIFBeM7S2Uw6nXi2+ggLE9matttt5WZ6WMf+9igH6eRFx6kfK9jI4PivN1rG1UUSqqe4ctTNCvvND31mM6m3p+hPBlOAAAwPBFcNtnYsWM1ffr0qid2s2fP1muvvVYyu5eoR3Ymm0EqlUmVwnQsr776aslpWPLKk72q14lvnoBHqk8Qkjeb9rOf/UzLly/XGWecUXY/1113nSTp2muvLbufRl14kPK/jnn2U4/3NU/32kYWhcojWyTryiuvLNomzzQ99ZzOpl4Z+zzydFGXWmtcKgCgMa655pqKy2h9BJeDkC1yU67raF55utHlOUHM042umuwJc6msWk9PT9/0K0uWLNGDDz44qMfKm71q1Ilvnjk+88iTTevp6dGjjz4qSXrkkUdKvoZ5s3J5Ljw0Ut6guB7v65QpUwq6Vpe6QFGv4kEvvfRSxeW8kgsq5ZalfNP01Gs6G6mx2caBzJnJdCUA0FmyxR6zy2h9BJeD0NvbW7D8zDPP1LS/PN3oqo31ytuNrpozzzyzYPkXv/hF0TYzZ84sWB5s9jJv9qoeJ755Ap483RXzyJNNO+mkkwqWTzzxxEHtp14BcV55X8dGBTS77LJLQdfqUtnbehUPuuWWWwqWb7755kHtJ1tdulS16TzT9NRrOhupsVnCPBeVmK4EAID2RHDZAqqd2OUZ65WnG10eSUay3HLebfJqVFYyT8CTZ47PPPJkZpKsZeKRRx4puZ88Wbl6BMR51WsqknppZFGovKp9n8eNG1dxWco3TU+9prORGpslzHNRqdHztwIAgPoguByEd7zjHQXL66yzTk37q3Zil2esV55udFL1E993vvOdBcvrrbde0TbZSrjZ5YFoVHe8PAFPnjk+8+jq6ioIeEoFznkyU3mycvUKiPOq11Qk9WxPo4pC5f3eV/s+H3nkkQXLRx99dNE2M2bMKGjzjBkzirbJO51Ntc9iM7KE1S4qNXr+VgAAUB8El4OQpxJsctJXbjlRrxO7PMGKVP3Ed8MNNyxYfve73120TXLSV265FeUJePJWyq1m7NixWnfddSVJ6667bsnAOTuWNSmSkzZ79uyC5VJZuXoFxHnlyabWszJvtYshjSwKtdFGGxUsv+c97ynZ3mrdlCdMmNCXrRw3blzRdy5p85QpUySFIlvlpqrJM51Ntc9iM7KE1S4qNTrbDAAA6oPgchDeeOONistS/qI/eU7sbrjhhoLl66+/vmibPN3o8gSyixYtKli+7bbbirbJVpDdcccdi7ZpNXkCnjzFjPLo7e3VY489Jkl6/PHHS77OBx98cEGQ9t///d9F22SzNaWykk8++WTF5XrLk02t59QW1S6GNLIo1MKFCwuWb7311pLtzdNN+cgjj9To0aNLZi0TM2bM0Kabbloya5nIUwys2mexFbOEjZ46CADQGqgW2/4ILodI3nku85zY5akumacbXZ5AdsqUKRo5cqQkaeTIkWUzUyussIKkynNztpJGzgfZ3d3dF4CVe53Hjh3bF7xut912JduTJyuZvWhRa+XiavKMcZTyBXPVspJ5LoY0sihUnvcjbzflCRMm6JJLLimZtRxIm/MUA6v2WWzFLGGj528FAAD1QXA5RPJ2U81zYpenumSebnR5Atmurq6C4LJUcJCem3OnnXZqmxO/avNB5p1/r5q8maCDDz5Ym266acmspZSvm269uvLmlWeMo5QvMKqWlczbXbNRRaHyvNaN7qZcTd7vfCtmCRs59yYAoHVcc801fT9oPwSXg5AncPzoRz9asJwtypPIc2KXp7qkVL0bXd7xacn4v+23375scNCOJ37V5oOsVwanXvuZOnVqQZYw2x057zb1VK/nlicrmTdIb1RRqDyvdaOD/WoaOSa13ho59yYAAKgPgstByJ7sjB07tmiblVZaqeJy+r7VTuzyVJdM9lXpZKyeGYp2O/HLE8zU6/XJu59Zs2Zp8eLFZaeN6erq6gsMynU/zrNNPdXrNcrbRbuVumvmea0bHexX08gxqQAAAASXg9Db21uw/MwzzxRtM5AultVO7PJUl8wjTyDb29ur6667TpJ07bXXDpvJy/MEM/XK4OR9nZNM3FVXXVV2PGHS/bhSNdBq29RTvV6jduyumee1bnSwX00jx6QCAAAQXA5Cnm6qeaZsSOQ5sctTXTKPaoHscJ28PG8Xy3plcKrtZ9asWQVjFytlL6u1p9FZp3o8Xrt216z23Bsd7OdBVhIAADSKJSe4nW7ixIm+cOFCTZs2rei2efPmFSwvWrSoIMibOXOmNt9884Jtenp6dPDBB/ctn3nmmYPOODbSXnvtpVdffbVvefTo0brkkkua16A6Of300zVnzhwtXbpUo0aN0s4776xDDjmkae3Zaaed+oJ4KWTm5syZ07T2NFpvb6/2228/vfHGG1pxxRV13nnnlc3wfv/739cxxxzTEoFaHu3Y5k5jZovcfWKz29EukuMjGic7vZjElAwAGqPWYySZy0HIdnHNzkMp5Z+yodW02ji3emm1LpbZizqddpFnOHfXbMc2AwAA1MOwDS7NbCczu9/MeszsqHrue8GCBQXLpbpY5p2yodW0WhBWL63WxTJ5jcstdwK6awLNM5THSABA5xqWZ7RmNlLSzyXtLGljSZ8zs43rtf882b12zQC2WhBWT60UzEyePLlgOZmjtJOQ4QOaY6iPkQCAzjUsx1ya2UclHe/u0+Py0ZLk7ieXu8+4ceN8iy220CuvvFJ026qrrto3FnPevHl69dVXC7oxmplGjx7dVtsk2+21114N22b06NF6xzveoSeeeKJltkleo0suuaRh2zT7vR/un7NW/CzyOWutz9nBBx/c0WMuB3qMrNeYyzPOOKMlx5aX+qyguuS72Wp22mmnptZUKIXP/vDRCZ97xlyW9k5JD6eWH4nrCpjZl81soZktfO211xrWOAAAmqjqMTJ9fHz66acb2jgAQPsarpnLT0nayd0PiMtflPQRd/9aufskV2YvuOACnXPOOX3rDzzwQH36058u2j5PRUiqRqISPh9Ac3R6tdiBHiOpFtt43d3d+vWvf923fNBBB2mfffZpYosAdAoyl6U9Kmn91PJ6cV1V2X/epQJLKd94McaUoRI+HwCaZNDHSDRGtjYAgSWAdjFcg8vbJG1kZhuY2YqS9pH017x3/tKXviQpZC0BABhmajpGojGSc5CDDjqoyS0BgPyGZbdYSTKzXSSdKmmkpHPc/aRK29PtBwA6Q6d3i5UGdozk+AgAnaPWY+Soejamlbj7bEmzm90OAABaDcdIAMBQGK7dYgEAAAAADURwCQAAAACoGcElAAAAAKBmBJcAAAAAgJoRXAIAAAAAakZwCQAAAACoGcElAAAAAKBmBJcAAAAAgJoRXAIAAAAAakZwCQAAAACoGcElAAAAAKBmBJcAAAAAgJoRXAIAAAAAakZwCQAAAACoGcElAAAAAKBmBJcAAAAAgJoRXAIAAAAAambu3uw2tAQze1rSktSqt0t6psrd6rVNox+PbTpzm1ZsE9sMv21asU3Zbca5+5pV7oOoxPERjZP3OwcMN3z2m6emYyTBZRlmttDdJzZim0Y/Htt05jat2Ca2GX7btGKb8rYbaDV8dtGp+Oy3L7rFAgAAAABqRnAJAAAAAKgZwWV5ZzVwm0Y/Htt05jaNfjy26cxtGv149Ww30Gr47KJT8dlvU4y5BAAAAADUjMwlAAAAAKBmBJcAAAAAgJoRXAIAAAAAajaq2Q1oF2Y2RtJBkv4j6Wx3f7HJTRoQMxspaW2l3nN3//cQPdaKkt4TF+939zeH4nGATmVmm0jaWNLKyTp3P695LRp6ZrZFpdvd/fZGtQVoFWa2raRX3P3OZrcFGEpmtqOkVd39kma3BZURXKbEf9J3uvsrZvYFSVtIOs3dl0i6SNL/kzRW0v8zs93d/cEK+1pb0lZx8VZ3f2qIm1+WmR0i6ThJT0paHle7pM0Gsa9Kr5HMbJKkcyU9JMkkrW9m+7n7dSX2tZYKT44HHOya2bslPeLur8fH3kzSee7+fGqbt0o6XtLH46prJX3P3V8ws29U2r+7/2SgbcrR5kMk/c7dn6uwzabuvrjC7dsqPKdxCt9jk+TuvmGJbfcusYsXJC1OPpfV3td6yhMYmdm+pe5bYru3Sdoos6/rUrevKuk1d18el0dIWtndXzWzKe6+oMzrI3e/ON5npKRD3f2nVZ7X7pIuTx6ryrZVP/vltjGz4yRNUngNZ0vaWdINks5L3Xekwvegq0o7Rks6QtK73P1AM9tI0nvd/W/x9o0knazi92vDeHuu789Avmfp98zM3iPpfZKukHRK3GRlSRMl3aXwud9M0kJJH03tY6LC931dSa9JukfSlZW+c0A7MTPzUJHxJEk/knRnc1sEDA0zs/jnbpKKziXRegguC/1S0gfN7IMKJ1xnK5ywbS9prLv/rySZ2TxJ15rZ83G7A9z9M8lOzOwzCv/sr1E4+TnDzL7p7n9ObfOe+Hhru/smZraZpD3c/cTUNhMlHaPiAGKz1DZrSjpSxSd/U1LP6zCFE8beSk8+574qvUZSOAGc5u73p57nHyRtmXqcPeJ260p6Kj6/f0j6QKY9e0uaKWmt+NyT5796arOLJE00swkKZasvlfR7SbuktjlH4eQyeY++KOk3kvaW9Ja47r0KFwP+Gpd3l3RridfnQEnjVZgB/pKZLVYI2EtKv2cKGeTbzOz22La5Xly2+RdmtpKk30rqdvcXMrfPkvR1SYskLSv3uNEMhRPvq+PypHi/Dczse+5+vqq8r9U+G2Z2WZXnv0fcrmpgFG2V+ntlSVMl3a7CAOoAhc/2egonVlsrXABKf17nS9pB0stxebSkeZK2ic9tgcJ7XdRkSRfHti8zs89JqhhcSvqspFPN7CJJ57j7fdkN8nz2c2zzKUkflHSHu+8fL2T9rqDxoc3jzGxFd3+jQpt/o/BZSAKzRyVdKOlvqduPi899sqT9VTicIu/35y3K7zpJH48XDuZJuk3SZ919siSZ2cWStkguvsSLFcfHv/eXdIikf8Xndb/C5+djko40s3skfXuoem0ADWQK/6eWSnq9yW0BhkxyfhQTBWOa3Bzk4e78xB9Jt8ff35E0I7PuRknjU9uapHcqnKyuk9nPXZLWSi2vKemuzDbXSvqwwglisu6ezDb3S9pD0gYKJ5jjJI3LbDNPIXj4h8LJ8jmSZma2uVrSqBzPP8++yr5G8e+7S+z37szyXQoZ4Dvi8mRJs0rcr0fS+3O+Z9+UdEj8+47MNneWuN+dmeXrJL0ltfwWSddltrlJIdj9jKRPJj/xtuT9+WH82TT+/EDSD0o8vkmaLumC+Dy/L+ndmW2SrFGPQsC8Y+q2WwbwuZ6rcBEjWV47rhuTfOZyvK8VPxtx3faSTpP0R4XgYvfY7p+mtlusEJzclWrLlTmewxqS5mTWLVYIHO6My++TdPEg3vsNSmyzQWb5p5J+ppAN2yL5KXG/1SV9RdLNCoHulzOfq6qf/WrbKPSEkELwtHr8LN1Xoi3nKQRm35b0jeQns83C7HdGqf9VkhYlr3V23UC/PwP4vCafxUMkfSv7nkm6t8R97o2/vypplQr7/pCkqYNpFz/8tMqPwsXaqfHv30raJv69kvqnmBvR7Hbyw0+tPwq9VE6Lf58q6cuZ263ZbeSn+IfMZaGXzOxohczWx2MXuhXibV+StGKyoYdP9aNx8dXMfkZ4YTfYXhUXTxrt7rf2Z/slhSuQaU+7+19V2Vh3n2Vmh7n7tQoZ1dsy2zwo6Rozu1ypK5xe3OUzz74qvUaStNDMzlZ/JqVLocta2pvu3mtmI8xshLtfbWanlnhuT7r7P6o8/zdjVmk/9WegVshs85qZfczdb5D6uoC+ltlmbUnpDM8bcV3aaHc/slQjvL9b8I7uvnnqpqNihvKozPZuZk9IekLhfX+bpD+b2ZXu/q24zQNmdqzC63e6pM1j95D/lXS1mf1IIbuWfk9LjTtb392fTC0/Fdc9a2bJeNjkff2CpO1KvK8VPxtxnczsFHefmLrfZWaWfv+T7o5LzWz1pC0l2pz1isJFlrT/uPt/zExmtpK732dm783ez8y2SF4XM9tSxe/9RQrBYtqflcq2KwQlkvS91DpXYZZU7v6imf1Z0iqSDpf0CUnfNLPT3f0M5fvsV9tmoZmtIenXCgHmywqBbNY/488Ilc8cvmFmq8TnknQzT2dBXo+fhQfM7GsK//NWK7GfPN8fmdnKChcpPqDCDPiXCjezjyr875gR141M3X53if8xd8f9/LzM80we585KtwNtYltJnzOzlxS+j6tLkrunv7tle5IAbaRX0rZmdqJCj5SH0jfGc6mkizhaBMFloc9K+rykL7n7E2b2LoXurfLYzTOnOWY2V6E7aLLfKzLbPBNP5JKTuk9JejyzzXHxJGq+CgOIi1PbJMHB42a2q6THVNxt4N/xZ0WlAuQS8uyr7GsU/bdC9uDQuHy9pF9k9vG8ma2mkO3oNrOnFIIHSQVjBBea2R8lXaLyz39/hUJLJ7n7v8xsA0nnZx7vvyWdG7tUSNJzkv4rs815km41s7/E5b0Uxo6m/c3MdnH32SrPzGxbd78xLmyjzIUFMztM0r6SnlHofvpNd38zOYmX9K3YTXp/SbtKulLS7u5+u5mtqxBIJON904FcUbATXWNmf1Po7iiFjOs1Fsa2PR/XJe/rjDLva57PhiStamYbehyPHN+PVVO35wqMMt1sRyh0o/1TZrNH4r4ukXSlmT0nKTtG9HBJF5rZYwoZvnfE5yoze59CkPNWKxx3ubpSgY8keeySWYmZ7anwuZqg8Hn6sLs/ZWFc498lnaEqn/2o4jbufnD880wzmyNpdXe/O9sed/9ubNdqcfnl7DYKXV7nKIyN7lY4af2v1O2HKfTOOFTSCQqfr/1K7CfP90cK3837FLL231MIDLMXkA6XdLSkv7j7vWa2ofq7dEvhe/HfsW1SeJ1+md6BmZ0r6TCPY69jF9tTMkEs0FbMbFV3f8XdTzez1xTGW75P0tvNbIbC/7gnFc7t7jOzUznpRjuKFyKXx/O6T0k6U9I0Sf82sxsUjksrKFyg7jGzH/BZbx3Ge1HIzMZJ2sjdr4onhSPd/aVB7GdvhXE+knS9u/8lc/uGCmMEt1EIdv4l6Qvu/lBqm98pHDjuVaoQT/oEycx2Uwjg1lc4eV1d0ndzZDxLtTnXvmp9jWJQ8x+FA2GXpLcqjCvsjbf/psLdfbAniDFTJi9T6TdmtZL37Dp3vyNz+0sKgdLrCsFW0RjQuI9z4nMyhff2S+mMopl9V2FMXlGxHDN7v7v/w8yuVRhXeaG7v5bZ5osexknmfd6mEFBuG1fdKOmigfwjHsBnYyeFz/WDCs9/nKSvuPvcEvscrzKBkZltn1pcKmmJuz9SoX3bK7zmczwzxtDMVlAYEyilqhfHYHAvha7n6efxkqQL3P2m1D7eqhCIbRdX9RWFSm3zW4X3tVTxqqnuPr/aZz9uW+378QlJC5LHjgH2JM9U0LMwFvF89V8EeEbSvu5+b2a7sQrjVU3Sze7+TLb9eVT7/sRt7nD3zc3sbnffLL4317v71iW2rRQUV2vLHZkeBCXXAe0i/g/+jML/w98qjFWfrtBV8GKF8wQpDCFYR+F/0T8b3U6gVvEY998KhQevjxdTxisMuxkvaU+Fc4sJkl5UGBbx9+a0FqUQXKaY2YEKY6TGuPu7LVRKPNPdpw5wPxtIetzd/xOXV1EY8/ZQiW1XVehGWxScmdn97p7t5jdgFoqxfEvFXdFKZbmq7avia2SlC9u8oNC180SvUlQo81h9GcDsujKP08cLix59X9IPM1mMI9z92My+6zZdS5Il9eJCPHV7rJhBzL6n3yt/j4r72lohaHy/QnZ7pKSX3f2tFe9Yel8rKVwUkcJYwNfN7H2x22rJ6SQywfdISVdVyxbG7Gqpff3bclaCjfv5qLuX6laafqyLFIpCJdm4L0r6oLvvPZA214OZ3enuH8qsKxVM3STpGHe/Oi5PkvR9d98mtU3JQFUhWD3cyhRq8ligKfN4VT/TZnaru3/YzK6TdLBCt/BbPVXl2Mw2VciEjlEIeJ9WKii24krJyWOl93FXfA7PxeUxkq51902z7QZanZl9QKEH0+cUxravpnCB8wSF3i37Szqh2v8xoNVZGNryJ4Ux969L+rnCxd+fKwzvOEfSDe7+naY1ElXRLbbQVxWK7Nwi9Y15W2sQ+7lQISOZWBbX9VXAzBnw3GRmG1e6ImMVKpimNutWKLKym0IX0v0UTtiSfXzL3X9oZmeo9InkoanFaq/RFfH5/j4u76PQfeEJSU+aWXZ8avpxVs+sOkPFY+GSdbul2iP1d4X9QonnsLPHSr/xcZ4zs10k9b3WVjhdyzL1V+IrmK7Fqk99sZJClnC8pFEWx9Smgz4LY9eOV4mpYSoEzQWVgs3sTIXXdbJC19pPKVPdNvV4earu/kzhvbpQoavtvuqfqzTJtJ+mUFV0uUJX1q976el4tlT/5/GD8TX4uMLn9JQS2xd05/VQ6XS5mb21XHAeXR7vawrvxwYKRbA+oByVYJPPvaTPWxi3W7hR4ef+3e7+ydTyd83szrxtNrMb3P1jMfudtLnvt7uvnrqt6O4qfL+y47el0v/LV00Cy9jGpCt02nGe6lXh7s9bqOh7QFz14xL7LW5gzu+PpLPid+jbCicMqykUkUr7lULhoXRQ/Gv1/0/NUyn5FIUpo5Ku4J9WKJoFtKNVJV0RvxNXWxhusbvCxaNj4kWh0y1M+XOD1F9hE2gzKyj0srklXpj+lML/84Pd/QQLFcEvNrNR6fM6tBaCy0Kvu/sbSUBgZqM0uEHxo9Jd8+I+s2MdqwY8Cl3V7jSzfylcwSmaikRh6o3rJV2l8ida1Qr1JGOesoV3Sqn2Gu3g7umAcLGZ3e7uW5jZF9x9UzM7QWF86fnq7/q3TnIHC8U8tpG0phXOj7e6YmEPL19A50grLqAz0kLBl9fjfVZRqKqXdpiqTNdi+aa+uFQhU7tI5cvDH17hsXYrsa6UbWK3wrvd/btmdoqKx/UmfqgwZrNicSR37zGzke6+TNJvzOwOhbFvUrhY8HOFAjVSCET/IOkj6X2Y2fmS3q3w+iSfR3f3A+MfeTN7Lyt8dq5U4XjDQ1N/F2ShYlb04HjbcfH3/hUeYyCf+zxFocq22d0/Fv8uOyVHpdsyFprZTxTeDylcYFlUYrsHzezbKrzwkr0YUDJQdfdkf2MV5u6sNtVB1e+PJLn72fHPayUVzckaVQuKX3D3cp/15D7nWSgklXw39650kQ5oRWa2soceUP+U9GEz+5y7/8Hdb7JwEP60mW3l7r+Oy0sIKtGOUudoSxSOzZPM7Fp3f8jMjpB0iZn1uvsvYo8btDCCy0LXmtn/SlrFzHZUOFG9bBD7edrM9vA4Hs3C2K7sOKY8Ac9OOR6rbAXTlIrFWNz9svi7VAGOrGqv0Ugz+7C73ypJZraV+is9JtVw93D3D6bu88vYjS3JYKyokNEYpcIqly8qZOjSzKoU0FHI3M63/rGc+6u42MjDCkFhJYcpZJ9vdvfJFgrCZLMh67l7tfet7GN5iXGYZSSBzasWivz0KhWgZ+SpuvtqvAByp5n9UCH4T7+Oo71wnOfvzOybJfYzUdLG2RMcK9M9NeGFRZqkMIYou64iDwWPPhIf7xtVtv3JAD/36aJQJulZFReFytXmGAR/TOGizA1eYmxi3G4tFWbIky6mhyhk/v4Yl69UfwY/7UuSvptq0/VxXVq1QHV3ST+10I31jwpjWrNVraV8359y78sLCtOb3BmXqwXFVSslm9n57v5FhUJK2XVAyzOzKZI+aqEoT2/8TuxpZs+7+xUehofsqdAT6TZ3P6u5LQYGJ56XTjSz77v7S2b2T4Wkw1Nmdl8MMA+VtJ+FCurMU9ziCC4LHaVQ+n6xwlx1s93914PYz0EKVR5/pnAi+rBCN8O0qgFPKjtXcJKZkaeC6YnxpPgI9Rdj+Xpyo5UZV5VqR3p8VdFrpNAtM3GApHMsFOMwhYDwgJh5ODlu84qZdSnM8egK40jSmZ4ku/rbHMHWjPh4BQV0Mu2faWZ3S0rGzp7gxQVm8kzXkmfqi5vMbFOPE7yXUfWxrPQYyFdSXSP/FrtC/UjS7QqvY7nPap6qu19UCCa/pvDZWF/SJy2MVZOkK8zsKPW/Z59VeO+z7lGoyJqtfJx0T11LISu9IC5PVpg/tCAoc/dz4wWXd3mZSs2ZQGWEQnfpx+Jy3ixg0rX8SIWKtCXHJMfA54NWoShUniDVzL6j0EUzeb6/NbML3f3E1DZ7KHQDWlehEt44hSu5H4iP84oyU9uU4mG84aFVNqsYqLr7/haK7uys8D39uYXpcg7I7CfvdEcT409yQWo3hWlEDoqvww9VPSj+SGpffQ+lwh4EH0g/qIXxoOmpZYCWZaEw2vclHR6/71IoxLaWpC4ze3u82HefpK3MbEXPFDID2kH8rJ+kMMzmTUly959aKHx4hEK19ysVekStqXCsX15uf2gNFPRJsdBt9LRq6wawv4rVDuOXaoe4eGU24Cl3kunuH0htk6eCadK1plw7k8qceysEBsn8cZ9TyHp9veQdK7AKBW2sv+rXtgonhTcqHEQfymx3tUqPAS0qRFTp8XK297hS6z1O5xC3+YvCRYDDFU5kn5O0grvvktrm7woVzMp2Zc75WAtVYgykux+dvZ+FcZ4rl3vuVrr6rnsclxtPvM9z964S9/2X+scGltrHhpntr1aYE/JWFQYZe8Tb50naz90fj8vrSPqtu0/P7Gd3hfF+K7r7Bmb2IYXqrHuktkm/jksV5r+6qNJnvZTYpj9K+h+lxiS7+5F5MqCp/WykcAElG6SmC83cr1AIKF3s605PFe6KWfwpCgWCNjezyQrZu5c8R5GdAV4syiUGmDspfP63c/e3Z26v+pmO210naZfkf2L8H3l53Pcid994oG3L7P9ohXlgV1GYfzj53L4h6axS3x+glVio8rxI0mfc/dJ48Wukwvna4zFb+cO4zfYKQ2yKKm4Drc5Coaq/SPqBu59jYTz+BIXj70Nm9gWFOg8bKyRFZjhzFbcFgssUi2MDM+vu8Jzl6y2MKfxduRPS7FV8qzKlR7mTTHefoQEwsx6FQhvXx58bygR9C919YqV1VlypMQme0ifQdaliamFqg8TKCoVylrr7t1LbFBTQST+eFRdR6bubigvaDLRtJae+iO9pkRwZ2Oz+F7r7RItTNsR1fZ9FC3NAHaxU90pJvxxoYJV6vBskTan16rcVTiHSJ2ajZWb/cPf3p7YfoVBG/P3p7c1skcJn/5rUc77H3TcZYHuSQkRbK7xORYWIzGyRu2+Zea1vc/etUkHTexW6RCdTluyuUOX0C6n93KBQ1Oan8fb9FSpBfye1zdWSPuH9hbzWkHRx+oJJ6r2/S9Lm7r48/v0ld1+U4zXOfbHIzN6jEFSPV+H3Z0q8fWeFLPUkSdcoVPGb56W7xlZlZvdJ2tT7p4NZSdJd7v4+65+mpGp162r/Y8zsZAJJtCML1eaPUuh6/weFC8yPKvQe+G93vziehL9D0vPJhTqg3ViY6/1ESfMU5mI/TmGIj8flI+KmGyhcXH2yGe3EwNEtVpKFSpGfl7SBmaXnu3uLwj/4vJKiE1W75FlqSg+FdP87FSaJTU978qaHsRYjLPQzv9rMTo33zz21g7tPsDBtw8cVypb/3MK4jQ9l229mGyYn3vEgl60uWbFSo+WoYhoDoxkqPjnMdmfNFim50cyyFVHLFtDxHEVUUm2qeEIbs3v3uvv74vprS+3Hc3RlznPyrOpjIM9TmI/xjLj8eYUxap8u8Xjrxe2SeS6vV5hgPj1v5IMKr+9fVdhF+SdxH9lu3cnt52WWS74uKfPNbK7CSZMUAperSmz3pru/YFaQMC3oClMmQ5dMe/OrGGjnKURUdkxyknmLGbctkos/Zna8QsYtbRUPc1la/BwcH4Pk71h/JeYXJN1roZuPS9pRxVV+n48ZvesUutc/pdAlelFsU8XXOBVknpK5WHSZhYx42oUK/3fOVumCYPsqZHW/4hWK+uT8TEthOMAtZnZpXN5d0u8tdJv/e2qbStWt81RKPiZe9d7AQ4XB9SWt43EsONCqPEwa/yOFLu2LFConnxEv9HSbWU/MVD7X1IYCNYjHyX9aKPB4pMLF21Pd/Swze79CDY6PeJhvuqeZbcXAEVwGNymcvL9dhVMlvKQwHigXd/9V/P3d7G1WXC02z7QnJU8y423fUAhOq07tEIOLbRWCyw8qTLZ8Q4n7fV1h3NSDCtm9cQrjKtOqVWrMU8U0GSsyXdL3FAZuFxWcsf7xflIIrLZUyBam5Smgk93vGpK+6u4npVZXPKH1MNXE/Wb2Lq8wmNyqjJfL81hRqTGQ6aI4m2S6EF5toUtuKb9RCLKSwPMLcd2OqW3+GX9GqPTFka1Sf6+scBHkdoUgt49VGSvq7l+zUOltu3iXszw1FUbKvWb2eYUCURspnGjdlNnmQYUxGOlA9SWFKVR+rfAa5ilEVHFMcrS2QtfKxBtxXdrrMRP7gIXpZh5VKEwl9VekXaTQDShxjYrtKek/sQ1dCp/5dFauavfbKM/FoqXu/ssSbUj2WTRFSxl5PtOKgd4V6r/QcZC7J69N0i27WnXrPP9jfq5wMWKKwlyAL8d1WwloURardXuo3P1jSfPd/VJJcvcrzOzPYrwZhgF395g0+buZnaQwXOTCeNs/4oXl7PEK7cLd+anzj8IJ4/jU8lYKXb/S29wSf98Rf4+SdHdmm1UVTs5HKZysHapw4jXQ9ixXCGL3zLHtSgoB6AclrVTi9h8oFJH5qEIBlS0UMjrZ53WzQoC1kqSezD6S53x3/L2CQgXW7GP9SyGA+JekBxS6Tnwss81ZCt3sSj2X9ePtf1MoNLSqQuD3tKTTMtsuSrcp/n1bZpvrFIKX+QrdI/8q6a+Zbe5SmL4heY6TJc0axGMdVuL5HJb6+3eStk4tf0Rh3GSp1+HOPOsG+JlaQ6FLcHb9QoUxE3fEz+7+kk7ObLO2QsZqN0lrldn/aIVB/rfFnxMVxpWmt7mtxP1ui7/vU8g+zlToYjZeIdD/VrY9OZ/vMfG9PT7+3CnpfzPbbKUQTK6nELxfnH6PBvGYq8fnMEbSmNT6GxSC+7vjczpeYTxq9v47KXQtukZh6o+HJE3PbHO8Qvfqdco81tbx9X9ZIaBeJunFEo9V9TMd172r1E9mm5vj77kKPS02l/TP1O15/sfcHn/fkVp3V7Y9/PDTKj8Kw2KS/4+Tk3XqH770+fg/aL1mt5Uffmr5URgukl1nqb8/oXAhdlyz28rP4H7IXKZUy7oMwMmS5pjZ6QrdXXdWOMlOu9aqTHvi/VXipOKpM9Lt3kbFY6bSGaXNFcbmfd5Cxc8HJF3r7rNK7G7L1L4+aGbZfVWr1JinimnSDfF5C8ULnlCoglfA3Tco0b6sj0n6Lys9F+h5CifVFymcaC9UCAo2dfcnyrSp5HQt0bdztKdsV+YBPtZ+CmMF0/4rtW5Lhcq0SRb1XZLuN7PFKp4LtTd2EUwyfJ9TGNfQxwZQPCl6RWXmKfQK82Wa2WcUPhvXKLxXZ5jZN939z/H2lRUyXxMUKhJ/1MuP71stnUmOXb+TTOEGCu930q82nYF3SUenuqqW5IVzap5kZnMUPm+StL9nphBx9yS79rKKv++KbdxNIZOWHbOcLsD1FYVqqf9RuDBksZ3J6122+22mPXNilvN9cdV9Xty1db/4O53NTT/Wz1SisFSJp5bnMy2FrsTJa76Kwvt0vwoz+6UyyYenbi/1PyZdsVqS3oxd2cNZS+i2S8YHLSn5fxm7b18k6VtmNtrdXzWzURamcjpGocjPI5X3BrSeeLxySfJQR+CtCseZgxUK8c2J2x2oUMX88z7AWhVoHRT0SbEBVOjMsa9JCmX9n1EoyvFE5vYRCuMOpymcPM6VdLan3pB4QJmpEHiZSp+Ilpu0vmAKgti99mMKXWO/EDcal9km177ysjJVTM3sAIUD6GYKGZ7VJH3H3c/MbLeCwvyCSRfKaxTG0r2Z2qbgOSTcfYmZ3eWp+TTN7BGFLEnRSWY86b9eIduZnNB+1+NcpQN4zldJ2kvhAsPbFbrGbuXu2+R5LOsf//uxuE3iLZKWu/vUSs87/fxTjzcuPs5HFU62b5J0qKe691qV4klWOL5xhEKXzD+5e8GUGBbGJu6gcLL/hEJ38/9K3gcLhWl2dPen4vKaCgWrktv/qBCoXK9wUeYhdz+81HM0s10Uxgv+U+G7sYHCgeoaSQe6+6mVXiMz2y+1+F2FYgJ9vMTUIlZ+7slcY0AtFNfaW9Li9Hc98xgPKATV2blxk9tvUvh8/FlhSpdHFartZafFSSpPZrvPnpfdrhyrUlgqtd2gvj8Wxowf7MVTm2S3O7zU+1nhf0yXQjfpLRQuzH1K0rEeu10BrSIVWK6nUDDrFIWeH99WqHz8hMLF0fvc/V/NaylQOwtF9tZT+JxfoXDh9yvufkm8/QOS3nD3B5rWSNSM4DIl74lUjv18W9JnFMZEbqYwduoId788s121efx6JO3u7kXjEVPb/EMlJq3PPi+FrmM3KVaMLXVFqNK+LGclXKtjFVMzO1uhy2xykv9FSctKnYiWOumPgcwk9Wevrk4vu3uuYk1WXG227yYVB/urKmScTP3j5brdvbfE/Us91jiFIOlkFc5l+JJCl8Olme3LBju1slA86fMK3bTSvRyWKjy/x939nyXa/5TC+/Z1hef/C3fvibcvdvdNU9uPUOiuuGn2djMbpVCRtWTRqrjNSurPzN2f/ZxZzkJE1b7nVjyW9l0KJ3vpaYFOU/EY0BcVPjuru/sXY4Z4aqkLHKn9zJG0t7u/Wub2rRTG8a6hkAV9q6QfuvvNme2OU/i8b6wwJ+nOCpWiP5XZrmwAWu1iQT1kPxNltvm3CrOXRbxw3laZ2fsUug+bwti1sv9HgWZIsjkxY/knhWz8HQrjsr8z0IubQCuzUAjvQwrDNa5VGPY0S9KnPRT36ctuor3RLbZQtQqdeY2V9GF3f03S/4sni2crVV0ynqz+SKH77QZWYh4/hWkDqp0QlZu0Pm1ndy8qrjHAfeWthFu1iqlVmD4ks6+tMiexC2LA2KfESf849RfQeatCv/10ydGkiq5L2jBP10jPUW02tX3VrswWCqscouLnv0cM+pcoZBnLqvK8k21yd/u08sWTTpV0tLsvzjz+pvG23TP7TC5avKaQDcyaY8XVYmenbu/LSrv7UiusFlvKRgrThKys0t24cxUiUoXXKTpBYfxhdu7JtG3cPf14l1n/lCb3xnXfkjTbzK5V4Tyg6WmKjlbo8nxLZptD4++q3W+jTymMnb7D3fc3s7XVPy2JpPIBqPpfny8qDA9IF5b6ZOr+uT9jcfv0xakRCpnFxyo8h767KvNZyz6UwhjX9GPfJ+k+M/sygSVaRSqgHOGhe+BYhe9bkrG8UNK33f0yTrYxzMxW6LX2qLs/a2YnKyQf/imFK/VNbR3qhuCyULUKnbl4mOh8FTN7r7vfH0+4d8xsdpxCtdhr4n3ujEFH2sLYTfASFZ5kXpzqgvcWSX+PWaaCSeuTbKOkL5Y6Sc+c0EqhG2fJfXmFSrgZeaqYlp0+JGOZmb07+ccTu1Nkp0soe9Lv7uOrtFXqr+JZk4FkNxXez1kKY2yz02vk3U+eYCf93Iq6fWYsio9rCpnJfyl02/5pNrBUaMhiMxufavfiMu1Ott8s/v6mhe7eydjFbLXYD5rZi8luFcYkv6jSWeJqgZHc/ZB0OyyM1bugXDsryDOWttIY0KTS7EkKQeHKCheWSvmVQnfXxSoxTtDMJiqMv0rGbUrqf41TXosnr0vNbHWFixDrZ7apGIDmuFgw0O9P+kLNUoULbhfluJ+7e6VAupKDFAp7AU2XOoF+v0Ll9tEKvVSeVDg2fNvdL8tsC7Q9T00FFXsmbaDC6ukYJgguC+3l7qcpdGtM5rc7TMWFVSoys90l/ViVs5Kl5vHLHkhWl/SqwrjM9DYXK1QqXVuF4/KkMKYyyTzmnnczOr7aBlZ9UvrbzWzrpIuemX1ExSegeacP+aZCcJrse7yKMzV5TvrT7T/e3Y9Plj0zrs7C2FS5+8s52tdnINlNSf9x99Nr3E/V551+bhbGrJUtCuVliifFYKycVVJ/75av2ZJC9+xlCoFTeooJufvIAeynamauhFcUDmjZQH50JqjNXhB43spPC5Q4QtINZlYwBtRCV+nktV/X3Tep0sYV3L1k9/OoW+G7UTL4TFkY379fK1w8eFnh+5pWMgAdwMWCcyXJzD7tmfGMZlY056qkv5fZ7sIqF1ZWsZxd88vcH2gZZvYlSTPMbEd3f9jMHlcYCvG/7j67yt2B4eDHCsdZ5h4ehgguC1Wr0JnX8SrOSmYra+aZx+9sd78xvcLMkvnh9lTp7orPSvq+wvQXebONittdm2OzkpPSm9lohRPDFVRcxfS+zD5uMrNNS2XE4nPYStLDHipibqQw4HsvhalI7spsnuekP20PlQiiLYw7O1+hwqWZ2dOS9nX3e7PbVpLpXpp4yVNFiCSdFrNu81SYIb696J7lJc/7euV73uWKx1TLzC80swPdvaDir4WiTIv6dl5cQGgjd7/KwrjiUZn7fUchM5dUi/2eu59TpR2lVM3MWWGRnZEK2YI/xTYP5ILAngrZu5JzT8b9zbbC6qzpMaCnxt+zzWyau8+r8FhXmNmXFTLb6c9HMkb4ac8xFsvdD45/nmmha/7qHiZfTysXgB5fbf8ZRyt05xv0umrvh4UqulL+i2WJSt1pgYZJusIqDD+Z6XFctYchAMe7+yt0hUWH+IVCb7n09wLDBAV9JFn5Cp2rKxSQmTrA/d3s7ltbqkiIpYoExeXRCl3bkqzkXEknpk5GZWa3e6aYSbLO4liuMo+fLZqyskIXxw+osGjHl+LtAylYU/A84rq7FIK2sjLBx98VppooNX2IzOx2STt46JO/nUI3xkMUBoK/31MFSWyABXSsTOEWCxU4j3H3q+PyJEnf91SV1zzM7CGFAOe52KY1FAqhPKlQwXSRhXEGX1Socpr8Q3UvP+1HqccZrf7n/QWFz2q3lylSVOqzFNf/Jv65lqRtFII+SZqscLFjhkK3lTfUH0xOVMjKf8KLqyAfqFDIaoy7vzsGW2d6f5Xb+xXGJvbG5bGSbvISlU5zvAa/UKimuI9C1vBlhfk7909ts33qLkslLfFBlPKP2bI/uvujVbarOC1Q/K6tqvC5f1Olv2OlKkK6u28Yb5+qMJ3MfGW6y2fasp1KcPfr4u2m0Ivg4bg8XpkANH6/kiD+PQqB8xXJxRIz21nSLgoFzP6YepjVFYqDfXgg29WqXFYzUSG7CTREvNA8S9L/uPui1Lp/e/lpl4Bhh6By+CJzGdyk0JX07QqD6hMvKUxUPlAVs5IW5l+73N0nKwSYBczsowon+mtmTpZWV8i+SCFoKWeVzPL5CtnD6QrZli6F4i+SBpzBucLCXJkXKASkSUGWl+K+njWzDyp0z5VCZdpstnHnKo8xMhUkfVZhXN5Fki4yszvTG3rOuUBTylUeXTUJLON+r4kn1gN1paQ/u/tcSTKzaQoFUH6jcKXuIwrFjTZ09zfK7qWMMhcCkm5/34ldMo+JWd+q3T6TQMzM5imc5D8el9eR9Ft3f1LSNhbGdCbdOS939yQIzfqqQtb+FoUHecBCRdtEr+JnJXpJmTk384iB0cnu/rwqZObc/Voze0dskysE9IPxFknzYs+APypk2p7MtKnkVD4qHANa9bvm1ed33V8hyFtBqYsTyhS0UeHclSsrvAaLFOekdXc3s9mSNo3LD5V4rOskfdzM3qaQab9N4TvZFW9/TKHb+x5KZbIV3tevp5bzbldVlYtlA81qAg0R/2eNUvhenqNQOPADCt1hlygU+KtbtW+g1RFYDl8El+rLqvVV6IzZlO0kvTzIK4mHKASNrytUxZyrUIAlebxlZrbczN7qmfnZohUVCoGMUuHJ0osK48ykHN0VzWxUbP8Ed/+0me3p7uea2e9VPFYzr8/E31/JrN9HkluYjuFA9Z/o/s7MznL3pHpsXxbTMtNopIxMtX2qQiYsMSreNwmcTIXBVqlM0FsVuvl9PC5fqzAGNv3aP2hhCpnz4/IXFMpkD9TW7n5gsuDu88zsx+7+FQtVcqVQlXcNhW6cA1IpOIkXLTZRGJO3yQAvGqyfBJbRkwpdmpPHvVphKpdqXnf3NyyOJbYwaN9TF0l6JN1iZpcqvG97ahAXcHIGRnXrhuuha/l3zWwzheDqWjN7xN13SG02UdWnBaqYTYzbjJb0DYVpir4cL1C9193/FjfZKk+m190LuoNamO7g1Mxmt5vZVt5fgbaoyR4mcp+hMKXMD9MXeOKFo7vi/xST9J540/2e6gru7neZ2T2SpnuFsb85VbpYNrvCcwGaJv5feNPM3qJQ5Xu+wsWauyT9QKHbPQC0PYJLSWb2N0lHufs9MWNzu8JV9nfHwOjUgezPwziKY1QiK5nysqTFZnalUmPlPEx9ca3Cyetv3X2JmY324jnvDpf0FwuThRd1V4zLtypk6pKTvOctjC18QqEb5IBVy6qY2d2SPpJkFM1spsIYrjNS21SbRuMPCs//GYUD7vXxfhMUqswONNt6jkJAlwTGX1TIJKbHG35JoYjTxQpBz/Vx3UA9bmZHqr8i6WclPRkDv+Qq3RoKUyTcpkxV3kE8Xh93X6Zwon9G1Y2LzbfiKUKuGsR+rjWz/1UowLKjwpynl6n/Isk/VZg9vHQQj5GoFhhJIUuwebYbrsJnYjCeUvj+9Kr4O5RnWqCK2cToN3Fd0iX7UYVxiklweZOZbezu2SrM1TyiMOY07SOSvmChO/crynRRV0i4fFQhgJsR15UqurSNQob2obiP9c1sv3TQHC+qrW9mKw4ma59S6WLZWRbGIl8g6Q+DeI2AIWNm71XouWKSfijpSi8cjw8AbY/gMtjA3e+Jf++v8A9/33iF8UYVX+0vycwqFtnIBA8Xqz+7l2Q6slUN1zWzKxSymO+K3U2/4u4HD7C74lmxW9uxClVmV5P07TzPKSt2STtYYXxqEoSd6f1jRU2F04UsK/G8Kk6j4e4nmdl8SetImpfKBI1QyAonbRkp6V53f58qe7e7fzK1/N0k+xKfz0EKY0AXSzqixoP95xWm/LgkLt8Y141Uf3BbaUqQmnks5DTA+3zNQnGfpDtzdoqQvI6UdIDCa/kVhS7TZ1fK5tXgI5K6zGyJSgdGUv264R6s8P6tqRDoHVgicCk7lU/q7zzZxHe7+2ctjAVXzBymv0NbK3SpKzlmObXv9ByUIxTGLN8eb0umTJle5akfrlBw5y/ufq+FsWGlMtg/kTTN3e+P+3+PwoWKLTPb/UvSjfF/Zfqi2kDGQpa9WBb/n7xXoSfFn83szdiOC8plt4FGcff7zWxNSUvTF4zNKOIDYPgguAzSwcRUhcqJcveXzGwgfcI/KulhhZOZW1SiBL6Z7alQROPncflWhRNWVzgxTztV4eTvr7E9d2W71VXprrhWqjtiUuTk5/H3YMYTSiE78ZL6M5Gfl3S+mb3i7v+lkHW5xcySwGQvheIFaXmm0bg5+8Du/n+Z5WVmdn/qRLmc18zsY+5+g9RXcTfpgnSuwvt/vcJY0PcrnFAPirs/o1QAnNETA+Jf5QiIG85DQZjsuL3cMsH+r8tsk3eOxjyqBUZSmW64yfdiAEHN+pIOd/c7K2xzfM59pZXKJr5hocquS5KZvVuF88HmmcZHKpwCaKlCJi+pPn2JpC1iz4iLMhdf+qR6UaxmZqt5mHLo0BKbrpAElvF+/2dmK5TYLslcj9Dgx0cmF8u+rf6LZd9JPfb9Cr0QvhsvyO2jkJl/wt23LbVDoFHc/cUS6wgsAQwbBJfBw2Z2iMKJ3haS5khSPMErdYJUzjsk7ahQyfHzChOE/8ELp7P4lsLJTmJFhav7qykEZgVl+j3MgZVelc4KVjMy7rfUPG+DPZht4u4bp5avtlD99T9SOFk3s2sUMpuStL+735HZx0CnD6nkbQoFlG5VYSYknSU+SNJ5FsZeSqGS637x7409VtY1s1kKXYkHLWZs/kfFFUOTIip5A+KGilnLmQoZIFOJsavV5HxueedozPN41cbuSuW74eYKbKx/apkfZZaTNjyb+rvqVD6Vsokpxyv8D1rfzLolbavU/K45n7ck/VlhTtVlcfuRqS726f8J2WmS0u3dVOGCUrUpehaa2dnqn2e0S8Xz2/ZNi2SDnE823ufs+Oe1Vdo+QuHzvLbCxbQBj3EGAAADQ3AZzFAoDLGDpM96qEAphe5nvyl3p6x4EjdH0hwLxVs+J+kaM/uuu/8sbraix9L/0Q3xBPVZK65O+rCFqQ08ZgEOU6rKaw6Pu/v3qm82ILeb2dZJZtHMPqJwEvlhM9tc/SetN8TfZmZbuPvtFsZMrq3iOQPHqXy2r5o83XtfdPcPWpgLUe7+opklY0fTRUeWZgL5wbhQ0pmSzlb5CwF5AuJG+6Gk3d19IJ+vUqo9t1xzNOZh1cfupoOZUuOW81ik8t3WXangxgqr866ocGHqlUyAXimbmLR5npktUvj/Y5IOixnx5HGqPu9ovsL/tCSAW0Wh4us2Kry4VOlC068kfcMLp+j5tfrHgyb+W6FScJLVvF6hOnIBK5xPVhbGVQ9oPtn4v/WTKr6A8714+8cV/vfupXAR4wJJX/fSxdMAAEAdMc9lGWb2Ds/M4ZfzfitJ2lXh5Ga8QretczzOj2dmPe4+ocx9/+nu704tv13SaQoniKZwYniYl5nDscT+7vASczrWwsz+Iem96i+Z/i5J9ytUiXxNofpdlrv7FAuFk45298WZfW6qMKfkoCY7N7NxkjZy96ssVNoc6e4vpW4vNV/oInff0syWqT8IMoUT8CSzM6DMXXq/VbbZvtT6PJmvoWJmN9ajy2C152Y552jM+Vh3KRTCKRi76+4zUtt8VKFb9mruXjBueaCPN8C2mcJFlK3d/agB3ne+Z+bWTa/L87zjdne6+4dKrUt97tOfeSnzuTezu9z9g5l9lFq3qjJZUkkrZQN6q8N8shamnXlBIfDvu4Dj7qeY2cMKlb8vkPQndydbCQBAA5G5LG+2ys+JWJKZnadQXGe2pO96f5GgtFus9BQiX1GmS2bMVnRp8KZW32TAyo33ulzSrkmXvTLWzgaWkuTuiy1M4D5gZnagwlQlYxTmGHynQuZwqpm9TyGb89bY7TOxumJ3QncvVfmyFpdZKP7yFxUGTwXdJ0sFxHVux0AtNLM/KozFG3TQlyNAzjtHYx5Vx+4qx7jlvOI4v41UOLfidaW2jWOoLjGz4yQdZWaLVTpD2FeMx0JxqdGS3h4fK8mUrq7wuU7ked6S9ErSayC2f0vFscYD+NznnaKnUpY0rR7zya7n7uX+D30s+z8ovpbPM64NAIChR3BZ3mD6R35BIRtwmKRDU10s09mAryucdH5e/WOttpS0kkI3LpnZtzzMJ5cen9XH3UsV1CiSDmhqZWareyhE8FKZTd6sElhKYQqOclYZVMNCV7wPKxRQkrs/EMeiSSHDult83HRW9CWFuTiHQjKWMz3lRLb7ZNmAeIjalMfqCtmraal1uYO+TJfQgptUmAHONUdjTrnG7npt45Yl9c2XeZik9STdqdBl9f8pNYVI5gLGCIWpgZIqyrvleJivKBSTWlchK5c0+kVJP0ttlzzv61V5zPLhki40s8fivt6hwvHeeaSn6JHKT9Gzcnr8pLu/HC+aZNVjPtmbzGzTUheqJO1nZn9y9/tiL5I5kj4oaamZfd7dBzO9DgAAyIngsryS1S4rcfcRObZ5SmEKkSnqHyOVnULkoNh9rKggRhP9XuEEORmDlj5bd4WiOSWZ2djYlXdhmaztAeqfq3OgXnf3N5LgwcxGxfbI3S+NXXGPdPfvD3L/A+JV5gGNKgXETeHu+1ffquL981b+HOwcjaVkx+6+VWHsdFqt45YTh0naStLN7j45ZsWzn6n0BYylCnM+7in1F+GRJDNbO+5Lkm5Num66+2mSTjOzQ9y90lyleygErYcpBGerKwSABdz9ttjOJJi/3wc4zY67P6fS1WGzslnSiSo9Kfyg55M1s3sUst2jJO1vZg+qeCqWzypMdST1X+hZU6Hb/rka3NytAAAgJ8ZcqrgCZFY9M4B5mNnhCidJ60j6k0LRj2zF1ZZmZv9U6Cr7O0m/dfeN40n1XyS9of5gcqJC8ZNPDHKM6w8lPS9pX4WiQAdL+ru7H5Pa5lZ3/3ANTydPO77l7j+Mf3/a3S9M3fZ9d//f1PIt7v6RZExsDIhv98FNx1EXZraewvQyybjL6xXG9z5S58f5h0K2tuIcjTn3tYFC0ar/xOVVFLpeP5TaptS45UMH+p02s9vcfSsL86N+xN1fN7N73T1bRKfafj6jUHn2mtiej0v6prv/ObPdJpI2VmE12J+rODucXOT5j0JV3GMkbZn3s5ijvZeVeMwXFC58/Sr12m+lMM7xsbjNOgrF0RbF27PzyZ4z0EDXzJ5TqK5bkodpVe7wOM7czC5SmCf3V3G5aOw1AACoL4JLSRYmI0+yce9SmKrCFLpT/jtnNmoo2jVOoRvbPgrdRn+vEGg+0IS2VDwpSzIWmft8XdKPFaYjOS+1frLC2FQpzIu4IHvfAbRrhEK132kK79lcSWenx1eZ2U8Vxvj9UYUVTIvaXEM7+k5csyexJZarBsSNZmZXKny+0t0Vu9x9xzo/zrhS63N0qS61r4WStnH3N+LyipJudPetKtznbZIOdveTBvhYf1EYL3q4QlfY5xTmdtylXPf1RLobu4ViPDsm2UoLE6pf5akCOXGc5iSF4HK2wvyrN7j7pyq0b6TCd6pb0ht5P4s5nvdpCpm/P8RVn1XopusKGdPTJT3s7k/EzPBXJO0t6e+SvpME8XE8b3o+2Yfc/fC87cjbdjO7WdIBkp5UKDS2pbv/K952n7fg/LIAAAwnBJcpZvZrSX9x99lxeWdJe7n7V5rbMsnCNB/nSNpsAMU46vn4V1e42RW6AR7o/XPwba3QDe1Hkqa5+2eGvpWllWm7e5x7sk6Pkc6Y9P1dZjkdEEvSXO+fu68prEJl0SF6vII5Gn0Qc36WafNdHqadWV9hmpp1FbLlFyh0x9xX4QLNYTW0fXuFLrhzYpfs/VI3f1fScent3f3c1H0Xe5xXNS6PkHRXZt1ihXGCd8Tnsrak3+UJ9C0UBjso72cxx/5uywbrqSzuvQrZ5x3c/VkLhZIuULhg8iFJ708C4vTzjpn6WweaRTSzRyT9pNztHubY3VrSbxUC4lPd/YR4310kfdHdPzeQxwQAAAPDmMtCW7t7X6EXd78iZpmaIp6E7ayQuZyq0JXu+Ga0xd0nV7o9nugngeWuCkHl7u7+f/GEd0iY2bYKr8k4hc9z0s2yr4BOtbbXSaV5A12SzGxPhUqXP5f0awuFfdaUtKWZPZ/tGtlgvWb2BfVnqD4nKdeUNwNh+edozONpM9vD47yZ8fVN5oM8T9K1ki5SqHC8UKEQz2YD6X5toSjNm0kXTjN7r0IV6SVJxjQTPB6eXi5hjpnNVWEmcHZmm9fcfbmZLbUwN+tTktbP0153/1Xm+1byszgAq5nZu5Lg38zeJWm1eNsbCtP+JF2MPyvpLHe/SNJFsQtxoh7zyY6Mj132zh7m3y3KTsYLhtnXGQAA1BnBZaHHzOxYhXGCUigS8liF7YeEme2ocHK/i8L0JBdI+rK7l6oI2ag2TXH3BVZYETPt9ZjBWV8hc7G5uz8WT44HOtXAQMxSKOhSMOddWsz8fF/Suu6+s5ltLOmj7j6rju34oJm9qHDiu0r8W3E5ydB9S4XVOldUqBS8mqTfSGpmcPklhTGXP1UIQG5S6AZabycoVFotmKNxkPs6SKFa6s8UXueHFTKTkjTG3Y+Pf881s08rdPNdXrybiuYoZJkfMLMJChViuyXtZmYf9uI5LEsGb/G+a7v7N+N36GPxpmR/aQvNbA2FomKLFKb3+H8DaHOez2JeR0i6wcIYapO0gaSDLUwfcq6kA8xslLsvVbgA9uXUfdPHlw9m2rFKqo3u+eaTfdzdswWbCpjZNzKrXOGCww1J91gAADB0CC4LfU6hS9tfFE5KrovrGu1ohfFvR3io1tgKtpe0QIUVMROuEIgfpZDN+KGkcyxUvN1Tg6i8OwAvuPsVVbb5rULwloxp/D+F8Zd1Cy5zdlVe0d0fTi3fELM+z9rA5/qrq5h13qMBD5V3jsaq3P2fkra2MC2HPDUVhtQ3vjLJcvUqzHdqcdu8BX3elhrjvJ9Cl9pD4vjORQqf+TxOVfheJ3OHXhzbuGm8re975e4Hxz/PNLM5klZ397tzPk5d525199lmtpH6s4H3eyziI+nU+Lm91syeUagOe73UF0y/UOc25Ul3lqpaPF7SMWZ2vLtfUId2AACAMhhzWYKZrdrMLOFwYKEA0FSFcWN1L/9v/QWGPqPQXe5ihfFfkgqL9aTGiKXHRQ7ZeMJyzKzH3SeUue2f7v7uRrYnPm7uYjR1eryrFOZzPVnS2xW6fG7l7tsMYB9fcPfflchSSeobe/eQwrQVpQKSgm7TVR7rbo+VbM3sRkk/cvdL4nIyvjM9x+dohflCpVRWrtTYxdRjZMdhblfmeV2Xp831ZGb7llrvhQW6tlaoDjsv+b9pZu+RtJrXt2jWmAFcFCi6r0K2nGqxAAAMITKXKRbmwztboZviu8zsg5K+ksokdDwLE5N/UiEb0Pf5yXZXiyeVdTuxLOGUzPLE9MMrNbm9whx8Y9U/9nFrpbIqDXSLlZ7n8ysK3Z+bIT2XalExmnpJuoWqeG7KcQrdqAciyfKWnVvT3ccPvJUl3W1mP5b0qMI0GvMkKXZbTR4rzxyfa1S4bZXM8jdTf6+sMCfqIhV+phslHRCvrHDB6HaFMa2S+sY5FnD3/6t3QwYbWCb3TbLWAABg6JC5TDGzWyR9StJfUxmue9x9k8r37Byxm94LKh7jeLwqZ8DyjKkaTHs2dPcHK62LWc4zFKZquEehiM6nBtLVsE5tXUvSJQoZ1iTw3lLSSgpViZ9sZHuyBlpJdID7/puko919cWb9ppK+7+6lulvXuw3Hp8Zh5r3PKpIOU8jMnePud8X120h6t7ufX+n+qf38QdKCEhcWDlCYmuSzFe67vkLl008OpO1DIQbVF7j7Ts1uy0DEsb3f9jpWiAYAAMUILlMsM7l9XHeXp+ag63TVgm0zO0HS4wrzJZpCdmodd//OELWnaO47M1vk7ltm1o2S9N7Ypvt9gBO415OZTVF/ddSa5vmsp1KvZR33nbtbaI59VfosucfpJ0rcry7Pz8y2GGh3z1hU6i8KY5IXxdUTFYo6faJSBduYcbvX3TceZJPrxsJclve4+3ub3ZZSLEzjkj2ojVEozLavu9/X+FYBANA56BZb6OGYkfB4EnWYwjQJ6HeTmW2azUCl7JEJxn9pYeL4ugaXZvY+hQDtrZkKtqsrUxGzxLixLcysYNxYI8VgsiUCygZao8Jt2W6h1ZQaD72qQlXXsQoVaUupV7fIsxWmI8ktZqW3iRm05OLM5aUuLGTGwY6QtLmGtot5ETObLemrkk5PtWWkpPdLurCRbRmg3TLLLqmXMfQAADQGwWWhgySdJumdCmOs5klivKUKMgKjJO1vZg8qdO9MipZsFjd9xcy6FKZPcYVqu0NxYvdehRPJNVRYwfYlSQdmtq06bqxTZYvRZKaLyDtFRB4Ly4w3PUD9mbxc3L1vvK2ZvUXhItD+Cp+57FjctC0r3DYQgw5S3f1qSVdX2SwZB+uSlkr6vbvfNNjHHKTfSJqrMN3IrQoZ16UK83s+0uC25BarHhcwsy9LOqsJzQEAoOPQLTbFzLZ19xurretEZjau0u3JSZ2ZjVcI0LdVODm+UdLh7v7QELXro+4+kDkA23bcWDurpVtomf2NkfQNhW7X50o6rdS0PWa2psLFhvEqLED1pYE/i7597pVUjK0nM9tT0nru/vO4fKvC+GCX9C13b+g8qHGKl29L2kmhm3vfHKHu/pNGtqUWQ9ndGwAAFCJzWegMFXd3K7WuEz2pkNmdIGmxpFkeJk4vEIPIPRvYrl4zm68wQf0mZraZQtfcEyvc5xWFyeDRIAPpFlqNmf1I0t4K2ahNPTO/ZcalCnMvXqXCAlR5H6vUd//fyfp6TrUh6VuS9kktr6iQbV1NIZPY0OBS4ULAKwoFp96iVHDZZqgSCwBAg5C5VMh+SdpG0uGSfpq6aXWFrErHF/Qxsz9KelPhRH1nhe5xh5XYbmWFsW8fUGrsYy2ZoirtulZh6oZflavwa2aXqXAM28aS/uTuRw1FmzC0zGy5QpfspSos3lLUlbfW+UzNrFIXVq9n9dFs0SMz+5m7fy3+fbO7b12vx8rRlp0k/UTSXyV9z91frXKXlmVm67VyV14AAIYTMpfBigrZgVEqnDvvRYWpSSBtnFT0NLNZKj8v4/mS7pM0XdL3FLotDmVRpNHufmtmCrtsRvXHmdtaetwYKnP3EQPY/G9mtou7zx7kY00ezP0G6W2Zx/5aanHNBrZDko6R9Gl3v7fBj1sXsev7vordoZP/D+5+aPNaBQDA8EdwKcndr5V0rZn9tlRBCEgKWUtJkrsvrTAf+QR3/7SZ7enu55rZ7xWynUPlGTN7t2IGy8w+pTAVSpJFrdqVF8PaYZL+18xeV/gMD6hQkZl9y91/GP/+tLtfmLrt++7+v3Vs6y1lih59ReUv5gwJd/94Ix9vCMyWdLPC975du/MCANB26BYrycxOdffDM90n+7j7Hk1oVksxs2Xqr/pqCtNHvKrMybqZ3eruHzaz6xQq7T4h6VZ333CI2rWhwti7bSQ9J+lfkr7g7g/l7coLlJMuBpMtDFPvQjFmtpakSxS6/CZjObdUGPO4Vxy3ihwo4gMAQHOQuQzOj79/XHGrDubuI3NuepaZvU2hyuRfFbob13WOy0y7HpS0g5mtKmmEu7+UujlvV14MY/HzuJEKxwBfl/fuZf4utVwTd39KoejRFIUxy9Igix5B55vZgZL+phCsS5Lc/dnmNQkAgOGP4FKSuy+Kv69tdlvanbufHf+8VtKQZCslycz2LbM+acd5yt+VF8NUnEfzMEnrSbpT0taS/p+kvIV4vMzfpZbrIgaTBJS1eUPSjxTGjibvk2sI/ycBAAC6xRYws20lHS9pnELgnXT55ISkCjP7RqXb6z0vnpmdUeamPSS9091H5e3Ki+HLzBZL2krSze7+ITN7n6Tvu/veOe+ffIbSnx/F5ZXdfYUhaDZqZGYPSvqwuz/T7LYAANBJyFwWmiXp6wqTvA94TrwOl1TZfa/Cyfxf4/LuGoLuqO5+SPK3hZRkl6QjFYp4nBS3yduVF8PXf9z9P2YmM1vJ3e8zs/fmvTOfobbVo/4LAQAAoEEILgu94O5XNLsR7cjdvytJsZDPFsnYRzM7XtLlQ/GYZjZK0n9J+h+FoPJT7n7/UDwW2tYjcVqKSyRdaWbPSaIi9PD3iqQ74zyl6TGXTEUCAMAQoltsipn9QNJISRer8ITk9rJ3QgEzu1/SZu7+elxeSdLd7p47W5Tzcb6qMJZuvqSZ7v5QPfeP4cfMtpf0Vklz3P2NZrcHQ8fM9iu13t3PbXRbAADoJASXKfEqt9RfACIZm5e3+EfHM7NjJH1G0l/iqr0k/cndv1/nx1ku6SlJT6uwsErynm1Wz8dDezKzrSXdm8qkry7p/e5+S3NbBgAAMPwQXKqgGE1STtQVgpYb3P1fzWlV+zKzLSV9LC5e5+53DMFjjKt0u7vT9REyszsUuml7XB4haSFzIA5vZraRpJMlbazCKWgozgYAwBBizGXwlhLrxkk6xsyOd/cLGt2gdubui8zsYcWTOjN7l7v/u86PURQ8mtlu7v63ej4O2p556gqauy+PY3UxvP1G0nGSfippsqT9JY1oaosAAOgAZC4rMLMxkq4iy5Gfme0h6RRJ6yp0W32XpPvc/QMV71ifx76d9wppZnaxpGsk/TKuOljSZHffq1ltwtAzs0XuvqWZLXb3TdPrmt02AACGM67kVuDuz6q/qyzyOUFhovr/c/cNJO2gUMm1EXivkHWQpG0kPSrpEUkfkfTlprYIjfB67AL9gJl9zcw+IWm1ZjcKAIDhju5hFZjZZEnPNbsdbeZNd+81sxFmNsLdrzazUxv02F9p0OOgTbj7U5L2aXY70HCHSRot6VCFC15TJJWsIAsAAOqH4FKSmS1WYcVRSRoj6TFJ+za+RW3teTNbTdJ1krrN7CmFOefqysz2LrN+PUly94vr/ZhoH2b2LXf/oZmdoeLvNvMdDnPuflv882WF8ZYAAKABCC6D3TLLLqnX3eseFHWAPSX9R9LXJXUpzCv4vSF4nN3j77UUuj0uiMuTJd2kMFcpOtc/4u+FTW0FmiJOK1XqogLTSgEAMIQo6IO2ZmbzJO3n7o/H5XUk/dbdpze3ZQCaJU6HlFhZ0iclLXX3bzWpSQAAdAQyl6ir2F11pkJG0eKPu/vqQ/SQ6yeBZfSkQoVaQGb2Hkn/I2m8Uv/vyGANb+6+KLPqRjO7tSmNAQCggxBcot5+KGl3d/9H1S3rY76ZzZX0h7j8WUlXNeix0foulHSmpLMlLWtyW9AgcRqpxAhJWyp00QcAAEOIbrGoKzO70d23bfBj7i3p43HxOnf/SyMfH62LuQ07k5n9S2HMpUlaKulfkr7n7jc0tWEAAAxzBJeoKzM7TdI7JF0i6fVkPdVb0QxmdrykpyT9RYWfx2eb1SYAAIDhiuASdWVmvymx2t39S0P0eI0e44k2EjNYWe7uGza8MRhyZra6pLXd/YG4/GlJq8Sb57r7k01rHAAAHYDgEm3NzHrU2DGeAFqUmZ0l6SZ3/21c7pF0hUKAudTdD2pi8wAAGPYo6IO6aOKk9U8SWCLLzKa4+4KY2S5CN+1haytJX0ktv+Tuh0iSmTHeEgCAIUZwiXpp1qT1C83sj2KMJwptL2mBpN1L3OaS+HwMT6O8sDvOF1N/r9HgtgAA0HHoFou6MbORkma6+/808DEbOsYTQOsys7skTXf3JzLr3ynpCnffrDktAwCgM5C5RF2Y2Sh3X2pmDZ2GxN33b+Tjob2Y2RqS9pU0Xqn/d0PYTRvN9SNJl5nZEZLuiOu2kPTjeBsAABhCBJeol1sVTuLuNLO/Kkxe/0py41B1UzWzlSXNkPQBSSunHo/MJSRptqSbJS2WtLzJbcEQc/ffmdkzkk5U+J/gku6V9B13v6KpjQMAoAMQXKLeVpbUK2mK+icxH8oxbudLuk/SdEnfk9Sl/vGfwMru/o1mNwKN4+5zJM1pdjsAAOhEjLlEXZjZI5J+ov5g0lI3u7v/ZIge9w5339zM7nb3zcxsBUnXu/vWQ/F4aC9m9nVJL0v6mwoLPj3btEZhyJjZsZJ+Ue79NbMpkka7+98a2zIAADoDmUvUy0hJq6kwqEwM5RWMN+Pv581sE0lPSFprCB8P7eUNhbF2x6j/c+iSNmxaizCUFiuMufyPpNslPa3Qm2IjSR+SdJWk7zetdQAADHNkLlEXZna7u2/RhMc9QNJFkjaT9BuFAPc77n5mo9uC1mNmD0r6sLs/0+y2oHHMbCNJ20paR9JrCl3lr3P315raMAAAhjmCS9RF0j212e0A0sxsnqS93P3VZrcFzWFmb5P0vHOwAwBgyNEtFvUytZEPZmYVi7QM1RhPtJ1XFCoYX63CMZdMRTIMmdl3JP3J3e8zs5UkXaHQHXapmX3e3a9qagMBABjmCC5RF00okPKWBj8e2tMl8Qed4bOSToh/7ydphKQ1Jb1H0rkKYy4BAMAQIbhEW3L37za7DWh97n6uma2oEFxI0v3u/mal+6CtvZHq/jpd0h/cfZmkf5gZxzsAAIbYiGY3AKiFma1nZn8xs6fiz0Vmtl6z24XWYGaTJD0g6eeSfiHp/8xsu2a2CUPqdTPbxMzWlDRZ0rzUbaOb1CYAADoGwSXa3W8k/VXSuvHnsrgOkKRTJE1z9+3dfTuFbNZPm9wmDJ3DJf1Z0n2Sfuru/5IkM9tF0h1NbBcAAB2BarFoa2Z2p7t/qNo6dCYzu9vdN6u2DgAAALVjDAraXa+ZfUHSH+Ly5yT1NrE9aC0LzexsSb+Ly12SFjaxPRhCJapIu6RnJN2QZDEBAMDQIXOJtmZm4ySdIemjCieSN0k61N3/3dSGoSXE6Si+KuljcdX1kn7h7q+XvxfalZkdV2L1GIXu0Me7+wUNbhIAAB2F4BLAsBaLu8jdn252W9AcZjZG0lXuvkWz2wIAwHBGt1i0JTM7QyFTWZK7H9rA5qDFmJlJOk7S1xQLl5nZMklnuPv3mtk2NJ67Pxs/EwAAYAhRLRbtaqGkRfFnj9TfyQ8629clbStpK3cf4+5jJH1E0rZm9vXmNg2NZmaTJT3X7HYAADDc0S0Wbc/M7nD3zZvdDrQOM7tD0o7u/kxm/ZqS5vF5GZ7MbLGKezSMkfSYpH3d/b7GtwoAgM5Bt1gMB1whQdYK2cBSCuMuzWyFZjQIDbFbZtkl9br7K81oDAAAnYbgEsBw9MYgb0Mbc/cl2XVm9mVJZzWhOQAAdBy6xaItmdlL6s9Yjpb0anKTJHf31ZvSMLSEWLynVLbKJK3s7mQvO4SZ3U6VWAAAGoPMJdqSu7+l2W1A63L3kc1uA1oGVWIBAGgQMpcAgGHLzNZz90ea3Q4AADoBwSUAYFgxs2+UWP2CpEXufmeDmwMAQMcguAQADCtm9ntJEyVdFlftJuluSeMlXejuP2xS0wAAGNYILgEAw4qZXSdpF3d/OS6vJulySTspZC83bmb7AAAYrkY0uwEAANTZWpJeTy2/KWltd38tsx4AANQR1WIBAMNNt6RbzOzSuLy7pN+b2aqS/t68ZgEAMLzRLRYAMOyY2VaStomLN7r7wma2BwCATkBwCQAYdsxspKS1leqh4+7/bl6LAAAY/ugWCwAYVszsEEnHSXpS0jJJJsklbdbMdgEAMNyRuQQADCtm1iPpI+7e2+y2AADQSagWCwAYbh6W9EKzGwEAQKehWywAYLh5UNI1Zna5UlOPuPtPmtckAACGP4JLAMBw8+/4s2L8AQAADcCYSwAAAABAzchcAgCGBTM71d0PN7PLFKrDFnD3PZrQLAAAOgbBJQBguDg//v5xU1sBAECHIrgEAAwL7r4o/rm6pMvdfXkz2wMAQKdhKhIAwHDzWUkPmNkPzex9zW4MAACdgoI+AIBhx8xWl/Q5SfsrjL/8jaQ/uPtLTW0YAADDGJlLAMCw4+4vSvqzpAskrSPpE5JuN7NDmtowAACGMTKXAIBhxcz2UMhYTpB0nqRz3f0pMxst6e/uPr6Z7QMAYLiioA8AYLj5pKSfuvt16ZXu/qqZzWhSmwAAGPbIXAIAAAAAakbmEgAwLJjZSwrFe4pukuTuvnqDmwQAQEchcwkAAAAAqBnVYgEAw4qZnZ9nHQAAqC+CSwDAcPOB9IKZjZK0ZZPaAgBAxyC4BAAMC2Z2dBx3uZmZvRh/XpL0pKRLm9w8AACGPcZcAgCGFTM72d2PbnY7AADoNASXAIBhxcy2K7U+O+8lAACoL4JLAMCwYmaXpRZXlvRhSYvcfUqTmgQAQEdgnksAwLDi7runl81sfUmnNqc1AAB0Dgr6AACGu0ckvb/ZjQAAYLgjcwkAGFbM7AxJyZiPEZI2l3R781oEAEBnILgEAAw3f5c0Mv79vKQ/uPuNzWsOAACdgeASADAsmNkoSd+X9CVJ/46r3yXpHDO71d3fbFrjAADoAIy5BAAMFz+SNEbSBu6+hbtvIWlDSWtI+nEzGwYAQCdgKhIAwLBgZg9Ieo9nDmxmNlLSfe6+UXNaBgBAZyBzCQAYLjwbWMaVy9Rf4AcAAAwRgksAwHDxdzPbN7vSzL4g6b4mtAcAgI5Ct1gAwLBgZu+UdLGk1yQtiqsnSlpF0ifc/dFmtQ0AgE5AcAkAGFbMbIqkD8TFv7v7/Ga2BwCATkFwCQAAAACoGWMuAQAAAAA1I7gEAAAAANSM4BIAAAAAUDOCSwAAAABAzQguAQAAAAA1+/8Gq1mYRYx1GAAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 1080x3960 with 10 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#Capital gain vs categorical Feature\n",
+    "fig,ax=plt.subplots(5,2,figsize=(15,55))\n",
+    "r=0\n",
+    "c=0\n",
+    "for i,n in enumerate(cat):\n",
+    "    if i%2==0 and i>0:\n",
+    "        r+=1\n",
+    "        c=0\n",
+    "    graph=sns.boxplot(x=n,y='capital.gain',data=df,ax=ax[r,c])\n",
+    "    if n=='native.country' or n=='occupation' or n=='education':\n",
+    "        graph.set_xticklabels(graph.get_xticklabels(),rotation = 90)\n",
+    "    else:\n",
+    "        graph.set_xticklabels(graph.get_xticklabels(),rotation = 45)\n",
+    "    if n!='education.num':\n",
+    "        graph.set(xlabel=None)\n",
+    "    c+=1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Highest capital gains are seen in individuals belonging to private or self employed workclass. There are more no. of prof-school  than any other education category with highest capital gains. There are individuals even with preschool knowledge have capital gain more than 40000. As the education level increases capital gain also increases. People from the armed forces have the least capital gain while most prominent capitals gains are found in people who are in the sales occupation. Whites have more capital gains than any other race. Men also seem to have high capital gains as compared to females. There are many people from <=50k income category who have captital gains more than 10000."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Multivariate Analysis"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:49.260323Z",
+     "iopub.status.busy": "2021-07-05T16:35:49.259888Z",
+     "iopub.status.idle": "2021-07-05T16:35:50.244228Z",
+     "shell.execute_reply": "2021-07-05T16:35:50.243292Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:49.260294Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
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+       "        if (typeof require !== 'undefined') {\n",
+       "        require.undef(\"plotly\");\n",
+       "        define('plotly', function(require, exports, module) {\n",
+       "            /**\n",
+       "* plotly.js v2.4.2\n",
+       "* Copyright 2012-2021, Plotly, Inc.\n",
+       "* All rights reserved.\n",
+       "* Licensed under the MIT license\n",
+       "*/\n",
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+       "/*!\n",
+       " * The buffer module from node.js, for the browser.\n",
+       " *\n",
+       " * @author   Feross Aboukhadijeh <feross@feross.org> <http://feross.org>\n",
+       " * @license  MIT\n",
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this._expand(r+1),this.words[r]=e?this.words[r]|1<<i:this.words[r]&~(1<<i),this.strip()},a.prototype.iadd=function(t){var e,r,n;if(0!==this.negative&&0===t.negative)return this.negative=0,e=this.isub(t),this.negative^=1,this._normSign();if(0===this.negative&&0!==t.negative)return t.negative=0,e=this.isub(t),t.negative=1,e._normSign();this.length>t.length?(r=this,n=t):(r=t,n=this);for(var i=0,a=0;a<n.length;a++)e=(0|r.words[a])+(0|n.words[a])+i,this.words[a]=67108863&e,i=e>>>26;for(;0!==i&&a<r.length;a++)e=(0|r.words[a])+i,this.words[a]=67108863&e,i=e>>>26;if(this.length=r.length,0!==i)this.words[this.length]=i,this.length++;else if(r!==this)for(;a<r.length;a++)this.words[a]=r.words[a];return this},a.prototype.add=function(t){var e;return 0!==t.negative&&0===this.negative?(t.negative=0,e=this.sub(t),t.negative^=1,e):0===t.negative&&0!==this.negative?(this.negative=0,e=t.sub(this),this.negative=1,e):this.length>t.length?this.clone().iadd(t):t.clone().iadd(this)},a.prototype.isub=function(t){if(0!==t.negative){t.negative=0;var e=this.iadd(t);return t.negative=1,e._normSign()}if(0!==this.negative)return this.negative=0,this.iadd(t),this.negative=1,this._normSign();var r,n,i=this.cmp(t);if(0===i)return this.negative=0,this.length=1,this.words[0]=0,this;i>0?(r=this,n=t):(r=t,n=this);for(var a=0,o=0;o<n.length;o++)a=(e=(0|r.words[o])-(0|n.words[o])+a)>>26,this.words[o]=67108863&e;for(;0!==a&&o<r.length;o++)a=(e=(0|r.words[o])+a)>>26,this.words[o]=67108863&e;if(0===a&&o<r.length&&r!==this)for(;o<r.length;o++)this.words[o]=r.words[o];return this.length=Math.max(this.length,o),r!==this&&(this.negative=1),this.strip()},a.prototype.sub=function(t){return this.clone().isub(t)};var p=function(t,e,r){var n,i,a,o=t.words,s=e.words,l=r.words,c=0,u=0|o[0],f=8191&u,h=u>>>13,p=0|o[1],d=8191&p,g=p>>>13,m=0|o[2],v=8191&m,y=m>>>13,x=0|o[3],b=8191&x,_=x>>>13,w=0|o[4],T=8191&w,k=w>>>13,A=0|o[5],M=8191&A,S=A>>>13,E=0|o[6],L=8191&E,C=E>>>13,P=0|o[7],I=8191&P,O=P>>>13,z=0|o[8],D=8191&z,R=z>>>13,F=0|o[9],B=8191&F,N=F>>>13,j=0|s[0],U=8191&j,V=j>>>13,q=0|s[1],H=8191&q,G=q>>>13,Y=0|s[2],W=8191&Y,X=Y>>>13,Z=0|s[3],J=8191&Z,K=Z>>>13,Q=0|s[4],$=8191&Q,tt=Q>>>13,et=0|s[5],rt=8191&et,nt=et>>>13,it=0|s[6],at=8191&it,ot=it>>>13,st=0|s[7],lt=8191&st,ct=st>>>13,ut=0|s[8],ft=8191&ut,ht=ut>>>13,pt=0|s[9],dt=8191&pt,gt=pt>>>13;r.negative=t.negative^e.negative,r.length=19;var mt=(c+(n=Math.imul(f,U))|0)+((8191&(i=(i=Math.imul(f,V))+Math.imul(h,U)|0))<<13)|0;c=((a=Math.imul(h,V))+(i>>>13)|0)+(mt>>>26)|0,mt&=67108863,n=Math.imul(d,U),i=(i=Math.imul(d,V))+Math.imul(g,U)|0,a=Math.imul(g,V);var vt=(c+(n=n+Math.imul(f,H)|0)|0)+((8191&(i=(i=i+Math.imul(f,G)|0)+Math.imul(h,H)|0))<<13)|0;c=((a=a+Math.imul(h,G)|0)+(i>>>13)|0)+(vt>>>26)|0,vt&=67108863,n=Math.imul(v,U),i=(i=Math.imul(v,V))+Math.imul(y,U)|0,a=Math.imul(y,V),n=n+Math.imul(d,H)|0,i=(i=i+Math.imul(d,G)|0)+Math.imul(g,H)|0,a=a+Math.imul(g,G)|0;var yt=(c+(n=n+Math.imul(f,W)|0)|0)+((8191&(i=(i=i+Math.imul(f,X)|0)+Math.imul(h,W)|0))<<13)|0;c=((a=a+Math.imul(h,X)|0)+(i>>>13)|0)+(yt>>>26)|0,yt&=67108863,n=Math.imul(b,U),i=(i=Math.imul(b,V))+Math.imul(_,U)|0,a=Math.imul(_,V),n=n+Math.imul(v,H)|0,i=(i=i+Math.imul(v,G)|0)+Math.imul(y,H)|0,a=a+Math.imul(y,G)|0,n=n+Math.imul(d,W)|0,i=(i=i+Math.imul(d,X)|0)+Math.imul(g,W)|0,a=a+Math.imul(g,X)|0;var xt=(c+(n=n+Math.imul(f,J)|0)|0)+((8191&(i=(i=i+Math.imul(f,K)|0)+Math.imul(h,J)|0))<<13)|0;c=((a=a+Math.imul(h,K)|0)+(i>>>13)|0)+(xt>>>26)|0,xt&=67108863,n=Math.imul(T,U),i=(i=Math.imul(T,V))+Math.imul(k,U)|0,a=Math.imul(k,V),n=n+Math.imul(b,H)|0,i=(i=i+Math.imul(b,G)|0)+Math.imul(_,H)|0,a=a+Math.imul(_,G)|0,n=n+Math.imul(v,W)|0,i=(i=i+Math.imul(v,X)|0)+Math.imul(y,W)|0,a=a+Math.imul(y,X)|0,n=n+Math.imul(d,J)|0,i=(i=i+Math.imul(d,K)|0)+Math.imul(g,J)|0,a=a+Math.imul(g,K)|0;var bt=(c+(n=n+Math.imul(f,$)|0)|0)+((8191&(i=(i=i+Math.imul(f,tt)|0)+Math.imul(h,$)|0))<<13)|0;c=((a=a+Math.imul(h,tt)|0)+(i>>>13)|0)+(bt>>>26)|0,bt&=67108863,n=Math.imul(M,U),i=(i=Math.imul(M,V))+Math.imul(S,U)|0,a=Math.imul(S,V),n=n+Math.imul(T,H)|0,i=(i=i+Math.imul(T,G)|0)+Math.imul(k,H)|0,a=a+Math.imul(k,G)|0,n=n+Math.imul(b,W)|0,i=(i=i+Math.imul(b,X)|0)+Math.imul(_,W)|0,a=a+Math.imul(_,X)|0,n=n+Math.imul(v,J)|0,i=(i=i+Math.imul(v,K)|0)+Math.imul(y,J)|0,a=a+Math.imul(y,K)|0,n=n+Math.imul(d,$)|0,i=(i=i+Math.imul(d,tt)|0)+Math.imul(g,$)|0,a=a+Math.imul(g,tt)|0;var _t=(c+(n=n+Math.imul(f,rt)|0)|0)+((8191&(i=(i=i+Math.imul(f,nt)|0)+Math.imul(h,rt)|0))<<13)|0;c=((a=a+Math.imul(h,nt)|0)+(i>>>13)|0)+(_t>>>26)|0,_t&=67108863,n=Math.imul(L,U),i=(i=Math.imul(L,V))+Math.imul(C,U)|0,a=Math.imul(C,V),n=n+Math.imul(M,H)|0,i=(i=i+Math.imul(M,G)|0)+Math.imul(S,H)|0,a=a+Math.imul(S,G)|0,n=n+Math.imul(T,W)|0,i=(i=i+Math.imul(T,X)|0)+Math.imul(k,W)|0,a=a+Math.imul(k,X)|0,n=n+Math.imul(b,J)|0,i=(i=i+Math.imul(b,K)|0)+Math.imul(_,J)|0,a=a+Math.imul(_,K)|0,n=n+Math.imul(v,$)|0,i=(i=i+Math.imul(v,tt)|0)+Math.imul(y,$)|0,a=a+Math.imul(y,tt)|0,n=n+Math.imul(d,rt)|0,i=(i=i+Math.imul(d,nt)|0)+Math.imul(g,rt)|0,a=a+Math.imul(g,nt)|0;var wt=(c+(n=n+Math.imul(f,at)|0)|0)+((8191&(i=(i=i+Math.imul(f,ot)|0)+Math.imul(h,at)|0))<<13)|0;c=((a=a+Math.imul(h,ot)|0)+(i>>>13)|0)+(wt>>>26)|0,wt&=67108863,n=Math.imul(I,U),i=(i=Math.imul(I,V))+Math.imul(O,U)|0,a=Math.imul(O,V),n=n+Math.imul(L,H)|0,i=(i=i+Math.imul(L,G)|0)+Math.imul(C,H)|0,a=a+Math.imul(C,G)|0,n=n+Math.imul(M,W)|0,i=(i=i+Math.imul(M,X)|0)+Math.imul(S,W)|0,a=a+Math.imul(S,X)|0,n=n+Math.imul(T,J)|0,i=(i=i+Math.imul(T,K)|0)+Math.imul(k,J)|0,a=a+Math.imul(k,K)|0,n=n+Math.imul(b,$)|0,i=(i=i+Math.imul(b,tt)|0)+Math.imul(_,$)|0,a=a+Math.imul(_,tt)|0,n=n+Math.imul(v,rt)|0,i=(i=i+Math.imul(v,nt)|0)+Math.imul(y,rt)|0,a=a+Math.imul(y,nt)|0,n=n+Math.imul(d,at)|0,i=(i=i+Math.imul(d,ot)|0)+Math.imul(g,at)|0,a=a+Math.imul(g,ot)|0;var Tt=(c+(n=n+Math.imul(f,lt)|0)|0)+((8191&(i=(i=i+Math.imul(f,ct)|0)+Math.imul(h,lt)|0))<<13)|0;c=((a=a+Math.imul(h,ct)|0)+(i>>>13)|0)+(Tt>>>26)|0,Tt&=67108863,n=Math.imul(D,U),i=(i=Math.imul(D,V))+Math.imul(R,U)|0,a=Math.imul(R,V),n=n+Math.imul(I,H)|0,i=(i=i+Math.imul(I,G)|0)+Math.imul(O,H)|0,a=a+Math.imul(O,G)|0,n=n+Math.imul(L,W)|0,i=(i=i+Math.imul(L,X)|0)+Math.imul(C,W)|0,a=a+Math.imul(C,X)|0,n=n+Math.imul(M,J)|0,i=(i=i+Math.imul(M,K)|0)+Math.imul(S,J)|0,a=a+Math.imul(S,K)|0,n=n+Math.imul(T,$)|0,i=(i=i+Math.imul(T,tt)|0)+Math.imul(k,$)|0,a=a+Math.imul(k,tt)|0,n=n+Math.imul(b,rt)|0,i=(i=i+Math.imul(b,nt)|0)+Math.imul(_,rt)|0,a=a+Math.imul(_,nt)|0,n=n+Math.imul(v,at)|0,i=(i=i+Math.imul(v,ot)|0)+Math.imul(y,at)|0,a=a+Math.imul(y,ot)|0,n=n+Math.imul(d,lt)|0,i=(i=i+Math.imul(d,ct)|0)+Math.imul(g,lt)|0,a=a+Math.imul(g,ct)|0;var kt=(c+(n=n+Math.imul(f,ft)|0)|0)+((8191&(i=(i=i+Math.imul(f,ht)|0)+Math.imul(h,ft)|0))<<13)|0;c=((a=a+Math.imul(h,ht)|0)+(i>>>13)|0)+(kt>>>26)|0,kt&=67108863,n=Math.imul(B,U),i=(i=Math.imul(B,V))+Math.imul(N,U)|0,a=Math.imul(N,V),n=n+Math.imul(D,H)|0,i=(i=i+Math.imul(D,G)|0)+Math.imul(R,H)|0,a=a+Math.imul(R,G)|0,n=n+Math.imul(I,W)|0,i=(i=i+Math.imul(I,X)|0)+Math.imul(O,W)|0,a=a+Math.imul(O,X)|0,n=n+Math.imul(L,J)|0,i=(i=i+Math.imul(L,K)|0)+Math.imul(C,J)|0,a=a+Math.imul(C,K)|0,n=n+Math.imul(M,$)|0,i=(i=i+Math.imul(M,tt)|0)+Math.imul(S,$)|0,a=a+Math.imul(S,tt)|0,n=n+Math.imul(T,rt)|0,i=(i=i+Math.imul(T,nt)|0)+Math.imul(k,rt)|0,a=a+Math.imul(k,nt)|0,n=n+Math.imul(b,at)|0,i=(i=i+Math.imul(b,ot)|0)+Math.imul(_,at)|0,a=a+Math.imul(_,ot)|0,n=n+Math.imul(v,lt)|0,i=(i=i+Math.imul(v,ct)|0)+Math.imul(y,lt)|0,a=a+Math.imul(y,ct)|0,n=n+Math.imul(d,ft)|0,i=(i=i+Math.imul(d,ht)|0)+Math.imul(g,ft)|0,a=a+Math.imul(g,ht)|0;var At=(c+(n=n+Math.imul(f,dt)|0)|0)+((8191&(i=(i=i+Math.imul(f,gt)|0)+Math.imul(h,dt)|0))<<13)|0;c=((a=a+Math.imul(h,gt)|0)+(i>>>13)|0)+(At>>>26)|0,At&=67108863,n=Math.imul(B,H),i=(i=Math.imul(B,G))+Math.imul(N,H)|0,a=Math.imul(N,G),n=n+Math.imul(D,W)|0,i=(i=i+Math.imul(D,X)|0)+Math.imul(R,W)|0,a=a+Math.imul(R,X)|0,n=n+Math.imul(I,J)|0,i=(i=i+Math.imul(I,K)|0)+Math.imul(O,J)|0,a=a+Math.imul(O,K)|0,n=n+Math.imul(L,$)|0,i=(i=i+Math.imul(L,tt)|0)+Math.imul(C,$)|0,a=a+Math.imul(C,tt)|0,n=n+Math.imul(M,rt)|0,i=(i=i+Math.imul(M,nt)|0)+Math.imul(S,rt)|0,a=a+Math.imul(S,nt)|0,n=n+Math.imul(T,at)|0,i=(i=i+Math.imul(T,ot)|0)+Math.imul(k,at)|0,a=a+Math.imul(k,ot)|0,n=n+Math.imul(b,lt)|0,i=(i=i+Math.imul(b,ct)|0)+Math.imul(_,lt)|0,a=a+Math.imul(_,ct)|0,n=n+Math.imul(v,ft)|0,i=(i=i+Math.imul(v,ht)|0)+Math.imul(y,ft)|0,a=a+Math.imul(y,ht)|0;var Mt=(c+(n=n+Math.imul(d,dt)|0)|0)+((8191&(i=(i=i+Math.imul(d,gt)|0)+Math.imul(g,dt)|0))<<13)|0;c=((a=a+Math.imul(g,gt)|0)+(i>>>13)|0)+(Mt>>>26)|0,Mt&=67108863,n=Math.imul(B,W),i=(i=Math.imul(B,X))+Math.imul(N,W)|0,a=Math.imul(N,X),n=n+Math.imul(D,J)|0,i=(i=i+Math.imul(D,K)|0)+Math.imul(R,J)|0,a=a+Math.imul(R,K)|0,n=n+Math.imul(I,$)|0,i=(i=i+Math.imul(I,tt)|0)+Math.imul(O,$)|0,a=a+Math.imul(O,tt)|0,n=n+Math.imul(L,rt)|0,i=(i=i+Math.imul(L,nt)|0)+Math.imul(C,rt)|0,a=a+Math.imul(C,nt)|0,n=n+Math.imul(M,at)|0,i=(i=i+Math.imul(M,ot)|0)+Math.imul(S,at)|0,a=a+Math.imul(S,ot)|0,n=n+Math.imul(T,lt)|0,i=(i=i+Math.imul(T,ct)|0)+Math.imul(k,lt)|0,a=a+Math.imul(k,ct)|0,n=n+Math.imul(b,ft)|0,i=(i=i+Math.imul(b,ht)|0)+Math.imul(_,ft)|0,a=a+Math.imul(_,ht)|0;var St=(c+(n=n+Math.imul(v,dt)|0)|0)+((8191&(i=(i=i+Math.imul(v,gt)|0)+Math.imul(y,dt)|0))<<13)|0;c=((a=a+Math.imul(y,gt)|0)+(i>>>13)|0)+(St>>>26)|0,St&=67108863,n=Math.imul(B,J),i=(i=Math.imul(B,K))+Math.imul(N,J)|0,a=Math.imul(N,K),n=n+Math.imul(D,$)|0,i=(i=i+Math.imul(D,tt)|0)+Math.imul(R,$)|0,a=a+Math.imul(R,tt)|0,n=n+Math.imul(I,rt)|0,i=(i=i+Math.imul(I,nt)|0)+Math.imul(O,rt)|0,a=a+Math.imul(O,nt)|0,n=n+Math.imul(L,at)|0,i=(i=i+Math.imul(L,ot)|0)+Math.imul(C,at)|0,a=a+Math.imul(C,ot)|0,n=n+Math.imul(M,lt)|0,i=(i=i+Math.imul(M,ct)|0)+Math.imul(S,lt)|0,a=a+Math.imul(S,ct)|0,n=n+Math.imul(T,ft)|0,i=(i=i+Math.imul(T,ht)|0)+Math.imul(k,ft)|0,a=a+Math.imul(k,ht)|0;var Et=(c+(n=n+Math.imul(b,dt)|0)|0)+((8191&(i=(i=i+Math.imul(b,gt)|0)+Math.imul(_,dt)|0))<<13)|0;c=((a=a+Math.imul(_,gt)|0)+(i>>>13)|0)+(Et>>>26)|0,Et&=67108863,n=Math.imul(B,$),i=(i=Math.imul(B,tt))+Math.imul(N,$)|0,a=Math.imul(N,tt),n=n+Math.imul(D,rt)|0,i=(i=i+Math.imul(D,nt)|0)+Math.imul(R,rt)|0,a=a+Math.imul(R,nt)|0,n=n+Math.imul(I,at)|0,i=(i=i+Math.imul(I,ot)|0)+Math.imul(O,at)|0,a=a+Math.imul(O,ot)|0,n=n+Math.imul(L,lt)|0,i=(i=i+Math.imul(L,ct)|0)+Math.imul(C,lt)|0,a=a+Math.imul(C,ct)|0,n=n+Math.imul(M,ft)|0,i=(i=i+Math.imul(M,ht)|0)+Math.imul(S,ft)|0,a=a+Math.imul(S,ht)|0;var Lt=(c+(n=n+Math.imul(T,dt)|0)|0)+((8191&(i=(i=i+Math.imul(T,gt)|0)+Math.imul(k,dt)|0))<<13)|0;c=((a=a+Math.imul(k,gt)|0)+(i>>>13)|0)+(Lt>>>26)|0,Lt&=67108863,n=Math.imul(B,rt),i=(i=Math.imul(B,nt))+Math.imul(N,rt)|0,a=Math.imul(N,nt),n=n+Math.imul(D,at)|0,i=(i=i+Math.imul(D,ot)|0)+Math.imul(R,at)|0,a=a+Math.imul(R,ot)|0,n=n+Math.imul(I,lt)|0,i=(i=i+Math.imul(I,ct)|0)+Math.imul(O,lt)|0,a=a+Math.imul(O,ct)|0,n=n+Math.imul(L,ft)|0,i=(i=i+Math.imul(L,ht)|0)+Math.imul(C,ft)|0,a=a+Math.imul(C,ht)|0;var Ct=(c+(n=n+Math.imul(M,dt)|0)|0)+((8191&(i=(i=i+Math.imul(M,gt)|0)+Math.imul(S,dt)|0))<<13)|0;c=((a=a+Math.imul(S,gt)|0)+(i>>>13)|0)+(Ct>>>26)|0,Ct&=67108863,n=Math.imul(B,at),i=(i=Math.imul(B,ot))+Math.imul(N,at)|0,a=Math.imul(N,ot),n=n+Math.imul(D,lt)|0,i=(i=i+Math.imul(D,ct)|0)+Math.imul(R,lt)|0,a=a+Math.imul(R,ct)|0,n=n+Math.imul(I,ft)|0,i=(i=i+Math.imul(I,ht)|0)+Math.imul(O,ft)|0,a=a+Math.imul(O,ht)|0;var Pt=(c+(n=n+Math.imul(L,dt)|0)|0)+((8191&(i=(i=i+Math.imul(L,gt)|0)+Math.imul(C,dt)|0))<<13)|0;c=((a=a+Math.imul(C,gt)|0)+(i>>>13)|0)+(Pt>>>26)|0,Pt&=67108863,n=Math.imul(B,lt),i=(i=Math.imul(B,ct))+Math.imul(N,lt)|0,a=Math.imul(N,ct),n=n+Math.imul(D,ft)|0,i=(i=i+Math.imul(D,ht)|0)+Math.imul(R,ft)|0,a=a+Math.imul(R,ht)|0;var It=(c+(n=n+Math.imul(I,dt)|0)|0)+((8191&(i=(i=i+Math.imul(I,gt)|0)+Math.imul(O,dt)|0))<<13)|0;c=((a=a+Math.imul(O,gt)|0)+(i>>>13)|0)+(It>>>26)|0,It&=67108863,n=Math.imul(B,ft),i=(i=Math.imul(B,ht))+Math.imul(N,ft)|0,a=Math.imul(N,ht);var Ot=(c+(n=n+Math.imul(D,dt)|0)|0)+((8191&(i=(i=i+Math.imul(D,gt)|0)+Math.imul(R,dt)|0))<<13)|0;c=((a=a+Math.imul(R,gt)|0)+(i>>>13)|0)+(Ot>>>26)|0,Ot&=67108863;var zt=(c+(n=Math.imul(B,dt))|0)+((8191&(i=(i=Math.imul(B,gt))+Math.imul(N,dt)|0))<<13)|0;return c=((a=Math.imul(N,gt))+(i>>>13)|0)+(zt>>>26)|0,zt&=67108863,l[0]=mt,l[1]=vt,l[2]=yt,l[3]=xt,l[4]=bt,l[5]=_t,l[6]=wt,l[7]=Tt,l[8]=kt,l[9]=At,l[10]=Mt,l[11]=St,l[12]=Et,l[13]=Lt,l[14]=Ct,l[15]=Pt,l[16]=It,l[17]=Ot,l[18]=zt,0!==c&&(l[19]=c,r.length++),r};function d(t,e,r){return(new g).mulp(t,e,r)}function g(t,e){this.x=t,this.y=e}Math.imul||(p=h),a.prototype.mulTo=function(t,e){var r=this.length+t.length;return 10===this.length&&10===t.length?p(this,t,e):r<63?h(this,t,e):r<1024?function(t,e,r){r.negative=e.negative^t.negative,r.length=t.length+e.length;for(var n=0,i=0,a=0;a<r.length-1;a++){var o=i;i=0;for(var s=67108863&n,l=Math.min(a,e.length-1),c=Math.max(0,a-t.length+1);c<=l;c++){var u=a-c,f=(0|t.words[u])*(0|e.words[c]),h=67108863&f;s=67108863&(h=h+s|0),i+=(o=(o=o+(f/67108864|0)|0)+(h>>>26)|0)>>>26,o&=67108863}r.words[a]=s,n=o,o=i}return 0!==n?r.words[a]=n:r.length--,r.strip()}(this,t,e):d(this,t,e)},g.prototype.makeRBT=function(t){for(var e=new Array(t),r=a.prototype._countBits(t)-1,n=0;n<t;n++)e[n]=this.revBin(n,r,t);return e},g.prototype.revBin=function(t,e,r){if(0===t||t===r-1)return t;for(var n=0,i=0;i<e;i++)n|=(1&t)<<e-i-1,t>>=1;return n},g.prototype.permute=function(t,e,r,n,i,a){for(var o=0;o<a;o++)n[o]=e[t[o]],i[o]=r[t[o]]},g.prototype.transform=function(t,e,r,n,i,a){this.permute(a,t,e,r,n,i);for(var o=1;o<i;o<<=1)for(var s=o<<1,l=Math.cos(2*Math.PI/s),c=Math.sin(2*Math.PI/s),u=0;u<i;u+=s)for(var f=l,h=c,p=0;p<o;p++){var d=r[u+p],g=n[u+p],m=r[u+p+o],v=n[u+p+o],y=f*m-h*v;v=f*v+h*m,m=y,r[u+p]=d+m,n[u+p]=g+v,r[u+p+o]=d-m,n[u+p+o]=g-v,p!==s&&(y=l*f-c*h,h=l*h+c*f,f=y)}},g.prototype.guessLen13b=function(t,e){var r=1|Math.max(e,t),n=1&r,i=0;for(r=r/2|0;r;r>>>=1)i++;return 1<<i+1+n},g.prototype.conjugate=function(t,e,r){if(!(r<=1))for(var n=0;n<r/2;n++){var i=t[n];t[n]=t[r-n-1],t[r-n-1]=i,i=e[n],e[n]=-e[r-n-1],e[r-n-1]=-i}},g.prototype.normalize13b=function(t,e){for(var r=0,n=0;n<e/2;n++){var i=8192*Math.round(t[2*n+1]/e)+Math.round(t[2*n]/e)+r;t[n]=67108863&i,r=i<67108864?0:i/67108864|0}return t},g.prototype.convert13b=function(t,e,r,i){for(var a=0,o=0;o<e;o++)a+=0|t[o],r[2*o]=8191&a,a>>>=13,r[2*o+1]=8191&a,a>>>=13;for(o=2*e;o<i;++o)r[o]=0;n(0===a),n(0==(-8192&a))},g.prototype.stub=function(t){for(var e=new Array(t),r=0;r<t;r++)e[r]=0;return e},g.prototype.mulp=function(t,e,r){var n=2*this.guessLen13b(t.length,e.length),i=this.makeRBT(n),a=this.stub(n),o=new Array(n),s=new Array(n),l=new Array(n),c=new Array(n),u=new Array(n),f=new Array(n),h=r.words;h.length=n,this.convert13b(t.words,t.length,o,n),this.convert13b(e.words,e.length,c,n),this.transform(o,a,s,l,n,i),this.transform(c,a,u,f,n,i);for(var p=0;p<n;p++){var d=s[p]*u[p]-l[p]*f[p];l[p]=s[p]*f[p]+l[p]*u[p],s[p]=d}return this.conjugate(s,l,n),this.transform(s,l,h,a,n,i),this.conjugate(h,a,n),this.normalize13b(h,n),r.negative=t.negative^e.negative,r.length=t.length+e.length,r.strip()},a.prototype.mul=function(t){var e=new a(null);return e.words=new Array(this.length+t.length),this.mulTo(t,e)},a.prototype.mulf=function(t){var e=new a(null);return e.words=new Array(this.length+t.length),d(this,t,e)},a.prototype.imul=function(t){return this.clone().mulTo(t,this)},a.prototype.imuln=function(t){n(\"number\"==typeof t),n(t<67108864);for(var e=0,r=0;r<this.length;r++){var i=(0|this.words[r])*t,a=(67108863&i)+(67108863&e);e>>=26,e+=i/67108864|0,e+=a>>>26,this.words[r]=67108863&a}return 0!==e&&(this.words[r]=e,this.length++),this},a.prototype.muln=function(t){return this.clone().imuln(t)},a.prototype.sqr=function(){return this.mul(this)},a.prototype.isqr=function(){return this.imul(this.clone())},a.prototype.pow=function(t){var e=function(t){for(var e=new Array(t.bitLength()),r=0;r<e.length;r++){var n=r/26|0,i=r%26;e[r]=(t.words[n]&1<<i)>>>i}return e}(t);if(0===e.length)return new a(1);for(var r=this,n=0;n<e.length&&0===e[n];n++,r=r.sqr());if(++n<e.length)for(var i=r.sqr();n<e.length;n++,i=i.sqr())0!==e[n]&&(r=r.mul(i));return r},a.prototype.iushln=function(t){n(\"number\"==typeof t&&t>=0);var e,r=t%26,i=(t-r)/26,a=67108863>>>26-r<<26-r;if(0!==r){var o=0;for(e=0;e<this.length;e++){var s=this.words[e]&a,l=(0|this.words[e])-s<<r;this.words[e]=l|o,o=s>>>26-r}o&&(this.words[e]=o,this.length++)}if(0!==i){for(e=this.length-1;e>=0;e--)this.words[e+i]=this.words[e];for(e=0;e<i;e++)this.words[e]=0;this.length+=i}return this.strip()},a.prototype.ishln=function(t){return n(0===this.negative),this.iushln(t)},a.prototype.iushrn=function(t,e,r){var i;n(\"number\"==typeof t&&t>=0),i=e?(e-e%26)/26:0;var a=t%26,o=Math.min((t-a)/26,this.length),s=67108863^67108863>>>a<<a,l=r;if(i-=o,i=Math.max(0,i),l){for(var c=0;c<o;c++)l.words[c]=this.words[c];l.length=o}if(0===o);else if(this.length>o)for(this.length-=o,c=0;c<this.length;c++)this.words[c]=this.words[c+o];else this.words[0]=0,this.length=1;var u=0;for(c=this.length-1;c>=0&&(0!==u||c>=i);c--){var f=0|this.words[c];this.words[c]=u<<26-a|f>>>a,u=f&s}return l&&0!==u&&(l.words[l.length++]=u),0===this.length&&(this.words[0]=0,this.length=1),this.strip()},a.prototype.ishrn=function(t,e,r){return n(0===this.negative),this.iushrn(t,e,r)},a.prototype.shln=function(t){return this.clone().ishln(t)},a.prototype.ushln=function(t){return this.clone().iushln(t)},a.prototype.shrn=function(t){return this.clone().ishrn(t)},a.prototype.ushrn=function(t){return this.clone().iushrn(t)},a.prototype.testn=function(t){n(\"number\"==typeof t&&t>=0);var e=t%26,r=(t-e)/26,i=1<<e;return!(this.length<=r)&&!!(this.words[r]&i)},a.prototype.imaskn=function(t){n(\"number\"==typeof t&&t>=0);var e=t%26,r=(t-e)/26;if(n(0===this.negative,\"imaskn works only with positive numbers\"),this.length<=r)return this;if(0!==e&&r++,this.length=Math.min(r,this.length),0!==e){var i=67108863^67108863>>>e<<e;this.words[this.length-1]&=i}return this.strip()},a.prototype.maskn=function(t){return this.clone().imaskn(t)},a.prototype.iaddn=function(t){return n(\"number\"==typeof t),n(t<67108864),t<0?this.isubn(-t):0!==this.negative?1===this.length&&(0|this.words[0])<t?(this.words[0]=t-(0|this.words[0]),this.negative=0,this):(this.negative=0,this.isubn(t),this.negative=1,this):this._iaddn(t)},a.prototype._iaddn=function(t){this.words[0]+=t;for(var e=0;e<this.length&&this.words[e]>=67108864;e++)this.words[e]-=67108864,e===this.length-1?this.words[e+1]=1:this.words[e+1]++;return this.length=Math.max(this.length,e+1),this},a.prototype.isubn=function(t){if(n(\"number\"==typeof t),n(t<67108864),t<0)return this.iaddn(-t);if(0!==this.negative)return this.negative=0,this.iaddn(t),this.negative=1,this;if(this.words[0]-=t,1===this.length&&this.words[0]<0)this.words[0]=-this.words[0],this.negative=1;else for(var e=0;e<this.length&&this.words[e]<0;e++)this.words[e]+=67108864,this.words[e+1]-=1;return this.strip()},a.prototype.addn=function(t){return this.clone().iaddn(t)},a.prototype.subn=function(t){return this.clone().isubn(t)},a.prototype.iabs=function(){return this.negative=0,this},a.prototype.abs=function(){return this.clone().iabs()},a.prototype._ishlnsubmul=function(t,e,r){var i,a,o=t.length+r;this._expand(o);var s=0;for(i=0;i<t.length;i++){a=(0|this.words[i+r])+s;var l=(0|t.words[i])*e;s=((a-=67108863&l)>>26)-(l/67108864|0),this.words[i+r]=67108863&a}for(;i<this.length-r;i++)s=(a=(0|this.words[i+r])+s)>>26,this.words[i+r]=67108863&a;if(0===s)return this.strip();for(n(-1===s),s=0,i=0;i<this.length;i++)s=(a=-(0|this.words[i])+s)>>26,this.words[i]=67108863&a;return this.negative=1,this.strip()},a.prototype._wordDiv=function(t,e){var r=(this.length,t.length),n=this.clone(),i=t,o=0|i.words[i.length-1];0!==(r=26-this._countBits(o))&&(i=i.ushln(r),n.iushln(r),o=0|i.words[i.length-1]);var s,l=n.length-i.length;if(\"mod\"!==e){(s=new a(null)).length=l+1,s.words=new Array(s.length);for(var c=0;c<s.length;c++)s.words[c]=0}var u=n.clone()._ishlnsubmul(i,1,l);0===u.negative&&(n=u,s&&(s.words[l]=1));for(var f=l-1;f>=0;f--){var h=67108864*(0|n.words[i.length+f])+(0|n.words[i.length+f-1]);for(h=Math.min(h/o|0,67108863),n._ishlnsubmul(i,h,f);0!==n.negative;)h--,n.negative=0,n._ishlnsubmul(i,1,f),n.isZero()||(n.negative^=1);s&&(s.words[f]=h)}return s&&s.strip(),n.strip(),\"div\"!==e&&0!==r&&n.iushrn(r),{div:s||null,mod:n}},a.prototype.divmod=function(t,e,r){return n(!t.isZero()),this.isZero()?{div:new a(0),mod:new a(0)}:0!==this.negative&&0===t.negative?(s=this.neg().divmod(t,e),\"mod\"!==e&&(i=s.div.neg()),\"div\"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.iadd(t)),{div:i,mod:o}):0===this.negative&&0!==t.negative?(s=this.divmod(t.neg(),e),\"mod\"!==e&&(i=s.div.neg()),{div:i,mod:s.mod}):0!=(this.negative&t.negative)?(s=this.neg().divmod(t.neg(),e),\"div\"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.isub(t)),{div:s.div,mod:o}):t.length>this.length||this.cmp(t)<0?{div:new a(0),mod:this}:1===t.length?\"div\"===e?{div:this.divn(t.words[0]),mod:null}:\"mod\"===e?{div:null,mod:new a(this.modn(t.words[0]))}:{div:this.divn(t.words[0]),mod:new a(this.modn(t.words[0]))}:this._wordDiv(t,e);var i,o,s},a.prototype.div=function(t){return this.divmod(t,\"div\",!1).div},a.prototype.mod=function(t){return this.divmod(t,\"mod\",!1).mod},a.prototype.umod=function(t){return this.divmod(t,\"mod\",!0).mod},a.prototype.divRound=function(t){var e=this.divmod(t);if(e.mod.isZero())return e.div;var r=0!==e.div.negative?e.mod.isub(t):e.mod,n=t.ushrn(1),i=t.andln(1),a=r.cmp(n);return a<0||1===i&&0===a?e.div:0!==e.div.negative?e.div.isubn(1):e.div.iaddn(1)},a.prototype.modn=function(t){n(t<=67108863);for(var e=(1<<26)%t,r=0,i=this.length-1;i>=0;i--)r=(e*r+(0|this.words[i]))%t;return r},a.prototype.idivn=function(t){n(t<=67108863);for(var e=0,r=this.length-1;r>=0;r--){var i=(0|this.words[r])+67108864*e;this.words[r]=i/t|0,e=i%t}return this.strip()},a.prototype.divn=function(t){return this.clone().idivn(t)},a.prototype.egcd=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var i=new a(1),o=new a(0),s=new a(0),l=new a(1),c=0;e.isEven()&&r.isEven();)e.iushrn(1),r.iushrn(1),++c;for(var u=r.clone(),f=e.clone();!e.isZero();){for(var h=0,p=1;0==(e.words[0]&p)&&h<26;++h,p<<=1);if(h>0)for(e.iushrn(h);h-- >0;)(i.isOdd()||o.isOdd())&&(i.iadd(u),o.isub(f)),i.iushrn(1),o.iushrn(1);for(var d=0,g=1;0==(r.words[0]&g)&&d<26;++d,g<<=1);if(d>0)for(r.iushrn(d);d-- >0;)(s.isOdd()||l.isOdd())&&(s.iadd(u),l.isub(f)),s.iushrn(1),l.iushrn(1);e.cmp(r)>=0?(e.isub(r),i.isub(s),o.isub(l)):(r.isub(e),s.isub(i),l.isub(o))}return{a:s,b:l,gcd:r.iushln(c)}},a.prototype._invmp=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var i,o=new a(1),s=new a(0),l=r.clone();e.cmpn(1)>0&&r.cmpn(1)>0;){for(var c=0,u=1;0==(e.words[0]&u)&&c<26;++c,u<<=1);if(c>0)for(e.iushrn(c);c-- >0;)o.isOdd()&&o.iadd(l),o.iushrn(1);for(var f=0,h=1;0==(r.words[0]&h)&&f<26;++f,h<<=1);if(f>0)for(r.iushrn(f);f-- >0;)s.isOdd()&&s.iadd(l),s.iushrn(1);e.cmp(r)>=0?(e.isub(r),o.isub(s)):(r.isub(e),s.isub(o))}return(i=0===e.cmpn(1)?o:s).cmpn(0)<0&&i.iadd(t),i},a.prototype.gcd=function(t){if(this.isZero())return t.abs();if(t.isZero())return this.abs();var e=this.clone(),r=t.clone();e.negative=0,r.negative=0;for(var n=0;e.isEven()&&r.isEven();n++)e.iushrn(1),r.iushrn(1);for(;;){for(;e.isEven();)e.iushrn(1);for(;r.isEven();)r.iushrn(1);var i=e.cmp(r);if(i<0){var a=e;e=r,r=a}else if(0===i||0===r.cmpn(1))break;e.isub(r)}return r.iushln(n)},a.prototype.invm=function(t){return this.egcd(t).a.umod(t)},a.prototype.isEven=function(){return 0==(1&this.words[0])},a.prototype.isOdd=function(){return 1==(1&this.words[0])},a.prototype.andln=function(t){return this.words[0]&t},a.prototype.bincn=function(t){n(\"number\"==typeof t);var e=t%26,r=(t-e)/26,i=1<<e;if(this.length<=r)return this._expand(r+1),this.words[r]|=i,this;for(var a=i,o=r;0!==a&&o<this.length;o++){var s=0|this.words[o];a=(s+=a)>>>26,s&=67108863,this.words[o]=s}return 0!==a&&(this.words[o]=a,this.length++),this},a.prototype.isZero=function(){return 1===this.length&&0===this.words[0]},a.prototype.cmpn=function(t){var e,r=t<0;if(0!==this.negative&&!r)return-1;if(0===this.negative&&r)return 1;if(this.strip(),this.length>1)e=1;else{r&&(t=-t),n(t<=67108863,\"Number is too big\");var i=0|this.words[0];e=i===t?0:i<t?-1:1}return 0!==this.negative?0|-e:e},a.prototype.cmp=function(t){if(0!==this.negative&&0===t.negative)return-1;if(0===this.negative&&0!==t.negative)return 1;var e=this.ucmp(t);return 0!==this.negative?0|-e:e},a.prototype.ucmp=function(t){if(this.length>t.length)return 1;if(this.length<t.length)return-1;for(var e=0,r=this.length-1;r>=0;r--){var n=0|this.words[r],i=0|t.words[r];if(n!==i){n<i?e=-1:n>i&&(e=1);break}}return e},a.prototype.gtn=function(t){return 1===this.cmpn(t)},a.prototype.gt=function(t){return 1===this.cmp(t)},a.prototype.gten=function(t){return this.cmpn(t)>=0},a.prototype.gte=function(t){return this.cmp(t)>=0},a.prototype.ltn=function(t){return-1===this.cmpn(t)},a.prototype.lt=function(t){return-1===this.cmp(t)},a.prototype.lten=function(t){return this.cmpn(t)<=0},a.prototype.lte=function(t){return this.cmp(t)<=0},a.prototype.eqn=function(t){return 0===this.cmpn(t)},a.prototype.eq=function(t){return 0===this.cmp(t)},a.red=function(t){return new w(t)},a.prototype.toRed=function(t){return n(!this.red,\"Already a number in reduction context\"),n(0===this.negative,\"red works only with positives\"),t.convertTo(this)._forceRed(t)},a.prototype.fromRed=function(){return n(this.red,\"fromRed works only with numbers in reduction context\"),this.red.convertFrom(this)},a.prototype._forceRed=function(t){return this.red=t,this},a.prototype.forceRed=function(t){return n(!this.red,\"Already a number 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numbers\"),this.red._verify1(this),this.red.sqr(this)},a.prototype.redISqr=function(){return n(this.red,\"redISqr works only with red numbers\"),this.red._verify1(this),this.red.isqr(this)},a.prototype.redSqrt=function(){return n(this.red,\"redSqrt works only with red numbers\"),this.red._verify1(this),this.red.sqrt(this)},a.prototype.redInvm=function(){return n(this.red,\"redInvm works only with red numbers\"),this.red._verify1(this),this.red.invm(this)},a.prototype.redNeg=function(){return n(this.red,\"redNeg works only with red numbers\"),this.red._verify1(this),this.red.neg(this)},a.prototype.redPow=function(t){return n(this.red&&!t.red,\"redPow(normalNum)\"),this.red._verify1(this),this.red.pow(this,t)};var m={k256:null,p224:null,p192:null,p25519:null};function v(t,e){this.name=t,this.p=new a(e,16),this.n=this.p.bitLength(),this.k=new a(1).iushln(this.n).isub(this.p),this.tmp=this._tmp()}function y(){v.call(this,\"k256\",\"ffffffff ffffffff ffffffff ffffffff ffffffff ffffffff 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e,r=t;do{this.split(r,this.tmp),e=(r=(r=this.imulK(r)).iadd(this.tmp)).bitLength()}while(e>this.n);var n=e<this.n?-1:r.ucmp(this.p);return 0===n?(r.words[0]=0,r.length=1):n>0?r.isub(this.p):r.strip(),r},v.prototype.split=function(t,e){t.iushrn(this.n,0,e)},v.prototype.imulK=function(t){return t.imul(this.k)},i(y,v),y.prototype.split=function(t,e){for(var r=Math.min(t.length,9),n=0;n<r;n++)e.words[n]=t.words[n];if(e.length=r,t.length<=9)return t.words[0]=0,void(t.length=1);var i=t.words[9];for(e.words[e.length++]=4194303&i,n=10;n<t.length;n++){var a=0|t.words[n];t.words[n-10]=(4194303&a)<<4|i>>>22,i=a}i>>>=22,t.words[n-10]=i,0===i&&t.length>10?t.length-=10:t.length-=9},y.prototype.imulK=function(t){t.words[t.length]=0,t.words[t.length+1]=0,t.length+=2;for(var e=0,r=0;r<t.length;r++){var n=0|t.words[r];e+=977*n,t.words[r]=67108863&e,e=64*n+(e/67108864|0)}return 0===t.words[t.length-1]&&(t.length--,0===t.words[t.length-1]&&t.length--),t},i(x,v),i(b,v),i(_,v),_.prototype.imulK=function(t){for(var e=0,r=0;r<t.length;r++){var n=19*(0|t.words[r])+e,i=67108863&n;n>>>=26,t.words[r]=i,e=n}return 0!==e&&(t.words[t.length++]=e),t},a._prime=function(t){if(m[t])return m[t];var e;if(\"k256\"===t)e=new y;else if(\"p224\"===t)e=new x;else if(\"p192\"===t)e=new b;else{if(\"p25519\"!==t)throw new Error(\"Unknown prime \"+t);e=new _}return m[t]=e,e},w.prototype._verify1=function(t){n(0===t.negative,\"red works only with positives\"),n(t.red,\"red works only with red numbers\")},w.prototype._verify2=function(t,e){n(0==(t.negative|e.negative),\"red works only with positives\"),n(t.red&&t.red===e.red,\"red works only with red numbers\")},w.prototype.imod=function(t){return this.prime?this.prime.ireduce(t)._forceRed(this):t.umod(this.m)._forceRed(this)},w.prototype.neg=function(t){return 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r=t.mul(e),n=r.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),i=r.isub(n).iushrn(this.shift),o=i;return i.cmp(this.m)>=0?o=i.isub(this.m):i.cmpn(0)<0&&(o=i.iadd(this.m)),o._forceRed(this)},T.prototype.invm=function(t){return this.imod(t._invmp(this.m).mul(this.r2))._forceRed(this)}}(void 0===e||e,this)},{buffer:115}],107:[function(t,e,r){\"use strict\";e.exports=function(t){var e,r,n,i=t.length,a=0;for(e=0;e<i;++e)a+=t[e].length;var o=new Array(a),s=0;for(e=0;e<i;++e){var l=t[e],c=l.length;for(r=0;r<c;++r){var u=o[s++]=new Array(c-1),f=0;for(n=0;n<c;++n)n!==r&&(u[f++]=l[n]);if(1&r){var h=u[1];u[1]=u[0],u[0]=h}}}return o}},{}],108:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){switch(arguments.length){case 1:return f(t);case 2:return\"function\"==typeof e?c(t,t,e,!0):h(t,e);case 3:return c(t,e,r,!1);default:throw new Error(\"box-intersect: Invalid arguments\")}};var n,i=t(\"typedarray-pool\"),a=t(\"./lib/sweep\"),o=t(\"./lib/intersect\");function s(t,e){for(var r=0;r<t;++r)if(!(e[r]<=e[r+t]))return!0;return!1}function l(t,e,r,n){for(var i=0,a=0,o=0,l=t.length;o<l;++o){var c=t[o];if(!s(e,c)){for(var u=0;u<2*e;++u)r[i++]=c[u];n[a++]=o}}return a}function c(t,e,r,n){var s=t.length,c=e.length;if(!(s<=0||c<=0)){var u=t[0].length>>>1;if(!(u<=0)){var f,h=i.mallocDouble(2*u*s),p=i.mallocInt32(s);if((s=l(t,u,h,p))>0){if(1===u&&n)a.init(s),f=a.sweepComplete(u,r,0,s,h,p,0,s,h,p);else{var d=i.mallocDouble(2*u*c),g=i.mallocInt32(c);(c=l(e,u,d,g))>0&&(a.init(s+c),f=1===u?a.sweepBipartite(u,r,0,s,h,p,0,c,d,g):o(u,r,n,s,h,p,c,d,g),i.free(d),i.free(g))}i.free(h),i.free(p)}return f}}}function u(t,e){n.push([t,e])}function f(t){return n=[],c(t,t,u,!0),n}function h(t,e){return n=[],c(t,e,u,!1),n}},{\"./lib/intersect\":110,\"./lib/sweep\":114,\"typedarray-pool\":617}],109:[function(t,e,r){\"use strict\";var n=[\"d\",\"ax\",\"vv\",\"rs\",\"re\",\"rb\",\"ri\",\"bs\",\"be\",\"bb\",\"bi\"];function i(t){var 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m\".replace(\"_\",n.join()).replace(\"$\",t)),Function.apply(void 0,r)}},{}],113:[function(t,e,r){\"use strict\";e.exports=function(t,e){e<=128?n(0,e-1,t):function t(e,r,u){var f=(r-e+1)/6|0,h=e+f,p=r-f,d=e+r>>1,g=d-f,m=d+f,v=h,y=g,x=d,b=m,_=p,w=e+1,T=r-1,k=0;l(v,y,u)&&(k=v,v=y,y=k);l(b,_,u)&&(k=b,b=_,_=k);l(v,x,u)&&(k=v,v=x,x=k);l(y,x,u)&&(k=y,y=x,x=k);l(v,b,u)&&(k=v,v=b,b=k);l(x,b,u)&&(k=x,x=b,b=k);l(y,_,u)&&(k=y,y=_,_=k);l(y,x,u)&&(k=y,y=x,x=k);l(b,_,u)&&(k=b,b=_,_=k);for(var A=u[2*y],M=u[2*y+1],S=u[2*b],E=u[2*b+1],L=2*v,C=2*x,P=2*_,I=2*h,O=2*d,z=2*p,D=0;D<2;++D){var R=u[L+D],F=u[C+D],B=u[P+D];u[I+D]=R,u[O+D]=F,u[z+D]=B}a(g,e,u),a(m,r,u);for(var N=w;N<=T;++N)if(c(N,A,M,u))N!==w&&i(N,w,u),++w;else if(!c(N,S,E,u))for(;;){if(c(T,S,E,u)){c(T,A,M,u)?(o(N,w,T,u),++w,--T):(i(N,T,u),--T);break}if(--T<N)break}s(e,w-1,A,M,u),s(r,T+1,S,E,u),w-2-e<=32?n(e,w-2,u):t(e,w-2,u);r-(T+2)<=32?n(T+2,r,u):t(T+2,r,u);T-w<=32?n(w,T,u):t(w,T,u)}(0,e-1,t)};function n(t,e,r){for(var 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r=8*e;h.length<r&&(n.free(h),h=n.mallocDouble(r))},sweepBipartite:function(t,e,r,n,i,u,f,g,m,v){for(var y=0,x=2*t,b=t-1,_=x-1,w=r;w<n;++w){var T=u[w],k=x*w;h[y++]=i[k+b],h[y++]=-(T+1),h[y++]=i[k+_],h[y++]=T}for(w=f;w<g;++w){T=v[w]+(1<<28);var A=x*w;h[y++]=m[A+b],h[y++]=-T,h[y++]=m[A+_],h[y++]=T}var M=y>>>1;a(h,M);var S=0,E=0;for(w=0;w<M;++w){var L=0|h[2*w+1];if(L>=1<<28)p(l,c,E--,L=L-(1<<28)|0);else if(L>=0)p(o,s,S--,L);else if(L<=-(1<<28)){L=-L-(1<<28)|0;for(var C=0;C<S;++C){if(void 0!==(P=e(o[C],L)))return P}d(l,c,E++,L)}else{L=-L-1|0;for(C=0;C<E;++C){var P;if(void 0!==(P=e(L,l[C])))return P}d(o,s,S++,L)}}},sweepComplete:function(t,e,r,n,i,g,m,v,y,x){for(var b=0,_=2*t,w=t-1,T=_-1,k=r;k<n;++k){var A=g[k]+1<<1,M=_*k;h[b++]=i[M+w],h[b++]=-A,h[b++]=i[M+T],h[b++]=A}for(k=m;k<v;++k){A=x[k]+1<<1;var S=_*k;h[b++]=y[S+w],h[b++]=1|-A,h[b++]=y[S+T],h[b++]=1|A}var E=b>>>1;a(h,E);var L=0,C=0,P=0;for(k=0;k<E;++k){var I=0|h[2*k+1],O=1&I;if(k<E-1&&I>>1==h[2*k+3]>>1&&(O=2,k+=1),I<0){for(var 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c(t){if(\"function\"!=typeof t)throw new TypeError('The \"listener\" argument must be of type Function. 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+       "/*!\n",
+       " * The buffer module from node.js, for the browser.\n",
+       " *\n",
+       " * @author   Feross Aboukhadijeh <https://feross.org>\n",
+       " * @license  MIT\n",
+       " */\n",
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h=a/2,p=s/2,d=g(h),m=o(h),y=g(p),b=o(p),T=o(s),k=L(T),A=y/(b+w*m*k),M=A*A,S=L(2/(1+M)),E=(w*b+(m+d)*k)/(w*b+(m-d)*k),C=L(E),P=C-1/C,I=C+1/C,O=S*P-2*c(C)-t,z=S*A*I-2*i(A)-e,R=y&&_*k*d*M/y,F=(w*m*b+k)/(2*(b+w*m*k)*(b+w*m*k)*k),B=-.5*A*S*S*S,N=B*R,j=B*F,U=(U=2*b+w*k*(m-d))*U*C,V=(w*m*b*k+T)/U,q=-w*d*y/(k*U),H=P*N-2*V/C+S*(V+V/E),G=P*j-2*q/C+S*(q+q/E),Y=A*I*N-2*R/(1+M)+S*I*R+S*A*(V-V/E),W=A*I*j-2*F/(1+M)+S*I*F+S*A*(q-q/E),X=G*Y-W*H;if(!X)break;var Z=(z*G-O*W)/X,J=(O*Y-z*H)/X;a-=Z,s=u(-x,f(x,s-J))}while((n(Z)>v||n(J)>v)&&--l>0);return n(n(s)-x)<v?[0,s]:l&&[a,s]};var wt=o(35*M);function Tt(t,e){var r=m(e/2);return[t*wt*L(1-r*r),(1+wt)*r]}function kt(t,e){var r=e/2,n=o(r);return[2*t/T*o(e)*n*n,T*m(r)]}function At(t){var e=1-t,r=i(y,0)[0]-i(-y,0)[0],n=L(2*(i(0,x)[1]-i(0,-x)[1])/r);function i(r,n){var i=o(n),a=g(n);return[i/(e+t*i)*r,e*n+t*a]}function a(t,e){var r=i(t,e);return[r[0]*n,r[1]/n]}function s(t){return a(0,t)[1]}return a.invert=function(r,i){var a=V(s,i);return[r/n*(t+e/o(a)),a]},a}function Mt(t){return[t[0]/2,S(m(t[1]/2*M))*A]}function St(t){return[2*t[0],2*i(g(t[1]*M))*A]}function Et(t,r){var i=2*y/r,s=t*t;function l(r,l){var c=e.geoAzimuthalEquidistantRaw(r,l),u=c[0],f=c[1],h=u*u+f*f;if(h>s){var d=L(h),m=a(f,u),b=i*p(m/i),_=m-b,w=t*o(_),T=(t*g(_)-_*g(w))/(x-w),k=Lt(_,T),A=(y-t)/Ct(k,w,y);u=d;var M,S=50;do{u-=M=(t+Ct(k,w,u)*A-d)/(k(u)*A)}while(n(M)>v&&--S>0);f=_*g(u),u<x&&(f-=T*(u-x));var E=g(b),C=o(b);c[0]=u*C-f*E,c[1]=u*E+f*C}return c}return l.invert=function(r,l){var c=r*r+l*l;if(c>s){var u=L(c),f=a(l,r),h=i*p(f/i),d=f-h;r=u*o(d),l=u*g(d);for(var m=r-x,v=g(r),b=l/v,_=r<x?1/0:0,w=10;;){var T=t*g(b),k=t*o(b),A=g(k),M=x-k,S=(T-b*A)/M,E=Lt(b,S);if(n(_)<1e-12||!--w)break;b-=_=(b*v-S*m-l)/(v-2*m*(M*(k+b*T*o(k)-A)-T*(T-b*A))/(M*M))}r=(u=t+Ct(E,k,r)*(y-t)/Ct(E,k,y))*o(f=h+b),l=u*g(f)}return e.geoAzimuthalEquidistantRaw.invert(r,l)},l}function Lt(t,e){return function(r){var n=t*o(r);return r<x&&(n-=e),L(1+n*n)}}function 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s=i(t,a);t=s[0],a=s[1];var l=g(a),c=o(a),u=o(t),f=E(e*l+r*c*u),h=g(f),p=n(h)>v?f/h:1;return[p*r*g(t),(n(t)>x?p:-p)*(e*c-r*l*u)]}return i.invert=qt(-t),s.invert=function(t,r){var n=L(t*t+r*r),s=-g(n),l=o(n),c=n*l,u=-r*s,f=n*e,h=L(c*c+u*u-f*f),p=a(c*f+u*h,u*f-c*h),d=(n>x?-1:1)*a(t*s,n*o(p)*l+r*g(p)*s);return i.invert(d,p)},s}function qt(t){var e=g(t),r=o(t);return function(t,n){var i=o(n),s=o(t)*i,l=g(t)*i,c=g(n);return[a(l,s*r-c*e),S(c*r+s*e)]}}Bt.invert=function(t,e){n(t)>1&&(t=2*d(t)-t),n(e)>1&&(e=2*d(e)-e);var r=d(t),i=d(e),s=-r*t,l=-i*e,c=l/s<1,u=function(t,e){var r=0,i=1,a=.5,s=50;for(;;){var l=a*a,c=L(a),u=S(1/L(1+l)),f=1-l+a*(1+l)*u,h=(1-c)/f,p=L(h),d=h*(1+l),g=p*(1-l),m=L(d-t*t),v=e+g+a*m;if(n(i-r)<1e-12||0==--s||0===v)break;v>0?r=a:i=a,a=.5*(r+i)}if(!s)return null;var x=S(c),b=o(x),_=1/b,w=2*c*b,T=(-f*b-(-3*a+u*(1+3*l))*w*(1-c))/(f*f);return[y/4*(t*(-2*_*(.5*T/p*(1-l)-2*a*p*w)+-_*w*m)+-_*(a*(1+l)*T+h*(1+3*l)*w)*S(t/L(d))),x]}(c?l:s,c?s:l),f=u[0],h=u[1],p=o(h);return c&&(f=-x-f),[r*(a(g(f)*p,-g(h))+y),i*S(o(f)*p)]},Ut.invert=function(t,e){var r,n,o,l,u,f,h=(w-1)/(w+1),p=L(1-h*h),d=jt(x,p*p),g=(n=-t,o=p*p,(r=.5*d-e)?(l=Nt(r,o),n?(f=(u=Nt(n,1-o))[1]*u[1]+o*l[0]*l[0]*u[0]*u[0],[[l[0]*u[2]/f,l[1]*l[2]*u[0]*u[1]/f],[l[1]*u[1]/f,-l[0]*l[2]*u[0]*u[2]/f],[l[2]*u[1]*u[2]/f,-o*l[0]*l[1]*u[0]/f]]):[[l[0],0],[l[1],0],[l[2],0]]):[[0,(u=Nt(n,1-o))[0]/u[1]],[1/u[1],0],[u[2]/u[1],0]]),m=function(t,e){var r=e[0]*e[0]+e[1]*e[1];return[(t[0]*e[0]+t[1]*e[1])/r,(t[1]*e[0]-t[0]*e[1])/r]}(g[0],g[1]);return[a(m[1],m[0])/-1,2*i(s(-.5*c(h*m[0]*m[0]+h*m[1]*m[1])))-x]};var Ht=S(1-1/3)*A,Gt=ht(0);function Yt(t){var e=Ht*M,r=lt(y,e)[0]-lt(-y,e)[0],i=Gt(0,e)[1],a=lt(0,e)[1],o=T-a,s=k/t,c=4/k,h=i+o*o*4/k;function p(p,d){var g,m=n(d);if(m>e){var v=f(t-1,u(0,l((p+y)/s)));(g=lt(p+=y*(t-1)/t-v*s,m))[0]=g[0]*k/r-k*(t-1)/(2*t)+v*k/t,g[1]=i+4*(g[1]-a)*o/k,d<0&&(g[1]=-g[1])}else g=Gt(p,d);return g[0]*=c,g[1]/=h,g}return p.invert=function(e,p){e/=c;var d=n(p*=h);if(d>i){var 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n=t(\"./lib/text.js\"),i=t(\"./lib/lines.js\"),a=t(\"./lib/background.js\"),o=t(\"./lib/cube.js\"),s=t(\"./lib/ticks.js\"),l=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]);function c(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function u(t){this.gl=t,this.pixelRatio=1,this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.autoTicks=!0,this.tickSpacing=[1,1,1],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickAlign=[\"auto\",\"auto\",\"auto\"],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[10,10,10],this.lastCubeProps={cubeEdges:[0,0,0],axis:[0,0,0]},this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=\"sans-serif\",this.labelSize=[20,20,20],this.labelAngle=[0,0,0],this.labelAlign=[\"auto\",\"auto\",\"auto\"],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[10,10,10],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[0,0,0],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!1,!1,!1],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._firstInit=!0,this._text=null,this._lines=null,this._background=a(t)}var f=u.prototype;function h(){this.primalOffset=[0,0,0],this.primalMinor=[0,0,0],this.mirrorOffset=[0,0,0],this.mirrorMinor=[0,0,0]}f.update=function(t){function e(e,r,n){if(n in t){var i,a=t[n],o=this[n];(e?Array.isArray(a)&&Array.isArray(a[0]):Array.isArray(a))?this[n]=i=[r(a[0]),r(a[1]),r(a[2])]:this[n]=i=[r(a),r(a),r(a)];for(var s=0;s<3;++s)if(i[s]!==o[s])return!0}return!1}t=t||{};var r,a=e.bind(this,!1,Number),o=e.bind(this,!1,Boolean),l=e.bind(this,!1,String),c=e.bind(this,!0,(function(t){if(Array.isArray(t)){if(3===t.length)return[+t[0],+t[1],+t[2],1];if(4===t.length)return[+t[0],+t[1],+t[2],+t[3]]}return[0,0,0,1]})),u=!1,f=!1;if(\"bounds\"in t)for(var h=t.bounds,p=0;p<2;++p)for(var d=0;d<3;++d)h[p][d]!==this.bounds[p][d]&&(f=!0),this.bounds[p][d]=h[p][d];if(\"ticks\"in t){r=t.ticks,u=!0,this.autoTicks=!1;for(p=0;p<3;++p)this.tickSpacing[p]=0}else a(\"tickSpacing\")&&(this.autoTicks=!0,f=!0);if(this._firstInit&&(\"ticks\"in t||\"tickSpacing\"in t||(this.autoTicks=!0),f=!0,u=!0,this._firstInit=!1),f&&this.autoTicks&&(r=s.create(this.bounds,this.tickSpacing),u=!0),u){for(p=0;p<3;++p)r[p].sort((function(t,e){return t.x-e.x}));s.equal(r,this.ticks)?u=!1:this.ticks=r}o(\"tickEnable\"),l(\"tickFont\")&&(u=!0),a(\"tickSize\"),a(\"tickAngle\"),a(\"tickPad\"),c(\"tickColor\");var g=l(\"labels\");l(\"labelFont\")&&(g=!0),o(\"labelEnable\"),a(\"labelSize\"),a(\"labelPad\"),c(\"labelColor\"),o(\"lineEnable\"),o(\"lineMirror\"),a(\"lineWidth\"),c(\"lineColor\"),o(\"lineTickEnable\"),o(\"lineTickMirror\"),a(\"lineTickLength\"),a(\"lineTickWidth\"),c(\"lineTickColor\"),o(\"gridEnable\"),a(\"gridWidth\"),c(\"gridColor\"),o(\"zeroEnable\"),c(\"zeroLineColor\"),a(\"zeroLineWidth\"),o(\"backgroundEnable\"),c(\"backgroundColor\"),this._text?this._text&&(g||u)&&this._text.update(this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont):this._text=n(this.gl,this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont),this._lines&&u&&(this._lines.dispose(),this._lines=null),this._lines||(this._lines=i(this.gl,this.bounds,this.ticks))};var p=[new h,new h,new h];function d(t,e,r,n,i){for(var a=t.primalOffset,o=t.primalMinor,s=t.mirrorOffset,l=t.mirrorMinor,c=n[e],u=0;u<3;++u)if(e!==u){var f=a,h=s,p=o,d=l;c&1<<u&&(f=s,h=a,p=l,d=o),f[u]=r[0][u],h[u]=r[1][u],i[u]>0?(p[u]=-1,d[u]=0):(p[u]=0,d[u]=1)}}var g=[0,0,0],m={model:l,view:l,projection:l,_ortho:!1};f.isOpaque=function(){return!0},f.isTransparent=function(){return!1},f.drawTransparent=function(t){};var v=[0,0,0],y=[0,0,0],x=[0,0,0];f.draw=function(t){t=t||m;for(var e=this.gl,r=t.model||l,n=t.view||l,i=t.projection||l,a=this.bounds,s=t._ortho||!1,u=o(r,n,i,a,s),f=u.cubeEdges,h=u.axis,b=n[12],_=n[13],w=n[14],T=n[15],k=(s?2:1)*this.pixelRatio*(i[3]*b+i[7]*_+i[11]*w+i[15]*T)/e.drawingBufferHeight,A=0;A<3;++A)this.lastCubeProps.cubeEdges[A]=f[A],this.lastCubeProps.axis[A]=h[A];var M=p;for(A=0;A<3;++A)d(p[A],A,this.bounds,f,h);e=this.gl;var S,E=g;for(A=0;A<3;++A)this.backgroundEnable[A]?E[A]=h[A]:E[A]=0;this._background.draw(r,n,i,a,E,this.backgroundColor),this._lines.bind(r,n,i,this);for(A=0;A<3;++A){var L=[0,0,0];h[A]>0?L[A]=a[1][A]:L[A]=a[0][A];for(var C=0;C<2;++C){var P=(A+1+C)%3,I=(A+1+(1^C))%3;this.gridEnable[P]&&this._lines.drawGrid(P,I,this.bounds,L,this.gridColor[P],this.gridWidth[P]*this.pixelRatio)}for(C=0;C<2;++C){P=(A+1+C)%3,I=(A+1+(1^C))%3;this.zeroEnable[I]&&Math.min(a[0][I],a[1][I])<=0&&Math.max(a[0][I],a[1][I])>=0&&this._lines.drawZero(P,I,this.bounds,L,this.zeroLineColor[I],this.zeroLineWidth[I]*this.pixelRatio)}}for(A=0;A<3;++A){this.lineEnable[A]&&this._lines.drawAxisLine(A,this.bounds,M[A].primalOffset,this.lineColor[A],this.lineWidth[A]*this.pixelRatio),this.lineMirror[A]&&this._lines.drawAxisLine(A,this.bounds,M[A].mirrorOffset,this.lineColor[A],this.lineWidth[A]*this.pixelRatio);var O=c(v,M[A].primalMinor),z=c(y,M[A].mirrorMinor),D=this.lineTickLength;for(C=0;C<3;++C){var R=k/r[5*C];O[C]*=D[C]*R,z[C]*=D[C]*R}this.lineTickEnable[A]&&this._lines.drawAxisTicks(A,M[A].primalOffset,O,this.lineTickColor[A],this.lineTickWidth[A]*this.pixelRatio),this.lineTickMirror[A]&&this._lines.drawAxisTicks(A,M[A].mirrorOffset,z,this.lineTickColor[A],this.lineTickWidth[A]*this.pixelRatio)}this._lines.unbind(),this._text.bind(r,n,i,this.pixelRatio);var F,B;function N(t){(B=[0,0,0])[t]=1}function j(t,e,r){var n=(t+1)%3,i=(t+2)%3,a=e[n],o=e[i],s=r[n],l=r[i];a>0&&l>0||a>0&&l<0||a<0&&l>0||a<0&&l<0?N(n):(o>0&&s>0||o>0&&s<0||o<0&&s>0||o<0&&s<0)&&N(i)}for(A=0;A<3;++A){var U=M[A].primalMinor,V=M[A].mirrorMinor,q=c(x,M[A].primalOffset);for(C=0;C<3;++C)this.lineTickEnable[A]&&(q[C]+=k*U[C]*Math.max(this.lineTickLength[C],0)/r[5*C]);var H=[0,0,0];if(H[A]=1,this.tickEnable[A]){-3600===this.tickAngle[A]?(this.tickAngle[A]=0,this.tickAlign[A]=\"auto\"):this.tickAlign[A]=-1,F=1,\"auto\"===(S=[this.tickAlign[A],.5,F])[0]?S[0]=0:S[0]=parseInt(\"\"+S[0]),B=[0,0,0],j(A,U,V);for(C=0;C<3;++C)q[C]+=k*U[C]*this.tickPad[C]/r[5*C];this._text.drawTicks(A,this.tickSize[A],this.tickAngle[A],q,this.tickColor[A],H,B,S)}if(this.labelEnable[A]){F=0,B=[0,0,0],this.labels[A].length>4&&(N(A),F=1),\"auto\"===(S=[this.labelAlign[A],.5,F])[0]?S[0]=0:S[0]=parseInt(\"\"+S[0]);for(C=0;C<3;++C)q[C]+=k*U[C]*this.labelPad[C]/r[5*C];q[A]+=.5*(a[0][A]+a[1][A]),this._text.drawLabel(A,this.labelSize[A],this.labelAngle[A],q,this.labelColor[A],[0,0,0],B,S)}}this._text.unbind()},f.dispose=function(){this._text.dispose(),this._lines.dispose(),this._background.dispose(),this._lines=null,this._text=null,this._background=null,this.gl=null}},{\"./lib/background.js\":259,\"./lib/cube.js\":260,\"./lib/lines.js\":261,\"./lib/text.js\":263,\"./lib/ticks.js\":264}],259:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=[],r=[],s=0,l=0;l<3;++l)for(var c=(l+1)%3,u=(l+2)%3,f=[0,0,0],h=[0,0,0],p=-1;p<=1;p+=2){r.push(s,s+2,s+1,s+1,s+2,s+3),f[l]=p,h[l]=p;for(var d=-1;d<=1;d+=2){f[c]=d;for(var g=-1;g<=1;g+=2)f[u]=g,e.push(f[0],f[1],f[2],h[0],h[1],h[2]),s+=1}var m=c;c=u,u=m}var v=n(t,new Float32Array(e)),y=n(t,new Uint16Array(r),t.ELEMENT_ARRAY_BUFFER),x=i(t,[{buffer:v,type:t.FLOAT,size:3,offset:0,stride:24},{buffer:v,type:t.FLOAT,size:3,offset:12,stride:24}],y),b=a(t);return b.attributes.position.location=0,b.attributes.normal.location=1,new o(t,v,x,b)};var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"./shaders\").bg;function o(t,e,r,n){this.gl=t,this.buffer=e,this.vao=r,this.shader=n}var s=o.prototype;s.draw=function(t,e,r,n,i,a){for(var o=!1,s=0;s<3;++s)o=o||i[s];if(o){var l=this.gl;l.enable(l.POLYGON_OFFSET_FILL),l.polygonOffset(1,2),this.shader.bind(),this.shader.uniforms={model:t,view:e,projection:r,bounds:n,enable:i,colors:a},this.vao.bind(),this.vao.draw(this.gl.TRIANGLES,36),this.vao.unbind(),l.disable(l.POLYGON_OFFSET_FILL)}},s.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()}},{\"./shaders\":262,\"gl-buffer\":267,\"gl-vao\":361}],260:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,a,p){i(s,e,t),i(s,r,s);for(var y=0,x=0;x<2;++x){u[2]=a[x][2];for(var b=0;b<2;++b){u[1]=a[b][1];for(var _=0;_<2;++_)u[0]=a[_][0],h(l[y],u,s),y+=1}}var w=-1;for(x=0;x<8;++x){for(var T=l[x][3],k=0;k<3;++k)c[x][k]=l[x][k]/T;p&&(c[x][2]*=-1),T<0&&(w<0||c[x][2]<c[w][2])&&(w=x)}if(w<0){w=0;for(var A=0;A<3;++A){for(var M=(A+2)%3,S=(A+1)%3,E=-1,L=-1,C=0;C<2;++C){var P=(O=C<<A)+(C<<M)+(1-C<<S),I=O+(1-C<<M)+(C<<S);o(c[O],c[P],c[I],f)<0||(C?E=1:L=1)}if(E<0||L<0)L>E&&(w|=1<<A);else{for(C=0;C<2;++C){P=(O=C<<A)+(C<<M)+(1-C<<S),I=O+(1-C<<M)+(C<<S);var O,z=d([l[O],l[P],l[I],l[O+(1<<M)+(1<<S)]]);C?E=z:L=z}L>E&&(w|=1<<A)}}}var D=7^w,R=-1;for(x=0;x<8;++x)x!==w&&x!==D&&(R<0||c[R][1]>c[x][1])&&(R=x);var F=-1;for(x=0;x<3;++x){if((N=R^1<<x)!==w&&N!==D)F<0&&(F=N),(S=c[N])[0]<c[F][0]&&(F=N)}var B=-1;for(x=0;x<3;++x){var N;if((N=R^1<<x)!==w&&N!==D&&N!==F)B<0&&(B=N),(S=c[N])[0]>c[B][0]&&(B=N)}var j=g;j[0]=j[1]=j[2]=0,j[n.log2(F^R)]=R&F,j[n.log2(R^B)]=R&B;var U=7^B;U===w||U===D?(U=7^F,j[n.log2(B^U)]=U&B):j[n.log2(F^U)]=U&F;var V=m,q=w;for(A=0;A<3;++A)V[A]=q&1<<A?-1:1;return v};var n=t(\"bit-twiddle\"),i=t(\"gl-mat4/multiply\"),a=t(\"split-polygon\"),o=t(\"robust-orientation\"),s=new Array(16),l=new Array(8),c=new Array(8),u=new Array(3),f=[0,0,0];function h(t,e,r){for(var n=0;n<4;++n){t[n]=r[12+n];for(var i=0;i<3;++i)t[n]+=e[i]*r[4*i+n]}}!function(){for(var t=0;t<8;++t)l[t]=[1,1,1,1],c[t]=[1,1,1]}();var p=[[0,0,1,0,0],[0,0,-1,1,0],[0,-1,0,1,0],[0,1,0,1,0],[-1,0,0,1,0],[1,0,0,1,0]];function d(t){for(var e=0;e<p.length;++e)if((t=a.positive(t,p[e])).length<3)return 0;var r=t[0],n=r[0]/r[3],i=r[1]/r[3],o=0;for(e=1;e+1<t.length;++e){var s=t[e],l=t[e+1],c=s[0]/s[3]-n,u=s[1]/s[3]-i,f=l[0]/l[3]-n,h=l[1]/l[3]-i;o+=Math.abs(c*h-u*f)}return o}var g=[1,1,1],m=[0,0,0],v={cubeEdges:g,axis:m}},{\"bit-twiddle\":104,\"gl-mat4/multiply\":301,\"robust-orientation\":548,\"split-polygon\":567}],261:[function(t,e,r){\"use strict\";e.exports=function(t,e,r){var o=[],s=[0,0,0],l=[0,0,0],c=[0,0,0],u=[0,0,0];o.push(0,0,1,0,1,1,0,0,-1,0,0,-1,0,1,1,0,1,-1);for(var f=0;f<3;++f){for(var h=o.length/3|0,d=0;d<r[f].length;++d){var g=+r[f][d].x;o.push(g,0,1,g,1,1,g,0,-1,g,0,-1,g,1,1,g,1,-1)}var m=o.length/3|0;s[f]=h,l[f]=m-h;h=o.length/3|0;for(var v=0;v<r[f].length;++v){g=+r[f][v].x;o.push(g,0,1,g,1,1,g,0,-1,g,0,-1,g,1,1,g,1,-1)}m=o.length/3|0;c[f]=h,u[f]=m-h}var y=n(t,new Float32Array(o)),x=i(t,[{buffer:y,type:t.FLOAT,size:3,stride:0,offset:0}]),b=a(t);return b.attributes.position.location=0,new p(t,y,x,b,l,s,u,c)};var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"./shaders\").line,o=[0,0,0],s=[0,0,0],l=[0,0,0],c=[0,0,0],u=[1,1];function f(t){return t[0]=t[1]=t[2]=0,t}function h(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function p(t,e,r,n,i,a,o,s){this.gl=t,this.vertBuffer=e,this.vao=r,this.shader=n,this.tickCount=i,this.tickOffset=a,this.gridCount=o,this.gridOffset=s}var d=p.prototype;d.bind=function(t,e,r){this.shader.bind(),this.shader.uniforms.model=t,this.shader.uniforms.view=e,this.shader.uniforms.projection=r,u[0]=this.gl.drawingBufferWidth,u[1]=this.gl.drawingBufferHeight,this.shader.uniforms.screenShape=u,this.vao.bind()},d.unbind=function(){this.vao.unbind()},d.drawAxisLine=function(t,e,r,n,i){var a=f(s);this.shader.uniforms.majorAxis=s,a[t]=e[1][t]-e[0][t],this.shader.uniforms.minorAxis=a;var o,u=h(c,r);u[t]+=e[0][t],this.shader.uniforms.offset=u,this.shader.uniforms.lineWidth=i,this.shader.uniforms.color=n,(o=f(l))[(t+2)%3]=1,this.shader.uniforms.screenAxis=o,this.vao.draw(this.gl.TRIANGLES,6),(o=f(l))[(t+1)%3]=1,this.shader.uniforms.screenAxis=o,this.vao.draw(this.gl.TRIANGLES,6)},d.drawAxisTicks=function(t,e,r,n,i){if(this.tickCount[t]){var a=f(o);a[t]=1,this.shader.uniforms.majorAxis=a,this.shader.uniforms.offset=e,this.shader.uniforms.minorAxis=r,this.shader.uniforms.color=n,this.shader.uniforms.lineWidth=i;var s=f(l);s[t]=1,this.shader.uniforms.screenAxis=s,this.vao.draw(this.gl.TRIANGLES,this.tickCount[t],this.tickOffset[t])}},d.drawGrid=function(t,e,r,n,i,a){if(this.gridCount[t]){var u=f(s);u[e]=r[1][e]-r[0][e],this.shader.uniforms.minorAxis=u;var p=h(c,n);p[e]+=r[0][e],this.shader.uniforms.offset=p;var d=f(o);d[t]=1,this.shader.uniforms.majorAxis=d;var g=f(l);g[t]=1,this.shader.uniforms.screenAxis=g,this.shader.uniforms.lineWidth=a,this.shader.uniforms.color=i,this.vao.draw(this.gl.TRIANGLES,this.gridCount[t],this.gridOffset[t])}},d.drawZero=function(t,e,r,n,i,a){var o=f(s);this.shader.uniforms.majorAxis=o,o[t]=r[1][t]-r[0][t],this.shader.uniforms.minorAxis=o;var u=h(c,n);u[t]+=r[0][t],this.shader.uniforms.offset=u;var p=f(l);p[e]=1,this.shader.uniforms.screenAxis=p,this.shader.uniforms.lineWidth=a,this.shader.uniforms.color=i,this.vao.draw(this.gl.TRIANGLES,6)},d.dispose=function(){this.vao.dispose(),this.vertBuffer.dispose(),this.shader.dispose()}},{\"./shaders\":262,\"gl-buffer\":267,\"gl-vao\":361}],262:[function(t,e,r){\"use strict\";var n=t(\"glslify\"),i=t(\"gl-shader\"),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, majorAxis, minorAxis, screenAxis;\\nuniform float lineWidth;\\nuniform vec2 screenShape;\\n\\nvec3 project(vec3 p) {\\n  vec4 pp = projection * view * model * vec4(p, 1.0);\\n  return pp.xyz / max(pp.w, 0.0001);\\n}\\n\\nvoid main() {\\n  vec3 major = position.x * majorAxis;\\n  vec3 minor = position.y * minorAxis;\\n\\n  vec3 vPosition = major + minor + offset;\\n  vec3 pPosition = project(vPosition);\\n  vec3 offset = project(vPosition + screenAxis * position.z);\\n\\n  vec2 screen = normalize((offset - pPosition).xy * screenShape) / screenShape;\\n\\n  gl_Position = vec4(pPosition + vec3(0.5 * screen * lineWidth, 0), 1.0);\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = color;\\n}\"]);r.line=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec3\"}])};var s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 offset, axis, alignDir, alignOpt;\\nuniform float scale, angle, pixelScale;\\nuniform vec2 resolution;\\n\\nvec3 project(vec3 p) {\\n  vec4 pp = projection * view * model * vec4(p, 1.0);\\n  return pp.xyz / max(pp.w, 0.0001);\\n}\\n\\nfloat computeViewAngle(vec3 a, vec3 b) {\\n  vec3 A = project(a);\\n  vec3 B = project(b);\\n\\n  return atan(\\n    (B.y - A.y) * resolution.y,\\n    (B.x - A.x) * resolution.x\\n  );\\n}\\n\\nconst float PI = 3.141592;\\nconst float TWO_PI = 2.0 * PI;\\nconst float HALF_PI = 0.5 * PI;\\nconst float ONE_AND_HALF_PI = 1.5 * PI;\\n\\nint option = int(floor(alignOpt.x + 0.001));\\nfloat hv_ratio =       alignOpt.y;\\nbool enableAlign =    (alignOpt.z != 0.0);\\n\\nfloat mod_angle(float a) {\\n  return mod(a, PI);\\n}\\n\\nfloat positive_angle(float a) {\\n  return mod_angle((a < 0.0) ?\\n    a + TWO_PI :\\n    a\\n  );\\n}\\n\\nfloat look_upwards(float a) {\\n  float b = positive_angle(a);\\n  return ((b > HALF_PI) && (b <= ONE_AND_HALF_PI)) ?\\n    b - PI :\\n    b;\\n}\\n\\nfloat look_horizontal_or_vertical(float a, float ratio) {\\n  // ratio controls the ratio between being horizontal to (vertical + horizontal)\\n  // if ratio is set to 0.5 then it is 50%, 50%.\\n  // when using a higher ratio e.g. 0.75 the result would\\n  // likely be more horizontal than vertical.\\n\\n  float b = positive_angle(a);\\n\\n  return\\n    (b < (      ratio) * HALF_PI) ? 0.0 :\\n    (b < (2.0 - ratio) * HALF_PI) ? -HALF_PI :\\n    (b < (2.0 + ratio) * HALF_PI) ? 0.0 :\\n    (b < (4.0 - ratio) * HALF_PI) ? HALF_PI :\\n                                    0.0;\\n}\\n\\nfloat roundTo(float a, float b) {\\n  return float(b * floor((a + 0.5 * b) / b));\\n}\\n\\nfloat look_round_n_directions(float a, int n) {\\n  float b = positive_angle(a);\\n  float div = TWO_PI / float(n);\\n  float c = roundTo(b, div);\\n  return look_upwards(c);\\n}\\n\\nfloat applyAlignOption(float rawAngle, float delta) {\\n  return\\n    (option >  2) ? look_round_n_directions(rawAngle + delta, option) :       // option 3-n: round to n directions\\n    (option == 2) ? look_horizontal_or_vertical(rawAngle + delta, hv_ratio) : // horizontal or vertical\\n    (option == 1) ? rawAngle + delta :       // use free angle, and flip to align with one direction of the axis\\n    (option == 0) ? look_upwards(rawAngle) : // use free angle, and stay upwards\\n    (option ==-1) ? 0.0 :                    // useful for backward compatibility, all texts remains horizontal\\n                    rawAngle;                // otherwise return back raw input angle\\n}\\n\\nbool isAxisTitle = (axis.x == 0.0) &&\\n                   (axis.y == 0.0) &&\\n                   (axis.z == 0.0);\\n\\nvoid main() {\\n  //Compute world offset\\n  float axisDistance = position.z;\\n  vec3 dataPosition = axisDistance * axis + offset;\\n\\n  float beta = angle; // i.e. user defined attributes for each tick\\n\\n  float axisAngle;\\n  float clipAngle;\\n  float flip;\\n\\n  if (enableAlign) {\\n    axisAngle = (isAxisTitle) ? HALF_PI :\\n                      computeViewAngle(dataPosition, dataPosition + axis);\\n    clipAngle = computeViewAngle(dataPosition, dataPosition + alignDir);\\n\\n    axisAngle += (sin(axisAngle) < 0.0) ? PI : 0.0;\\n    clipAngle += (sin(clipAngle) < 0.0) ? 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n=t(\"extract-frustum-planes\"),i=t(\"split-polygon\"),a=t(\"./lib/cube.js\"),o=t(\"gl-mat4/multiply\"),s=t(\"gl-mat4/transpose\"),l=t(\"gl-vec4/transformMat4\"),c=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]),u=new Float32Array(16);function f(t,e,r){this.lo=t,this.hi=e,this.pixelsPerDataUnit=r}var h=[0,0,0,1],p=[0,0,0,1];function d(t,e,r,n,i){for(var a=0;a<3;++a){for(var o=h,s=p,c=0;c<3;++c)s[c]=o[c]=r[c];s[3]=o[3]=1,s[a]+=1,l(s,s,e),s[3]<0&&(t[a]=1/0),o[a]-=1,l(o,o,e),o[3]<0&&(t[a]=1/0);var u=(o[0]/o[3]-s[0]/s[3])*n,f=(o[1]/o[3]-s[1]/s[3])*i;t[a]=.25*Math.sqrt(u*u+f*f)}return t}var g=[new f(1/0,-1/0,1/0),new f(1/0,-1/0,1/0),new f(1/0,-1/0,1/0)],m=[0,0,0]},{\"./lib/cube.js\":260,\"extract-frustum-planes\":248,\"gl-mat4/multiply\":301,\"gl-mat4/transpose\":312,\"gl-vec4/transformMat4\":432,\"split-polygon\":567}],267:[function(t,e,r){\"use strict\";var n=t(\"typedarray-pool\"),i=t(\"ndarray-ops\"),a=t(\"ndarray\"),o=[\"uint8\",\"uint8_clamped\",\"uint16\",\"uint32\",\"int8\",\"int16\",\"int32\",\"float32\"];function s(t,e,r,n,i){this.gl=t,this.type=e,this.handle=r,this.length=n,this.usage=i}var l=s.prototype;function c(t,e,r,n,i,a){var o=i.length*i.BYTES_PER_ELEMENT;if(a<0)return t.bufferData(e,i,n),o;if(o+a>r)throw new Error(\"gl-buffer: If resizing buffer, must not specify offset\");return t.bufferSubData(e,a,i),r}function u(t,e){for(var r=n.malloc(t.length,e),i=t.length,a=0;a<i;++a)r[a]=t[a];return r}l.bind=function(){this.gl.bindBuffer(this.type,this.handle)},l.unbind=function(){this.gl.bindBuffer(this.type,null)},l.dispose=function(){this.gl.deleteBuffer(this.handle)},l.update=function(t,e){if(\"number\"!=typeof e&&(e=-1),this.bind(),\"object\"==typeof t&&void 0!==t.shape){var r=t.dtype;if(o.indexOf(r)<0&&(r=\"float32\"),this.type===this.gl.ELEMENT_ARRAY_BUFFER)r=gl.getExtension(\"OES_element_index_uint\")&&\"uint16\"!==r?\"uint32\":\"uint16\";if(r===t.dtype&&function(t,e){for(var r=1,n=e.length-1;n>=0;--n){if(e[n]!==r)return!1;r*=t[n]}return!0}(t.shape,t.stride))0===t.offset&&t.data.length===t.shape[0]?this.length=c(this.gl,this.type,this.length,this.usage,t.data,e):this.length=c(this.gl,this.type,this.length,this.usage,t.data.subarray(t.offset,t.shape[0]),e);else{var s=n.malloc(t.size,r),l=a(s,t.shape);i.assign(l,t),this.length=c(this.gl,this.type,this.length,this.usage,e<0?s:s.subarray(0,t.size),e),n.free(s)}}else if(Array.isArray(t)){var f;f=this.type===this.gl.ELEMENT_ARRAY_BUFFER?u(t,\"uint16\"):u(t,\"float32\"),this.length=c(this.gl,this.type,this.length,this.usage,e<0?f:f.subarray(0,t.length),e),n.free(f)}else if(\"object\"==typeof t&&\"number\"==typeof t.length)this.length=c(this.gl,this.type,this.length,this.usage,t,e);else{if(\"number\"!=typeof 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r=t.positions,i=t.vectors,a={positions:[],vertexIntensity:[],vertexIntensityBounds:t.vertexIntensityBounds,vectors:[],cells:[],coneOffset:t.coneOffset,colormap:t.colormap};if(0===t.positions.length)return e&&(e[0]=[0,0,0],e[1]=[0,0,0]),a;for(var o=0,s=1/0,l=-1/0,c=1/0,u=-1/0,f=1/0,h=-1/0,p=null,d=null,g=[],m=1/0,v=!1,y=0;y<r.length;y++){var x=r[y];s=Math.min(x[0],s),l=Math.max(x[0],l),c=Math.min(x[1],c),u=Math.max(x[1],u),f=Math.min(x[2],f),h=Math.max(x[2],h);var b=i[y];if(n.length(b)>o&&(o=n.length(b)),y){var _=2*n.distance(p,x)/(n.length(d)+n.length(b));_?(m=Math.min(m,_),v=!1):v=!0}v||(p=x,d=b),g.push(b)}var w=[s,c,f],T=[l,u,h];e&&(e[0]=w,e[1]=T),0===o&&(o=1);var k=1/o;isFinite(m)||(m=1),a.vectorScale=m;var A=t.coneSize||.5;t.absoluteConeSize&&(A=t.absoluteConeSize*k),a.coneScale=A;y=0;for(var M=0;y<r.length;y++)for(var S=(x=r[y])[0],E=x[1],L=x[2],C=g[y],P=n.length(C)*k,I=0;I<8;I++){a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.positions.push([S,E,L,M++]),a.vectors.push(C),a.vectors.push(C),a.vectors.push(C),a.vectors.push(C),a.vectors.push(C),a.vectors.push(C),a.vertexIntensity.push(P,P,P),a.vertexIntensity.push(P,P,P);var O=a.positions.length;a.cells.push([O-6,O-5,O-4],[O-3,O-2,O-1])}return a};var i=t(\"./lib/shaders\");e.exports.createMesh=t(\"./create_mesh\"),e.exports.createConeMesh=function(t,r){return e.exports.createMesh(t,r,{shaders:i,traceType:\"cone\"})}},{\"./create_mesh\":269,\"./lib/shaders\":270,\"gl-vec3\":380}],269:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=t(\"gl-buffer\"),a=t(\"gl-vao\"),o=t(\"gl-texture2d\"),s=t(\"gl-mat4/multiply\"),l=t(\"gl-mat4/invert\"),c=t(\"ndarray\"),u=t(\"colormap\"),f=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function h(t,e,r,n,i,a,o,s,l,c,u){this.gl=t,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.pickShader=n,this.trianglePositions=i,this.triangleVectors=a,this.triangleColors=s,this.triangleUVs=l,this.triangleIds=o,this.triangleVAO=c,this.triangleCount=0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.traceType=u,this.tubeScale=1,this.coneScale=2,this.vectorScale=1,this.coneOffset=.25,this._model=f,this._view=f,this._projection=f,this._resolution=[1,1]}var p=h.prototype;function d(t,e){var r=n(t,e.meshShader.vertex,e.meshShader.fragment,null,e.meshShader.attributes);return r.attributes.position.location=0,r.attributes.color.location=2,r.attributes.uv.location=3,r.attributes.vector.location=4,r}function g(t,e){var r=n(t,e.pickShader.vertex,e.pickShader.fragment,null,e.pickShader.attributes);return r.attributes.position.location=0,r.attributes.id.location=1,r.attributes.vector.location=4,r}p.isOpaque=function(){return this.opacity>=1},p.isTransparent=function(){return this.opacity<1},p.pickSlots=1,p.setPickBase=function(t){this.pickId=t},p.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"lightPosition\"in t&&(this.lightPosition=t.lightPosition),\"opacity\"in t&&(this.opacity=t.opacity),\"ambient\"in t&&(this.ambientLight=t.ambient),\"diffuse\"in t&&(this.diffuseLight=t.diffuse),\"specular\"in t&&(this.specularLight=t.specular),\"roughness\"in t&&(this.roughness=t.roughness),\"fresnel\"in t&&(this.fresnel=t.fresnel),void 0!==t.tubeScale&&(this.tubeScale=t.tubeScale),void 0!==t.vectorScale&&(this.vectorScale=t.vectorScale),void 0!==t.coneScale&&(this.coneScale=t.coneScale),void 0!==t.coneOffset&&(this.coneOffset=t.coneOffset),t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(function(t){for(var e=u({colormap:t,nshades:256,format:\"rgba\"}),r=new Uint8Array(1024),n=0;n<256;++n){for(var i=e[n],a=0;a<3;++a)r[4*n+a]=i[a];r[4*n+3]=255*i[3]}return c(r,[256,256,4],[4,0,1])}(t.colormap)),this.texture.generateMipmap());var r=t.cells,n=t.positions,i=t.vectors;if(n&&r&&i){var a=[],o=[],s=[],l=[],f=[];this.cells=r,this.positions=n,this.vectors=i;var h=t.meshColor||[1,1,1,1],p=t.vertexIntensity,d=1/0,g=-1/0;if(p)if(t.vertexIntensityBounds)d=+t.vertexIntensityBounds[0],g=+t.vertexIntensityBounds[1];else for(var m=0;m<p.length;++m){var v=p[m];d=Math.min(d,v),g=Math.max(g,v)}else for(m=0;m<n.length;++m){v=n[m][2];d=Math.min(d,v),g=Math.max(g,v)}this.intensity=p||function(t){for(var e=t.length,r=new Array(e),n=0;n<e;++n)r[n]=t[n][2];return r}(n),this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(m=0;m<n.length;++m)for(var y=n[m],x=0;x<3;++x)!isNaN(y[x])&&isFinite(y[x])&&(this.bounds[0][x]=Math.min(this.bounds[0][x],y[x]),this.bounds[1][x]=Math.max(this.bounds[1][x],y[x]));var b=0;t:for(m=0;m<r.length;++m){var _=r[m];switch(_.length){case 3:for(x=0;x<3;++x){y=n[T=_[x]];for(var w=0;w<3;++w)if(isNaN(y[w])||!isFinite(y[w]))continue t}for(x=0;x<3;++x){var T;y=n[T=_[2-x]];a.push(y[0],y[1],y[2],y[3]);var k=i[T];o.push(k[0],k[1],k[2],k[3]||0);var A,M=h;3===M.length?s.push(M[0],M[1],M[2],1):s.push(M[0],M[1],M[2],M[3]),A=p?[(p[T]-d)/(g-d),0]:[(y[2]-d)/(g-d),0],l.push(A[0],A[1]),f.push(m)}b+=1}}this.triangleCount=b,this.trianglePositions.update(a),this.triangleVectors.update(o),this.triangleColors.update(s),this.triangleUVs.update(l),this.triangleIds.update(new Uint32Array(f))}},p.drawTransparent=p.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||f,n=t.view||f,i=t.projection||f,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);var c={model:r,view:n,projection:i,inverseModel:f.slice(),clipBounds:a,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],opacity:this.opacity,tubeScale:this.tubeScale,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,texture:0};c.inverseModel=l(c.inverseModel,c.model),e.disable(e.CULL_FACE),this.texture.bind(0);var u=new Array(16);s(u,c.view,c.model),s(u,c.projection,u),l(u,u);for(o=0;o<3;++o)c.eyePosition[o]=u[12+o]/u[15];var h=u[15];for(o=0;o<3;++o)h+=this.lightPosition[o]*u[4*o+3];for(o=0;o<3;++o){for(var p=u[12+o],d=0;d<3;++d)p+=u[4*d+o]*this.lightPosition[d];c.lightPosition[o]=p/h}if(this.triangleCount>0){var g=this.triShader;g.bind(),g.uniforms=c,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()}},p.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||f,n=t.view||f,i=t.projection||f,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s={model:r,view:n,projection:i,clipBounds:a,tubeScale:this.tubeScale,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,pickId:this.pickId/255},l=this.pickShader;l.bind(),l.uniforms=s,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind())},p.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions[r[1]].slice(0,3),i={position:n,dataCoordinate:n,index:Math.floor(r[1]/48)};return\"cone\"===this.traceType?i.index=Math.floor(r[1]/48):\"streamtube\"===this.traceType&&(i.intensity=this.intensity[r[1]],i.velocity=this.vectors[r[1]].slice(0,3),i.divergence=this.vectors[r[1]][3],i.index=e),i},p.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.pickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleVectors.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleIds.dispose()},e.exports=function(t,e,r){var n=r.shaders;1===arguments.length&&(t=(e=t).gl);var s=d(t,n),l=g(t,n),u=o(t,c(new Uint8Array([255,255,255,255]),[1,1,4]));u.generateMipmap(),u.minFilter=t.LINEAR_MIPMAP_LINEAR,u.magFilter=t.LINEAR;var f=i(t),p=i(t),m=i(t),v=i(t),y=i(t),x=a(t,[{buffer:f,type:t.FLOAT,size:4},{buffer:y,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:m,type:t.FLOAT,size:4},{buffer:v,type:t.FLOAT,size:2},{buffer:p,type:t.FLOAT,size:4}]),b=new h(t,u,s,l,f,p,y,m,v,x,r.traceType||\"cone\");return b.update(e),b}},{colormap:137,\"gl-buffer\":267,\"gl-mat4/invert\":299,\"gl-mat4/multiply\":301,\"gl-shader\":339,\"gl-texture2d\":356,\"gl-vao\":361,ndarray:483}],270:[function(t,e,r){var n=t(\"glslify\"),i=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the cone vertex and normal at the given index.\\n//\\n// The returned vertex is for a cone with its top at origin and height of 1.0,\\n// pointing in the direction of the vector attribute.\\n//\\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\\n// These vertices are used to make up the triangles of the cone by the following:\\n//   segment + 0 top vertex\\n//   segment + 1 perimeter vertex a+1\\n//   segment + 2 perimeter vertex a\\n//   segment + 3 center base vertex\\n//   segment + 4 perimeter vertex a\\n//   segment + 5 perimeter vertex a+1\\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\\n// To go from index to segment, floor(index / 6)\\n// To go from segment to angle, 2*pi * (segment/segmentCount)\\n// To go from index to segment index, index - (segment*6)\\n//\\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\\n\\n  const float segmentCount = 8.0;\\n\\n  float index = rawIndex - floor(rawIndex /\\n    (segmentCount * 6.0)) *\\n    (segmentCount * 6.0);\\n\\n  float segment = floor(0.001 + index/6.0);\\n  float segmentIndex = index - (segment*6.0);\\n\\n  normal = -normalize(d);\\n\\n  if (segmentIndex > 2.99 && segmentIndex < 3.01) {\\n    return mix(vec3(0.0), -d, coneOffset);\\n  }\\n\\n  float nextAngle = (\\n    (segmentIndex > 0.99 &&  segmentIndex < 1.01) ||\\n    (segmentIndex > 4.99 &&  segmentIndex < 5.01)\\n  ) ? 1.0 : 0.0;\\n  float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\\n\\n  vec3 v1 = mix(d, vec3(0.0), coneOffset);\\n  vec3 v2 = v1 - d;\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d)*0.25;\\n  vec3 y = v * sin(angle) * length(d)*0.25;\\n  vec3 v3 = v2 + x + y;\\n  if (segmentIndex < 3.0) {\\n    vec3 tx = u * sin(angle);\\n    vec3 ty = v * -cos(angle);\\n    vec3 tangent = tx + ty;\\n    normal = normalize(cross(v3 - v1, tangent));\\n  }\\n\\n  if (segmentIndex == 0.0) {\\n    return mix(d, vec3(0.0), coneOffset);\\n  }\\n  return v3;\\n}\\n\\nattribute vec3 vector;\\nattribute vec4 color, position;\\nattribute vec2 uv;\\n\\nuniform float vectorScale, coneScale, coneOffset;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 eyePosition, lightPosition;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  // Scale the vector magnitude to stay constant with\\n  // model & view changes.\\n  vec3 normal;\\n  vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector), position.w, coneOffset, normal);\\n  vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * conePosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n  f_eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n  // vec4 m_position  = model * vec4(conePosition, 1.0);\\n  vec4 t_position  = view * conePosition;\\n  gl_Position      = projection * t_position;\\n\\n  f_color          = color;\\n  f_data           = conePosition.xyz;\\n  f_position       = position.xyz;\\n  f_uv             = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n  float G = min(1.0, min(G1, G2));\\n  \\n  //Distribution term\\n  float D = beckmannDistribution(NdotH, roughness);\\n\\n  //Fresnel term\\n  float F = pow(1.0 - VdotN, fresnel);\\n\\n  //Multiply terms and done\\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n  vec3 N = normalize(f_normal);\\n  vec3 L = normalize(f_lightDirection);\\n  vec3 V = normalize(f_eyeDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = litColor * opacity;\\n}\\n\"]),o=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the cone vertex and normal at the given index.\\n//\\n// The returned vertex is for a cone with its top at origin and height of 1.0,\\n// pointing in the direction of the vector attribute.\\n//\\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\\n// These vertices are used to make up the triangles of the cone by the following:\\n//   segment + 0 top vertex\\n//   segment + 1 perimeter vertex a+1\\n//   segment + 2 perimeter vertex a\\n//   segment + 3 center base vertex\\n//   segment + 4 perimeter vertex a\\n//   segment + 5 perimeter vertex a+1\\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\\n// To go from index to segment, floor(index / 6)\\n// To go from segment to angle, 2*pi * (segment/segmentCount)\\n// To go from index to segment index, index - (segment*6)\\n//\\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\\n\\n  const float segmentCount = 8.0;\\n\\n  float index = rawIndex - floor(rawIndex /\\n    (segmentCount * 6.0)) *\\n    (segmentCount * 6.0);\\n\\n  float segment = floor(0.001 + index/6.0);\\n  float segmentIndex = index - (segment*6.0);\\n\\n  normal = -normalize(d);\\n\\n  if (segmentIndex > 2.99 && segmentIndex < 3.01) {\\n    return mix(vec3(0.0), -d, coneOffset);\\n  }\\n\\n  float nextAngle = (\\n    (segmentIndex > 0.99 &&  segmentIndex < 1.01) ||\\n    (segmentIndex > 4.99 &&  segmentIndex < 5.01)\\n  ) ? 1.0 : 0.0;\\n  float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\\n\\n  vec3 v1 = mix(d, vec3(0.0), coneOffset);\\n  vec3 v2 = v1 - d;\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d)*0.25;\\n  vec3 y = v * sin(angle) * length(d)*0.25;\\n  vec3 v3 = v2 + x + y;\\n  if (segmentIndex < 3.0) {\\n    vec3 tx = u * sin(angle);\\n    vec3 ty = v * -cos(angle);\\n    vec3 tangent = tx + ty;\\n    normal = normalize(cross(v3 - v1, tangent));\\n  }\\n\\n  if (segmentIndex == 0.0) {\\n    return mix(d, vec3(0.0), coneOffset);\\n  }\\n  return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform float vectorScale, coneScale, coneOffset;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  vec3 normal;\\n  vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector.xyz), position.w, coneOffset, normal);\\n  vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n  gl_Position = projection * view * conePosition;\\n  f_id        = id;\\n  f_position  = position.xyz;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3  clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n  gl_FragColor = vec4(pickId, 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r=0;r<3;++r)t[0][r]=Math.min(t[0][r],e[r]),t[1][r]=Math.max(t[1][r],e[r])}l.isOpaque=function(){return!this.hasAlpha},l.isTransparent=function(){return this.hasAlpha},l.drawTransparent=l.draw=function(t){var e=this.gl,r=this.shader.uniforms;this.shader.bind();var n=r.view=t.view||o,i=r.projection=t.projection||o;r.model=t.model||o,r.clipBounds=this.clipBounds,r.opacity=this.opacity;var a=n[12],s=n[13],l=n[14],c=n[15],u=(t._ortho||!1?2:1)*this.pixelRatio*(i[3]*a+i[7]*s+i[11]*l+i[15]*c)/e.drawingBufferHeight;this.vao.bind();for(var f=0;f<3;++f)e.lineWidth(this.lineWidth[f]*this.pixelRatio),r.capSize=this.capSize[f]*u,this.lineCount[f]&&e.drawArrays(e.LINES,this.lineOffset[f],this.lineCount[f]);this.vao.unbind()};var u=function(){for(var t=new Array(3),e=0;e<3;++e){for(var r=[],n=1;n<=2;++n)for(var i=-1;i<=1;i+=2){var a=[0,0,0];a[(n+e)%3]=i,r.push(a)}t[e]=r}return t}();function f(t,e,r,n){for(var i=u[n],a=0;a<i.length;++a){var 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t.bindRenderbuffer(t.RENDERBUFFER,a),t.renderbufferStorage(t.RENDERBUFFER,n,e,r),t.framebufferRenderbuffer(t.FRAMEBUFFER,i,t.RENDERBUFFER,a),a}function d(t,e,r,n,i,a,o,s){this.gl=t,this._shape=[0|e,0|r],this._destroyed=!1,this._ext=s,this.color=new Array(i);for(var d=0;d<i;++d)this.color[d]=null;this._color_rb=null,this.depth=null,this._depth_rb=null,this._colorType=n,this._useDepth=a,this._useStencil=o;var g=this,m=[0|e,0|r];Object.defineProperties(m,{0:{get:function(){return g._shape[0]},set:function(t){return g.width=t}},1:{get:function(){return g._shape[1]},set:function(t){return g.height=t}}}),this._shapeVector=m,function(t){var e=c(t.gl),r=t.gl,n=t.handle=r.createFramebuffer(),i=t._shape[0],a=t._shape[1],o=t.color.length,s=t._ext,d=t._useStencil,g=t._useDepth,m=t._colorType;r.bindFramebuffer(r.FRAMEBUFFER,n);for(var v=0;v<o;++v)t.color[v]=h(r,i,a,m,r.RGBA,r.COLOR_ATTACHMENT0+v);0===o?(t._color_rb=p(r,i,a,r.RGBA4,r.COLOR_ATTACHMENT0),s&&s.drawBuffersWEBGL(l[0])):o>1&&s.drawBuffersWEBGL(l[o]);var y=r.getExtension(\"WEBGL_depth_texture\");y?d?t.depth=h(r,i,a,y.UNSIGNED_INT_24_8_WEBGL,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):g&&(t.depth=h(r,i,a,r.UNSIGNED_SHORT,r.DEPTH_COMPONENT,r.DEPTH_ATTACHMENT)):g&&d?t._depth_rb=p(r,i,a,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):g?t._depth_rb=p(r,i,a,r.DEPTH_COMPONENT16,r.DEPTH_ATTACHMENT):d&&(t._depth_rb=p(r,i,a,r.STENCIL_INDEX,r.STENCIL_ATTACHMENT));var x=r.checkFramebufferStatus(r.FRAMEBUFFER);if(x!==r.FRAMEBUFFER_COMPLETE){t._destroyed=!0,r.bindFramebuffer(r.FRAMEBUFFER,null),r.deleteFramebuffer(t.handle),t.handle=null,t.depth&&(t.depth.dispose(),t.depth=null),t._depth_rb&&(r.deleteRenderbuffer(t._depth_rb),t._depth_rb=null);for(v=0;v<t.color.length;++v)t.color[v].dispose(),t.color[v]=null;t._color_rb&&(r.deleteRenderbuffer(t._color_rb),t._color_rb=null),u(r,e),f(x)}u(r,e)}(this)}var g=d.prototype;function m(t,e,r){if(t._destroyed)throw new Error(\"gl-fbo: Can't resize destroyed FBO\");if(t._shape[0]!==e||t._shape[1]!==r){var n=t.gl,i=n.getParameter(n.MAX_RENDERBUFFER_SIZE);if(e<0||e>i||r<0||r>i)throw new Error(\"gl-fbo: Can't resize FBO, invalid dimensions\");t._shape[0]=e,t._shape[1]=r;for(var a=c(n),o=0;o<t.color.length;++o)t.color[o].shape=t._shape;t._color_rb&&(n.bindRenderbuffer(n.RENDERBUFFER,t._color_rb),n.renderbufferStorage(n.RENDERBUFFER,n.RGBA4,t._shape[0],t._shape[1])),t.depth&&(t.depth.shape=t._shape),t._depth_rb&&(n.bindRenderbuffer(n.RENDERBUFFER,t._depth_rb),t._useDepth&&t._useStencil?n.renderbufferStorage(n.RENDERBUFFER,n.DEPTH_STENCIL,t._shape[0],t._shape[1]):t._useDepth?n.renderbufferStorage(n.RENDERBUFFER,n.DEPTH_COMPONENT16,t._shape[0],t._shape[1]):t._useStencil&&n.renderbufferStorage(n.RENDERBUFFER,n.STENCIL_INDEX,t._shape[0],t._shape[1])),n.bindFramebuffer(n.FRAMEBUFFER,t.handle);var s=n.checkFramebufferStatus(n.FRAMEBUFFER);s!==n.FRAMEBUFFER_COMPLETE&&(t.dispose(),u(n,a),f(s)),u(n,a)}}Object.defineProperties(g,{shape:{get:function(){return this._destroyed?[0,0]:this._shapeVector},set:function(t){if(Array.isArray(t)||(t=[0|t,0|t]),2!==t.length)throw new Error(\"gl-fbo: Shape vector must be length 2\");var e=0|t[0],r=0|t[1];return m(this,e,r),[e,r]},enumerable:!1},width:{get:function(){return this._destroyed?0:this._shape[0]},set:function(t){return m(this,t|=0,this._shape[1]),t},enumerable:!1},height:{get:function(){return this._destroyed?0:this._shape[1]},set:function(t){return t|=0,m(this,this._shape[0],t),t},enumerable:!1}}),g.bind=function(){if(!this._destroyed){var t=this.gl;t.bindFramebuffer(t.FRAMEBUFFER,this.handle),t.viewport(0,0,this._shape[0],this._shape[1])}},g.dispose=function(){if(!this._destroyed){this._destroyed=!0;var t=this.gl;t.deleteFramebuffer(this.handle),this.handle=null,this.depth&&(this.depth.dispose(),this.depth=null),this._depth_rb&&(t.deleteRenderbuffer(this._depth_rb),this._depth_rb=null);for(var e=0;e<this.color.length;++e)this.color[e].dispose(),this.color[e]=null;this._color_rb&&(t.deleteRenderbuffer(this._color_rb),this._color_rb=null)}}},{\"gl-texture2d\":356}],277:[function(t,e,r){var n=t(\"sprintf-js\").sprintf,i=t(\"gl-constants/lookup\"),a=t(\"glsl-shader-name\"),o=t(\"add-line-numbers\");e.exports=function(t,e,r){\"use strict\";var s=a(e)||\"of unknown name (see npm glsl-shader-name)\",l=\"unknown type\";void 0!==r&&(l=r===i.FRAGMENT_SHADER?\"fragment\":\"vertex\");for(var c=n(\"Error compiling %s shader %s:\\n\",l,s),u=n(\"%s%s\",c,t),f=t.split(\"\\n\"),h={},p=0;p<f.length;p++){var d=f[p];if(\"\"!==d&&\"\\0\"!==d){var g=parseInt(d.split(\":\")[2]);if(isNaN(g))throw new Error(n(\"Could not parse error: %s\",d));h[g]=d}}var m=o(e).split(\"\\n\");for(p=0;p<m.length;p++)if(h[p+3]||h[p+2]||h[p+1]){var v=m[p];if(c+=v+\"\\n\",h[p+1]){var y=h[p+1];y=y.substr(y.split(\":\",3).join(\":\").length+1).trim(),c+=n(\"^^^ %s\\n\\n\",y)}}return{long:c.trim(),short:u.trim()}}},{\"add-line-numbers\":72,\"gl-constants/lookup\":272,\"glsl-shader-name\":434,\"sprintf-js\":568}],278:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=t.gl,n=o(r,l.vertex,l.fragment),i=o(r,l.pickVertex,l.pickFragment),a=s(r),u=s(r),f=s(r),h=s(r),p=new c(t,n,i,a,u,f,h);return p.update(e),t.addObject(p),p};var n=t(\"binary-search-bounds\"),i=t(\"iota-array\"),a=t(\"typedarray-pool\"),o=t(\"gl-shader\"),s=t(\"gl-buffer\"),l=t(\"./lib/shaders\");function c(t,e,r,n,i,a,o){this.plot=t,this.shader=e,this.pickShader=r,this.positionBuffer=n,this.weightBuffer=i,this.colorBuffer=a,this.idBuffer=o,this.xData=[],this.yData=[],this.shape=[0,0],this.bounds=[1/0,1/0,-1/0,-1/0],this.pickOffset=0}var u,f=c.prototype,h=[0,0,1,0,0,1,1,0,1,1,0,1];f.draw=(u=[1,0,0,0,1,0,0,0,1],function(){var t=this.plot,e=this.shader,r=this.bounds,n=this.numVertices;if(!(n<=0)){var i=t.gl,a=t.dataBox,o=r[2]-r[0],s=r[3]-r[1],l=a[2]-a[0],c=a[3]-a[1];u[0]=2*o/l,u[4]=2*s/c,u[6]=2*(r[0]-a[0])/l-1,u[7]=2*(r[1]-a[1])/c-1,e.bind();var f=e.uniforms;f.viewTransform=u,f.shape=this.shape;var h=e.attributes;this.positionBuffer.bind(),h.position.pointer(),this.weightBuffer.bind(),h.weight.pointer(i.UNSIGNED_BYTE,!1),this.colorBuffer.bind(),h.color.pointer(i.UNSIGNED_BYTE,!0),i.drawArrays(i.TRIANGLES,0,n)}}),f.drawPick=function(){var t=[1,0,0,0,1,0,0,0,1],e=[0,0,0,0];return function(r){var n=this.plot,i=this.pickShader,a=this.bounds,o=this.numVertices;if(!(o<=0)){var s=n.gl,l=n.dataBox,c=a[2]-a[0],u=a[3]-a[1],f=l[2]-l[0],h=l[3]-l[1];t[0]=2*c/f,t[4]=2*u/h,t[6]=2*(a[0]-l[0])/f-1,t[7]=2*(a[1]-l[1])/h-1;for(var p=0;p<4;++p)e[p]=r>>8*p&255;this.pickOffset=r,i.bind();var d=i.uniforms;d.viewTransform=t,d.pickOffset=e,d.shape=this.shape;var g=i.attributes;return this.positionBuffer.bind(),g.position.pointer(),this.weightBuffer.bind(),g.weight.pointer(s.UNSIGNED_BYTE,!1),this.idBuffer.bind(),g.pickId.pointer(s.UNSIGNED_BYTE,!1),s.drawArrays(s.TRIANGLES,0,o),r+this.shape[0]*this.shape[1]}}}(),f.pick=function(t,e,r){var n=this.pickOffset,i=this.shape[0]*this.shape[1];if(r<n||r>=n+i)return null;var a=r-n,o=this.xData,s=this.yData;return{object:this,pointId:a,dataCoord:[o[a%this.shape[0]],s[a/this.shape[0]|0]]}},f.update=function(t){var e=(t=t||{}).shape||[0,0],r=t.x||i(e[0]),o=t.y||i(e[1]),s=t.z||new Float32Array(e[0]*e[1]),l=!1!==t.zsmooth;this.xData=r,this.yData=o;var c,u,f,p,d=t.colorLevels||[0],g=t.colorValues||[0,0,0,1],m=d.length,v=this.bounds;l?(c=v[0]=r[0],u=v[1]=o[0],f=v[2]=r[r.length-1],p=v[3]=o[o.length-1]):(c=v[0]=r[0]+(r[1]-r[0])/2,u=v[1]=o[0]+(o[1]-o[0])/2,f=v[2]=r[r.length-1]+(r[r.length-1]-r[r.length-2])/2,p=v[3]=o[o.length-1]+(o[o.length-1]-o[o.length-2])/2);var y=1/(f-c),x=1/(p-u),b=e[0],_=e[1];this.shape=[b,_];var w=(l?(b-1)*(_-1):b*_)*(h.length>>>1);this.numVertices=w;for(var T=a.mallocUint8(4*w),k=a.mallocFloat32(2*w),A=a.mallocUint8(2*w),M=a.mallocUint32(w),S=0,E=l?b-1:b,L=l?_-1:_,C=0;C<L;++C){var P,I;l?(P=x*(o[C]-u),I=x*(o[C+1]-u)):(P=C<_-1?x*(o[C]-(o[C+1]-o[C])/2-u):x*(o[C]-(o[C]-o[C-1])/2-u),I=C<_-1?x*(o[C]+(o[C+1]-o[C])/2-u):x*(o[C]+(o[C]-o[C-1])/2-u));for(var O=0;O<E;++O){var z,D;l?(z=y*(r[O]-c),D=y*(r[O+1]-c)):(z=O<b-1?y*(r[O]-(r[O+1]-r[O])/2-c):y*(r[O]-(r[O]-r[O-1])/2-c),D=O<b-1?y*(r[O]+(r[O+1]-r[O])/2-c):y*(r[O]+(r[O]-r[O-1])/2-c));for(var R=0;R<h.length;R+=2){var F,B,N,j,U=h[R],V=h[R+1],q=s[l?(C+V)*b+(O+U):C*b+O],H=n.le(d,q);if(H<0)F=g[0],B=g[1],N=g[2],j=g[3];else if(H===m-1)F=g[4*m-4],B=g[4*m-3],N=g[4*m-2],j=g[4*m-1];else{var G=(q-d[H])/(d[H+1]-d[H]),Y=1-G,W=4*H,X=4*(H+1);F=Y*g[W]+G*g[X],B=Y*g[W+1]+G*g[X+1],N=Y*g[W+2]+G*g[X+2],j=Y*g[W+3]+G*g[X+3]}T[4*S]=255*F,T[4*S+1]=255*B,T[4*S+2]=255*N,T[4*S+3]=255*j,k[2*S]=.5*z+.5*D,k[2*S+1]=.5*P+.5*I,A[2*S]=U,A[2*S+1]=V,M[S]=C*b+O,S+=1}}}this.positionBuffer.update(k),this.weightBuffer.update(A),this.colorBuffer.update(T),this.idBuffer.update(M),a.free(k),a.free(T),a.free(A),a.free(M)},f.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.positionBuffer.dispose(),this.weightBuffer.dispose(),this.colorBuffer.dispose(),this.idBuffer.dispose(),this.plot.removeObject(this)}},{\"./lib/shaders\":279,\"binary-search-bounds\":103,\"gl-buffer\":267,\"gl-shader\":339,\"iota-array\":451,\"typedarray-pool\":617}],279:[function(t,e,r){\"use strict\";var n=t(\"glslify\");e.exports={fragment:n([\"precision lowp float;\\n#define GLSLIFY 1\\nvarying vec4 fragColor;\\nvoid main() {\\n  gl_FragColor = vec4(fragColor.rgb * fragColor.a, fragColor.a);\\n}\\n\"]),vertex:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 color;\\nattribute vec2 weight;\\n\\nuniform vec2 shape;\\nuniform mat3 viewTransform;\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  vec3 vPosition = viewTransform * vec3( position + (weight-.5)/(shape-1.) , 1.0);\\n  fragColor = color;\\n  gl_Position = vec4(vPosition.xy, 0, vPosition.z);\\n}\\n\"]),pickFragment:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragId;\\nvarying vec2 vWeight;\\n\\nuniform vec2 shape;\\nuniform vec4 pickOffset;\\n\\nvoid main() {\\n  vec2 d = step(.5, vWeight);\\n  vec4 id = fragId + pickOffset;\\n  id.x += d.x + d.y*shape.x;\\n\\n  id.y += floor(id.x / 256.0);\\n  id.x -= floor(id.x / 256.0) * 256.0;\\n\\n  id.z += floor(id.y / 256.0);\\n  id.y -= floor(id.y / 256.0) * 256.0;\\n\\n  id.w += floor(id.z / 256.0);\\n  id.z -= floor(id.z / 256.0) * 256.0;\\n\\n  gl_FragColor = id/255.;\\n}\\n\"]),pickVertex:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\nattribute vec2 weight;\\n\\nuniform vec2 shape;\\nuniform mat3 viewTransform;\\n\\nvarying vec4 fragId;\\nvarying vec2 vWeight;\\n\\nvoid main() {\\n  vWeight = weight;\\n\\n  fragId = pickId;\\n\\n  vec3 vPosition = viewTransform * vec3( position + (weight-.5)/(shape-1.) , 1.0);\\n  gl_Position = vec4(vPosition.xy, 0, vPosition.z);\\n}\\n\"])}},{glslify:442}],280:[function(t,e,r){var n=t(\"glslify\"),i=t(\"gl-shader\"),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, nextPosition;\\nattribute float arcLength, lineWidth;\\nattribute vec4 color;\\n\\nuniform vec2 screenShape;\\nuniform float pixelRatio;\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 fragColor;\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\n\\nvec4 project(vec3 p) {\\n  return projection * view * model * vec4(p, 1.0);\\n}\\n\\nvoid main() {\\n  vec4 startPoint = project(position);\\n  vec4 endPoint   = project(nextPosition);\\n\\n  vec2 A = startPoint.xy / startPoint.w;\\n  vec2 B =   endPoint.xy /   endPoint.w;\\n\\n  float clipAngle = atan(\\n    (B.y - A.y) * screenShape.y,\\n    (B.x - A.x) * screenShape.x\\n  );\\n\\n  vec2 offset = 0.5 * pixelRatio * lineWidth * vec2(\\n    sin(clipAngle),\\n    -cos(clipAngle)\\n  ) / screenShape;\\n\\n  gl_Position = vec4(startPoint.xy + startPoint.w * offset, startPoint.zw);\\n\\n  worldPosition = position;\\n  pixelArcLength = arcLength;\\n  fragColor = color;\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3      clipBounds[2];\\nuniform sampler2D dashTexture;\\nuniform float     dashScale;\\nuniform float     opacity;\\n\\nvarying vec3    worldPosition;\\nvarying float   pixelArcLength;\\nvarying vec4    fragColor;\\n\\nvoid main() {\\n  if (\\n    outOfRange(clipBounds[0], clipBounds[1], worldPosition) ||\\n    fragColor.a * opacity == 0.\\n  ) discard;\\n\\n  float dashWeight = texture2D(dashTexture, vec2(dashScale * pixelArcLength, 0)).r;\\n  if(dashWeight < 0.5) {\\n    discard;\\n  }\\n  gl_FragColor = fragColor * opacity;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\n#define FLOAT_MAX  1.70141184e38\\n#define FLOAT_MIN  1.17549435e-38\\n\\n// https://github.com/mikolalysenko/glsl-read-float/blob/master/index.glsl\\nvec4 packFloat(float v) {\\n  float av = abs(v);\\n\\n  //Handle special cases\\n  if(av < FLOAT_MIN) {\\n    return vec4(0.0, 0.0, 0.0, 0.0);\\n  } else if(v > FLOAT_MAX) {\\n    return vec4(127.0, 128.0, 0.0, 0.0) / 255.0;\\n  } else if(v < -FLOAT_MAX) {\\n    return vec4(255.0, 128.0, 0.0, 0.0) / 255.0;\\n  }\\n\\n  vec4 c = vec4(0,0,0,0);\\n\\n  //Compute exponent and mantissa\\n  float e = floor(log2(av));\\n  float m = av * pow(2.0, -e) - 1.0;\\n\\n  //Unpack mantissa\\n  c[1] = floor(128.0 * m);\\n  m -= c[1] / 128.0;\\n  c[2] = floor(32768.0 * m);\\n  m -= c[2] / 32768.0;\\n  c[3] = floor(8388608.0 * m);\\n\\n  //Unpack exponent\\n  float ebias = e + 127.0;\\n  c[0] = floor(ebias / 2.0);\\n  ebias -= c[0] * 2.0;\\n  c[1] += floor(ebias) * 128.0;\\n\\n  //Unpack sign bit\\n  c[0] += 128.0 * step(0.0, -v);\\n\\n  //Scale back to range\\n  return c / 255.0;\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform float pickId;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 worldPosition;\\nvarying float pixelArcLength;\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], worldPosition)) discard;\\n\\n  gl_FragColor = vec4(pickId/255.0, packFloat(pixelArcLength).xyz);\\n}\"]),l=[{name:\"position\",type:\"vec3\"},{name:\"nextPosition\",type:\"vec3\"},{name:\"arcLength\",type:\"float\"},{name:\"lineWidth\",type:\"float\"},{name:\"color\",type:\"vec4\"}];r.createShader=function(t){return i(t,a,o,null,l)},r.createPickShader=function(t){return i(t,a,s,null,l)}},{\"gl-shader\":339,glslify:282}],281:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl||t.scene&&t.scene.gl,r=f(e);r.attributes.position.location=0,r.attributes.nextPosition.location=1,r.attributes.arcLength.location=2,r.attributes.lineWidth.location=3,r.attributes.color.location=4;var o=h(e);o.attributes.position.location=0,o.attributes.nextPosition.location=1,o.attributes.arcLength.location=2,o.attributes.lineWidth.location=3,o.attributes.color.location=4;for(var s=n(e),l=i(e,[{buffer:s,size:3,offset:0,stride:48},{buffer:s,size:3,offset:12,stride:48},{buffer:s,size:1,offset:24,stride:48},{buffer:s,size:1,offset:28,stride:48},{buffer:s,size:4,offset:32,stride:48}]),u=c(new Array(1024),[256,1,4]),p=0;p<1024;++p)u.data[p]=255;var d=a(e,u);d.wrap=e.REPEAT;var g=new v(e,r,o,s,l,d);return g.update(t),g};var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"gl-texture2d\"),o=new Uint8Array(4),s=new Float32Array(o.buffer);var l=t(\"binary-search-bounds\"),c=t(\"ndarray\"),u=t(\"./lib/shaders\"),f=u.createShader,h=u.createPickShader,p=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function d(t,e){for(var r=0,n=0;n<3;++n){var i=t[n]-e[n];r+=i*i}return Math.sqrt(r)}function g(t){for(var e=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],r=0;r<3;++r)e[0][r]=Math.max(t[0][r],e[0][r]),e[1][r]=Math.min(t[1][r],e[1][r]);return e}function m(t,e,r,n){this.arcLength=t,this.position=e,this.index=r,this.dataCoordinate=n}function v(t,e,r,n,i,a){this.gl=t,this.shader=e,this.pickShader=r,this.buffer=n,this.vao=i,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.points=[],this.arcLength=[],this.vertexCount=0,this.bounds=[[0,0,0],[0,0,0]],this.pickId=0,this.lineWidth=1,this.texture=a,this.dashScale=1,this.opacity=1,this.hasAlpha=!1,this.dirty=!0,this.pixelRatio=1}var y=v.prototype;y.isTransparent=function(){return this.hasAlpha},y.isOpaque=function(){return!this.hasAlpha},y.pickSlots=1,y.setPickBase=function(t){this.pickId=t},y.drawTransparent=y.draw=function(t){if(this.vertexCount){var e=this.gl,r=this.shader,n=this.vao;r.bind(),r.uniforms={model:t.model||p,view:t.view||p,projection:t.projection||p,clipBounds:g(this.clipBounds),dashTexture:this.texture.bind(),dashScale:this.dashScale/this.arcLength[this.arcLength.length-1],opacity:this.opacity,screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount),n.unbind()}},y.drawPick=function(t){if(this.vertexCount){var e=this.gl,r=this.pickShader,n=this.vao;r.bind(),r.uniforms={model:t.model||p,view:t.view||p,projection:t.projection||p,pickId:this.pickId,clipBounds:g(this.clipBounds),screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount),n.unbind()}},y.update=function(t){var e,r;this.dirty=!0;var n=!!t.connectGaps;\"dashScale\"in t&&(this.dashScale=t.dashScale),this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=+t.opacity,this.opacity<1&&(this.hasAlpha=!0));var i=[],a=[],o=[],s=0,u=0,f=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],h=t.position||t.positions;if(h){var p=t.color||t.colors||[0,0,0,1],g=t.lineWidth||1,m=!1;t:for(e=1;e<h.length;++e){var v,y,x,b=h[e-1],_=h[e];for(a.push(s),o.push(b.slice()),r=0;r<3;++r){if(isNaN(b[r])||isNaN(_[r])||!isFinite(b[r])||!isFinite(_[r])){if(!n&&i.length>0){for(var w=0;w<24;++w)i.push(i[i.length-12]);u+=2,m=!0}continue t}f[0][r]=Math.min(f[0][r],b[r],_[r]),f[1][r]=Math.max(f[1][r],b[r],_[r])}Array.isArray(p[0])?(v=p.length>e-1?p[e-1]:p.length>0?p[p.length-1]:[0,0,0,1],y=p.length>e?p[e]:p.length>0?p[p.length-1]:[0,0,0,1]):v=y=p,3===v.length&&(v=[v[0],v[1],v[2],1]),3===y.length&&(y=[y[0],y[1],y[2],1]),!this.hasAlpha&&v[3]<1&&(this.hasAlpha=!0),x=Array.isArray(g)?g.length>e-1?g[e-1]:g.length>0?g[g.length-1]:[0,0,0,1]:g;var T=s;if(s+=d(b,_),m){for(r=0;r<2;++r)i.push(b[0],b[1],b[2],_[0],_[1],_[2],T,x,v[0],v[1],v[2],v[3]);u+=2,m=!1}i.push(b[0],b[1],b[2],_[0],_[1],_[2],T,x,v[0],v[1],v[2],v[3],b[0],b[1],b[2],_[0],_[1],_[2],T,-x,v[0],v[1],v[2],v[3],_[0],_[1],_[2],b[0],b[1],b[2],s,-x,y[0],y[1],y[2],y[3],_[0],_[1],_[2],b[0],b[1],b[2],s,x,y[0],y[1],y[2],y[3]),u+=4}}if(this.buffer.update(i),a.push(s),o.push(h[h.length-1].slice()),this.bounds=f,this.vertexCount=u,this.points=o,this.arcLength=a,\"dashes\"in t){var k=t.dashes.slice();for(k.unshift(0),e=1;e<k.length;++e)k[e]=k[e-1]+k[e];var A=c(new Array(1024),[256,1,4]);for(e=0;e<256;++e){for(r=0;r<4;++r)A.set(e,0,r,0);1&l.le(k,k[k.length-1]*e/255)?A.set(e,0,0,0):A.set(e,0,0,255)}this.texture.setPixels(A)}},y.dispose=function(){this.shader.dispose(),this.vao.dispose(),this.buffer.dispose()},y.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=function(t,e,r,n){return o[0]=n,o[1]=r,o[2]=e,o[3]=t,s[0]}(t.value[0],t.value[1],t.value[2],0),r=l.le(this.arcLength,e);if(r<0)return null;if(r===this.arcLength.length-1)return new m(this.arcLength[this.arcLength.length-1],this.points[this.points.length-1].slice(),r);for(var n=this.points[r],i=this.points[Math.min(r+1,this.points.length-1)],a=(e-this.arcLength[r])/(this.arcLength[r+1]-this.arcLength[r]),c=1-a,u=[0,0,0],f=0;f<3;++f)u[f]=c*n[f]+a*i[f];var h=Math.min(a<.5?r:r+1,this.points.length-1);return new m(e,u,h,this.points[h])}},{\"./lib/shaders\":280,\"binary-search-bounds\":103,\"gl-buffer\":267,\"gl-texture2d\":356,\"gl-vao\":361,ndarray:483}],282:[function(t,e,r){arguments[4][265][0].apply(r,arguments)},{dup:265}],283:[function(t,e,r){e.exports=function(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=e[4],s=e[5],l=e[6],c=e[7],u=e[8],f=e[9],h=e[10],p=e[11],d=e[12],g=e[13],m=e[14],v=e[15];return t[0]=s*(h*v-p*m)-f*(l*v-c*m)+g*(l*p-c*h),t[1]=-(n*(h*v-p*m)-f*(i*v-a*m)+g*(i*p-a*h)),t[2]=n*(l*v-c*m)-s*(i*v-a*m)+g*(i*c-a*l),t[3]=-(n*(l*p-c*h)-s*(i*p-a*h)+f*(i*c-a*l)),t[4]=-(o*(h*v-p*m)-u*(l*v-c*m)+d*(l*p-c*h)),t[5]=r*(h*v-p*m)-u*(i*v-a*m)+d*(i*p-a*h),t[6]=-(r*(l*v-c*m)-o*(i*v-a*m)+d*(i*c-a*l)),t[7]=r*(l*p-c*h)-o*(i*p-a*h)+u*(i*c-a*l),t[8]=o*(f*v-p*g)-u*(s*v-c*g)+d*(s*p-c*f),t[9]=-(r*(f*v-p*g)-u*(n*v-a*g)+d*(n*p-a*f)),t[10]=r*(s*v-c*g)-o*(n*v-a*g)+d*(n*c-a*s),t[11]=-(r*(s*p-c*f)-o*(n*p-a*f)+u*(n*c-a*s)),t[12]=-(o*(f*m-h*g)-u*(s*m-l*g)+d*(s*h-l*f)),t[13]=r*(f*m-h*g)-u*(n*m-i*g)+d*(n*h-i*f),t[14]=-(r*(s*m-l*g)-o*(n*m-i*g)+d*(n*l-i*s)),t[15]=r*(s*h-l*f)-o*(n*h-i*f)+u*(n*l-i*s),t}},{}],284:[function(t,e,r){e.exports=function(t){var e=new Float32Array(16);return 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r=e[0],n=e[1],i=e[2],a=e[3],o=r+r,s=n+n,l=i+i,c=r*o,u=n*o,f=n*s,h=i*o,p=i*s,d=i*l,g=a*o,m=a*s,v=a*l;return t[0]=1-f-d,t[1]=u+v,t[2]=h-m,t[3]=0,t[4]=u-v,t[5]=1-c-d,t[6]=p+g,t[7]=0,t[8]=h+m,t[9]=p-g,t[10]=1-c-f,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],289:[function(t,e,r){e.exports=function(t,e,r){var n,i,a,o=r[0],s=r[1],l=r[2],c=Math.sqrt(o*o+s*s+l*l);if(Math.abs(c)<1e-6)return null;return o*=c=1/c,s*=c,l*=c,n=Math.sin(e),i=Math.cos(e),a=1-i,t[0]=o*o*a+i,t[1]=s*o*a+l*n,t[2]=l*o*a-s*n,t[3]=0,t[4]=o*s*a-l*n,t[5]=s*s*a+i,t[6]=l*s*a+o*n,t[7]=0,t[8]=o*l*a+s*n,t[9]=s*l*a-o*n,t[10]=l*l*a+i,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],290:[function(t,e,r){e.exports=function(t,e,r){var n=e[0],i=e[1],a=e[2],o=e[3],s=n+n,l=i+i,c=a+a,u=n*s,f=n*l,h=n*c,p=i*l,d=i*c,g=a*c,m=o*s,v=o*l,y=o*c;return t[0]=1-(p+g),t[1]=f+y,t[2]=h-v,t[3]=0,t[4]=f-y,t[5]=1-(u+g),t[6]=d+m,t[7]=0,t[8]=h+v,t[9]=d-m,t[10]=1-(u+p),t[11]=0,t[12]=r[0],t[13]=r[1],t[14]=r[2],t[15]=1,t}},{}],291:[function(t,e,r){e.exports=function(t,e){return t[0]=e[0],t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=e[1],t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=e[2],t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],292:[function(t,e,r){e.exports=function(t,e){return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=e[0],t[13]=e[1],t[14]=e[2],t[15]=1,t}},{}],293:[function(t,e,r){e.exports=function(t,e){var r=Math.sin(e),n=Math.cos(e);return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=n,t[6]=r,t[7]=0,t[8]=0,t[9]=-r,t[10]=n,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],294:[function(t,e,r){e.exports=function(t,e){var r=Math.sin(e),n=Math.cos(e);return t[0]=n,t[1]=0,t[2]=-r,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=r,t[9]=0,t[10]=n,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],295:[function(t,e,r){e.exports=function(t,e){var r=Math.sin(e),n=Math.cos(e);return t[0]=n,t[1]=r,t[2]=0,t[3]=0,t[4]=-r,t[5]=n,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],296:[function(t,e,r){e.exports=function(t,e,r,n,i,a,o){var s=1/(r-e),l=1/(i-n),c=1/(a-o);return t[0]=2*a*s,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=2*a*l,t[6]=0,t[7]=0,t[8]=(r+e)*s,t[9]=(i+n)*l,t[10]=(o+a)*c,t[11]=-1,t[12]=0,t[13]=0,t[14]=o*a*2*c,t[15]=0,t}},{}],297:[function(t,e,r){e.exports=function(t){return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],298:[function(t,e,r){e.exports={create:t(\"./create\"),clone:t(\"./clone\"),copy:t(\"./copy\"),identity:t(\"./identity\"),transpose:t(\"./transpose\"),invert:t(\"./invert\"),adjoint:t(\"./adjoint\"),determinant:t(\"./determinant\"),multiply:t(\"./multiply\"),translate:t(\"./translate\"),scale:t(\"./scale\"),rotate:t(\"./rotate\"),rotateX:t(\"./rotateX\"),rotateY:t(\"./rotateY\"),rotateZ:t(\"./rotateZ\"),fromRotation:t(\"./fromRotation\"),fromRotationTranslation:t(\"./fromRotationTranslation\"),fromScaling:t(\"./fromScaling\"),fromTranslation:t(\"./fromTranslation\"),fromXRotation:t(\"./fromXRotation\"),fromYRotation:t(\"./fromYRotation\"),fromZRotation:t(\"./fromZRotation\"),fromQuat:t(\"./fromQuat\"),frustum:t(\"./frustum\"),perspective:t(\"./perspective\"),perspectiveFromFieldOfView:t(\"./perspectiveFromFieldOfView\"),ortho:t(\"./ortho\"),lookAt:t(\"./lookAt\"),str:t(\"./str\")}},{\"./adjoint\":283,\"./clone\":284,\"./copy\":285,\"./create\":286,\"./determinant\":287,\"./fromQuat\":288,\"./fromRotation\":289,\"./fromRotationTranslation\":290,\"./fromScaling\":291,\"./fromTranslation\":292,\"./fromXRotation\":293,\"./fromYRotation\":294,\"./fromZRotation\":295,\"./frustum\":296,\"./identity\":297,\"./invert\":299,\"./lookAt\":300,\"./multiply\":301,\"./ortho\":302,\"./perspective\":303,\"./perspectiveFromFieldOfView\":304,\"./rotate\":305,\"./rotateX\":306,\"./rotateY\":307,\"./rotateZ\":308,\"./scale\":309,\"./str\":310,\"./translate\":311,\"./transpose\":312}],299:[function(t,e,r){e.exports=function(t,e){var r=e[0],n=e[1],i=e[2],a=e[3],o=e[4],s=e[5],l=e[6],c=e[7],u=e[8],f=e[9],h=e[10],p=e[11],d=e[12],g=e[13],m=e[14],v=e[15],y=r*s-n*o,x=r*l-i*o,b=r*c-a*o,_=n*l-i*s,w=n*c-a*s,T=i*c-a*l,k=u*g-f*d,A=u*m-h*d,M=u*v-p*d,S=f*m-h*g,E=f*v-p*g,L=h*v-p*m,C=y*L-x*E+b*S+_*M-w*A+T*k;if(!C)return null;return C=1/C,t[0]=(s*L-l*E+c*S)*C,t[1]=(i*E-n*L-a*S)*C,t[2]=(g*T-m*w+v*_)*C,t[3]=(h*w-f*T-p*_)*C,t[4]=(l*M-o*L-c*A)*C,t[5]=(r*L-i*M+a*A)*C,t[6]=(m*b-d*T-v*x)*C,t[7]=(u*T-h*b+p*x)*C,t[8]=(o*E-s*M+c*k)*C,t[9]=(n*M-r*E-a*k)*C,t[10]=(d*w-g*b+v*y)*C,t[11]=(f*b-u*w-p*y)*C,t[12]=(s*A-o*S-l*k)*C,t[13]=(r*S-n*A+i*k)*C,t[14]=(g*x-d*_-m*y)*C,t[15]=(u*_-f*x+h*y)*C,t}},{}],300:[function(t,e,r){var n=t(\"./identity\");e.exports=function(t,e,r,i){var a,o,s,l,c,u,f,h,p,d,g=e[0],m=e[1],v=e[2],y=i[0],x=i[1],b=i[2],_=r[0],w=r[1],T=r[2];if(Math.abs(g-_)<1e-6&&Math.abs(m-w)<1e-6&&Math.abs(v-T)<1e-6)return n(t);f=g-_,h=m-w,p=v-T,d=1/Math.sqrt(f*f+h*h+p*p),a=x*(p*=d)-b*(h*=d),o=b*(f*=d)-y*p,s=y*h-x*f,(d=Math.sqrt(a*a+o*o+s*s))?(a*=d=1/d,o*=d,s*=d):(a=0,o=0,s=0);l=h*s-p*o,c=p*a-f*s,u=f*o-h*a,(d=Math.sqrt(l*l+c*c+u*u))?(l*=d=1/d,c*=d,u*=d):(l=0,c=0,u=0);return t[0]=a,t[1]=l,t[2]=f,t[3]=0,t[4]=o,t[5]=c,t[6]=h,t[7]=0,t[8]=s,t[9]=u,t[10]=p,t[11]=0,t[12]=-(a*g+o*m+s*v),t[13]=-(l*g+c*m+u*v),t[14]=-(f*g+h*m+p*v),t[15]=1,t}},{\"./identity\":297}],301:[function(t,e,r){e.exports=function(t,e,r){var n=e[0],i=e[1],a=e[2],o=e[3],s=e[4],l=e[5],c=e[6],u=e[7],f=e[8],h=e[9],p=e[10],d=e[11],g=e[12],m=e[13],v=e[14],y=e[15],x=r[0],b=r[1],_=r[2],w=r[3];return t[0]=x*n+b*s+_*f+w*g,t[1]=x*i+b*l+_*h+w*m,t[2]=x*a+b*c+_*p+w*v,t[3]=x*o+b*u+_*d+w*y,x=r[4],b=r[5],_=r[6],w=r[7],t[4]=x*n+b*s+_*f+w*g,t[5]=x*i+b*l+_*h+w*m,t[6]=x*a+b*c+_*p+w*v,t[7]=x*o+b*u+_*d+w*y,x=r[8],b=r[9],_=r[10],w=r[11],t[8]=x*n+b*s+_*f+w*g,t[9]=x*i+b*l+_*h+w*m,t[10]=x*a+b*c+_*p+w*v,t[11]=x*o+b*u+_*d+w*y,x=r[12],b=r[13],_=r[14],w=r[15],t[12]=x*n+b*s+_*f+w*g,t[13]=x*i+b*l+_*h+w*m,t[14]=x*a+b*c+_*p+w*v,t[15]=x*o+b*u+_*d+w*y,t}},{}],302:[function(t,e,r){e.exports=function(t,e,r,n,i,a,o){var s=1/(e-r),l=1/(n-i),c=1/(a-o);return t[0]=-2*s,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=-2*l,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=2*c,t[11]=0,t[12]=(e+r)*s,t[13]=(i+n)*l,t[14]=(o+a)*c,t[15]=1,t}},{}],303:[function(t,e,r){e.exports=function(t,e,r,n,i){var a=1/Math.tan(e/2),o=1/(n-i);return t[0]=a/r,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=a,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=(i+n)*o,t[11]=-1,t[12]=0,t[13]=0,t[14]=2*i*n*o,t[15]=0,t}},{}],304:[function(t,e,r){e.exports=function(t,e,r,n){var i=Math.tan(e.upDegrees*Math.PI/180),a=Math.tan(e.downDegrees*Math.PI/180),o=Math.tan(e.leftDegrees*Math.PI/180),s=Math.tan(e.rightDegrees*Math.PI/180),l=2/(o+s),c=2/(i+a);return t[0]=l,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=c,t[6]=0,t[7]=0,t[8]=-(o-s)*l*.5,t[9]=(i-a)*c*.5,t[10]=n/(r-n),t[11]=-1,t[12]=0,t[13]=0,t[14]=n*r/(r-n),t[15]=0,t}},{}],305:[function(t,e,r){e.exports=function(t,e,r,n){var i,a,o,s,l,c,u,f,h,p,d,g,m,v,y,x,b,_,w,T,k,A,M,S,E=n[0],L=n[1],C=n[2],P=Math.sqrt(E*E+L*L+C*C);if(Math.abs(P)<1e-6)return null;E*=P=1/P,L*=P,C*=P,i=Math.sin(r),a=Math.cos(r),o=1-a,s=e[0],l=e[1],c=e[2],u=e[3],f=e[4],h=e[5],p=e[6],d=e[7],g=e[8],m=e[9],v=e[10],y=e[11],x=E*E*o+a,b=L*E*o+C*i,_=C*E*o-L*i,w=E*L*o-C*i,T=L*L*o+a,k=C*L*o+E*i,A=E*C*o+L*i,M=L*C*o-E*i,S=C*C*o+a,t[0]=s*x+f*b+g*_,t[1]=l*x+h*b+m*_,t[2]=c*x+p*b+v*_,t[3]=u*x+d*b+y*_,t[4]=s*w+f*T+g*k,t[5]=l*w+h*T+m*k,t[6]=c*w+p*T+v*k,t[7]=u*w+d*T+y*k,t[8]=s*A+f*M+g*S,t[9]=l*A+h*M+m*S,t[10]=c*A+p*M+v*S,t[11]=u*A+d*M+y*S,e!==t&&(t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t}},{}],306:[function(t,e,r){e.exports=function(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[4],o=e[5],s=e[6],l=e[7],c=e[8],u=e[9],f=e[10],h=e[11];e!==t&&(t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=e[3],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t[4]=a*i+c*n,t[5]=o*i+u*n,t[6]=s*i+f*n,t[7]=l*i+h*n,t[8]=c*i-a*n,t[9]=u*i-o*n,t[10]=f*i-s*n,t[11]=h*i-l*n,t}},{}],307:[function(t,e,r){e.exports=function(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[0],o=e[1],s=e[2],l=e[3],c=e[8],u=e[9],f=e[10],h=e[11];e!==t&&(t[4]=e[4],t[5]=e[5],t[6]=e[6],t[7]=e[7],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t[0]=a*i-c*n,t[1]=o*i-u*n,t[2]=s*i-f*n,t[3]=l*i-h*n,t[8]=a*n+c*i,t[9]=o*n+u*i,t[10]=s*n+f*i,t[11]=l*n+h*i,t}},{}],308:[function(t,e,r){e.exports=function(t,e,r){var n=Math.sin(r),i=Math.cos(r),a=e[0],o=e[1],s=e[2],l=e[3],c=e[4],u=e[5],f=e[6],h=e[7];e!==t&&(t[8]=e[8],t[9]=e[9],t[10]=e[10],t[11]=e[11],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t[0]=a*i+c*n,t[1]=o*i+u*n,t[2]=s*i+f*n,t[3]=l*i+h*n,t[4]=c*i-a*n,t[5]=u*i-o*n,t[6]=f*i-s*n,t[7]=h*i-l*n,t}},{}],309:[function(t,e,r){e.exports=function(t,e,r){var n=r[0],i=r[1],a=r[2];return t[0]=e[0]*n,t[1]=e[1]*n,t[2]=e[2]*n,t[3]=e[3]*n,t[4]=e[4]*i,t[5]=e[5]*i,t[6]=e[6]*i,t[7]=e[7]*i,t[8]=e[8]*a,t[9]=e[9]*a,t[10]=e[10]*a,t[11]=e[11]*a,t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15],t}},{}],310:[function(t,e,r){e.exports=function(t){return\"mat4(\"+t[0]+\", \"+t[1]+\", \"+t[2]+\", \"+t[3]+\", \"+t[4]+\", \"+t[5]+\", \"+t[6]+\", \"+t[7]+\", \"+t[8]+\", \"+t[9]+\", \"+t[10]+\", \"+t[11]+\", \"+t[12]+\", \"+t[13]+\", \"+t[14]+\", \"+t[15]+\")\"}},{}],311:[function(t,e,r){e.exports=function(t,e,r){var n,i,a,o,s,l,c,u,f,h,p,d,g=r[0],m=r[1],v=r[2];e===t?(t[12]=e[0]*g+e[4]*m+e[8]*v+e[12],t[13]=e[1]*g+e[5]*m+e[9]*v+e[13],t[14]=e[2]*g+e[6]*m+e[10]*v+e[14],t[15]=e[3]*g+e[7]*m+e[11]*v+e[15]):(n=e[0],i=e[1],a=e[2],o=e[3],s=e[4],l=e[5],c=e[6],u=e[7],f=e[8],h=e[9],p=e[10],d=e[11],t[0]=n,t[1]=i,t[2]=a,t[3]=o,t[4]=s,t[5]=l,t[6]=c,t[7]=u,t[8]=f,t[9]=h,t[10]=p,t[11]=d,t[12]=n*g+s*m+f*v+e[12],t[13]=i*g+l*m+h*v+e[13],t[14]=a*g+c*m+p*v+e[14],t[15]=o*g+u*m+d*v+e[15]);return t}},{}],312:[function(t,e,r){e.exports=function(t,e){if(t===e){var r=e[1],n=e[2],i=e[3],a=e[6],o=e[7],s=e[11];t[1]=e[4],t[2]=e[8],t[3]=e[12],t[4]=r,t[6]=e[9],t[7]=e[13],t[8]=n,t[9]=a,t[11]=e[14],t[12]=i,t[13]=o,t[14]=s}else t[0]=e[0],t[1]=e[4],t[2]=e[8],t[3]=e[12],t[4]=e[1],t[5]=e[5],t[6]=e[9],t[7]=e[13],t[8]=e[2],t[9]=e[6],t[10]=e[10],t[11]=e[14],t[12]=e[3],t[13]=e[7],t[14]=e[11],t[15]=e[15];return t}},{}],313:[function(t,e,r){\"use strict\";var n=t(\"barycentric\"),i=t(\"polytope-closest-point/lib/closest_point_2d.js\");function a(t,e){for(var r=[0,0,0,0],n=0;n<4;++n)for(var i=0;i<4;++i)r[i]+=t[4*n+i]*e[n];return r}function o(t,e,r,n,i){for(var o=a(n,a(r,a(e,[t[0],t[1],t[2],1]))),s=0;s<3;++s)o[s]/=o[3];return[.5*i[0]*(1+o[0]),.5*i[1]*(1-o[1])]}function s(t,e){for(var r=[0,0,0],n=0;n<t.length;++n)for(var i=t[n],a=e[n],o=0;o<3;++o)r[o]+=a*i[o];return r}e.exports=function(t,e,r,a,l,c){if(1===t.length)return[0,t[0].slice()];for(var u=new Array(t.length),f=0;f<t.length;++f)u[f]=o(t[f],r,a,l,c);var h=0,p=1/0;for(f=0;f<u.length;++f){for(var d=0,g=0;g<2;++g)d+=Math.pow(u[f][g]-e[g],2);d<p&&(p=d,h=f)}var m=function(t,e){if(2===t.length){for(var r=0,a=0,o=0;o<2;++o)r+=Math.pow(e[o]-t[0][o],2),a+=Math.pow(e[o]-t[1][o],2);return r=Math.sqrt(r),a=Math.sqrt(a),r+a<1e-6?[1,0]:[a/(r+a),r/(a+r)]}if(3===t.length){var s=[0,0];return i(t[0],t[1],t[2],e,s),n(t,s)}return[]}(u,e),v=0;for(f=0;f<3;++f){if(m[f]<-.001||m[f]>1.0001)return null;v+=m[f]}if(Math.abs(v-1)>.001)return null;return[h,s(t,m),m]}},{barycentric:85,\"polytope-closest-point/lib/closest_point_2d.js\":512}],314:[function(t,e,r){var n=t(\"glslify\"),i=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position, normal;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model\\n           , view\\n           , projection\\n           , inverseModel;\\nuniform vec3 eyePosition\\n           , lightPosition;\\n\\nvarying vec3 f_normal\\n           , f_lightDirection\\n           , f_eyeDirection\\n           , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvec4 project(vec3 p) {\\n  return projection * view * model * vec4(p, 1.0);\\n}\\n\\nvoid main() {\\n  gl_Position      = project(position);\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * vec4(position , 1.0);\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n  f_eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  f_normal  = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n  f_color          = color;\\n  f_data           = position;\\n  f_uv             = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n  float G = min(1.0, min(G1, G2));\\n  \\n  //Distribution term\\n  float D = beckmannDistribution(NdotH, roughness);\\n\\n  //Fresnel term\\n  float F = pow(1.0 - VdotN, fresnel);\\n\\n  //Multiply terms and done\\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\n//#pragma glslify: beckmann = require(glsl-specular-beckmann) // used in gl-surface3d\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness\\n            , fresnel\\n            , kambient\\n            , kdiffuse\\n            , kspecular;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal\\n           , f_lightDirection\\n           , f_eyeDirection\\n           , f_data;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (f_color.a == 0.0 ||\\n    outOfRange(clipBounds[0], clipBounds[1], f_data)\\n  ) discard;\\n\\n  vec3 N = normalize(f_normal);\\n  vec3 L = normalize(f_lightDirection);\\n  vec3 V = normalize(f_eyeDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n  //float specular = max(0.0, beckmann(L, V, N, roughness)); // used in gl-surface3d\\n\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  vec4 surfaceColor = vec4(f_color.rgb, 1.0) * texture2D(texture, f_uv);\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = litColor * f_color.a;\\n}\\n\"]),o=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n  f_color = color;\\n  f_data  = position;\\n  f_uv    = uv;\\n}\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec3 f_data;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_data)) discard;\\n\\n  gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\"]),l=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 uv;\\nattribute float pointSize;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0.0, 0.0 ,0.0 ,0.0);\\n  } else {\\n    gl_Position = projection * view * model * vec4(position, 1.0);\\n  }\\n  gl_PointSize = pointSize;\\n  f_color = color;\\n  f_uv = uv;\\n}\"]),c=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D texture;\\nuniform float opacity;\\n\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  vec2 pointR = gl_PointCoord.xy - vec2(0.5, 0.5);\\n  if(dot(pointR, pointR) > 0.25) {\\n    discard;\\n  }\\n  gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\\n}\"]),u=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n  f_id        = id;\\n  f_position  = position;\\n}\"]),f=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3  clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n  gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]),h=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3  position;\\nattribute float pointSize;\\nattribute vec4  id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0.0, 0.0, 0.0, 0.0);\\n  } else {\\n    gl_Position  = projection * view * model * vec4(position, 1.0);\\n    gl_PointSize = pointSize;\\n  }\\n  f_id         = id;\\n  f_position   = position;\\n}\"]),p=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec3 position;\\n\\nuniform mat4 model, view, projection;\\n\\nvoid main() {\\n  gl_Position = projection * view * model * vec4(position, 1.0);\\n}\"]),d=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform vec3 contourColor;\\n\\nvoid main() {\\n  gl_FragColor = vec4(contourColor, 1.0);\\n}\\n\"]);r.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},r.wireShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"}]},r.pointShader={vertex:l,fragment:c,attributes:[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"pointSize\",type:\"float\"}]},r.pickShader={vertex:u,fragment:f,attributes:[{name:\"position\",type:\"vec3\"},{name:\"id\",type:\"vec4\"}]},r.pointPickShader={vertex:h,fragment:f,attributes:[{name:\"position\",type:\"vec3\"},{name:\"pointSize\",type:\"float\"},{name:\"id\",type:\"vec4\"}]},r.contourShader={vertex:p,fragment:d,attributes:[{name:\"position\",type:\"vec3\"}]}},{glslify:442}],315:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=t(\"gl-buffer\"),a=t(\"gl-vao\"),o=t(\"gl-texture2d\"),s=t(\"normals\"),l=t(\"gl-mat4/multiply\"),c=t(\"gl-mat4/invert\"),u=t(\"ndarray\"),f=t(\"colormap\"),h=t(\"simplicial-complex-contour\"),p=t(\"typedarray-pool\"),d=t(\"./lib/shaders\"),g=t(\"./lib/closest-point\"),m=d.meshShader,v=d.wireShader,y=d.pointShader,x=d.pickShader,b=d.pointPickShader,_=d.contourShader,w=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function T(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g,m,v,y,x,b,_,T,k,A,M,S){this.gl=t,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.lineShader=n,this.pointShader=i,this.pickShader=a,this.pointPickShader=o,this.contourShader=s,this.trianglePositions=l,this.triangleColors=u,this.triangleNormals=h,this.triangleUVs=f,this.triangleIds=c,this.triangleVAO=p,this.triangleCount=0,this.lineWidth=1,this.edgePositions=d,this.edgeColors=m,this.edgeUVs=v,this.edgeIds=g,this.edgeVAO=y,this.edgeCount=0,this.pointPositions=x,this.pointColors=_,this.pointUVs=T,this.pointSizes=k,this.pointIds=b,this.pointVAO=A,this.pointCount=0,this.contourLineWidth=1,this.contourPositions=M,this.contourVAO=S,this.contourCount=0,this.contourColor=[0,0,0],this.contourEnable=!0,this.pickVertex=!0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.hasAlpha=!1,this.opacityscale=!1,this._model=w,this._view=w,this._projection=w,this._resolution=[1,1]}var k=T.prototype;function A(t,e){if(!e)return 1;if(!e.length)return 1;for(var r=0;r<e.length;++r){if(e.length<2)return 1;if(e[r][0]===t)return e[r][1];if(e[r][0]>t&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}function M(t){var e=n(t,m.vertex,m.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.normal.location=4,e}function S(t){var e=n(t,v.vertex,v.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e}function E(t){var e=n(t,y.vertex,y.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.pointSize.location=4,e}function L(t){var e=n(t,x.vertex,x.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e}function C(t){var e=n(t,b.vertex,b.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e.attributes.pointSize.location=4,e}function P(t){var e=n(t,_.vertex,_.fragment);return e.attributes.position.location=0,e}k.isOpaque=function(){return!this.hasAlpha},k.isTransparent=function(){return this.hasAlpha},k.pickSlots=1,k.setPickBase=function(t){this.pickId=t},k.highlight=function(t){if(t&&this.contourEnable){for(var e=h(this.cells,this.intensity,t.intensity),r=e.cells,n=e.vertexIds,i=e.vertexWeights,a=r.length,o=p.mallocFloat32(6*a),s=0,l=0;l<a;++l)for(var c=r[l],u=0;u<2;++u){var f=c[0];2===c.length&&(f=c[u]);for(var d=n[f][0],g=n[f][1],m=i[f],v=1-m,y=this.positions[d],x=this.positions[g],b=0;b<3;++b)o[s++]=m*y[b]+v*x[b]}this.contourCount=s/3|0,this.contourPositions.update(o.subarray(0,s)),p.free(o)}else this.contourCount=0},k.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,\"contourEnable\"in t&&(this.contourEnable=t.contourEnable),\"contourColor\"in t&&(this.contourColor=t.contourColor),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"lightPosition\"in t&&(this.lightPosition=t.lightPosition),this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=t.opacity,this.opacity<1&&(this.hasAlpha=!0)),\"opacityscale\"in t&&(this.opacityscale=t.opacityscale,this.hasAlpha=!0),\"ambient\"in t&&(this.ambientLight=t.ambient),\"diffuse\"in t&&(this.diffuseLight=t.diffuse),\"specular\"in t&&(this.specularLight=t.specular),\"roughness\"in t&&(this.roughness=t.roughness),\"fresnel\"in t&&(this.fresnel=t.fresnel),t.texture?(this.texture.dispose(),this.texture=o(e,t.texture)):t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(function(t,e){for(var r=f({colormap:t,nshades:256,format:\"rgba\"}),n=new Uint8Array(1024),i=0;i<256;++i){for(var a=r[i],o=0;o<3;++o)n[4*i+o]=a[o];n[4*i+3]=e?255*A(i/255,e):255*a[3]}return u(n,[256,256,4],[4,0,1])}(t.colormap,this.opacityscale)),this.texture.generateMipmap());var r=t.cells,n=t.positions;if(n&&r){var i=[],a=[],l=[],c=[],h=[],p=[],d=[],g=[],m=[],v=[],y=[],x=[],b=[],_=[];this.cells=r,this.positions=n;var w=t.vertexNormals,T=t.cellNormals,k=void 0===t.vertexNormalsEpsilon?1e-6:t.vertexNormalsEpsilon,M=void 0===t.faceNormalsEpsilon?1e-6:t.faceNormalsEpsilon;t.useFacetNormals&&!T&&(T=s.faceNormals(r,n,M)),T||w||(w=s.vertexNormals(r,n,k));var S=t.vertexColors,E=t.cellColors,L=t.meshColor||[1,1,1,1],C=t.vertexUVs,P=t.vertexIntensity,I=t.cellUVs,O=t.cellIntensity,z=1/0,D=-1/0;if(!C&&!I)if(P)if(t.vertexIntensityBounds)z=+t.vertexIntensityBounds[0],D=+t.vertexIntensityBounds[1];else for(var R=0;R<P.length;++R){var F=P[R];z=Math.min(z,F),D=Math.max(D,F)}else if(O)if(t.cellIntensityBounds)z=+t.cellIntensityBounds[0],D=+t.cellIntensityBounds[1];else for(R=0;R<O.length;++R){F=O[R];z=Math.min(z,F),D=Math.max(D,F)}else for(R=0;R<n.length;++R){F=n[R][2];z=Math.min(z,F),D=Math.max(D,F)}this.intensity=P||(O||function(t){for(var e=t.length,r=new Array(e),n=0;n<e;++n)r[n]=t[n][2];return r}(n)),this.pickVertex=!(O||E);var B=t.pointSizes,N=t.pointSize||1;this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(R=0;R<n.length;++R)for(var j=n[R],U=0;U<3;++U)!isNaN(j[U])&&isFinite(j[U])&&(this.bounds[0][U]=Math.min(this.bounds[0][U],j[U]),this.bounds[1][U]=Math.max(this.bounds[1][U],j[U]));var V=0,q=0,H=0;t:for(R=0;R<r.length;++R){var G=r[R];switch(G.length){case 1:for(j=n[W=G[0]],U=0;U<3;++U)if(isNaN(j[U])||!isFinite(j[U]))continue t;v.push(j[0],j[1],j[2]),X=S?S[W]:E?E[R]:L,this.opacityscale&&P?a.push(X[0],X[1],X[2],this.opacity*A((P[W]-z)/(D-z),this.opacityscale)):3===X.length?y.push(X[0],X[1],X[2],this.opacity):(y.push(X[0],X[1],X[2],X[3]*this.opacity),X[3]<1&&(this.hasAlpha=!0)),Z=C?C[W]:P?[(P[W]-z)/(D-z),0]:I?I[R]:O?[(O[R]-z)/(D-z),0]:[(j[2]-z)/(D-z),0],x.push(Z[0],Z[1]),B?b.push(B[W]):b.push(N),_.push(R),H+=1;break;case 2:for(U=0;U<2;++U){j=n[W=G[U]];for(var Y=0;Y<3;++Y)if(isNaN(j[Y])||!isFinite(j[Y]))continue t}for(U=0;U<2;++U){j=n[W=G[U]];p.push(j[0],j[1],j[2]),X=S?S[W]:E?E[R]:L,this.opacityscale&&P?a.push(X[0],X[1],X[2],this.opacity*A((P[W]-z)/(D-z),this.opacityscale)):3===X.length?d.push(X[0],X[1],X[2],this.opacity):(d.push(X[0],X[1],X[2],X[3]*this.opacity),X[3]<1&&(this.hasAlpha=!0)),Z=C?C[W]:P?[(P[W]-z)/(D-z),0]:I?I[R]:O?[(O[R]-z)/(D-z),0]:[(j[2]-z)/(D-z),0],g.push(Z[0],Z[1]),m.push(R)}q+=1;break;case 3:for(U=0;U<3;++U)for(j=n[W=G[U]],Y=0;Y<3;++Y)if(isNaN(j[Y])||!isFinite(j[Y]))continue t;for(U=0;U<3;++U){var W,X,Z,J;j=n[W=G[2-U]];i.push(j[0],j[1],j[2]),(X=S?S[W]:E?E[R]:L)?this.opacityscale&&P?a.push(X[0],X[1],X[2],this.opacity*A((P[W]-z)/(D-z),this.opacityscale)):3===X.length?a.push(X[0],X[1],X[2],this.opacity):(a.push(X[0],X[1],X[2],X[3]*this.opacity),X[3]<1&&(this.hasAlpha=!0)):a.push(.5,.5,.5,1),Z=C?C[W]:P?[(P[W]-z)/(D-z),0]:I?I[R]:O?[(O[R]-z)/(D-z),0]:[(j[2]-z)/(D-z),0],c.push(Z[0],Z[1]),J=w?w[W]:T[R],l.push(J[0],J[1],J[2]),h.push(R)}V+=1}}this.pointCount=H,this.edgeCount=q,this.triangleCount=V,this.pointPositions.update(v),this.pointColors.update(y),this.pointUVs.update(x),this.pointSizes.update(b),this.pointIds.update(new Uint32Array(_)),this.edgePositions.update(p),this.edgeColors.update(d),this.edgeUVs.update(g),this.edgeIds.update(new Uint32Array(m)),this.trianglePositions.update(i),this.triangleColors.update(a),this.triangleUVs.update(c),this.triangleNormals.update(l),this.triangleIds.update(new Uint32Array(h))}},k.drawTransparent=k.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||w,n=t.view||w,i=t.projection||w,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);var s={model:r,view:n,projection:i,inverseModel:w.slice(),clipBounds:a,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],contourColor:this.contourColor,texture:0};s.inverseModel=c(s.inverseModel,s.model),e.disable(e.CULL_FACE),this.texture.bind(0);var u=new Array(16);l(u,s.view,s.model),l(u,s.projection,u),c(u,u);for(o=0;o<3;++o)s.eyePosition[o]=u[12+o]/u[15];var f,h=u[15];for(o=0;o<3;++o)h+=this.lightPosition[o]*u[4*o+3];for(o=0;o<3;++o){for(var p=u[12+o],d=0;d<3;++d)p+=u[4*d+o]*this.lightPosition[d];s.lightPosition[o]=p/h}this.triangleCount>0&&((f=this.triShader).bind(),f.uniforms=s,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind());this.edgeCount>0&&this.lineWidth>0&&((f=this.lineShader).bind(),f.uniforms=s,this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind());this.pointCount>0&&((f=this.pointShader).bind(),f.uniforms=s,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind());this.contourEnable&&this.contourCount>0&&this.contourLineWidth>0&&((f=this.contourShader).bind(),f.uniforms=s,this.contourVAO.bind(),e.drawArrays(e.LINES,0,this.contourCount),this.contourVAO.unbind())},k.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||w,n=t.view||w,i=t.projection||w,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s,l={model:r,view:n,projection:i,clipBounds:a,pickId:this.pickId/255};((s=this.pickShader).bind(),s.uniforms=l,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&(this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0)&&((s=this.pointPickShader).bind(),s.uniforms=l,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind())},k.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;for(var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions,i=new Array(r.length),a=0;a<r.length;++a)i[a]=n[r[a]];var o=t.coord[0],s=t.coord[1];if(!this.pickVertex){var l=this.positions[r[0]],c=this.positions[r[1]],u=this.positions[r[2]],f=[(l[0]+c[0]+u[0])/3,(l[1]+c[1]+u[1])/3,(l[2]+c[2]+u[2])/3];return{_cellCenter:!0,position:[o,s],index:e,cell:r,cellId:e,intensity:this.intensity[e],dataCoordinate:f}}var h=g(i,[o*this.pixelRatio,this._resolution[1]-s*this.pixelRatio],this._model,this._view,this._projection,this._resolution);if(!h)return null;var p=h[2],d=0;for(a=0;a<r.length;++a)d+=p[a]*this.intensity[r[a]];return{position:h[1],index:r[h[0]],cell:r,cellId:e,intensity:d,dataCoordinate:this.positions[r[h[0]]]}},k.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.lineShader.dispose(),this.pointShader.dispose(),this.pickShader.dispose(),this.pointPickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleNormals.dispose(),this.triangleIds.dispose(),this.edgeVAO.dispose(),this.edgePositions.dispose(),this.edgeColors.dispose(),this.edgeUVs.dispose(),this.edgeIds.dispose(),this.pointVAO.dispose(),this.pointPositions.dispose(),this.pointColors.dispose(),this.pointUVs.dispose(),this.pointSizes.dispose(),this.pointIds.dispose(),this.contourVAO.dispose(),this.contourPositions.dispose(),this.contourShader.dispose()},e.exports=function(t,e){1===arguments.length&&(t=(e=t).gl);var r=t.getExtension(\"OES_standard_derivatives\")||t.getExtension(\"MOZ_OES_standard_derivatives\")||t.getExtension(\"WEBKIT_OES_standard_derivatives\");if(!r)throw new Error(\"derivatives not supported\");var n=M(t),s=S(t),l=E(t),c=L(t),f=C(t),h=P(t),p=o(t,u(new Uint8Array([255,255,255,255]),[1,1,4]));p.generateMipmap(),p.minFilter=t.LINEAR_MIPMAP_LINEAR,p.magFilter=t.LINEAR;var d=i(t),g=i(t),m=i(t),v=i(t),y=i(t),x=a(t,[{buffer:d,type:t.FLOAT,size:3},{buffer:y,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:g,type:t.FLOAT,size:4},{buffer:m,type:t.FLOAT,size:2},{buffer:v,type:t.FLOAT,size:3}]),b=i(t),_=i(t),w=i(t),k=i(t),A=a(t,[{buffer:b,type:t.FLOAT,size:3},{buffer:k,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:_,type:t.FLOAT,size:4},{buffer:w,type:t.FLOAT,size:2}]),I=i(t),O=i(t),z=i(t),D=i(t),R=i(t),F=a(t,[{buffer:I,type:t.FLOAT,size:3},{buffer:R,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:O,type:t.FLOAT,size:4},{buffer:z,type:t.FLOAT,size:2},{buffer:D,type:t.FLOAT,size:1}]),B=i(t),N=a(t,[{buffer:B,type:t.FLOAT,size:3}]),j=new T(t,p,n,s,l,c,f,h,d,y,g,m,v,x,b,k,_,w,A,I,R,O,z,D,F,B,N);return j.update(e),j}},{\"./lib/closest-point\":313,\"./lib/shaders\":314,colormap:137,\"gl-buffer\":267,\"gl-mat4/invert\":299,\"gl-mat4/multiply\":301,\"gl-shader\":339,\"gl-texture2d\":356,\"gl-vao\":361,ndarray:483,normals:486,\"simplicial-complex-contour\":557,\"typedarray-pool\":617}],316:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e,[0,0,0,1,1,0,1,1]),s=i(e,a.boxVert,a.lineFrag);return new o(t,r,s)};var n=t(\"gl-buffer\"),i=t(\"gl-shader\"),a=t(\"./shaders\");function o(t,e,r){this.plot=t,this.vbo=e,this.shader=r}var s,l,c=o.prototype;c.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},c.drawBox=(s=[0,0],l=[0,0],function(t,e,r,n,i){var a=this.plot,o=this.shader,c=a.gl;s[0]=t,s[1]=e,l[0]=r,l[1]=n,o.uniforms.lo=s,o.uniforms.hi=l,o.uniforms.color=i,c.drawArrays(c.TRIANGLE_STRIP,0,4)}),c.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":319,\"gl-buffer\":267,\"gl-shader\":339}],317:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e),a=i(e,o.gridVert,o.gridFrag),l=i(e,o.tickVert,o.gridFrag);return new s(t,r,a,l)};var n=t(\"gl-buffer\"),i=t(\"gl-shader\"),a=t(\"binary-search-bounds\"),o=t(\"./shaders\");function s(t,e,r,n){this.plot=t,this.vbo=e,this.shader=r,this.tickShader=n,this.ticks=[[],[]]}function l(t,e){return t-e}var c,u,f,h,p,d=s.prototype;d.draw=(c=[0,0],u=[0,0],f=[0,0],function(){for(var t=this.plot,e=this.vbo,r=this.shader,n=this.ticks,i=t.gl,a=t._tickBounds,o=t.dataBox,s=t.viewBox,l=t.gridLineWidth,h=t.gridLineColor,p=t.gridLineEnable,d=t.pixelRatio,g=0;g<2;++g){var m=a[g],v=a[g+2]-m,y=.5*(o[g+2]+o[g]),x=o[g+2]-o[g];u[g]=2*v/x,c[g]=2*(m-y)/x}r.bind(),e.bind(),r.attributes.dataCoord.pointer(),r.uniforms.dataShift=c,r.uniforms.dataScale=u;var b=0;for(g=0;g<2;++g){f[0]=f[1]=0,f[g]=1,r.uniforms.dataAxis=f,r.uniforms.lineWidth=l[g]/(s[g+2]-s[g])*d,r.uniforms.color=h[g];var _=6*n[g].length;p[g]&&_&&i.drawArrays(i.TRIANGLES,b,_),b+=_}}),d.drawTickMarks=function(){var t=[0,0],e=[0,0],r=[1,0],n=[0,1],i=[0,0],o=[0,0];return function(){for(var s=this.plot,c=this.vbo,u=this.tickShader,f=this.ticks,h=s.gl,p=s._tickBounds,d=s.dataBox,g=s.viewBox,m=s.pixelRatio,v=s.screenBox,y=v[2]-v[0],x=v[3]-v[1],b=g[2]-g[0],_=g[3]-g[1],w=0;w<2;++w){var T=p[w],k=p[w+2]-T,A=.5*(d[w+2]+d[w]),M=d[w+2]-d[w];e[w]=2*k/M,t[w]=2*(T-A)/M}e[0]*=b/y,t[0]*=b/y,e[1]*=_/x,t[1]*=_/x,u.bind(),c.bind(),u.attributes.dataCoord.pointer();var S=u.uniforms;S.dataShift=t,S.dataScale=e;var E=s.tickMarkLength,L=s.tickMarkWidth,C=s.tickMarkColor,P=6*f[0].length,I=Math.min(a.ge(f[0],(d[0]-p[0])/(p[2]-p[0]),l),f[0].length),O=Math.min(a.gt(f[0],(d[2]-p[0])/(p[2]-p[0]),l),f[0].length),z=0+6*I,D=6*Math.max(0,O-I),R=Math.min(a.ge(f[1],(d[1]-p[1])/(p[3]-p[1]),l),f[1].length),F=Math.min(a.gt(f[1],(d[3]-p[1])/(p[3]-p[1]),l),f[1].length),B=P+6*R,N=6*Math.max(0,F-R);i[0]=2*(g[0]-E[1])/y-1,i[1]=(g[3]+g[1])/x-1,o[0]=E[1]*m/y,o[1]=L[1]*m/x,N&&(S.color=C[1],S.tickScale=o,S.dataAxis=n,S.screenOffset=i,h.drawArrays(h.TRIANGLES,B,N)),i[0]=(g[2]+g[0])/y-1,i[1]=2*(g[1]-E[0])/x-1,o[0]=L[0]*m/y,o[1]=E[0]*m/x,D&&(S.color=C[0],S.tickScale=o,S.dataAxis=r,S.screenOffset=i,h.drawArrays(h.TRIANGLES,z,D)),i[0]=2*(g[2]+E[3])/y-1,i[1]=(g[3]+g[1])/x-1,o[0]=E[3]*m/y,o[1]=L[3]*m/x,N&&(S.color=C[3],S.tickScale=o,S.dataAxis=n,S.screenOffset=i,h.drawArrays(h.TRIANGLES,B,N)),i[0]=(g[2]+g[0])/y-1,i[1]=2*(g[3]+E[2])/x-1,o[0]=L[2]*m/y,o[1]=E[2]*m/x,D&&(S.color=C[2],S.tickScale=o,S.dataAxis=r,S.screenOffset=i,h.drawArrays(h.TRIANGLES,z,D))}}(),d.update=(h=[1,1,-1,-1,1,-1],p=[1,-1,1,1,-1,-1],function(t){for(var e=t.ticks,r=t.bounds,n=new Float32Array(18*(e[0].length+e[1].length)),i=(this.plot.zeroLineEnable,0),a=[[],[]],o=0;o<2;++o)for(var s=a[o],l=e[o],c=r[o],u=r[o+2],f=0;f<l.length;++f){var d=(l[f].x-c)/(u-c);s.push(d);for(var g=0;g<6;++g)n[i++]=d,n[i++]=h[g],n[i++]=p[g]}this.ticks=a,this.vbo.update(n)}),d.dispose=function(){this.vbo.dispose(),this.shader.dispose(),this.tickShader.dispose()}},{\"./shaders\":319,\"binary-search-bounds\":103,\"gl-buffer\":267,\"gl-shader\":339}],318:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e,[-1,-1,-1,1,1,-1,1,1]),s=i(e,a.lineVert,a.lineFrag);return new o(t,r,s)};var n=t(\"gl-buffer\"),i=t(\"gl-shader\"),a=t(\"./shaders\");function o(t,e,r){this.plot=t,this.vbo=e,this.shader=r}var s,l,c=o.prototype;c.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},c.drawLine=(s=[0,0],l=[0,0],function(t,e,r,n,i,a){var o=this.plot,c=this.shader,u=o.gl;s[0]=t,s[1]=e,l[0]=r,l[1]=n,c.uniforms.start=s,c.uniforms.end=l,c.uniforms.width=i*o.pixelRatio,c.uniforms.color=a,u.drawArrays(u.TRIANGLE_STRIP,0,4)}),c.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":319,\"gl-buffer\":267,\"gl-shader\":339}],319:[function(t,e,r){\"use strict\";var n=t(\"glslify\"),i=n([\"precision lowp float;\\n#define GLSLIFY 1\\nuniform vec4 color;\\nvoid main() {\\n  gl_FragColor = vec4(color.xyz * color.w, color.w);\\n}\\n\"]);e.exports={lineVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 coord;\\n\\nuniform vec4 screenBox;\\nuniform vec2 start, end;\\nuniform float width;\\n\\nvec2 perp(vec2 v) {\\n  return vec2(v.y, -v.x);\\n}\\n\\nvec2 screen(vec2 v) {\\n  return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\\n}\\n\\nvoid main() {\\n  vec2 delta = normalize(perp(start - end));\\n  vec2 offset = mix(start, end, 0.5 * (coord.y+1.0));\\n  gl_Position = vec4(screen(offset + 0.5 * width * delta * coord.x), 0, 1);\\n}\\n\"]),lineFrag:i,textVert:n([\"#define GLSLIFY 1\\nattribute vec3 textCoordinate;\\n\\nuniform vec2 dataScale, dataShift, dataAxis, screenOffset, textScale;\\nuniform float angle;\\n\\nvoid main() {\\n  float dataOffset  = textCoordinate.z;\\n  vec2 glyphOffset  = textCoordinate.xy;\\n  mat2 glyphMatrix = mat2(cos(angle), sin(angle), -sin(angle), cos(angle));\\n  vec2 screenCoordinate = dataAxis * (dataScale * dataOffset + dataShift) +\\n    glyphMatrix * glyphOffset * textScale + screenOffset;\\n  gl_Position = vec4(screenCoordinate, 0, 1);\\n}\\n\"]),textFrag:i,gridVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 dataCoord;\\n\\nuniform vec2 dataAxis, dataShift, dataScale;\\nuniform float lineWidth;\\n\\nvoid main() {\\n  vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\\n  pos += 10.0 * dataCoord.y * vec2(dataAxis.y, -dataAxis.x) + dataCoord.z * lineWidth;\\n  gl_Position = vec4(pos, 0, 1);\\n}\\n\"]),gridFrag:i,boxVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 coord;\\n\\nuniform vec4 screenBox;\\nuniform vec2 lo, hi;\\n\\nvec2 screen(vec2 v) {\\n  return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\\n}\\n\\nvoid main() {\\n  gl_Position = vec4(screen(mix(lo, hi, coord)), 0, 1);\\n}\\n\"]),tickVert:n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec3 dataCoord;\\n\\nuniform vec2 dataAxis, dataShift, dataScale, screenOffset, tickScale;\\n\\nvoid main() {\\n  vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\\n  gl_Position = vec4(pos + tickScale*dataCoord.yz + screenOffset, 0, 1);\\n}\\n\"])}},{glslify:321}],320:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e),a=i(e,s.textVert,s.textFrag);return new l(t,r,a)};var n=t(\"gl-buffer\"),i=t(\"gl-shader\"),a=t(\"text-cache\"),o=t(\"binary-search-bounds\"),s=t(\"./shaders\");function l(t,e,r){this.plot=t,this.vbo=e,this.shader=r,this.tickOffset=[[],[]],this.tickX=[[],[]],this.labelOffset=[0,0],this.labelCount=[0,0]}var c,u,f,h,p,d,g=l.prototype;g.drawTicks=(c=[0,0],u=[0,0],f=[0,0],function(t){var e=this.plot,r=this.shader,n=this.tickX[t],i=this.tickOffset[t],a=e.gl,s=e.viewBox,l=e.dataBox,h=e.screenBox,p=e.pixelRatio,d=e.tickEnable,g=e.tickPad,m=e.tickColor,v=e.tickAngle,y=e.labelEnable,x=e.labelPad,b=e.labelColor,_=e.labelAngle,w=this.labelOffset[t],T=this.labelCount[t],k=o.lt(n,l[t]),A=o.le(n,l[t+2]);c[0]=c[1]=0,c[t]=1,u[t]=(s[2+t]+s[t])/(h[2+t]-h[t])-1;var M=2/h[2+(1^t)]-h[1^t];u[1^t]=M*s[1^t]-1,d[t]&&(u[1^t]-=M*p*g[t],k<A&&i[A]>i[k]&&(r.uniforms.dataAxis=c,r.uniforms.screenOffset=u,r.uniforms.color=m[t],r.uniforms.angle=v[t],a.drawArrays(a.TRIANGLES,i[k],i[A]-i[k]))),y[t]&&T&&(u[1^t]-=M*p*x[t],r.uniforms.dataAxis=f,r.uniforms.screenOffset=u,r.uniforms.color=b[t],r.uniforms.angle=_[t],a.drawArrays(a.TRIANGLES,w,T)),u[1^t]=M*s[2+(1^t)]-1,d[t+2]&&(u[1^t]+=M*p*g[t+2],k<A&&i[A]>i[k]&&(r.uniforms.dataAxis=c,r.uniforms.screenOffset=u,r.uniforms.color=m[t+2],r.uniforms.angle=v[t+2],a.drawArrays(a.TRIANGLES,i[k],i[A]-i[k]))),y[t+2]&&T&&(u[1^t]+=M*p*x[t+2],r.uniforms.dataAxis=f,r.uniforms.screenOffset=u,r.uniforms.color=b[t+2],r.uniforms.angle=_[t+2],a.drawArrays(a.TRIANGLES,w,T))}),g.drawTitle=function(){var t=[0,0],e=[0,0];return function(){var r=this.plot,n=this.shader,i=r.gl,a=r.screenBox,o=r.titleCenter,s=r.titleAngle,l=r.titleColor,c=r.pixelRatio;if(this.titleCount){for(var u=0;u<2;++u)e[u]=2*(o[u]*c-a[u])/(a[2+u]-a[u])-1;n.bind(),n.uniforms.dataAxis=t,n.uniforms.screenOffset=e,n.uniforms.angle=s,n.uniforms.color=l,i.drawArrays(i.TRIANGLES,this.titleOffset,this.titleCount)}}}(),g.bind=(h=[0,0],p=[0,0],d=[0,0],function(){var t=this.plot,e=this.shader,r=t._tickBounds,n=t.dataBox,i=t.screenBox,a=t.viewBox;e.bind();for(var o=0;o<2;++o){var s=r[o],l=r[o+2]-s,c=.5*(n[o+2]+n[o]),u=n[o+2]-n[o],f=a[o],g=a[o+2]-f,m=i[o],v=i[o+2]-m;p[o]=2*l/u*g/v,h[o]=2*(s-c)/u*g/v}d[1]=2*t.pixelRatio/(i[3]-i[1]),d[0]=d[1]*(i[3]-i[1])/(i[2]-i[0]),e.uniforms.dataScale=p,e.uniforms.dataShift=h,e.uniforms.textScale=d,this.vbo.bind(),e.attributes.textCoordinate.pointer()}),g.update=function(t){var e,r,n,i,o,s=[],l=t.ticks,c=t.bounds;for(o=0;o<2;++o){var u=[Math.floor(s.length/3)],f=[-1/0],h=l[o];for(e=0;e<h.length;++e){var p=h[e],d=p.x,g=p.text,m=p.font||\"sans-serif\";i=p.fontSize||12;for(var v=1/(c[o+2]-c[o]),y=c[o],x=g.split(\"\\n\"),b=0;b<x.length;b++)for(n=a(m,x[b]).data,r=0;r<n.length;r+=2)s.push(n[r]*i,-n[r+1]*i-b*i*1.2,(d-y)*v);u.push(Math.floor(s.length/3)),f.push(d)}this.tickOffset[o]=u,this.tickX[o]=f}for(o=0;o<2;++o){for(this.labelOffset[o]=Math.floor(s.length/3),n=a(t.labelFont[o],t.labels[o],{textAlign:\"center\"}).data,i=t.labelSize[o],e=0;e<n.length;e+=2)s.push(n[e]*i,-n[e+1]*i,0);this.labelCount[o]=Math.floor(s.length/3)-this.labelOffset[o]}for(this.titleOffset=Math.floor(s.length/3),n=a(t.titleFont,t.title).data,i=t.titleSize,e=0;e<n.length;e+=2)s.push(n[e]*i,-n[e+1]*i,0);this.titleCount=Math.floor(s.length/3)-this.titleOffset,this.vbo.update(s)},g.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{\"./shaders\":319,\"binary-search-bounds\":103,\"gl-buffer\":267,\"gl-shader\":339,\"text-cache\":596}],321:[function(t,e,r){arguments[4][265][0].apply(r,arguments)},{dup:265}],322:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=n(e,[e.drawingBufferWidth,e.drawingBufferHeight]),c=new l(e,r);return c.grid=i(c),c.text=a(c),c.line=o(c),c.box=s(c),c.update(t),c};var n=t(\"gl-select-static\"),i=t(\"./lib/grid\"),a=t(\"./lib/text\"),o=t(\"./lib/line\"),s=t(\"./lib/box\");function l(t,e){this.gl=t,this.pickBuffer=e,this.screenBox=[0,0,t.drawingBufferWidth,t.drawingBufferHeight],this.viewBox=[0,0,0,0],this.dataBox=[-10,-10,10,10],this.gridLineEnable=[!0,!0],this.gridLineWidth=[1,1],this.gridLineColor=[[0,0,0,1],[0,0,0,1]],this.pixelRatio=1,this.tickMarkLength=[0,0,0,0],this.tickMarkWidth=[0,0,0,0],this.tickMarkColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[15,15,15,15],this.tickAngle=[0,0,0,0],this.tickEnable=[!0,!0,!0,!0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[15,15,15,15],this.labelAngle=[0,Math.PI/2,0,3*Math.PI/2],this.labelEnable=[!0,!0,!0,!0],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.titleCenter=[0,0],this.titleEnable=!0,this.titleAngle=0,this.titleColor=[0,0,0,1],this.borderColor=[0,0,0,0],this.backgroundColor=[0,0,0,0],this.zeroLineEnable=[!0,!0],this.zeroLineWidth=[4,4],this.zeroLineColor=[[0,0,0,1],[0,0,0,1]],this.borderLineEnable=[!0,!0,!0,!0],this.borderLineWidth=[2,2,2,2],this.borderLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.grid=null,this.text=null,this.line=null,this.box=null,this.objects=[],this.overlays=[],this._tickBounds=[1/0,1/0,-1/0,-1/0],this.static=!1,this.dirty=!1,this.pickDirty=!1,this.pickDelay=120,this.pickRadius=10,this._pickTimeout=null,this._drawPick=this.drawPick.bind(this),this._depthCounter=0}var c=l.prototype;function u(t){for(var e=t.slice(),r=0;r<e.length;++r)e[r]=e[r].slice();return e}function f(t,e){return t.x-e.x}c.setDirty=function(){this.dirty=this.pickDirty=!0},c.setOverlayDirty=function(){this.dirty=!0},c.nextDepthValue=function(){return this._depthCounter++/65536},c.draw=function(){var t=this.gl,e=this.screenBox,r=this.viewBox,n=this.dataBox,i=this.pixelRatio,a=this.grid,o=this.line,s=this.text,l=this.objects;if(this._depthCounter=0,this.pickDirty&&(this._pickTimeout&&clearTimeout(this._pickTimeout),this.pickDirty=!1,this._pickTimeout=setTimeout(this._drawPick,this.pickDelay)),this.dirty){if(this.dirty=!1,t.bindFramebuffer(t.FRAMEBUFFER,null),t.enable(t.SCISSOR_TEST),t.disable(t.DEPTH_TEST),t.depthFunc(t.LESS),t.depthMask(!1),t.enable(t.BLEND),t.blendEquation(t.FUNC_ADD,t.FUNC_ADD),t.blendFunc(t.ONE,t.ONE_MINUS_SRC_ALPHA),this.borderColor){t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]);var c=this.borderColor;t.clearColor(c[0]*c[3],c[1]*c[3],c[2]*c[3],c[3]),t.clear(t.COLOR_BUFFER_BIT|t.DEPTH_BUFFER_BIT)}t.scissor(r[0],r[1],r[2]-r[0],r[3]-r[1]),t.viewport(r[0],r[1],r[2]-r[0],r[3]-r[1]);var u=this.backgroundColor;t.clearColor(u[0]*u[3],u[1]*u[3],u[2]*u[3],u[3]),t.clear(t.COLOR_BUFFER_BIT),a.draw();var f=this.zeroLineEnable,h=this.zeroLineColor,p=this.zeroLineWidth;if(f[0]||f[1]){o.bind();for(var d=0;d<2;++d)if(f[d]&&n[d]<=0&&n[d+2]>=0){var g=e[d]-n[d]*(e[d+2]-e[d])/(n[d+2]-n[d]);0===d?o.drawLine(g,e[1],g,e[3],p[d],h[d]):o.drawLine(e[0],g,e[2],g,p[d],h[d])}}for(d=0;d<l.length;++d)l[d].draw();t.viewport(e[0],e[1],e[2]-e[0],e[3]-e[1]),t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]),this.grid.drawTickMarks(),o.bind();var m=this.borderLineEnable,v=this.borderLineWidth,y=this.borderLineColor;for(m[1]&&o.drawLine(r[0],r[1]-.5*v[1]*i,r[0],r[3]+.5*v[3]*i,v[1],y[1]),m[0]&&o.drawLine(r[0]-.5*v[0]*i,r[1],r[2]+.5*v[2]*i,r[1],v[0],y[0]),m[3]&&o.drawLine(r[2],r[1]-.5*v[1]*i,r[2],r[3]+.5*v[3]*i,v[3],y[3]),m[2]&&o.drawLine(r[0]-.5*v[0]*i,r[3],r[2]+.5*v[2]*i,r[3],v[2],y[2]),s.bind(),d=0;d<2;++d)s.drawTicks(d);this.titleEnable&&s.drawTitle();var x=this.overlays;for(d=0;d<x.length;++d)x[d].draw();t.disable(t.SCISSOR_TEST),t.disable(t.BLEND),t.depthMask(!0)}},c.drawPick=function(){if(!this.static){var t=this.pickBuffer;this.gl,this._pickTimeout=null,t.begin();for(var e=1,r=this.objects,n=0;n<r.length;++n)e=r[n].drawPick(e);t.end()}},c.pick=function(t,e){if(!this.static){var r=this.pixelRatio,n=this.pickPixelRatio,i=this.viewBox,a=0|Math.round((t-i[0]/r)*n),o=0|Math.round((e-i[1]/r)*n),s=this.pickBuffer.query(a,o,this.pickRadius);if(!s)return null;for(var l=s.id+(s.value[0]<<8)+(s.value[1]<<16)+(s.value[2]<<24),c=this.objects,u=0;u<c.length;++u){var f=c[u].pick(a,o,l);if(f)return f}return null}},c.setScreenBox=function(t){var e=this.screenBox,r=this.pixelRatio;e[0]=0|Math.round(t[0]*r),e[1]=0|Math.round(t[1]*r),e[2]=0|Math.round(t[2]*r),e[3]=0|Math.round(t[3]*r),this.setDirty()},c.setDataBox=function(t){var e=this.dataBox;(e[0]!==t[0]||e[1]!==t[1]||e[2]!==t[2]||e[3]!==t[3])&&(e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],this.setDirty())},c.setViewBox=function(t){var e=this.pixelRatio,r=this.viewBox;r[0]=0|Math.round(t[0]*e),r[1]=0|Math.round(t[1]*e),r[2]=0|Math.round(t[2]*e),r[3]=0|Math.round(t[3]*e);var n=this.pickPixelRatio;this.pickBuffer.shape=[0|Math.round((t[2]-t[0])*n),0|Math.round((t[3]-t[1])*n)],this.setDirty()},c.update=function(t){t=t||{};var e=this.gl;this.pixelRatio=t.pixelRatio||1;var r=this.pixelRatio;this.pickPixelRatio=Math.max(r,1),this.setScreenBox(t.screenBox||[0,0,e.drawingBufferWidth/r,e.drawingBufferHeight/r]);this.screenBox;this.setViewBox(t.viewBox||[.125*(this.screenBox[2]-this.screenBox[0])/r,.125*(this.screenBox[3]-this.screenBox[1])/r,.875*(this.screenBox[2]-this.screenBox[0])/r,.875*(this.screenBox[3]-this.screenBox[1])/r]);var n=this.viewBox,i=(n[2]-n[0])/(n[3]-n[1]);this.setDataBox(t.dataBox||[-10,-10/i,10,10/i]),this.borderColor=!1!==t.borderColor&&(t.borderColor||[0,0,0,0]).slice(),this.backgroundColor=(t.backgroundColor||[0,0,0,0]).slice(),this.gridLineEnable=(t.gridLineEnable||[!0,!0]).slice(),this.gridLineWidth=(t.gridLineWidth||[1,1]).slice(),this.gridLineColor=u(t.gridLineColor||[[.5,.5,.5,1],[.5,.5,.5,1]]),this.zeroLineEnable=(t.zeroLineEnable||[!0,!0]).slice(),this.zeroLineWidth=(t.zeroLineWidth||[4,4]).slice(),this.zeroLineColor=u(t.zeroLineColor||[[0,0,0,1],[0,0,0,1]]),this.tickMarkLength=(t.tickMarkLength||[0,0,0,0]).slice(),this.tickMarkWidth=(t.tickMarkWidth||[0,0,0,0]).slice(),this.tickMarkColor=u(t.tickMarkColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.titleCenter=(t.titleCenter||[.5*(n[0]+n[2])/r,(n[3]+120)/r]).slice(),this.titleEnable=!(\"titleEnable\"in t)||!!t.titleEnable,this.titleAngle=t.titleAngle||0,this.titleColor=(t.titleColor||[0,0,0,1]).slice(),this.labelPad=(t.labelPad||[15,15,15,15]).slice(),this.labelAngle=(t.labelAngle||[0,Math.PI/2,0,3*Math.PI/2]).slice(),this.labelEnable=(t.labelEnable||[!0,!0,!0,!0]).slice(),this.labelColor=u(t.labelColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.tickPad=(t.tickPad||[15,15,15,15]).slice(),this.tickAngle=(t.tickAngle||[0,0,0,0]).slice(),this.tickEnable=(t.tickEnable||[!0,!0,!0,!0]).slice(),this.tickColor=u(t.tickColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.borderLineEnable=(t.borderLineEnable||[!0,!0,!0,!0]).slice(),this.borderLineWidth=(t.borderLineWidth||[2,2,2,2]).slice(),this.borderLineColor=u(t.borderLineColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]);var a=t.ticks||[[],[]],o=this._tickBounds;o[0]=o[1]=1/0,o[2]=o[3]=-1/0;for(var s=0;s<2;++s){var l=a[s].slice(0);0!==l.length&&(l.sort(f),o[s]=Math.min(o[s],l[0].x),o[s+2]=Math.max(o[s+2],l[l.length-1].x))}this.grid.update({bounds:o,ticks:a}),this.text.update({bounds:o,ticks:a,labels:t.labels||[\"x\",\"y\"],labelSize:t.labelSize||[12,12],labelFont:t.labelFont||[\"sans-serif\",\"sans-serif\"],title:t.title||\"\",titleSize:t.titleSize||18,titleFont:t.titleFont||\"sans-serif\"}),this.static=!!t.static,this.setDirty()},c.dispose=function(){this.box.dispose(),this.grid.dispose(),this.text.dispose(),this.line.dispose();for(var t=this.objects.length-1;t>=0;--t)this.objects[t].dispose();this.objects.length=0;for(t=this.overlays.length-1;t>=0;--t)this.overlays[t].dispose();this.overlays.length=0,this.gl=null},c.addObject=function(t){this.objects.indexOf(t)<0&&(this.objects.push(t),this.setDirty())},c.removeObject=function(t){for(var e=this.objects,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setDirty();break}},c.addOverlay=function(t){this.overlays.indexOf(t)<0&&(this.overlays.push(t),this.setOverlayDirty())},c.removeOverlay=function(t){for(var e=this.overlays,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setOverlayDirty();break}}},{\"./lib/box\":316,\"./lib/grid\":317,\"./lib/line\":318,\"./lib/text\":320,\"gl-select-static\":338}],323:[function(t,e,r){\"use strict\";e.exports=function(t,e){t=t||document.body,e=e||{};var r=[.01,1/0];\"distanceLimits\"in e&&(r[0]=e.distanceLimits[0],r[1]=e.distanceLimits[1]);\"zoomMin\"in e&&(r[0]=e.zoomMin);\"zoomMax\"in e&&(r[1]=e.zoomMax);var c=i({center:e.center||[0,0,0],up:e.up||[0,1,0],eye:e.eye||[0,0,10],mode:e.mode||\"orbit\",distanceLimits:r}),u=[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],f=0,h=t.clientWidth,p=t.clientHeight,d={keyBindingMode:\"rotate\",enableWheel:!0,view:c,element:t,delay:e.delay||16,rotateSpeed:e.rotateSpeed||1,zoomSpeed:e.zoomSpeed||1,translateSpeed:e.translateSpeed||1,flipX:!!e.flipX,flipY:!!e.flipY,modes:c.modes,_ortho:e._ortho||e.projection&&\"orthographic\"===e.projection.type||!1,tick:function(){var e=n(),r=this.delay,i=e-2*r;c.idle(e-r),c.recalcMatrix(i),c.flush(e-(100+2*r));for(var a=!0,o=c.computedMatrix,s=0;s<16;++s)a=a&&u[s]===o[s],u[s]=o[s];var l=t.clientWidth===h&&t.clientHeight===p;return h=t.clientWidth,p=t.clientHeight,a?!l:(f=Math.exp(c.computedRadius[0]),!0)},lookAt:function(t,e,r){c.lookAt(c.lastT(),t,e,r)},rotate:function(t,e,r){c.rotate(c.lastT(),t,e,r)},pan:function(t,e,r){c.pan(c.lastT(),t,e,r)},translate:function(t,e,r){c.translate(c.lastT(),t,e,r)}};return Object.defineProperties(d,{matrix:{get:function(){return c.computedMatrix},set:function(t){return c.setMatrix(c.lastT(),t),c.computedMatrix},enumerable:!0},mode:{get:function(){return c.getMode()},set:function(t){var e=c.computedUp.slice(),r=c.computedEye.slice(),i=c.computedCenter.slice();if(c.setMode(t),\"turntable\"===t){var a=n();c._active.lookAt(a,r,i,e),c._active.lookAt(a+500,r,i,[0,0,1]),c._active.flush(a)}return c.getMode()},enumerable:!0},center:{get:function(){return c.computedCenter},set:function(t){return c.lookAt(c.lastT(),null,t),c.computedCenter},enumerable:!0},eye:{get:function(){return c.computedEye},set:function(t){return c.lookAt(c.lastT(),t),c.computedEye},enumerable:!0},up:{get:function(){return c.computedUp},set:function(t){return c.lookAt(c.lastT(),null,null,t),c.computedUp},enumerable:!0},distance:{get:function(){return f},set:function(t){return c.setDistance(c.lastT(),t),t},enumerable:!0},distanceLimits:{get:function(){return c.getDistanceLimits(r)},set:function(t){return c.setDistanceLimits(t),t},enumerable:!0}}),t.addEventListener(\"contextmenu\",(function(t){return t.preventDefault(),!1})),d._lastX=-1,d._lastY=-1,d._lastMods={shift:!1,control:!1,alt:!1,meta:!1},d.enableMouseListeners=function(){function e(e,r,i,a){var o=d.keyBindingMode;if(!1!==o){var s=\"rotate\"===o,l=\"pan\"===o,u=\"zoom\"===o,h=!!a.control,p=!!a.alt,g=!!a.shift,m=!!(1&e),v=!!(2&e),y=!!(4&e),x=1/t.clientHeight,b=x*(r-d._lastX),_=x*(i-d._lastY),w=d.flipX?1:-1,T=d.flipY?1:-1,k=Math.PI*d.rotateSpeed,A=n();if(-1!==d._lastX&&-1!==d._lastY&&((s&&m&&!h&&!p&&!g||m&&!h&&!p&&g)&&c.rotate(A,w*k*b,-T*k*_,0),(l&&m&&!h&&!p&&!g||v||m&&h&&!p&&!g)&&c.pan(A,-d.translateSpeed*b*f,d.translateSpeed*_*f,0),u&&m&&!h&&!p&&!g||y||m&&!h&&p&&!g)){var M=-d.zoomSpeed*_/window.innerHeight*(A-c.lastT())*100;c.pan(A,0,0,f*(Math.exp(M)-1))}return d._lastX=r,d._lastY=i,d._lastMods=a,!0}}d.mouseListener=a(t,e),t.addEventListener(\"touchstart\",(function(r){var n=s(r.changedTouches[0],t);e(0,n[0],n[1],d._lastMods),e(1,n[0],n[1],d._lastMods)}),!!l&&{passive:!0}),t.addEventListener(\"touchmove\",(function(r){var n=s(r.changedTouches[0],t);e(1,n[0],n[1],d._lastMods),r.preventDefault()}),!!l&&{passive:!1}),t.addEventListener(\"touchend\",(function(t){e(0,d._lastX,d._lastY,d._lastMods)}),!!l&&{passive:!0}),d.wheelListener=o(t,(function(t,e){if(!1!==d.keyBindingMode&&d.enableWheel){var r=d.flipX?1:-1,i=d.flipY?1:-1,a=n();if(Math.abs(t)>Math.abs(e))c.rotate(a,0,0,-t*r*Math.PI*d.rotateSpeed/window.innerWidth);else if(!d._ortho){var o=-d.zoomSpeed*i*e/window.innerHeight*(a-c.lastT())/20;c.pan(a,0,0,f*(Math.exp(o)-1))}}}),!0)},d.enableMouseListeners(),d};var n=t(\"right-now\"),i=t(\"3d-view\"),a=t(\"mouse-change\"),o=t(\"mouse-wheel\"),s=t(\"mouse-event-offset\"),l=t(\"has-passive-events\")},{\"3d-view\":55,\"has-passive-events\":444,\"mouse-change\":470,\"mouse-event-offset\":471,\"mouse-wheel\":473,\"right-now\":542}],324:[function(t,e,r){var n=t(\"glslify\"),i=t(\"gl-shader\"),a=n([\"precision mediump float;\\n#define GLSLIFY 1\\nattribute vec2 position;\\nvarying vec2 uv;\\nvoid main() {\\n  uv = position;\\n  gl_Position = vec4(position, 0, 1);\\n}\"]),o=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D accumBuffer;\\nvarying vec2 uv;\\n\\nvoid main() {\\n  vec4 accum = texture2D(accumBuffer, 0.5 * (uv + 1.0));\\n  gl_FragColor = min(vec4(1,1,1,1), accum);\\n}\"]);e.exports=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec2\"}])}},{\"gl-shader\":339,glslify:325}],325:[function(t,e,r){arguments[4][265][0].apply(r,arguments)},{dup:265}],326:[function(t,e,r){\"use strict\";var n=t(\"./camera.js\"),i=t(\"gl-axes3d\"),a=t(\"gl-axes3d/properties\"),o=t(\"gl-spikes3d\"),s=t(\"gl-select-static\"),l=t(\"gl-fbo\"),c=t(\"a-big-triangle\"),u=t(\"mouse-change\"),f=t(\"gl-mat4/perspective\"),h=t(\"gl-mat4/ortho\"),p=t(\"./lib/shader\"),d=t(\"is-mobile\")({tablet:!0,featureDetect:!0});function g(){this.mouse=[-1,-1],this.screen=null,this.distance=1/0,this.index=null,this.dataCoordinate=null,this.dataPosition=null,this.object=null,this.data=null}function m(t){var e=Math.round(Math.log(Math.abs(t))/Math.log(10));if(e<0){var r=Math.round(Math.pow(10,-e));return Math.ceil(t*r)/r}if(e>0){r=Math.round(Math.pow(10,e));return Math.ceil(t/r)*r}return Math.ceil(t)}function v(t){return\"boolean\"!=typeof t||t}e.exports={createScene:function(t){(t=t||{}).camera=t.camera||{};var e=t.canvas;if(!e){if(e=document.createElement(\"canvas\"),t.container)t.container.appendChild(e);else document.body.appendChild(e)}var r=t.gl;r||(t.glOptions&&(d=!!t.glOptions.preserveDrawingBuffer),r=function(t,e){var r=null;try{(r=t.getContext(\"webgl\",e))||(r=t.getContext(\"experimental-webgl\",e))}catch(t){return null}return r}(e,t.glOptions||{premultipliedAlpha:!0,antialias:!0,preserveDrawingBuffer:d}));if(!r)throw new Error(\"webgl not supported\");var y=t.bounds||[[-10,-10,-10],[10,10,10]],x=new g,b=l(r,r.drawingBufferWidth,r.drawingBufferHeight,{preferFloat:!d}),_=p(r),w=t.cameraObject&&!0===t.cameraObject._ortho||t.camera.projection&&\"orthographic\"===t.camera.projection.type||!1,T={eye:t.camera.eye||[2,0,0],center:t.camera.center||[0,0,0],up:t.camera.up||[0,1,0],zoomMin:t.camera.zoomMax||.1,zoomMax:t.camera.zoomMin||100,mode:t.camera.mode||\"turntable\",_ortho:w},k=t.axes||{},A=i(r,k);A.enable=!k.disable;var M=t.spikes||{},S=o(r,M),E=[],L=[],C=[],P=[],I=!0,O=!0,z=new Array(16),D=new Array(16),R={view:null,projection:z,model:D,_ortho:!1},F=(O=!0,[r.drawingBufferWidth,r.drawingBufferHeight]),B=t.cameraObject||n(e,T),N={gl:r,contextLost:!1,pixelRatio:t.pixelRatio||1,canvas:e,selection:x,camera:B,axes:A,axesPixels:null,spikes:S,bounds:y,objects:E,shape:F,aspect:t.aspectRatio||[1,1,1],pickRadius:t.pickRadius||10,zNear:t.zNear||.01,zFar:t.zFar||1e3,fovy:t.fovy||Math.PI/4,clearColor:t.clearColor||[0,0,0,0],autoResize:v(t.autoResize),autoBounds:v(t.autoBounds),autoScale:!!t.autoScale,autoCenter:v(t.autoCenter),clipToBounds:v(t.clipToBounds),snapToData:!!t.snapToData,onselect:t.onselect||null,onrender:t.onrender||null,onclick:t.onclick||null,cameraParams:R,oncontextloss:null,mouseListener:null,_stopped:!1,getAspectratio:function(){return{x:this.aspect[0],y:this.aspect[1],z:this.aspect[2]}},setAspectratio:function(t){this.aspect[0]=t.x,this.aspect[1]=t.y,this.aspect[2]=t.z,O=!0},setBounds:function(t,e){this.bounds[0][t]=e.min,this.bounds[1][t]=e.max},setClearColor:function(t){this.clearColor=t},clearRGBA:function(){this.gl.clearColor(this.clearColor[0],this.clearColor[1],this.clearColor[2],this.clearColor[3]),this.gl.clear(this.gl.COLOR_BUFFER_BIT|this.gl.DEPTH_BUFFER_BIT)}},j=[r.drawingBufferWidth/N.pixelRatio|0,r.drawingBufferHeight/N.pixelRatio|0];function U(){if(!N._stopped&&N.autoResize){var t=e.parentNode,r=1,n=1;t&&t!==document.body?(r=t.clientWidth,n=t.clientHeight):(r=window.innerWidth,n=window.innerHeight);var i=0|Math.ceil(r*N.pixelRatio),a=0|Math.ceil(n*N.pixelRatio);if(i!==e.width||a!==e.height){e.width=i,e.height=a;var o=e.style;o.position=o.position||\"absolute\",o.left=\"0px\",o.top=\"0px\",o.width=r+\"px\",o.height=n+\"px\",I=!0}}}N.autoResize&&U();function V(){for(var t=E.length,e=P.length,n=0;n<e;++n)C[n]=0;t:for(n=0;n<t;++n){var i=E[n],a=i.pickSlots;if(a){for(var o=0;o<e;++o)if(C[o]+a<255){L[n]=o,i.setPickBase(C[o]+1),C[o]+=a;continue t}var l=s(r,F);L[n]=e,P.push(l),C.push(a),i.setPickBase(1),e+=1}else L[n]=-1}for(;e>0&&0===C[e-1];)C.pop(),P.pop().dispose()}function q(){if(N.contextLost)return!0;r.isContextLost()&&(N.contextLost=!0,N.mouseListener.enabled=!1,N.selection.object=null,N.oncontextloss&&N.oncontextloss())}window.addEventListener(\"resize\",U),N.update=function(t){N._stopped||(t=t||{},I=!0,O=!0)},N.add=function(t){N._stopped||(t.axes=A,E.push(t),L.push(-1),I=!0,O=!0,V())},N.remove=function(t){if(!N._stopped){var e=E.indexOf(t);e<0||(E.splice(e,1),L.pop(),I=!0,O=!0,V())}},N.dispose=function(){if(!N._stopped&&(N._stopped=!0,window.removeEventListener(\"resize\",U),e.removeEventListener(\"webglcontextlost\",q),N.mouseListener.enabled=!1,!N.contextLost)){A.dispose(),S.dispose();for(var t=0;t<E.length;++t)E[t].dispose();b.dispose();for(t=0;t<P.length;++t)P[t].dispose();_.dispose(),r=null,A=null,S=null,E=[]}},N._mouseRotating=!1,N._prevButtons=0,N.enableMouseListeners=function(){N.mouseListener=u(e,(function(t,e,r){if(!N._stopped){var n=P.length,i=E.length,a=x.object;x.distance=1/0,x.mouse[0]=e,x.mouse[1]=r,x.object=null,x.screen=null,x.dataCoordinate=x.dataPosition=null;var o=!1;if(t&&N._prevButtons)N._mouseRotating=!0;else{N._mouseRotating&&(O=!0),N._mouseRotating=!1;for(var s=0;s<n;++s){var l=P[s].query(e,j[1]-r-1,N.pickRadius);if(l){if(l.distance>x.distance)continue;for(var c=0;c<i;++c){var u=E[c];if(L[c]===s){var f=u.pick(l);f&&(x.buttons=t,x.screen=l.coord,x.distance=l.distance,x.object=u,x.index=f.distance,x.dataPosition=f.position,x.dataCoordinate=f.dataCoordinate,x.data=f,o=!0)}}}}}a&&a!==x.object&&(a.highlight&&a.highlight(null),I=!0),x.object&&(x.object.highlight&&x.object.highlight(x.data),I=!0),(o=o||x.object!==a)&&N.onselect&&N.onselect(x),1&t&&!(1&N._prevButtons)&&N.onclick&&N.onclick(x),N._prevButtons=t}}))},e.addEventListener(\"webglcontextlost\",q);var H=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],G=[H[0].slice(),H[1].slice()];function Y(){if(!q()){U();var t=N.camera.tick();R.view=N.camera.matrix,I=I||t,O=O||t,A.pixelRatio=N.pixelRatio,S.pixelRatio=N.pixelRatio;var e=E.length,n=H[0],i=H[1];n[0]=n[1]=n[2]=1/0,i[0]=i[1]=i[2]=-1/0;for(var o=0;o<e;++o){(C=E[o]).pixelRatio=N.pixelRatio,C.axes=N.axes,I=I||!!C.dirty,O=O||!!C.dirty;var s=C.bounds;if(s)for(var l=s[0],u=s[1],p=0;p<3;++p)n[p]=Math.min(n[p],l[p]),i[p]=Math.max(i[p],u[p])}var d=N.bounds;if(N.autoBounds)for(p=0;p<3;++p){if(i[p]<n[p])n[p]=-1,i[p]=1;else{n[p]===i[p]&&(n[p]-=1,i[p]+=1);var g=.05*(i[p]-n[p]);n[p]=n[p]-g,i[p]=i[p]+g}d[0][p]=n[p],d[1][p]=i[p]}var v=!1;for(p=0;p<3;++p)v=v||G[0][p]!==d[0][p]||G[1][p]!==d[1][p],G[0][p]=d[0][p],G[1][p]=d[1][p];if(O=O||v,I=I||v){if(v){var y=[0,0,0];for(o=0;o<3;++o)y[o]=m((d[1][o]-d[0][o])/10);A.autoTicks?A.update({bounds:d,tickSpacing:y}):A.update({bounds:d})}var T=r.drawingBufferWidth,k=r.drawingBufferHeight;F[0]=T,F[1]=k,j[0]=0|Math.max(T/N.pixelRatio,1),j[1]=0|Math.max(k/N.pixelRatio,1),function(t,e){var r=t.bounds,n=t.cameraParams,i=n.projection,a=n.model,o=t.gl.drawingBufferWidth,s=t.gl.drawingBufferHeight,l=t.zNear,c=t.zFar,u=t.fovy,p=o/s;e?(h(i,-p,p,-1,1,l,c),n._ortho=!0):(f(i,u,p,l,c),n._ortho=!1);for(var d=0;d<16;++d)a[d]=0;a[15]=1;var g=0;for(d=0;d<3;++d)g=Math.max(g,r[1][d]-r[0][d]);for(d=0;d<3;++d)t.autoScale?a[5*d]=t.aspect[d]/(r[1][d]-r[0][d]):a[5*d]=1/g,t.autoCenter&&(a[12+d]=.5*-a[5*d]*(r[0][d]+r[1][d]))}(N,w);for(o=0;o<e;++o){(C=E[o]).axesBounds=d,N.clipToBounds&&(C.clipBounds=d)}x.object&&(N.snapToData?S.position=x.dataCoordinate:S.position=x.dataPosition,S.bounds=d),O&&(O=!1,function(){if(!q()){r.colorMask(!0,!0,!0,!0),r.depthMask(!0),r.disable(r.BLEND),r.enable(r.DEPTH_TEST),r.depthFunc(r.LEQUAL);for(var t=E.length,e=P.length,n=0;n<e;++n){var i=P[n];i.shape=j,i.begin();for(var a=0;a<t;++a)if(L[a]===n){var o=E[a];o.drawPick&&(o.pixelRatio=1,o.drawPick(R))}i.end()}}}()),N.axesPixels=a(N.axes,R,T,k),N.onrender&&N.onrender(),r.bindFramebuffer(r.FRAMEBUFFER,null),r.viewport(0,0,T,k),N.clearRGBA(),r.depthMask(!0),r.colorMask(!0,!0,!0,!0),r.enable(r.DEPTH_TEST),r.depthFunc(r.LEQUAL),r.disable(r.BLEND),r.disable(r.CULL_FACE);var M=!1;A.enable&&(M=M||A.isTransparent(),A.draw(R)),S.axes=A,x.object&&S.draw(R),r.disable(r.CULL_FACE);for(o=0;o<e;++o){(C=E[o]).axes=A,C.pixelRatio=N.pixelRatio,C.isOpaque&&C.isOpaque()&&C.draw(R),C.isTransparent&&C.isTransparent()&&(M=!0)}if(M){b.shape=F,b.bind(),r.clear(r.DEPTH_BUFFER_BIT),r.colorMask(!1,!1,!1,!1),r.depthMask(!0),r.depthFunc(r.LESS),A.enable&&A.isTransparent()&&A.drawTransparent(R);for(o=0;o<e;++o){(C=E[o]).isOpaque&&C.isOpaque()&&C.draw(R)}r.enable(r.BLEND),r.blendEquation(r.FUNC_ADD),r.blendFunc(r.ONE,r.ONE_MINUS_SRC_ALPHA),r.colorMask(!0,!0,!0,!0),r.depthMask(!1),r.clearColor(0,0,0,0),r.clear(r.COLOR_BUFFER_BIT),A.isTransparent()&&A.drawTransparent(R);for(o=0;o<e;++o){var C;(C=E[o]).isTransparent&&C.isTransparent()&&C.drawTransparent(R)}r.bindFramebuffer(r.FRAMEBUFFER,null),r.blendFunc(r.ONE,r.ONE_MINUS_SRC_ALPHA),r.disable(r.DEPTH_TEST),_.bind(),b.color[0].bind(0),_.uniforms.accumBuffer=0,c(r),r.disable(r.BLEND)}I=!1;for(o=0;o<e;++o)E[o].dirty=!1}}}return N.enableMouseListeners(),function t(){if(N._stopped||N.contextLost)return;Y(),requestAnimationFrame(t)}(),N.redraw=function(){N._stopped||(I=!0,Y())},N},createCamera:n}},{\"./camera.js\":323,\"./lib/shader\":324,\"a-big-triangle\":70,\"gl-axes3d\":258,\"gl-axes3d/properties\":266,\"gl-fbo\":276,\"gl-mat4/ortho\":302,\"gl-mat4/perspective\":303,\"gl-select-static\":338,\"gl-spikes3d\":349,\"is-mobile\":455,\"mouse-change\":470}],327:[function(t,e,r){var n=t(\"glslify\");r.pointVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform float pointCloud;\\n\\nhighp float rand(vec2 co) {\\n  highp float a = 12.9898;\\n  highp float b = 78.233;\\n  highp float c = 43758.5453;\\n  highp float d = dot(co.xy, vec2(a, b));\\n  highp float e = mod(d, 3.14);\\n  return fract(sin(e) * c);\\n}\\n\\nvoid main() {\\n  vec3 hgPosition = matrix * vec3(position, 1);\\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\\n    // if we don't jitter the point size a bit, overall point cloud\\n    // saturation 'jumps' on zooming, which is disturbing and confusing\\n  gl_PointSize = pointSize * ((19.5 + rand(position)) / 20.0);\\n  if(pointCloud != 0.0) { // pointCloud is truthy\\n    // get the same square surface as circle would be\\n    gl_PointSize *= 0.886;\\n  }\\n}\"]),r.pointFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color, borderColor;\\nuniform float centerFraction;\\nuniform float pointCloud;\\n\\nvoid main() {\\n  float radius;\\n  vec4 baseColor;\\n  if(pointCloud != 0.0) { // pointCloud is truthy\\n    if(centerFraction == 1.0) {\\n      gl_FragColor = color;\\n    } else {\\n      gl_FragColor = mix(borderColor, color, centerFraction);\\n    }\\n  } else {\\n    radius = length(2.0 * gl_PointCoord.xy - 1.0);\\n    if(radius > 1.0) {\\n      discard;\\n    }\\n    baseColor = mix(borderColor, color, step(radius, centerFraction));\\n    gl_FragColor = vec4(baseColor.rgb * baseColor.a, baseColor.a);\\n  }\\n}\\n\"]),r.pickVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position;\\nattribute vec4 pickId;\\n\\nuniform mat3 matrix;\\nuniform float pointSize;\\nuniform vec4 pickOffset;\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  vec3 hgPosition = matrix * vec3(position, 1);\\n  gl_Position  = vec4(hgPosition.xy, 0, hgPosition.z);\\n  gl_PointSize = pointSize;\\n\\n  vec4 id = pickId + pickOffset;\\n  id.y += floor(id.x / 256.0);\\n  id.x -= floor(id.x / 256.0) * 256.0;\\n\\n  id.z += floor(id.y / 256.0);\\n  id.y -= floor(id.y / 256.0) * 256.0;\\n\\n  id.w += floor(id.z / 256.0);\\n  id.z -= floor(id.z / 256.0) * 256.0;\\n\\n  fragId = id;\\n}\\n\"]),r.pickFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragId;\\n\\nvoid main() {\\n  float radius = length(2.0 * gl_PointCoord.xy - 1.0);\\n  if(radius > 1.0) {\\n    discard;\\n  }\\n  gl_FragColor = fragId / 255.0;\\n}\\n\"])},{glslify:442}],328:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=t(\"gl-buffer\"),a=t(\"typedarray-pool\"),o=t(\"./lib/shader\");function s(t,e,r,n,i){this.plot=t,this.offsetBuffer=e,this.pickBuffer=r,this.shader=n,this.pickShader=i,this.sizeMin=.5,this.sizeMinCap=2,this.sizeMax=20,this.areaRatio=1,this.pointCount=0,this.color=[1,0,0,1],this.borderColor=[0,0,0,1],this.blend=!1,this.pickOffset=0,this.points=null}e.exports=function(t,e){var r=t.gl,a=i(r),l=i(r),c=n(r,o.pointVertex,o.pointFragment),u=n(r,o.pickVertex,o.pickFragment),f=new s(t,a,l,c,u);return f.update(e),t.addObject(f),f};var l,c,u=s.prototype;u.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.offsetBuffer.dispose(),this.pickBuffer.dispose(),this.plot.removeObject(this)},u.update=function(t){var e;function r(e,r){return e in t?t[e]:r}t=t||{},this.sizeMin=r(\"sizeMin\",.5),this.sizeMax=r(\"sizeMax\",20),this.color=r(\"color\",[1,0,0,1]).slice(),this.areaRatio=r(\"areaRatio\",1),this.borderColor=r(\"borderColor\",[0,0,0,1]).slice(),this.blend=r(\"blend\",!1);var n=t.positions.length>>>1,i=t.positions instanceof Float32Array,o=t.idToIndex instanceof Int32Array&&t.idToIndex.length>=n,s=t.positions,l=i?s:a.mallocFloat32(s.length),c=o?t.idToIndex:a.mallocInt32(n);if(i||l.set(s),!o)for(l.set(s),e=0;e<n;e++)c[e]=e;this.points=s,this.offsetBuffer.update(l),this.pickBuffer.update(c),i||a.free(l),o||a.free(c),this.pointCount=n,this.pickOffset=0},u.unifiedDraw=(l=[1,0,0,0,1,0,0,0,1],c=[0,0,0,0],function(t){var e=void 0!==t,r=e?this.pickShader:this.shader,n=this.plot.gl,i=this.plot.dataBox;if(0===this.pointCount)return t;var a=i[2]-i[0],o=i[3]-i[1],s=function(t,e){var r,n=0,i=t.length>>>1;for(r=0;r<i;r++){var a=t[2*r],o=t[2*r+1];a>=e[0]&&a<=e[2]&&o>=e[1]&&o<=e[3]&&n++}return n}(this.points,i),u=this.plot.pickPixelRatio*Math.max(Math.min(this.sizeMinCap,this.sizeMin),Math.min(this.sizeMax,this.sizeMax/Math.pow(s,.33333)));l[0]=2/a,l[4]=2/o,l[6]=-2*i[0]/a-1,l[7]=-2*i[1]/o-1,this.offsetBuffer.bind(),r.bind(),r.attributes.position.pointer(),r.uniforms.matrix=l,r.uniforms.color=this.color,r.uniforms.borderColor=this.borderColor,r.uniforms.pointCloud=u<5,r.uniforms.pointSize=u,r.uniforms.centerFraction=Math.min(1,Math.max(0,Math.sqrt(1-this.areaRatio))),e&&(c[0]=255&t,c[1]=t>>8&255,c[2]=t>>16&255,c[3]=t>>24&255,this.pickBuffer.bind(),r.attributes.pickId.pointer(n.UNSIGNED_BYTE),r.uniforms.pickOffset=c,this.pickOffset=t);var f=n.getParameter(n.BLEND),h=n.getParameter(n.DITHER);return f&&!this.blend&&n.disable(n.BLEND),h&&n.disable(n.DITHER),n.drawArrays(n.POINTS,0,this.pointCount),f&&!this.blend&&n.enable(n.BLEND),h&&n.enable(n.DITHER),t+this.pointCount}),u.draw=u.unifiedDraw,u.drawPick=u.unifiedDraw,u.pick=function(t,e,r){var n=this.pickOffset,i=this.pointCount;if(r<n||r>=n+i)return null;var a=r-n,o=this.points;return{object:this,pointId:a,dataCoord:[o[2*a],o[2*a+1]]}}},{\"./lib/shader\":327,\"gl-buffer\":267,\"gl-shader\":339,\"typedarray-pool\":617}],329:[function(t,e,r){e.exports=function(t,e,r,n){var i,a,o,s,l,c=e[0],u=e[1],f=e[2],h=e[3],p=r[0],d=r[1],g=r[2],m=r[3];(a=c*p+u*d+f*g+h*m)<0&&(a=-a,p=-p,d=-d,g=-g,m=-m);1-a>1e-6?(i=Math.acos(a),o=Math.sin(i),s=Math.sin((1-n)*i)/o,l=Math.sin(n*i)/o):(s=1-n,l=n);return t[0]=s*c+l*p,t[1]=s*u+l*d,t[2]=s*f+l*g,t[3]=s*h+l*m,t}},{}],330:[function(t,e,r){\"use strict\";e.exports=function(t){return t||0===t?t.toString():\"\"}},{}],331:[function(t,e,r){\"use strict\";var n=t(\"vectorize-text\");e.exports=function(t,e,r){var a=i[e];a||(a=i[e]={});if(t in a)return a[t];var o={textAlign:\"center\",textBaseline:\"middle\",lineHeight:1,font:e,lineSpacing:1.25,styletags:{breaklines:!0,bolds:!0,italics:!0,subscripts:!0,superscripts:!0},triangles:!0},s=n(t,o);o.triangles=!1;var l,c,u=n(t,o);if(r&&1!==r){for(l=0;l<s.positions.length;++l)for(c=0;c<s.positions[l].length;++c)s.positions[l][c]/=r;for(l=0;l<u.positions.length;++l)for(c=0;c<u.positions[l].length;++c)u.positions[l][c]/=r}var f=[[1/0,1/0],[-1/0,-1/0]],h=u.positions.length;for(l=0;l<h;++l){var p=u.positions[l];for(c=0;c<2;++c)f[0][c]=Math.min(f[0][c],p[c]),f[1][c]=Math.max(f[1][c],p[c])}return a[t]=[s,u,f]};var i={}},{\"vectorize-text\":623}],332:[function(t,e,r){var n=t(\"gl-shader\"),i=t(\"glslify\"),a=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform vec4 highlightId;\\nuniform float highlightScale;\\nuniform mat4 model, view, projection;\\nuniform vec3 clipBounds[2];\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float scale = 1.0;\\n    if(distance(highlightId, id) < 0.0001) {\\n      scale = highlightScale;\\n    }\\n\\n    vec4 worldPosition = model * vec4(position, 1);\\n    vec4 viewPosition = view * worldPosition;\\n    viewPosition = viewPosition / viewPosition.w;\\n    vec4 clipPosition = projection * (viewPosition + scale * vec4(glyph.x, -glyph.y, 0, 0));\\n\\n    gl_Position = clipPosition;\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = position;\\n  }\\n}\"]),o=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float highlightScale, pixelRatio;\\nuniform vec4 highlightId;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float scale = pixelRatio;\\n    if(distance(highlightId.bgr, id.bgr) < 0.001) {\\n      scale *= highlightScale;\\n    }\\n\\n    vec4 worldPosition = model * vec4(position, 1.0);\\n    vec4 viewPosition = view * worldPosition;\\n    vec4 clipPosition = projection * viewPosition;\\n    clipPosition /= clipPosition.w;\\n\\n    gl_Position = clipPosition + vec4(screenSize * scale * vec2(glyph.x, -glyph.y), 0.0, 0.0);\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = position;\\n  }\\n}\"]),s=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nattribute vec3 position;\\nattribute vec4 color;\\nattribute vec2 glyph;\\nattribute vec4 id;\\n\\nuniform float highlightScale;\\nuniform vec4 highlightId;\\nuniform vec3 axes[2];\\nuniform mat4 model, view, projection;\\nuniform vec2 screenSize;\\nuniform vec3 clipBounds[2];\\nuniform float scale, pixelRatio;\\n\\nvarying vec4 interpColor;\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], position)) {\\n\\n    gl_Position = vec4(0,0,0,0);\\n  } else {\\n    float lscale = pixelRatio * scale;\\n    if(distance(highlightId, id) < 0.0001) {\\n      lscale *= highlightScale;\\n    }\\n\\n    vec4 clipCenter   = projection * view * model * vec4(position, 1);\\n    vec3 dataPosition = position + 0.5*lscale*(axes[0] * glyph.x + axes[1] * glyph.y) * clipCenter.w * screenSize.y;\\n    vec4 clipPosition = projection * view * model * vec4(dataPosition, 1);\\n\\n    gl_Position = clipPosition;\\n    interpColor = color;\\n    pickId = id;\\n    dataCoordinate = dataPosition;\\n  }\\n}\\n\"]),l=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float opacity;\\n\\nvarying vec4 interpColor;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (\\n    outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate) ||\\n    interpColor.a * opacity == 0.\\n  ) discard;\\n  gl_FragColor = interpColor * opacity;\\n}\\n\"]),c=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 fragClipBounds[2];\\nuniform float pickGroup;\\n\\nvarying vec4 pickId;\\nvarying vec3 dataCoordinate;\\n\\nvoid main() {\\n  if (outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate)) discard;\\n\\n  gl_FragColor = vec4(pickGroup, pickId.bgr);\\n}\"]),u=[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec4\"},{name:\"glyph\",type:\"vec2\"},{name:\"id\",type:\"vec4\"}],f={vertex:a,fragment:l,attributes:u},h={vertex:o,fragment:l,attributes:u},p={vertex:s,fragment:l,attributes:u},d={vertex:a,fragment:c,attributes:u},g={vertex:o,fragment:c,attributes:u},m={vertex:s,fragment:c,attributes:u};function v(t,e){var r=n(t,e),i=r.attributes;return i.position.location=0,i.color.location=1,i.glyph.location=2,i.id.location=3,r}r.createPerspective=function(t){return v(t,f)},r.createOrtho=function(t){return v(t,h)},r.createProject=function(t){return v(t,p)},r.createPickPerspective=function(t){return v(t,d)},r.createPickOrtho=function(t){return v(t,g)},r.createPickProject=function(t){return v(t,m)}},{\"gl-shader\":339,glslify:333}],333:[function(t,e,r){arguments[4][265][0].apply(r,arguments)},{dup:265}],334:[function(t,e,r){\"use strict\";var n=t(\"is-string-blank\"),i=t(\"gl-buffer\"),a=t(\"gl-vao\"),o=t(\"typedarray-pool\"),s=t(\"gl-mat4/multiply\"),l=t(\"./lib/shaders\"),c=t(\"./lib/glyphs\"),u=t(\"./lib/get-simple-string\"),f=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function h(t,e){var r=t[0],n=t[1],i=t[2],a=t[3];return t[0]=e[0]*r+e[4]*n+e[8]*i+e[12]*a,t[1]=e[1]*r+e[5]*n+e[9]*i+e[13]*a,t[2]=e[2]*r+e[6]*n+e[10]*i+e[14]*a,t[3]=e[3]*r+e[7]*n+e[11]*i+e[15]*a,t}function p(t,e,r,n){return h(n,n),h(n,n),h(n,n)}function d(t,e){this.index=t,this.dataCoordinate=this.position=e}function g(t){return!0===t||t>1?1:t}function m(t,e,r,n,i,a,o,s,l,c,u,f){this.gl=t,this.pixelRatio=1,this.shader=e,this.orthoShader=r,this.projectShader=n,this.pointBuffer=i,this.colorBuffer=a,this.glyphBuffer=o,this.idBuffer=s,this.vao=l,this.vertexCount=0,this.lineVertexCount=0,this.opacity=1,this.hasAlpha=!1,this.lineWidth=0,this.projectScale=[2/3,2/3,2/3],this.projectOpacity=[1,1,1],this.projectHasAlpha=!1,this.pickId=0,this.pickPerspectiveShader=c,this.pickOrthoShader=u,this.pickProjectShader=f,this.points=[],this._selectResult=new d(0,[0,0,0]),this.useOrtho=!0,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.axesProject=[!0,!0,!0],this.axesBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.highlightId=[1,1,1,1],this.highlightScale=2,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.dirty=!0}e.exports=function(t){var e=t.gl,r=l.createPerspective(e),n=l.createOrtho(e),o=l.createProject(e),s=l.createPickPerspective(e),c=l.createPickOrtho(e),u=l.createPickProject(e),f=i(e),h=i(e),p=i(e),d=i(e),g=a(e,[{buffer:f,size:3,type:e.FLOAT},{buffer:h,size:4,type:e.FLOAT},{buffer:p,size:2,type:e.FLOAT},{buffer:d,size:4,type:e.UNSIGNED_BYTE,normalized:!0}]),v=new m(e,r,n,o,f,h,p,d,g,s,c,u);return v.update(t),v};var v=m.prototype;v.pickSlots=1,v.setPickBase=function(t){this.pickId=t},v.isTransparent=function(){if(this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&this.projectHasAlpha)return!0;return!1},v.isOpaque=function(){if(!this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&!this.projectHasAlpha)return!0;return!1};var y=[0,0],x=[0,0,0],b=[0,0,0],_=[0,0,0,1],w=[0,0,0,1],T=f.slice(),k=[0,0,0],A=[[0,0,0],[0,0,0]];function M(t){return t[0]=t[1]=t[2]=0,t}function S(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=1,t}function E(t,e,r,n){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[r]=n,t}function L(t,e,r,n){var i,a=e.axesProject,o=e.gl,l=t.uniforms,c=r.model||f,u=r.view||f,h=r.projection||f,d=e.axesBounds,g=function(t){for(var e=A,r=0;r<2;++r)for(var n=0;n<3;++n)e[r][n]=Math.max(Math.min(t[r][n],1e8),-1e8);return e}(e.clipBounds);i=e.axes&&e.axes.lastCubeProps?e.axes.lastCubeProps.axis:[1,1,1],y[0]=2/o.drawingBufferWidth,y[1]=2/o.drawingBufferHeight,t.bind(),l.view=u,l.projection=h,l.screenSize=y,l.highlightId=e.highlightId,l.highlightScale=e.highlightScale,l.clipBounds=g,l.pickGroup=e.pickId/255,l.pixelRatio=n;for(var m=0;m<3;++m)if(a[m]){l.scale=e.projectScale[m],l.opacity=e.projectOpacity[m];for(var v=T,L=0;L<16;++L)v[L]=0;for(L=0;L<4;++L)v[5*L]=1;v[5*m]=0,i[m]<0?v[12+m]=d[0][m]:v[12+m]=d[1][m],s(v,c,v),l.model=v;var C=(m+1)%3,P=(m+2)%3,I=M(x),O=M(b);I[C]=1,O[P]=1;var z=p(0,0,0,S(_,I)),D=p(0,0,0,S(w,O));if(Math.abs(z[1])>Math.abs(D[1])){var R=z;z=D,D=R,R=I,I=O,O=R;var F=C;C=P,P=F}z[0]<0&&(I[C]=-1),D[1]>0&&(O[P]=-1);var B=0,N=0;for(L=0;L<4;++L)B+=Math.pow(c[4*C+L],2),N+=Math.pow(c[4*P+L],2);I[C]/=Math.sqrt(B),O[P]/=Math.sqrt(N),l.axes[0]=I,l.axes[1]=O,l.fragClipBounds[0]=E(k,g[0],m,-1e8),l.fragClipBounds[1]=E(k,g[1],m,1e8),e.vao.bind(),e.vao.draw(o.TRIANGLES,e.vertexCount),e.lineWidth>0&&(o.lineWidth(e.lineWidth*n),e.vao.draw(o.LINES,e.lineVertexCount,e.vertexCount)),e.vao.unbind()}}var C=[[-1e8,-1e8,-1e8],[1e8,1e8,1e8]];function P(t,e,r,n,i,a,o){var s=r.gl;if((a===r.projectHasAlpha||o)&&L(e,r,n,i),a===r.hasAlpha||o){t.bind();var l=t.uniforms;l.model=n.model||f,l.view=n.view||f,l.projection=n.projection||f,y[0]=2/s.drawingBufferWidth,y[1]=2/s.drawingBufferHeight,l.screenSize=y,l.highlightId=r.highlightId,l.highlightScale=r.highlightScale,l.fragClipBounds=C,l.clipBounds=r.axes.bounds,l.opacity=r.opacity,l.pickGroup=r.pickId/255,l.pixelRatio=i,r.vao.bind(),r.vao.draw(s.TRIANGLES,r.vertexCount),r.lineWidth>0&&(s.lineWidth(r.lineWidth*i),r.vao.draw(s.LINES,r.lineVertexCount,r.vertexCount)),r.vao.unbind()}}function I(t,e,r,i){var a;a=Array.isArray(t)?e<t.length?t[e]:void 0:t,a=u(a);var o=!0;n(a)&&(a=\"\\u25bc\",o=!1);var s=c(a,r,i);return{mesh:s[0],lines:s[1],bounds:s[2],visible:o}}v.draw=function(t){P(this.useOrtho?this.orthoShader:this.shader,this.projectShader,this,t,this.pixelRatio,!1,!1)},v.drawTransparent=function(t){P(this.useOrtho?this.orthoShader:this.shader,this.projectShader,this,t,this.pixelRatio,!0,!1)},v.drawPick=function(t){P(this.useOrtho?this.pickOrthoShader:this.pickPerspectiveShader,this.pickProjectShader,this,t,1,!0,!0)},v.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[2]+(t.value[1]<<8)+(t.value[0]<<16);if(e>=this.pointCount||e<0)return null;var r=this.points[e],n=this._selectResult;n.index=e;for(var i=0;i<3;++i)n.position[i]=n.dataCoordinate[i]=r[i];return n},v.highlight=function(t){if(t){var e=t.index,r=255&e,n=e>>8&255,i=e>>16&255;this.highlightId=[r/255,n/255,i/255,0]}else this.highlightId=[1,1,1,1]},v.update=function(t){if(\"perspective\"in(t=t||{})&&(this.useOrtho=!t.perspective),\"orthographic\"in t&&(this.useOrtho=!!t.orthographic),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"project\"in t)if(Array.isArray(t.project))this.axesProject=t.project;else{var e=!!t.project;this.axesProject=[e,e,e]}if(\"projectScale\"in t)if(Array.isArray(t.projectScale))this.projectScale=t.projectScale.slice();else{var r=+t.projectScale;this.projectScale=[r,r,r]}if(this.projectHasAlpha=!1,\"projectOpacity\"in t){if(Array.isArray(t.projectOpacity))this.projectOpacity=t.projectOpacity.slice();else{r=+t.projectOpacity;this.projectOpacity=[r,r,r]}for(var n=0;n<3;++n)this.projectOpacity[n]=g(this.projectOpacity[n]),this.projectOpacity[n]<1&&(this.projectHasAlpha=!0)}this.hasAlpha=!1,\"opacity\"in t&&(this.opacity=g(t.opacity),this.opacity<1&&(this.hasAlpha=!0)),this.dirty=!0;var i,a,s=t.position,l=t.font||\"normal\",c=t.alignment||[0,0];if(2===c.length)i=c[0],a=c[1];else{i=[],a=[];for(n=0;n<c.length;++n)i[n]=c[n][0],a[n]=c[n][1]}var u=[1/0,1/0,1/0],f=[-1/0,-1/0,-1/0],h=t.glyph,p=t.color,d=t.size,m=t.angle,v=t.lineColor,y=-1,x=0,b=0,_=0;if(s.length){_=s.length;t:for(n=0;n<_;++n){for(var w=s[n],T=0;T<3;++T)if(isNaN(w[T])||!isFinite(w[T]))continue t;var k=(N=I(h,n,l,this.pixelRatio)).mesh,A=N.lines,M=N.bounds;x+=3*k.cells.length,b+=2*A.edges.length}}var S=x+b,E=o.mallocFloat(3*S),L=o.mallocFloat(4*S),C=o.mallocFloat(2*S),P=o.mallocUint32(S);if(S>0){var O=0,z=x,D=[0,0,0,1],R=[0,0,0,1],F=Array.isArray(p)&&Array.isArray(p[0]),B=Array.isArray(v)&&Array.isArray(v[0]);t:for(n=0;n<_;++n){y+=1;for(w=s[n],T=0;T<3;++T){if(isNaN(w[T])||!isFinite(w[T]))continue t;f[T]=Math.max(f[T],w[T]),u[T]=Math.min(u[T],w[T])}k=(N=I(h,n,l,this.pixelRatio)).mesh,A=N.lines,M=N.bounds;var N,j=N.visible;if(j)if(Array.isArray(p)){if(3===(U=F?n<p.length?p[n]:[0,0,0,0]:p).length){for(T=0;T<3;++T)D[T]=U[T];D[3]=1}else if(4===U.length){for(T=0;T<4;++T)D[T]=U[T];!this.hasAlpha&&U[3]<1&&(this.hasAlpha=!0)}}else D[0]=D[1]=D[2]=0,D[3]=1;else D=[1,1,1,0];if(j)if(Array.isArray(v)){var U;if(3===(U=B?n<v.length?v[n]:[0,0,0,0]:v).length){for(T=0;T<3;++T)R[T]=U[T];R[T]=1}else if(4===U.length){for(T=0;T<4;++T)R[T]=U[T];!this.hasAlpha&&U[3]<1&&(this.hasAlpha=!0)}}else R[0]=R[1]=R[2]=0,R[3]=1;else R=[1,1,1,0];var V=.5;j?Array.isArray(d)?V=n<d.length?+d[n]:12:d?V=+d:this.useOrtho&&(V=12):V=0;var q=0;Array.isArray(m)?q=n<m.length?+m[n]:0:m&&(q=+m);var H=Math.cos(q),G=Math.sin(q);for(w=s[n],T=0;T<3;++T)f[T]=Math.max(f[T],w[T]),u[T]=Math.min(u[T],w[T]);var Y=i,W=a;Y=0;Array.isArray(i)?Y=n<i.length?i[n]:0:i&&(Y=i);W=0;Array.isArray(a)?W=n<a.length?a[n]:0:a&&(W=a);var X=[Y*=Y>0?1-M[0][0]:Y<0?1+M[1][0]:1,W*=W>0?1-M[0][1]:W<0?1+M[1][1]:1],Z=k.cells||[],J=k.positions||[];for(T=0;T<Z.length;++T)for(var K=Z[T],Q=0;Q<3;++Q){for(var $=0;$<3;++$)E[3*O+$]=w[$];for($=0;$<4;++$)L[4*O+$]=D[$];P[O]=y;var tt=J[K[Q]];C[2*O]=V*(H*tt[0]-G*tt[1]+X[0]),C[2*O+1]=V*(G*tt[0]+H*tt[1]+X[1]),O+=1}for(Z=A.edges,J=A.positions,T=0;T<Z.length;++T)for(K=Z[T],Q=0;Q<2;++Q){for($=0;$<3;++$)E[3*z+$]=w[$];for($=0;$<4;++$)L[4*z+$]=R[$];P[z]=y;tt=J[K[Q]];C[2*z]=V*(H*tt[0]-G*tt[1]+X[0]),C[2*z+1]=V*(G*tt[0]+H*tt[1]+X[1]),z+=1}}}this.bounds=[u,f],this.points=s,this.pointCount=s.length,this.vertexCount=x,this.lineVertexCount=b,this.pointBuffer.update(E),this.colorBuffer.update(L),this.glyphBuffer.update(C),this.idBuffer.update(P),o.free(E),o.free(L),o.free(C),o.free(P)},v.dispose=function(){this.shader.dispose(),this.orthoShader.dispose(),this.pickPerspectiveShader.dispose(),this.pickOrthoShader.dispose(),this.vao.dispose(),this.pointBuffer.dispose(),this.colorBuffer.dispose(),this.glyphBuffer.dispose(),this.idBuffer.dispose()}},{\"./lib/get-simple-string\":330,\"./lib/glyphs\":331,\"./lib/shaders\":332,\"gl-buffer\":267,\"gl-mat4/multiply\":301,\"gl-vao\":361,\"is-string-blank\":458,\"typedarray-pool\":617}],335:[function(t,e,r){\"use strict\";var n=t(\"glslify\");r.boxVertex=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nattribute vec2 vertex;\\n\\nuniform vec2 cornerA, cornerB;\\n\\nvoid main() {\\n  gl_Position = vec4(mix(cornerA, cornerB, vertex), 0, 1);\\n}\\n\"]),r.boxFragment=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nuniform vec4 color;\\n\\nvoid main() {\\n  gl_FragColor = color;\\n}\\n\"])},{glslify:336}],336:[function(t,e,r){arguments[4][265][0].apply(r,arguments)},{dup:265}],337:[function(t,e,r){\"use strict\";var n=t(\"gl-shader\"),i=t(\"gl-buffer\"),a=t(\"./lib/shaders\");function o(t,e,r){this.plot=t,this.boxBuffer=e,this.boxShader=r,this.enabled=!0,this.selectBox=[1/0,1/0,-1/0,-1/0],this.borderColor=[0,0,0,1],this.innerFill=!1,this.innerColor=[0,0,0,.25],this.outerFill=!0,this.outerColor=[0,0,0,.5],this.borderWidth=10}e.exports=function(t,e){var r=t.gl,s=i(r,[0,0,0,1,1,0,1,1]),l=n(r,a.boxVertex,a.boxFragment),c=new o(t,s,l);return c.update(e),t.addOverlay(c),c};var s=o.prototype;s.draw=function(){if(this.enabled){var t=this.plot,e=this.selectBox,r=this.borderWidth,n=(this.innerFill,this.innerColor),i=(this.outerFill,this.outerColor),a=this.borderColor,o=t.box,s=t.screenBox,l=t.dataBox,c=t.viewBox,u=t.pixelRatio,f=(e[0]-l[0])*(c[2]-c[0])/(l[2]-l[0])+c[0],h=(e[1]-l[1])*(c[3]-c[1])/(l[3]-l[1])+c[1],p=(e[2]-l[0])*(c[2]-c[0])/(l[2]-l[0])+c[0],d=(e[3]-l[1])*(c[3]-c[1])/(l[3]-l[1])+c[1];if(f=Math.max(f,c[0]),h=Math.max(h,c[1]),p=Math.min(p,c[2]),d=Math.min(d,c[3]),!(p<f||d<h)){o.bind();var g=s[2]-s[0],m=s[3]-s[1];if(this.outerFill&&(o.drawBox(0,0,g,h,i),o.drawBox(0,h,f,d,i),o.drawBox(0,d,g,m,i),o.drawBox(p,h,g,d,i)),this.innerFill&&o.drawBox(f,h,p,d,n),r>0){var v=r*u;o.drawBox(f-v,h-v,p+v,h+v,a),o.drawBox(f-v,d-v,p+v,d+v,a),o.drawBox(f-v,h-v,f+v,d+v,a),o.drawBox(p-v,h-v,p+v,d+v,a)}}}},s.update=function(t){t=t||{},this.innerFill=!!t.innerFill,this.outerFill=!!t.outerFill,this.innerColor=(t.innerColor||[0,0,0,.5]).slice(),this.outerColor=(t.outerColor||[0,0,0,.5]).slice(),this.borderColor=(t.borderColor||[0,0,0,1]).slice(),this.borderWidth=t.borderWidth||0,this.selectBox=(t.selectBox||this.selectBox).slice()},s.dispose=function(){this.boxBuffer.dispose(),this.boxShader.dispose(),this.plot.removeOverlay(this)}},{\"./lib/shaders\":335,\"gl-buffer\":267,\"gl-shader\":339}],338:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r=e[0],a=e[1],o=n(t,r,a,{}),s=i.mallocUint8(r*a*4);return new l(t,o,s)};var n=t(\"gl-fbo\"),i=t(\"typedarray-pool\"),a=t(\"ndarray\"),o=t(\"bit-twiddle\").nextPow2;function s(t,e,r,n,i){this.coord=[t,e],this.id=r,this.value=n,this.distance=i}function 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a=[t.id,e.id,r.join(\":\"),i.join(\":\")].join(\"@\"),o=this.programs[a];return o&&this.gl.isProgram(o)||(this.programs[a]=o=function(t,e,r,i,a){var o=t.createProgram();t.attachShader(o,e),t.attachShader(o,r);for(var s=0;s<i.length;++s)t.bindAttribLocation(o,a[s],i[s]);if(t.linkProgram(o),!t.getProgramParameter(o,t.LINK_STATUS)){var l=t.getProgramInfoLog(o);throw new n(l,\"Error linking program: \"+l)}return o}(this.gl,t.shader,e.shader,r,i),t.programs.push(a),e.programs.push(a)),o}},{\"./GLError\":340,\"gl-format-compiler-error\":277,\"weakmap-shim\":628}],346:[function(t,e,r){\"use strict\";function n(t){this.plot=t,this.enable=[!0,!0,!1,!1],this.width=[1,1,1,1],this.color=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.center=[1/0,1/0]}e.exports=function(t,e){var r=new n(t);return r.update(e),t.addOverlay(r),r};var 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1\\n\\nattribute vec3 position, color;\\nattribute float weight;\\n\\nuniform mat4 model, view, projection;\\nuniform vec3 coordinates[3];\\nuniform vec4 colors[3];\\nuniform vec2 screenShape;\\nuniform float lineWidth;\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  vec3 vertexPosition = mix(coordinates[0],\\n    mix(coordinates[2], coordinates[1], 0.5 * (position + 1.0)), abs(position));\\n\\n  vec4 clipPos = projection * view * model * vec4(vertexPosition, 1.0);\\n  vec2 clipOffset = (projection * view * model * vec4(color, 0.0)).xy;\\n  vec2 delta = weight * clipOffset * screenShape;\\n  vec2 lineOffset = normalize(vec2(delta.y, -delta.x)) / screenShape;\\n\\n  gl_Position   = vec4(clipPos.xy + clipPos.w * 0.5 * lineWidth * lineOffset, clipPos.z, clipPos.w);\\n  fragColor     = color.x * colors[0] + color.y * colors[1] + color.z * colors[2];\\n}\\n\"]),o=n([\"precision mediump float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n  gl_FragColor = fragColor;\\n}\"]);e.exports=function(t){return i(t,a,o,null,[{name:\"position\",type:\"vec3\"},{name:\"color\",type:\"vec3\"},{name:\"weight\",type:\"float\"}])}},{\"gl-shader\":339,glslify:347}],349:[function(t,e,r){\"use strict\";var n=t(\"gl-buffer\"),i=t(\"gl-vao\"),a=t(\"./shaders/index\");e.exports=function(t,e){var r=[];function o(t,e,n,i,a,o){var s=[t,e,n,0,0,0,1];s[i+3]=1,s[i]=a,r.push.apply(r,s),s[6]=-1,r.push.apply(r,s),s[i]=o,r.push.apply(r,s),r.push.apply(r,s),s[6]=1,r.push.apply(r,s),s[i]=a,r.push.apply(r,s)}o(0,0,0,0,0,1),o(0,0,0,1,0,1),o(0,0,0,2,0,1),o(1,0,0,1,-1,1),o(1,0,0,2,-1,1),o(0,1,0,0,-1,1),o(0,1,0,2,-1,1),o(0,0,1,0,-1,1),o(0,0,1,1,-1,1);var l=n(t,r),c=i(t,[{type:t.FLOAT,buffer:l,size:3,offset:0,stride:28},{type:t.FLOAT,buffer:l,size:3,offset:12,stride:28},{type:t.FLOAT,buffer:l,size:1,offset:24,stride:28}]),u=a(t);u.attributes.position.location=0,u.attributes.color.location=1,u.attributes.weight.location=2;var f=new s(t,l,c,u);return f.update(e),f};var o=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function s(t,e,r,n){this.gl=t,this.buffer=e,this.vao=r,this.shader=n,this.pixelRatio=1,this.bounds=[[-1e3,-1e3,-1e3],[1e3,1e3,1e3]],this.position=[0,0,0],this.lineWidth=[2,2,2],this.colors=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.enabled=[!0,!0,!0],this.drawSides=[!0,!0,!0],this.axes=null}var l=s.prototype,c=[0,0,0],u=[0,0,0],f=[0,0];l.isTransparent=function(){return!1},l.drawTransparent=function(t){},l.draw=function(t){var e=this.gl,r=this.vao,n=this.shader;r.bind(),n.bind();var i,a=t.model||o,s=t.view||o,l=t.projection||o;this.axes&&(i=this.axes.lastCubeProps.axis);for(var h=c,p=u,d=0;d<3;++d)i&&i[d]<0?(h[d]=this.bounds[0][d],p[d]=this.bounds[1][d]):(h[d]=this.bounds[1][d],p[d]=this.bounds[0][d]);f[0]=e.drawingBufferWidth,f[1]=e.drawingBufferHeight,n.uniforms.model=a,n.uniforms.view=s,n.uniforms.projection=l,n.uniforms.coordinates=[this.position,h,p],n.uniforms.colors=this.colors,n.uniforms.screenShape=f;for(d=0;d<3;++d)n.uniforms.lineWidth=this.lineWidth[d]*this.pixelRatio,this.enabled[d]&&(r.draw(e.TRIANGLES,6,6*d),this.drawSides[d]&&r.draw(e.TRIANGLES,12,18+12*d));r.unbind()},l.update=function(t){t&&(\"bounds\"in t&&(this.bounds=t.bounds),\"position\"in t&&(this.position=t.position),\"lineWidth\"in t&&(this.lineWidth=t.lineWidth),\"colors\"in t&&(this.colors=t.colors),\"enabled\"in t&&(this.enabled=t.enabled),\"drawSides\"in t&&(this.drawSides=t.drawSides))},l.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()}},{\"./shaders/index\":348,\"gl-buffer\":267,\"gl-vao\":361}],350:[function(t,e,r){var n=t(\"glslify\"),i=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the tube vertex and normal at the given index.\\n//\\n// The returned vertex is for a tube ring with its center at origin, radius of length(d), pointing in the direction of d.\\n//\\n// Each tube segment is made up of a ring of vertices.\\n// These vertices are used to make up the triangles of the tube by connecting them together in the vertex array.\\n// The indexes of tube segments run from 0 to 8.\\n//\\nvec3 getTubePosition(vec3 d, float index, out vec3 normal) {\\n  float segmentCount = 8.0;\\n\\n  float angle = 2.0 * 3.14159 * (index / segmentCount);\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d);\\n  vec3 y = v * sin(angle) * length(d);\\n  vec3 v3 = x + y;\\n\\n  normal = normalize(v3);\\n\\n  return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 color, position;\\nattribute vec2 uv;\\n\\nuniform float vectorScale, tubeScale;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 eyePosition, lightPosition;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  // Scale the vector magnitude to stay constant with\\n  // model & view changes.\\n  vec3 normal;\\n  vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\\n  vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * tubePosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  f_lightDirection = lightPosition - cameraCoordinate.xyz;\\n  f_eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\\n\\n  // vec4 m_position  = model * vec4(tubePosition, 1.0);\\n  vec4 t_position  = view * tubePosition;\\n  gl_Position      = projection * t_position;\\n\\n  f_color          = color;\\n  f_data           = tubePosition.xyz;\\n  f_position       = position.xyz;\\n  f_uv             = uv;\\n}\\n\"]),a=n([\"#extension GL_OES_standard_derivatives : enable\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat cookTorranceSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness,\\n  float fresnel) {\\n\\n  float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\\n  float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\\n\\n  //Half angle vector\\n  vec3 H = normalize(lightDirection + viewDirection);\\n\\n  //Geometric term\\n  float NdotH = max(dot(surfaceNormal, H), 0.0);\\n  float VdotH = max(dot(viewDirection, H), 0.000001);\\n  float LdotH = max(dot(lightDirection, H), 0.000001);\\n  float G1 = (2.0 * NdotH * VdotN) / VdotH;\\n  float G2 = (2.0 * NdotH * LdotN) / LdotH;\\n  float G = min(1.0, min(G1, G2));\\n  \\n  //Distribution term\\n  float D = beckmannDistribution(NdotH, roughness);\\n\\n  //Fresnel term\\n  float F = pow(1.0 - VdotN, fresnel);\\n\\n  //Multiply terms and done\\n  return  G * F * D / max(3.14159265 * VdotN, 0.000001);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform sampler2D texture;\\n\\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\\nvarying vec4 f_color;\\nvarying vec2 f_uv;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n  vec3 N = normalize(f_normal);\\n  vec3 L = normalize(f_lightDirection);\\n  vec3 V = normalize(f_eyeDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  vec4 surfaceColor = f_color * texture2D(texture, f_uv);\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = litColor * opacity;\\n}\\n\"]),o=n([\"precision highp float;\\n\\nprecision highp float;\\n#define GLSLIFY 1\\n\\nvec3 getOrthogonalVector(vec3 v) {\\n  // Return up-vector for only-z vector.\\n  // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\\n  // From the above if-statement we have ||a|| > 0  U  ||b|| > 0.\\n  // Assign z = 0, x = -b, y = a:\\n  // a*-b + b*a + c*0 = -ba + ba + 0 = 0\\n  if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\\n    return normalize(vec3(-v.y, v.x, 0.0));\\n  } else {\\n    return normalize(vec3(0.0, v.z, -v.y));\\n  }\\n}\\n\\n// Calculate the tube vertex and normal at the given index.\\n//\\n// The returned vertex is for a tube ring with its center at origin, radius of length(d), pointing in the direction of d.\\n//\\n// Each tube segment is made up of a ring of vertices.\\n// These vertices are used to make up the triangles of the tube by connecting them together in the vertex array.\\n// The indexes of tube segments run from 0 to 8.\\n//\\nvec3 getTubePosition(vec3 d, float index, out vec3 normal) {\\n  float segmentCount = 8.0;\\n\\n  float angle = 2.0 * 3.14159 * (index / segmentCount);\\n\\n  vec3 u = getOrthogonalVector(d);\\n  vec3 v = normalize(cross(u, d));\\n\\n  vec3 x = u * cos(angle) * length(d);\\n  vec3 y = v * sin(angle) * length(d);\\n  vec3 v3 = x + y;\\n\\n  normal = normalize(v3);\\n\\n  return v3;\\n}\\n\\nattribute vec4 vector;\\nattribute vec4 position;\\nattribute vec4 id;\\n\\nuniform mat4 model, view, projection;\\nuniform float tubeScale;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  vec3 normal;\\n  vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\\n  vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\\n\\n  gl_Position = projection * view * tubePosition;\\n  f_id        = id;\\n  f_position  = position.xyz;\\n}\\n\"]),s=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3  clipBounds[2];\\nuniform float pickId;\\n\\nvarying vec3 f_position;\\nvarying vec4 f_id;\\n\\nvoid main() {\\n  if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\\n\\n  gl_FragColor = vec4(pickId, f_id.xyz);\\n}\"]);r.meshShader={vertex:i,fragment:a,attributes:[{name:\"position\",type:\"vec4\"},{name:\"color\",type:\"vec4\"},{name:\"uv\",type:\"vec2\"},{name:\"vector\",type:\"vec4\"}]},r.pickShader={vertex:o,fragment:s,attributes:[{name:\"position\",type:\"vec4\"},{name:\"id\",type:\"vec4\"},{name:\"vector\",type:\"vec4\"}]}},{glslify:351}],351:[function(t,e,r){arguments[4][265][0].apply(r,arguments)},{dup:265}],352:[function(t,e,r){\"use strict\";var n=t(\"gl-vec3\"),i=t(\"gl-vec4\"),a=[\"xyz\",\"xzy\",\"yxz\",\"yzx\",\"zxy\",\"zyx\"],o=function(t,e,r,a){for(var o=0,s=0;s<t.length;s++)for(var l=t[s].velocities,c=0;c<l.length;c++)o=Math.max(o,n.length(l[c]));var u=t.map((function(t){return function(t,e,r,a){for(var o=t.points,s=t.velocities,l=t.divergences,c=[],u=[],f=[],h=[],p=[],d=[],g=0,m=0,v=i.create(),y=i.create(),x=0;x<o.length;x++){var b=o[x],_=s[x],w=l[x];0===e&&(w=.05*r),m=n.length(_)/a,v=i.create(),n.copy(v,_),v[3]=w;for(var T=0;T<8;T++)p[T]=[b[0],b[1],b[2],T];if(h.length>0)for(T=0;T<8;T++){var k=(T+1)%8;c.push(h[T],p[T],p[k],p[k],h[k],h[T]),f.push(y,v,v,v,y,y),d.push(g,m,m,m,g,g);var A=c.length;u.push([A-6,A-5,A-4],[A-3,A-2,A-1])}var M=h;h=p,p=M;var S=y;y=v,v=S;var E=g;g=m,m=E}return{positions:c,cells:u,vectors:f,vertexIntensity:d}}(t,r,a,o)})),f=[],h=[],p=[],d=[];for(s=0;s<u.length;s++){var g=u[s],m=f.length;f=f.concat(g.positions),p=p.concat(g.vectors),d=d.concat(g.vertexIntensity);for(c=0;c<g.cells.length;c++){var v=g.cells[c],y=[];h.push(y);for(var x=0;x<v.length;x++)y.push(v[x]+m)}}return{positions:f,cells:h,vectors:p,vertexIntensity:d,colormap:e}},s=function(t,e){var r,n=t.length;for(r=0;r<n;r++){var i=t[r];if(i===e)return r;if(i>e)return r-1}return r},l=function(t,e,r){return t<e?e:t>r?r:t},c=function(t){var e=1/0;t.sort((function(t,e){return t-e}));for(var r=t.length,n=1;n<r;n++){var i=Math.abs(t[n]-t[n-1]);i<e&&(e=i)}return e};e.exports=function(t,e){var r=t.startingPositions,i=t.maxLength||1e3,u=t.tubeSize||1,f=t.absoluteTubeSize,h=t.gridFill||\"+x+y+z\",p={};-1!==h.indexOf(\"-x\")&&(p.reversedX=!0),-1!==h.indexOf(\"-y\")&&(p.reversedY=!0),-1!==h.indexOf(\"-z\")&&(p.reversedZ=!0),p.filled=a.indexOf(h.replace(/-/g,\"\").replace(/\\+/g,\"\"));var d=t.getVelocity||function(e){return function(t,e,r){var i=e.vectors,a=e.meshgrid,o=t[0],c=t[1],u=t[2],f=a[0].length,h=a[1].length,p=a[2].length,d=s(a[0],o),g=s(a[1],c),m=s(a[2],u),v=d+1,y=g+1,x=m+1;if(d=l(d,0,f-1),v=l(v,0,f-1),g=l(g,0,h-1),y=l(y,0,h-1),m=l(m,0,p-1),x=l(x,0,p-1),d<0||g<0||m<0||v>f-1||y>h-1||x>p-1)return n.create();var b,_,w,T,k,A,M=a[0][d],S=a[0][v],E=a[1][g],L=a[1][y],C=a[2][m],P=(o-M)/(S-M),I=(c-E)/(L-E),O=(u-C)/(a[2][x]-C);switch(isFinite(P)||(P=.5),isFinite(I)||(I=.5),isFinite(O)||(O=.5),r.reversedX&&(d=f-1-d,v=f-1-v),r.reversedY&&(g=h-1-g,y=h-1-y),r.reversedZ&&(m=p-1-m,x=p-1-x),r.filled){case 5:k=m,A=x,w=g*p,T=y*p,b=d*p*h,_=v*p*h;break;case 4:k=m,A=x,b=d*p,_=v*p,w=g*p*f,T=y*p*f;break;case 3:w=g,T=y,k=m*h,A=x*h,b=d*h*p,_=v*h*p;break;case 2:w=g,T=y,b=d*h,_=v*h,k=m*h*f,A=x*h*f;break;case 1:b=d,_=v,k=m*f,A=x*f,w=g*f*p,T=y*f*p;break;default:b=d,_=v,w=g*f,T=y*f,k=m*f*h,A=x*f*h}var z=i[b+w+k],D=i[b+w+A],R=i[b+T+k],F=i[b+T+A],B=i[_+w+k],N=i[_+w+A],j=i[_+T+k],U=i[_+T+A],V=n.create(),q=n.create(),H=n.create(),G=n.create();n.lerp(V,z,B,P),n.lerp(q,D,N,P),n.lerp(H,R,j,P),n.lerp(G,F,U,P);var Y=n.create(),W=n.create();n.lerp(Y,V,H,I),n.lerp(W,q,G,I);var X=n.create();return n.lerp(X,Y,W,O),X}(e,t,p)},g=t.getDivergence||function(t,e){var r=n.create(),i=1e-4;n.add(r,t,[i,0,0]);var a=d(r);n.subtract(a,a,e),n.scale(a,a,1/i),n.add(r,t,[0,i,0]);var o=d(r);n.subtract(o,o,e),n.scale(o,o,1/i),n.add(r,t,[0,0,i]);var s=d(r);return n.subtract(s,s,e),n.scale(s,s,1/i),n.add(r,a,o),n.add(r,r,s),r},m=[],v=e[0][0],y=e[0][1],x=e[0][2],b=e[1][0],_=e[1][1],w=e[1][2],T=function(t){var e=t[0],r=t[1],n=t[2];return!(e<v||e>b||r<y||r>_||n<x||n>w)},k=10*n.distance(e[0],e[1])/i,A=k*k,M=1,S=0,E=r.length;E>1&&(M=function(t){for(var e=[],r=[],n=[],i={},a={},o={},s=t.length,l=0;l<s;l++){var u=t[l],f=u[0],h=u[1],p=u[2];i[f]||(e.push(f),i[f]=!0),a[h]||(r.push(h),a[h]=!0),o[p]||(n.push(p),o[p]=!0)}var d=c(e),g=c(r),m=c(n),v=Math.min(d,g,m);return isFinite(v)?v:1}(r));for(var L=0;L<E;L++){var C=n.create();n.copy(C,r[L]);var P=[C],I=[],O=d(C),z=C;I.push(O);var D=[],R=g(C,O),F=n.length(R);isFinite(F)&&F>S&&(S=F),D.push(F),m.push({points:P,velocities:I,divergences:D});for(var B=0;B<100*i&&P.length<i&&T(C);){B++;var N=n.clone(O),j=n.squaredLength(N);if(0===j)break;if(j>A&&n.scale(N,N,k/Math.sqrt(j)),n.add(N,N,C),O=d(N),n.squaredDistance(z,N)-A>-1e-4*A){P.push(N),z=N,I.push(O);R=g(N,O),F=n.length(R);isFinite(F)&&F>S&&(S=F),D.push(F)}C=N}}var U=o(m,t.colormap,S,M);return f?U.tubeScale=f:(0===S&&(S=1),U.tubeScale=.5*u*M/S),U};var u=t(\"./lib/shaders\"),f=t(\"gl-cone3d\").createMesh;e.exports.createTubeMesh=function(t,e){return f(t,e,{shaders:u,traceType:\"streamtube\"})}},{\"./lib/shaders\":350,\"gl-cone3d\":268,\"gl-vec3\":380,\"gl-vec4\":416}],353:[function(t,e,r){var n=t(\"gl-shader\"),i=t(\"glslify\"),a=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec4 uv;\\nattribute vec3 f;\\nattribute vec3 normal;\\n\\nuniform vec3 objectOffset;\\nuniform mat4 model, view, projection, inverseModel;\\nuniform vec3 lightPosition, eyePosition;\\nuniform sampler2D colormap;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n  vec3 localCoordinate = vec3(uv.zw, f.x);\\n  worldCoordinate = objectOffset + localCoordinate;\\n  vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\\n  vec4 clipPosition = projection * view * worldPosition;\\n  gl_Position = clipPosition;\\n  kill = f.y;\\n  value = f.z;\\n  planeCoordinate = uv.xy;\\n\\n  vColor = texture2D(colormap, vec2(value, value));\\n\\n  //Lighting geometry parameters\\n  vec4 cameraCoordinate = view * worldPosition;\\n  cameraCoordinate.xyz /= cameraCoordinate.w;\\n  lightDirection = lightPosition - cameraCoordinate.xyz;\\n  eyeDirection   = eyePosition - cameraCoordinate.xyz;\\n  surfaceNormal  = normalize((vec4(normal,0) * inverseModel).xyz);\\n}\\n\"]),o=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nfloat beckmannDistribution(float x, float roughness) {\\n  float NdotH = max(x, 0.0001);\\n  float cos2Alpha = NdotH * NdotH;\\n  float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\\n  float roughness2 = roughness * roughness;\\n  float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\\n  return exp(tan2Alpha / roughness2) / denom;\\n}\\n\\nfloat beckmannSpecular(\\n  vec3 lightDirection,\\n  vec3 viewDirection,\\n  vec3 surfaceNormal,\\n  float roughness) {\\n  return beckmannDistribution(dot(surfaceNormal, normalize(lightDirection + viewDirection)), roughness);\\n}\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec3 lowerBound, upperBound;\\nuniform float contourTint;\\nuniform vec4 contourColor;\\nuniform sampler2D colormap;\\nuniform vec3 clipBounds[2];\\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\\nuniform float vertexColor;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n  if (\\n    kill > 0.0 ||\\n    vColor.a == 0.0 ||\\n    outOfRange(clipBounds[0], clipBounds[1], worldCoordinate)\\n  ) discard;\\n\\n  vec3 N = normalize(surfaceNormal);\\n  vec3 V = normalize(eyeDirection);\\n  vec3 L = normalize(lightDirection);\\n\\n  if(gl_FrontFacing) {\\n    N = -N;\\n  }\\n\\n  float specular = max(beckmannSpecular(L, V, N, roughness), 0.);\\n  float diffuse  = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\\n\\n  //decide how to interpolate color \\u2014 in vertex or in fragment\\n  vec4 surfaceColor =\\n    step(vertexColor, .5) * texture2D(colormap, vec2(value, value)) +\\n    step(.5, vertexColor) * vColor;\\n\\n  vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular,  1.0);\\n\\n  gl_FragColor = mix(litColor, contourColor, contourTint) * opacity;\\n}\\n\"]),s=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec4 uv;\\nattribute float f;\\n\\nuniform vec3 objectOffset;\\nuniform mat3 permutation;\\nuniform mat4 model, view, projection;\\nuniform float height, zOffset;\\nuniform sampler2D colormap;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\\nvarying vec4 vColor;\\n\\nvoid main() {\\n  vec3 dataCoordinate = permutation * vec3(uv.xy, height);\\n  worldCoordinate = objectOffset + dataCoordinate;\\n  vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\\n\\n  vec4 clipPosition = projection * view * worldPosition;\\n  clipPosition.z += zOffset;\\n\\n  gl_Position = clipPosition;\\n  value = f + objectOffset.z;\\n  kill = -1.0;\\n  planeCoordinate = uv.zw;\\n\\n  vColor = texture2D(colormap, vec2(value, value));\\n\\n  //Don't do lighting for contours\\n  surfaceNormal   = vec3(1,0,0);\\n  eyeDirection    = vec3(0,1,0);\\n  lightDirection  = vec3(0,0,1);\\n}\\n\"]),l=i([\"precision highp float;\\n#define GLSLIFY 1\\n\\nbool outOfRange(float a, float b, float p) {\\n  return ((p > max(a, b)) || \\n          (p < min(a, b)));\\n}\\n\\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y));\\n}\\n\\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\\n  return (outOfRange(a.x, b.x, p.x) ||\\n          outOfRange(a.y, b.y, p.y) ||\\n          outOfRange(a.z, b.z, p.z));\\n}\\n\\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\\n  return outOfRange(a.xyz, b.xyz, p.xyz);\\n}\\n\\nuniform vec2 shape;\\nuniform vec3 clipBounds[2];\\nuniform float pickId;\\n\\nvarying float value, kill;\\nvarying vec3 worldCoordinate;\\nvarying vec2 planeCoordinate;\\nvarying vec3 surfaceNormal;\\n\\nvec2 splitFloat(float v) {\\n  float vh = 255.0 * v;\\n  float upper = floor(vh);\\n  float lower = fract(vh);\\n  return vec2(upper / 255.0, floor(lower * 16.0) / 16.0);\\n}\\n\\nvoid main() {\\n  if ((kill > 0.0) ||\\n      (outOfRange(clipBounds[0], clipBounds[1], worldCoordinate))) discard;\\n\\n  vec2 ux = splitFloat(planeCoordinate.x / shape.x);\\n  vec2 uy = splitFloat(planeCoordinate.y / shape.y);\\n  gl_FragColor = vec4(pickId, ux.x, uy.x, ux.y + (uy.y/16.0));\\n}\\n\"]);r.createShader=function(t){var e=n(t,a,o,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createPickShader=function(t){var e=n(t,a,l,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"vec3\"},{name:\"normal\",type:\"vec3\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createContourShader=function(t){var e=n(t,s,o,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e},r.createPickContourShader=function(t){var e=n(t,s,l,null,[{name:\"uv\",type:\"vec4\"},{name:\"f\",type:\"float\"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e}},{\"gl-shader\":339,glslify:442}],354:[function(t,e,r){\"use strict\";e.exports=function(t){var e=t.gl,r=y(e),n=b(e),s=x(e),l=_(e),c=i(e),u=a(e,[{buffer:c,size:4,stride:40,offset:0},{buffer:c,size:3,stride:40,offset:16},{buffer:c,size:3,stride:40,offset:28}]),f=i(e),h=a(e,[{buffer:f,size:4,stride:20,offset:0},{buffer:f,size:1,stride:20,offset:16}]),p=i(e),d=a(e,[{buffer:p,size:2,type:e.FLOAT}]),g=o(e,1,256,e.RGBA,e.UNSIGNED_BYTE);g.minFilter=e.LINEAR,g.magFilter=e.LINEAR;var m=new M(e,[0,0],[[0,0,0],[0,0,0]],r,n,c,u,g,s,l,f,h,p,d,[0,0,0]),v={levels:[[],[],[]]};for(var w in t)v[w]=t[w];return v.colormap=v.colormap||\"jet\",m.update(v),m};var n=t(\"bit-twiddle\"),i=t(\"gl-buffer\"),a=t(\"gl-vao\"),o=t(\"gl-texture2d\"),s=t(\"typedarray-pool\"),l=t(\"colormap\"),c=t(\"ndarray-ops\"),u=t(\"ndarray-pack\"),f=t(\"ndarray\"),h=t(\"surface-nets\"),p=t(\"gl-mat4/multiply\"),d=t(\"gl-mat4/invert\"),g=t(\"binary-search-bounds\"),m=t(\"ndarray-gradient\"),v=t(\"./lib/shaders\"),y=v.createShader,x=v.createContourShader,b=v.createPickShader,_=v.createPickContourShader,w=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],T=[[0,0],[0,1],[1,0],[1,1],[1,0],[0,1]],k=[[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0]];function A(t,e,r,n,i){this.position=t,this.index=e,this.uv=r,this.level=n,this.dataCoordinate=i}!function(){for(var t=0;t<3;++t){var e=k[t],r=(t+2)%3;e[(t+1)%3+0]=1,e[r+3]=1,e[t+6]=1}}();function M(t,e,r,n,i,a,o,l,c,u,h,p,d,g,m){this.gl=t,this.shape=e,this.bounds=r,this.objectOffset=m,this.intensityBounds=[],this._shader=n,this._pickShader=i,this._coordinateBuffer=a,this._vao=o,this._colorMap=l,this._contourShader=c,this._contourPickShader=u,this._contourBuffer=h,this._contourVAO=p,this._contourOffsets=[[],[],[]],this._contourCounts=[[],[],[]],this._vertexCount=0,this._pickResult=new A([0,0,0],[0,0],[0,0],[0,0,0],[0,0,0]),this._dynamicBuffer=d,this._dynamicVAO=g,this._dynamicOffsets=[0,0,0],this._dynamicCounts=[0,0,0],this.contourWidth=[1,1,1],this.contourLevels=[[1],[1],[1]],this.contourTint=[0,0,0],this.contourColor=[[.5,.5,.5,1],[.5,.5,.5,1],[.5,.5,.5,1]],this.showContour=!0,this.showSurface=!0,this.enableHighlight=[!0,!0,!0],this.highlightColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.highlightTint=[1,1,1],this.highlightLevel=[-1,-1,-1],this.enableDynamic=[!0,!0,!0],this.dynamicLevel=[NaN,NaN,NaN],this.dynamicColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.dynamicTint=[1,1,1],this.dynamicWidth=[1,1,1],this.axesBounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.surfaceProject=[!1,!1,!1],this.contourProject=[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],this.colorBounds=[!1,!1],this._field=[f(s.mallocFloat(1024),[0,0]),f(s.mallocFloat(1024),[0,0]),f(s.mallocFloat(1024),[0,0])],this.pickId=1,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.snapToData=!1,this.pixelRatio=1,this.opacity=1,this.lightPosition=[10,1e4,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.vertexColor=0,this.dirty=!0}var S=M.prototype;S.genColormap=function(t,e){var r=!1,n=u([l({colormap:t,nshades:256,format:\"rgba\"}).map((function(t,n){var i=e?function(t,e){if(!e)return 1;if(!e.length)return 1;for(var r=0;r<e.length;++r){if(e.length<2)return 1;if(e[r][0]===t)return e[r][1];if(e[r][0]>t&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}(n/255,e):t[3];return i<1&&(r=!0),[t[0],t[1],t[2],255*i]}))]);return c.divseq(n,255),this.hasAlphaScale=r,n},S.isTransparent=function(){return this.opacity<1||this.hasAlphaScale},S.isOpaque=function(){return!this.isTransparent()},S.pickSlots=1,S.setPickBase=function(t){this.pickId=t};var E=[0,0,0],L={showSurface:!1,showContour:!1,projections:[w.slice(),w.slice(),w.slice()],clipBounds:[[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]]]};function C(t,e){var r,n,i,a=e.axes&&e.axes.lastCubeProps.axis||E,o=e.showSurface,s=e.showContour;for(r=0;r<3;++r)for(o=o||e.surfaceProject[r],n=0;n<3;++n)s=s||e.contourProject[r][n];for(r=0;r<3;++r){var l=L.projections[r];for(n=0;n<16;++n)l[n]=0;for(n=0;n<4;++n)l[5*n]=1;l[5*r]=0,l[12+r]=e.axesBounds[+(a[r]>0)][r],p(l,t.model,l);var c=L.clipBounds[r];for(i=0;i<2;++i)for(n=0;n<3;++n)c[i][n]=t.clipBounds[i][n];c[0][r]=-1e8,c[1][r]=1e8}return L.showSurface=o,L.showContour=s,L}var P={model:w,view:w,projection:w,inverseModel:w.slice(),lowerBound:[0,0,0],upperBound:[0,0,0],colorMap:0,clipBounds:[[0,0,0],[0,0,0]],height:0,contourTint:0,contourColor:[0,0,0,1],permutation:[1,0,0,0,1,0,0,0,1],zOffset:-1e-4,objectOffset:[0,0,0],kambient:1,kdiffuse:1,kspecular:1,lightPosition:[1e3,1e3,1e3],eyePosition:[0,0,0],roughness:1,fresnel:1,opacity:1,vertexColor:0},I=w.slice(),O=[1,0,0,0,1,0,0,0,1];function z(t,e){t=t||{};var r=this.gl;r.disable(r.CULL_FACE),this._colorMap.bind(0);var n=P;n.model=t.model||w,n.view=t.view||w,n.projection=t.projection||w,n.lowerBound=[this.bounds[0][0],this.bounds[0][1],this.colorBounds[0]||this.bounds[0][2]],n.upperBound=[this.bounds[1][0],this.bounds[1][1],this.colorBounds[1]||this.bounds[1][2]],n.objectOffset=this.objectOffset,n.contourColor=this.contourColor[0],n.inverseModel=d(n.inverseModel,n.model);for(var i=0;i<2;++i)for(var a=n.clipBounds[i],o=0;o<3;++o)a[o]=Math.min(Math.max(this.clipBounds[i][o],-1e8),1e8);n.kambient=this.ambientLight,n.kdiffuse=this.diffuseLight,n.kspecular=this.specularLight,n.roughness=this.roughness,n.fresnel=this.fresnel,n.opacity=this.opacity,n.height=0,n.permutation=O,n.vertexColor=this.vertexColor;var s=I;for(p(s,n.view,n.model),p(s,n.projection,s),d(s,s),i=0;i<3;++i)n.eyePosition[i]=s[12+i]/s[15];var l=s[15];for(i=0;i<3;++i)l+=this.lightPosition[i]*s[4*i+3];for(i=0;i<3;++i){var c=s[12+i];for(o=0;o<3;++o)c+=s[4*o+i]*this.lightPosition[o];n.lightPosition[i]=c/l}var u=C(n,this);if(u.showSurface){for(this._shader.bind(),this._shader.uniforms=n,this._vao.bind(),this.showSurface&&this._vertexCount&&this._vao.draw(r.TRIANGLES,this._vertexCount),i=0;i<3;++i)this.surfaceProject[i]&&this.vertexCount&&(this._shader.uniforms.model=u.projections[i],this._shader.uniforms.clipBounds=u.clipBounds[i],this._vao.draw(r.TRIANGLES,this._vertexCount));this._vao.unbind()}if(u.showContour){var f=this._contourShader;n.kambient=1,n.kdiffuse=0,n.kspecular=0,n.opacity=1,f.bind(),f.uniforms=n;var h=this._contourVAO;for(h.bind(),i=0;i<3;++i)for(f.uniforms.permutation=k[i],r.lineWidth(this.contourWidth[i]*this.pixelRatio),o=0;o<this.contourLevels[i].length;++o)o===this.highlightLevel[i]?(f.uniforms.contourColor=this.highlightColor[i],f.uniforms.contourTint=this.highlightTint[i]):0!==o&&o-1!==this.highlightLevel[i]||(f.uniforms.contourColor=this.contourColor[i],f.uniforms.contourTint=this.contourTint[i]),this._contourCounts[i][o]&&(f.uniforms.height=this.contourLevels[i][o],h.draw(r.LINES,this._contourCounts[i][o],this._contourOffsets[i][o]));for(i=0;i<3;++i)for(f.uniforms.model=u.projections[i],f.uniforms.clipBounds=u.clipBounds[i],o=0;o<3;++o)if(this.contourProject[i][o]){f.uniforms.permutation=k[o],r.lineWidth(this.contourWidth[o]*this.pixelRatio);for(var g=0;g<this.contourLevels[o].length;++g)g===this.highlightLevel[o]?(f.uniforms.contourColor=this.highlightColor[o],f.uniforms.contourTint=this.highlightTint[o]):0!==g&&g-1!==this.highlightLevel[o]||(f.uniforms.contourColor=this.contourColor[o],f.uniforms.contourTint=this.contourTint[o]),this._contourCounts[o][g]&&(f.uniforms.height=this.contourLevels[o][g],h.draw(r.LINES,this._contourCounts[o][g],this._contourOffsets[o][g]))}for(h.unbind(),(h=this._dynamicVAO).bind(),i=0;i<3;++i)if(0!==this._dynamicCounts[i])for(f.uniforms.model=n.model,f.uniforms.clipBounds=n.clipBounds,f.uniforms.permutation=k[i],r.lineWidth(this.dynamicWidth[i]*this.pixelRatio),f.uniforms.contourColor=this.dynamicColor[i],f.uniforms.contourTint=this.dynamicTint[i],f.uniforms.height=this.dynamicLevel[i],h.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]),o=0;o<3;++o)this.contourProject[o][i]&&(f.uniforms.model=u.projections[o],f.uniforms.clipBounds=u.clipBounds[o],h.draw(r.LINES,this._dynamicCounts[i],this._dynamicOffsets[i]));h.unbind()}}S.draw=function(t){return z.call(this,t,!1)},S.drawTransparent=function(t){return z.call(this,t,!0)};var D={model:w,view:w,projection:w,inverseModel:w,clipBounds:[[0,0,0],[0,0,0]],height:0,shape:[0,0],pickId:0,lowerBound:[0,0,0],upperBound:[0,0,0],zOffset:0,objectOffset:[0,0,0],permutation:[1,0,0,0,1,0,0,0,1],lightPosition:[0,0,0],eyePosition:[0,0,0]};function R(t,e){return Array.isArray(t)?[e(t[0]),e(t[1]),e(t[2])]:[e(t),e(t),e(t)]}function F(t){return Array.isArray(t)?3===t.length?[t[0],t[1],t[2],1]:[t[0],t[1],t[2],t[3]]:[0,0,0,1]}function B(t){if(Array.isArray(t)){if(Array.isArray(t))return[F(t[0]),F(t[1]),F(t[2])];var e=F(t);return[e.slice(),e.slice(),e.slice()]}}S.drawPick=function(t){t=t||{};var e=this.gl;e.disable(e.CULL_FACE);var r=D;r.model=t.model||w,r.view=t.view||w,r.projection=t.projection||w,r.shape=this._field[2].shape,r.pickId=this.pickId/255,r.lowerBound=this.bounds[0],r.upperBound=this.bounds[1],r.objectOffset=this.objectOffset,r.permutation=O;for(var n=0;n<2;++n)for(var i=r.clipBounds[n],a=0;a<3;++a)i[a]=Math.min(Math.max(this.clipBounds[n][a],-1e8),1e8);var o=C(r,this);if(o.showSurface){for(this._pickShader.bind(),this._pickShader.uniforms=r,this._vao.bind(),this._vao.draw(e.TRIANGLES,this._vertexCount),n=0;n<3;++n)this.surfaceProject[n]&&(this._pickShader.uniforms.model=o.projections[n],this._pickShader.uniforms.clipBounds=o.clipBounds[n],this._vao.draw(e.TRIANGLES,this._vertexCount));this._vao.unbind()}if(o.showContour){var s=this._contourPickShader;s.bind(),s.uniforms=r;var l=this._contourVAO;for(l.bind(),a=0;a<3;++a)for(e.lineWidth(this.contourWidth[a]*this.pixelRatio),s.uniforms.permutation=k[a],n=0;n<this.contourLevels[a].length;++n)this._contourCounts[a][n]&&(s.uniforms.height=this.contourLevels[a][n],l.draw(e.LINES,this._contourCounts[a][n],this._contourOffsets[a][n]));for(n=0;n<3;++n)for(s.uniforms.model=o.projections[n],s.uniforms.clipBounds=o.clipBounds[n],a=0;a<3;++a)if(this.contourProject[n][a]){s.uniforms.permutation=k[a],e.lineWidth(this.contourWidth[a]*this.pixelRatio);for(var c=0;c<this.contourLevels[a].length;++c)this._contourCounts[a][c]&&(s.uniforms.height=this.contourLevels[a][c],l.draw(e.LINES,this._contourCounts[a][c],this._contourOffsets[a][c]))}l.unbind()}},S.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=this._field[2].shape,r=this._pickResult,n=e[0]*(t.value[0]+(t.value[2]>>4)/16)/255,i=Math.floor(n),a=n-i,o=e[1]*(t.value[1]+(15&t.value[2])/16)/255,s=Math.floor(o),l=o-s;i+=1,s+=1;var c=r.position;c[0]=c[1]=c[2]=0;for(var u=0;u<2;++u)for(var f=u?a:1-a,h=0;h<2;++h)for(var p=i+u,d=s+h,m=f*(h?l:1-l),v=0;v<3;++v)c[v]+=this._field[v].get(p,d)*m;for(var y=this._pickResult.level,x=0;x<3;++x)if(y[x]=g.le(this.contourLevels[x],c[x]),y[x]<0)this.contourLevels[x].length>0&&(y[x]=0);else if(y[x]<this.contourLevels[x].length-1){var b=this.contourLevels[x][y[x]],_=this.contourLevels[x][y[x]+1];Math.abs(b-c[x])>Math.abs(_-c[x])&&(y[x]+=1)}for(r.index[0]=a<.5?i:i+1,r.index[1]=l<.5?s:s+1,r.uv[0]=n/e[0],r.uv[1]=o/e[1],v=0;v<3;++v)r.dataCoordinate[v]=this._field[v].get(r.index[0],r.index[1]);return r},S.padField=function(t,e){var r=e.shape.slice(),n=t.shape.slice();c.assign(t.lo(1,1).hi(r[0],r[1]),e),c.assign(t.lo(1).hi(r[0],1),e.hi(r[0],1)),c.assign(t.lo(1,n[1]-1).hi(r[0],1),e.lo(0,r[1]-1).hi(r[0],1)),c.assign(t.lo(0,1).hi(1,r[1]),e.hi(1)),c.assign(t.lo(n[0]-1,1).hi(1,r[1]),e.lo(r[0]-1)),t.set(0,0,e.get(0,0)),t.set(0,n[1]-1,e.get(0,r[1]-1)),t.set(n[0]-1,0,e.get(r[0]-1,0)),t.set(n[0]-1,n[1]-1,e.get(r[0]-1,r[1]-1))},S.update=function(t){t=t||{},this.objectOffset=t.objectOffset||this.objectOffset,this.dirty=!0,\"contourWidth\"in t&&(this.contourWidth=R(t.contourWidth,Number)),\"showContour\"in t&&(this.showContour=R(t.showContour,Boolean)),\"showSurface\"in t&&(this.showSurface=!!t.showSurface),\"contourTint\"in t&&(this.contourTint=R(t.contourTint,Boolean)),\"contourColor\"in t&&(this.contourColor=B(t.contourColor)),\"contourProject\"in t&&(this.contourProject=R(t.contourProject,(function(t){return R(t,Boolean)}))),\"surfaceProject\"in t&&(this.surfaceProject=t.surfaceProject),\"dynamicColor\"in t&&(this.dynamicColor=B(t.dynamicColor)),\"dynamicTint\"in t&&(this.dynamicTint=R(t.dynamicTint,Number)),\"dynamicWidth\"in t&&(this.dynamicWidth=R(t.dynamicWidth,Number)),\"opacity\"in t&&(this.opacity=t.opacity),\"opacityscale\"in t&&(this.opacityscale=t.opacityscale),\"colorBounds\"in t&&(this.colorBounds=t.colorBounds),\"vertexColor\"in t&&(this.vertexColor=t.vertexColor?1:0),\"colormap\"in t&&this._colorMap.setPixels(this.genColormap(t.colormap,this.opacityscale));var e=t.field||t.coords&&t.coords[2]||null,r=!1;if(e||(e=this._field[2].shape[0]||this._field[2].shape[2]?this._field[2].lo(1,1).hi(this._field[2].shape[0]-2,this._field[2].shape[1]-2):this._field[2].hi(0,0)),\"field\"in t||\"coords\"in t){var i=(e.shape[0]+2)*(e.shape[1]+2);i>this._field[2].data.length&&(s.freeFloat(this._field[2].data),this._field[2].data=s.mallocFloat(n.nextPow2(i))),this._field[2]=f(this._field[2].data,[e.shape[0]+2,e.shape[1]+2]),this.padField(this._field[2],e),this.shape=e.shape.slice();for(var a=this.shape,o=0;o<2;++o)this._field[2].size>this._field[o].data.length&&(s.freeFloat(this._field[o].data),this._field[o].data=s.mallocFloat(this._field[2].size)),this._field[o]=f(this._field[o].data,[a[0]+2,a[1]+2]);if(t.coords){var l=t.coords;if(!Array.isArray(l)||3!==l.length)throw new Error(\"gl-surface: invalid coordinates for x/y\");for(o=0;o<2;++o){var c=l[o];for(v=0;v<2;++v)if(c.shape[v]!==a[v])throw new Error(\"gl-surface: coords have incorrect shape\");this.padField(this._field[o],c)}}else if(t.ticks){var u=t.ticks;if(!Array.isArray(u)||2!==u.length)throw new Error(\"gl-surface: invalid ticks\");for(o=0;o<2;++o){var p=u[o];if((Array.isArray(p)||p.length)&&(p=f(p)),p.shape[0]!==a[o])throw new Error(\"gl-surface: invalid tick length\");var d=f(p.data,a);d.stride[o]=p.stride[0],d.stride[1^o]=0,this.padField(this._field[o],d)}}else{for(o=0;o<2;++o){var g=[0,0];g[o]=1,this._field[o]=f(this._field[o].data,[a[0]+2,a[1]+2],g,0)}this._field[0].set(0,0,0);for(var v=0;v<a[0];++v)this._field[0].set(v+1,0,v);for(this._field[0].set(a[0]+1,0,a[0]-1),this._field[1].set(0,0,0),v=0;v<a[1];++v)this._field[1].set(0,v+1,v);this._field[1].set(0,a[1]+1,a[1]-1)}var y=this._field,x=f(s.mallocFloat(3*y[2].size*2),[3,a[0]+2,a[1]+2,2]);for(o=0;o<3;++o)m(x.pick(o),y[o],\"mirror\");var b=f(s.mallocFloat(3*y[2].size),[a[0]+2,a[1]+2,3]);for(o=0;o<a[0]+2;++o)for(v=0;v<a[1]+2;++v){var _=x.get(0,o,v,0),w=x.get(0,o,v,1),k=x.get(1,o,v,0),A=x.get(1,o,v,1),M=x.get(2,o,v,0),S=x.get(2,o,v,1),E=k*S-A*M,L=M*w-S*_,C=_*A-w*k,P=Math.sqrt(E*E+L*L+C*C);P<1e-8?(P=Math.max(Math.abs(E),Math.abs(L),Math.abs(C)))<1e-8?(C=1,L=E=0,P=1):P=1/P:P=1/Math.sqrt(P),b.set(o,v,0,E*P),b.set(o,v,1,L*P),b.set(o,v,2,C*P)}s.free(x.data);var I=[1/0,1/0,1/0],O=[-1/0,-1/0,-1/0],z=1/0,D=-1/0,F=(a[0]-1)*(a[1]-1)*6,N=s.mallocFloat(n.nextPow2(10*F)),j=0,U=0;for(o=0;o<a[0]-1;++o)t:for(v=0;v<a[1]-1;++v){for(var V=0;V<2;++V)for(var q=0;q<2;++q)for(var H=0;H<3;++H){var G=this._field[H].get(1+o+V,1+v+q);if(isNaN(G)||!isFinite(G))continue t}for(H=0;H<6;++H){var Y=o+T[H][0],W=v+T[H][1],X=this._field[0].get(Y+1,W+1),Z=this._field[1].get(Y+1,W+1);G=this._field[2].get(Y+1,W+1),E=b.get(Y+1,W+1,0),L=b.get(Y+1,W+1,1),C=b.get(Y+1,W+1,2),t.intensity&&(J=t.intensity.get(Y,W));var J=t.intensity?t.intensity.get(Y,W):G+this.objectOffset[2];N[j++]=Y,N[j++]=W,N[j++]=X,N[j++]=Z,N[j++]=G,N[j++]=0,N[j++]=J,N[j++]=E,N[j++]=L,N[j++]=C,I[0]=Math.min(I[0],X+this.objectOffset[0]),I[1]=Math.min(I[1],Z+this.objectOffset[1]),I[2]=Math.min(I[2],G+this.objectOffset[2]),z=Math.min(z,J),O[0]=Math.max(O[0],X+this.objectOffset[0]),O[1]=Math.max(O[1],Z+this.objectOffset[1]),O[2]=Math.max(O[2],G+this.objectOffset[2]),D=Math.max(D,J),U+=1}}for(t.intensityBounds&&(z=+t.intensityBounds[0],D=+t.intensityBounds[1]),o=6;o<j;o+=10)N[o]=(N[o]-z)/(D-z);this._vertexCount=U,this._coordinateBuffer.update(N.subarray(0,j)),s.freeFloat(N),s.free(b.data),this.bounds=[I,O],this.intensity=t.intensity||this._field[2],this.intensityBounds[0]===z&&this.intensityBounds[1]===D||(r=!0),this.intensityBounds=[z,D]}if(\"levels\"in t){var K=t.levels;for(K=Array.isArray(K[0])?K.slice():[[],[],K],o=0;o<3;++o)K[o]=K[o].slice(),K[o].sort((function(t,e){return t-e}));for(o=0;o<3;++o)for(v=0;v<K[o].length;++v)K[o][v]-=this.objectOffset[o];t:for(o=0;o<3;++o){if(K[o].length!==this.contourLevels[o].length){r=!0;break}for(v=0;v<K[o].length;++v)if(K[o][v]!==this.contourLevels[o][v]){r=!0;break t}}this.contourLevels=K}if(r){y=this._field,a=this.shape;for(var Q=[],$=0;$<3;++$){var tt=this.contourLevels[$],et=[],rt=[],nt=[0,0,0];for(o=0;o<tt.length;++o){var it=h(this._field[$],tt[o]);et.push(Q.length/5|0),U=0;t:for(v=0;v<it.cells.length;++v){var at=it.cells[v];for(H=0;H<2;++H){var ot=it.positions[at[H]],st=ot[0],lt=0|Math.floor(st),ct=st-lt,ut=ot[1],ft=0|Math.floor(ut),ht=ut-ft,pt=!1;e:for(var dt=0;dt<3;++dt){nt[dt]=0;var gt=($+dt+1)%3;for(V=0;V<2;++V){var mt=V?ct:1-ct;for(Y=0|Math.min(Math.max(lt+V,0),a[0]),q=0;q<2;++q){var vt=q?ht:1-ht;if(W=0|Math.min(Math.max(ft+q,0),a[1]),G=dt<2?this._field[gt].get(Y,W):(this.intensity.get(Y,W)-this.intensityBounds[0])/(this.intensityBounds[1]-this.intensityBounds[0]),!isFinite(G)||isNaN(G)){pt=!0;break e}var yt=mt*vt;nt[dt]+=yt*G}}}if(pt){if(H>0){for(var xt=0;xt<5;++xt)Q.pop();U-=1}continue t}Q.push(nt[0],nt[1],ot[0],ot[1],nt[2]),U+=1}}rt.push(U)}this._contourOffsets[$]=et,this._contourCounts[$]=rt}var bt=s.mallocFloat(Q.length);for(o=0;o<Q.length;++o)bt[o]=Q[o];this._contourBuffer.update(bt),s.freeFloat(bt)}},S.dispose=function(){this._shader.dispose(),this._vao.dispose(),this._coordinateBuffer.dispose(),this._colorMap.dispose(),this._contourBuffer.dispose(),this._contourVAO.dispose(),this._contourShader.dispose(),this._contourPickShader.dispose(),this._dynamicBuffer.dispose(),this._dynamicVAO.dispose();for(var t=0;t<3;++t)s.freeFloat(this._field[t].data)},S.highlight=function(t){var e,r;if(!t)return this._dynamicCounts=[0,0,0],this.dyanamicLevel=[NaN,NaN,NaN],void(this.highlightLevel=[-1,-1,-1]);for(e=0;e<3;++e)this.enableHighlight[e]?this.highlightLevel[e]=t.level[e]:this.highlightLevel[e]=-1;for(r=this.snapToData?t.dataCoordinate:t.position,e=0;e<3;++e)r[e]-=this.objectOffset[e];if(this.enableDynamic[0]&&r[0]!==this.dynamicLevel[0]||this.enableDynamic[1]&&r[1]!==this.dynamicLevel[1]||this.enableDynamic[2]&&r[2]!==this.dynamicLevel[2]){for(var n=0,i=this.shape,a=s.mallocFloat(12*i[0]*i[1]),o=0;o<3;++o)if(this.enableDynamic[o]){this.dynamicLevel[o]=r[o];var l=(o+1)%3,c=(o+2)%3,u=this._field[o],f=this._field[l],p=this._field[c],d=h(u,r[o]),g=d.cells,m=d.positions;for(this._dynamicOffsets[o]=n,e=0;e<g.length;++e)for(var v=g[e],y=0;y<2;++y){var x=m[v[y]],b=+x[0],_=0|b,w=0|Math.min(_+1,i[0]),T=b-_,k=1-T,A=+x[1],M=0|A,S=0|Math.min(M+1,i[1]),E=A-M,L=1-E,C=k*L,P=k*E,I=T*L,O=T*E,z=C*f.get(_,M)+P*f.get(_,S)+I*f.get(w,M)+O*f.get(w,S),D=C*p.get(_,M)+P*p.get(_,S)+I*p.get(w,M)+O*p.get(w,S);if(isNaN(z)||isNaN(D)){y&&(n-=1);break}a[2*n+0]=z,a[2*n+1]=D,n+=1}this._dynamicCounts[o]=n-this._dynamicOffsets[o]}else this.dynamicLevel[o]=NaN,this._dynamicCounts[o]=0;this._dynamicBuffer.update(a.subarray(0,2*n)),s.freeFloat(a)}}},{\"./lib/shaders\":353,\"binary-search-bounds\":103,\"bit-twiddle\":104,colormap:137,\"gl-buffer\":267,\"gl-mat4/invert\":299,\"gl-mat4/multiply\":301,\"gl-texture2d\":356,\"gl-vao\":361,ndarray:483,\"ndarray-gradient\":476,\"ndarray-ops\":478,\"ndarray-pack\":479,\"surface-nets\":591,\"typedarray-pool\":617}],355:[function(t,e,r){\"use strict\";var n=t(\"css-font\"),i=t(\"pick-by-alias\"),a=t(\"regl\"),o=t(\"gl-util/context\"),s=t(\"es6-weak-map\"),l=t(\"color-normalize\"),c=t(\"font-atlas\"),u=t(\"typedarray-pool\"),f=t(\"parse-rect\"),h=t(\"is-plain-obj\"),p=t(\"parse-unit\"),d=t(\"to-px\"),g=t(\"detect-kerning\"),m=t(\"object-assign\"),v=t(\"font-measure\"),y=t(\"flatten-vertex-data\"),x=t(\"bit-twiddle\").nextPow2,b=new s,_=!1;if(document.body){var w=document.body.appendChild(document.createElement(\"div\"));w.style.font=\"italic small-caps bold condensed 16px/2 cursive\",getComputedStyle(w).fontStretch&&(_=!0),document.body.removeChild(w)}var T=function(t){!function(t){return\"function\"==typeof t&&t._gl&&t.prop&&t.texture&&t.buffer}(t)?this.gl=o(t):(t={regl:t},this.gl=t.regl._gl),this.shader=b.get(this.gl),this.shader?this.regl=this.shader.regl:this.regl=t.regl||a({gl:this.gl}),this.charBuffer=this.regl.buffer({type:\"uint8\",usage:\"stream\"}),this.sizeBuffer=this.regl.buffer({type:\"float\",usage:\"stream\"}),this.shader||(this.shader=this.createShader(),b.set(this.gl,this.shader)),this.batch=[],this.fontSize=[],this.font=[],this.fontAtlas=[],this.draw=this.shader.draw.bind(this),this.render=function(){this.regl._refresh(),this.draw(this.batch)},this.canvas=this.gl.canvas,this.update(h(t)?t:{})};T.prototype.createShader=function(){var t=this.regl,e=t({blend:{enable:!0,color:[0,0,0,1],func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:\"one minus dst alpha\",dstAlpha:\"one\"}},stencil:{enable:!1},depth:{enable:!1},count:t.prop(\"count\"),offset:t.prop(\"offset\"),attributes:{charOffset:{offset:4,stride:8,buffer:t.this(\"sizeBuffer\")},width:{offset:0,stride:8,buffer:t.this(\"sizeBuffer\")},char:t.this(\"charBuffer\"),position:t.this(\"position\")},uniforms:{atlasSize:function(t,e){return[e.atlas.width,e.atlas.height]},atlasDim:function(t,e){return[e.atlas.cols,e.atlas.rows]},atlas:function(t,e){return e.atlas.texture},charStep:function(t,e){return e.atlas.step},em:function(t,e){return e.atlas.em},color:t.prop(\"color\"),opacity:t.prop(\"opacity\"),viewport:t.this(\"viewportArray\"),scale:t.this(\"scale\"),align:t.prop(\"align\"),baseline:t.prop(\"baseline\"),translate:t.this(\"translate\"),positionOffset:t.prop(\"positionOffset\")},primitive:\"points\",viewport:t.this(\"viewport\"),vert:\"\\n\\t\\t\\tprecision highp float;\\n\\t\\t\\tattribute float width, charOffset, char;\\n\\t\\t\\tattribute vec2 position;\\n\\t\\t\\tuniform float fontSize, charStep, em, align, baseline;\\n\\t\\t\\tuniform vec4 viewport;\\n\\t\\t\\tuniform vec4 color;\\n\\t\\t\\tuniform vec2 atlasSize, atlasDim, scale, translate, positionOffset;\\n\\t\\t\\tvarying vec2 charCoord, charId;\\n\\t\\t\\tvarying float charWidth;\\n\\t\\t\\tvarying vec4 fontColor;\\n\\t\\t\\tvoid main () {\\n\\t\\t\\t\\t\"+(T.normalViewport?\"\":\"vec2 positionOffset = vec2(positionOffset.x,- positionOffset.y);\")+\"\\n\\n\\t\\t\\t\\tvec2 offset = floor(em * (vec2(align + charOffset, baseline)\\n\\t\\t\\t\\t\\t+ positionOffset))\\n\\t\\t\\t\\t\\t/ (viewport.zw * scale.xy);\\n\\n\\t\\t\\t\\tvec2 position = (position + translate) * scale;\\n\\t\\t\\t\\tposition += offset * scale;\\n\\n\\t\\t\\t\\t\"+(T.normalViewport?\"position.y = 1. - position.y;\":\"\")+\"\\n\\n\\t\\t\\t\\tcharCoord = position * viewport.zw + viewport.xy;\\n\\n\\t\\t\\t\\tgl_Position = vec4(position * 2. - 1., 0, 1);\\n\\n\\t\\t\\t\\tgl_PointSize = charStep;\\n\\n\\t\\t\\t\\tcharId.x = mod(char, atlasDim.x);\\n\\t\\t\\t\\tcharId.y = floor(char / atlasDim.x);\\n\\n\\t\\t\\t\\tcharWidth = width * em;\\n\\n\\t\\t\\t\\tfontColor = color / 255.;\\n\\t\\t\\t}\",frag:\"\\n\\t\\t\\tprecision highp float;\\n\\t\\t\\tuniform sampler2D atlas;\\n\\t\\t\\tuniform float fontSize, charStep, opacity;\\n\\t\\t\\tuniform vec2 atlasSize;\\n\\t\\t\\tuniform vec4 viewport;\\n\\t\\t\\tvarying vec4 fontColor;\\n\\t\\t\\tvarying vec2 charCoord, charId;\\n\\t\\t\\tvarying float charWidth;\\n\\n\\t\\t\\tfloat lightness(vec4 color) {\\n\\t\\t\\t\\treturn color.r * 0.299 + color.g * 0.587 + color.b * 0.114;\\n\\t\\t\\t}\\n\\n\\t\\t\\tvoid main () {\\n\\t\\t\\t\\tvec2 uv = gl_FragCoord.xy - charCoord + charStep * .5;\\n\\t\\t\\t\\tfloat halfCharStep = floor(charStep * .5 + .5);\\n\\n\\t\\t\\t\\t// invert y and shift by 1px (FF expecially needs that)\\n\\t\\t\\t\\tuv.y = charStep - uv.y;\\n\\n\\t\\t\\t\\t// ignore points outside of character bounding box\\n\\t\\t\\t\\tfloat halfCharWidth = ceil(charWidth * .5);\\n\\t\\t\\t\\tif (floor(uv.x) > halfCharStep + halfCharWidth ||\\n\\t\\t\\t\\t\\tfloor(uv.x) < halfCharStep - halfCharWidth) return;\\n\\n\\t\\t\\t\\tuv += charId * charStep;\\n\\t\\t\\t\\tuv = uv / atlasSize;\\n\\n\\t\\t\\t\\tvec4 color = fontColor;\\n\\t\\t\\t\\tvec4 mask = texture2D(atlas, uv);\\n\\n\\t\\t\\t\\tfloat maskY = lightness(mask);\\n\\t\\t\\t\\t// float colorY = lightness(color);\\n\\t\\t\\t\\tcolor.a *= maskY;\\n\\t\\t\\t\\tcolor.a *= opacity;\\n\\n\\t\\t\\t\\t// color.a += .1;\\n\\n\\t\\t\\t\\t// antialiasing, see yiq color space y-channel formula\\n\\t\\t\\t\\t// color.rgb += (1. - color.rgb) * (1. - mask.rgb);\\n\\n\\t\\t\\t\\tgl_FragColor = color;\\n\\t\\t\\t}\"});return{regl:t,draw:e,atlas:{}}},T.prototype.update=function(t){var e=this;if(\"string\"==typeof t)t={text:t};else if(!t)return;null!=(t=i(t,{position:\"position positions coord coords coordinates\",font:\"font fontFace fontface typeface cssFont css-font family fontFamily\",fontSize:\"fontSize fontsize size font-size\",text:\"text texts chars characters value values symbols\",align:\"align alignment textAlign textbaseline\",baseline:\"baseline textBaseline textbaseline\",direction:\"dir direction textDirection\",color:\"color colour fill fill-color fillColor textColor textcolor\",kerning:\"kerning kern\",range:\"range dataBox\",viewport:\"vp viewport viewBox viewbox viewPort\",opacity:\"opacity alpha transparency visible visibility opaque\",offset:\"offset positionOffset padding shift indent indentation\"},!0)).opacity&&(Array.isArray(t.opacity)?this.opacity=t.opacity.map((function(t){return parseFloat(t)})):this.opacity=parseFloat(t.opacity)),null!=t.viewport&&(this.viewport=f(t.viewport),T.normalViewport&&(this.viewport.y=this.canvas.height-this.viewport.y-this.viewport.height),this.viewportArray=[this.viewport.x,this.viewport.y,this.viewport.width,this.viewport.height]),null==this.viewport&&(this.viewport={x:0,y:0,width:this.gl.drawingBufferWidth,height:this.gl.drawingBufferHeight},this.viewportArray=[this.viewport.x,this.viewport.y,this.viewport.width,this.viewport.height]),null!=t.kerning&&(this.kerning=t.kerning),null!=t.offset&&(\"number\"==typeof t.offset&&(t.offset=[t.offset,0]),this.positionOffset=y(t.offset)),t.direction&&(this.direction=t.direction),t.range&&(this.range=t.range,this.scale=[1/(t.range[2]-t.range[0]),1/(t.range[3]-t.range[1])],this.translate=[-t.range[0],-t.range[1]]),t.scale&&(this.scale=t.scale),t.translate&&(this.translate=t.translate),this.scale||(this.scale=[1/this.viewport.width,1/this.viewport.height]),this.translate||(this.translate=[0,0]),this.font.length||t.font||(t.font=T.baseFontSize+\"px sans-serif\");var r,a=!1,o=!1;if(t.font&&(Array.isArray(t.font)?t.font:[t.font]).forEach((function(t,r){if(\"string\"==typeof t)try{t=n.parse(t)}catch(e){t=n.parse(T.baseFontSize+\"px \"+t)}else t=n.parse(n.stringify(t));var i=n.stringify({size:T.baseFontSize,family:t.family,stretch:_?t.stretch:void 0,variant:t.variant,weight:t.weight,style:t.style}),s=p(t.size),l=Math.round(s[0]*d(s[1]));if(l!==e.fontSize[r]&&(o=!0,e.fontSize[r]=l),!(e.font[r]&&i==e.font[r].baseString||(a=!0,e.font[r]=T.fonts[i],e.font[r]))){var c=t.family.join(\", \"),u=[t.style];t.style!=t.variant&&u.push(t.variant),t.variant!=t.weight&&u.push(t.weight),_&&t.weight!=t.stretch&&u.push(t.stretch),e.font[r]={baseString:i,family:c,weight:t.weight,stretch:t.stretch,style:t.style,variant:t.variant,width:{},kerning:{},metrics:v(c,{origin:\"top\",fontSize:T.baseFontSize,fontStyle:u.join(\" \")})},T.fonts[i]=e.font[r]}})),(a||o)&&this.font.forEach((function(r,i){var a=n.stringify({size:e.fontSize[i],family:r.family,stretch:_?r.stretch:void 0,variant:r.variant,weight:r.weight,style:r.style});if(e.fontAtlas[i]=e.shader.atlas[a],!e.fontAtlas[i]){var o=r.metrics;e.shader.atlas[a]=e.fontAtlas[i]={fontString:a,step:2*Math.ceil(e.fontSize[i]*o.bottom*.5),em:e.fontSize[i],cols:0,rows:0,height:0,width:0,chars:[],ids:{},texture:e.regl.texture()}}null==t.text&&(t.text=e.text)})),\"string\"==typeof t.text&&t.position&&t.position.length>2){for(var s=Array(.5*t.position.length),h=0;h<s.length;h++)s[h]=t.text;t.text=s}if(null!=t.text||a){if(this.textOffsets=[0],Array.isArray(t.text)){this.count=t.text[0].length,this.counts=[this.count];for(var b=1;b<t.text.length;b++)this.textOffsets[b]=this.textOffsets[b-1]+t.text[b-1].length,this.count+=t.text[b].length,this.counts.push(t.text[b].length);this.text=t.text.join(\"\")}else this.text=t.text,this.count=this.text.length,this.counts=[this.count];r=[],this.font.forEach((function(t,n){T.atlasContext.font=t.baseString;for(var i=e.fontAtlas[n],a=0;a<e.text.length;a++){var o=e.text.charAt(a);if(null==i.ids[o]&&(i.ids[o]=i.chars.length,i.chars.push(o),r.push(o)),null==t.width[o]&&(t.width[o]=T.atlasContext.measureText(o).width/T.baseFontSize,e.kerning)){var s=[];for(var l in t.width)s.push(l+o,o+l);m(t.kerning,g(t.family,{pairs:s}))}}}))}if(t.position)if(t.position.length>2){for(var w=!t.position[0].length,k=u.mallocFloat(2*this.count),A=0,M=0;A<this.counts.length;A++){var S=this.counts[A];if(w)for(var E=0;E<S;E++)k[M++]=t.position[2*A],k[M++]=t.position[2*A+1];else for(var L=0;L<S;L++)k[M++]=t.position[A][0],k[M++]=t.position[A][1]}this.position.call?this.position({type:\"float\",data:k}):this.position=this.regl.buffer({type:\"float\",data:k}),u.freeFloat(k)}else this.position.destroy&&this.position.destroy(),this.position={constant:t.position};if(t.text||a){var C=u.mallocUint8(this.count),P=u.mallocFloat(2*this.count);this.textWidth=[];for(var I=0,O=0;I<this.counts.length;I++){for(var z=this.counts[I],D=this.font[I]||this.font[0],R=this.fontAtlas[I]||this.fontAtlas[0],F=0;F<z;F++){var B=this.text.charAt(O),N=this.text.charAt(O-1);if(C[O]=R.ids[B],P[2*O]=D.width[B],F){var j=P[2*O-2],U=P[2*O],V=P[2*O-1]+.5*j+.5*U;if(this.kerning){var q=D.kerning[N+B];q&&(V+=.001*q)}P[2*O+1]=V}else P[2*O+1]=.5*P[2*O];O++}this.textWidth.push(P.length?.5*P[2*O-2]+P[2*O-1]:0)}t.align||(t.align=this.align),this.charBuffer({data:C,type:\"uint8\",usage:\"stream\"}),this.sizeBuffer({data:P,type:\"float\",usage:\"stream\"}),u.freeUint8(C),u.freeFloat(P),r.length&&this.font.forEach((function(t,r){var n=e.fontAtlas[r],i=n.step,a=Math.floor(T.maxAtlasSize/i),o=Math.min(a,n.chars.length),s=Math.ceil(n.chars.length/o),l=x(o*i),u=x(s*i);n.width=l,n.height=u,n.rows=s,n.cols=o,n.em&&n.texture({data:c({canvas:T.atlasCanvas,font:n.fontString,chars:n.chars,shape:[l,u],step:[i,i]})})}))}if(t.align&&(this.align=t.align,this.alignOffset=this.textWidth.map((function(t,r){var n=Array.isArray(e.align)?e.align.length>1?e.align[r]:e.align[0]:e.align;if(\"number\"==typeof n)return n;switch(n){case\"right\":case\"end\":return-t;case\"center\":case\"centre\":case\"middle\":return.5*-t}return 0}))),null==this.baseline&&null==t.baseline&&(t.baseline=0),null!=t.baseline&&(this.baseline=t.baseline,Array.isArray(this.baseline)||(this.baseline=[this.baseline]),this.baselineOffset=this.baseline.map((function(t,r){var n=(e.font[r]||e.font[0]).metrics,i=0;return i+=.5*n.bottom,i+=\"number\"==typeof t?t-n.baseline:-n[t],T.normalViewport||(i*=-1),i}))),null!=t.color)if(t.color||(t.color=\"transparent\"),\"string\"!=typeof t.color&&isNaN(t.color)){var H;if(\"number\"==typeof t.color[0]&&t.color.length>this.counts.length){var G=t.color.length;H=u.mallocUint8(G);for(var Y=(t.color.subarray||t.color.slice).bind(t.color),W=0;W<G;W+=4)H.set(l(Y(W,W+4),\"uint8\"),W)}else{var X=t.color.length;H=u.mallocUint8(4*X);for(var Z=0;Z<X;Z++)H.set(l(t.color[Z]||0,\"uint8\"),4*Z)}this.color=H}else this.color=l(t.color,\"uint8\");if(t.position||t.text||t.color||t.baseline||t.align||t.font||t.offset||t.opacity)if(this.color.length>4||this.baselineOffset.length>1||this.align&&this.align.length>1||this.fontAtlas.length>1||this.positionOffset.length>2){var J=Math.max(.5*this.position.length||0,.25*this.color.length||0,this.baselineOffset.length||0,this.alignOffset.length||0,this.font.length||0,this.opacity.length||0,.5*this.positionOffset.length||0);this.batch=Array(J);for(var K=0;K<this.batch.length;K++)this.batch[K]={count:this.counts.length>1?this.counts[K]:this.counts[0],offset:this.textOffsets.length>1?this.textOffsets[K]:this.textOffsets[0],color:this.color?this.color.length<=4?this.color:this.color.subarray(4*K,4*K+4):[0,0,0,255],opacity:Array.isArray(this.opacity)?this.opacity[K]:this.opacity,baseline:null!=this.baselineOffset[K]?this.baselineOffset[K]:this.baselineOffset[0],align:this.align?null!=this.alignOffset[K]?this.alignOffset[K]:this.alignOffset[0]:0,atlas:this.fontAtlas[K]||this.fontAtlas[0],positionOffset:this.positionOffset.length>2?this.positionOffset.subarray(2*K,2*K+2):this.positionOffset}}else this.count?this.batch=[{count:this.count,offset:0,color:this.color||[0,0,0,255],opacity:Array.isArray(this.opacity)?this.opacity[0]:this.opacity,baseline:this.baselineOffset[0],align:this.alignOffset?this.alignOffset[0]:0,atlas:this.fontAtlas[0],positionOffset:this.positionOffset}]:this.batch=[]},T.prototype.destroy=function(){},T.prototype.kerning=!0,T.prototype.position={constant:new Float32Array(2)},T.prototype.translate=null,T.prototype.scale=null,T.prototype.font=null,T.prototype.text=\"\",T.prototype.positionOffset=[0,0],T.prototype.opacity=1,T.prototype.color=new Uint8Array([0,0,0,255]),T.prototype.alignOffset=[0,0],T.normalViewport=!1,T.maxAtlasSize=1024,T.atlasCanvas=document.createElement(\"canvas\"),T.atlasContext=T.atlasCanvas.getContext(\"2d\",{alpha:!1}),T.baseFontSize=64,T.fonts={},e.exports=T},{\"bit-twiddle\":104,\"color-normalize\":131,\"css-font\":150,\"detect-kerning\":181,\"es6-weak-map\":241,\"flatten-vertex-data\":252,\"font-atlas\":253,\"font-measure\":254,\"gl-util/context\":357,\"is-plain-obj\":457,\"object-assign\":487,\"parse-rect\":492,\"parse-unit\":494,\"pick-by-alias\":498,regl:540,\"to-px\":600,\"typedarray-pool\":617}],356:[function(t,e,r){\"use strict\";var n=t(\"ndarray\"),i=t(\"ndarray-ops\"),a=t(\"typedarray-pool\");e.exports=function(t){if(arguments.length<=1)throw new Error(\"gl-texture2d: Missing arguments for texture2d constructor\");o||c(t);if(\"number\"==typeof arguments[1])return v(t,arguments[1],arguments[2],arguments[3]||t.RGBA,arguments[4]||t.UNSIGNED_BYTE);if(Array.isArray(arguments[1]))return v(t,0|arguments[1][0],0|arguments[1][1],arguments[2]||t.RGBA,arguments[3]||t.UNSIGNED_BYTE);if(\"object\"==typeof arguments[1]){var e=arguments[1],r=u(e)?e:e.raw;if(r)return y(t,r,0|e.width,0|e.height,arguments[2]||t.RGBA,arguments[3]||t.UNSIGNED_BYTE);if(e.shape&&e.data&&e.stride)return x(t,e)}throw new Error(\"gl-texture2d: Invalid arguments for texture2d constructor\")};var o=null,s=null,l=null;function c(t){o=[t.LINEAR,t.NEAREST_MIPMAP_LINEAR,t.LINEAR_MIPMAP_NEAREST,t.LINEAR_MIPMAP_NEAREST],s=[t.NEAREST,t.LINEAR,t.NEAREST_MIPMAP_NEAREST,t.NEAREST_MIPMAP_LINEAR,t.LINEAR_MIPMAP_NEAREST,t.LINEAR_MIPMAP_LINEAR],l=[t.REPEAT,t.CLAMP_TO_EDGE,t.MIRRORED_REPEAT]}function u(t){return\"undefined\"!=typeof HTMLCanvasElement&&t instanceof HTMLCanvasElement||\"undefined\"!=typeof HTMLImageElement&&t instanceof HTMLImageElement||\"undefined\"!=typeof HTMLVideoElement&&t instanceof HTMLVideoElement||\"undefined\"!=typeof ImageData&&t instanceof ImageData}var f=function(t,e){i.muls(t,e,255)};function h(t,e,r){var n=t.gl,i=n.getParameter(n.MAX_TEXTURE_SIZE);if(e<0||e>i||r<0||r>i)throw new Error(\"gl-texture2d: Invalid texture size\");return t._shape=[e,r],t.bind(),n.texImage2D(n.TEXTURE_2D,0,t.format,e,r,0,t.format,t.type,null),t._mipLevels=[0],t}function p(t,e,r,n,i,a){this.gl=t,this.handle=e,this.format=i,this.type=a,this._shape=[r,n],this._mipLevels=[0],this._magFilter=t.NEAREST,this._minFilter=t.NEAREST,this._wrapS=t.CLAMP_TO_EDGE,this._wrapT=t.CLAMP_TO_EDGE,this._anisoSamples=1;var o=this,s=[this._wrapS,this._wrapT];Object.defineProperties(s,[{get:function(){return o._wrapS},set:function(t){return o.wrapS=t}},{get:function(){return o._wrapT},set:function(t){return o.wrapT=t}}]),this._wrapVector=s;var l=[this._shape[0],this._shape[1]];Object.defineProperties(l,[{get:function(){return o._shape[0]},set:function(t){return o.width=t}},{get:function(){return o._shape[1]},set:function(t){return o.height=t}}]),this._shapeVector=l}var d=p.prototype;function g(t,e){return 3===t.length?1===e[2]&&e[1]===t[0]*t[2]&&e[0]===t[2]:1===e[0]&&e[1]===t[0]}function m(t){var e=t.createTexture();return t.bindTexture(t.TEXTURE_2D,e),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MIN_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_MAG_FILTER,t.NEAREST),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_S,t.CLAMP_TO_EDGE),t.texParameteri(t.TEXTURE_2D,t.TEXTURE_WRAP_T,t.CLAMP_TO_EDGE),e}function v(t,e,r,n,i){var a=t.getParameter(t.MAX_TEXTURE_SIZE);if(e<0||e>a||r<0||r>a)throw new Error(\"gl-texture2d: Invalid texture shape\");if(i===t.FLOAT&&!t.getExtension(\"OES_texture_float\"))throw new Error(\"gl-texture2d: Floating point textures not supported on this platform\");var o=m(t);return t.texImage2D(t.TEXTURE_2D,0,n,e,r,0,n,i,null),new p(t,o,e,r,n,i)}function y(t,e,r,n,i,a){var o=m(t);return t.texImage2D(t.TEXTURE_2D,0,i,i,a,e),new p(t,o,r,n,i,a)}function x(t,e){var r=e.dtype,o=e.shape.slice(),s=t.getParameter(t.MAX_TEXTURE_SIZE);if(o[0]<0||o[0]>s||o[1]<0||o[1]>s)throw new Error(\"gl-texture2d: Invalid texture size\");var l=g(o,e.stride.slice()),c=0;\"float32\"===r?c=t.FLOAT:\"float64\"===r?(c=t.FLOAT,l=!1,r=\"float32\"):\"uint8\"===r?c=t.UNSIGNED_BYTE:(c=t.UNSIGNED_BYTE,l=!1,r=\"uint8\");var u,h,d=0;if(2===o.length)d=t.LUMINANCE,o=[o[0],o[1],1],e=n(e.data,o,[e.stride[0],e.stride[1],1],e.offset);else{if(3!==o.length)throw new Error(\"gl-texture2d: Invalid shape for texture\");if(1===o[2])d=t.ALPHA;else if(2===o[2])d=t.LUMINANCE_ALPHA;else if(3===o[2])d=t.RGB;else{if(4!==o[2])throw new Error(\"gl-texture2d: Invalid shape for pixel coords\");d=t.RGBA}}c!==t.FLOAT||t.getExtension(\"OES_texture_float\")||(c=t.UNSIGNED_BYTE,l=!1);var v=e.size;if(l)u=0===e.offset&&e.data.length===v?e.data:e.data.subarray(e.offset,e.offset+v);else{var y=[o[2],o[2]*o[0],1];h=a.malloc(v,r);var 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f(this.rightPoints,t,e)}return h(this.leftPoints,e)},a.queryInterval=function(t,e,r){var n;if(t<this.mid&&this.left&&(n=this.left.queryInterval(t,e,r)))return n;if(e>this.mid&&this.right&&(n=this.right.queryInterval(t,e,r)))return n;return e<this.mid?u(this.leftPoints,e,r):t>this.mid?f(this.rightPoints,t,r):h(this.leftPoints,r)};var y=v.prototype;y.insert=function(t){this.root?this.root.insert(t):this.root=new i(t[0],null,null,[t],[t])},y.remove=function(t){if(this.root){var e=this.root.remove(t);return 2===e&&(this.root=null),0!==e}return!1},y.queryPoint=function(t,e){if(this.root)return this.root.queryPoint(t,e)},y.queryInterval=function(t,e,r){if(t<=e&&this.root)return this.root.queryInterval(t,e,r)},Object.defineProperty(y,\"count\",{get:function(){return this.root?this.root.count:0}}),Object.defineProperty(y,\"intervals\",{get:function(){return this.root?this.root.intervals([]):[]}})},{\"binary-search-bounds\":449}],449:[function(t,e,r){arguments[4][251][0].apply(r,arguments)},{dup:251}],450:[function(t,e,r){\"use strict\";e.exports=function(t,e){e=e||new Array(t.length);for(var r=0;r<t.length;++r)e[t[r]]=r;return e}},{}],451:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=new Array(t),r=0;r<t;++r)e[r]=r;return e}},{}],452:[function(t,e,r){e.exports=!0},{}],453:[function(t,e,r){function n(t){return!!t.constructor&&\"function\"==typeof t.constructor.isBuffer&&t.constructor.isBuffer(t)}\n",
+       "/*!\n",
+       " * Determine if an object is a Buffer\n",
+       " *\n",
+       " * @author   Feross Aboukhadijeh <https://feross.org>\n",
+       " * @license  MIT\n",
+       " */\n",
+       "e.exports=function(t){return null!=t&&(n(t)||function(t){return\"function\"==typeof t.readFloatLE&&\"function\"==typeof t.slice&&n(t.slice(0,0))}(t)||!!t._isBuffer)}},{}],454:[function(t,e,r){\"use strict\";e.exports=\"undefined\"!=typeof navigator&&(/MSIE/.test(navigator.userAgent)||/Trident\\//.test(navigator.appVersion))},{}],455:[function(t,e,r){\"use strict\";e.exports=a,e.exports.isMobile=a,e.exports.default=a;var n=/(android|bb\\d+|meego).+mobile|avantgo|bada\\/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|iris|kindle|lge |maemo|midp|mmp|mobile.+firefox|netfront|opera m(ob|in)i|palm( os)?|phone|p(ixi|re)\\/|plucker|pocket|psp|series[46]0|symbian|treo|up\\.(browser|link)|vodafone|wap|windows (ce|phone)|xda|xiino/i,i=/(android|bb\\d+|meego).+mobile|avantgo|bada\\/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|iris|kindle|lge |maemo|midp|mmp|mobile.+firefox|netfront|opera m(ob|in)i|palm( os)?|phone|p(ixi|re)\\/|plucker|pocket|psp|series[46]0|symbian|treo|up\\.(browser|link)|vodafone|wap|windows (ce|phone)|xda|xiino|android|ipad|playbook|silk/i;function a(t){t||(t={});var e=t.ua;if(e||\"undefined\"==typeof navigator||(e=navigator.userAgent),e&&e.headers&&\"string\"==typeof e.headers[\"user-agent\"]&&(e=e.headers[\"user-agent\"]),\"string\"!=typeof e)return!1;var r=t.tablet?i.test(e):n.test(e);return!r&&t.tablet&&t.featureDetect&&navigator&&navigator.maxTouchPoints>1&&-1!==e.indexOf(\"Macintosh\")&&-1!==e.indexOf(\"Safari\")&&(r=!0),r}},{}],456:[function(t,e,r){\"use strict\";e.exports=function(t){var e=typeof t;return null!==t&&(\"object\"===e||\"function\"===e)}},{}],457:[function(t,e,r){\"use strict\";var n=Object.prototype.toString;e.exports=function(t){var e;return\"[object Object]\"===n.call(t)&&(null===(e=Object.getPrototypeOf(t))||e===Object.getPrototypeOf({}))}},{}],458:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e,r=t.length,n=0;n<r;n++)if(((e=t.charCodeAt(n))<9||e>13)&&32!==e&&133!==e&&160!==e&&5760!==e&&6158!==e&&(e<8192||e>8205)&&8232!==e&&8233!==e&&8239!==e&&8287!==e&&8288!==e&&12288!==e&&65279!==e)return!1;return!0}},{}],459:[function(t,e,r){\"use strict\";e.exports=function(t){return\"string\"==typeof t&&(t=t.trim(),!!(/^[mzlhvcsqta]\\s*[-+.0-9][^mlhvzcsqta]+/i.test(t)&&/[\\dz]$/i.test(t)&&t.length>4))}},{}],460:[function(t,e,r){e.exports=function(t,e,r){return t*(1-r)+e*r}},{}],461:[function(t,e,r){!function(t,n){\"object\"==typeof r&&void 0!==e?e.exports=n():(t=t||self).mapboxgl=n()}(this,(function(){\"use strict\";var t,e,r;function n(n,i){if(t)if(e){var a=\"var sharedChunk = {}; (\"+t+\")(sharedChunk); (\"+e+\")(sharedChunk);\",o={};t(o),(r=i(o)).workerUrl=window.URL.createObjectURL(new Blob([a],{type:\"text/javascript\"}))}else e=i;else t=i}return n(0,(function(t){function e(t,e){return t(e={exports:{}},e.exports),e.exports}var r=n;function n(t,e,r,n){this.cx=3*t,this.bx=3*(r-t)-this.cx,this.ax=1-this.cx-this.bx,this.cy=3*e,this.by=3*(n-e)-this.cy,this.ay=1-this.cy-this.by,this.p1x=t,this.p1y=n,this.p2x=r,this.p2y=n}n.prototype.sampleCurveX=function(t){return((this.ax*t+this.bx)*t+this.cx)*t},n.prototype.sampleCurveY=function(t){return((this.ay*t+this.by)*t+this.cy)*t},n.prototype.sampleCurveDerivativeX=function(t){return(3*this.ax*t+2*this.bx)*t+this.cx},n.prototype.solveCurveX=function(t,e){var r,n,i,a,o;for(void 0===e&&(e=1e-6),i=t,o=0;o<8;o++){if(a=this.sampleCurveX(i)-t,Math.abs(a)<e)return i;var s=this.sampleCurveDerivativeX(i);if(Math.abs(s)<1e-6)break;i-=a/s}if((i=t)<(r=0))return r;if(i>(n=1))return n;for(;r<n;){if(a=this.sampleCurveX(i),Math.abs(a-t)<e)return i;t>a?r=i:n=i,i=.5*(n-r)+r}return i},n.prototype.solve=function(t,e){return this.sampleCurveY(this.solveCurveX(t,e))};var i=a;function a(t,e){this.x=t,this.y=e}function o(t,e,n,i){var a=new r(t,e,n,i);return function(t){return a.solve(t)}}a.prototype={clone:function(){return new a(this.x,this.y)},add:function(t){return this.clone()._add(t)},sub:function(t){return this.clone()._sub(t)},multByPoint:function(t){return this.clone()._multByPoint(t)},divByPoint:function(t){return this.clone()._divByPoint(t)},mult:function(t){return this.clone()._mult(t)},div:function(t){return this.clone()._div(t)},rotate:function(t){return this.clone()._rotate(t)},rotateAround:function(t,e){return this.clone()._rotateAround(t,e)},matMult:function(t){return this.clone()._matMult(t)},unit:function(){return this.clone()._unit()},perp:function(){return this.clone()._perp()},round:function(){return this.clone()._round()},mag:function(){return Math.sqrt(this.x*this.x+this.y*this.y)},equals:function(t){return this.x===t.x&&this.y===t.y},dist:function(t){return Math.sqrt(this.distSqr(t))},distSqr:function(t){var e=t.x-this.x,r=t.y-this.y;return e*e+r*r},angle:function(){return Math.atan2(this.y,this.x)},angleTo:function(t){return Math.atan2(this.y-t.y,this.x-t.x)},angleWith:function(t){return this.angleWithSep(t.x,t.y)},angleWithSep:function(t,e){return Math.atan2(this.x*e-this.y*t,this.x*t+this.y*e)},_matMult:function(t){var e=t[0]*this.x+t[1]*this.y,r=t[2]*this.x+t[3]*this.y;return this.x=e,this.y=r,this},_add:function(t){return this.x+=t.x,this.y+=t.y,this},_sub:function(t){return this.x-=t.x,this.y-=t.y,this},_mult:function(t){return this.x*=t,this.y*=t,this},_div:function(t){return this.x/=t,this.y/=t,this},_multByPoint:function(t){return this.x*=t.x,this.y*=t.y,this},_divByPoint:function(t){return this.x/=t.x,this.y/=t.y,this},_unit:function(){return this._div(this.mag()),this},_perp:function(){var t=this.y;return this.y=this.x,this.x=-t,this},_rotate:function(t){var e=Math.cos(t),r=Math.sin(t),n=e*this.x-r*this.y,i=r*this.x+e*this.y;return this.x=n,this.y=i,this},_rotateAround:function(t,e){var r=Math.cos(t),n=Math.sin(t),i=e.x+r*(this.x-e.x)-n*(this.y-e.y),a=e.y+n*(this.x-e.x)+r*(this.y-e.y);return this.x=i,this.y=a,this},_round:function(){return this.x=Math.round(this.x),this.y=Math.round(this.y),this}},a.convert=function(t){return t instanceof a?t:Array.isArray(t)?new a(t[0],t[1]):t};var s=o(.25,.1,.25,1);function l(t,e,r){return Math.min(r,Math.max(e,t))}function c(t,e,r){var n=r-e,i=((t-e)%n+n)%n+e;return i===e?r:i}function u(t){for(var e=[],r=arguments.length-1;r-- >0;)e[r]=arguments[r+1];for(var n=0,i=e;n<i.length;n+=1){var a=i[n];for(var o in a)t[o]=a[o]}return t}var f=1;function h(){return f++}function p(){return function t(e){return e?(e^16*Math.random()>>e/4).toString(16):([1e7]+-[1e3]+-4e3+-8e3+-1e11).replace(/[018]/g,t)}()}function d(t){return!!t&&/^[0-9a-f]{8}-[0-9a-f]{4}-[4][0-9a-f]{3}-[89ab][0-9a-f]{3}-[0-9a-f]{12}$/i.test(t)}function g(t,e){t.forEach((function(t){e[t]&&(e[t]=e[t].bind(e))}))}function m(t,e){return-1!==t.indexOf(e,t.length-e.length)}function v(t,e,r){var n={};for(var i in t)n[i]=e.call(r||this,t[i],i,t);return n}function y(t,e,r){var n={};for(var i 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Date.now()>this._skuTokenExpiresAt},q.prototype.transformRequest=function(t,e){return this._transformRequestFn&&this._transformRequestFn(t,e)||{url:t}},q.prototype.normalizeStyleURL=function(t,e){if(!H(t))return t;var r=X(t);return r.path=\"/styles/v1\"+r.path,this._makeAPIURL(r,this._customAccessToken||e)},q.prototype.normalizeGlyphsURL=function(t,e){if(!H(t))return t;var r=X(t);return r.path=\"/fonts/v1\"+r.path,this._makeAPIURL(r,this._customAccessToken||e)},q.prototype.normalizeSourceURL=function(t,e){if(!H(t))return t;var r=X(t);return r.path=\"/v4/\"+r.authority+\".json\",r.params.push(\"secure\"),this._makeAPIURL(r,this._customAccessToken||e)},q.prototype.normalizeSpriteURL=function(t,e,r,n){var i=X(t);return H(t)?(i.path=\"/styles/v1\"+i.path+\"/sprite\"+e+r,this._makeAPIURL(i,this._customAccessToken||n)):(i.path+=\"\"+e+r,Z(i))},q.prototype.normalizeTileURL=function(t,e){if(this._isSkuTokenExpired()&&this._createSkuToken(),t&&!H(t))return t;var r=X(t),n=R.devicePixelRatio>=2||512===e?\"@2x\":\"\",i=B.supported?\".webp\":\"$1\";r.path=r.path.replace(/(\\.(png|jpg)\\d*)(?=$)/,\"\"+n+i),r.path=r.path.replace(/^.+\\/v4\\//,\"/\"),r.path=\"/v4\"+r.path;var a=this._customAccessToken||function(t){for(var e=0,r=t;e<r.length;e+=1){var n=r[e].match(/^access_token=(.*)$/);if(n)return n[1]}return null}(r.params)||F.ACCESS_TOKEN;return F.REQUIRE_ACCESS_TOKEN&&a&&this._skuToken&&r.params.push(\"sku=\"+this._skuToken),this._makeAPIURL(r,a)},q.prototype.canonicalizeTileURL=function(t,e){var r=X(t);if(!r.path.match(/(^\\/v4\\/)/)||!r.path.match(/\\.[\\w]+$/))return t;var n=\"mapbox://tiles/\";n+=r.path.replace(\"/v4/\",\"\");var i=r.params;return e&&(i=i.filter((function(t){return!t.match(/^access_token=/)}))),i.length&&(n+=\"?\"+i.join(\"&\")),n},q.prototype.canonicalizeTileset=function(t,e){for(var r=!!e&&H(e),n=[],i=0,a=t.tiles||[];i<a.length;i+=1){var o=a[i];Y(o)?n.push(this.canonicalizeTileURL(o,r)):n.push(o)}return 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r=e.parse(t[1],1,Bt);if(!r)return null;var n=[],i=null;e.expectedType&&\"value\"!==e.expectedType.kind&&(i=e.expectedType);for(var a=1;a<t.length;a+=2){var o=1===a?-1/0:t[a],s=t[a+1],l=a,c=a+1;if(\"number\"!=typeof o)return e.error('Input/output pairs for \"step\" expressions must be defined using literal numeric values (not computed expressions) for the input values.',l);if(n.length&&n[n.length-1][0]>=o)return e.error('Input/output pairs for \"step\" expressions must be arranged with input values in strictly ascending order.',l);var u=e.parse(s,c,i);if(!u)return null;i=i||u.type,n.push([o,u])}return new qe(i,r,n)},qe.prototype.evaluate=function(t){var e=this.labels,r=this.outputs;if(1===e.length)return r[0].evaluate(t);var n=this.input.evaluate(t);if(n<=e[0])return r[0].evaluate(t);var i=e.length;return n>=e[i-1]?r[i-1].evaluate(t):r[Ve(e,n)].evaluate(t)},qe.prototype.eachChild=function(t){t(this.input);for(var e=0,r=this.outputs;e<r.length;e+=1){t(r[e])}},qe.prototype.outputDefined=function(){return this.outputs.every((function(t){return t.outputDefined()}))},qe.prototype.serialize=function(){for(var t=[\"step\",this.input.serialize()],e=0;e<this.labels.length;e++)e>0&&t.push(this.labels[e]),t.push(this.outputs[e].serialize());return t};var Ge=Object.freeze({__proto__:null,number:He,color:function(t,e,r){return new te(He(t.r,e.r,r),He(t.g,e.g,r),He(t.b,e.b,r),He(t.a,e.a,r))},array:function(t,e,r){return t.map((function(t,n){return He(t,e[n],r)}))}}),Ye=6/29,We=3*Ye*Ye,Xe=Math.PI/180,Ze=180/Math.PI;function Je(t){return t>.008856451679035631?Math.pow(t,1/3):t/We+4/29}function Ke(t){return t>Ye?t*t*t:We*(t-4/29)}function Qe(t){return 255*(t<=.0031308?12.92*t:1.055*Math.pow(t,1/2.4)-.055)}function $e(t){return(t/=255)<=.04045?t/12.92:Math.pow((t+.055)/1.055,2.4)}function tr(t){var e=$e(t.r),r=$e(t.g),n=$e(t.b),i=Je((.4124564*e+.3575761*r+.1804375*n)/.95047),a=Je((.2126729*e+.7151522*r+.072175*n)/1);return{l:116*a-16,a:500*(i-a),b:200*(a-Je((.0193339*e+.119192*r+.9503041*n)/1.08883)),alpha:t.a}}function er(t){var e=(t.l+16)/116,r=isNaN(t.a)?e:e+t.a/500,n=isNaN(t.b)?e:e-t.b/200;return e=1*Ke(e),r=.95047*Ke(r),n=1.08883*Ke(n),new te(Qe(3.2404542*r-1.5371385*e-.4985314*n),Qe(-.969266*r+1.8760108*e+.041556*n),Qe(.0556434*r-.2040259*e+1.0572252*n),t.alpha)}function rr(t,e,r){var n=e-t;return t+r*(n>180||n<-180?n-360*Math.round(n/360):n)}var nr={forward:tr,reverse:er,interpolate:function(t,e,r){return{l:He(t.l,e.l,r),a:He(t.a,e.a,r),b:He(t.b,e.b,r),alpha:He(t.alpha,e.alpha,r)}}},ir={forward:function(t){var e=tr(t),r=e.l,n=e.a,i=e.b,a=Math.atan2(i,n)*Ze;return{h:a<0?a+360:a,c:Math.sqrt(n*n+i*i),l:r,alpha:t.a}},reverse:function(t){var e=t.h*Xe,r=t.c;return er({l:t.l,a:Math.cos(e)*r,b:Math.sin(e)*r,alpha:t.alpha})},interpolate:function(t,e,r){return{h:rr(t.h,e.h,r),c:He(t.c,e.c,r),l:He(t.l,e.l,r),alpha:He(t.alpha,e.alpha,r)}}},ar=Object.freeze({__proto__:null,lab:nr,hcl:ir}),or=function(t,e,r,n,i){this.type=t,this.operator=e,this.interpolation=r,this.input=n,this.labels=[],this.outputs=[];for(var a=0,o=i;a<o.length;a+=1){var s=o[a],l=s[0],c=s[1];this.labels.push(l),this.outputs.push(c)}};function sr(t,e,r,n){var i=n-r,a=t-r;return 0===i?0:1===e?a/i:(Math.pow(e,a)-1)/(Math.pow(e,i)-1)}or.interpolationFactor=function(t,e,n,i){var a=0;if(\"exponential\"===t.name)a=sr(e,t.base,n,i);else if(\"linear\"===t.name)a=sr(e,1,n,i);else if(\"cubic-bezier\"===t.name){var o=t.controlPoints;a=new r(o[0],o[1],o[2],o[3]).solve(sr(e,1,n,i))}return a},or.parse=function(t,e){var r=t[0],n=t[1],i=t[2],a=t.slice(3);if(!Array.isArray(n)||0===n.length)return e.error(\"Expected an interpolation type expression.\",1);if(\"linear\"===n[0])n={name:\"linear\"};else if(\"exponential\"===n[0]){var o=n[1];if(\"number\"!=typeof o)return e.error(\"Exponential interpolation requires a numeric base.\",1,1);n={name:\"exponential\",base:o}}else{if(\"cubic-bezier\"!==n[0])return e.error(\"Unknown interpolation type \"+String(n[0]),1,0);var s=n.slice(1);if(4!==s.length||s.some((function(t){return\"number\"!=typeof t||t<0||t>1})))return e.error(\"Cubic bezier interpolation requires four numeric arguments with values between 0 and 1.\",1);n={name:\"cubic-bezier\",controlPoints:s}}if(t.length-1<4)return e.error(\"Expected at least 4 arguments, but found only \"+(t.length-1)+\".\");if((t.length-1)%2!=0)return e.error(\"Expected an even number of arguments.\");if(!(i=e.parse(i,2,Bt)))return null;var l=[],c=null;\"interpolate-hcl\"===r||\"interpolate-lab\"===r?c=Ut:e.expectedType&&\"value\"!==e.expectedType.kind&&(c=e.expectedType);for(var u=0;u<a.length;u+=2){var f=a[u],h=a[u+1],p=u+3,d=u+4;if(\"number\"!=typeof f)return e.error('Input/output pairs for 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a=Ve(e,n),o=e[a],s=e[a+1],l=or.interpolationFactor(this.interpolation,n,o,s),c=r[a].evaluate(t),u=r[a+1].evaluate(t);return\"interpolate\"===this.operator?Ge[this.type.kind.toLowerCase()](c,u,l):\"interpolate-hcl\"===this.operator?ir.reverse(ir.interpolate(ir.forward(c),ir.forward(u),l)):nr.reverse(nr.interpolate(nr.forward(c),nr.forward(u),l))},or.prototype.eachChild=function(t){t(this.input);for(var e=0,r=this.outputs;e<r.length;e+=1){t(r[e])}},or.prototype.outputDefined=function(){return this.outputs.every((function(t){return t.outputDefined()}))},or.prototype.serialize=function(){var t;t=\"linear\"===this.interpolation.name?[\"linear\"]:\"exponential\"===this.interpolation.name?1===this.interpolation.base?[\"linear\"]:[\"exponential\",this.interpolation.base]:[\"cubic-bezier\"].concat(this.interpolation.controlPoints);for(var e=[this.operator,t,this.input.serialize()],r=0;r<this.labels.length;r++)e.push(this.labels[r],this.outputs[r].serialize());return e};var lr=function(t,e){this.type=t,this.args=e};lr.parse=function(t,e){if(t.length<2)return e.error(\"Expectected at least one argument.\");var r=null,n=e.expectedType;n&&\"value\"!==n.kind&&(r=n);for(var i=[],a=0,o=t.slice(1);a<o.length;a+=1){var s=o[a],l=e.parse(s,1+i.length,r,void 0,{typeAnnotation:\"omit\"});if(!l)return null;r=r||l.type,i.push(l)}var c=n&&i.some((function(t){return Jt(n,t.type)}));return new lr(c?qt:r,i)},lr.prototype.evaluate=function(t){for(var e,r=null,n=0,i=0,a=this.args;i<a.length;i+=1){if(n++,(r=a[i].evaluate(t))&&r instanceof ie&&!r.available&&(e||(e=r.name),r=null,n===this.args.length&&(r=e)),null!==r)break}return r},lr.prototype.eachChild=function(t){this.args.forEach(t)},lr.prototype.outputDefined=function(){return this.args.every((function(t){return t.outputDefined()}))},lr.prototype.serialize=function(){var t=[\"coalesce\"];return this.eachChild((function(e){t.push(e.serialize())})),t};var cr=function(t,e){this.type=e.type,this.bindings=[].concat(t),this.result=e};cr.prototype.evaluate=function(t){return this.result.evaluate(t)},cr.prototype.eachChild=function(t){for(var e=0,r=this.bindings;e<r.length;e+=1){t(r[e][1])}t(this.result)},cr.parse=function(t,e){if(t.length<4)return e.error(\"Expected at least 3 arguments, but found \"+(t.length-1)+\" instead.\");for(var r=[],n=1;n<t.length-1;n+=2){var i=t[n];if(\"string\"!=typeof i)return e.error(\"Expected string, but found \"+typeof i+\" instead.\",n);if(/[^a-zA-Z0-9_]/.test(i))return e.error(\"Variable names must contain only alphanumeric characters or '_'.\",n);var a=e.parse(t[n+1],n+1);if(!a)return null;r.push([i,a])}var o=e.parse(t[t.length-1],t.length-1,e.expectedType,r);return o?new cr(r,o):null},cr.prototype.outputDefined=function(){return this.result.outputDefined()},cr.prototype.serialize=function(){for(var t=[\"let\"],e=0,r=this.bindings;e<r.length;e+=1){var n=r[e],i=n[0],a=n[1];t.push(i,a.serialize())}return t.push(this.result.serialize()),t};var ur=function(t,e,r){this.type=t,this.index=e,this.input=r};ur.parse=function(t,e){if(3!==t.length)return e.error(\"Expected 2 arguments, but found \"+(t.length-1)+\" instead.\");var r=e.parse(t[1],1,Bt),n=e.parse(t[2],2,Wt(e.expectedType||qt));if(!r||!n)return null;var i=n.type;return new ur(i.itemType,r,n)},ur.prototype.evaluate=function(t){var e=this.index.evaluate(t),r=this.input.evaluate(t);if(e<0)throw new ue(\"Array index out of bounds: \"+e+\" < 0.\");if(e>=r.length)throw new ue(\"Array index out of bounds: \"+e+\" > \"+(r.length-1)+\".\");if(e!==Math.floor(e))throw new ue(\"Array index must be an integer, but found \"+e+\" instead.\");return r[e]},ur.prototype.eachChild=function(t){t(this.index),t(this.input)},ur.prototype.outputDefined=function(){return!1},ur.prototype.serialize=function(){return[\"at\",this.index.serialize(),this.input.serialize()]};var fr=function(t,e){this.type=jt,this.needle=t,this.haystack=e};fr.parse=function(t,e){if(3!==t.length)return e.error(\"Expected 2 arguments, but found \"+(t.length-1)+\" instead.\");var r=e.parse(t[1],1,qt),n=e.parse(t[2],2,qt);return r&&n?Kt(r.type,[jt,Nt,Bt,Ft,qt])?new fr(r,n):e.error(\"Expected first argument to be of type boolean, string, number or null, but found \"+Xt(r.type)+\" instead\"):null},fr.prototype.evaluate=function(t){var e=this.needle.evaluate(t),r=this.haystack.evaluate(t);if(!r)return!1;if(!Qt(e,[\"boolean\",\"string\",\"number\",\"null\"]))throw new ue(\"Expected first argument to be of type boolean, string, number or null, but found \"+Xt(se(e))+\" instead.\");if(!Qt(r,[\"string\",\"array\"]))throw new ue(\"Expected second argument to be of type array or string, but found \"+Xt(se(r))+\" instead.\");return r.indexOf(e)>=0},fr.prototype.eachChild=function(t){t(this.needle),t(this.haystack)},fr.prototype.outputDefined=function(){return!0},fr.prototype.serialize=function(){return[\"in\",this.needle.serialize(),this.haystack.serialize()]};var hr=function(t,e,r){this.type=Bt,this.needle=t,this.haystack=e,this.fromIndex=r};hr.parse=function(t,e){if(t.length<=2||t.length>=5)return e.error(\"Expected 3 or 4 arguments, but found \"+(t.length-1)+\" instead.\");var r=e.parse(t[1],1,qt),n=e.parse(t[2],2,qt);if(!r||!n)return null;if(!Kt(r.type,[jt,Nt,Bt,Ft,qt]))return e.error(\"Expected first argument to be of type boolean, string, number or null, but found \"+Xt(r.type)+\" instead\");if(4===t.length){var i=e.parse(t[3],3,Bt);return i?new hr(r,n,i):null}return new hr(r,n)},hr.prototype.evaluate=function(t){var e=this.needle.evaluate(t),r=this.haystack.evaluate(t);if(!Qt(e,[\"boolean\",\"string\",\"number\",\"null\"]))throw new ue(\"Expected first argument to be of type boolean, string, number or null, but found \"+Xt(se(e))+\" instead.\");if(!Qt(r,[\"string\",\"array\"]))throw new ue(\"Expected second argument to be of type array or string, but found \"+Xt(se(r))+\" instead.\");if(this.fromIndex){var n=this.fromIndex.evaluate(t);return r.indexOf(e,n)}return r.indexOf(e)},hr.prototype.eachChild=function(t){t(this.needle),t(this.haystack),this.fromIndex&&t(this.fromIndex)},hr.prototype.outputDefined=function(){return!1},hr.prototype.serialize=function(){if(null!=this.fromIndex&&void 0!==this.fromIndex){var t=this.fromIndex.serialize();return[\"index-of\",this.needle.serialize(),this.haystack.serialize(),t]}return[\"index-of\",this.needle.serialize(),this.haystack.serialize()]};var pr=function(t,e,r,n,i,a){this.inputType=t,this.type=e,this.input=r,this.cases=n,this.outputs=i,this.otherwise=a};pr.parse=function(t,e){if(t.length<5)return e.error(\"Expected at least 4 arguments, but found only \"+(t.length-1)+\".\");if(t.length%2!=1)return e.error(\"Expected an even number of 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g?\"value\"!==d.type.kind&&e.concat(1).checkSubtype(r,d.type)?null:new pr(r,n,d,i,a,g):null},pr.prototype.evaluate=function(t){var e=this.input.evaluate(t);return(se(e)===this.inputType&&this.outputs[this.cases[e]]||this.otherwise).evaluate(t)},pr.prototype.eachChild=function(t){t(this.input),this.outputs.forEach(t),t(this.otherwise)},pr.prototype.outputDefined=function(){return this.outputs.every((function(t){return t.outputDefined()}))&&this.otherwise.outputDefined()},pr.prototype.serialize=function(){for(var t=this,e=[\"match\",this.input.serialize()],r=[],n={},i=0,a=Object.keys(this.cases).sort();i<a.length;i+=1){var o=a[i];void 0===(f=n[this.cases[o]])?(n[this.cases[o]]=r.length,r.push([this.cases[o],[o]])):r[f][1].push(o)}for(var s=function(e){return\"number\"===t.inputType.kind?Number(e):e},l=0,c=r;l<c.length;l+=1){var u=c[l],f=u[0],h=u[1];1===h.length?e.push(s(h[0])):e.push(h.map(s)),e.push(this.outputs[outputIndex$1].serialize())}return e.push(this.otherwise.serialize()),e};var dr=function(t,e,r){this.type=t,this.branches=e,this.otherwise=r};dr.parse=function(t,e){if(t.length<4)return e.error(\"Expected at least 3 arguments, but found only \"+(t.length-1)+\".\");if(t.length%2!=0)return e.error(\"Expected an odd number of arguments.\");var r;e.expectedType&&\"value\"!==e.expectedType.kind&&(r=e.expectedType);for(var n=[],i=1;i<t.length-1;i+=2){var a=e.parse(t[i],i,jt);if(!a)return null;var o=e.parse(t[i+1],i+1,r);if(!o)return null;n.push([a,o]),r=r||o.type}var s=e.parse(t[t.length-1],t.length-1,r);return s?new dr(r,n,s):null},dr.prototype.evaluate=function(t){for(var e=0,r=this.branches;e<r.length;e+=1){var n=r[e],i=n[0],a=n[1];if(i.evaluate(t))return a.evaluate(t)}return this.otherwise.evaluate(t)},dr.prototype.eachChild=function(t){for(var e=0,r=this.branches;e<r.length;e+=1){var n=r[e],i=n[0],a=n[1];t(i),t(a)}t(this.otherwise)},dr.prototype.outputDefined=function(){return this.branches.every((function(t){t[0];return 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or?a.interpolation:void 0;return Ir(new Zr(n?\"camera\":\"composite\",t.value,a.labels,o))}Zr.prototype.evaluateWithoutErrorHandling=function(t,e,r,n,i,a){return this._styleExpression.evaluateWithoutErrorHandling(t,e,r,n,i,a)},Zr.prototype.evaluate=function(t,e,r,n,i,a){return this._styleExpression.evaluate(t,e,r,n,i,a)},Zr.prototype.interpolationFactor=function(t,e,r){return this.interpolationType?or.interpolationFactor(this.interpolationType,t,e,r):0};var Kr=function(t,e){this._parameters=t,this._specification=e,It(this,function t(e,r){var n,i,a,o=\"color\"===r.type,s=e.stops&&\"object\"==typeof e.stops[0][0],l=s||void 0!==e.property,c=s||!l,u=e.type||(Rr(r)?\"exponential\":\"interval\");if(o&&((e=It({},e)).stops&&(e.stops=e.stops.map((function(t){return[t[0],te.parse(t[1])]}))),e.default?e.default=te.parse(e.default):e.default=te.parse(r.default)),e.colorSpace&&\"rgb\"!==e.colorSpace&&!ar[e.colorSpace])throw new Error(\"Unknown color space: 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n&&r<n.minimum?[new Ct(e,r,r+\" is less than the minimum value \"+n.minimum)]:\"maximum\"in n&&r>n.maximum?[new Ct(e,r,r+\" is greater than the maximum value \"+n.maximum)]:[]}function en(t){var e,r,n,i=t.valueSpec,a=Ot(t.value.type),o={},s=\"categorical\"!==a&&void 0===t.value.property,l=!s,c=\"array\"===Fr(t.value.stops)&&\"array\"===Fr(t.value.stops[0])&&\"object\"===Fr(t.value.stops[0][0]),u=Qr({key:t.key,value:t.value,valueSpec:t.styleSpec.function,style:t.style,styleSpec:t.styleSpec,objectElementValidators:{stops:function(t){if(\"identity\"===a)return[new Ct(t.key,t.value,'identity function may not have a \"stops\" property')];var e=[],r=t.value;e=e.concat($r({key:t.key,value:r,valueSpec:t.valueSpec,style:t.style,styleSpec:t.styleSpec,arrayElementValidator:f})),\"array\"===Fr(r)&&0===r.length&&e.push(new Ct(t.key,r,\"array must have at least one stop\"));return e},default:function(t){return kn({key:t.key,value:t.value,valueSpec:i,style:t.style,styleSpec:t.styleSpec})}}});return\"identity\"===a&&s&&u.push(new Ct(t.key,t.value,'missing required property \"property\"')),\"identity\"===a||t.value.stops||u.push(new Ct(t.key,t.value,'missing required property \"stops\"')),\"exponential\"===a&&t.valueSpec.expression&&!Rr(t.valueSpec)&&u.push(new Ct(t.key,t.value,\"exponential functions not supported\")),t.styleSpec.$version>=8&&(l&&!zr(t.valueSpec)?u.push(new Ct(t.key,t.value,\"property functions not supported\")):s&&!Dr(t.valueSpec)&&u.push(new Ct(t.key,t.value,\"zoom functions not supported\"))),\"categorical\"!==a&&!c||void 0!==t.value.property||u.push(new Ct(t.key,t.value,'\"property\" property is required')),u;function f(t){var e=[],a=t.value,s=t.key;if(\"array\"!==Fr(a))return[new Ct(s,a,\"array expected, \"+Fr(a)+\" found\")];if(2!==a.length)return[new Ct(s,a,\"array length 2 expected, length \"+a.length+\" found\")];if(c){if(\"object\"!==Fr(a[0]))return[new Ct(s,a,\"object expected, \"+Fr(a[0])+\" found\")];if(void 0===a[0].zoom)return[new Ct(s,a,\"object stop key must have zoom\")];if(void 0===a[0].value)return[new Ct(s,a,\"object stop key must have value\")];if(n&&n>Ot(a[0].zoom))return[new Ct(s,a[0].zoom,\"stop zoom values must appear in ascending order\")];Ot(a[0].zoom)!==n&&(n=Ot(a[0].zoom),r=void 0,o={}),e=e.concat(Qr({key:s+\"[0]\",value:a[0],valueSpec:{zoom:{}},style:t.style,styleSpec:t.styleSpec,objectElementValidators:{zoom:tn,value:h}}))}else e=e.concat(h({key:s+\"[0]\",value:a[0],valueSpec:{},style:t.style,styleSpec:t.styleSpec},a));return Yr(zt(a[1]))?e.concat([new Ct(s+\"[1]\",a[1],\"expressions are not allowed in function stops.\")]):e.concat(kn({key:s+\"[1]\",value:a[1],valueSpec:i,style:t.style,styleSpec:t.styleSpec}))}function h(t,n){var s=Fr(t.value),l=Ot(t.value),c=null!==t.value?t.value:n;if(e){if(s!==e)return[new Ct(t.key,c,s+\" stop domain type must match previous stop domain type \"+e)]}else e=s;if(\"number\"!==s&&\"string\"!==s&&\"boolean\"!==s)return[new Ct(t.key,c,\"stop domain value must be a number, string, or boolean\")];if(\"number\"!==s&&\"categorical\"!==a){var u=\"number expected, \"+s+\" found\";return zr(i)&&void 0===a&&(u+='\\nIf you intended to use a categorical function, specify `\"type\": \"categorical\"`.'),[new Ct(t.key,c,u)]}return\"categorical\"!==a||\"number\"!==s||isFinite(l)&&Math.floor(l)===l?\"categorical\"!==a&&\"number\"===s&&void 0!==r&&l<r?[new Ct(t.key,c,\"stop domain values must appear in ascending order\")]:(r=l,\"categorical\"===a&&l in o?[new Ct(t.key,c,\"stop domain values must be unique\")]:(o[l]=!0,[])):[new Ct(t.key,c,\"integer expected, found \"+l)]}}function rn(t){var e=(\"property\"===t.expressionContext?Jr:Wr)(zt(t.value),t.valueSpec);if(\"error\"===e.result)return e.value.map((function(e){return new Ct(\"\"+t.key+e.key,t.value,e.message)}));var r=e.value.expression||e.value._styleExpression.expression;if(\"property\"===t.expressionContext&&\"text-font\"===t.propertyKey&&!r.outputDefined())return[new Ct(t.key,t.value,'Invalid data expression for \"'+t.propertyKey+'\". Output values must be contained as literals within the expression.')];if(\"property\"===t.expressionContext&&\"layout\"===t.propertyType&&!Be(r))return[new Ct(t.key,t.value,'\"feature-state\" data expressions are not supported with layout properties.')];if(\"filter\"===t.expressionContext&&!Be(r))return[new Ct(t.key,t.value,'\"feature-state\" data expressions are not supported with filters.')];if(t.expressionContext&&0===t.expressionContext.indexOf(\"cluster\")){if(!Ne(r,[\"zoom\",\"feature-state\"]))return[new Ct(t.key,t.value,'\"zoom\" and \"feature-state\" expressions are not supported with cluster properties.')];if(\"cluster-initial\"===t.expressionContext&&!Fe(r))return[new Ct(t.key,t.value,\"Feature data expressions are not supported with initial expression part of cluster properties.\")]}return[]}function nn(t){var e=t.key,r=t.value,n=t.valueSpec,i=[];return Array.isArray(n.values)?-1===n.values.indexOf(Ot(r))&&i.push(new Ct(e,r,\"expected one of [\"+n.values.join(\", \")+\"], 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on={type:\"boolean\",default:!1,transition:!1,\"property-type\":\"data-driven\",expression:{interpolated:!1,parameters:[\"zoom\",\"feature\"]}};function sn(t){if(null==t)return{filter:function(){return!0},needGeometry:!1};an(t)||(t=cn(t));var e=Wr(t,on);if(\"error\"===e.result)throw new Error(e.value.map((function(t){return t.key+\": \"+t.message})).join(\", \"));return{filter:function(t,r,n){return e.value.evaluate(t,r,{},n)},needGeometry:function t(e){if(!Array.isArray(e))return!1;if(\"within\"===e[0])return!0;for(var r=1;r<e.length;r++)if(t(e[r]))return!0;return!1}(t)}}function ln(t,e){return t<e?-1:t>e?1:0}function cn(t){if(!t)return!0;var e,r=t[0];return t.length<=1?\"any\"!==r:\"==\"===r?un(t[1],t[2],\"==\"):\"!=\"===r?pn(un(t[1],t[2],\"==\")):\"<\"===r||\">\"===r||\"<=\"===r||\">=\"===r?un(t[1],t[2],r):\"any\"===r?(e=t.slice(1),[\"any\"].concat(e.map(cn))):\"all\"===r?[\"all\"].concat(t.slice(1).map(cn)):\"none\"===r?[\"all\"].concat(t.slice(1).map(cn).map(pn)):\"in\"===r?fn(t[1],t.slice(2)):\"!in\"===r?pn(fn(t[1],t.slice(2))):\"has\"===r?hn(t[1]):\"!has\"===r?pn(hn(t[1])):\"within\"!==r||t}function un(t,e,r){switch(t){case\"$type\":return[\"filter-type-\"+r,e];case\"$id\":return[\"filter-id-\"+r,e];default:return[\"filter-\"+r,t,e]}}function fn(t,e){if(0===e.length)return!1;switch(t){case\"$type\":return[\"filter-type-in\",[\"literal\",e]];case\"$id\":return[\"filter-id-in\",[\"literal\",e]];default:return e.length>200&&!e.some((function(t){return typeof t!=typeof e[0]}))?[\"filter-in-large\",t,[\"literal\",e.sort(ln)]]:[\"filter-in-small\",t,[\"literal\",e]]}}function hn(t){switch(t){case\"$type\":return!0;case\"$id\":return[\"filter-has-id\"];default:return[\"filter-has\",t]}}function pn(t){return[\"!\",t]}function dn(t){return an(zt(t.value))?rn(It({},t,{expressionContext:\"filter\",valueSpec:{value:\"boolean\"}})):function t(e){var r=e.value,n=e.key;if(\"array\"!==Fr(r))return[new Ct(n,r,\"array expected, \"+Fr(r)+\" found\")];var i,a=e.styleSpec,o=[];if(r.length<1)return[new Ct(n,r,\"filter array must have at least 1 element\")];switch(o=o.concat(nn({key:n+\"[0]\",value:r[0],valueSpec:a.filter_operator,style:e.style,styleSpec:e.styleSpec})),Ot(r[0])){case\"<\":case\"<=\":case\">\":case\">=\":r.length>=2&&\"$type\"===Ot(r[1])&&o.push(new Ct(n,r,'\"$type\" cannot be use with operator \"'+r[0]+'\"'));case\"==\":case\"!=\":3!==r.length&&o.push(new Ct(n,r,'filter array for operator \"'+r[0]+'\" must have 3 elements'));case\"in\":case\"!in\":r.length>=2&&\"string\"!==(i=Fr(r[1]))&&o.push(new Ct(n+\"[1]\",r[1],\"string expected, \"+i+\" 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r=t.key,n=t.style,i=t.styleSpec,a=t.value,o=t.objectKey,s=i[e+\"_\"+t.layerType];if(!s)return[];var l=o.match(/^(.*)-transition$/);if(\"paint\"===e&&l&&s[l[1]]&&s[l[1]].transition)return kn({key:r,value:a,valueSpec:i.transition,style:n,styleSpec:i});var c,u=t.valueSpec||s[o];if(!u)return[new Ct(r,a,'unknown property \"'+o+'\"')];if(\"string\"===Fr(a)&&zr(u)&&!u.tokens&&(c=/^{([^}]+)}$/.exec(a)))return[new Ct(r,a,'\"'+o+'\" does not support interpolation syntax\\nUse an identity property function instead: `{ \"type\": \"identity\", \"property\": '+JSON.stringify(c[1])+\" }`.\")];var f=[];return\"symbol\"===t.layerType&&(\"text-field\"===o&&n&&!n.glyphs&&f.push(new Ct(r,a,'use of \"text-field\" requires a style \"glyphs\" property')),\"text-font\"===o&&Br(zt(a))&&\"identity\"===Ot(a.type)&&f.push(new Ct(r,a,'\"text-font\" does not support identity 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Kr(t,e);if(Yr(t)){var r=Jr(t,e);if(\"error\"===r.result)throw new Error(r.value.map((function(t){return t.key+\": \"+t.message})).join(\", \"));return r.value}var n=t;return\"string\"==typeof t&&\"color\"===e.type&&(n=te.parse(t)),{kind:\"constant\",evaluate:function(){return n}}}(void 0===e?t.specification.default:e,t.specification)};di.prototype.isDataDriven=function(){return\"source\"===this.expression.kind||\"composite\"===this.expression.kind},di.prototype.possiblyEvaluate=function(t,e,r){return this.property.possiblyEvaluate(this,t,e,r)};var gi=function(t){this.property=t,this.value=new di(t,void 0)};gi.prototype.transitioned=function(t,e){return new vi(this.property,this.value,e,u({},t.transition,this.transition),t.now)},gi.prototype.untransitioned=function(){return new vi(this.property,this.value,null,{},0)};var mi=function(t){this._properties=t,this._values=Object.create(t.defaultTransitionablePropertyValues)};mi.prototype.getValue=function(t){return x(this._values[t].value.value)},mi.prototype.setValue=function(t,e){this._values.hasOwnProperty(t)||(this._values[t]=new gi(this._values[t].property)),this._values[t].value=new di(this._values[t].property,null===e?void 0:x(e))},mi.prototype.getTransition=function(t){return x(this._values[t].transition)},mi.prototype.setTransition=function(t,e){this._values.hasOwnProperty(t)||(this._values[t]=new gi(this._values[t].property)),this._values[t].transition=x(e)||void 0},mi.prototype.serialize=function(){for(var t={},e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e],i=this.getValue(n);void 0!==i&&(t[n]=i);var a=this.getTransition(n);void 0!==a&&(t[n+\"-transition\"]=a)}return t},mi.prototype.transitioned=function(t,e){for(var r=new yi(this._properties),n=0,i=Object.keys(this._values);n<i.length;n+=1){var a=i[n];r._values[a]=this._values[a].transitioned(t,e._values[a])}return r},mi.prototype.untransitioned=function(){for(var t=new yi(this._properties),e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e];t._values[n]=this._values[n].untransitioned()}return t};var vi=function(t,e,r,n,i){this.property=t,this.value=e,this.begin=i+n.delay||0,this.end=this.begin+n.duration||0,t.specification.transition&&(n.delay||n.duration)&&(this.prior=r)};vi.prototype.possiblyEvaluate=function(t,e,r){var n=t.now||0,i=this.value.possiblyEvaluate(t,e,r),a=this.prior;if(a){if(n>this.end)return this.prior=null,i;if(this.value.isDataDriven())return this.prior=null,i;if(n<this.begin)return a.possiblyEvaluate(t,e,r);var o=(n-this.begin)/(this.end-this.begin);return this.property.interpolate(a.possiblyEvaluate(t,e,r),i,function(t){if(t<=0)return 0;if(t>=1)return 1;var e=t*t,r=e*t;return 4*(t<.5?r:3*(t-e)+r-.75)}(o))}return i};var yi=function(t){this._properties=t,this._values=Object.create(t.defaultTransitioningPropertyValues)};yi.prototype.possiblyEvaluate=function(t,e,r){for(var n=new _i(this._properties),i=0,a=Object.keys(this._values);i<a.length;i+=1){var o=a[i];n._values[o]=this._values[o].possiblyEvaluate(t,e,r)}return n},yi.prototype.hasTransition=function(){for(var t=0,e=Object.keys(this._values);t<e.length;t+=1){var r=e[t];if(this._values[r].prior)return!0}return!1};var xi=function(t){this._properties=t,this._values=Object.create(t.defaultPropertyValues)};xi.prototype.getValue=function(t){return x(this._values[t].value)},xi.prototype.setValue=function(t,e){this._values[t]=new di(this._values[t].property,null===e?void 0:x(e))},xi.prototype.serialize=function(){for(var t={},e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e],i=this.getValue(n);void 0!==i&&(t[n]=i)}return t},xi.prototype.possiblyEvaluate=function(t,e,r){for(var n=new _i(this._properties),i=0,a=Object.keys(this._values);i<a.length;i+=1){var o=a[i];n._values[o]=this._values[o].possiblyEvaluate(t,e,r)}return n};var bi=function(t,e,r){this.property=t,this.value=e,this.parameters=r};bi.prototype.isConstant=function(){return\"constant\"===this.value.kind},bi.prototype.constantOr=function(t){return\"constant\"===this.value.kind?this.value.value:t},bi.prototype.evaluate=function(t,e,r,n){return this.property.evaluate(this.value,this.parameters,t,e,r,n)};var _i=function(t){this._properties=t,this._values=Object.create(t.defaultPossiblyEvaluatedValues)};_i.prototype.get=function(t){return this._values[t]};var wi=function(t){this.specification=t};wi.prototype.possiblyEvaluate=function(t,e){return t.expression.evaluate(e)},wi.prototype.interpolate=function(t,e,r){var n=Ge[this.specification.type];return n?n(t,e,r):t};var Ti=function(t,e){this.specification=t,this.overrides=e};Ti.prototype.possiblyEvaluate=function(t,e,r,n){return\"constant\"===t.expression.kind||\"camera\"===t.expression.kind?new bi(this,{kind:\"constant\",value:t.expression.evaluate(e,null,{},r,n)},e):new bi(this,t.expression,e)},Ti.prototype.interpolate=function(t,e,r){if(\"constant\"!==t.value.kind||\"constant\"!==e.value.kind)return t;if(void 0===t.value.value||void 0===e.value.value)return new bi(this,{kind:\"constant\",value:void 0},t.parameters);var n=Ge[this.specification.type];return n?new bi(this,{kind:\"constant\",value:n(t.value.value,e.value.value,r)},t.parameters):t},Ti.prototype.evaluate=function(t,e,r,n,i,a){return\"constant\"===t.kind?t.value:t.evaluate(e,r,n,i,a)};var ki=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.possiblyEvaluate=function(t,e,r,n){if(void 0===t.value)return new bi(this,{kind:\"constant\",value:void 0},e);if(\"constant\"===t.expression.kind){var i=t.expression.evaluate(e,null,{},r,n),a=\"resolvedImage\"===t.property.specification.type&&\"string\"!=typeof i?i.name:i,o=this._calculate(a,a,a,e);return new bi(this,{kind:\"constant\",value:o},e)}if(\"camera\"===t.expression.kind){var s=this._calculate(t.expression.evaluate({zoom:e.zoom-1}),t.expression.evaluate({zoom:e.zoom}),t.expression.evaluate({zoom:e.zoom+1}),e);return new bi(this,{kind:\"constant\",value:s},e)}return new bi(this,t.expression,e)},e.prototype.evaluate=function(t,e,r,n,i,a){if(\"source\"===t.kind){var o=t.evaluate(e,r,n,i,a);return this._calculate(o,o,o,e)}return\"composite\"===t.kind?this._calculate(t.evaluate({zoom:Math.floor(e.zoom)-1},r,n),t.evaluate({zoom:Math.floor(e.zoom)},r,n),t.evaluate({zoom:Math.floor(e.zoom)+1},r,n),e):t.value},e.prototype._calculate=function(t,e,r,n){return n.zoom>n.zoomHistory.lastIntegerZoom?{from:t,to:e}:{from:r,to:e}},e.prototype.interpolate=function(t){return t},e}(Ti),Ai=function(t){this.specification=t};Ai.prototype.possiblyEvaluate=function(t,e,r,n){if(void 0!==t.value){if(\"constant\"===t.expression.kind){var i=t.expression.evaluate(e,null,{},r,n);return this._calculate(i,i,i,e)}return this._calculate(t.expression.evaluate(new pi(Math.floor(e.zoom-1),e)),t.expression.evaluate(new pi(Math.floor(e.zoom),e)),t.expression.evaluate(new pi(Math.floor(e.zoom+1),e)),e)}},Ai.prototype._calculate=function(t,e,r,n){return n.zoom>n.zoomHistory.lastIntegerZoom?{from:t,to:e}:{from:r,to:e}},Ai.prototype.interpolate=function(t){return t};var Mi=function(t){this.specification=t};Mi.prototype.possiblyEvaluate=function(t,e,r,n){return!!t.expression.evaluate(e,null,{},r,n)},Mi.prototype.interpolate=function(){return!1};var Si=function(t){for(var e in this.properties=t,this.defaultPropertyValues={},this.defaultTransitionablePropertyValues={},this.defaultTransitioningPropertyValues={},this.defaultPossiblyEvaluatedValues={},this.overridableProperties=[],t){var r=t[e];r.specification.overridable&&this.overridableProperties.push(e);var n=this.defaultPropertyValues[e]=new di(r,void 0),i=this.defaultTransitionablePropertyValues[e]=new gi(r);this.defaultTransitioningPropertyValues[e]=i.untransitioned(),this.defaultPossiblyEvaluatedValues[e]=n.possiblyEvaluate({})}};Nn(\"DataDrivenProperty\",Ti),Nn(\"DataConstantProperty\",wi),Nn(\"CrossFadedDataDrivenProperty\",ki),Nn(\"CrossFadedProperty\",Ai),Nn(\"ColorRampProperty\",Mi);var Ei=function(t){function e(e,r){if(t.call(this),this.id=e.id,this.type=e.type,this._featureFilter={filter:function(){return!0},needGeometry:!1},\"custom\"!==e.type&&(e=e,this.metadata=e.metadata,this.minzoom=e.minzoom,this.maxzoom=e.maxzoom,\"background\"!==e.type&&(this.source=e.source,this.sourceLayer=e[\"source-layer\"],this.filter=e.filter),r.layout&&(this._unevaluatedLayout=new xi(r.layout)),r.paint)){for(var n in this._transitionablePaint=new mi(r.paint),e.paint)this.setPaintProperty(n,e.paint[n],{validate:!1});for(var i in e.layout)this.setLayoutProperty(i,e.layout[i],{validate:!1});this._transitioningPaint=this._transitionablePaint.untransitioned(),this.paint=new _i(r.paint)}}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getCrossfadeParameters=function(){return this._crossfadeParameters},e.prototype.getLayoutProperty=function(t){return\"visibility\"===t?this.visibility:this._unevaluatedLayout.getValue(t)},e.prototype.setLayoutProperty=function(t,e,r){if(void 0===r&&(r={}),null!=e){var n=\"layers.\"+this.id+\".layout.\"+t;if(this._validate(In,n,t,e,r))return}\"visibility\"!==t?this._unevaluatedLayout.setValue(t,e):this.visibility=e},e.prototype.getPaintProperty=function(t){return m(t,\"-transition\")?this._transitionablePaint.getTransition(t.slice(0,-\"-transition\".length)):this._transitionablePaint.getValue(t)},e.prototype.setPaintProperty=function(t,e,r){if(void 0===r&&(r={}),null!=e){var n=\"layers.\"+this.id+\".paint.\"+t;if(this._validate(Pn,n,t,e,r))return!1}if(m(t,\"-transition\"))return this._transitionablePaint.setTransition(t.slice(0,-\"-transition\".length),e||void 0),!1;var i=this._transitionablePaint._values[t],a=\"cross-faded-data-driven\"===i.property.specification[\"property-type\"],o=i.value.isDataDriven(),s=i.value;this._transitionablePaint.setValue(t,e),this._handleSpecialPaintPropertyUpdate(t);var l=this._transitionablePaint._values[t].value;return l.isDataDriven()||o||a||this._handleOverridablePaintPropertyUpdate(t,s,l)},e.prototype._handleSpecialPaintPropertyUpdate=function(t){},e.prototype._handleOverridablePaintPropertyUpdate=function(t,e,r){return!1},e.prototype.isHidden=function(t){return!!(this.minzoom&&t<this.minzoom)||(!!(this.maxzoom&&t>=this.maxzoom)||\"none\"===this.visibility)},e.prototype.updateTransitions=function(t){this._transitioningPaint=this._transitionablePaint.transitioned(t,this._transitioningPaint)},e.prototype.hasTransition=function(){return this._transitioningPaint.hasTransition()},e.prototype.recalculate=function(t,e){t.getCrossfadeParameters&&(this._crossfadeParameters=t.getCrossfadeParameters()),this._unevaluatedLayout&&(this.layout=this._unevaluatedLayout.possiblyEvaluate(t,void 0,e)),this.paint=this._transitioningPaint.possiblyEvaluate(t,void 0,e)},e.prototype.serialize=function(){var t={id:this.id,type:this.type,source:this.source,\"source-layer\":this.sourceLayer,metadata:this.metadata,minzoom:this.minzoom,maxzoom:this.maxzoom,filter:this.filter,layout:this._unevaluatedLayout&&this._unevaluatedLayout.serialize(),paint:this._transitionablePaint&&this._transitionablePaint.serialize()};return this.visibility&&(t.layout=t.layout||{},t.layout.visibility=this.visibility),y(t,(function(t,e){return!(void 0===t||\"layout\"===e&&!Object.keys(t).length||\"paint\"===e&&!Object.keys(t).length)}))},e.prototype._validate=function(t,e,r,n,i){return void 0===i&&(i={}),(!i||!1!==i.validate)&&On(this,t.call(Ln,{key:e,layerType:this.type,objectKey:r,value:n,styleSpec:Lt,style:{glyphs:!0,sprite:!0}}))},e.prototype.is3D=function(){return!1},e.prototype.isTileClipped=function(){return!1},e.prototype.hasOffscreenPass=function(){return!1},e.prototype.resize=function(){},e.prototype.isStateDependent=function(){for(var t in this.paint._values){var e=this.paint.get(t);if(e instanceof bi&&zr(e.property.specification)&&((\"source\"===e.value.kind||\"composite\"===e.value.kind)&&e.value.isStateDependent))return!0}return!1},e}(Et),Li={Int8:Int8Array,Uint8:Uint8Array,Int16:Int16Array,Uint16:Uint16Array,Int32:Int32Array,Uint32:Uint32Array,Float32:Float32Array},Ci=function(t,e){this._structArray=t,this._pos1=e*this.size,this._pos2=this._pos1/2,this._pos4=this._pos1/4,this._pos8=this._pos1/8},Pi=function(){this.isTransferred=!1,this.capacity=-1,this.resize(0)};function Ii(t,e){void 0===e&&(e=1);var r=0,n=0;return{members:t.map((function(t){var i,a=(i=t.type,Li[i].BYTES_PER_ELEMENT),o=r=Oi(r,Math.max(e,a)),s=t.components||1;return n=Math.max(n,a),r+=a*s,{name:t.name,type:t.type,components:s,offset:o}})),size:Oi(r,Math.max(n,e)),alignment:e}}function Oi(t,e){return Math.ceil(t/e)*e}Pi.serialize=function(t,e){return t._trim(),e&&(t.isTransferred=!0,e.push(t.arrayBuffer)),{length:t.length,arrayBuffer:t.arrayBuffer}},Pi.deserialize=function(t){var e=Object.create(this.prototype);return e.arrayBuffer=t.arrayBuffer,e.length=t.length,e.capacity=t.arrayBuffer.byteLength/e.bytesPerElement,e._refreshViews(),e},Pi.prototype._trim=function(){this.length!==this.capacity&&(this.capacity=this.length,this.arrayBuffer=this.arrayBuffer.slice(0,this.length*this.bytesPerElement),this._refreshViews())},Pi.prototype.clear=function(){this.length=0},Pi.prototype.resize=function(t){this.reserve(t),this.length=t},Pi.prototype.reserve=function(t){if(t>this.capacity){this.capacity=Math.max(t,Math.floor(5*this.capacity),128),this.arrayBuffer=new ArrayBuffer(this.capacity*this.bytesPerElement);var e=this.uint8;this._refreshViews(),e&&this.uint8.set(e)}},Pi.prototype._refreshViews=function(){throw new Error(\"_refreshViews() must be implemented by each concrete StructArray layout\")};var zi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;return this.resize(r+1),this.emplace(r,t,e)},e.prototype.emplace=function(t,e,r){var n=2*t;return this.int16[n+0]=e,this.int16[n+1]=r,t},e}(Pi);zi.prototype.bytesPerElement=4,Nn(\"StructArrayLayout2i4\",zi);var Di=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var i=this.length;return this.resize(i+1),this.emplace(i,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,i){var a=4*t;return this.int16[a+0]=e,this.int16[a+1]=r,this.int16[a+2]=n,this.int16[a+3]=i,t},e}(Pi);Di.prototype.bytesPerElement=8,Nn(\"StructArrayLayout4i8\",Di);var Ri=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,i,a)},e.prototype.emplace=function(t,e,r,n,i,a,o){var s=6*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.int16[s+2]=n,this.int16[s+3]=i,this.int16[s+4]=a,this.int16[s+5]=o,t},e}(Pi);Ri.prototype.bytesPerElement=12,Nn(\"StructArrayLayout2i4i12\",Ri);var Fi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,i,a)},e.prototype.emplace=function(t,e,r,n,i,a,o){var s=4*t,l=8*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.uint8[l+4]=n,this.uint8[l+5]=i,this.uint8[l+6]=a,this.uint8[l+7]=o,t},e}(Pi);Fi.prototype.bytesPerElement=8,Nn(\"StructArrayLayout2i4ub8\",Fi);var Bi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,c){var u=this.length;return this.resize(u+1),this.emplace(u,t,e,r,n,i,a,o,s,l,c)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c,u){var f=9*t,h=18*t;return this.uint16[f+0]=e,this.uint16[f+1]=r,this.uint16[f+2]=n,this.uint16[f+3]=i,this.uint16[f+4]=a,this.uint16[f+5]=o,this.uint16[f+6]=s,this.uint16[f+7]=l,this.uint8[h+16]=c,this.uint8[h+17]=u,t},e}(Pi);Bi.prototype.bytesPerElement=18,Nn(\"StructArrayLayout8ui2ub18\",Bi);var Ni=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,c,u,f){var h=this.length;return this.resize(h+1),this.emplace(h,t,e,r,n,i,a,o,s,l,c,u,f)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c,u,f,h){var p=12*t;return this.int16[p+0]=e,this.int16[p+1]=r,this.int16[p+2]=n,this.int16[p+3]=i,this.uint16[p+4]=a,this.uint16[p+5]=o,this.uint16[p+6]=s,this.uint16[p+7]=l,this.int16[p+8]=c,this.int16[p+9]=u,this.int16[p+10]=f,this.int16[p+11]=h,t},e}(Pi);Ni.prototype.bytesPerElement=24,Nn(\"StructArrayLayout4i4ui4i24\",Ni);var ji=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=3*t;return this.float32[i+0]=e,this.float32[i+1]=r,this.float32[i+2]=n,t},e}(Pi);ji.prototype.bytesPerElement=12,Nn(\"StructArrayLayout3f12\",ji);var Ui=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;return this.resize(e+1),this.emplace(e,t)},e.prototype.emplace=function(t,e){var r=1*t;return this.uint32[r+0]=e,t},e}(Pi);Ui.prototype.bytesPerElement=4,Nn(\"StructArrayLayout1ul4\",Ui);var Vi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l){var c=this.length;return this.resize(c+1),this.emplace(c,t,e,r,n,i,a,o,s,l)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c){var u=10*t,f=5*t;return this.int16[u+0]=e,this.int16[u+1]=r,this.int16[u+2]=n,this.int16[u+3]=i,this.int16[u+4]=a,this.int16[u+5]=o,this.uint32[f+3]=s,this.uint16[u+8]=l,this.uint16[u+9]=c,t},e}(Pi);Vi.prototype.bytesPerElement=20,Nn(\"StructArrayLayout6i1ul2ui20\",Vi);var qi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,i,a)},e.prototype.emplace=function(t,e,r,n,i,a,o){var s=6*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.int16[s+2]=n,this.int16[s+3]=i,this.int16[s+4]=a,this.int16[s+5]=o,t},e}(Pi);qi.prototype.bytesPerElement=12,Nn(\"StructArrayLayout2i2i2i12\",qi);var Hi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i){var a=this.length;return this.resize(a+1),this.emplace(a,t,e,r,n,i)},e.prototype.emplace=function(t,e,r,n,i,a){var o=4*t,s=8*t;return this.float32[o+0]=e,this.float32[o+1]=r,this.float32[o+2]=n,this.int16[s+6]=i,this.int16[s+7]=a,t},e}(Pi);Hi.prototype.bytesPerElement=16,Nn(\"StructArrayLayout2f1f2i16\",Hi);var Gi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var i=this.length;return this.resize(i+1),this.emplace(i,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,i){var a=12*t,o=3*t;return this.uint8[a+0]=e,this.uint8[a+1]=r,this.float32[o+1]=n,this.float32[o+2]=i,t},e}(Pi);Gi.prototype.bytesPerElement=12,Nn(\"StructArrayLayout2ub2f12\",Gi);var Yi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=3*t;return this.uint16[i+0]=e,this.uint16[i+1]=r,this.uint16[i+2]=n,t},e}(Pi);Yi.prototype.bytesPerElement=6,Nn(\"StructArrayLayout3ui6\",Yi);var Wi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g,m){var v=this.length;return this.resize(v+1),this.emplace(v,t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g,m)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g,m,v){var y=24*t,x=12*t,b=48*t;return this.int16[y+0]=e,this.int16[y+1]=r,this.uint16[y+2]=n,this.uint16[y+3]=i,this.uint32[x+2]=a,this.uint32[x+3]=o,this.uint32[x+4]=s,this.uint16[y+10]=l,this.uint16[y+11]=c,this.uint16[y+12]=u,this.float32[x+7]=f,this.float32[x+8]=h,this.uint8[b+36]=p,this.uint8[b+37]=d,this.uint8[b+38]=g,this.uint32[x+10]=m,this.int16[y+22]=v,t},e}(Pi);Wi.prototype.bytesPerElement=48,Nn(\"StructArrayLayout2i2ui3ul3ui2f3ub1ul1i48\",Wi);var Xi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g,m,v,y,x,b,_,w,T,k,A,M,S){var E=this.length;return this.resize(E+1),this.emplace(E,t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g,m,v,y,x,b,_,w,T,k,A,M,S)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g,m,v,y,x,b,_,w,T,k,A,M,S,E){var L=34*t,C=17*t;return this.int16[L+0]=e,this.int16[L+1]=r,this.int16[L+2]=n,this.int16[L+3]=i,this.int16[L+4]=a,this.int16[L+5]=o,this.int16[L+6]=s,this.int16[L+7]=l,this.uint16[L+8]=c,this.uint16[L+9]=u,this.uint16[L+10]=f,this.uint16[L+11]=h,this.uint16[L+12]=p,this.uint16[L+13]=d,this.uint16[L+14]=g,this.uint16[L+15]=m,this.uint16[L+16]=v,this.uint16[L+17]=y,this.uint16[L+18]=x,this.uint16[L+19]=b,this.uint16[L+20]=_,this.uint16[L+21]=w,this.uint16[L+22]=T,this.uint32[C+12]=k,this.float32[C+13]=A,this.float32[C+14]=M,this.float32[C+15]=S,this.float32[C+16]=E,t},e}(Pi);Xi.prototype.bytesPerElement=68,Nn(\"StructArrayLayout8i15ui1ul4f68\",Xi);var Zi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;return this.resize(e+1),this.emplace(e,t)},e.prototype.emplace=function(t,e){var r=1*t;return this.float32[r+0]=e,t},e}(Pi);Zi.prototype.bytesPerElement=4,Nn(\"StructArrayLayout1f4\",Zi);var Ji=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=3*t;return this.int16[i+0]=e,this.int16[i+1]=r,this.int16[i+2]=n,t},e}(Pi);Ji.prototype.bytesPerElement=6,Nn(\"StructArrayLayout3i6\",Ji);var Ki=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=2*t,a=4*t;return this.uint32[i+0]=e,this.uint16[a+2]=r,this.uint16[a+3]=n,t},e}(Pi);Ki.prototype.bytesPerElement=8,Nn(\"StructArrayLayout1ul2ui8\",Ki);var Qi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;return this.resize(r+1),this.emplace(r,t,e)},e.prototype.emplace=function(t,e,r){var n=2*t;return this.uint16[n+0]=e,this.uint16[n+1]=r,t},e}(Pi);Qi.prototype.bytesPerElement=4,Nn(\"StructArrayLayout2ui4\",Qi);var $i=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;return this.resize(e+1),this.emplace(e,t)},e.prototype.emplace=function(t,e){var r=1*t;return this.uint16[r+0]=e,t},e}(Pi);$i.prototype.bytesPerElement=2,Nn(\"StructArrayLayout1ui2\",$i);var ta=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;return this.resize(r+1),this.emplace(r,t,e)},e.prototype.emplace=function(t,e,r){var n=2*t;return this.float32[n+0]=e,this.float32[n+1]=r,t},e}(Pi);ta.prototype.bytesPerElement=8,Nn(\"StructArrayLayout2f8\",ta);var ea=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var i=this.length;return this.resize(i+1),this.emplace(i,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,i){var a=4*t;return this.float32[a+0]=e,this.float32[a+1]=r,this.float32[a+2]=n,this.float32[a+3]=i,t},e}(Pi);ea.prototype.bytesPerElement=16,Nn(\"StructArrayLayout4f16\",ea);var ra=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={anchorPointX:{configurable:!0},anchorPointY:{configurable:!0},x1:{configurable:!0},y1:{configurable:!0},x2:{configurable:!0},y2:{configurable:!0},featureIndex:{configurable:!0},sourceLayerIndex:{configurable:!0},bucketIndex:{configurable:!0},anchorPoint:{configurable:!0}};return r.anchorPointX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorPointY.get=function(){return this._structArray.int16[this._pos2+1]},r.x1.get=function(){return this._structArray.int16[this._pos2+2]},r.y1.get=function(){return this._structArray.int16[this._pos2+3]},r.x2.get=function(){return this._structArray.int16[this._pos2+4]},r.y2.get=function(){return this._structArray.int16[this._pos2+5]},r.featureIndex.get=function(){return this._structArray.uint32[this._pos4+3]},r.sourceLayerIndex.get=function(){return this._structArray.uint16[this._pos2+8]},r.bucketIndex.get=function(){return this._structArray.uint16[this._pos2+9]},r.anchorPoint.get=function(){return new i(this.anchorPointX,this.anchorPointY)},Object.defineProperties(e.prototype,r),e}(Ci);ra.prototype.size=20;var na=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.get=function(t){return new ra(this,t)},e}(Vi);Nn(\"CollisionBoxArray\",na);var ia=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={anchorX:{configurable:!0},anchorY:{configurable:!0},glyphStartIndex:{configurable:!0},numGlyphs:{configurable:!0},vertexStartIndex:{configurable:!0},lineStartIndex:{configurable:!0},lineLength:{configurable:!0},segment:{configurable:!0},lowerSize:{configurable:!0},upperSize:{configurable:!0},lineOffsetX:{configurable:!0},lineOffsetY:{configurable:!0},writingMode:{configurable:!0},placedOrientation:{configurable:!0},hidden:{configurable:!0},crossTileID:{configurable:!0},associatedIconIndex:{configurable:!0}};return r.anchorX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorY.get=function(){return this._structArray.int16[this._pos2+1]},r.glyphStartIndex.get=function(){return this._structArray.uint16[this._pos2+2]},r.numGlyphs.get=function(){return this._structArray.uint16[this._pos2+3]},r.vertexStartIndex.get=function(){return this._structArray.uint32[this._pos4+2]},r.lineStartIndex.get=function(){return this._structArray.uint32[this._pos4+3]},r.lineLength.get=function(){return this._structArray.uint32[this._pos4+4]},r.segment.get=function(){return this._structArray.uint16[this._pos2+10]},r.lowerSize.get=function(){return this._structArray.uint16[this._pos2+11]},r.upperSize.get=function(){return this._structArray.uint16[this._pos2+12]},r.lineOffsetX.get=function(){return this._structArray.float32[this._pos4+7]},r.lineOffsetY.get=function(){return this._structArray.float32[this._pos4+8]},r.writingMode.get=function(){return this._structArray.uint8[this._pos1+36]},r.placedOrientation.get=function(){return this._structArray.uint8[this._pos1+37]},r.placedOrientation.set=function(t){this._structArray.uint8[this._pos1+37]=t},r.hidden.get=function(){return this._structArray.uint8[this._pos1+38]},r.hidden.set=function(t){this._structArray.uint8[this._pos1+38]=t},r.crossTileID.get=function(){return this._structArray.uint32[this._pos4+10]},r.crossTileID.set=function(t){this._structArray.uint32[this._pos4+10]=t},r.associatedIconIndex.get=function(){return this._structArray.int16[this._pos2+22]},Object.defineProperties(e.prototype,r),e}(Ci);ia.prototype.size=48;var aa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.get=function(t){return new ia(this,t)},e}(Wi);Nn(\"PlacedSymbolArray\",aa);var oa=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={anchorX:{configurable:!0},anchorY:{configurable:!0},rightJustifiedTextSymbolIndex:{configurable:!0},centerJustifiedTextSymbolIndex:{configurable:!0},leftJustifiedTextSymbolIndex:{configurable:!0},verticalPlacedTextSymbolIndex:{configurable:!0},placedIconSymbolIndex:{configurable:!0},verticalPlacedIconSymbolIndex:{configurable:!0},key:{configurable:!0},textBoxStartIndex:{configurable:!0},textBoxEndIndex:{configurable:!0},verticalTextBoxStartIndex:{configurable:!0},verticalTextBoxEndIndex:{configurable:!0},iconBoxStartIndex:{configurable:!0},iconBoxEndIndex:{configurable:!0},verticalIconBoxStartIndex:{configurable:!0},verticalIconBoxEndIndex:{configurable:!0},featureIndex:{configurable:!0},numHorizontalGlyphVertices:{configurable:!0},numVerticalGlyphVertices:{configurable:!0},numIconVertices:{configurable:!0},numVerticalIconVertices:{configurable:!0},useRuntimeCollisionCircles:{configurable:!0},crossTileID:{configurable:!0},textBoxScale:{configurable:!0},textOffset0:{configurable:!0},textOffset1:{configurable:!0},collisionCircleDiameter:{configurable:!0}};return r.anchorX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorY.get=function(){return this._structArray.int16[this._pos2+1]},r.rightJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+2]},r.centerJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+3]},r.leftJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+4]},r.verticalPlacedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+5]},r.placedIconSymbolIndex.get=function(){return this._structArray.int16[this._pos2+6]},r.verticalPlacedIconSymbolIndex.get=function(){return this._structArray.int16[this._pos2+7]},r.key.get=function(){return this._structArray.uint16[this._pos2+8]},r.textBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+9]},r.textBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+10]},r.verticalTextBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+11]},r.verticalTextBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+12]},r.iconBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+13]},r.iconBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+14]},r.verticalIconBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+15]},r.verticalIconBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+16]},r.featureIndex.get=function(){return this._structArray.uint16[this._pos2+17]},r.numHorizontalGlyphVertices.get=function(){return this._structArray.uint16[this._pos2+18]},r.numVerticalGlyphVertices.get=function(){return this._structArray.uint16[this._pos2+19]},r.numIconVertices.get=function(){return this._structArray.uint16[this._pos2+20]},r.numVerticalIconVertices.get=function(){return this._structArray.uint16[this._pos2+21]},r.useRuntimeCollisionCircles.get=function(){return this._structArray.uint16[this._pos2+22]},r.crossTileID.get=function(){return this._structArray.uint32[this._pos4+12]},r.crossTileID.set=function(t){this._structArray.uint32[this._pos4+12]=t},r.textBoxScale.get=function(){return this._structArray.float32[this._pos4+13]},r.textOffset0.get=function(){return this._structArray.float32[this._pos4+14]},r.textOffset1.get=function(){return this._structArray.float32[this._pos4+15]},r.collisionCircleDiameter.get=function(){return this._structArray.float32[this._pos4+16]},Object.defineProperties(e.prototype,r),e}(Ci);oa.prototype.size=68;var sa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.get=function(t){return new oa(this,t)},e}(Xi);Nn(\"SymbolInstanceArray\",sa);var la=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getoffsetX=function(t){return this.float32[1*t+0]},e}(Zi);Nn(\"GlyphOffsetArray\",la);var ca=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getx=function(t){return this.int16[3*t+0]},e.prototype.gety=function(t){return this.int16[3*t+1]},e.prototype.gettileUnitDistanceFromAnchor=function(t){return this.int16[3*t+2]},e}(Ji);Nn(\"SymbolLineVertexArray\",ca);var ua=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={featureIndex:{configurable:!0},sourceLayerIndex:{configurable:!0},bucketIndex:{configurable:!0}};return r.featureIndex.get=function(){return this._structArray.uint32[this._pos4+0]},r.sourceLayerIndex.get=function(){return 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t.paint._values)if(r(a)){var o=t.paint.get(a);if(o instanceof bi&&zr(o.property.specification)){var s=Va(a,t.type),l=o.value,c=o.property.specification.type,u=o.property.useIntegerZoom,f=o.property.specification[\"property-type\"],h=\"cross-faded\"===f||\"cross-faded-data-driven\"===f;if(\"constant\"===l.kind)this.binders[a]=h?new Ra(l.value,s):new Da(l.value,s,c),i.push(\"/u_\"+a);else if(\"source\"===l.kind||h){var p=qa(a,c,\"source\");this.binders[a]=h?new Na(l,c,u,e,p,t.id):new Fa(l,s,c,p),i.push(\"/a_\"+a)}else{var d=qa(a,c,\"composite\");this.binders[a]=new Ba(l,s,c,u,e,d),i.push(\"/z_\"+a)}}}this.cacheKey=i.sort().join(\"\")};ja.prototype.getMaxValue=function(t){var e=this.binders[t];return e instanceof Fa||e instanceof Ba?e.maxValue:0},ja.prototype.populatePaintArrays=function(t,e,r,n,i){for(var a in this.binders){var o=this.binders[a];(o instanceof Fa||o instanceof Ba||o instanceof Na)&&o.populatePaintArray(t,e,r,n,i)}},ja.prototype.setConstantPatternPositions=function(t,e){for(var r in this.binders){var n=this.binders[r];n instanceof Ra&&n.setConstantPatternPositions(t,e)}},ja.prototype.updatePaintArrays=function(t,e,r,n,i){var a=!1;for(var o in t)for(var s=0,l=e.getPositions(o);s<l.length;s+=1){var c=l[s],u=r.feature(c.index);for(var f in this.binders){var h=this.binders[f];if((h instanceof Fa||h instanceof Ba||h instanceof Na)&&!0===h.expression.isStateDependent){var p=n.paint.get(f);h.expression=p.value,h.updatePaintArray(c.start,c.end,u,t[o],i),a=!0}}}return a},ja.prototype.defines=function(){var t=[];for(var e in this.binders){var r=this.binders[e];(r instanceof Da||r instanceof Ra)&&t.push.apply(t,r.uniformNames.map((function(t){return\"#define HAS_UNIFORM_\"+t})))}return t},ja.prototype.getPaintVertexBuffers=function(){return this._buffers},ja.prototype.getUniforms=function(t,e){var r=[];for(var n in this.binders){var i=this.binders[n];if(i instanceof Da||i instanceof Ra||i instanceof Ba)for(var a=0,o=i.uniformNames;a<o.length;a+=1){var s=o[a];if(e[s]){var l=i.getBinding(t,e[s],s);r.push({name:s,property:n,binding:l})}}}return r},ja.prototype.setUniforms=function(t,e,r,n){for(var i=0,a=e;i<a.length;i+=1){var o=a[i],s=o.name,l=o.property,c=o.binding;this.binders[l].setUniform(c,n,r.get(l),s)}},ja.prototype.updatePaintBuffers=function(t){for(var e in this._buffers=[],this.binders){var r=this.binders[e];if(t&&r instanceof Na){var n=2===t.fromScale?r.zoomInPaintVertexBuffer:r.zoomOutPaintVertexBuffer;n&&this._buffers.push(n)}else(r instanceof Fa||r instanceof Ba)&&r.paintVertexBuffer&&this._buffers.push(r.paintVertexBuffer)}},ja.prototype.upload=function(t){for(var e in this.binders){var r=this.binders[e];(r instanceof Fa||r instanceof Ba||r instanceof Na)&&r.upload(t)}this.updatePaintBuffers()},ja.prototype.destroy=function(){for(var t in this.binders){var e=this.binders[t];(e instanceof Fa||e instanceof Ba||e instanceof Na)&&e.destroy()}};var Ua=function(t,e,r,n){void 0===n&&(n=function(){return!0}),this.programConfigurations={};for(var i=0,a=e;i<a.length;i+=1){var o=a[i];this.programConfigurations[o.id]=new ja(o,r,n,t)}this.needsUpload=!1,this._featureMap=new _a,this._bufferOffset=0};function Va(t,e){return{\"text-opacity\":[\"opacity\"],\"icon-opacity\":[\"opacity\"],\"text-color\":[\"fill_color\"],\"icon-color\":[\"fill_color\"],\"text-halo-color\":[\"halo_color\"],\"icon-halo-color\":[\"halo_color\"],\"text-halo-blur\":[\"halo_blur\"],\"icon-halo-blur\":[\"halo_blur\"],\"text-halo-width\":[\"halo_width\"],\"icon-halo-width\":[\"halo_width\"],\"line-gap-width\":[\"gapwidth\"],\"line-pattern\":[\"pattern_to\",\"pattern_from\",\"pixel_ratio_to\",\"pixel_ratio_from\"],\"fill-pattern\":[\"pattern_to\",\"pattern_from\",\"pixel_ratio_to\",\"pixel_ratio_from\"],\"fill-extrusion-pattern\":[\"pattern_to\",\"pattern_from\",\"pixel_ratio_to\",\"pixel_ratio_from\"]}[t]||[t.replace(e+\"-\",\"\").replace(/-/g,\"_\")]}function qa(t,e,r){var n={color:{source:ta,composite:ea},number:{source:Zi,composite:ta}},i=function(t){return{\"line-pattern\":{source:Bi,composite:Bi},\"fill-pattern\":{source:Bi,composite:Bi},\"fill-extrusion-pattern\":{source:Bi,composite:Bi}}[t]}(t);return 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c=t.readVarint();n=7&c,a=c>>3}if(a--,1===n||2===n)o+=t.readSVarint(),s+=t.readSVarint(),1===n&&(e&&l.push(e),e=[]),e.push(new i(o,s));else{if(7!==n)throw new Error(\"unknown command \"+n);e&&e.push(e[0].clone())}}return e&&l.push(e),l},ws.prototype.bbox=function(){var t=this._pbf;t.pos=this._geometry;for(var e=t.readVarint()+t.pos,r=1,n=0,i=0,a=0,o=1/0,s=-1/0,l=1/0,c=-1/0;t.pos<e;){if(n<=0){var u=t.readVarint();r=7&u,n=u>>3}if(n--,1===r||2===r)(i+=t.readSVarint())<o&&(o=i),i>s&&(s=i),(a+=t.readSVarint())<l&&(l=a),a>c&&(c=a);else if(7!==r)throw new Error(\"unknown command \"+r)}return[o,l,s,c]},ws.prototype.toGeoJSON=function(t,e,r){var n,i,a=this.extent*Math.pow(2,r),o=this.extent*t,s=this.extent*e,l=this.loadGeometry(),c=ws.types[this.type];function u(t){for(var e=0;e<t.length;e++){var r=t[e],n=180-360*(r.y+s)/a;t[e]=[360*(r.x+o)/a-180,360/Math.PI*Math.atan(Math.exp(n*Math.PI/180))-90]}}switch(this.type){case 1:var f=[];for(n=0;n<l.length;n++)f[n]=l[n][0];u(l=f);break;case 2:for(n=0;n<l.length;n++)u(l[n]);break;case 3:for(l=function(t){var e=t.length;if(e<=1)return[t];for(var r,n,i=[],a=0;a<e;a++){var o=ks(t[a]);0!==o&&(void 0===n&&(n=o<0),n===o<0?(r&&i.push(r),r=[t[a]]):r.push(t[a]))}r&&i.push(r);return i}(l),n=0;n<l.length;n++)for(i=0;i<l[n].length;i++)u(l[n][i])}1===l.length?l=l[0]:c=\"Multi\"+c;var h={type:\"Feature\",geometry:{type:c,coordinates:l},properties:this.properties};return\"id\"in this&&(h.id=this.id),h};var As=Ms;function Ms(t,e){this.version=1,this.name=null,this.extent=4096,this.length=0,this._pbf=t,this._keys=[],this._values=[],this._features=[],t.readFields(Ss,this,e),this.length=this._features.length}function Ss(t,e,r){15===t?e.version=r.readVarint():1===t?e.name=r.readString():5===t?e.extent=r.readVarint():2===t?e._features.push(r.pos):3===t?e._keys.push(r.readString()):4===t&&e._values.push(function(t){var e=null,r=t.readVarint()+t.pos;for(;t.pos<r;){var n=t.readVarint()>>3;e=1===n?t.readString():2===n?t.readFloat():3===n?t.readDouble():4===n?t.readVarint64():5===n?t.readVarint():6===n?t.readSVarint():7===n?t.readBoolean():null}return e}(r))}function Es(t,e,r){if(3===t){var n=new As(r,r.readVarint()+r.pos);n.length&&(e[n.name]=n)}}Ms.prototype.feature=function(t){if(t<0||t>=this._features.length)throw new Error(\"feature index out of bounds\");this._pbf.pos=this._features[t];var e=this._pbf.readVarint()+this._pbf.pos;return new _s(this._pbf,e,this.extent,this._keys,this._values)};var Ls={VectorTile:function(t,e){this.layers=t.readFields(Es,{},e)},VectorTileFeature:_s,VectorTileLayer:As},Cs=Ls.VectorTileFeature.types,Ps=Math.pow(2,13);function Is(t,e,r,n,i,a,o,s){t.emplaceBack(e,r,2*Math.floor(n*Ps)+o,i*Ps*2,a*Ps*2,Math.round(s))}var Os=function(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.hasPattern=!1,this.layoutVertexArray=new Ri,this.indexArray=new Yi,this.programConfigurations=new Ua(bs,t.layers,t.zoom),this.segments=new pa,this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id}))};function zs(t,e){return t.x===e.x&&(t.x<0||t.x>8192)||t.y===e.y&&(t.y<0||t.y>8192)}function Ds(t){return t.every((function(t){return t.x<0}))||t.every((function(t){return t.x>8192}))||t.every((function(t){return t.y<0}))||t.every((function(t){return t.y>8192}))}Os.prototype.populate=function(t,e,r){this.features=[],this.hasPattern=ds(\"fill-extrusion\",this.layers,e);for(var n=0,i=t;n<i.length;n+=1){var a=i[n],o=a.feature,s=a.id,l=a.index,c=a.sourceLayerIndex,u=this.layers[0]._featureFilter.needGeometry,f={type:o.type,id:s,properties:o.properties,geometry:u?Ya(o):[]};if(this.layers[0]._featureFilter.filter(new pi(this.zoom),f,r)){var h={id:s,sourceLayerIndex:c,index:l,geometry:u?f.geometry:Ya(o),properties:o.properties,type:o.type,patterns:{}};void 0!==o.id&&(h.id=o.id),this.hasPattern?this.features.push(gs(\"fill-extrusion\",this.layers,h,this.zoom,e)):this.addFeature(h,h.geometry,l,r,{}),e.featureIndex.insert(o,h.geometry,l,c,this.index,!0)}}},Os.prototype.addFeatures=function(t,e,r){for(var n=0,i=this.features;n<i.length;n+=1){var a=i[n],o=a.geometry;this.addFeature(a,o,a.index,e,r)}},Os.prototype.update=function(t,e,r){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(t,e,this.stateDependentLayers,r)},Os.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length},Os.prototype.uploadPending=function(){return!this.uploaded||this.programConfigurations.needsUpload},Os.prototype.upload=function(t){this.uploaded||(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,bs),this.indexBuffer=t.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(t),this.uploaded=!0},Os.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())},Os.prototype.addFeature=function(t,e,r,n,i){for(var a=0,o=hs(e,500);a<o.length;a+=1){for(var s=o[a],l=0,c=0,u=s;c<u.length;c+=1){l+=u[c].length}for(var f=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray),h=0,p=s;h<p.length;h+=1){var d=p[h];if(0!==d.length&&!Ds(d))for(var g=0,m=0;m<d.length;m++){var v=d[m];if(m>=1){var y=d[m-1];if(!zs(v,y)){f.vertexLength+4>pa.MAX_VERTEX_ARRAY_LENGTH&&(f=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray));var x=v.sub(y)._perp()._unit(),b=y.dist(v);g+b>32768&&(g=0),Is(this.layoutVertexArray,v.x,v.y,x.x,x.y,0,0,g),Is(this.layoutVertexArray,v.x,v.y,x.x,x.y,0,1,g),g+=b,Is(this.layoutVertexArray,y.x,y.y,x.x,x.y,0,0,g),Is(this.layoutVertexArray,y.x,y.y,x.x,x.y,0,1,g);var _=f.vertexLength;this.indexArray.emplaceBack(_,_+2,_+1),this.indexArray.emplaceBack(_+1,_+2,_+3),f.vertexLength+=4,f.primitiveLength+=2}}}}if(f.vertexLength+l>pa.MAX_VERTEX_ARRAY_LENGTH&&(f=this.segments.prepareSegment(l,this.layoutVertexArray,this.indexArray)),\"Polygon\"===Cs[t.type]){for(var w=[],T=[],k=f.vertexLength,A=0,M=s;A<M.length;A+=1){var S=M[A];if(0!==S.length){S!==s[0]&&T.push(w.length/2);for(var E=0;E<S.length;E++){var L=S[E];Is(this.layoutVertexArray,L.x,L.y,0,0,1,1,0),w.push(L.x),w.push(L.y)}}}for(var C=Do(w,T),P=0;P<C.length;P+=3)this.indexArray.emplaceBack(k+C[P],k+C[P+2],k+C[P+1]);f.primitiveLength+=C.length/3,f.vertexLength+=l}}this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,t,r,i,n)},Nn(\"FillExtrusionBucket\",Os,{omit:[\"layers\",\"features\"]});var Rs={paint:new Si({\"fill-extrusion-opacity\":new wi(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-opacity\"]),\"fill-extrusion-color\":new Ti(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-color\"]),\"fill-extrusion-translate\":new wi(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-translate\"]),\"fill-extrusion-translate-anchor\":new wi(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-translate-anchor\"]),\"fill-extrusion-pattern\":new ki(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-pattern\"]),\"fill-extrusion-height\":new Ti(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-height\"]),\"fill-extrusion-base\":new Ti(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-base\"]),\"fill-extrusion-vertical-gradient\":new wi(Lt[\"paint_fill-extrusion\"][\"fill-extrusion-vertical-gradient\"])})},Fs=function(t){function e(e){t.call(this,e,Rs)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.createBucket=function(t){return new Os(t)},e.prototype.queryRadius=function(){return so(this.paint.get(\"fill-extrusion-translate\"))},e.prototype.is3D=function(){return!0},e.prototype.queryIntersectsFeature=function(t,e,r,n,a,o,s,l){var c=lo(t,this.paint.get(\"fill-extrusion-translate\"),this.paint.get(\"fill-extrusion-translate-anchor\"),o.angle,s),u=this.paint.get(\"fill-extrusion-height\").evaluate(e,r),f=this.paint.get(\"fill-extrusion-base\").evaluate(e,r),h=function(t,e,r,n){for(var a=[],o=0,s=t;o<s.length;o+=1){var l=s[o],c=[l.x,l.y,n,1];xo(c,c,e),a.push(new i(c[0]/c[3],c[1]/c[3]))}return a}(c,l,0,0),p=function(t,e,r,n){for(var a=[],o=[],s=n[8]*e,l=n[9]*e,c=n[10]*e,u=n[11]*e,f=n[8]*r,h=n[9]*r,p=n[10]*r,d=n[11]*r,g=0,m=t;g<m.length;g+=1){for(var v=m[g],y=[],x=[],b=0,_=v;b<_.length;b+=1){var w=_[b],T=w.x,k=w.y,A=n[0]*T+n[4]*k+n[12],M=n[1]*T+n[5]*k+n[13],S=n[2]*T+n[6]*k+n[14],E=n[3]*T+n[7]*k+n[15],L=S+c,C=E+u,P=A+f,I=M+h,O=S+p,z=E+d,D=new i((A+s)/C,(M+l)/C);D.z=L/C,y.push(D);var R=new i(P/z,I/z);R.z=O/z,x.push(R)}a.push(y),o.push(x)}return[a,o]}(n,f,u,l);return function(t,e,r){var n=1/0;Ka(r,e)&&(n=Ns(r,e[0]));for(var i=0;i<e.length;i++)for(var a=e[i],o=t[i],s=0;s<a.length-1;s++){var l=a[s],c=a[s+1],u=o[s],f=o[s+1],h=[l,c,f,u,l];Za(r,h)&&(n=Math.min(n,Ns(r,h)))}return n!==1/0&&n}(p[0],p[1],h)},e}(Ei);function Bs(t,e){return t.x*e.x+t.y*e.y}function Ns(t,e){if(1===t.length){for(var r,n=0,i=e[n++];!r||i.equals(r);)if(!(r=e[n++]))return 1/0;for(;n<e.length;n++){var a=e[n],o=t[0],s=r.sub(i),l=a.sub(i),c=o.sub(i),u=Bs(s,s),f=Bs(s,l),h=Bs(l,l),p=Bs(c,s),d=Bs(c,l),g=u*h-f*f,m=(h*p-f*d)/g,v=(u*d-f*p)/g,y=1-m-v,x=i.z*y+r.z*m+a.z*v;if(isFinite(x))return x}return 1/0}for(var b=1/0,_=0,w=e;_<w.length;_+=1){var T=w[_];b=Math.min(b,T.z)}return b}var js=Ii([{name:\"a_pos_normal\",components:2,type:\"Int16\"},{name:\"a_data\",components:4,type:\"Uint8\"}],4).members,Us=Ls.VectorTileFeature.types,Vs=Math.cos(Math.PI/180*37.5),qs=Math.pow(2,14)/.5,Hs=function(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.hasPattern=!1,this.patternFeatures=[],this.layoutVertexArray=new Fi,this.indexArray=new Yi,this.programConfigurations=new Ua(js,t.layers,t.zoom),this.segments=new pa,this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id}))};Hs.prototype.populate=function(t,e,r){this.hasPattern=ds(\"line\",this.layers,e);for(var n=this.layers[0].layout.get(\"line-sort-key\"),i=[],a=0,o=t;a<o.length;a+=1){var s=o[a],l=s.feature,c=s.id,u=s.index,f=s.sourceLayerIndex,h=this.layers[0]._featureFilter.needGeometry,p={type:l.type,id:c,properties:l.properties,geometry:h?Ya(l):[]};if(this.layers[0]._featureFilter.filter(new pi(this.zoom),p,r)){h||(p.geometry=Ya(l));var d=n?n.evaluate(p,{},r):void 0,g={id:c,properties:l.properties,type:l.type,sourceLayerIndex:f,index:u,geometry:p.geometry,patterns:{},sortKey:d};i.push(g)}}n&&i.sort((function(t,e){return t.sortKey-e.sortKey}));for(var m=0,v=i;m<v.length;m+=1){var y=v[m],x=y,b=x.geometry,_=x.index,w=x.sourceLayerIndex;if(this.hasPattern){var T=gs(\"line\",this.layers,y,this.zoom,e);this.patternFeatures.push(T)}else this.addFeature(y,b,_,r,{});var k=t[_].feature;e.featureIndex.insert(k,b,_,w,this.index)}},Hs.prototype.update=function(t,e,r){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(t,e,this.stateDependentLayers,r)},Hs.prototype.addFeatures=function(t,e,r){for(var n=0,i=this.patternFeatures;n<i.length;n+=1){var a=i[n];this.addFeature(a,a.geometry,a.index,e,r)}},Hs.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length},Hs.prototype.uploadPending=function(){return!this.uploaded||this.programConfigurations.needsUpload},Hs.prototype.upload=function(t){this.uploaded||(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,js),this.indexBuffer=t.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(t),this.uploaded=!0},Hs.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())},Hs.prototype.addFeature=function(t,e,r,n,i){for(var a=this.layers[0].layout,o=a.get(\"line-join\").evaluate(t,{}),s=a.get(\"line-cap\"),l=a.get(\"line-miter-limit\"),c=a.get(\"line-round-limit\"),u=0,f=e;u<f.length;u+=1){var h=f[u];this.addLine(h,t,o,s,l,c)}this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,t,r,i,n)},Hs.prototype.addLine=function(t,e,r,n,i,a){if(this.distance=0,this.scaledDistance=0,this.totalDistance=0,e.properties&&e.properties.hasOwnProperty(\"mapbox_clip_start\")&&e.properties.hasOwnProperty(\"mapbox_clip_end\")){this.clipStart=+e.properties.mapbox_clip_start,this.clipEnd=+e.properties.mapbox_clip_end;for(var o=0;o<t.length-1;o++)this.totalDistance+=t[o].dist(t[o+1]);this.updateScaledDistance()}for(var s=\"Polygon\"===Us[e.type],l=t.length;l>=2&&t[l-1].equals(t[l-2]);)l--;for(var c=0;c<l-1&&t[c].equals(t[c+1]);)c++;if(!(l<(s?3:2))){\"bevel\"===r&&(i=1.05);var u,f=this.overscaling<=16?122880/(512*this.overscaling):0,h=this.segments.prepareSegment(10*l,this.layoutVertexArray,this.indexArray),p=void 0,d=void 0,g=void 0,m=void 0;this.e1=this.e2=-1,s&&(u=t[l-2],m=t[c].sub(u)._unit()._perp());for(var v=c;v<l;v++)if(!(d=v===l-1?s?t[c+1]:void 0:t[v+1])||!t[v].equals(d)){m&&(g=m),u&&(p=u),u=t[v],m=d?d.sub(u)._unit()._perp():g;var y=(g=g||m).add(m);0===y.x&&0===y.y||y._unit();var x=g.x*m.x+g.y*m.y,b=y.x*m.x+y.y*m.y,_=0!==b?1/b:1/0,w=2*Math.sqrt(2-2*b),T=b<Vs&&p&&d,k=g.x*m.y-g.y*m.x>0;if(T&&v>c){var A=u.dist(p);if(A>2*f){var M=u.sub(u.sub(p)._mult(f/A)._round());this.updateDistance(p,M),this.addCurrentVertex(M,g,0,0,h),p=M}}var S=p&&d,E=S?r:s?\"butt\":n;if(S&&\"round\"===E&&(_<a?E=\"miter\":_<=2&&(E=\"fakeround\")),\"miter\"===E&&_>i&&(E=\"bevel\"),\"bevel\"===E&&(_>2&&(E=\"flipbevel\"),_<i&&(E=\"miter\")),p&&this.updateDistance(p,u),\"miter\"===E)y._mult(_),this.addCurrentVertex(u,y,0,0,h);else if(\"flipbevel\"===E){if(_>100)y=m.mult(-1);else{var L=_*g.add(m).mag()/g.sub(m).mag();y._perp()._mult(L*(k?-1:1))}this.addCurrentVertex(u,y,0,0,h),this.addCurrentVertex(u,y.mult(-1),0,0,h)}else if(\"bevel\"===E||\"fakeround\"===E){var C=-Math.sqrt(_*_-1),P=k?C:0,I=k?0:C;if(p&&this.addCurrentVertex(u,g,P,I,h),\"fakeround\"===E)for(var O=Math.round(180*w/Math.PI/20),z=1;z<O;z++){var D=z/O;if(.5!==D){var R=D-.5;D+=D*R*(D-1)*((1.0904+x*(x*(3.55645-1.43519*x)-3.2452))*R*R+(.848013+x*(.215638*x-1.06021)))}var F=m.sub(g)._mult(D)._add(g)._unit()._mult(k?-1:1);this.addHalfVertex(u,F.x,F.y,!1,k,0,h)}d&&this.addCurrentVertex(u,m,-P,-I,h)}else if(\"butt\"===E)this.addCurrentVertex(u,y,0,0,h);else if(\"square\"===E){var B=p?1:-1;this.addCurrentVertex(u,y,B,B,h)}else\"round\"===E&&(p&&(this.addCurrentVertex(u,g,0,0,h),this.addCurrentVertex(u,g,1,1,h,!0)),d&&(this.addCurrentVertex(u,m,-1,-1,h,!0),this.addCurrentVertex(u,m,0,0,h)));if(T&&v<l-1){var N=u.dist(d);if(N>2*f){var j=u.add(d.sub(u)._mult(f/N)._round());this.updateDistance(u,j),this.addCurrentVertex(j,m,0,0,h),u=j}}}}},Hs.prototype.addCurrentVertex=function(t,e,r,n,i,a){void 0===a&&(a=!1);var o=e.x+e.y*r,s=e.y-e.x*r,l=-e.x+e.y*n,c=-e.y-e.x*n;this.addHalfVertex(t,o,s,a,!1,r,i),this.addHalfVertex(t,l,c,a,!0,-n,i),this.distance>qs/2&&0===this.totalDistance&&(this.distance=0,this.addCurrentVertex(t,e,r,n,i,a))},Hs.prototype.addHalfVertex=function(t,e,r,n,i,a,o){var s=t.x,l=t.y,c=.5*this.scaledDistance;this.layoutVertexArray.emplaceBack((s<<1)+(n?1:0),(l<<1)+(i?1:0),Math.round(63*e)+128,Math.round(63*r)+128,1+(0===a?0:a<0?-1:1)|(63&c)<<2,c>>6);var u=o.vertexLength++;this.e1>=0&&this.e2>=0&&(this.indexArray.emplaceBack(this.e1,this.e2,u),o.primitiveLength++),i?this.e2=u:this.e1=u},Hs.prototype.updateScaledDistance=function(){this.scaledDistance=this.totalDistance>0?(this.clipStart+(this.clipEnd-this.clipStart)*this.distance/this.totalDistance)*(qs-1):this.distance},Hs.prototype.updateDistance=function(t,e){this.distance+=t.dist(e),this.updateScaledDistance()},Nn(\"LineBucket\",Hs,{omit:[\"layers\",\"patternFeatures\"]});var Gs=new Si({\"line-cap\":new wi(Lt.layout_line[\"line-cap\"]),\"line-join\":new Ti(Lt.layout_line[\"line-join\"]),\"line-miter-limit\":new wi(Lt.layout_line[\"line-miter-limit\"]),\"line-round-limit\":new wi(Lt.layout_line[\"line-round-limit\"]),\"line-sort-key\":new Ti(Lt.layout_line[\"line-sort-key\"])}),Ys={paint:new Si({\"line-opacity\":new Ti(Lt.paint_line[\"line-opacity\"]),\"line-color\":new Ti(Lt.paint_line[\"line-color\"]),\"line-translate\":new wi(Lt.paint_line[\"line-translate\"]),\"line-translate-anchor\":new wi(Lt.paint_line[\"line-translate-anchor\"]),\"line-width\":new Ti(Lt.paint_line[\"line-width\"]),\"line-gap-width\":new Ti(Lt.paint_line[\"line-gap-width\"]),\"line-offset\":new Ti(Lt.paint_line[\"line-offset\"]),\"line-blur\":new Ti(Lt.paint_line[\"line-blur\"]),\"line-dasharray\":new Ai(Lt.paint_line[\"line-dasharray\"]),\"line-pattern\":new ki(Lt.paint_line[\"line-pattern\"]),\"line-gradient\":new Mi(Lt.paint_line[\"line-gradient\"])}),layout:Gs},Ws=new(function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.possiblyEvaluate=function(e,r){return r=new pi(Math.floor(r.zoom),{now:r.now,fadeDuration:r.fadeDuration,zoomHistory:r.zoomHistory,transition:r.transition}),t.prototype.possiblyEvaluate.call(this,e,r)},e.prototype.evaluate=function(e,r,n,i){return r=u({},r,{zoom:Math.floor(r.zoom)}),t.prototype.evaluate.call(this,e,r,n,i)},e}(Ti))(Ys.paint.properties[\"line-width\"].specification);Ws.useIntegerZoom=!0;var Xs=function(t){function e(e){t.call(this,e,Ys)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._handleSpecialPaintPropertyUpdate=function(t){\"line-gradient\"===t&&this._updateGradient()},e.prototype._updateGradient=function(){var t=this._transitionablePaint._values[\"line-gradient\"].value.expression;this.gradient=Co(t,\"lineProgress\"),this.gradientTexture=null},e.prototype.recalculate=function(e,r){t.prototype.recalculate.call(this,e,r),this.paint._values[\"line-floorwidth\"]=Ws.possiblyEvaluate(this._transitioningPaint._values[\"line-width\"].value,e)},e.prototype.createBucket=function(t){return new Hs(t)},e.prototype.queryRadius=function(t){var e=t,r=Zs(oo(\"line-width\",this,e),oo(\"line-gap-width\",this,e)),n=oo(\"line-offset\",this,e);return r/2+Math.abs(n)+so(this.paint.get(\"line-translate\"))},e.prototype.queryIntersectsFeature=function(t,e,r,n,a,o,s){var l=lo(t,this.paint.get(\"line-translate\"),this.paint.get(\"line-translate-anchor\"),o.angle,s),c=s/2*Zs(this.paint.get(\"line-width\").evaluate(e,r),this.paint.get(\"line-gap-width\").evaluate(e,r)),u=this.paint.get(\"line-offset\").evaluate(e,r);return u&&(n=function(t,e){for(var r=[],n=new i(0,0),a=0;a<t.length;a++){for(var o=t[a],s=[],l=0;l<o.length;l++){var c=o[l-1],u=o[l],f=o[l+1],h=0===l?n:u.sub(c)._unit()._perp(),p=l===o.length-1?n:f.sub(u)._unit()._perp(),d=h._add(p)._unit(),g=d.x*p.x+d.y*p.y;d._mult(1/g),s.push(d._mult(e)._add(u))}r.push(s)}return r}(n,u*s)),function(t,e,r){for(var n=0;n<e.length;n++){var i=e[n];if(t.length>=3)for(var a=0;a<i.length;a++)if(io(t,i[a]))return!0;if(Qa(t,i,r))return!0}return!1}(l,n,c)},e.prototype.isTileClipped=function(){return!0},e}(Ei);function Zs(t,e){return e>0?e+2*t:t}var 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el(t,e,r){return t.sections.forEach((function(t){t.text=function(t,e,r){var n=e.layout.get(\"text-transform\").evaluate(r,{});return\"uppercase\"===n?t=t.toLocaleUpperCase():\"lowercase\"===n&&(t=t.toLocaleLowerCase()),hi.applyArabicShaping&&(t=hi.applyArabicShaping(t)),t}(t.text,e,r)})),t}var 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nl=function(t,e,r,n,i){var a,o,s=8*i-n-1,l=(1<<s)-1,c=l>>1,u=-7,f=r?i-1:0,h=r?-1:1,p=t[e+f];for(f+=h,a=p&(1<<-u)-1,p>>=-u,u+=s;u>0;a=256*a+t[e+f],f+=h,u-=8);for(o=a&(1<<-u)-1,a>>=-u,u+=n;u>0;o=256*o+t[e+f],f+=h,u-=8);if(0===a)a=1-c;else{if(a===l)return o?NaN:1/0*(p?-1:1);o+=Math.pow(2,n),a-=c}return(p?-1:1)*o*Math.pow(2,a-n)},il=function(t,e,r,n,i,a){var o,s,l,c=8*a-i-1,u=(1<<c)-1,f=u>>1,h=23===i?Math.pow(2,-24)-Math.pow(2,-77):0,p=n?0:a-1,d=n?1:-1,g=e<0||0===e&&1/e<0?1:0;for(e=Math.abs(e),isNaN(e)||e===1/0?(s=isNaN(e)?1:0,o=u):(o=Math.floor(Math.log(e)/Math.LN2),e*(l=Math.pow(2,-o))<1&&(o--,l*=2),(e+=o+f>=1?h/l:h*Math.pow(2,1-f))*l>=2&&(o++,l/=2),o+f>=u?(s=0,o=u):o+f>=1?(s=(e*l-1)*Math.pow(2,i),o+=f):(s=e*Math.pow(2,f-1)*Math.pow(2,i),o=0));i>=8;t[r+p]=255&s,p+=d,s/=256,i-=8);for(o=o<<i|s,c+=i;c>0;t[r+p]=255&o,p+=d,o/=256,c-=8);t[r+p-d]|=128*g},al=ol;function ol(t){this.buf=ArrayBuffer.isView&&ArrayBuffer.isView(t)?t:new 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e=ll(this);for(t=t||[];this.pos<e;)t.push(this.readSFixed32());return t},readPackedFixed64:function(t){if(this.type!==ol.Bytes)return t.push(this.readFixed64());var e=ll(this);for(t=t||[];this.pos<e;)t.push(this.readFixed64());return t},readPackedSFixed64:function(t){if(this.type!==ol.Bytes)return t.push(this.readSFixed64());var e=ll(this);for(t=t||[];this.pos<e;)t.push(this.readSFixed64());return t},skip:function(t){var e=7&t;if(e===ol.Varint)for(;this.buf[this.pos++]>127;);else if(e===ol.Bytes)this.pos=this.readVarint()+this.pos;else if(e===ol.Fixed32)this.pos+=4;else{if(e!==ol.Fixed64)throw new Error(\"Unimplemented type: \"+e);this.pos+=8}},writeTag:function(t,e){this.writeVarint(t<<3|e)},realloc:function(t){for(var e=this.length||16;e<this.pos+t;)e*=2;if(e!==this.length){var r=new Uint8Array(e);r.set(this.buf),this.buf=r,this.length=e}},finish:function(){return this.length=this.pos,this.pos=0,this.buf.subarray(0,this.length)},writeFixed32:function(t){this.realloc(4),_l(this.buf,t,this.pos),this.pos+=4},writeSFixed32:function(t){this.realloc(4),_l(this.buf,t,this.pos),this.pos+=4},writeFixed64:function(t){this.realloc(8),_l(this.buf,-1&t,this.pos),_l(this.buf,Math.floor(t*(1/4294967296)),this.pos+4),this.pos+=8},writeSFixed64:function(t){this.realloc(8),_l(this.buf,-1&t,this.pos),_l(this.buf,Math.floor(t*(1/4294967296)),this.pos+4),this.pos+=8},writeVarint:function(t){(t=+t||0)>268435455||t<0?function(t,e){var r,n;t>=0?(r=t%4294967296|0,n=t/4294967296|0):(n=~(-t/4294967296),4294967295^(r=~(-t%4294967296))?r=r+1|0:(r=0,n=n+1|0));if(t>=0x10000000000000000||t<-0x10000000000000000)throw new Error(\"Given varint doesn't fit into 10 bytes\");e.realloc(10),function(t,e,r){r.buf[r.pos++]=127&t|128,t>>>=7,r.buf[r.pos++]=127&t|128,t>>>=7,r.buf[r.pos++]=127&t|128,t>>>=7,r.buf[r.pos++]=127&t|128,t>>>=7,r.buf[r.pos]=127&t}(r,0,e),function(t,e){var r=(7&t)<<4;if(e.buf[e.pos++]|=r|((t>>>=3)?128:0),!t)return;if(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),!t)return;if(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),!t)return;if(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),!t)return;if(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),!t)return;e.buf[e.pos++]=127&t}(n,e)}(t,this):(this.realloc(4),this.buf[this.pos++]=127&t|(t>127?128:0),t<=127||(this.buf[this.pos++]=127&(t>>>=7)|(t>127?128:0),t<=127||(this.buf[this.pos++]=127&(t>>>=7)|(t>127?128:0),t<=127||(this.buf[this.pos++]=t>>>7&127))))},writeSVarint:function(t){this.writeVarint(t<0?2*-t-1:2*t)},writeBoolean:function(t){this.writeVarint(Boolean(t))},writeString:function(t){t=String(t),this.realloc(4*t.length),this.pos++;var e=this.pos;this.pos=function(t,e,r){for(var n,i,a=0;a<e.length;a++){if((n=e.charCodeAt(a))>55295&&n<57344){if(!i){n>56319||a+1===e.length?(t[r++]=239,t[r++]=191,t[r++]=189):i=n;continue}if(n<56320){t[r++]=239,t[r++]=191,t[r++]=189,i=n;continue}n=i-55296<<10|n-56320|65536,i=null}else i&&(t[r++]=239,t[r++]=191,t[r++]=189,i=null);n<128?t[r++]=n:(n<2048?t[r++]=n>>6|192:(n<65536?t[r++]=n>>12|224:(t[r++]=n>>18|240,t[r++]=n>>12&63|128),t[r++]=n>>6&63|128),t[r++]=63&n|128)}return r}(this.buf,t,this.pos);var r=this.pos-e;r>=128&&ul(e,r,this),this.pos=e-1,this.writeVarint(r),this.pos+=r},writeFloat:function(t){this.realloc(4),il(this.buf,t,this.pos,!0,23,4),this.pos+=4},writeDouble:function(t){this.realloc(8),il(this.buf,t,this.pos,!0,52,8),this.pos+=8},writeBytes:function(t){var e=t.length;this.writeVarint(e),this.realloc(e);for(var r=0;r<e;r++)this.buf[this.pos++]=t[r]},writeRawMessage:function(t,e){this.pos++;var r=this.pos;t(e,this);var n=this.pos-r;n>=128&&ul(r,n,this),this.pos=r-1,this.writeVarint(n),this.pos+=n},writeMessage:function(t,e,r){this.writeTag(t,ol.Bytes),this.writeRawMessage(e,r)},writePackedVarint:function(t,e){e.length&&this.writeMessage(t,fl,e)},writePackedSVarint:function(t,e){e.length&&this.writeMessage(t,hl,e)},writePackedBoolean:function(t,e){e.length&&this.writeMessage(t,gl,e)},writePackedFloat:function(t,e){e.length&&this.writeMessage(t,pl,e)},writePackedDouble:function(t,e){e.length&&this.writeMessage(t,dl,e)},writePackedFixed32:function(t,e){e.length&&this.writeMessage(t,ml,e)},writePackedSFixed32:function(t,e){e.length&&this.writeMessage(t,vl,e)},writePackedFixed64:function(t,e){e.length&&this.writeMessage(t,yl,e)},writePackedSFixed64:function(t,e){e.length&&this.writeMessage(t,xl,e)},writeBytesField:function(t,e){this.writeTag(t,ol.Bytes),this.writeBytes(e)},writeFixed32Field:function(t,e){this.writeTag(t,ol.Fixed32),this.writeFixed32(e)},writeSFixed32Field:function(t,e){this.writeTag(t,ol.Fixed32),this.writeSFixed32(e)},writeFixed64Field:function(t,e){this.writeTag(t,ol.Fixed64),this.writeFixed64(e)},writeSFixed64Field:function(t,e){this.writeTag(t,ol.Fixed64),this.writeSFixed64(e)},writeVarintField:function(t,e){this.writeTag(t,ol.Varint),this.writeVarint(e)},writeSVarintField:function(t,e){this.writeTag(t,ol.Varint),this.writeSVarint(e)},writeStringField:function(t,e){this.writeTag(t,ol.Bytes),this.writeString(e)},writeFloatField:function(t,e){this.writeTag(t,ol.Fixed32),this.writeFloat(e)},writeDoubleField:function(t,e){this.writeTag(t,ol.Fixed64),this.writeDouble(e)},writeBooleanField:function(t,e){this.writeVarintField(t,Boolean(e))}};function Tl(t,e,r){1===t&&r.readMessage(kl,e)}function kl(t,e,r){if(3===t){var n=r.readMessage(Al,{}),i=n.id,a=n.bitmap,o=n.width,s=n.height,l=n.left,c=n.top,u=n.advance;e.push({id:i,bitmap:new So({width:o+6,height:s+6},a),metrics:{width:o,height:s,left:l,top:c,advance:u}})}}function Al(t,e,r){1===t?e.id=r.readVarint():2===t?e.bitmap=r.readBytes():3===t?e.width=r.readVarint():4===t?e.height=r.readVarint():5===t?e.left=r.readSVarint():6===t?e.top=r.readSVarint():7===t&&(e.advance=r.readVarint())}function Ml(t){for(var e=0,r=0,n=0,i=t;n<i.length;n+=1){var a=i[n];e+=a.w*a.h,r=Math.max(r,a.w)}t.sort((function(t,e){return e.h-t.h}));for(var o=[{x:0,y:0,w:Math.max(Math.ceil(Math.sqrt(e/.95)),r),h:1/0}],s=0,l=0,c=0,u=t;c<u.length;c+=1)for(var f=u[c],h=o.length-1;h>=0;h--){var p=o[h];if(!(f.w>p.w||f.h>p.h)){if(f.x=p.x,f.y=p.y,l=Math.max(l,f.y+f.h),s=Math.max(s,f.x+f.w),f.w===p.w&&f.h===p.h){var d=o.pop();h<o.length&&(o[h]=d)}else 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Eo({width:o||1,height:s||1});for(var c in t){var u=t[c],f=r[c].paddedRect;Eo.copy(u.data,l,{x:0,y:0},{x:f.x+1,y:f.y+1},u.data)}for(var h in e){var p=e[h],d=n[h].paddedRect,g=d.x+1,m=d.y+1,v=p.data.width,y=p.data.height;Eo.copy(p.data,l,{x:0,y:0},{x:g,y:m},p.data),Eo.copy(p.data,l,{x:0,y:y-1},{x:g,y:m-1},{width:v,height:1}),Eo.copy(p.data,l,{x:0,y:0},{x:g,y:m+y},{width:v,height:1}),Eo.copy(p.data,l,{x:v-1,y:0},{x:g-1,y:m},{width:1,height:y}),Eo.copy(p.data,l,{x:0,y:0},{x:g+v,y:m},{width:1,height:y})}this.image=l,this.iconPositions=r,this.patternPositions=n};Ll.prototype.addImages=function(t,e,r){for(var n in t){var i=t[n],a={x:0,y:0,w:i.data.width+2,h:i.data.height+2};r.push(a),e[n]=new Sl(a,i),i.hasRenderCallback&&this.haveRenderCallbacks.push(n)}},Ll.prototype.patchUpdatedImages=function(t,e){for(var r in t.dispatchRenderCallbacks(this.haveRenderCallbacks),t.updatedImages)this.patchUpdatedImage(this.iconPositions[r],t.getImage(r),e),this.patchUpdatedImage(this.patternPositions[r],t.getImage(r),e)},Ll.prototype.patchUpdatedImage=function(t,e,r){if(t&&e&&t.version!==e.version){t.version=e.version;var n=t.tl,i=n[0],a=n[1];r.update(e.data,void 0,{x:i,y:a})}},Nn(\"ImagePosition\",Sl),Nn(\"ImageAtlas\",Ll);var Cl={horizontal:1,vertical:2,horizontalOnly:3};var Pl=function(){this.scale=1,this.fontStack=\"\",this.imageName=null};Pl.forText=function(t,e){var r=new Pl;return r.scale=t||1,r.fontStack=e,r},Pl.forImage=function(t){var e=new Pl;return e.imageName=t,e};var Il=function(){this.text=\"\",this.sectionIndex=[],this.sections=[],this.imageSectionID=null};function Ol(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g){var m,v=Il.fromFeature(t,i);f===Cl.vertical&&v.verticalizePunctuation();var y=hi.processBidirectionalText,x=hi.processStyledBidirectionalText;if(y&&1===v.sections.length){m=[];for(var b=0,_=y(v.toString(),jl(v,c,a,e,n,p,d));b<_.length;b+=1){var w=_[b],T=new Il;T.text=w,T.sections=v.sections;for(var k=0;k<w.length;k++)T.sectionIndex.push(0);m.push(T)}}else if(x){m=[];for(var A=0,M=x(v.text,v.sectionIndex,jl(v,c,a,e,n,p,d));A<M.length;A+=1){var S=M[A],E=new Il;E.text=S[0],E.sectionIndex=S[1],E.sections=v.sections,m.push(E)}}else m=function(t,e){for(var r=[],n=t.text,i=0,a=0,o=e;a<o.length;a+=1){var s=o[a];r.push(t.substring(i,s)),i=s}return i<n.length&&r.push(t.substring(i,n.length)),r}(v,jl(v,c,a,e,n,p,d));var L=[],C={positionedLines:L,text:v.toString(),top:u[1],bottom:u[1],left:u[0],right:u[0],writingMode:f,iconsInText:!1,verticalizable:!1};return function(t,e,r,n,i,a,o,s,l,c,u,f){for(var h=0,p=-17,d=0,g=0,m=\"right\"===s?1:\"left\"===s?0:.5,v=0,y=0,x=i;y<x.length;y+=1){var b=x[y];b.trim();var _=b.getMaxScale(),w=24*(_-1),T={positionedGlyphs:[],lineOffset:0};t.positionedLines[v]=T;var k=T.positionedGlyphs,A=0;if(b.length()){for(var M=0;M<b.length();M++){var S=b.getSection(M),E=b.getSectionIndex(M),L=b.getCharCode(M),C=0,P=null,I=null,O=null,z=24,D=!(l===Cl.horizontal||!u&&!Zn(L)||u&&(zl[L]||(Y=L,Yn.Arabic(Y)||Yn[\"Arabic Supplement\"](Y)||Yn[\"Arabic Extended-A\"](Y)||Yn[\"Arabic Presentation Forms-A\"](Y)||Yn[\"Arabic Presentation Forms-B\"](Y))));if(S.imageName){var R=n[S.imageName];if(!R)continue;O=S.imageName,t.iconsInText=t.iconsInText||!0,I=R.paddedRect;var F=R.displaySize;S.scale=24*S.scale/f,P={width:F[0],height:F[1],left:1,top:-3,advance:D?F[1]:F[0]};var B=24-F[1]*S.scale;C=w+B,z=P.advance;var N=D?F[0]*S.scale-24*_:F[1]*S.scale-24*_;N>0&&N>A&&(A=N)}else{var j=r[S.fontStack],U=j&&j[L];if(U&&U.rect)I=U.rect,P=U.metrics;else{var V=e[S.fontStack],q=V&&V[L];if(!q)continue;P=q.metrics}C=24*(_-S.scale)}D?(t.verticalizable=!0,k.push({glyph:L,imageName:O,x:h,y:p+C,vertical:D,scale:S.scale,fontStack:S.fontStack,sectionIndex:E,metrics:P,rect:I}),h+=z*S.scale+c):(k.push({glyph:L,imageName:O,x:h,y:p+C,vertical:D,scale:S.scale,fontStack:S.fontStack,sectionIndex:E,metrics:P,rect:I}),h+=P.advance*S.scale+c)}if(0!==k.length){var H=h-c;d=Math.max(H,d),Vl(k,0,k.length-1,m,A)}h=0;var G=a*_+A;T.lineOffset=Math.max(A,w),p+=G,g=Math.max(G,g),++v}else p+=a,++v}var Y;var W=p- -17,X=Ul(o),Z=X.horizontalAlign,J=X.verticalAlign;(function(t,e,r,n,i,a,o,s,l){var c=(e-r)*i,u=0;u=a!==o?-s*n- -17:(-n*l+.5)*o;for(var f=0,h=t;f<h.length;f+=1)for(var p=h[f],d=0,g=p.positionedGlyphs;d<g.length;d+=1){var m=g[d];m.x+=c,m.y+=u}})(t.positionedLines,m,Z,J,d,g,a,W,i.length),t.top+=-J*W,t.bottom=t.top+W,t.left+=-Z*d,t.right=t.left+d}(C,e,r,n,m,o,s,l,f,c,h,g),!function(t){for(var e=0,r=t;e<r.length;e+=1){if(0!==r[e].positionedGlyphs.length)return!1}return!0}(L)&&C}Il.fromFeature=function(t,e){for(var r=new Il,n=0;n<t.sections.length;n++){var i=t.sections[n];i.image?r.addImageSection(i):r.addTextSection(i,e)}return r},Il.prototype.length=function(){return this.text.length},Il.prototype.getSection=function(t){return this.sections[this.sectionIndex[t]]},Il.prototype.getSectionIndex=function(t){return this.sectionIndex[t]},Il.prototype.getCharCode=function(t){return this.text.charCodeAt(t)},Il.prototype.verticalizePunctuation=function(){this.text=function(t){for(var e=\"\",r=0;r<t.length;r++){var n=t.charCodeAt(r+1)||null,i=t.charCodeAt(r-1)||null;(!n||!Jn(n)||rl[t[r+1]])&&(!i||!Jn(i)||rl[t[r-1]])&&rl[t[r]]?e+=rl[t[r]]:e+=t[r]}return e}(this.text)},Il.prototype.trim=function(){for(var t=0,e=0;e<this.text.length&&zl[this.text.charCodeAt(e)];e++)t++;for(var 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e=this.data,r=this.compare,n=this.length>>1,i=e[t];t<n;){var a=1+(t<<1),o=e[a],s=a+1;if(s<this.length&&r(e[s],o)<0&&(a=s,o=e[s]),r(o,i)>=0)break;e[t]=o,t=a}e[t]=i};var pc=Number.POSITIVE_INFINITY;function dc(t,e){return e[1]!==pc?function(t,e,r){var n=0,i=0;switch(e=Math.abs(e),r=Math.abs(r),t){case\"top-right\":case\"top-left\":case\"top\":i=r-7;break;case\"bottom-right\":case\"bottom-left\":case\"bottom\":i=7-r}switch(t){case\"top-right\":case\"bottom-right\":case\"right\":n=-e;break;case\"top-left\":case\"bottom-left\":case\"left\":n=e}return[n,i]}(t,e[0],e[1]):function(t,e){var r=0,n=0;e<0&&(e=0);var i=e/Math.sqrt(2);switch(t){case\"top-right\":case\"top-left\":n=i-7;break;case\"bottom-right\":case\"bottom-left\":n=7-i;break;case\"bottom\":n=7-e;break;case\"top\":n=e-7}switch(t){case\"top-right\":case\"bottom-right\":r=-i;break;case\"top-left\":case\"bottom-left\":r=i;break;case\"left\":r=e;break;case\"right\":r=-e}return[r,n]}(t,e[0])}function gc(t){switch(t){case\"right\":case\"top-right\":case\"bottom-right\":return\"right\";case\"left\":case\"top-left\":case\"bottom-left\":return\"left\"}return\"center\"}function mc(t,e,r,n,a,o,s,l,c,u,f,h,p,d,g){var m=function(t,e,r,n,a,o,s,l){for(var c=n.layout.get(\"text-rotate\").evaluate(o,{})*Math.PI/180,u=[],f=0,h=e.positionedLines;f<h.length;f+=1)for(var p=h[f],d=0,g=p.positionedGlyphs;d<g.length;d+=1){var m=g[d];if(m.rect){var v=m.rect||{},y=4,x=!0,b=1,_=0,w=(a||l)&&m.vertical,T=m.metrics.advance*m.scale/2;if(l&&e.verticalizable){var k=24*(m.scale-1),A=(24-m.metrics.width*m.scale)/2;_=p.lineOffset/2-(m.imageName?-A:k)}if(m.imageName){var M=s[m.imageName];x=M.sdf,y=1/(b=M.pixelRatio)}var S=a?[m.x+T,m.y]:[0,0],E=a?[0,0]:[m.x+T+r[0],m.y+r[1]-_],L=[0,0];w&&(L=E,E=[0,0]);var C=(m.metrics.left-y)*m.scale-T+E[0],P=(-m.metrics.top-y)*m.scale+E[1],I=C+v.w*m.scale/b,O=P+v.h*m.scale/b,z=new i(C,P),D=new i(I,P),R=new i(C,O),F=new i(I,O);if(w){var B=new i(-T,T- -17),N=-Math.PI/2,j=12-T,U=m.imageName?j:0,V=new i(22-j,-U),q=new(Function.prototype.bind.apply(i,[null].concat(L)));z._rotateAround(N,B)._add(V)._add(q),D._rotateAround(N,B)._add(V)._add(q),R._rotateAround(N,B)._add(V)._add(q),F._rotateAround(N,B)._add(V)._add(q)}if(c){var H=Math.sin(c),G=Math.cos(c),Y=[G,-H,H,G];z._matMult(Y),D._matMult(Y),R._matMult(Y),F._matMult(Y)}var W=new i(0,0),X=new i(0,0);u.push({tl:z,tr:D,bl:R,br:F,tex:v,writingMode:e.writingMode,glyphOffset:S,sectionIndex:m.sectionIndex,isSDF:x,pixelOffsetTL:W,pixelOffsetBR:X,minFontScaleX:0,minFontScaleY:0})}}return u}(0,r,l,a,o,s,n,t.allowVerticalPlacement),v=t.textSizeData,y=null;\"source\"===v.kind?(y=[128*a.layout.get(\"text-size\").evaluate(s,{})])[0]>32640&&_(t.layerIds[0]+': Value for \"text-size\" is >= 255. Reduce your \"text-size\".'):\"composite\"===v.kind&&((y=[128*d.compositeTextSizes[0].evaluate(s,{},g),128*d.compositeTextSizes[1].evaluate(s,{},g)])[0]>32640||y[1]>32640)&&_(t.layerIds[0]+': Value for \"text-size\" is >= 255. Reduce your \"text-size\".'),t.addSymbols(t.text,m,y,l,o,s,u,e,c.lineStartIndex,c.lineLength,p,g);for(var x=0,b=f;x<b.length;x+=1){h[b[x]]=t.text.placedSymbolArray.length-1}return 4*m.length}function vc(t){for(var e in t)return t[e];return null}function yc(t,e,r,n){var i=t.compareText;if(e in i){for(var a=i[e],o=a.length-1;o>=0;o--)if(n.dist(a[o])<r)return!0}else i[e]=[];return i[e].push(n),!1}var xc=Ls.VectorTileFeature.types,bc=[{name:\"a_fade_opacity\",components:1,type:\"Uint8\",offset:0}];function _c(t,e,r,n,i,a,o,s,l,c,u,f,h){var p=s?Math.min(32640,Math.round(s[0])):0,d=s?Math.min(32640,Math.round(s[1])):0;t.emplaceBack(e,r,Math.round(32*n),Math.round(32*i),a,o,(p<<1)+(l?1:0),d,16*c,16*u,256*f,256*h)}function wc(t,e,r){t.emplaceBack(e.x,e.y,r),t.emplaceBack(e.x,e.y,r),t.emplaceBack(e.x,e.y,r),t.emplaceBack(e.x,e.y,r)}function Tc(t){for(var e=0,r=t.sections;e<r.length;e+=1){if($n(r[e].text))return!0}return!1}var kc=function(t){this.layoutVertexArray=new Ni,this.indexArray=new Yi,this.programConfigurations=t,this.segments=new pa,this.dynamicLayoutVertexArray=new ji,this.opacityVertexArray=new Ui,this.placedSymbolArray=new aa};kc.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length&&0===this.indexArray.length&&0===this.dynamicLayoutVertexArray.length&&0===this.opacityVertexArray.length},kc.prototype.upload=function(t,e,r,n){this.isEmpty()||(r&&(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,Js.members),this.indexBuffer=t.createIndexBuffer(this.indexArray,e),this.dynamicLayoutVertexBuffer=t.createVertexBuffer(this.dynamicLayoutVertexArray,Ks.members,!0),this.opacityVertexBuffer=t.createVertexBuffer(this.opacityVertexArray,bc,!0),this.opacityVertexBuffer.itemSize=1),(r||n)&&this.programConfigurations.upload(t))},kc.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy(),this.dynamicLayoutVertexBuffer.destroy(),this.opacityVertexBuffer.destroy())},Nn(\"SymbolBuffers\",kc);var Ac=function(t,e,r){this.layoutVertexArray=new t,this.layoutAttributes=e,this.indexArray=new r,this.segments=new pa,this.collisionVertexArray=new Gi};Ac.prototype.upload=function(t){this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,this.layoutAttributes),this.indexBuffer=t.createIndexBuffer(this.indexArray),this.collisionVertexBuffer=t.createVertexBuffer(this.collisionVertexArray,Qs.members,!0)},Ac.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.segments.destroy(),this.collisionVertexBuffer.destroy())},Nn(\"CollisionBuffers\",Ac);var Mc=function(t){this.collisionBoxArray=t.collisionBoxArray,this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.pixelRatio=t.pixelRatio,this.sourceLayerIndex=t.sourceLayerIndex,this.hasPattern=!1,this.hasRTLText=!1,this.sortKeyRanges=[],this.collisionCircleArray=[],this.placementInvProjMatrix=ho([]),this.placementViewportMatrix=ho([]);var e=this.layers[0]._unevaluatedLayout._values;this.textSizeData=Gl(this.zoom,e[\"text-size\"]),this.iconSizeData=Gl(this.zoom,e[\"icon-size\"]);var r=this.layers[0].layout,n=r.get(\"symbol-sort-key\"),i=r.get(\"symbol-z-order\");this.sortFeaturesByKey=\"viewport-y\"!==i&&void 0!==n.constantOr(1);var a=\"viewport-y\"===i||\"auto\"===i&&!this.sortFeaturesByKey;this.sortFeaturesByY=a&&(r.get(\"text-allow-overlap\")||r.get(\"icon-allow-overlap\")||r.get(\"text-ignore-placement\")||r.get(\"icon-ignore-placement\")),\"point\"===r.get(\"symbol-placement\")&&(this.writingModes=r.get(\"text-writing-mode\").map((function(t){return Cl[t]}))),this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id})),this.sourceID=t.sourceID};Mc.prototype.createArrays=function(){this.text=new kc(new Ua(Js.members,this.layers,this.zoom,(function(t){return/^text/.test(t)}))),this.icon=new kc(new Ua(Js.members,this.layers,this.zoom,(function(t){return/^icon/.test(t)}))),this.glyphOffsetArray=new la,this.lineVertexArray=new ca,this.symbolInstances=new sa},Mc.prototype.calculateGlyphDependencies=function(t,e,r,n,i){for(var a=0;a<t.length;a++)if(e[t.charCodeAt(a)]=!0,(r||n)&&i){var o=rl[t.charAt(a)];o&&(e[o.charCodeAt(0)]=!0)}},Mc.prototype.populate=function(t,e,r){var n=this.layers[0],i=n.layout,a=i.get(\"text-font\"),o=i.get(\"text-field\"),s=i.get(\"icon-image\"),l=(\"constant\"!==o.value.kind||o.value.value instanceof ne&&!o.value.value.isEmpty()||o.value.value.toString().length>0)&&(\"constant\"!==a.value.kind||a.value.value.length>0),c=\"constant\"!==s.value.kind||!!s.value.value||Object.keys(s.parameters).length>0,u=i.get(\"symbol-sort-key\");if(this.features=[],l||c){for(var f=e.iconDependencies,h=e.glyphDependencies,p=e.availableImages,d=new pi(this.zoom),g=0,m=t;g<m.length;g+=1){var v=m[g],y=v.feature,x=v.id,b=v.index,_=v.sourceLayerIndex,w=n._featureFilter.needGeometry,T={type:y.type,id:x,properties:y.properties,geometry:w?Ya(y):[]};if(n._featureFilter.filter(d,T,r)){w||(T.geometry=Ya(y));var k=void 0;if(l){var A=n.getValueAndResolveTokens(\"text-field\",T,r,p),M=ne.factory(A);Tc(M)&&(this.hasRTLText=!0),(!this.hasRTLText||\"unavailable\"===ui()||this.hasRTLText&&hi.isParsed())&&(k=el(M,n,T))}var S=void 0;if(c){var E=n.getValueAndResolveTokens(\"icon-image\",T,r,p);S=E instanceof ie?E:ie.fromString(E)}if(k||S){var L=this.sortFeaturesByKey?u.evaluate(T,{},r):void 0,C={id:x,text:k,icon:S,index:b,sourceLayerIndex:_,geometry:Ya(y),properties:y.properties,type:xc[y.type],sortKey:L};if(this.features.push(C),S&&(f[S.name]=!0),k){var P=a.evaluate(T,{},r).join(\",\"),I=\"map\"===i.get(\"text-rotation-alignment\")&&\"point\"!==i.get(\"symbol-placement\");this.allowVerticalPlacement=this.writingModes&&this.writingModes.indexOf(Cl.vertical)>=0;for(var O=0,z=k.sections;O<z.length;O+=1){var D=z[O];if(D.image)f[D.image.name]=!0;else{var R=Wn(k.toString()),F=D.fontStack||P,B=h[F]=h[F]||{};this.calculateGlyphDependencies(D.text,B,I,this.allowVerticalPlacement,R)}}}}}}\"line\"===i.get(\"symbol-placement\")&&(this.features=function(t){var e={},r={},n=[],i=0;function a(e){n.push(t[e]),i++}function o(t,e,i){var a=r[t];return delete r[t],r[e]=a,n[a].geometry[0].pop(),n[a].geometry[0]=n[a].geometry[0].concat(i[0]),a}function s(t,r,i){var a=e[r];return delete e[r],e[t]=a,n[a].geometry[0].shift(),n[a].geometry[0]=i[0].concat(n[a].geometry[0]),a}function l(t,e,r){var n=r?e[0][e[0].length-1]:e[0][0];return t+\":\"+n.x+\":\"+n.y}for(var c=0;c<t.length;c++){var u=t[c],f=u.geometry,h=u.text?u.text.toString():null;if(h){var p=l(h,f),d=l(h,f,!0);if(p in r&&d in e&&r[p]!==e[d]){var g=s(p,d,f),m=o(p,d,n[g].geometry);delete e[p],delete r[d],r[l(h,n[m].geometry,!0)]=m,n[g].geometry=null}else p in r?o(p,d,f):d in e?s(p,d,f):(a(c),e[p]=i-1,r[d]=i-1)}else a(c)}return n.filter((function(t){return t.geometry}))}(this.features)),this.sortFeaturesByKey&&this.features.sort((function(t,e){return t.sortKey-e.sortKey}))}},Mc.prototype.update=function(t,e,r){this.stateDependentLayers.length&&(this.text.programConfigurations.updatePaintArrays(t,e,this.layers,r),this.icon.programConfigurations.updatePaintArrays(t,e,this.layers,r))},Mc.prototype.isEmpty=function(){return 0===this.symbolInstances.length&&!this.hasRTLText},Mc.prototype.uploadPending=function(){return!this.uploaded||this.text.programConfigurations.needsUpload||this.icon.programConfigurations.needsUpload},Mc.prototype.upload=function(t){!this.uploaded&&this.hasDebugData()&&(this.textCollisionBox.upload(t),this.iconCollisionBox.upload(t)),this.text.upload(t,this.sortFeaturesByY,!this.uploaded,this.text.programConfigurations.needsUpload),this.icon.upload(t,this.sortFeaturesByY,!this.uploaded,this.icon.programConfigurations.needsUpload),this.uploaded=!0},Mc.prototype.destroyDebugData=function(){this.textCollisionBox.destroy(),this.iconCollisionBox.destroy()},Mc.prototype.destroy=function(){this.text.destroy(),this.icon.destroy(),this.hasDebugData()&&this.destroyDebugData()},Mc.prototype.addToLineVertexArray=function(t,e){var r=this.lineVertexArray.length;if(void 0!==t.segment){for(var n=t.dist(e[t.segment+1]),i=t.dist(e[t.segment]),a={},o=t.segment+1;o<e.length;o++)a[o]={x:e[o].x,y:e[o].y,tileUnitDistanceFromAnchor:n},o<e.length-1&&(n+=e[o+1].dist(e[o]));for(var s=t.segment||0;s>=0;s--)a[s]={x:e[s].x,y:e[s].y,tileUnitDistanceFromAnchor:i},s>0&&(i+=e[s-1].dist(e[s]));for(var l=0;l<e.length;l++){var c=a[l];this.lineVertexArray.emplaceBack(c.x,c.y,c.tileUnitDistanceFromAnchor)}}return{lineStartIndex:r,lineLength:this.lineVertexArray.length-r}},Mc.prototype.addSymbols=function(t,e,r,n,i,a,o,s,l,c,u,f){for(var h=t.indexArray,p=t.layoutVertexArray,d=t.segments.prepareSegment(4*e.length,p,h,a.sortKey),g=this.glyphOffsetArray.length,m=d.vertexLength,v=this.allowVerticalPlacement&&o===Cl.vertical?Math.PI/2:0,y=a.text&&a.text.sections,x=0;x<e.length;x++){var b=e[x],_=b.tl,w=b.tr,T=b.bl,k=b.br,A=b.tex,M=b.pixelOffsetTL,S=b.pixelOffsetBR,E=b.minFontScaleX,L=b.minFontScaleY,C=b.glyphOffset,P=b.isSDF,I=b.sectionIndex,O=d.vertexLength,z=C[1];_c(p,s.x,s.y,_.x,z+_.y,A.x,A.y,r,P,M.x,M.y,E,L),_c(p,s.x,s.y,w.x,z+w.y,A.x+A.w,A.y,r,P,S.x,M.y,E,L),_c(p,s.x,s.y,T.x,z+T.y,A.x,A.y+A.h,r,P,M.x,S.y,E,L),_c(p,s.x,s.y,k.x,z+k.y,A.x+A.w,A.y+A.h,r,P,S.x,S.y,E,L),wc(t.dynamicLayoutVertexArray,s,v),h.emplaceBack(O,O+1,O+2),h.emplaceBack(O+1,O+2,O+3),d.vertexLength+=4,d.primitiveLength+=2,this.glyphOffsetArray.emplaceBack(C[0]),x!==e.length-1&&I===e[x+1].sectionIndex||t.programConfigurations.populatePaintArrays(p.length,a,a.index,{},f,y&&y[I])}t.placedSymbolArray.emplaceBack(s.x,s.y,g,this.glyphOffsetArray.length-g,m,l,c,s.segment,r?r[0]:0,r?r[1]:0,n[0],n[1],o,0,!1,0,u)},Mc.prototype._addCollisionDebugVertex=function(t,e,r,n,i,a){return e.emplaceBack(0,0),t.emplaceBack(r.x,r.y,n,i,Math.round(a.x),Math.round(a.y))},Mc.prototype.addCollisionDebugVertices=function(t,e,r,n,a,o,s){var l=a.segments.prepareSegment(4,a.layoutVertexArray,a.indexArray),c=l.vertexLength,u=a.layoutVertexArray,f=a.collisionVertexArray,h=s.anchorX,p=s.anchorY;this._addCollisionDebugVertex(u,f,o,h,p,new i(t,e)),this._addCollisionDebugVertex(u,f,o,h,p,new i(r,e)),this._addCollisionDebugVertex(u,f,o,h,p,new i(r,n)),this._addCollisionDebugVertex(u,f,o,h,p,new i(t,n)),l.vertexLength+=4;var d=a.indexArray;d.emplaceBack(c,c+1),d.emplaceBack(c+1,c+2),d.emplaceBack(c+2,c+3),d.emplaceBack(c+3,c),l.primitiveLength+=4},Mc.prototype.addDebugCollisionBoxes=function(t,e,r,n){for(var i=t;i<e;i++){var a=this.collisionBoxArray.get(i),o=a.x1,s=a.y1,l=a.x2,c=a.y2;this.addCollisionDebugVertices(o,s,l,c,n?this.textCollisionBox:this.iconCollisionBox,a.anchorPoint,r)}},Mc.prototype.generateCollisionDebugBuffers=function(){this.hasDebugData()&&this.destroyDebugData(),this.textCollisionBox=new Ac(qi,$s.members,Qi),this.iconCollisionBox=new Ac(qi,$s.members,Qi);for(var t=0;t<this.symbolInstances.length;t++){var e=this.symbolInstances.get(t);this.addDebugCollisionBoxes(e.textBoxStartIndex,e.textBoxEndIndex,e,!0),this.addDebugCollisionBoxes(e.verticalTextBoxStartIndex,e.verticalTextBoxEndIndex,e,!0),this.addDebugCollisionBoxes(e.iconBoxStartIndex,e.iconBoxEndIndex,e,!1),this.addDebugCollisionBoxes(e.verticalIconBoxStartIndex,e.verticalIconBoxEndIndex,e,!1)}},Mc.prototype._deserializeCollisionBoxesForSymbol=function(t,e,r,n,i,a,o,s,l){for(var c={},u=e;u<r;u++){var f=t.get(u);c.textBox={x1:f.x1,y1:f.y1,x2:f.x2,y2:f.y2,anchorPointX:f.anchorPointX,anchorPointY:f.anchorPointY},c.textFeatureIndex=f.featureIndex;break}for(var h=n;h<i;h++){var p=t.get(h);c.verticalTextBox={x1:p.x1,y1:p.y1,x2:p.x2,y2:p.y2,anchorPointX:p.anchorPointX,anchorPointY:p.anchorPointY},c.verticalTextFeatureIndex=p.featureIndex;break}for(var d=a;d<o;d++){var g=t.get(d);c.iconBox={x1:g.x1,y1:g.y1,x2:g.x2,y2:g.y2,anchorPointX:g.anchorPointX,anchorPointY:g.anchorPointY},c.iconFeatureIndex=g.featureIndex;break}for(var m=s;m<l;m++){var v=t.get(m);c.verticalIconBox={x1:v.x1,y1:v.y1,x2:v.x2,y2:v.y2,anchorPointX:v.anchorPointX,anchorPointY:v.anchorPointY},c.verticalIconFeatureIndex=v.featureIndex;break}return c},Mc.prototype.deserializeCollisionBoxes=function(t){this.collisionArrays=[];for(var e=0;e<this.symbolInstances.length;e++){var r=this.symbolInstances.get(e);this.collisionArrays.push(this._deserializeCollisionBoxesForSymbol(t,r.textBoxStartIndex,r.textBoxEndIndex,r.verticalTextBoxStartIndex,r.verticalTextBoxEndIndex,r.iconBoxStartIndex,r.iconBoxEndIndex,r.verticalIconBoxStartIndex,r.verticalIconBoxEndIndex))}},Mc.prototype.hasTextData=function(){return this.text.segments.get().length>0},Mc.prototype.hasIconData=function(){return this.icon.segments.get().length>0},Mc.prototype.hasDebugData=function(){return this.textCollisionBox&&this.iconCollisionBox},Mc.prototype.hasTextCollisionBoxData=function(){return this.hasDebugData()&&this.textCollisionBox.segments.get().length>0},Mc.prototype.hasIconCollisionBoxData=function(){return this.hasDebugData()&&this.iconCollisionBox.segments.get().length>0},Mc.prototype.addIndicesForPlacedSymbol=function(t,e){for(var r=t.placedSymbolArray.get(e),n=r.vertexStartIndex+4*r.numGlyphs,i=r.vertexStartIndex;i<n;i+=4)t.indexArray.emplaceBack(i,i+1,i+2),t.indexArray.emplaceBack(i+1,i+2,i+3)},Mc.prototype.getSortedSymbolIndexes=function(t){if(this.sortedAngle===t&&void 0!==this.symbolInstanceIndexes)return this.symbolInstanceIndexes;for(var e=Math.sin(t),r=Math.cos(t),n=[],i=[],a=[],o=0;o<this.symbolInstances.length;++o){a.push(o);var s=this.symbolInstances.get(o);n.push(0|Math.round(e*s.anchorX+r*s.anchorY)),i.push(s.featureIndex)}return a.sort((function(t,e){return n[t]-n[e]||i[e]-i[t]})),a},Mc.prototype.addToSortKeyRanges=function(t,e){var r=this.sortKeyRanges[this.sortKeyRanges.length-1];r&&r.sortKey===e?r.symbolInstanceEnd=t+1:this.sortKeyRanges.push({sortKey:e,symbolInstanceStart:t,symbolInstanceEnd:t+1})},Mc.prototype.sortFeatures=function(t){var e=this;if(this.sortFeaturesByY&&this.sortedAngle!==t&&!(this.text.segments.get().length>1||this.icon.segments.get().length>1)){this.symbolInstanceIndexes=this.getSortedSymbolIndexes(t),this.sortedAngle=t,this.text.indexArray.clear(),this.icon.indexArray.clear(),this.featureSortOrder=[];for(var r=0,n=this.symbolInstanceIndexes;r<n.length;r+=1){var i=n[r],a=this.symbolInstances.get(i);this.featureSortOrder.push(a.featureIndex),[a.rightJustifiedTextSymbolIndex,a.centerJustifiedTextSymbolIndex,a.leftJustifiedTextSymbolIndex].forEach((function(t,r,n){t>=0&&n.indexOf(t)===r&&e.addIndicesForPlacedSymbol(e.text,t)})),a.verticalPlacedTextSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.text,a.verticalPlacedTextSymbolIndex),a.placedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,a.placedIconSymbolIndex),a.verticalPlacedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,a.verticalPlacedIconSymbolIndex)}this.text.indexBuffer&&this.text.indexBuffer.updateData(this.text.indexArray),this.icon.indexBuffer&&this.icon.indexBuffer.updateData(this.icon.indexArray)}},Nn(\"SymbolBucket\",Mc,{omit:[\"layers\",\"collisionBoxArray\",\"features\",\"compareText\"]}),Mc.MAX_GLYPHS=65535,Mc.addDynamicAttributes=wc;var Sc=new Si({\"symbol-placement\":new wi(Lt.layout_symbol[\"symbol-placement\"]),\"symbol-spacing\":new wi(Lt.layout_symbol[\"symbol-spacing\"]),\"symbol-avoid-edges\":new wi(Lt.layout_symbol[\"symbol-avoid-edges\"]),\"symbol-sort-key\":new Ti(Lt.layout_symbol[\"symbol-sort-key\"]),\"symbol-z-order\":new wi(Lt.layout_symbol[\"symbol-z-order\"]),\"icon-allow-overlap\":new wi(Lt.layout_symbol[\"icon-allow-overlap\"]),\"icon-ignore-placement\":new wi(Lt.layout_symbol[\"icon-ignore-placement\"]),\"icon-optional\":new wi(Lt.layout_symbol[\"icon-optional\"]),\"icon-rotation-alignment\":new wi(Lt.layout_symbol[\"icon-rotation-alignment\"]),\"icon-size\":new Ti(Lt.layout_symbol[\"icon-size\"]),\"icon-text-fit\":new wi(Lt.layout_symbol[\"icon-text-fit\"]),\"icon-text-fit-padding\":new wi(Lt.layout_symbol[\"icon-text-fit-padding\"]),\"icon-image\":new Ti(Lt.layout_symbol[\"icon-image\"]),\"icon-rotate\":new Ti(Lt.layout_symbol[\"icon-rotate\"]),\"icon-padding\":new wi(Lt.layout_symbol[\"icon-padding\"]),\"icon-keep-upright\":new wi(Lt.layout_symbol[\"icon-keep-upright\"]),\"icon-offset\":new Ti(Lt.layout_symbol[\"icon-offset\"]),\"icon-anchor\":new Ti(Lt.layout_symbol[\"icon-anchor\"]),\"icon-pitch-alignment\":new wi(Lt.layout_symbol[\"icon-pitch-alignment\"]),\"text-pitch-alignment\":new wi(Lt.layout_symbol[\"text-pitch-alignment\"]),\"text-rotation-alignment\":new wi(Lt.layout_symbol[\"text-rotation-alignment\"]),\"text-field\":new Ti(Lt.layout_symbol[\"text-field\"]),\"text-font\":new Ti(Lt.layout_symbol[\"text-font\"]),\"text-size\":new Ti(Lt.layout_symbol[\"text-size\"]),\"text-max-width\":new Ti(Lt.layout_symbol[\"text-max-width\"]),\"text-line-height\":new wi(Lt.layout_symbol[\"text-line-height\"]),\"text-letter-spacing\":new Ti(Lt.layout_symbol[\"text-letter-spacing\"]),\"text-justify\":new Ti(Lt.layout_symbol[\"text-justify\"]),\"text-radial-offset\":new Ti(Lt.layout_symbol[\"text-radial-offset\"]),\"text-variable-anchor\":new wi(Lt.layout_symbol[\"text-variable-anchor\"]),\"text-anchor\":new Ti(Lt.layout_symbol[\"text-anchor\"]),\"text-max-angle\":new wi(Lt.layout_symbol[\"text-max-angle\"]),\"text-writing-mode\":new wi(Lt.layout_symbol[\"text-writing-mode\"]),\"text-rotate\":new Ti(Lt.layout_symbol[\"text-rotate\"]),\"text-padding\":new wi(Lt.layout_symbol[\"text-padding\"]),\"text-keep-upright\":new wi(Lt.layout_symbol[\"text-keep-upright\"]),\"text-transform\":new Ti(Lt.layout_symbol[\"text-transform\"]),\"text-offset\":new Ti(Lt.layout_symbol[\"text-offset\"]),\"text-allow-overlap\":new wi(Lt.layout_symbol[\"text-allow-overlap\"]),\"text-ignore-placement\":new wi(Lt.layout_symbol[\"text-ignore-placement\"]),\"text-optional\":new wi(Lt.layout_symbol[\"text-optional\"])}),Ec={paint:new Si({\"icon-opacity\":new Ti(Lt.paint_symbol[\"icon-opacity\"]),\"icon-color\":new Ti(Lt.paint_symbol[\"icon-color\"]),\"icon-halo-color\":new Ti(Lt.paint_symbol[\"icon-halo-color\"]),\"icon-halo-width\":new Ti(Lt.paint_symbol[\"icon-halo-width\"]),\"icon-halo-blur\":new Ti(Lt.paint_symbol[\"icon-halo-blur\"]),\"icon-translate\":new wi(Lt.paint_symbol[\"icon-translate\"]),\"icon-translate-anchor\":new wi(Lt.paint_symbol[\"icon-translate-anchor\"]),\"text-opacity\":new Ti(Lt.paint_symbol[\"text-opacity\"]),\"text-color\":new Ti(Lt.paint_symbol[\"text-color\"],{runtimeType:Ut,getOverride:function(t){return t.textColor},hasOverride:function(t){return!!t.textColor}}),\"text-halo-color\":new Ti(Lt.paint_symbol[\"text-halo-color\"]),\"text-halo-width\":new Ti(Lt.paint_symbol[\"text-halo-width\"]),\"text-halo-blur\":new Ti(Lt.paint_symbol[\"text-halo-blur\"]),\"text-translate\":new wi(Lt.paint_symbol[\"text-translate\"]),\"text-translate-anchor\":new wi(Lt.paint_symbol[\"text-translate-anchor\"])}),layout:Sc},Lc=function(t){this.type=t.property.overrides?t.property.overrides.runtimeType:Ft,this.defaultValue=t};Lc.prototype.evaluate=function(t){if(t.formattedSection){var e=this.defaultValue.property.overrides;if(e&&e.hasOverride(t.formattedSection))return e.getOverride(t.formattedSection)}return t.feature&&t.featureState?this.defaultValue.evaluate(t.feature,t.featureState):this.defaultValue.property.specification.default},Lc.prototype.eachChild=function(t){this.defaultValue.isConstant()||t(this.defaultValue.value._styleExpression.expression)},Lc.prototype.outputDefined=function(){return!1},Lc.prototype.serialize=function(){return null},Nn(\"FormatSectionOverride\",Lc,{omit:[\"defaultValue\"]});var Cc=function(t){function e(e){t.call(this,e,Ec)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.recalculate=function(e,r){if(t.prototype.recalculate.call(this,e,r),\"auto\"===this.layout.get(\"icon-rotation-alignment\")&&(\"point\"!==this.layout.get(\"symbol-placement\")?this.layout._values[\"icon-rotation-alignment\"]=\"map\":this.layout._values[\"icon-rotation-alignment\"]=\"viewport\"),\"auto\"===this.layout.get(\"text-rotation-alignment\")&&(\"point\"!==this.layout.get(\"symbol-placement\")?this.layout._values[\"text-rotation-alignment\"]=\"map\":this.layout._values[\"text-rotation-alignment\"]=\"viewport\"),\"auto\"===this.layout.get(\"text-pitch-alignment\")&&(this.layout._values[\"text-pitch-alignment\"]=this.layout.get(\"text-rotation-alignment\")),\"auto\"===this.layout.get(\"icon-pitch-alignment\")&&(this.layout._values[\"icon-pitch-alignment\"]=this.layout.get(\"icon-rotation-alignment\")),\"point\"===this.layout.get(\"symbol-placement\")){var n=this.layout.get(\"text-writing-mode\");if(n){for(var i=[],a=0,o=n;a<o.length;a+=1){var s=o[a];i.indexOf(s)<0&&i.push(s)}this.layout._values[\"text-writing-mode\"]=i}else this.layout._values[\"text-writing-mode\"]=[\"horizontal\"]}this._setPaintOverrides()},e.prototype.getValueAndResolveTokens=function(t,e,r,n){var i=this.layout.get(t).evaluate(e,{},r,n),a=this._unevaluatedLayout._values[t];return a.isDataDriven()||Yr(a.value)||!i?i:function(t,e){return e.replace(/{([^{}]+)}/g,(function(e,r){return r in t?String(t[r]):\"\"}))}(e.properties,i)},e.prototype.createBucket=function(t){return new Mc(t)},e.prototype.queryRadius=function(){return 0},e.prototype.queryIntersectsFeature=function(){return!1},e.prototype._setPaintOverrides=function(){for(var t=0,r=Ec.paint.overridableProperties;t<r.length;t+=1){var n=r[t];if(e.hasPaintOverride(this.layout,n)){var i=this.paint.get(n),a=new Lc(i),o=new Gr(a,i.property.specification),s=null;s=\"constant\"===i.value.kind||\"source\"===i.value.kind?new Xr(\"source\",o):new Zr(\"composite\",o,i.value.zoomStops,i.value._interpolationType),this.paint._values[n]=new bi(i.property,s,i.parameters)}}},e.prototype._handleOverridablePaintPropertyUpdate=function(t,r,n){return!(!this.layout||r.isDataDriven()||n.isDataDriven())&&e.hasPaintOverride(this.layout,t)},e.hasPaintOverride=function(t,e){var r=t.get(\"text-field\"),n=Ec.paint.properties[e],i=!1,a=function(t){for(var e=0,r=t;e<r.length;e+=1){var a=r[e];if(n.overrides&&n.overrides.hasOverride(a))return void(i=!0)}};if(\"constant\"===r.value.kind&&r.value.value instanceof ne)a(r.value.value.sections);else if(\"source\"===r.value.kind){var o=function(t){if(!i)if(t instanceof ce&&se(t.value)===Gt){var e=t.value;a(e.sections)}else t instanceof pe?a(t.sections):t.eachChild(o)},s=r.value;s._styleExpression&&o(s._styleExpression.expression)}return i},e}(Ei),Pc={paint:new Si({\"background-color\":new wi(Lt.paint_background[\"background-color\"]),\"background-pattern\":new Ai(Lt.paint_background[\"background-pattern\"]),\"background-opacity\":new wi(Lt.paint_background[\"background-opacity\"])})},Ic=function(t){function e(e){t.call(this,e,Pc)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(Ei),Oc={paint:new Si({\"raster-opacity\":new wi(Lt.paint_raster[\"raster-opacity\"]),\"raster-hue-rotate\":new wi(Lt.paint_raster[\"raster-hue-rotate\"]),\"raster-brightness-min\":new wi(Lt.paint_raster[\"raster-brightness-min\"]),\"raster-brightness-max\":new wi(Lt.paint_raster[\"raster-brightness-max\"]),\"raster-saturation\":new wi(Lt.paint_raster[\"raster-saturation\"]),\"raster-contrast\":new wi(Lt.paint_raster[\"raster-contrast\"]),\"raster-resampling\":new wi(Lt.paint_raster[\"raster-resampling\"]),\"raster-fade-duration\":new wi(Lt.paint_raster[\"raster-fade-duration\"])})},zc=function(t){function e(e){t.call(this,e,Oc)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(Ei);var Dc=function(t){function e(e){t.call(this,e,{}),this.implementation=e}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.is3D=function(){return\"3d\"===this.implementation.renderingMode},e.prototype.hasOffscreenPass=function(){return void 0!==this.implementation.prerender},e.prototype.recalculate=function(){},e.prototype.updateTransitions=function(){},e.prototype.hasTransition=function(){},e.prototype.serialize=function(){},e.prototype.onAdd=function(t){this.implementation.onAdd&&this.implementation.onAdd(t,t.painter.context.gl)},e.prototype.onRemove=function(t){this.implementation.onRemove&&this.implementation.onRemove(t,t.painter.context.gl)},e}(Ei),Rc={circle:_o,heatmap:Po,hillshade:Oo,fill:xs,\"fill-extrusion\":Fs,line:Xs,symbol:Cc,background:Ic,raster:zc};var Fc=self.HTMLImageElement,Bc=self.HTMLCanvasElement,Nc=self.HTMLVideoElement,jc=self.ImageData,Uc=self.ImageBitmap,Vc=function(t,e,r,n){this.context=t,this.format=r,this.texture=t.gl.createTexture(),this.update(e,n)};Vc.prototype.update=function(t,e,r){var n=t.width,i=t.height,a=!(this.size&&this.size[0]===n&&this.size[1]===i||r),o=this.context,s=o.gl;if(this.useMipmap=Boolean(e&&e.useMipmap),s.bindTexture(s.TEXTURE_2D,this.texture),o.pixelStoreUnpackFlipY.set(!1),o.pixelStoreUnpack.set(1),o.pixelStoreUnpackPremultiplyAlpha.set(this.format===s.RGBA&&(!e||!1!==e.premultiply)),a)this.size=[n,i],t instanceof Fc||t instanceof Bc||t instanceof Nc||t instanceof jc||Uc&&t instanceof Uc?s.texImage2D(s.TEXTURE_2D,0,this.format,this.format,s.UNSIGNED_BYTE,t):s.texImage2D(s.TEXTURE_2D,0,this.format,n,i,0,this.format,s.UNSIGNED_BYTE,t.data);else{var l=r||{x:0,y:0},c=l.x,u=l.y;t instanceof Fc||t instanceof Bc||t instanceof Nc||t instanceof jc||Uc&&t instanceof Uc?s.texSubImage2D(s.TEXTURE_2D,0,c,u,s.RGBA,s.UNSIGNED_BYTE,t):s.texSubImage2D(s.TEXTURE_2D,0,c,u,n,i,s.RGBA,s.UNSIGNED_BYTE,t.data)}this.useMipmap&&this.isSizePowerOfTwo()&&s.generateMipmap(s.TEXTURE_2D)},Vc.prototype.bind=function(t,e,r){var n=this.context.gl;n.bindTexture(n.TEXTURE_2D,this.texture),r!==n.LINEAR_MIPMAP_NEAREST||this.isSizePowerOfTwo()||(r=n.LINEAR),t!==this.filter&&(n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MAG_FILTER,t),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MIN_FILTER,r||t),this.filter=t),e!==this.wrap&&(n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_S,e),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_T,e),this.wrap=e)},Vc.prototype.isSizePowerOfTwo=function(){return this.size[0]===this.size[1]&&Math.log(this.size[0])/Math.LN2%1==0},Vc.prototype.destroy=function(){this.context.gl.deleteTexture(this.texture),this.texture=null};var qc=function(t){var e=this;this._callback=t,this._triggered=!1,\"undefined\"!=typeof MessageChannel&&(this._channel=new MessageChannel,this._channel.port2.onmessage=function(){e._triggered=!1,e._callback()})};qc.prototype.trigger=function(){var t=this;this._triggered||(this._triggered=!0,this._channel?this._channel.port1.postMessage(!0):setTimeout((function(){t._triggered=!1,t._callback()}),0))},qc.prototype.remove=function(){delete this._channel,this._callback=function(){}};var Hc=function(t,e,r){this.target=t,this.parent=e,this.mapId=r,this.callbacks={},this.tasks={},this.taskQueue=[],this.cancelCallbacks={},g([\"receive\",\"process\"],this),this.invoker=new qc(this.process),this.target.addEventListener(\"message\",this.receive,!1),this.globalScope=k()?t:self};function Gc(t,e,r){var n=2*Math.PI*6378137/256/Math.pow(2,r);return[t*n-2*Math.PI*6378137/2,e*n-2*Math.PI*6378137/2]}Hc.prototype.send=function(t,e,r,n,i){var a=this;void 0===i&&(i=!1);var o=Math.round(1e18*Math.random()).toString(36).substring(0,10);r&&(this.callbacks[o]=r);var s=S(this.globalScope)?void 0:[];return this.target.postMessage({id:o,type:t,hasCallback:!!r,targetMapId:n,mustQueue:i,sourceMapId:this.mapId,data:qn(e,s)},s),{cancel:function(){r&&delete a.callbacks[o],a.target.postMessage({id:o,type:\"<cancel>\",targetMapId:n,sourceMapId:a.mapId})}}},Hc.prototype.receive=function(t){var e=t.data,r=e.id;if(r&&(!e.targetMapId||this.mapId===e.targetMapId))if(\"<cancel>\"===e.type){delete this.tasks[r];var n=this.cancelCallbacks[r];delete this.cancelCallbacks[r],n&&n()}else k()||e.mustQueue?(this.tasks[r]=e,this.taskQueue.push(r),this.invoker.trigger()):this.processTask(r,e)},Hc.prototype.process=function(){if(this.taskQueue.length){var t=this.taskQueue.shift(),e=this.tasks[t];delete this.tasks[t],this.taskQueue.length&&this.invoker.trigger(),e&&this.processTask(t,e)}},Hc.prototype.processTask=function(t,e){var r=this;if(\"<response>\"===e.type){var n=this.callbacks[t];delete this.callbacks[t],n&&(e.error?n(Hn(e.error)):n(null,Hn(e.data)))}else{var i=!1,a=S(this.globalScope)?void 0:[],o=e.hasCallback?function(e,n){i=!0,delete r.cancelCallbacks[t],r.target.postMessage({id:t,type:\"<response>\",sourceMapId:r.mapId,error:e?qn(e):null,data:qn(n,a)},a)}:function(t){i=!0},s=null,l=Hn(e.data);if(this.parent[e.type])s=this.parent[e.type](e.sourceMapId,l,o);else if(this.parent.getWorkerSource){var c=e.type.split(\".\");s=this.parent.getWorkerSource(e.sourceMapId,c[0],l.source)[c[1]](l,o)}else o(new Error(\"Could not find function \"+e.type));!i&&s&&s.cancel&&(this.cancelCallbacks[t]=s.cancel)}},Hc.prototype.remove=function(){this.invoker.remove(),this.target.removeEventListener(\"message\",this.receive,!1)};var Yc=function(t,e){t&&(e?this.setSouthWest(t).setNorthEast(e):4===t.length?this.setSouthWest([t[0],t[1]]).setNorthEast([t[2],t[3]]):this.setSouthWest(t[0]).setNorthEast(t[1]))};Yc.prototype.setNorthEast=function(t){return this._ne=t instanceof Wc?new Wc(t.lng,t.lat):Wc.convert(t),this},Yc.prototype.setSouthWest=function(t){return this._sw=t instanceof Wc?new Wc(t.lng,t.lat):Wc.convert(t),this},Yc.prototype.extend=function(t){var e,r,n=this._sw,i=this._ne;if(t instanceof Wc)e=t,r=t;else{if(!(t instanceof Yc)){if(Array.isArray(t)){if(4===t.length||t.every(Array.isArray)){var a=t;return this.extend(Yc.convert(a))}var o=t;return this.extend(Wc.convert(o))}return this}if(e=t._sw,r=t._ne,!e||!r)return this}return n||i?(n.lng=Math.min(e.lng,n.lng),n.lat=Math.min(e.lat,n.lat),i.lng=Math.max(r.lng,i.lng),i.lat=Math.max(r.lat,i.lat)):(this._sw=new Wc(e.lng,e.lat),this._ne=new Wc(r.lng,r.lat)),this},Yc.prototype.getCenter=function(){return new Wc((this._sw.lng+this._ne.lng)/2,(this._sw.lat+this._ne.lat)/2)},Yc.prototype.getSouthWest=function(){return this._sw},Yc.prototype.getNorthEast=function(){return this._ne},Yc.prototype.getNorthWest=function(){return new Wc(this.getWest(),this.getNorth())},Yc.prototype.getSouthEast=function(){return new Wc(this.getEast(),this.getSouth())},Yc.prototype.getWest=function(){return this._sw.lng},Yc.prototype.getSouth=function(){return this._sw.lat},Yc.prototype.getEast=function(){return this._ne.lng},Yc.prototype.getNorth=function(){return this._ne.lat},Yc.prototype.toArray=function(){return[this._sw.toArray(),this._ne.toArray()]},Yc.prototype.toString=function(){return\"LngLatBounds(\"+this._sw.toString()+\", \"+this._ne.toString()+\")\"},Yc.prototype.isEmpty=function(){return!(this._sw&&this._ne)},Yc.prototype.contains=function(t){var e=Wc.convert(t),r=e.lng,n=e.lat,i=this._sw.lat<=n&&n<=this._ne.lat,a=this._sw.lng<=r&&r<=this._ne.lng;return this._sw.lng>this._ne.lng&&(a=this._sw.lng>=r&&r>=this._ne.lng),i&&a},Yc.convert=function(t){return!t||t instanceof Yc?t:new Yc(t)};var Wc=function(t,e){if(isNaN(t)||isNaN(e))throw new Error(\"Invalid LngLat object: (\"+t+\", \"+e+\")\");if(this.lng=+t,this.lat=+e,this.lat>90||this.lat<-90)throw new Error(\"Invalid LngLat latitude value: must be between -90 and 90\")};Wc.prototype.wrap=function(){return new Wc(c(this.lng,-180,180),this.lat)},Wc.prototype.toArray=function(){return[this.lng,this.lat]},Wc.prototype.toString=function(){return\"LngLat(\"+this.lng+\", \"+this.lat+\")\"},Wc.prototype.distanceTo=function(t){var e=Math.PI/180,r=this.lat*e,n=t.lat*e,i=Math.sin(r)*Math.sin(n)+Math.cos(r)*Math.cos(n)*Math.cos((t.lng-this.lng)*e);return 6371008.8*Math.acos(Math.min(i,1))},Wc.prototype.toBounds=function(t){void 0===t&&(t=0);var e=360*t/40075017,r=e/Math.cos(Math.PI/180*this.lat);return new Yc(new Wc(this.lng-r,this.lat-e),new Wc(this.lng+r,this.lat+e))},Wc.convert=function(t){if(t instanceof Wc)return t;if(Array.isArray(t)&&(2===t.length||3===t.length))return new Wc(Number(t[0]),Number(t[1]));if(!Array.isArray(t)&&\"object\"==typeof t&&null!==t)return new Wc(Number(\"lng\"in t?t.lng:t.lon),Number(t.lat));throw new Error(\"`LngLatLike` argument must be specified as a LngLat instance, an object {lng: <lng>, lat: <lat>}, an object {lon: <lng>, lat: <lat>}, or an array of [<lng>, <lat>]\")};var Xc=2*Math.PI*6371008.8;function Zc(t){return Xc*Math.cos(t*Math.PI/180)}function Jc(t){return(180+t)/360}function Kc(t){return(180-180/Math.PI*Math.log(Math.tan(Math.PI/4+t*Math.PI/360)))/360}function Qc(t,e){return t/Zc(e)}function $c(t){var e=180-360*t;return 360/Math.PI*Math.atan(Math.exp(e*Math.PI/180))-90}var tu=function(t,e,r){void 0===r&&(r=0),this.x=+t,this.y=+e,this.z=+r};tu.fromLngLat=function(t,e){void 0===e&&(e=0);var r=Wc.convert(t);return new tu(Jc(r.lng),Kc(r.lat),Qc(e,r.lat))},tu.prototype.toLngLat=function(){return new Wc(360*this.x-180,$c(this.y))},tu.prototype.toAltitude=function(){return t=this.z,e=this.y,t*Zc($c(e));var t,e},tu.prototype.meterInMercatorCoordinateUnits=function(){return 1/Xc*(t=$c(this.y),1/Math.cos(t*Math.PI/180));var t};var eu=function(t,e,r){this.z=t,this.x=e,this.y=r,this.key=iu(0,t,t,e,r)};eu.prototype.equals=function(t){return this.z===t.z&&this.x===t.x&&this.y===t.y},eu.prototype.url=function(t,e){var r,n,i,a,o,s=(r=this.x,n=this.y,i=this.z,a=Gc(256*r,256*(n=Math.pow(2,i)-n-1),i),o=Gc(256*(r+1),256*(n+1),i),a[0]+\",\"+a[1]+\",\"+o[0]+\",\"+o[1]),l=function(t,e,r){for(var n,i=\"\",a=t;a>0;a--)i+=(e&(n=1<<a-1)?1:0)+(r&n?2:0);return i}(this.z,this.x,this.y);return t[(this.x+this.y)%t.length].replace(\"{prefix}\",(this.x%16).toString(16)+(this.y%16).toString(16)).replace(\"{z}\",String(this.z)).replace(\"{x}\",String(this.x)).replace(\"{y}\",String(\"tms\"===e?Math.pow(2,this.z)-this.y-1:this.y)).replace(\"{quadkey}\",l).replace(\"{bbox-epsg-3857}\",s)},eu.prototype.getTilePoint=function(t){var e=Math.pow(2,this.z);return new i(8192*(t.x*e-this.x),8192*(t.y*e-this.y))},eu.prototype.toString=function(){return this.z+\"/\"+this.x+\"/\"+this.y};var ru=function(t,e){this.wrap=t,this.canonical=e,this.key=iu(t,e.z,e.z,e.x,e.y)},nu=function(t,e,r,n,i){this.overscaledZ=t,this.wrap=e,this.canonical=new eu(r,+n,+i),this.key=iu(e,t,r,n,i)};function iu(t,e,r,n,i){(t*=2)<0&&(t=-1*t-1);var a=1<<r;return(a*a*t+a*i+n).toString(36)+r.toString(36)+e.toString(36)}nu.prototype.equals=function(t){return this.overscaledZ===t.overscaledZ&&this.wrap===t.wrap&&this.canonical.equals(t.canonical)},nu.prototype.scaledTo=function(t){var e=this.canonical.z-t;return t>this.canonical.z?new nu(t,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y):new nu(t,this.wrap,t,this.canonical.x>>e,this.canonical.y>>e)},nu.prototype.calculateScaledKey=function(t,e){var r=this.canonical.z-t;return t>this.canonical.z?iu(this.wrap*+e,t,this.canonical.z,this.canonical.x,this.canonical.y):iu(this.wrap*+e,t,t,this.canonical.x>>r,this.canonical.y>>r)},nu.prototype.isChildOf=function(t){if(t.wrap!==this.wrap)return!1;var e=this.canonical.z-t.canonical.z;return 0===t.overscaledZ||t.overscaledZ<this.overscaledZ&&t.canonical.x===this.canonical.x>>e&&t.canonical.y===this.canonical.y>>e},nu.prototype.children=function(t){if(this.overscaledZ>=t)return[new nu(this.overscaledZ+1,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y)];var e=this.canonical.z+1,r=2*this.canonical.x,n=2*this.canonical.y;return[new nu(e,this.wrap,e,r,n),new nu(e,this.wrap,e,r+1,n),new nu(e,this.wrap,e,r,n+1),new nu(e,this.wrap,e,r+1,n+1)]},nu.prototype.isLessThan=function(t){return this.wrap<t.wrap||!(this.wrap>t.wrap)&&(this.overscaledZ<t.overscaledZ||!(this.overscaledZ>t.overscaledZ)&&(this.canonical.x<t.canonical.x||!(this.canonical.x>t.canonical.x)&&this.canonical.y<t.canonical.y))},nu.prototype.wrapped=function(){return new nu(this.overscaledZ,0,this.canonical.z,this.canonical.x,this.canonical.y)},nu.prototype.unwrapTo=function(t){return new nu(this.overscaledZ,t,this.canonical.z,this.canonical.x,this.canonical.y)},nu.prototype.overscaleFactor=function(){return Math.pow(2,this.overscaledZ-this.canonical.z)},nu.prototype.toUnwrapped=function(){return new ru(this.wrap,this.canonical)},nu.prototype.toString=function(){return this.overscaledZ+\"/\"+this.canonical.x+\"/\"+this.canonical.y},nu.prototype.getTilePoint=function(t){return this.canonical.getTilePoint(new tu(t.x-this.wrap,t.y))},Nn(\"CanonicalTileID\",eu),Nn(\"OverscaledTileID\",nu,{omit:[\"posMatrix\"]});var au=function(t,e,r){if(this.uid=t,e.height!==e.width)throw new RangeError(\"DEM tiles must be square\");if(r&&\"mapbox\"!==r&&\"terrarium\"!==r)return _('\"'+r+'\" is not a valid encoding type. Valid types include \"mapbox\" and \"terrarium\".');this.stride=e.height;var n=this.dim=e.height-2;this.data=new Uint32Array(e.data.buffer),this.encoding=r||\"mapbox\";for(var i=0;i<n;i++)this.data[this._idx(-1,i)]=this.data[this._idx(0,i)],this.data[this._idx(n,i)]=this.data[this._idx(n-1,i)],this.data[this._idx(i,-1)]=this.data[this._idx(i,0)],this.data[this._idx(i,n)]=this.data[this._idx(i,n-1)];this.data[this._idx(-1,-1)]=this.data[this._idx(0,0)],this.data[this._idx(n,-1)]=this.data[this._idx(n-1,0)],this.data[this._idx(-1,n)]=this.data[this._idx(0,n-1)],this.data[this._idx(n,n)]=this.data[this._idx(n-1,n-1)]};au.prototype.get=function(t,e){var r=new Uint8Array(this.data.buffer),n=4*this._idx(t,e);return(\"terrarium\"===this.encoding?this._unpackTerrarium:this._unpackMapbox)(r[n],r[n+1],r[n+2])},au.prototype.getUnpackVector=function(){return\"terrarium\"===this.encoding?[256,1,1/256,32768]:[6553.6,25.6,.1,1e4]},au.prototype._idx=function(t,e){if(t<-1||t>=this.dim+1||e<-1||e>=this.dim+1)throw new RangeError(\"out of range source coordinates for DEM data\");return(e+1)*this.stride+(t+1)},au.prototype._unpackMapbox=function(t,e,r){return(256*t*256+256*e+r)/10-1e4},au.prototype._unpackTerrarium=function(t,e,r){return 256*t+e+r/256-32768},au.prototype.getPixels=function(){return new Eo({width:this.stride,height:this.stride},new Uint8Array(this.data.buffer))},au.prototype.backfillBorder=function(t,e,r){if(this.dim!==t.dim)throw new Error(\"dem dimension mismatch\");var n=e*this.dim,i=e*this.dim+this.dim,a=r*this.dim,o=r*this.dim+this.dim;switch(e){case-1:n=i-1;break;case 1:i=n+1}switch(r){case-1:a=o-1;break;case 1:o=a+1}for(var s=-e*this.dim,l=-r*this.dim,c=a;c<o;c++)for(var u=n;u<i;u++)this.data[this._idx(u,c)]=t.data[this._idx(u+s,c+l)]},Nn(\"DEMData\",au);var ou=function(t){this._stringToNumber={},this._numberToString=[];for(var e=0;e<t.length;e++){var r=t[e];this._stringToNumber[r]=e,this._numberToString[e]=r}};ou.prototype.encode=function(t){return this._stringToNumber[t]},ou.prototype.decode=function(t){return this._numberToString[t]};var su=function(t,e,r,n,i){this.type=\"Feature\",this._vectorTileFeature=t,t._z=e,t._x=r,t._y=n,this.properties=t.properties,this.id=i},lu={geometry:{configurable:!0}};lu.geometry.get=function(){return void 0===this._geometry&&(this._geometry=this._vectorTileFeature.toGeoJSON(this._vectorTileFeature._x,this._vectorTileFeature._y,this._vectorTileFeature._z).geometry),this._geometry},lu.geometry.set=function(t){this._geometry=t},su.prototype.toJSON=function(){var t={geometry:this.geometry};for(var e in this)\"_geometry\"!==e&&\"_vectorTileFeature\"!==e&&(t[e]=this[e]);return t},Object.defineProperties(su.prototype,lu);var cu=function(){this.state={},this.stateChanges={},this.deletedStates={}};cu.prototype.updateState=function(t,e,r){var n=String(e);if(this.stateChanges[t]=this.stateChanges[t]||{},this.stateChanges[t][n]=this.stateChanges[t][n]||{},u(this.stateChanges[t][n],r),null===this.deletedStates[t])for(var i in this.deletedStates[t]={},this.state[t])i!==n&&(this.deletedStates[t][i]=null);else if(this.deletedStates[t]&&null===this.deletedStates[t][n])for(var a in this.deletedStates[t][n]={},this.state[t][n])r[a]||(this.deletedStates[t][n][a]=null);else for(var o in r){this.deletedStates[t]&&this.deletedStates[t][n]&&null===this.deletedStates[t][n][o]&&delete this.deletedStates[t][n][o]}},cu.prototype.removeFeatureState=function(t,e,r){if(!(null===this.deletedStates[t])){var n=String(e);if(this.deletedStates[t]=this.deletedStates[t]||{},r&&void 0!==e)null!==this.deletedStates[t][n]&&(this.deletedStates[t][n]=this.deletedStates[t][n]||{},this.deletedStates[t][n][r]=null);else if(void 0!==e){if(this.stateChanges[t]&&this.stateChanges[t][n])for(r in this.deletedStates[t][n]={},this.stateChanges[t][n])this.deletedStates[t][n][r]=null;else this.deletedStates[t][n]=null}else this.deletedStates[t]=null}},cu.prototype.getState=function(t,e){var r=String(e),n=this.state[t]||{},i=this.stateChanges[t]||{},a=u({},n[r],i[r]);if(null===this.deletedStates[t])return{};if(this.deletedStates[t]){var o=this.deletedStates[t][e];if(null===o)return{};for(var s in o)delete a[s]}return a},cu.prototype.initializeTileState=function(t,e){t.setFeatureState(this.state,e)},cu.prototype.coalesceChanges=function(t,e){var r={};for(var n in this.stateChanges){this.state[n]=this.state[n]||{};var i={};for(var a in this.stateChanges[n])this.state[n][a]||(this.state[n][a]={}),u(this.state[n][a],this.stateChanges[n][a]),i[a]=this.state[n][a];r[n]=i}for(var o in this.deletedStates){this.state[o]=this.state[o]||{};var s={};if(null===this.deletedStates[o])for(var l in this.state[o])s[l]={},this.state[o][l]={};else for(var c in this.deletedStates[o]){if(null===this.deletedStates[o][c])this.state[o][c]={};else for(var f=0,h=Object.keys(this.deletedStates[o][c]);f<h.length;f+=1){var p=h[f];delete this.state[o][c][p]}s[c]=this.state[o][c]}r[o]=r[o]||{},u(r[o],s)}if(this.stateChanges={},this.deletedStates={},0!==Object.keys(r).length)for(var d in t){t[d].setFeatureState(r,e)}};var uu=function(t,e){this.tileID=t,this.x=t.canonical.x,this.y=t.canonical.y,this.z=t.canonical.z,this.grid=new zn(8192,16,0),this.grid3D=new zn(8192,16,0),this.featureIndexArray=new fa,this.promoteId=e};function fu(t,e,r,n,i){return v(t,(function(t,a){var o=e instanceof _i?e.get(a):null;return o&&o.evaluate?o.evaluate(r,n,i):o}))}function hu(t){for(var e=1/0,r=1/0,n=-1/0,i=-1/0,a=0,o=t;a<o.length;a+=1){var s=o[a];e=Math.min(e,s.x),r=Math.min(r,s.y),n=Math.max(n,s.x),i=Math.max(i,s.y)}return{minX:e,minY:r,maxX:n,maxY:i}}function pu(t,e){return e-t}uu.prototype.insert=function(t,e,r,n,i,a){var o=this.featureIndexArray.length;this.featureIndexArray.emplaceBack(r,n,i);for(var s=a?this.grid3D:this.grid,l=0;l<e.length;l++){for(var c=e[l],u=[1/0,1/0,-1/0,-1/0],f=0;f<c.length;f++){var h=c[f];u[0]=Math.min(u[0],h.x),u[1]=Math.min(u[1],h.y),u[2]=Math.max(u[2],h.x),u[3]=Math.max(u[3],h.y)}u[0]<8192&&u[1]<8192&&u[2]>=0&&u[3]>=0&&s.insert(o,u[0],u[1],u[2],u[3])}},uu.prototype.loadVTLayers=function(){return this.vtLayers||(this.vtLayers=new Ls.VectorTile(new al(this.rawTileData)).layers,this.sourceLayerCoder=new ou(this.vtLayers?Object.keys(this.vtLayers).sort():[\"_geojsonTileLayer\"])),this.vtLayers},uu.prototype.query=function(t,e,r,n){var a=this;this.loadVTLayers();for(var o=t.params||{},s=8192/t.tileSize/t.scale,l=sn(o.filter),c=t.queryGeometry,u=t.queryPadding*s,f=hu(c),h=this.grid.query(f.minX-u,f.minY-u,f.maxX+u,f.maxY+u),p=hu(t.cameraQueryGeometry),d=this.grid3D.query(p.minX-u,p.minY-u,p.maxX+u,p.maxY+u,(function(e,r,n,a){return function(t,e,r,n,a){for(var o=0,s=t;o<s.length;o+=1){var l=s[o];if(e<=l.x&&r<=l.y&&n>=l.x&&a>=l.y)return!0}var c=[new i(e,r),new i(e,a),new i(n,a),new i(n,r)];if(t.length>2)for(var u=0,f=c;u<f.length;u+=1){if(io(t,f[u]))return!0}for(var h=0;h<t.length-1;h++){if(ao(t[h],t[h+1],c))return!0}return!1}(t.cameraQueryGeometry,e-u,r-u,n+u,a+u)})),g=0,m=d;g<m.length;g+=1){var v=m[g];h.push(v)}h.sort(pu);for(var y,x={},b=function(i){var u=h[i];if(u!==y){y=u;var f=a.featureIndexArray.get(u),p=null;a.loadMatchingFeature(x,f.bucketIndex,f.sourceLayerIndex,f.featureIndex,l,o.layers,o.availableImages,e,r,n,(function(e,r,n){return p||(p=Ya(e)),r.queryIntersectsFeature(c,e,n,p,a.z,t.transform,s,t.pixelPosMatrix)}))}},_=0;_<h.length;_++)b(_);return x},uu.prototype.loadMatchingFeature=function(t,e,r,n,i,a,o,s,l,c,u){var f=this.bucketLayerIDs[e];if(!a||function(t,e){for(var r=0;r<t.length;r++)if(e.indexOf(t[r])>=0)return!0;return!1}(a,f)){var h=this.sourceLayerCoder.decode(r),p=this.vtLayers[h].feature(n);if(i.filter(new pi(this.tileID.overscaledZ),p))for(var d=this.getId(p,h),g=0;g<f.length;g++){var m=f[g];if(!(a&&a.indexOf(m)<0)){var v=s[m];if(v){var y={};void 0!==d&&c&&(y=c.getState(v.sourceLayer||\"_geojsonTileLayer\",d));var x=l[m];x.paint=fu(x.paint,v.paint,p,y,o),x.layout=fu(x.layout,v.layout,p,y,o);var b=!u||u(p,v,y);if(b){var _=new su(p,this.z,this.x,this.y,d);_.layer=x;var w=t[m];void 0===w&&(w=t[m]=[]),w.push({featureIndex:n,feature:_,intersectionZ:b})}}}}}},uu.prototype.lookupSymbolFeatures=function(t,e,r,n,i,a,o,s){var l={};this.loadVTLayers();for(var c=sn(i),u=0,f=t;u<f.length;u+=1){var h=f[u];this.loadMatchingFeature(l,r,n,h,c,a,o,s,e)}return l},uu.prototype.hasLayer=function(t){for(var e=0,r=this.bucketLayerIDs;e<r.length;e+=1)for(var n=0,i=r[e];n<i.length;n+=1){if(t===i[n])return!0}return!1},uu.prototype.getId=function(t,e){var r=t.id;if(this.promoteId){var n=\"string\"==typeof this.promoteId?this.promoteId:this.promoteId[e];\"boolean\"==typeof(r=t.properties[n])&&(r=Number(r))}return r},Nn(\"FeatureIndex\",uu,{omit:[\"rawTileData\",\"sourceLayerCoder\"]});var du=function(t,e){this.tileID=t,this.uid=h(),this.uses=0,this.tileSize=e,this.buckets={},this.expirationTime=null,this.queryPadding=0,this.hasSymbolBuckets=!1,this.hasRTLText=!1,this.dependencies={},this.expiredRequestCount=0,this.state=\"loading\"};du.prototype.registerFadeDuration=function(t){var e=t+this.timeAdded;e<R.now()||this.fadeEndTime&&e<this.fadeEndTime||(this.fadeEndTime=e)},du.prototype.wasRequested=function(){return\"errored\"===this.state||\"loaded\"===this.state||\"reloading\"===this.state},du.prototype.loadVectorData=function(t,e,r){if(this.hasData()&&this.unloadVectorData(),this.state=\"loaded\",t){for(var n in t.featureIndex&&(this.latestFeatureIndex=t.featureIndex,t.rawTileData?(this.latestRawTileData=t.rawTileData,this.latestFeatureIndex.rawTileData=t.rawTileData):this.latestRawTileData&&(this.latestFeatureIndex.rawTileData=this.latestRawTileData)),this.collisionBoxArray=t.collisionBoxArray,this.buckets=function(t,e){var r={};if(!e)return r;for(var n=function(){var t=a[i],n=t.layerIds.map((function(t){return e.getLayer(t)})).filter(Boolean);if(0!==n.length){t.layers=n,t.stateDependentLayerIds&&(t.stateDependentLayers=t.stateDependentLayerIds.map((function(t){return n.filter((function(e){return e.id===t}))[0]})));for(var o=0,s=n;o<s.length;o+=1){var l=s[o];r[l.id]=t}}},i=0,a=t;i<a.length;i+=1)n();return r}(t.buckets,e.style),this.hasSymbolBuckets=!1,this.buckets){var i=this.buckets[n];if(i instanceof Mc){if(this.hasSymbolBuckets=!0,!r)break;i.justReloaded=!0}}if(this.hasRTLText=!1,this.hasSymbolBuckets)for(var a in this.buckets){var o=this.buckets[a];if(o instanceof Mc&&o.hasRTLText){this.hasRTLText=!0,hi.isLoading()||hi.isLoaded()||\"deferred\"!==ui()||fi();break}}for(var s in this.queryPadding=0,this.buckets){var l=this.buckets[s];this.queryPadding=Math.max(this.queryPadding,e.style.getLayer(s).queryRadius(l))}t.imageAtlas&&(this.imageAtlas=t.imageAtlas),t.glyphAtlasImage&&(this.glyphAtlasImage=t.glyphAtlasImage)}else this.collisionBoxArray=new na},du.prototype.unloadVectorData=function(){for(var t in this.buckets)this.buckets[t].destroy();this.buckets={},this.imageAtlasTexture&&this.imageAtlasTexture.destroy(),this.imageAtlas&&(this.imageAtlas=null),this.glyphAtlasTexture&&this.glyphAtlasTexture.destroy(),this.latestFeatureIndex=null,this.state=\"unloaded\"},du.prototype.getBucket=function(t){return this.buckets[t.id]},du.prototype.upload=function(t){for(var e in this.buckets){var r=this.buckets[e];r.uploadPending()&&r.upload(t)}var n=t.gl;this.imageAtlas&&!this.imageAtlas.uploaded&&(this.imageAtlasTexture=new Vc(t,this.imageAtlas.image,n.RGBA),this.imageAtlas.uploaded=!0),this.glyphAtlasImage&&(this.glyphAtlasTexture=new Vc(t,this.glyphAtlasImage,n.ALPHA),this.glyphAtlasImage=null)},du.prototype.prepare=function(t){this.imageAtlas&&this.imageAtlas.patchUpdatedImages(t,this.imageAtlasTexture)},du.prototype.queryRenderedFeatures=function(t,e,r,n,i,a,o,s,l,c){return this.latestFeatureIndex&&this.latestFeatureIndex.rawTileData?this.latestFeatureIndex.query({queryGeometry:n,cameraQueryGeometry:i,scale:a,tileSize:this.tileSize,pixelPosMatrix:c,transform:s,params:o,queryPadding:this.queryPadding*l},t,e,r):{}},du.prototype.querySourceFeatures=function(t,e){var r=this.latestFeatureIndex;if(r&&r.rawTileData){var n=r.loadVTLayers(),i=e?e.sourceLayer:\"\",a=n._geojsonTileLayer||n[i];if(a)for(var o=sn(e&&e.filter),s=this.tileID.canonical,l=s.z,c=s.x,u=s.y,f={z:l,x:c,y:u},h=0;h<a.length;h++){var p=a.feature(h);if(o.filter(new pi(this.tileID.overscaledZ),p)){var d=r.getId(p,i),g=new su(p,l,c,u,d);g.tile=f,t.push(g)}}}},du.prototype.hasData=function(){return\"loaded\"===this.state||\"reloading\"===this.state||\"expired\"===this.state},du.prototype.patternsLoaded=function(){return this.imageAtlas&&!!Object.keys(this.imageAtlas.patternPositions).length},du.prototype.setExpiryData=function(t){var e=this.expirationTime;if(t.cacheControl){var r=A(t.cacheControl);r[\"max-age\"]&&(this.expirationTime=Date.now()+1e3*r[\"max-age\"])}else t.expires&&(this.expirationTime=new Date(t.expires).getTime());if(this.expirationTime){var n=Date.now(),i=!1;if(this.expirationTime>n)i=!1;else if(e)if(this.expirationTime<e)i=!0;else{var a=this.expirationTime-e;a?this.expirationTime=n+Math.max(a,3e4):i=!0}else i=!0;i?(this.expiredRequestCount++,this.state=\"expired\"):this.expiredRequestCount=0}},du.prototype.getExpiryTimeout=function(){if(this.expirationTime)return this.expiredRequestCount?1e3*(1<<Math.min(this.expiredRequestCount-1,31)):Math.min(this.expirationTime-(new Date).getTime(),Math.pow(2,31)-1)},du.prototype.setFeatureState=function(t,e){if(this.latestFeatureIndex&&this.latestFeatureIndex.rawTileData&&0!==Object.keys(t).length){var r=this.latestFeatureIndex.loadVTLayers();for(var n in this.buckets)if(e.style.hasLayer(n)){var i=this.buckets[n],a=i.layers[0].sourceLayer||\"_geojsonTileLayer\",o=r[a],s=t[a];if(o&&s&&0!==Object.keys(s).length){i.update(s,o,this.imageAtlas&&this.imageAtlas.patternPositions||{});var l=e&&e.style&&e.style.getLayer(n);l&&(this.queryPadding=Math.max(this.queryPadding,l.queryRadius(i)))}}}},du.prototype.holdingForFade=function(){return void 0!==this.symbolFadeHoldUntil},du.prototype.symbolFadeFinished=function(){return!this.symbolFadeHoldUntil||this.symbolFadeHoldUntil<R.now()},du.prototype.clearFadeHold=function(){this.symbolFadeHoldUntil=void 0},du.prototype.setHoldDuration=function(t){this.symbolFadeHoldUntil=R.now()+t},du.prototype.setDependencies=function(t,e){for(var r={},n=0,i=e;n<i.length;n+=1){r[i[n]]=!0}this.dependencies[t]=r},du.prototype.hasDependency=function(t,e){for(var r=0,n=t;r<n.length;r+=1){var i=n[r],a=this.dependencies[i];if(a)for(var o=0,s=e;o<s.length;o+=1){if(a[s[o]])return!0}}return!1};var 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r},t.makeRequest=yt,t.mapObject=v,t.mercatorXfromLng=Jc,t.mercatorYfromLat=Kc,t.mercatorZfromAltitude=Qc,t.mul=go,t.multiply=po,t.mvt=Ls,t.normalize=function(t,e){var r=e[0],n=e[1],i=e[2],a=r*r+n*n+i*i;return a>0&&(a=1/Math.sqrt(a)),t[0]=e[0]*a,t[1]=e[1]*a,t[2]=e[2]*a,t},t.number=He,t.offscreenCanvasSupported=pt,t.ortho=function(t,e,r,n,i,a,o){var s=1/(e-r),l=1/(n-i),c=1/(a-o);return t[0]=-2*s,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=-2*l,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=2*c,t[11]=0,t[12]=(e+r)*s,t[13]=(i+n)*l,t[14]=(o+a)*c,t[15]=1,t},t.parseGlyphPBF=function(t){return new al(t).readFields(Tl,[])},t.pbf=al,t.performSymbolLayout=function(t,e,r,n,i,a,o){t.createArrays();var s=512*t.overscaling;t.tilePixelRatio=8192/s,t.compareText={},t.iconsNeedLinear=!1;var l=t.layers[0].layout,c=t.layers[0]._unevaluatedLayout._values,u={};if(\"composite\"===t.textSizeData.kind){var f=t.textSizeData,h=f.minZoom,p=f.maxZoom;u.compositeTextSizes=[c[\"text-size\"].possiblyEvaluate(new 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m=(c+1)%2;(0===c?r-i<=d:n-i<=g)&&(o.push(f),o.push(p-1),o.push(m)),(0===c?r+i>=d:n+i>=g)&&(o.push(p+1),o.push(u),o.push(m))}}return s}(this.ids,this.coords,t,e,r,this.nodeSize)};var j={minZoom:0,maxZoom:16,radius:40,extent:512,nodeSize:64,log:!1,generateId:!1,reduce:null,map:function(t){return t}},U=function(t){this.options=X(Object.create(j),t),this.trees=new Array(this.options.maxZoom+1)};function V(t,e,r,n,i){return{x:t,y:e,zoom:1/0,id:r,parentId:-1,numPoints:n,properties:i}}function q(t,e){var r=t.geometry.coordinates,n=r[0],i=r[1];return{x:Y(n),y:W(i),zoom:1/0,index:e,parentId:-1}}function H(t){return{type:\"Feature\",id:t.id,properties:G(t),geometry:{type:\"Point\",coordinates:[(n=t.x,360*(n-.5)),(e=t.y,r=(180-360*e)*Math.PI/180,360*Math.atan(Math.exp(r))/Math.PI-90)]}};var e,r,n}function G(t){var e=t.numPoints,r=e>=1e4?Math.round(e/1e3)+\"k\":e>=1e3?Math.round(e/100)/10+\"k\":e;return 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r=0;r<e.length;r+=3)t.minX=Math.min(t.minX,e[r]),t.minY=Math.min(t.minY,e[r+1]),t.maxX=Math.max(t.maxX,e[r]),t.maxY=Math.max(t.maxY,e[r+1])}function tt(t,e,r,n){if(e.geometry){var i=e.geometry.coordinates,a=e.geometry.type,o=Math.pow(r.tolerance/((1<<r.maxZoom)*r.extent),2),s=[],l=e.id;if(r.promoteId?l=e.properties[r.promoteId]:r.generateId&&(l=n||0),\"Point\"===a)et(i,s);else if(\"MultiPoint\"===a)for(var c=0;c<i.length;c++)et(i[c],s);else if(\"LineString\"===a)rt(i,s,o,!1);else if(\"MultiLineString\"===a){if(r.lineMetrics){for(c=0;c<i.length;c++)s=[],rt(i[c],s,o,!1),t.push(Q(l,\"LineString\",s,e.properties));return}nt(i,s,o,!1)}else if(\"Polygon\"===a)nt(i,s,o,!0);else{if(\"MultiPolygon\"!==a){if(\"GeometryCollection\"===a){for(c=0;c<e.geometry.geometries.length;c++)tt(t,{id:l,geometry:e.geometry.geometries[c],properties:e.properties},r,n);return}throw new Error(\"Input data is not a valid GeoJSON object.\")}for(c=0;c<i.length;c++){var 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r=[],n=0;n<t.length;n++){var i,a=t[n],o=a.type;if(\"Point\"===o||\"MultiPoint\"===o||\"LineString\"===o)i=gt(a.geometry,e);else if(\"MultiLineString\"===o||\"Polygon\"===o){i=[];for(var s=0;s<a.geometry.length;s++)i.push(gt(a.geometry[s],e))}else if(\"MultiPolygon\"===o)for(i=[],s=0;s<a.geometry.length;s++){for(var l=[],c=0;c<a.geometry[s].length;c++)l.push(gt(a.geometry[s][c],e));i.push(l)}r.push(Q(a.id,o,i,a.tags))}return r}function gt(t,e){var r=[];r.size=t.size,void 0!==t.start&&(r.start=t.start,r.end=t.end);for(var n=0;n<t.length;n+=3)r.push(t[n]+e,t[n+1],t[n+2]);return r}function mt(t,e){if(t.transformed)return t;var r,n,i,a=1<<t.z,o=t.x,s=t.y;for(r=0;r<t.features.length;r++){var l=t.features[r],c=l.geometry,u=l.type;if(l.geometry=[],1===u)for(n=0;n<c.length;n+=2)l.geometry.push(vt(c[n],c[n+1],e,a,o,s));else for(n=0;n<c.length;n++){var f=[];for(i=0;i<c[n].length;i+=2)f.push(vt(c[n][i],c[n][i+1],e,a,o,s));l.geometry.push(f)}}return t.transformed=!0,t}function 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u={},e.tags)u[f]=e.tags[f];u.mapbox_clip_start=i.start/i.size,u.mapbox_clip_end=i.end/i.size}var h={geometry:o,type:\"Polygon\"===a||\"MultiPolygon\"===a?3:\"LineString\"===a||\"MultiLineString\"===a?2:1,tags:u};null!==e.id&&(h.id=e.id),t.features.push(h)}}function bt(t,e,r,n,i,a){var o=n*n;if(n>0&&e.size<(i?o:n))r.numPoints+=e.length/3;else{for(var s=[],l=0;l<e.length;l+=3)(0===n||e[l+2]>o)&&(r.numSimplified++,s.push(e[l]),s.push(e[l+1])),r.numPoints++;i&&function(t,e){for(var r=0,n=0,i=t.length,a=i-2;n<i;a=n,n+=2)r+=(t[n]-t[a])*(t[n+1]+t[a+1]);if(r>0===e)for(n=0,i=t.length;n<i/2;n+=2){var o=t[n],s=t[n+1];t[n]=t[i-2-n],t[n+1]=t[i-1-n],t[i-2-n]=o,t[i-1-n]=s}}(s,a),t.push(s)}}function _t(t,e){var r=(e=this.options=function(t,e){for(var r in e)t[r]=e[r];return t}(Object.create(this.options),e)).debug;if(r&&console.time(\"preprocess data\"),e.maxZoom<0||e.maxZoom>24)throw new Error(\"maxZoom should be in the 0-24 range\");if(e.promoteId&&e.generateId)throw new Error(\"promoteId and generateId cannot be used together.\");var n=function(t,e){var r=[];if(\"FeatureCollection\"===t.type)for(var n=0;n<t.features.length;n++)tt(r,t.features[n],e,n);else\"Feature\"===t.type?tt(r,t,e):tt(r,{geometry:t},e);return r}(t,e);this.tiles={},this.tileCoords=[],r&&(console.timeEnd(\"preprocess data\"),console.log(\"index: maxZoom: %d, maxPoints: %d\",e.indexMaxZoom,e.indexMaxPoints),console.time(\"generate tiles\"),this.stats={},this.total=0),(n=function(t,e){var r=e.buffer/e.extent,n=t,i=ot(t,1,-1-r,r,0,-1,2,e),a=ot(t,1,1-r,2+r,0,-1,2,e);return(i||a)&&(n=ot(t,1,-r,1+r,0,-1,2,e)||[],i&&(n=dt(i,1).concat(n)),a&&(n=n.concat(dt(a,-1)))),n}(n,e)).length&&this.splitTile(n,0,0,0),r&&(n.length&&console.log(\"features: %d, points: %d\",this.tiles[0].numFeatures,this.tiles[0].numPoints),console.timeEnd(\"generate tiles\"),console.log(\"tiles generated:\",this.total,JSON.stringify(this.stats)))}function wt(t,e,r){return 32*((1<<t)*r+e)+t}function Tt(t,e){var r=t.tileID.canonical;if(!this._geoJSONIndex)return e(null,null);var n=this._geoJSONIndex.getTile(r.z,r.x,r.y);if(!n)return e(null,null);var i=new m(n.features),a=_(i);0===a.byteOffset&&a.byteLength===a.buffer.byteLength||(a=new Uint8Array(a)),e(null,{vectorTile:i,rawData:a.buffer})}U.prototype.load=function(t){var e=this.options,r=e.log,n=e.minZoom,i=e.maxZoom,a=e.nodeSize;r&&console.time(\"total time\");var o=\"prepare \"+t.length+\" points\";r&&console.time(o),this.points=t;for(var s=[],l=0;l<t.length;l++)t[l].geometry&&s.push(q(t[l],l));this.trees[i+1]=new N(s,Z,J,a,Float32Array),r&&console.timeEnd(o);for(var c=i;c>=n;c--){var u=+Date.now();s=this._cluster(s,c),this.trees[c]=new N(s,Z,J,a,Float32Array),r&&console.log(\"z%d: %d clusters in %dms\",c,s.length,+Date.now()-u)}return r&&console.timeEnd(\"total time\"),this},U.prototype.getClusters=function(t,e){var r=((t[0]+180)%360+360)%360-180,n=Math.max(-90,Math.min(90,t[1])),i=180===t[2]?180:((t[2]+180)%360+360)%360-180,a=Math.max(-90,Math.min(90,t[3]));if(t[2]-t[0]>=360)r=-180,i=180;else if(r>i){var o=this.getClusters([r,n,180,a],e),s=this.getClusters([-180,n,i,a],e);return o.concat(s)}for(var l=this.trees[this._limitZoom(e)],c=[],u=0,f=l.range(Y(r),W(a),Y(i),W(n));u<f.length;u+=1){var h=f[u],p=l.points[h];c.push(p.numPoints?H(p):this.points[p.index])}return c},U.prototype.getChildren=function(t){var e=this._getOriginId(t),r=this._getOriginZoom(t),n=\"No cluster with the specified id.\",i=this.trees[r];if(!i)throw new Error(n);var a=i.points[e];if(!a)throw new Error(n);for(var o=this.options.radius/(this.options.extent*Math.pow(2,r-1)),s=[],l=0,c=i.within(a.x,a.y,o);l<c.length;l+=1){var u=c[l],f=i.points[u];f.parentId===t&&s.push(f.numPoints?H(f):this.points[f.index])}if(0===s.length)throw new Error(n);return s},U.prototype.getLeaves=function(t,e,r){e=e||10,r=r||0;var n=[];return this._appendLeaves(n,t,e,r,0),n},U.prototype.getTile=function(t,e,r){var n=this.trees[this._limitZoom(t)],i=Math.pow(2,t),a=this.options,o=a.extent,s=a.radius/o,l=(r-s)/i,c=(r+1+s)/i,u={features:[]};return this._addTileFeatures(n.range((e-s)/i,l,(e+1+s)/i,c),n.points,e,r,i,u),0===e&&this._addTileFeatures(n.range(1-s/i,l,1,c),n.points,i,r,i,u),e===i-1&&this._addTileFeatures(n.range(0,l,s/i,c),n.points,-1,r,i,u),u.features.length?u:null},U.prototype.getClusterExpansionZoom=function(t){for(var e=this._getOriginZoom(t)-1;e<=this.options.maxZoom;){var r=this.getChildren(t);if(e++,1!==r.length)break;t=r[0].properties.cluster_id}return e},U.prototype._appendLeaves=function(t,e,r,n,i){for(var a=0,o=this.getChildren(e);a<o.length;a+=1){var s=o[a],l=s.properties;if(l&&l.cluster?i+l.point_count<=n?i+=l.point_count:i=this._appendLeaves(t,l.cluster_id,r,n,i):i<n?i++:t.push(s),t.length===r)break}return i},U.prototype._addTileFeatures=function(t,e,r,n,i,a){for(var o=0,s=t;o<s.length;o+=1){var l=e[s[o]],c=l.numPoints,u={type:1,geometry:[[Math.round(this.options.extent*(l.x*i-r)),Math.round(this.options.extent*(l.y*i-n))]],tags:c?G(l):this.points[l.index].properties},f=void 0;c?f=l.id:this.options.generateId?f=l.index:this.points[l.index].id&&(f=this.points[l.index].id),void 0!==f&&(u.id=f),a.features.push(u)}},U.prototype._limitZoom=function(t){return Math.max(this.options.minZoom,Math.min(t,this.options.maxZoom+1))},U.prototype._cluster=function(t,e){for(var r=[],n=this.options,i=n.radius,a=n.extent,o=n.reduce,s=i/(a*Math.pow(2,e)),l=0;l<t.length;l++){var c=t[l];if(!(c.zoom<=e)){c.zoom=e;for(var u=this.trees[e+1],f=u.within(c.x,c.y,s),h=c.numPoints||1,p=c.x*h,d=c.y*h,g=o&&h>1?this._map(c,!0):null,m=(l<<5)+(e+1)+this.points.length,v=0,y=f;v<y.length;v+=1){var x=y[v],b=u.points[x];if(!(b.zoom<=e)){b.zoom=e;var _=b.numPoints||1;p+=b.x*_,d+=b.y*_,h+=_,b.parentId=m,o&&(g||(g=this._map(c,!0)),o(g,this._map(b)))}}1===h?r.push(c):(c.parentId=m,r.push(V(p/h,d/h,m,h,g)))}}return r},U.prototype._getOriginId=function(t){return t-this.points.length>>5},U.prototype._getOriginZoom=function(t){return(t-this.points.length)%32},U.prototype._map=function(t,e){if(t.numPoints)return e?X({},t.properties):t.properties;var r=this.points[t.index].properties,n=this.options.map(r);return e&&n===r?X({},n):n},_t.prototype.options={maxZoom:14,indexMaxZoom:5,indexMaxPoints:1e5,tolerance:3,extent:4096,buffer:64,lineMetrics:!1,promoteId:null,generateId:!1,debug:0},_t.prototype.splitTile=function(t,e,r,n,i,a,o){for(var s=[t,e,r,n],l=this.options,c=l.debug;s.length;){n=s.pop(),r=s.pop(),e=s.pop(),t=s.pop();var u=1<<e,f=wt(e,r,n),h=this.tiles[f];if(!h&&(c>1&&console.time(\"creation\"),h=this.tiles[f]=yt(t,e,r,n,l),this.tileCoords.push({z:e,x:r,y:n}),c)){c>1&&(console.log(\"tile z%d-%d-%d (features: %d, points: %d, simplified: %d)\",e,r,n,h.numFeatures,h.numPoints,h.numSimplified),console.timeEnd(\"creation\"));var p=\"z\"+e;this.stats[p]=(this.stats[p]||0)+1,this.total++}if(h.source=t,i){if(e===l.maxZoom||e===i)continue;var d=1<<i-e;if(r!==Math.floor(a/d)||n!==Math.floor(o/d))continue}else if(e===l.indexMaxZoom||h.numPoints<=l.indexMaxPoints)continue;if(h.source=null,0!==t.length){c>1&&console.time(\"clipping\");var g,m,v,y,x,b,_=.5*l.buffer/l.extent,w=.5-_,T=.5+_,k=1+_;g=m=v=y=null,x=ot(t,u,r-_,r+T,0,h.minX,h.maxX,l),b=ot(t,u,r+w,r+k,0,h.minX,h.maxX,l),t=null,x&&(g=ot(x,u,n-_,n+T,1,h.minY,h.maxY,l),m=ot(x,u,n+w,n+k,1,h.minY,h.maxY,l),x=null),b&&(v=ot(b,u,n-_,n+T,1,h.minY,h.maxY,l),y=ot(b,u,n+w,n+k,1,h.minY,h.maxY,l),b=null),c>1&&console.timeEnd(\"clipping\"),s.push(g||[],e+1,2*r,2*n),s.push(m||[],e+1,2*r,2*n+1),s.push(v||[],e+1,2*r+1,2*n),s.push(y||[],e+1,2*r+1,2*n+1)}}},_t.prototype.getTile=function(t,e,r){var n=this.options,i=n.extent,a=n.debug;if(t<0||t>24)return null;var o=1<<t,s=wt(t,e=(e%o+o)%o,r);if(this.tiles[s])return mt(this.tiles[s],i);a>1&&console.log(\"drilling down to z%d-%d-%d\",t,e,r);for(var l,c=t,u=e,f=r;!l&&c>0;)c--,u=Math.floor(u/2),f=Math.floor(f/2),l=this.tiles[wt(c,u,f)];return l&&l.source?(a>1&&console.log(\"found parent tile z%d-%d-%d\",c,u,f),a>1&&console.time(\"drilling down\"),this.splitTile(l.source,c,u,f,t,e,r),a>1&&console.timeEnd(\"drilling down\"),this.tiles[s]?mt(this.tiles[s],i):null):null};var kt=function(e){function r(t,r,n,i){e.call(this,t,r,n,Tt),i&&(this.loadGeoJSON=i)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.loadData=function(t,e){this._pendingCallback&&this._pendingCallback(null,{abandoned:!0}),this._pendingCallback=e,this._pendingLoadDataParams=t,this._state&&\"Idle\"!==this._state?this._state=\"NeedsLoadData\":(this._state=\"Coalescing\",this._loadData())},r.prototype._loadData=function(){var e=this;if(this._pendingCallback&&this._pendingLoadDataParams){var r=this._pendingCallback,n=this._pendingLoadDataParams;delete this._pendingCallback,delete this._pendingLoadDataParams;var i=!!(n&&n.request&&n.request.collectResourceTiming)&&new t.RequestPerformance(n.request);this.loadGeoJSON(n,(function(a,o){if(a||!o)return r(a);if(\"object\"!=typeof o)return r(new Error(\"Input data given to '\"+n.source+\"' is not a valid GeoJSON object.\"));f(o,!0);try{e._geoJSONIndex=n.cluster?new U(function(e){var r=e.superclusterOptions,n=e.clusterProperties;if(!n||!r)return r;for(var i={},a={},o={accumulated:null,zoom:0},s={properties:null},l=Object.keys(n),c=0,u=l;c<u.length;c+=1){var f=u[c],h=n[f],p=h[0],d=h[1],g=t.createExpression(d),m=t.createExpression(\"string\"==typeof p?[p,[\"accumulated\"],[\"get\",f]]:p);i[f]=g.value,a[f]=m.value}return r.map=function(t){s.properties=t;for(var e={},r=0,n=l;r<n.length;r+=1){var a=n[r];e[a]=i[a].evaluate(o,s)}return e},r.reduce=function(t,e){s.properties=e;for(var r=0,n=l;r<n.length;r+=1){var i=n[r];o.accumulated=t[i],t[i]=a[i].evaluate(o,s)}},r}(n)).load(o.features):function(t,e){return new _t(t,e)}(o,n.geojsonVtOptions)}catch(a){return r(a)}e.loaded={};var s={};if(i){var l=i.finish();l&&(s.resourceTiming={},s.resourceTiming[n.source]=JSON.parse(JSON.stringify(l)))}r(null,s)}))}},r.prototype.coalesce=function(){\"Coalescing\"===this._state?this._state=\"Idle\":\"NeedsLoadData\"===this._state&&(this._state=\"Coalescing\",this._loadData())},r.prototype.reloadTile=function(t,r){var n=this.loaded,i=t.uid;return n&&n[i]?e.prototype.reloadTile.call(this,t,r):this.loadTile(t,r)},r.prototype.loadGeoJSON=function(e,r){if(e.request)t.getJSON(e.request,r);else{if(\"string\"!=typeof e.data)return r(new Error(\"Input data given to '\"+e.source+\"' is not a valid GeoJSON object.\"));try{return r(null,JSON.parse(e.data))}catch(t){return r(new Error(\"Input data given to '\"+e.source+\"' is not a valid GeoJSON 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t.Point(r.clientX-n.left-e.clientLeft,r.clientY-n.top-e.clientTop)},r.touchPos=function(e,r){for(var n=e.getBoundingClientRect(),i=[],a=0;a<r.length;a++)i.push(new t.Point(r[a].clientX-n.left-e.clientLeft,r[a].clientY-n.top-e.clientTop));return i},r.mouseButton=function(e){return void 0!==t.window.InstallTrigger&&2===e.button&&e.ctrlKey&&t.window.navigator.platform.toUpperCase().indexOf(\"MAC\")>=0?0:e.button},r.remove=function(t){t.parentNode&&t.parentNode.removeChild(t)};var h=function(e){function r(){e.call(this),this.images={},this.updatedImages={},this.callbackDispatchedThisFrame={},this.loaded=!1,this.requestors=[],this.patterns={},this.atlasImage=new t.RGBAImage({width:1,height:1}),this.dirty=!0}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.isLoaded=function(){return this.loaded},r.prototype.setLoaded=function(t){if(this.loaded!==t&&(this.loaded=t,t)){for(var e=0,r=this.requestors;e<r.length;e+=1){var n=r[e],i=n.ids,a=n.callback;this._notify(i,a)}this.requestors=[]}},r.prototype.getImage=function(t){return this.images[t]},r.prototype.addImage=function(t,e){this._validate(t,e)&&(this.images[t]=e)},r.prototype._validate=function(e,r){var n=!0;return this._validateStretch(r.stretchX,r.data&&r.data.width)||(this.fire(new t.ErrorEvent(new Error('Image \"'+e+'\" has invalid \"stretchX\" value'))),n=!1),this._validateStretch(r.stretchY,r.data&&r.data.height)||(this.fire(new t.ErrorEvent(new Error('Image \"'+e+'\" has invalid \"stretchY\" value'))),n=!1),this._validateContent(r.content,r)||(this.fire(new t.ErrorEvent(new Error('Image \"'+e+'\" has invalid \"content\" value'))),n=!1),n},r.prototype._validateStretch=function(t,e){if(!t)return!0;for(var r=0,n=0,i=t;n<i.length;n+=1){var a=i[n];if(a[0]<r||a[1]<a[0]||e<a[1])return!1;r=a[1]}return!0},r.prototype._validateContent=function(t,e){return!t||4===t.length&&(!(t[0]<0||e.data.width<t[0])&&(!(t[1]<0||e.data.height<t[1])&&(!(t[2]<0||e.data.width<t[2])&&(!(t[3]<0||e.data.height<t[3])&&(!(t[2]<t[0])&&!(t[3]<t[1]))))))},r.prototype.updateImage=function(t,e){var r=this.images[t];e.version=r.version+1,this.images[t]=e,this.updatedImages[t]=!0},r.prototype.removeImage=function(t){var e=this.images[t];delete this.images[t],delete this.patterns[t],e.userImage&&e.userImage.onRemove&&e.userImage.onRemove()},r.prototype.listImages=function(){return Object.keys(this.images)},r.prototype.getImages=function(t,e){var r=!0;if(!this.isLoaded())for(var n=0,i=t;n<i.length;n+=1){var a=i[n];this.images[a]||(r=!1)}this.isLoaded()||r?this._notify(t,e):this.requestors.push({ids:t,callback:e})},r.prototype._notify=function(e,r){for(var n={},i=0,a=e;i<a.length;i+=1){var o=a[i];this.images[o]||this.fire(new t.Event(\"styleimagemissing\",{id:o}));var s=this.images[o];s?n[o]={data:s.data.clone(),pixelRatio:s.pixelRatio,sdf:s.sdf,version:s.version,stretchX:s.stretchX,stretchY:s.stretchY,content:s.content,hasRenderCallback:Boolean(s.userImage&&s.userImage.render)}:t.warnOnce('Image \"'+o+'\" could not be loaded. Please make sure you have added the image with map.addImage() or a \"sprite\" property in your style. You can provide missing images by listening for the \"styleimagemissing\" map event.')}r(null,n)},r.prototype.getPixelSize=function(){var t=this.atlasImage;return{width:t.width,height:t.height}},r.prototype.getPattern=function(e){var r=this.patterns[e],n=this.getImage(e);if(!n)return null;if(r&&r.position.version===n.version)return r.position;if(r)r.position.version=n.version;else{var i={w:n.data.width+2,h:n.data.height+2,x:0,y:0},a=new t.ImagePosition(i,n);this.patterns[e]={bin:i,position:a}}return this._updatePatternAtlas(),this.patterns[e].position},r.prototype.bind=function(e){var r=e.gl;this.atlasTexture?this.dirty&&(this.atlasTexture.update(this.atlasImage),this.dirty=!1):this.atlasTexture=new t.Texture(e,this.atlasImage,r.RGBA),this.atlasTexture.bind(r.LINEAR,r.CLAMP_TO_EDGE)},r.prototype._updatePatternAtlas=function(){var e=[];for(var r in this.patterns)e.push(this.patterns[r].bin);var n=t.potpack(e),i=n.w,a=n.h,o=this.atlasImage;for(var s in o.resize({width:i||1,height:a||1}),this.patterns){var l=this.patterns[s].bin,c=l.x+1,u=l.y+1,f=this.images[s].data,h=f.width,p=f.height;t.RGBAImage.copy(f,o,{x:0,y:0},{x:c,y:u},{width:h,height:p}),t.RGBAImage.copy(f,o,{x:0,y:p-1},{x:c,y:u-1},{width:h,height:1}),t.RGBAImage.copy(f,o,{x:0,y:0},{x:c,y:u+p},{width:h,height:1}),t.RGBAImage.copy(f,o,{x:h-1,y:0},{x:c-1,y:u},{width:1,height:p}),t.RGBAImage.copy(f,o,{x:0,y:0},{x:c+h,y:u},{width:1,height:p})}this.dirty=!0},r.prototype.beginFrame=function(){this.callbackDispatchedThisFrame={}},r.prototype.dispatchRenderCallbacks=function(t){for(var e=0,r=t;e<r.length;e+=1){var n=r[e];if(!this.callbackDispatchedThisFrame[n]){this.callbackDispatchedThisFrame[n]=!0;var i=this.images[n];f(i)&&this.updateImage(n,i)}}},r}(t.Evented);var p=m,d=m,g=1e20;function m(t,e,r,n,i,a){this.fontSize=t||24,this.buffer=void 0===e?3:e,this.cutoff=n||.25,this.fontFamily=i||\"sans-serif\",this.fontWeight=a||\"normal\",this.radius=r||8;var o=this.size=this.fontSize+2*this.buffer;this.canvas=document.createElement(\"canvas\"),this.canvas.width=this.canvas.height=o,this.ctx=this.canvas.getContext(\"2d\"),this.ctx.font=this.fontWeight+\" \"+this.fontSize+\"px \"+this.fontFamily,this.ctx.textBaseline=\"middle\",this.ctx.fillStyle=\"black\",this.gridOuter=new Float64Array(o*o),this.gridInner=new Float64Array(o*o),this.f=new Float64Array(o),this.d=new Float64Array(o),this.z=new Float64Array(o+1),this.v=new Int16Array(o),this.middle=Math.round(o/2*(navigator.userAgent.indexOf(\"Gecko/\")>=0?1.2:1))}function v(t,e,r,n,i,a,o){for(var s=0;s<e;s++){for(var l=0;l<r;l++)n[l]=t[l*e+s];for(y(n,i,a,o,r),l=0;l<r;l++)t[l*e+s]=i[l]}for(l=0;l<r;l++){for(s=0;s<e;s++)n[s]=t[l*e+s];for(y(n,i,a,o,e),s=0;s<e;s++)t[l*e+s]=Math.sqrt(i[s])}}function y(t,e,r,n,i){r[0]=0,n[0]=-g,n[1]=+g;for(var a=1,o=0;a<i;a++){for(var s=(t[a]+a*a-(t[r[o]]+r[o]*r[o]))/(2*a-2*r[o]);s<=n[o];)o--,s=(t[a]+a*a-(t[r[o]]+r[o]*r[o]))/(2*a-2*r[o]);r[++o]=a,n[o]=s,n[o+1]=+g}for(a=0,o=0;a<i;a++){for(;n[o+1]<a;)o++;e[a]=(a-r[o])*(a-r[o])+t[r[o]]}}m.prototype.draw=function(t){this.ctx.clearRect(0,0,this.size,this.size),this.ctx.fillText(t,this.buffer,this.middle);for(var e=this.ctx.getImageData(0,0,this.size,this.size),r=new Uint8ClampedArray(this.size*this.size),n=0;n<this.size*this.size;n++){var i=e.data[4*n+3]/255;this.gridOuter[n]=1===i?0:0===i?g:Math.pow(Math.max(0,.5-i),2),this.gridInner[n]=1===i?g:0===i?0:Math.pow(Math.max(0,i-.5),2)}for(v(this.gridOuter,this.size,this.size,this.f,this.d,this.v,this.z),v(this.gridInner,this.size,this.size,this.f,this.d,this.v,this.z),n=0;n<this.size*this.size;n++){var a=this.gridOuter[n]-this.gridInner[n];r[n]=Math.max(0,Math.min(255,Math.round(255-255*(a/this.radius+this.cutoff))))}return r},p.default=d;var x=function(t,e){this.requestManager=t,this.localIdeographFontFamily=e,this.entries={}};x.prototype.setURL=function(t){this.url=t},x.prototype.getGlyphs=function(e,r){var n=this,i=[];for(var a in e)for(var o=0,s=e[a];o<s.length;o+=1){var l=s[o];i.push({stack:a,id:l})}t.asyncAll(i,(function(t,e){var r=t.stack,i=t.id,a=n.entries[r];a||(a=n.entries[r]={glyphs:{},requests:{},ranges:{}});var o=a.glyphs[i];if(void 0===o){if(o=n._tinySDF(a,r,i))return a.glyphs[i]=o,void e(null,{stack:r,id:i,glyph:o});var s=Math.floor(i/256);if(256*s>65535)e(new Error(\"glyphs > 65535 not supported\"));else if(a.ranges[s])e(null,{stack:r,id:i,glyph:o});else{var l=a.requests[s];l||(l=a.requests[s]=[],x.loadGlyphRange(r,s,n.url,n.requestManager,(function(t,e){if(e){for(var r in e)n._doesCharSupportLocalGlyph(+r)||(a.glyphs[+r]=e[+r]);a.ranges[s]=!0}for(var i=0,o=l;i<o.length;i+=1){(0,o[i])(t,e)}delete a.requests[s]}))),l.push((function(t,n){t?e(t):n&&e(null,{stack:r,id:i,glyph:n[i]||null})}))}}else e(null,{stack:r,id:i,glyph:o})}),(function(t,e){if(t)r(t);else if(e){for(var n={},i=0,a=e;i<a.length;i+=1){var o=a[i],s=o.stack,l=o.id,c=o.glyph;(n[s]||(n[s]={}))[l]=c&&{id:c.id,bitmap:c.bitmap.clone(),metrics:c.metrics}}r(null,n)}}))},x.prototype._doesCharSupportLocalGlyph=function(e){return!!this.localIdeographFontFamily&&(t.isChar[\"CJK Unified Ideographs\"](e)||t.isChar[\"Hangul Syllables\"](e)||t.isChar.Hiragana(e)||t.isChar.Katakana(e))},x.prototype._tinySDF=function(e,r,n){var i=this.localIdeographFontFamily;if(i&&this._doesCharSupportLocalGlyph(n)){var a=e.tinySDF;if(!a){var o=\"400\";/bold/i.test(r)?o=\"900\":/medium/i.test(r)?o=\"500\":/light/i.test(r)&&(o=\"200\"),a=e.tinySDF=new x.TinySDF(24,3,8,.25,i,o)}return{id:n,bitmap:new t.AlphaImage({width:30,height:30},a.draw(String.fromCharCode(n))),metrics:{width:24,height:24,left:0,top:-8,advance:24}}}},x.loadGlyphRange=function(e,r,n,i,a){var o=256*r,s=o+255,l=i.transformRequest(i.normalizeGlyphsURL(n).replace(\"{fontstack}\",e).replace(\"{range}\",o+\"-\"+s),t.ResourceType.Glyphs);t.getArrayBuffer(l,(function(e,r){if(e)a(e);else if(r){for(var n={},i=0,o=t.parseGlyphPBF(r);i<o.length;i+=1){var s=o[i];n[s.id]=s}a(null,n)}}))},x.TinySDF=p;var b=function(){this.specification=t.styleSpec.light.position};b.prototype.possiblyEvaluate=function(e,r){return t.sphericalToCartesian(e.expression.evaluate(r))},b.prototype.interpolate=function(e,r,n){return{x:t.number(e.x,r.x,n),y:t.number(e.y,r.y,n),z:t.number(e.z,r.z,n)}};var _=new t.Properties({anchor:new t.DataConstantProperty(t.styleSpec.light.anchor),position:new b,color:new t.DataConstantProperty(t.styleSpec.light.color),intensity:new t.DataConstantProperty(t.styleSpec.light.intensity)}),w=function(e){function r(r){e.call(this),this._transitionable=new t.Transitionable(_),this.setLight(r),this._transitioning=this._transitionable.untransitioned()}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.getLight=function(){return this._transitionable.serialize()},r.prototype.setLight=function(e,r){if(void 0===r&&(r={}),!this._validate(t.validateLight,e,r))for(var n in e){var i=e[n];t.endsWith(n,\"-transition\")?this._transitionable.setTransition(n.slice(0,-\"-transition\".length),i):this._transitionable.setValue(n,i)}},r.prototype.updateTransitions=function(t){this._transitioning=this._transitionable.transitioned(t,this._transitioning)},r.prototype.hasTransition=function(){return this._transitioning.hasTransition()},r.prototype.recalculate=function(t){this.properties=this._transitioning.possiblyEvaluate(t)},r.prototype._validate=function(e,r,n){return(!n||!1!==n.validate)&&t.emitValidationErrors(this,e.call(t.validateStyle,t.extend({value:r,style:{glyphs:!0,sprite:!0},styleSpec:t.styleSpec})))},r}(t.Evented),T=function(t,e){this.width=t,this.height=e,this.nextRow=0,this.data=new Uint8Array(this.width*this.height),this.dashEntry={}};T.prototype.getDash=function(t,e){var r=t.join(\",\")+String(e);return this.dashEntry[r]||(this.dashEntry[r]=this.addDash(t,e)),this.dashEntry[r]},T.prototype.getDashRanges=function(t,e,r){var n=[],i=t.length%2==1?-t[t.length-1]*r:0,a=t[0]*r,o=!0;n.push({left:i,right:a,isDash:o,zeroLength:0===t[0]});for(var s=t[0],l=1;l<t.length;l++){o=!o;var c=t[l];i=s*r,a=(s+=c)*r,n.push({left:i,right:a,isDash:o,zeroLength:0===c})}return n},T.prototype.addRoundDash=function(t,e,r){for(var n=e/2,i=-r;i<=r;i++)for(var a=this.nextRow+r+i,o=this.width*a,s=0,l=t[s],c=0;c<this.width;c++){c/l.right>1&&(l=t[++s]);var u=Math.abs(c-l.left),f=Math.abs(c-l.right),h=Math.min(u,f),p=void 0,d=i/r*(n+1);if(l.isDash){var g=n-Math.abs(d);p=Math.sqrt(h*h+g*g)}else p=n-Math.sqrt(h*h+d*d);this.data[o+c]=Math.max(0,Math.min(255,p+128))}},T.prototype.addRegularDash=function(t){for(var e=t.length-1;e>=0;--e){var r=t[e],n=t[e+1];r.zeroLength?t.splice(e,1):n&&n.isDash===r.isDash&&(n.left=r.left,t.splice(e,1))}var i=t[0],a=t[t.length-1];i.isDash===a.isDash&&(i.left=a.left-this.width,a.right=i.right+this.width);for(var o=this.width*this.nextRow,s=0,l=t[s],c=0;c<this.width;c++){c/l.right>1&&(l=t[++s]);var u=Math.abs(c-l.left),f=Math.abs(c-l.right),h=Math.min(u,f),p=l.isDash?h:-h;this.data[o+c]=Math.max(0,Math.min(255,p+128))}},T.prototype.addDash=function(e,r){var n=r?7:0,i=2*n+1;if(this.nextRow+i>this.height)return t.warnOnce(\"LineAtlas out of space\"),null;for(var a=0,o=0;o<e.length;o++)a+=e[o];if(0!==a){var s=this.width/a,l=this.getDashRanges(e,this.width,s);r?this.addRoundDash(l,s,n):this.addRegularDash(l)}var c={y:(this.nextRow+n+.5)/this.height,height:2*n/this.height,width:a};return this.nextRow+=i,this.dirty=!0,c},T.prototype.bind=function(t){var e=t.gl;this.texture?(e.bindTexture(e.TEXTURE_2D,this.texture),this.dirty&&(this.dirty=!1,e.texSubImage2D(e.TEXTURE_2D,0,0,0,this.width,this.height,e.ALPHA,e.UNSIGNED_BYTE,this.data))):(this.texture=e.createTexture(),e.bindTexture(e.TEXTURE_2D,this.texture),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_WRAP_S,e.REPEAT),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_WRAP_T,e.REPEAT),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MIN_FILTER,e.LINEAR),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MAG_FILTER,e.LINEAR),e.texImage2D(e.TEXTURE_2D,0,e.ALPHA,this.width,this.height,0,e.ALPHA,e.UNSIGNED_BYTE,this.data))};var k=function e(r,n){this.workerPool=r,this.actors=[],this.currentActor=0,this.id=t.uniqueId();for(var i=this.workerPool.acquire(this.id),a=0;a<i.length;a++){var o=i[a],s=new e.Actor(o,n,this.id);s.name=\"Worker \"+a,this.actors.push(s)}};function A(e,r,n){var i=function(i,a){if(i)return n(i);if(a){var o=t.pick(t.extend(a,e),[\"tiles\",\"minzoom\",\"maxzoom\",\"attribution\",\"mapbox_logo\",\"bounds\",\"scheme\",\"tileSize\",\"encoding\"]);a.vector_layers&&(o.vectorLayers=a.vector_layers,o.vectorLayerIds=o.vectorLayers.map((function(t){return t.id}))),o.tiles=r.canonicalizeTileset(o,e.url),n(null,o)}};return e.url?t.getJSON(r.transformRequest(r.normalizeSourceURL(e.url),t.ResourceType.Source),i):t.browser.frame((function(){return i(null,e)}))}k.prototype.broadcast=function(e,r,n){n=n||function(){},t.asyncAll(this.actors,(function(t,n){t.send(e,r,n)}),n)},k.prototype.getActor=function(){return this.currentActor=(this.currentActor+1)%this.actors.length,this.actors[this.currentActor]},k.prototype.remove=function(){this.actors.forEach((function(t){t.remove()})),this.actors=[],this.workerPool.release(this.id)},k.Actor=t.Actor;var M=function(e,r,n){this.bounds=t.LngLatBounds.convert(this.validateBounds(e)),this.minzoom=r||0,this.maxzoom=n||24};M.prototype.validateBounds=function(t){return Array.isArray(t)&&4===t.length?[Math.max(-180,t[0]),Math.max(-90,t[1]),Math.min(180,t[2]),Math.min(90,t[3])]:[-180,-90,180,90]},M.prototype.contains=function(e){var r=Math.pow(2,e.z),n=Math.floor(t.mercatorXfromLng(this.bounds.getWest())*r),i=Math.floor(t.mercatorYfromLat(this.bounds.getNorth())*r),a=Math.ceil(t.mercatorXfromLng(this.bounds.getEast())*r),o=Math.ceil(t.mercatorYfromLat(this.bounds.getSouth())*r);return e.x>=n&&e.x<a&&e.y>=i&&e.y<o};var S=function(e){function r(r,n,i,a){if(e.call(this),this.id=r,this.dispatcher=i,this.type=\"vector\",this.minzoom=0,this.maxzoom=22,this.scheme=\"xyz\",this.tileSize=512,this.reparseOverscaled=!0,this.isTileClipped=!0,this._loaded=!1,t.extend(this,t.pick(n,[\"url\",\"scheme\",\"tileSize\",\"promoteId\"])),this._options=t.extend({type:\"vector\"},n),this._collectResourceTiming=n.collectResourceTiming,512!==this.tileSize)throw new Error(\"vector tile sources must have a tileSize of 512\");this.setEventedParent(a)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._tileJSONRequest=A(this._options,this.map._requestManager,(function(r,n){e._tileJSONRequest=null,e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(t.extend(e,n),n.bounds&&(e.tileBounds=new M(n.bounds,e.minzoom,e.maxzoom)),t.postTurnstileEvent(n.tiles,e.map._requestManager._customAccessToken),t.postMapLoadEvent(n.tiles,e.map._getMapId(),e.map._requestManager._skuToken,e.map._requestManager._customAccessToken),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.hasTile=function(t){return!this.tileBounds||this.tileBounds.contains(t.canonical)},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.onRemove=function(){this._tileJSONRequest&&(this._tileJSONRequest.cancel(),this._tileJSONRequest=null)},r.prototype.serialize=function(){return t.extend({},this._options)},r.prototype.loadTile=function(e,r){var n=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme)),i={request:this.map._requestManager.transformRequest(n,t.ResourceType.Tile),uid:e.uid,tileID:e.tileID,zoom:e.tileID.overscaledZ,tileSize:this.tileSize*e.tileID.overscaleFactor(),type:this.type,source:this.id,pixelRatio:t.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};function a(n,i){return delete e.request,e.aborted?r(null):n&&404!==n.status?r(n):(i&&i.resourceTiming&&(e.resourceTiming=i.resourceTiming),this.map._refreshExpiredTiles&&i&&e.setExpiryData(i),e.loadVectorData(i,this.map.painter),t.cacheEntryPossiblyAdded(this.dispatcher),r(null),void(e.reloadCallback&&(this.loadTile(e,e.reloadCallback),e.reloadCallback=null)))}i.request.collectResourceTiming=this._collectResourceTiming,e.actor&&\"expired\"!==e.state?\"loading\"===e.state?e.reloadCallback=r:e.request=e.actor.send(\"reloadTile\",i,a.bind(this)):(e.actor=this.dispatcher.getActor(),e.request=e.actor.send(\"loadTile\",i,a.bind(this)))},r.prototype.abortTile=function(t){t.request&&(t.request.cancel(),delete t.request),t.actor&&t.actor.send(\"abortTile\",{uid:t.uid,type:this.type,source:this.id},void 0)},r.prototype.unloadTile=function(t){t.unloadVectorData(),t.actor&&t.actor.send(\"removeTile\",{uid:t.uid,type:this.type,source:this.id},void 0)},r.prototype.hasTransition=function(){return!1},r}(t.Evented),E=function(e){function r(r,n,i,a){e.call(this),this.id=r,this.dispatcher=i,this.setEventedParent(a),this.type=\"raster\",this.minzoom=0,this.maxzoom=22,this.roundZoom=!0,this.scheme=\"xyz\",this.tileSize=512,this._loaded=!1,this._options=t.extend({type:\"raster\"},n),t.extend(this,t.pick(n,[\"url\",\"scheme\",\"tileSize\"]))}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._tileJSONRequest=A(this._options,this.map._requestManager,(function(r,n){e._tileJSONRequest=null,e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(t.extend(e,n),n.bounds&&(e.tileBounds=new M(n.bounds,e.minzoom,e.maxzoom)),t.postTurnstileEvent(n.tiles),t.postMapLoadEvent(n.tiles,e.map._getMapId(),e.map._requestManager._skuToken),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})),e.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.onRemove=function(){this._tileJSONRequest&&(this._tileJSONRequest.cancel(),this._tileJSONRequest=null)},r.prototype.serialize=function(){return t.extend({},this._options)},r.prototype.hasTile=function(t){return!this.tileBounds||this.tileBounds.contains(t.canonical)},r.prototype.loadTile=function(e,r){var n=this,i=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme),this.tileSize);e.request=t.getImage(this.map._requestManager.transformRequest(i,t.ResourceType.Tile),(function(i,a){if(delete e.request,e.aborted)e.state=\"unloaded\",r(null);else if(i)e.state=\"errored\",r(i);else if(a){n.map._refreshExpiredTiles&&e.setExpiryData(a),delete a.cacheControl,delete a.expires;var o=n.map.painter.context,s=o.gl;e.texture=n.map.painter.getTileTexture(a.width),e.texture?e.texture.update(a,{useMipmap:!0}):(e.texture=new t.Texture(o,a,s.RGBA,{useMipmap:!0}),e.texture.bind(s.LINEAR,s.CLAMP_TO_EDGE,s.LINEAR_MIPMAP_NEAREST),o.extTextureFilterAnisotropic&&s.texParameterf(s.TEXTURE_2D,o.extTextureFilterAnisotropic.TEXTURE_MAX_ANISOTROPY_EXT,o.extTextureFilterAnisotropicMax)),e.state=\"loaded\",t.cacheEntryPossiblyAdded(n.dispatcher),r(null)}}))},r.prototype.abortTile=function(t,e){t.request&&(t.request.cancel(),delete t.request),e()},r.prototype.unloadTile=function(t,e){t.texture&&this.map.painter.saveTileTexture(t.texture),e()},r.prototype.hasTransition=function(){return!1},r}(t.Evented),L=function(e){function r(r,n,i,a){e.call(this,r,n,i,a),this.type=\"raster-dem\",this.maxzoom=22,this._options=t.extend({type:\"raster-dem\"},n),this.encoding=n.encoding||\"mapbox\"}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.serialize=function(){return{type:\"raster-dem\",url:this.url,tileSize:this.tileSize,tiles:this.tiles,bounds:this.bounds,encoding:this.encoding}},r.prototype.loadTile=function(e,r){var n=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme),this.tileSize);function i(t,n){t&&(e.state=\"errored\",r(t)),n&&(e.dem=n,e.needsHillshadePrepare=!0,e.state=\"loaded\",r(null))}e.request=t.getImage(this.map._requestManager.transformRequest(n,t.ResourceType.Tile),function(n,a){if(delete e.request,e.aborted)e.state=\"unloaded\",r(null);else if(n)e.state=\"errored\",r(n);else if(a){this.map._refreshExpiredTiles&&e.setExpiryData(a),delete a.cacheControl,delete a.expires;var o=t.window.ImageBitmap&&a instanceof t.window.ImageBitmap&&t.offscreenCanvasSupported()?a:t.browser.getImageData(a,1),s={uid:e.uid,coord:e.tileID,source:this.id,rawImageData:o,encoding:this.encoding};e.actor&&\"expired\"!==e.state||(e.actor=this.dispatcher.getActor(),e.actor.send(\"loadDEMTile\",s,i.bind(this)))}}.bind(this)),e.neighboringTiles=this._getNeighboringTiles(e.tileID)},r.prototype._getNeighboringTiles=function(e){var r=e.canonical,n=Math.pow(2,r.z),i=(r.x-1+n)%n,a=0===r.x?e.wrap-1:e.wrap,o=(r.x+1+n)%n,s=r.x+1===n?e.wrap+1:e.wrap,l={};return l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y).key]={backfilled:!1},r.y>0&&(l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,e.wrap,r.z,r.x,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y-1).key]={backfilled:!1}),r.y+1<n&&(l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y+1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,e.wrap,r.z,r.x,r.y+1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y+1).key]={backfilled:!1}),l},r.prototype.unloadTile=function(t){t.demTexture&&this.map.painter.saveTileTexture(t.demTexture),t.fbo&&(t.fbo.destroy(),delete t.fbo),t.dem&&delete t.dem,delete t.neighboringTiles,t.state=\"unloaded\",t.actor&&t.actor.send(\"removeDEMTile\",{uid:t.uid,source:this.id})},r}(E),C=function(e){function r(r,n,i,a){e.call(this),this.id=r,this.type=\"geojson\",this.minzoom=0,this.maxzoom=18,this.tileSize=512,this.isTileClipped=!0,this.reparseOverscaled=!0,this._removed=!1,this._loaded=!1,this.actor=i.getActor(),this.setEventedParent(a),this._data=n.data,this._options=t.extend({},n),this._collectResourceTiming=n.collectResourceTiming,this._resourceTiming=[],void 0!==n.maxzoom&&(this.maxzoom=n.maxzoom),n.type&&(this.type=n.type),n.attribution&&(this.attribution=n.attribution),this.promoteId=n.promoteId;var o=t.EXTENT/this.tileSize;this.workerOptions=t.extend({source:this.id,cluster:n.cluster||!1,geojsonVtOptions:{buffer:(void 0!==n.buffer?n.buffer:128)*o,tolerance:(void 0!==n.tolerance?n.tolerance:.375)*o,extent:t.EXTENT,maxZoom:this.maxzoom,lineMetrics:n.lineMetrics||!1,generateId:n.generateId||!1},superclusterOptions:{maxZoom:void 0!==n.clusterMaxZoom?Math.min(n.clusterMaxZoom,this.maxzoom-1):this.maxzoom-1,extent:t.EXTENT,radius:(n.clusterRadius||50)*o,log:!1,generateId:n.generateId||!1},clusterProperties:n.clusterProperties},n.workerOptions)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._updateWorkerData((function(r){if(r)e.fire(new t.ErrorEvent(r));else{var n={dataType:\"source\",sourceDataType:\"metadata\"};e._collectResourceTiming&&e._resourceTiming&&e._resourceTiming.length>0&&(n.resourceTiming=e._resourceTiming,e._resourceTiming=[]),e.fire(new t.Event(\"data\",n))}}))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setData=function(e){var r=this;return this._data=e,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this._updateWorkerData((function(e){if(e)r.fire(new t.ErrorEvent(e));else{var n={dataType:\"source\",sourceDataType:\"content\"};r._collectResourceTiming&&r._resourceTiming&&r._resourceTiming.length>0&&(n.resourceTiming=r._resourceTiming,r._resourceTiming=[]),r.fire(new t.Event(\"data\",n))}})),this},r.prototype.getClusterExpansionZoom=function(t,e){return this.actor.send(\"geojson.getClusterExpansionZoom\",{clusterId:t,source:this.id},e),this},r.prototype.getClusterChildren=function(t,e){return this.actor.send(\"geojson.getClusterChildren\",{clusterId:t,source:this.id},e),this},r.prototype.getClusterLeaves=function(t,e,r,n){return this.actor.send(\"geojson.getClusterLeaves\",{source:this.id,clusterId:t,limit:e,offset:r},n),this},r.prototype._updateWorkerData=function(e){var r=this;this._loaded=!1;var n=t.extend({},this.workerOptions),i=this._data;\"string\"==typeof i?(n.request=this.map._requestManager.transformRequest(t.browser.resolveURL(i),t.ResourceType.Source),n.request.collectResourceTiming=this._collectResourceTiming):n.data=JSON.stringify(i),this.actor.send(this.type+\".loadData\",n,(function(t,i){r._removed||i&&i.abandoned||(r._loaded=!0,i&&i.resourceTiming&&i.resourceTiming[r.id]&&(r._resourceTiming=i.resourceTiming[r.id].slice(0)),r.actor.send(r.type+\".coalesce\",{source:n.source},null),e(t))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.loadTile=function(e,r){var n=this,i=e.actor?\"reloadTile\":\"loadTile\";e.actor=this.actor;var a={type:this.type,uid:e.uid,tileID:e.tileID,zoom:e.tileID.overscaledZ,maxZoom:this.maxzoom,tileSize:this.tileSize,source:this.id,pixelRatio:t.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};e.request=this.actor.send(i,a,(function(t,a){return delete e.request,e.unloadVectorData(),e.aborted?r(null):t?r(t):(e.loadVectorData(a,n.map.painter,\"reloadTile\"===i),r(null))}))},r.prototype.abortTile=function(t){t.request&&(t.request.cancel(),delete t.request),t.aborted=!0},r.prototype.unloadTile=function(t){t.unloadVectorData(),this.actor.send(\"removeTile\",{uid:t.uid,type:this.type,source:this.id})},r.prototype.onRemove=function(){this._removed=!0,this.actor.send(\"removeSource\",{type:this.type,source:this.id})},r.prototype.serialize=function(){return t.extend({},this._options,{type:this.type,data:this._data})},r.prototype.hasTransition=function(){return!1},r}(t.Evented),P=t.createLayout([{name:\"a_pos\",type:\"Int16\",components:2},{name:\"a_texture_pos\",type:\"Int16\",components:2}]),I=function(e){function r(t,r,n,i){e.call(this),this.id=t,this.dispatcher=n,this.coordinates=r.coordinates,this.type=\"image\",this.minzoom=0,this.maxzoom=22,this.tileSize=512,this.tiles={},this._loaded=!1,this.setEventedParent(i),this.options=r}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(e,r){var n=this;this._loaded=!1,this.fire(new t.Event(\"dataloading\",{dataType:\"source\"})),this.url=this.options.url,t.getImage(this.map._requestManager.transformRequest(this.url,t.ResourceType.Image),(function(i,a){n._loaded=!0,i?n.fire(new t.ErrorEvent(i)):a&&(n.image=a,e&&(n.coordinates=e),r&&r(),n._finishLoading())}))},r.prototype.loaded=function(){return this._loaded},r.prototype.updateImage=function(t){var e=this;return this.image&&t.url?(this.options.url=t.url,this.load(t.coordinates,(function(){e.texture=null})),this):this},r.prototype._finishLoading=function(){this.map&&(this.setCoordinates(this.coordinates),this.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"metadata\"})))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setCoordinates=function(e){var r=this;this.coordinates=e;var n=e.map(t.MercatorCoordinate.fromLngLat);this.tileID=function(e){for(var r=1/0,n=1/0,i=-1/0,a=-1/0,o=0,s=e;o<s.length;o+=1){var l=s[o];r=Math.min(r,l.x),n=Math.min(n,l.y),i=Math.max(i,l.x),a=Math.max(a,l.y)}var c=i-r,u=a-n,f=Math.max(c,u),h=Math.max(0,Math.floor(-Math.log(f)/Math.LN2)),p=Math.pow(2,h);return new t.CanonicalTileID(h,Math.floor((r+i)/2*p),Math.floor((n+a)/2*p))}(n),this.minzoom=this.maxzoom=this.tileID.z;var i=n.map((function(t){return r.tileID.getTilePoint(t)._round()}));return this._boundsArray=new t.StructArrayLayout4i8,this._boundsArray.emplaceBack(i[0].x,i[0].y,0,0),this._boundsArray.emplaceBack(i[1].x,i[1].y,t.EXTENT,0),this._boundsArray.emplaceBack(i[3].x,i[3].y,0,t.EXTENT),this._boundsArray.emplaceBack(i[2].x,i[2].y,t.EXTENT,t.EXTENT),this.boundsBuffer&&(this.boundsBuffer.destroy(),delete this.boundsBuffer),this.fire(new t.Event(\"data\",{dataType:\"source\",sourceDataType:\"content\"})),this},r.prototype.prepare=function(){if(0!==Object.keys(this.tiles).length&&this.image){var e=this.map.painter.context,r=e.gl;for(var n in this.boundsBuffer||(this.boundsBuffer=e.createVertexBuffer(this._boundsArray,P.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture||(this.texture=new t.Texture(e,this.image,r.RGBA),this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE)),this.tiles){var i=this.tiles[n];\"loaded\"!==i.state&&(i.state=\"loaded\",i.texture=this.texture)}}},r.prototype.loadTile=function(t,e){this.tileID&&this.tileID.equals(t.tileID.canonical)?(this.tiles[String(t.tileID.wrap)]=t,t.buckets={},e(null)):(t.state=\"errored\",e(null))},r.prototype.serialize=function(){return{type:\"image\",url:this.options.url,coordinates:this.coordinates}},r.prototype.hasTransition=function(){return!1},r}(t.Evented);var O=function(e){function r(t,r,n,i){e.call(this,t,r,n,i),this.roundZoom=!0,this.type=\"video\",this.options=r}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1;var r=this.options;this.urls=[];for(var n=0,i=r.urls;n<i.length;n+=1){var a=i[n];this.urls.push(this.map._requestManager.transformRequest(a,t.ResourceType.Source).url)}t.getVideo(this.urls,(function(r,n){e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(e.video=n,e.video.loop=!0,e.video.addEventListener(\"playing\",(function(){e.map.triggerRepaint()})),e.map&&e.video.play(),e._finishLoading())}))},r.prototype.pause=function(){this.video&&this.video.pause()},r.prototype.play=function(){this.video&&this.video.play()},r.prototype.seek=function(e){if(this.video){var r=this.video.seekable;e<r.start(0)||e>r.end(0)?this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+this.id,null,\"Playback for this video can be set only between the \"+r.start(0)+\" and \"+r.end(0)+\"-second mark.\"))):this.video.currentTime=e}},r.prototype.getVideo=function(){return this.video},r.prototype.onAdd=function(t){this.map||(this.map=t,this.load(),this.video&&(this.video.play(),this.setCoordinates(this.coordinates)))},r.prototype.prepare=function(){if(!(0===Object.keys(this.tiles).length||this.video.readyState<2)){var e=this.map.painter.context,r=e.gl;for(var n in this.boundsBuffer||(this.boundsBuffer=e.createVertexBuffer(this._boundsArray,P.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?this.video.paused||(this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE),r.texSubImage2D(r.TEXTURE_2D,0,0,0,r.RGBA,r.UNSIGNED_BYTE,this.video)):(this.texture=new t.Texture(e,this.video,r.RGBA),this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE)),this.tiles){var i=this.tiles[n];\"loaded\"!==i.state&&(i.state=\"loaded\",i.texture=this.texture)}}},r.prototype.serialize=function(){return{type:\"video\",urls:this.urls,coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this.video&&!this.video.paused},r}(I),z=function(e){function r(r,n,i,a){e.call(this,r,n,i,a),n.coordinates?Array.isArray(n.coordinates)&&4===n.coordinates.length&&!n.coordinates.some((function(t){return!Array.isArray(t)||2!==t.length||t.some((function(t){return\"number\"!=typeof t}))}))||this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'\"coordinates\" property must be an array of 4 longitude/latitude array pairs'))):this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'missing required property \"coordinates\"'))),n.animate&&\"boolean\"!=typeof n.animate&&this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'optional \"animate\" property must be a boolean value'))),n.canvas?\"string\"==typeof n.canvas||n.canvas instanceof t.window.HTMLCanvasElement||this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'\"canvas\" must be either a string representing the ID of the canvas element from which to read, or an HTMLCanvasElement instance'))):this.fire(new t.ErrorEvent(new t.ValidationError(\"sources.\"+r,null,'missing required property \"canvas\"'))),this.options=n,this.animate=void 0===n.animate||n.animate}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){this._loaded=!0,this.canvas||(this.canvas=this.options.canvas instanceof t.window.HTMLCanvasElement?this.options.canvas:t.window.document.getElementById(this.options.canvas)),this.width=this.canvas.width,this.height=this.canvas.height,this._hasInvalidDimensions()?this.fire(new t.ErrorEvent(new Error(\"Canvas dimensions cannot be less than or equal to zero.\"))):(this.play=function(){this._playing=!0,this.map.triggerRepaint()},this.pause=function(){this._playing&&(this.prepare(),this._playing=!1)},this._finishLoading())},r.prototype.getCanvas=function(){return this.canvas},r.prototype.onAdd=function(t){this.map=t,this.load(),this.canvas&&this.animate&&this.play()},r.prototype.onRemove=function(){this.pause()},r.prototype.prepare=function(){var e=!1;if(this.canvas.width!==this.width&&(this.width=this.canvas.width,e=!0),this.canvas.height!==this.height&&(this.height=this.canvas.height,e=!0),!this._hasInvalidDimensions()&&0!==Object.keys(this.tiles).length){var r=this.map.painter.context,n=r.gl;for(var i in this.boundsBuffer||(this.boundsBuffer=r.createVertexBuffer(this._boundsArray,P.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?(e||this._playing)&&this.texture.update(this.canvas,{premultiply:!0}):this.texture=new t.Texture(r,this.canvas,n.RGBA,{premultiply:!0}),this.tiles){var a=this.tiles[i];\"loaded\"!==a.state&&(a.state=\"loaded\",a.texture=this.texture)}}},r.prototype.serialize=function(){return{type:\"canvas\",coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this._playing},r.prototype._hasInvalidDimensions=function(){for(var t=0,e=[this.canvas.width,this.canvas.height];t<e.length;t+=1){var 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e=this.gl;e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,t,0),this.current=t,this.dirty=!1}},e}(_t),Tt=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.set=function(t){if(t!==this.current||this.dirty){this.context.bindFramebuffer.set(this.parent);var e=this.gl;e.framebufferRenderbuffer(e.FRAMEBUFFER,e.DEPTH_ATTACHMENT,e.RENDERBUFFER,t),this.current=t,this.dirty=!1}},e}(_t),kt=function(t,e,r,n){this.context=t,this.width=e,this.height=r;var i=t.gl,a=this.framebuffer=i.createFramebuffer();this.colorAttachment=new wt(t,a),n&&(this.depthAttachment=new Tt(t,a))};kt.prototype.destroy=function(){var t=this.context.gl,e=this.colorAttachment.get();if(e&&t.deleteTexture(e),this.depthAttachment){var r=this.depthAttachment.get();r&&t.deleteRenderbuffer(r)}t.deleteFramebuffer(this.framebuffer)};var At=function(t,e,r){this.func=t,this.mask=e,this.range=r};At.ReadOnly=!1,At.ReadWrite=!0,At.disabled=new At(519,At.ReadOnly,[0,1]);var Mt=function(t,e,r,n,i,a){this.test=t,this.ref=e,this.mask=r,this.fail=n,this.depthFail=i,this.pass=a};Mt.disabled=new Mt({func:519,mask:0},0,0,7680,7680,7680);var St=function(t,e,r){this.blendFunction=t,this.blendColor=e,this.mask=r};St.disabled=new St(St.Replace=[1,0],t.Color.transparent,[!1,!1,!1,!1]),St.unblended=new St(St.Replace,t.Color.transparent,[!0,!0,!0,!0]),St.alphaBlended=new St([1,771],t.Color.transparent,[!0,!0,!0,!0]);var Et=function(t,e,r){this.enable=t,this.mode=e,this.frontFace=r};Et.disabled=new Et(!1,1029,2305),Et.backCCW=new Et(!0,1029,2305);var Lt=function(t){this.gl=t,this.extVertexArrayObject=this.gl.getExtension(\"OES_vertex_array_object\"),this.clearColor=new H(this),this.clearDepth=new G(this),this.clearStencil=new Y(this),this.colorMask=new W(this),this.depthMask=new X(this),this.stencilMask=new Z(this),this.stencilFunc=new J(this),this.stencilOp=new K(this),this.stencilTest=new Q(this),this.depthRange=new $(this),this.depthTest=new tt(this),this.depthFunc=new et(this),this.blend=new rt(this),this.blendFunc=new nt(this),this.blendColor=new it(this),this.blendEquation=new at(this),this.cullFace=new ot(this),this.cullFaceSide=new st(this),this.frontFace=new lt(this),this.program=new ct(this),this.activeTexture=new ut(this),this.viewport=new ft(this),this.bindFramebuffer=new ht(this),this.bindRenderbuffer=new pt(this),this.bindTexture=new dt(this),this.bindVertexBuffer=new gt(this),this.bindElementBuffer=new mt(this),this.bindVertexArrayOES=this.extVertexArrayObject&&new vt(this),this.pixelStoreUnpack=new yt(this),this.pixelStoreUnpackPremultiplyAlpha=new xt(this),this.pixelStoreUnpackFlipY=new bt(this),this.extTextureFilterAnisotropic=t.getExtension(\"EXT_texture_filter_anisotropic\")||t.getExtension(\"MOZ_EXT_texture_filter_anisotropic\")||t.getExtension(\"WEBKIT_EXT_texture_filter_anisotropic\"),this.extTextureFilterAnisotropic&&(this.extTextureFilterAnisotropicMax=t.getParameter(this.extTextureFilterAnisotropic.MAX_TEXTURE_MAX_ANISOTROPY_EXT)),this.extTextureHalfFloat=t.getExtension(\"OES_texture_half_float\"),this.extTextureHalfFloat&&(t.getExtension(\"OES_texture_half_float_linear\"),this.extRenderToTextureHalfFloat=t.getExtension(\"EXT_color_buffer_half_float\")),this.extTimerQuery=t.getExtension(\"EXT_disjoint_timer_query\")};Lt.prototype.setDefault=function(){this.unbindVAO(),this.clearColor.setDefault(),this.clearDepth.setDefault(),this.clearStencil.setDefault(),this.colorMask.setDefault(),this.depthMask.setDefault(),this.stencilMask.setDefault(),this.stencilFunc.setDefault(),this.stencilOp.setDefault(),this.stencilTest.setDefault(),this.depthRange.setDefault(),this.depthTest.setDefault(),this.depthFunc.setDefault(),this.blend.setDefault(),this.blendFunc.setDefault(),this.blendColor.setDefault(),this.blendEquation.setDefault(),this.cullFace.setDefault(),this.cullFaceSide.setDefault(),this.frontFace.setDefault(),this.program.setDefault(),this.activeTexture.setDefault(),this.bindFramebuffer.setDefault(),this.pixelStoreUnpack.setDefault(),this.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.pixelStoreUnpackFlipY.setDefault()},Lt.prototype.setDirty=function(){this.clearColor.dirty=!0,this.clearDepth.dirty=!0,this.clearStencil.dirty=!0,this.colorMask.dirty=!0,this.depthMask.dirty=!0,this.stencilMask.dirty=!0,this.stencilFunc.dirty=!0,this.stencilOp.dirty=!0,this.stencilTest.dirty=!0,this.depthRange.dirty=!0,this.depthTest.dirty=!0,this.depthFunc.dirty=!0,this.blend.dirty=!0,this.blendFunc.dirty=!0,this.blendColor.dirty=!0,this.blendEquation.dirty=!0,this.cullFace.dirty=!0,this.cullFaceSide.dirty=!0,this.frontFace.dirty=!0,this.program.dirty=!0,this.activeTexture.dirty=!0,this.viewport.dirty=!0,this.bindFramebuffer.dirty=!0,this.bindRenderbuffer.dirty=!0,this.bindTexture.dirty=!0,this.bindVertexBuffer.dirty=!0,this.bindElementBuffer.dirty=!0,this.extVertexArrayObject&&(this.bindVertexArrayOES.dirty=!0),this.pixelStoreUnpack.dirty=!0,this.pixelStoreUnpackPremultiplyAlpha.dirty=!0,this.pixelStoreUnpackFlipY.dirty=!0},Lt.prototype.createIndexBuffer=function(t,e){return new j(this,t,e)},Lt.prototype.createVertexBuffer=function(t,e,r){return new V(this,t,e,r)},Lt.prototype.createRenderbuffer=function(t,e,r){var n=this.gl,i=n.createRenderbuffer();return this.bindRenderbuffer.set(i),n.renderbufferStorage(n.RENDERBUFFER,t,e,r),this.bindRenderbuffer.set(null),i},Lt.prototype.createFramebuffer=function(t,e,r){return new kt(this,t,e,r)},Lt.prototype.clear=function(t){var e=t.color,r=t.depth,n=this.gl,i=0;e&&(i|=n.COLOR_BUFFER_BIT,this.clearColor.set(e),this.colorMask.set([!0,!0,!0,!0])),void 0!==r&&(i|=n.DEPTH_BUFFER_BIT,this.depthRange.set([0,1]),this.clearDepth.set(r),this.depthMask.set(!0)),n.clear(i)},Lt.prototype.setCullFace=function(t){!1===t.enable?this.cullFace.set(!1):(this.cullFace.set(!0),this.cullFaceSide.set(t.mode),this.frontFace.set(t.frontFace))},Lt.prototype.setDepthMode=function(t){t.func!==this.gl.ALWAYS||t.mask?(this.depthTest.set(!0),this.depthFunc.set(t.func),this.depthMask.set(t.mask),this.depthRange.set(t.range)):this.depthTest.set(!1)},Lt.prototype.setStencilMode=function(t){t.test.func!==this.gl.ALWAYS||t.mask?(this.stencilTest.set(!0),this.stencilMask.set(t.mask),this.stencilOp.set([t.fail,t.depthFail,t.pass]),this.stencilFunc.set({func:t.test.func,ref:t.ref,mask:t.test.mask})):this.stencilTest.set(!1)},Lt.prototype.setColorMode=function(e){t.deepEqual(e.blendFunction,St.Replace)?this.blend.set(!1):(this.blend.set(!0),this.blendFunc.set(e.blendFunction),this.blendColor.set(e.blendColor)),this.colorMask.set(e.mask)},Lt.prototype.unbindVAO=function(){this.extVertexArrayObject&&this.bindVertexArrayOES.set(null)};var Ct=function(e){function r(r,n,i){var a=this;e.call(this),this.id=r,this.dispatcher=i,this.on(\"data\",(function(t){\"source\"===t.dataType&&\"metadata\"===t.sourceDataType&&(a._sourceLoaded=!0),a._sourceLoaded&&!a._paused&&\"source\"===t.dataType&&\"content\"===t.sourceDataType&&(a.reload(),a.transform&&a.update(a.transform))})),this.on(\"error\",(function(){a._sourceErrored=!0})),this._source=function(e,r,n,i){var a=new D[r.type](e,r,n,i);if(a.id!==e)throw new Error(\"Expected Source id to be \"+e+\" instead of \"+a.id);return t.bindAll([\"load\",\"abort\",\"unload\",\"serialize\",\"prepare\"],a),a}(r,n,i,this),this._tiles={},this._cache=new N(0,this._unloadTile.bind(this)),this._timers={},this._cacheTimers={},this._maxTileCacheSize=null,this._loadedParentTiles={},this._coveredTiles={},this._state=new t.SourceFeatureState}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.onAdd=function(t){this.map=t,this._maxTileCacheSize=t?t._maxTileCacheSize:null,this._source&&this._source.onAdd&&this._source.onAdd(t)},r.prototype.onRemove=function(t){this._source&&this._source.onRemove&&this._source.onRemove(t)},r.prototype.loaded=function(){if(this._sourceErrored)return!0;if(!this._sourceLoaded)return!1;if(!this._source.loaded())return!1;for(var t in this._tiles){var e=this._tiles[t];if(\"loaded\"!==e.state&&\"errored\"!==e.state)return!1}return!0},r.prototype.getSource=function(){return this._source},r.prototype.pause=function(){this._paused=!0},r.prototype.resume=function(){if(this._paused){var t=this._shouldReloadOnResume;this._paused=!1,this._shouldReloadOnResume=!1,t&&this.reload(),this.transform&&this.update(this.transform)}},r.prototype._loadTile=function(t,e){return this._source.loadTile(t,e)},r.prototype._unloadTile=function(t){if(this._source.unloadTile)return this._source.unloadTile(t,(function(){}))},r.prototype._abortTile=function(t){if(this._source.abortTile)return this._source.abortTile(t,(function(){}))},r.prototype.serialize=function(){return this._source.serialize()},r.prototype.prepare=function(t){for(var e in this._source.prepare&&this._source.prepare(),this._state.coalesceChanges(this._tiles,this.map?this.map.painter:null),this._tiles){var r=this._tiles[e];r.upload(t),r.prepare(this.map.style.imageManager)}},r.prototype.getIds=function(){return t.values(this._tiles).map((function(t){return t.tileID})).sort(Pt).map((function(t){return t.key}))},r.prototype.getRenderableIds=function(e){var r=this,n=[];for(var i in this._tiles)this._isIdRenderable(i,e)&&n.push(this._tiles[i]);return e?n.sort((function(e,n){var i=e.tileID,a=n.tileID,o=new t.Point(i.canonical.x,i.canonical.y)._rotate(r.transform.angle),s=new t.Point(a.canonical.x,a.canonical.y)._rotate(r.transform.angle);return i.overscaledZ-a.overscaledZ||s.y-o.y||s.x-o.x})).map((function(t){return t.tileID.key})):n.map((function(t){return t.tileID})).sort(Pt).map((function(t){return t.key}))},r.prototype.hasRenderableParent=function(t){var e=this.findLoadedParent(t,0);return!!e&&this._isIdRenderable(e.tileID.key)},r.prototype._isIdRenderable=function(t,e){return this._tiles[t]&&this._tiles[t].hasData()&&!this._coveredTiles[t]&&(e||!this._tiles[t].holdingForFade())},r.prototype.reload=function(){if(this._paused)this._shouldReloadOnResume=!0;else for(var t in this._cache.reset(),this._tiles)\"errored\"!==this._tiles[t].state&&this._reloadTile(t,\"reloading\")},r.prototype._reloadTile=function(t,e){var r=this._tiles[t];r&&(\"loading\"!==r.state&&(r.state=e),this._loadTile(r,this._tileLoaded.bind(this,r,t,e)))},r.prototype._tileLoaded=function(e,r,n,i){if(i)return e.state=\"errored\",void(404!==i.status?this._source.fire(new t.ErrorEvent(i,{tile:e})):this.update(this.transform));e.timeAdded=t.browser.now(),\"expired\"===n&&(e.refreshedUponExpiration=!0),this._setTileReloadTimer(r,e),\"raster-dem\"===this.getSource().type&&e.dem&&this._backfillDEM(e),this._state.initializeTileState(e,this.map?this.map.painter:null),this._source.fire(new t.Event(\"data\",{dataType:\"source\",tile:e,coord:e.tileID}))},r.prototype._backfillDEM=function(t){for(var e=this.getRenderableIds(),r=0;r<e.length;r++){var n=e[r];if(t.neighboringTiles&&t.neighboringTiles[n]){var i=this.getTileByID(n);a(t,i),a(i,t)}}function a(t,e){t.needsHillshadePrepare=!0;var r=e.tileID.canonical.x-t.tileID.canonical.x,n=e.tileID.canonical.y-t.tileID.canonical.y,i=Math.pow(2,t.tileID.canonical.z),a=e.tileID.key;0===r&&0===n||Math.abs(n)>1||(Math.abs(r)>1&&(1===Math.abs(r+i)?r+=i:1===Math.abs(r-i)&&(r-=i)),e.dem&&t.dem&&(t.dem.backfillBorder(e.dem,r,n),t.neighboringTiles&&t.neighboringTiles[a]&&(t.neighboringTiles[a].backfilled=!0)))}},r.prototype.getTile=function(t){return this.getTileByID(t.key)},r.prototype.getTileByID=function(t){return this._tiles[t]},r.prototype._retainLoadedChildren=function(t,e,r,n){for(var i in this._tiles){var a=this._tiles[i];if(!(n[i]||!a.hasData()||a.tileID.overscaledZ<=e||a.tileID.overscaledZ>r)){for(var o=a.tileID;a&&a.tileID.overscaledZ>e+1;){var s=a.tileID.scaledTo(a.tileID.overscaledZ-1);(a=this._tiles[s.key])&&a.hasData()&&(o=s)}for(var l=o;l.overscaledZ>e;)if(t[(l=l.scaledTo(l.overscaledZ-1)).key]){n[o.key]=o;break}}}},r.prototype.findLoadedParent=function(t,e){if(t.key in this._loadedParentTiles){var r=this._loadedParentTiles[t.key];return r&&r.tileID.overscaledZ>=e?r:null}for(var n=t.overscaledZ-1;n>=e;n--){var i=t.scaledTo(n),a=this._getLoadedTile(i);if(a)return a}},r.prototype._getLoadedTile=function(t){var e=this._tiles[t.key];return e&&e.hasData()?e:this._cache.getByKey(t.wrapped().key)},r.prototype.updateCacheSize=function(t){var e=(Math.ceil(t.width/this._source.tileSize)+1)*(Math.ceil(t.height/this._source.tileSize)+1),r=Math.floor(5*e),n=\"number\"==typeof this._maxTileCacheSize?Math.min(this._maxTileCacheSize,r):r;this._cache.setMaxSize(n)},r.prototype.handleWrapJump=function(t){var e=(t-(void 0===this._prevLng?t:this._prevLng))/360,r=Math.round(e);if(this._prevLng=t,r){var n={};for(var i in this._tiles){var a=this._tiles[i];a.tileID=a.tileID.unwrapTo(a.tileID.wrap+r),n[a.tileID.key]=a}for(var o in this._tiles=n,this._timers)clearTimeout(this._timers[o]),delete this._timers[o];for(var s in this._tiles){var l=this._tiles[s];this._setTileReloadTimer(s,l)}}},r.prototype.update=function(e){var n=this;if(this.transform=e,this._sourceLoaded&&!this._paused){var i;this.updateCacheSize(e),this.handleWrapJump(this.transform.center.lng),this._coveredTiles={},this.used?this._source.tileID?i=e.getVisibleUnwrappedCoordinates(this._source.tileID).map((function(e){return new t.OverscaledTileID(e.canonical.z,e.wrap,e.canonical.z,e.canonical.x,e.canonical.y)})):(i=e.coveringTiles({tileSize:this._source.tileSize,minzoom:this._source.minzoom,maxzoom:this._source.maxzoom,roundZoom:this._source.roundZoom,reparseOverscaled:this._source.reparseOverscaled}),this._source.hasTile&&(i=i.filter((function(t){return n._source.hasTile(t)})))):i=[];var a=e.coveringZoomLevel(this._source),o=Math.max(a-r.maxOverzooming,this._source.minzoom),s=Math.max(a+r.maxUnderzooming,this._source.minzoom),l=this._updateRetainedTiles(i,a);if(It(this._source.type)){for(var c={},u={},f=0,h=Object.keys(l);f<h.length;f+=1){var p=h[f],d=l[p],g=this._tiles[p];if(g&&!(g.fadeEndTime&&g.fadeEndTime<=t.browser.now())){var m=this.findLoadedParent(d,o);m&&(this._addTile(m.tileID),c[m.tileID.key]=m.tileID),u[p]=d}}for(var v in this._retainLoadedChildren(u,a,s,l),c)l[v]||(this._coveredTiles[v]=!0,l[v]=c[v])}for(var y in l)this._tiles[y].clearFadeHold();for(var x=0,b=t.keysDifference(this._tiles,l);x<b.length;x+=1){var _=b[x],w=this._tiles[_];w.hasSymbolBuckets&&!w.holdingForFade()?w.setHoldDuration(this.map._fadeDuration):w.hasSymbolBuckets&&!w.symbolFadeFinished()||this._removeTile(_)}this._updateLoadedParentTileCache()}},r.prototype.releaseSymbolFadeTiles=function(){for(var t in this._tiles)this._tiles[t].holdingForFade()&&this._removeTile(t)},r.prototype._updateRetainedTiles=function(t,e){for(var n={},i={},a=Math.max(e-r.maxOverzooming,this._source.minzoom),o=Math.max(e+r.maxUnderzooming,this._source.minzoom),s={},l=0,c=t;l<c.length;l+=1){var u=c[l],f=this._addTile(u);n[u.key]=u,f.hasData()||e<this._source.maxzoom&&(s[u.key]=u)}this._retainLoadedChildren(s,e,o,n);for(var h=0,p=t;h<p.length;h+=1){var d=p[h],g=this._tiles[d.key];if(!g.hasData()){if(e+1>this._source.maxzoom){var m=d.children(this._source.maxzoom)[0],v=this.getTile(m);if(v&&v.hasData()){n[m.key]=m;continue}}else{var y=d.children(this._source.maxzoom);if(n[y[0].key]&&n[y[1].key]&&n[y[2].key]&&n[y[3].key])continue}for(var x=g.wasRequested(),b=d.overscaledZ-1;b>=a;--b){var _=d.scaledTo(b);if(i[_.key])break;if(i[_.key]=!0,!(g=this.getTile(_))&&x&&(g=this._addTile(_)),g&&(n[_.key]=_,x=g.wasRequested(),g.hasData()))break}}}return n},r.prototype._updateLoadedParentTileCache=function(){for(var t in this._loadedParentTiles={},this._tiles){for(var e=[],r=void 0,n=this._tiles[t].tileID;n.overscaledZ>0;){if(n.key in this._loadedParentTiles){r=this._loadedParentTiles[n.key];break}e.push(n.key);var i=n.scaledTo(n.overscaledZ-1);if(r=this._getLoadedTile(i))break;n=i}for(var a=0,o=e;a<o.length;a+=1){var s=o[a];this._loadedParentTiles[s]=r}}},r.prototype._addTile=function(e){var r=this._tiles[e.key];if(r)return r;(r=this._cache.getAndRemove(e))&&(this._setTileReloadTimer(e.key,r),r.tileID=e,this._state.initializeTileState(r,this.map?this.map.painter:null),this._cacheTimers[e.key]&&(clearTimeout(this._cacheTimers[e.key]),delete this._cacheTimers[e.key],this._setTileReloadTimer(e.key,r)));var n=Boolean(r);return n||(r=new t.Tile(e,this._source.tileSize*e.overscaleFactor()),this._loadTile(r,this._tileLoaded.bind(this,r,e.key,r.state))),r?(r.uses++,this._tiles[e.key]=r,n||this._source.fire(new t.Event(\"dataloading\",{tile:r,coord:r.tileID,dataType:\"source\"})),r):null},r.prototype._setTileReloadTimer=function(t,e){var r=this;t in this._timers&&(clearTimeout(this._timers[t]),delete this._timers[t]);var n=e.getExpiryTimeout();n&&(this._timers[t]=setTimeout((function(){r._reloadTile(t,\"expired\"),delete r._timers[t]}),n))},r.prototype._removeTile=function(t){var e=this._tiles[t];e&&(e.uses--,delete this._tiles[t],this._timers[t]&&(clearTimeout(this._timers[t]),delete this._timers[t]),e.uses>0||(e.hasData()&&\"reloading\"!==e.state?this._cache.add(e.tileID,e,e.getExpiryTimeout()):(e.aborted=!0,this._abortTile(e),this._unloadTile(e))))},r.prototype.clearTiles=function(){for(var t in this._shouldReloadOnResume=!1,this._paused=!1,this._tiles)this._removeTile(t);this._cache.reset()},r.prototype.tilesIn=function(e,r,n){var i=this,a=[],o=this.transform;if(!o)return a;for(var s=n?o.getCameraQueryGeometry(e):e,l=e.map((function(t){return o.pointCoordinate(t)})),c=s.map((function(t){return o.pointCoordinate(t)})),u=this.getIds(),f=1/0,h=1/0,p=-1/0,d=-1/0,g=0,m=c;g<m.length;g+=1){var v=m[g];f=Math.min(f,v.x),h=Math.min(h,v.y),p=Math.max(p,v.x),d=Math.max(d,v.y)}for(var y=function(e){var n=i._tiles[u[e]];if(!n.holdingForFade()){var s=n.tileID,g=Math.pow(2,o.zoom-n.tileID.overscaledZ),m=r*n.queryPadding*t.EXTENT/n.tileSize/g,v=[s.getTilePoint(new t.MercatorCoordinate(f,h)),s.getTilePoint(new t.MercatorCoordinate(p,d))];if(v[0].x-m<t.EXTENT&&v[0].y-m<t.EXTENT&&v[1].x+m>=0&&v[1].y+m>=0){var y=l.map((function(t){return s.getTilePoint(t)})),x=c.map((function(t){return s.getTilePoint(t)}));a.push({tile:n,tileID:s,queryGeometry:y,cameraQueryGeometry:x,scale:g})}}},x=0;x<u.length;x++)y(x);return a},r.prototype.getVisibleCoordinates=function(t){for(var e=this,r=this.getRenderableIds(t).map((function(t){return e._tiles[t].tileID})),n=0,i=r;n<i.length;n+=1){var a=i[n];a.posMatrix=this.transform.calculatePosMatrix(a.toUnwrapped())}return r},r.prototype.hasTransition=function(){if(this._source.hasTransition())return!0;if(It(this._source.type))for(var e in this._tiles){var r=this._tiles[e];if(void 0!==r.fadeEndTime&&r.fadeEndTime>=t.browser.now())return!0}return!1},r.prototype.setFeatureState=function(t,e,r){t=t||\"_geojsonTileLayer\",this._state.updateState(t,e,r)},r.prototype.removeFeatureState=function(t,e,r){t=t||\"_geojsonTileLayer\",this._state.removeFeatureState(t,e,r)},r.prototype.getFeatureState=function(t,e){return t=t||\"_geojsonTileLayer\",this._state.getState(t,e)},r.prototype.setDependencies=function(t,e,r){var n=this._tiles[t];n&&n.setDependencies(e,r)},r.prototype.reloadTilesForDependencies=function(t,e){for(var r in this._tiles){this._tiles[r].hasDependency(t,e)&&this._reloadTile(r,\"reloading\")}this._cache.filter((function(r){return!r.hasDependency(t,e)}))},r}(t.Evented);function Pt(t,e){var r=Math.abs(2*t.wrap)-+(t.wrap<0),n=Math.abs(2*e.wrap)-+(e.wrap<0);return t.overscaledZ-e.overscaledZ||n-r||e.canonical.y-t.canonical.y||e.canonical.x-t.canonical.x}function It(t){return\"raster\"===t||\"image\"===t||\"video\"===t}function Ot(){return new t.window.Worker(Zi.workerUrl)}Ct.maxOverzooming=10,Ct.maxUnderzooming=3;var zt=\"mapboxgl_preloaded_worker_pool\",Dt=function(){this.active={}};Dt.prototype.acquire=function(t){if(!this.workers)for(this.workers=[];this.workers.length<Dt.workerCount;)this.workers.push(new Ot);return this.active[t]=!0,this.workers.slice()},Dt.prototype.release=function(t){delete this.active[t],0===this.numActive()&&(this.workers.forEach((function(t){t.terminate()})),this.workers=null)},Dt.prototype.isPreloaded=function(){return!!this.active[zt]},Dt.prototype.numActive=function(){return Object.keys(this.active).length};var Rt,Ft=Math.floor(t.browser.hardwareConcurrency/2);function Bt(){return Rt||(Rt=new Dt),Rt}function Nt(e,r){var n={};for(var i in e)\"ref\"!==i&&(n[i]=e[i]);return t.refProperties.forEach((function(t){t in r&&(n[t]=r[t])})),n}function jt(t){t=t.slice();for(var e=Object.create(null),r=0;r<t.length;r++)e[t[r].id]=t[r];for(var n=0;n<t.length;n++)\"ref\"in t[n]&&(t[n]=Nt(t[n],e[t[n].ref]));return t}Dt.workerCount=Math.max(Math.min(Ft,6),1);var Ut={setStyle:\"setStyle\",addLayer:\"addLayer\",removeLayer:\"removeLayer\",setPaintProperty:\"setPaintProperty\",setLayoutProperty:\"setLayoutProperty\",setFilter:\"setFilter\",addSource:\"addSource\",removeSource:\"removeSource\",setGeoJSONSourceData:\"setGeoJSONSourceData\",setLayerZoomRange:\"setLayerZoomRange\",setLayerProperty:\"setLayerProperty\",setCenter:\"setCenter\",setZoom:\"setZoom\",setBearing:\"setBearing\",setPitch:\"setPitch\",setSprite:\"setSprite\",setGlyphs:\"setGlyphs\",setTransition:\"setTransition\",setLight:\"setLight\"};function Vt(t,e,r){r.push({command:Ut.addSource,args:[t,e[t]]})}function qt(t,e,r){e.push({command:Ut.removeSource,args:[t]}),r[t]=!0}function Ht(t,e,r,n){qt(t,r,n),Vt(t,e,r)}function Gt(e,r,n){var i;for(i in e[n])if(e[n].hasOwnProperty(i)&&\"data\"!==i&&!t.deepEqual(e[n][i],r[n][i]))return!1;for(i in r[n])if(r[n].hasOwnProperty(i)&&\"data\"!==i&&!t.deepEqual(e[n][i],r[n][i]))return!1;return!0}function Yt(e,r,n,i,a,o){var s;for(s in r=r||{},e=e||{})e.hasOwnProperty(s)&&(t.deepEqual(e[s],r[s])||n.push({command:o,args:[i,s,r[s],a]}));for(s in r)r.hasOwnProperty(s)&&!e.hasOwnProperty(s)&&(t.deepEqual(e[s],r[s])||n.push({command:o,args:[i,s,r[s],a]}))}function Wt(t){return t.id}function Xt(t,e){return t[e.id]=e,t}function Zt(e,r){if(!e)return[{command:Ut.setStyle,args:[r]}];var n=[];try{if(!t.deepEqual(e.version,r.version))return[{command:Ut.setStyle,args:[r]}];t.deepEqual(e.center,r.center)||n.push({command:Ut.setCenter,args:[r.center]}),t.deepEqual(e.zoom,r.zoom)||n.push({command:Ut.setZoom,args:[r.zoom]}),t.deepEqual(e.bearing,r.bearing)||n.push({command:Ut.setBearing,args:[r.bearing]}),t.deepEqual(e.pitch,r.pitch)||n.push({command:Ut.setPitch,args:[r.pitch]}),t.deepEqual(e.sprite,r.sprite)||n.push({command:Ut.setSprite,args:[r.sprite]}),t.deepEqual(e.glyphs,r.glyphs)||n.push({command:Ut.setGlyphs,args:[r.glyphs]}),t.deepEqual(e.transition,r.transition)||n.push({command:Ut.setTransition,args:[r.transition]}),t.deepEqual(e.light,r.light)||n.push({command:Ut.setLight,args:[r.light]});var i={},a=[];!function(e,r,n,i){var a;for(a in r=r||{},e=e||{})e.hasOwnProperty(a)&&(r.hasOwnProperty(a)||qt(a,n,i));for(a in r)r.hasOwnProperty(a)&&(e.hasOwnProperty(a)?t.deepEqual(e[a],r[a])||(\"geojson\"===e[a].type&&\"geojson\"===r[a].type&&Gt(e,r,a)?n.push({command:Ut.setGeoJSONSourceData,args:[a,r[a].data]}):Ht(a,r,n,i)):Vt(a,r,n))}(e.sources,r.sources,a,i);var o=[];e.layers&&e.layers.forEach((function(t){i[t.source]?n.push({command:Ut.removeLayer,args:[t.id]}):o.push(t)})),n=n.concat(a),function(e,r,n){r=r||[];var i,a,o,s,l,c,u,f=(e=e||[]).map(Wt),h=r.map(Wt),p=e.reduce(Xt,{}),d=r.reduce(Xt,{}),g=f.slice(),m=Object.create(null);for(i=0,a=0;i<f.length;i++)o=f[i],d.hasOwnProperty(o)?a++:(n.push({command:Ut.removeLayer,args:[o]}),g.splice(g.indexOf(o,a),1));for(i=0,a=0;i<h.length;i++)o=h[h.length-1-i],g[g.length-1-i]!==o&&(p.hasOwnProperty(o)?(n.push({command:Ut.removeLayer,args:[o]}),g.splice(g.lastIndexOf(o,g.length-a),1)):a++,c=g[g.length-i],n.push({command:Ut.addLayer,args:[d[o],c]}),g.splice(g.length-i,0,o),m[o]=!0);for(i=0;i<h.length;i++)if(s=p[o=h[i]],l=d[o],!m[o]&&!t.deepEqual(s,l))if(t.deepEqual(s.source,l.source)&&t.deepEqual(s[\"source-layer\"],l[\"source-layer\"])&&t.deepEqual(s.type,l.type)){for(u in Yt(s.layout,l.layout,n,o,null,Ut.setLayoutProperty),Yt(s.paint,l.paint,n,o,null,Ut.setPaintProperty),t.deepEqual(s.filter,l.filter)||n.push({command:Ut.setFilter,args:[o,l.filter]}),t.deepEqual(s.minzoom,l.minzoom)&&t.deepEqual(s.maxzoom,l.maxzoom)||n.push({command:Ut.setLayerZoomRange,args:[o,l.minzoom,l.maxzoom]}),s)s.hasOwnProperty(u)&&\"layout\"!==u&&\"paint\"!==u&&\"filter\"!==u&&\"metadata\"!==u&&\"minzoom\"!==u&&\"maxzoom\"!==u&&(0===u.indexOf(\"paint.\")?Yt(s[u],l[u],n,o,u.slice(6),Ut.setPaintProperty):t.deepEqual(s[u],l[u])||n.push({command:Ut.setLayerProperty,args:[o,u,l[u]]}));for(u in l)l.hasOwnProperty(u)&&!s.hasOwnProperty(u)&&\"layout\"!==u&&\"paint\"!==u&&\"filter\"!==u&&\"metadata\"!==u&&\"minzoom\"!==u&&\"maxzoom\"!==u&&(0===u.indexOf(\"paint.\")?Yt(s[u],l[u],n,o,u.slice(6),Ut.setPaintProperty):t.deepEqual(s[u],l[u])||n.push({command:Ut.setLayerProperty,args:[o,u,l[u]]}))}else n.push({command:Ut.removeLayer,args:[o]}),c=g[g.lastIndexOf(o)+1],n.push({command:Ut.addLayer,args:[l,c]})}(o,r.layers,n)}catch(t){console.warn(\"Unable to compute style diff:\",t),n=[{command:Ut.setStyle,args:[r]}]}return n}var Jt=function(t,e){this.reset(t,e)};Jt.prototype.reset=function(t,e){this.points=t||[],this._distances=[0];for(var r=1;r<this.points.length;r++)this._distances[r]=this._distances[r-1]+this.points[r].dist(this.points[r-1]);this.length=this._distances[this._distances.length-1],this.padding=Math.min(e||0,.5*this.length),this.paddedLength=this.length-2*this.padding},Jt.prototype.lerp=function(e){if(1===this.points.length)return this.points[0];e=t.clamp(e,0,1);for(var r=1,n=this._distances[r],i=e*this.paddedLength+this.padding;n<i&&r<this._distances.length;)n=this._distances[++r];var a=r-1,o=this._distances[a],s=n-o,l=s>0?(i-o)/s:0;return this.points[a].mult(1-l).add(this.points[r].mult(l))};var Kt=function(t,e,r){var n=this.boxCells=[],i=this.circleCells=[];this.xCellCount=Math.ceil(t/r),this.yCellCount=Math.ceil(e/r);for(var a=0;a<this.xCellCount*this.yCellCount;a++)n.push([]),i.push([]);this.circleKeys=[],this.boxKeys=[],this.bboxes=[],this.circles=[],this.width=t,this.height=e,this.xScale=this.xCellCount/t,this.yScale=this.yCellCount/e,this.boxUid=0,this.circleUid=0};function Qt(e,r,n,i,a){var o=t.create();return r?(t.scale(o,o,[1/a,1/a,1]),n||t.rotateZ(o,o,i.angle)):t.multiply(o,i.labelPlaneMatrix,e),o}function $t(e,r,n,i,a){if(r){var o=t.clone(e);return t.scale(o,o,[a,a,1]),n||t.rotateZ(o,o,-i.angle),o}return i.glCoordMatrix}function te(e,r){var n=[e.x,e.y,0,1];fe(n,n,r);var i=n[3];return{point:new t.Point(n[0]/i,n[1]/i),signedDistanceFromCamera:i}}function ee(t,e){return.5+t/e*.5}function re(t,e){var r=t[0]/t[3],n=t[1]/t[3];return r>=-e[0]&&r<=e[0]&&n>=-e[1]&&n<=e[1]}function ne(e,r,n,i,a,o,s,l){var c=i?e.textSizeData:e.iconSizeData,u=t.evaluateSizeForZoom(c,n.transform.zoom),f=[256/n.width*2+1,256/n.height*2+1],h=i?e.text.dynamicLayoutVertexArray:e.icon.dynamicLayoutVertexArray;h.clear();for(var p=e.lineVertexArray,d=i?e.text.placedSymbolArray:e.icon.placedSymbolArray,g=n.transform.width/n.transform.height,m=!1,v=0;v<d.length;v++){var y=d.get(v);if(y.hidden||y.writingMode===t.WritingMode.vertical&&!m)ue(y.numGlyphs,h);else{m=!1;var x=[y.anchorX,y.anchorY,0,1];if(t.transformMat4(x,x,r),re(x,f)){var b=x[3],_=ee(n.transform.cameraToCenterDistance,b),w=t.evaluateSizeForFeature(c,u,y),T=s?w/_:w*_,k=new t.Point(y.anchorX,y.anchorY),A=te(k,a).point,M={},S=oe(y,T,!1,l,r,a,o,e.glyphOffsetArray,p,h,A,k,M,g);m=S.useVertical,(S.notEnoughRoom||m||S.needsFlipping&&oe(y,T,!0,l,r,a,o,e.glyphOffsetArray,p,h,A,k,M,g).notEnoughRoom)&&ue(y.numGlyphs,h)}else ue(y.numGlyphs,h)}}i?e.text.dynamicLayoutVertexBuffer.updateData(h):e.icon.dynamicLayoutVertexBuffer.updateData(h)}function ie(t,e,r,n,i,a,o,s,l,c,u){var f=s.glyphStartIndex+s.numGlyphs,h=s.lineStartIndex,p=s.lineStartIndex+s.lineLength,d=e.getoffsetX(s.glyphStartIndex),g=e.getoffsetX(f-1),m=le(t*d,r,n,i,a,o,s.segment,h,p,l,c,u);if(!m)return null;var v=le(t*g,r,n,i,a,o,s.segment,h,p,l,c,u);return v?{first:m,last:v}:null}function ae(e,r,n,i){if(e===t.WritingMode.horizontal&&Math.abs(n.y-r.y)>Math.abs(n.x-r.x)*i)return{useVertical:!0};return(e===t.WritingMode.vertical?r.y<n.y:r.x>n.x)?{needsFlipping:!0}:null}function oe(e,r,n,i,a,o,s,l,c,u,f,h,p,d){var g,m=r/24,v=e.lineOffsetX*m,y=e.lineOffsetY*m;if(e.numGlyphs>1){var x=e.glyphStartIndex+e.numGlyphs,b=e.lineStartIndex,_=e.lineStartIndex+e.lineLength,w=ie(m,l,v,y,n,f,h,e,c,o,p);if(!w)return{notEnoughRoom:!0};var T=te(w.first.point,s).point,k=te(w.last.point,s).point;if(i&&!n){var A=ae(e.writingMode,T,k,d);if(A)return A}g=[w.first];for(var M=e.glyphStartIndex+1;M<x-1;M++)g.push(le(m*l.getoffsetX(M),v,y,n,f,h,e.segment,b,_,c,o,p));g.push(w.last)}else{if(i&&!n){var S=te(h,a).point,E=e.lineStartIndex+e.segment+1,L=new t.Point(c.getx(E),c.gety(E)),C=te(L,a),P=C.signedDistanceFromCamera>0?C.point:se(h,L,S,1,a),I=ae(e.writingMode,S,P,d);if(I)return I}var O=le(m*l.getoffsetX(e.glyphStartIndex),v,y,n,f,h,e.segment,e.lineStartIndex,e.lineStartIndex+e.lineLength,c,o,p);if(!O)return{notEnoughRoom:!0};g=[O]}for(var z=0,D=g;z<D.length;z+=1){var R=D[z];t.addDynamicAttributes(u,R.point,R.angle)}return{}}function se(t,e,r,n,i){var a=te(t.add(t.sub(e)._unit()),i).point,o=r.sub(a);return r.add(o._mult(n/o.mag()))}function le(e,r,n,i,a,o,s,l,c,u,f,h){var p=i?e-r:e+r,d=p>0?1:-1,g=0;i&&(d*=-1,g=Math.PI),d<0&&(g+=Math.PI);for(var m=d>0?l+s:l+s+1,v=a,y=a,x=0,b=0,_=Math.abs(p),w=[];x+b<=_;){if((m+=d)<l||m>=c)return null;if(y=v,w.push(v),void 0===(v=h[m])){var T=new t.Point(u.getx(m),u.gety(m)),k=te(T,f);if(k.signedDistanceFromCamera>0)v=h[m]=k.point;else{var A=m-d;v=se(0===x?o:new t.Point(u.getx(A),u.gety(A)),T,y,_-x+1,f)}}x+=b,b=y.dist(v)}var M=(_-x)/b,S=v.sub(y),E=S.mult(M)._add(y);E._add(S._unit()._perp()._mult(n*d));var L=g+Math.atan2(v.y-y.y,v.x-y.x);return w.push(E),{point:E,angle:L,path:w}}Kt.prototype.keysLength=function(){return this.boxKeys.length+this.circleKeys.length},Kt.prototype.insert=function(t,e,r,n,i){this._forEachCell(e,r,n,i,this._insertBoxCell,this.boxUid++),this.boxKeys.push(t),this.bboxes.push(e),this.bboxes.push(r),this.bboxes.push(n),this.bboxes.push(i)},Kt.prototype.insertCircle=function(t,e,r,n){this._forEachCell(e-n,r-n,e+n,r+n,this._insertCircleCell,this.circleUid++),this.circleKeys.push(t),this.circles.push(e),this.circles.push(r),this.circles.push(n)},Kt.prototype._insertBoxCell=function(t,e,r,n,i,a){this.boxCells[i].push(a)},Kt.prototype._insertCircleCell=function(t,e,r,n,i,a){this.circleCells[i].push(a)},Kt.prototype._query=function(t,e,r,n,i,a){if(r<0||t>this.width||n<0||e>this.height)return!i&&[];var o=[];if(t<=0&&e<=0&&this.width<=r&&this.height<=n){if(i)return!0;for(var s=0;s<this.boxKeys.length;s++)o.push({key:this.boxKeys[s],x1:this.bboxes[4*s],y1:this.bboxes[4*s+1],x2:this.bboxes[4*s+2],y2:this.bboxes[4*s+3]});for(var l=0;l<this.circleKeys.length;l++){var c=this.circles[3*l],u=this.circles[3*l+1],f=this.circles[3*l+2];o.push({key:this.circleKeys[l],x1:c-f,y1:u-f,x2:c+f,y2:u+f})}return a?o.filter(a):o}var h={hitTest:i,seenUids:{box:{},circle:{}}};return this._forEachCell(t,e,r,n,this._queryCell,o,h,a),i?o.length>0:o},Kt.prototype._queryCircle=function(t,e,r,n,i){var a=t-r,o=t+r,s=e-r,l=e+r;if(o<0||a>this.width||l<0||s>this.height)return!n&&[];var c=[],u={hitTest:n,circle:{x:t,y:e,radius:r},seenUids:{box:{},circle:{}}};return this._forEachCell(a,s,o,l,this._queryCellCircle,c,u,i),n?c.length>0:c},Kt.prototype.query=function(t,e,r,n,i){return this._query(t,e,r,n,!1,i)},Kt.prototype.hitTest=function(t,e,r,n,i){return this._query(t,e,r,n,!0,i)},Kt.prototype.hitTestCircle=function(t,e,r,n){return this._queryCircle(t,e,r,!0,n)},Kt.prototype._queryCell=function(t,e,r,n,i,a,o,s){var l=o.seenUids,c=this.boxCells[i];if(null!==c)for(var u=this.bboxes,f=0,h=c;f<h.length;f+=1){var p=h[f];if(!l.box[p]){l.box[p]=!0;var d=4*p;if(t<=u[d+2]&&e<=u[d+3]&&r>=u[d+0]&&n>=u[d+1]&&(!s||s(this.boxKeys[p]))){if(o.hitTest)return a.push(!0),!0;a.push({key:this.boxKeys[p],x1:u[d],y1:u[d+1],x2:u[d+2],y2:u[d+3]})}}}var g=this.circleCells[i];if(null!==g)for(var m=this.circles,v=0,y=g;v<y.length;v+=1){var x=y[v];if(!l.circle[x]){l.circle[x]=!0;var b=3*x;if(this._circleAndRectCollide(m[b],m[b+1],m[b+2],t,e,r,n)&&(!s||s(this.circleKeys[x]))){if(o.hitTest)return a.push(!0),!0;var _=m[b],w=m[b+1],T=m[b+2];a.push({key:this.circleKeys[x],x1:_-T,y1:w-T,x2:_+T,y2:w+T})}}}},Kt.prototype._queryCellCircle=function(t,e,r,n,i,a,o,s){var l=o.circle,c=o.seenUids,u=this.boxCells[i];if(null!==u)for(var f=this.bboxes,h=0,p=u;h<p.length;h+=1){var d=p[h];if(!c.box[d]){c.box[d]=!0;var g=4*d;if(this._circleAndRectCollide(l.x,l.y,l.radius,f[g+0],f[g+1],f[g+2],f[g+3])&&(!s||s(this.boxKeys[d])))return a.push(!0),!0}}var m=this.circleCells[i];if(null!==m)for(var v=this.circles,y=0,x=m;y<x.length;y+=1){var b=x[y];if(!c.circle[b]){c.circle[b]=!0;var _=3*b;if(this._circlesCollide(v[_],v[_+1],v[_+2],l.x,l.y,l.radius)&&(!s||s(this.circleKeys[b])))return a.push(!0),!0}}},Kt.prototype._forEachCell=function(t,e,r,n,i,a,o,s){for(var l=this._convertToXCellCoord(t),c=this._convertToYCellCoord(e),u=this._convertToXCellCoord(r),f=this._convertToYCellCoord(n),h=l;h<=u;h++)for(var p=c;p<=f;p++){var d=this.xCellCount*p+h;if(i.call(this,t,e,r,n,d,a,o,s))return}},Kt.prototype._convertToXCellCoord=function(t){return Math.max(0,Math.min(this.xCellCount-1,Math.floor(t*this.xScale)))},Kt.prototype._convertToYCellCoord=function(t){return Math.max(0,Math.min(this.yCellCount-1,Math.floor(t*this.yScale)))},Kt.prototype._circlesCollide=function(t,e,r,n,i,a){var o=n-t,s=i-e,l=r+a;return l*l>o*o+s*s},Kt.prototype._circleAndRectCollide=function(t,e,r,n,i,a,o){var s=(a-n)/2,l=Math.abs(t-(n+s));if(l>s+r)return!1;var c=(o-i)/2,u=Math.abs(e-(i+c));if(u>c+r)return!1;if(l<=s||u<=c)return!0;var f=l-s,h=u-c;return f*f+h*h<=r*r};var ce=new Float32Array([-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0]);function ue(t,e){for(var r=0;r<t;r++){var n=e.length;e.resize(n+4),e.float32.set(ce,3*n)}}function fe(t,e,r){var n=e[0],i=e[1];return t[0]=r[0]*n+r[4]*i+r[12],t[1]=r[1]*n+r[5]*i+r[13],t[3]=r[3]*n+r[7]*i+r[15],t}var he=function(t,e,r){void 0===e&&(e=new Kt(t.width+200,t.height+200,25)),void 0===r&&(r=new Kt(t.width+200,t.height+200,25)),this.transform=t,this.grid=e,this.ignoredGrid=r,this.pitchfactor=Math.cos(t._pitch)*t.cameraToCenterDistance,this.screenRightBoundary=t.width+100,this.screenBottomBoundary=t.height+100,this.gridRightBoundary=t.width+200,this.gridBottomBoundary=t.height+200};function pe(e,r,n){return r*(t.EXTENT/(e.tileSize*Math.pow(2,n-e.tileID.overscaledZ)))}he.prototype.placeCollisionBox=function(t,e,r,n,i){var a=this.projectAndGetPerspectiveRatio(n,t.anchorPointX,t.anchorPointY),o=r*a.perspectiveRatio,s=t.x1*o+a.point.x,l=t.y1*o+a.point.y,c=t.x2*o+a.point.x,u=t.y2*o+a.point.y;return!this.isInsideGrid(s,l,c,u)||!e&&this.grid.hitTest(s,l,c,u,i)?{box:[],offscreen:!1}:{box:[s,l,c,u],offscreen:this.isOffscreen(s,l,c,u)}},he.prototype.placeCollisionCircles=function(e,r,n,i,a,o,s,l,c,u,f,h,p){var d=[],g=new t.Point(r.anchorX,r.anchorY),m=te(g,o),v=ee(this.transform.cameraToCenterDistance,m.signedDistanceFromCamera),y=(u?a/v:a*v)/t.ONE_EM,x=te(g,s).point,b=ie(y,i,r.lineOffsetX*y,r.lineOffsetY*y,!1,x,g,r,n,s,{}),_=!1,w=!1,T=!0;if(b){for(var k=.5*h*v+p,A=new t.Point(-100,-100),M=new t.Point(this.screenRightBoundary,this.screenBottomBoundary),S=new Jt,E=b.first,L=b.last,C=[],P=E.path.length-1;P>=1;P--)C.push(E.path[P]);for(var I=1;I<L.path.length;I++)C.push(L.path[I]);var O=2.5*k;if(l){var z=C.map((function(t){return te(t,l)}));C=z.some((function(t){return t.signedDistanceFromCamera<=0}))?[]:z.map((function(t){return t.point}))}var D=[];if(C.length>0){for(var R=C[0].clone(),F=C[0].clone(),B=1;B<C.length;B++)R.x=Math.min(R.x,C[B].x),R.y=Math.min(R.y,C[B].y),F.x=Math.max(F.x,C[B].x),F.y=Math.max(F.y,C[B].y);D=R.x>=A.x&&F.x<=M.x&&R.y>=A.y&&F.y<=M.y?[C]:F.x<A.x||R.x>M.x||F.y<A.y||R.y>M.y?[]:t.clipLine([C],A.x,A.y,M.x,M.y)}for(var N=0,j=D;N<j.length;N+=1){var U=j[N];S.reset(U,.25*k);var V=0;V=S.length<=.5*k?1:Math.ceil(S.paddedLength/O)+1;for(var q=0;q<V;q++){var H=q/Math.max(V-1,1),G=S.lerp(H),Y=G.x+100,W=G.y+100;d.push(Y,W,k,0);var X=Y-k,Z=W-k,J=Y+k,K=W+k;if(T=T&&this.isOffscreen(X,Z,J,K),w=w||this.isInsideGrid(X,Z,J,K),!e&&this.grid.hitTestCircle(Y,W,k,f)&&(_=!0,!c))return{circles:[],offscreen:!1,collisionDetected:_}}}}return{circles:!c&&_||!w?[]:d,offscreen:T,collisionDetected:_}},he.prototype.queryRenderedSymbols=function(e){if(0===e.length||0===this.grid.keysLength()&&0===this.ignoredGrid.keysLength())return{};for(var r=[],n=1/0,i=1/0,a=-1/0,o=-1/0,s=0,l=e;s<l.length;s+=1){var c=l[s],u=new t.Point(c.x+100,c.y+100);n=Math.min(n,u.x),i=Math.min(i,u.y),a=Math.max(a,u.x),o=Math.max(o,u.y),r.push(u)}for(var f={},h={},p=0,d=this.grid.query(n,i,a,o).concat(this.ignoredGrid.query(n,i,a,o));p<d.length;p+=1){var g=d[p],m=g.key;if(void 0===f[m.bucketInstanceId]&&(f[m.bucketInstanceId]={}),!f[m.bucketInstanceId][m.featureIndex]){var v=[new t.Point(g.x1,g.y1),new t.Point(g.x2,g.y1),new t.Point(g.x2,g.y2),new t.Point(g.x1,g.y2)];t.polygonIntersectsPolygon(r,v)&&(f[m.bucketInstanceId][m.featureIndex]=!0,void 0===h[m.bucketInstanceId]&&(h[m.bucketInstanceId]=[]),h[m.bucketInstanceId].push(m.featureIndex))}}return h},he.prototype.insertCollisionBox=function(t,e,r,n,i){var a={bucketInstanceId:r,featureIndex:n,collisionGroupID:i};(e?this.ignoredGrid:this.grid).insert(a,t[0],t[1],t[2],t[3])},he.prototype.insertCollisionCircles=function(t,e,r,n,i){for(var a=e?this.ignoredGrid:this.grid,o={bucketInstanceId:r,featureIndex:n,collisionGroupID:i},s=0;s<t.length;s+=4)a.insertCircle(o,t[s],t[s+1],t[s+2])},he.prototype.projectAndGetPerspectiveRatio=function(e,r,n){var i=[r,n,0,1];return fe(i,i,e),{point:new t.Point((i[0]/i[3]+1)/2*this.transform.width+100,(-i[1]/i[3]+1)/2*this.transform.height+100),perspectiveRatio:.5+this.transform.cameraToCenterDistance/i[3]*.5}},he.prototype.isOffscreen=function(t,e,r,n){return r<100||t>=this.screenRightBoundary||n<100||e>this.screenBottomBoundary},he.prototype.isInsideGrid=function(t,e,r,n){return r>=0&&t<this.gridRightBoundary&&n>=0&&e<this.gridBottomBoundary},he.prototype.getViewportMatrix=function(){var e=t.identity([]);return t.translate(e,e,[-100,-100,0]),e};var de=function(t,e,r,n){this.opacity=t?Math.max(0,Math.min(1,t.opacity+(t.placed?e:-e))):n&&r?1:0,this.placed=r};de.prototype.isHidden=function(){return 0===this.opacity&&!this.placed};var ge=function(t,e,r,n,i){this.text=new de(t?t.text:null,e,r,i),this.icon=new de(t?t.icon:null,e,n,i)};ge.prototype.isHidden=function(){return this.text.isHidden()&&this.icon.isHidden()};var me=function(t,e,r){this.text=t,this.icon=e,this.skipFade=r},ve=function(){this.invProjMatrix=t.create(),this.viewportMatrix=t.create(),this.circles=[]},ye=function(t,e,r,n,i){this.bucketInstanceId=t,this.featureIndex=e,this.sourceLayerIndex=r,this.bucketIndex=n,this.tileID=i},xe=function(t){this.crossSourceCollisions=t,this.maxGroupID=0,this.collisionGroups={}};function be(e,r,n,i,a){var o=t.getAnchorAlignment(e),s=-(o.horizontalAlign-.5)*r,l=-(o.verticalAlign-.5)*n,c=t.evaluateVariableOffset(e,i);return new t.Point(s+c[0]*a,l+c[1]*a)}function _e(e,r,n,i,a,o){var s=e.x1,l=e.x2,c=e.y1,u=e.y2,f=e.anchorPointX,h=e.anchorPointY,p=new t.Point(r,n);return i&&p._rotate(a?o:-o),{x1:s+p.x,y1:c+p.y,x2:l+p.x,y2:u+p.y,anchorPointX:f,anchorPointY:h}}xe.prototype.get=function(t){if(this.crossSourceCollisions)return{ID:0,predicate:null};if(!this.collisionGroups[t]){var e=++this.maxGroupID;this.collisionGroups[t]={ID:e,predicate:function(t){return t.collisionGroupID===e}}}return this.collisionGroups[t]};var we=function(t,e,r,n){this.transform=t.clone(),this.collisionIndex=new he(this.transform),this.placements={},this.opacities={},this.variableOffsets={},this.stale=!1,this.commitTime=0,this.fadeDuration=e,this.retainedQueryData={},this.collisionGroups=new xe(r),this.collisionCircleArrays={},this.prevPlacement=n,n&&(n.prevPlacement=void 0),this.placedOrientations={}};function Te(t,e,r,n,i){t.emplaceBack(e?1:0,r?1:0,n||0,i||0),t.emplaceBack(e?1:0,r?1:0,n||0,i||0),t.emplaceBack(e?1:0,r?1:0,n||0,i||0),t.emplaceBack(e?1:0,r?1:0,n||0,i||0)}we.prototype.getBucketParts=function(e,r,n,i){var a=n.getBucket(r),o=n.latestFeatureIndex;if(a&&o&&r.id===a.layerIds[0]){var s=n.collisionBoxArray,l=a.layers[0].layout,c=Math.pow(2,this.transform.zoom-n.tileID.overscaledZ),u=n.tileSize/t.EXTENT,f=this.transform.calculatePosMatrix(n.tileID.toUnwrapped()),h=\"map\"===l.get(\"text-pitch-alignment\"),p=\"map\"===l.get(\"text-rotation-alignment\"),d=pe(n,1,this.transform.zoom),g=Qt(f,h,p,this.transform,d),m=null;if(h){var v=$t(f,h,p,this.transform,d);m=t.multiply([],this.transform.labelPlaneMatrix,v)}this.retainedQueryData[a.bucketInstanceId]=new ye(a.bucketInstanceId,o,a.sourceLayerIndex,a.index,n.tileID);var y={bucket:a,layout:l,posMatrix:f,textLabelPlaneMatrix:g,labelToScreenMatrix:m,scale:c,textPixelRatio:u,holdingForFade:n.holdingForFade(),collisionBoxArray:s,partiallyEvaluatedTextSize:t.evaluateSizeForZoom(a.textSizeData,this.transform.zoom),collisionGroup:this.collisionGroups.get(a.sourceID)};if(i)for(var x=0,b=a.sortKeyRanges;x<b.length;x+=1){var _=b[x],w=_.sortKey,T=_.symbolInstanceStart,k=_.symbolInstanceEnd;e.push({sortKey:w,symbolInstanceStart:T,symbolInstanceEnd:k,parameters:y})}else e.push({symbolInstanceStart:0,symbolInstanceEnd:a.symbolInstances.length,parameters:y})}},we.prototype.attemptAnchorPlacement=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d){var g,m=[f.textOffset0,f.textOffset1],v=be(t,r,n,m,i),y=this.collisionIndex.placeCollisionBox(_e(e,v.x,v.y,a,o,this.transform.angle),u,s,l,c.predicate);if(d&&0===this.collisionIndex.placeCollisionBox(_e(d,v.x,v.y,a,o,this.transform.angle),u,s,l,c.predicate).box.length)return;if(y.box.length>0)return this.prevPlacement&&this.prevPlacement.variableOffsets[f.crossTileID]&&this.prevPlacement.placements[f.crossTileID]&&this.prevPlacement.placements[f.crossTileID].text&&(g=this.prevPlacement.variableOffsets[f.crossTileID].anchor),this.variableOffsets[f.crossTileID]={textOffset:m,width:r,height:n,anchor:t,textBoxScale:i,prevAnchor:g},this.markUsedJustification(h,t,f,p),h.allowVerticalPlacement&&(this.markUsedOrientation(h,p,f),this.placedOrientations[f.crossTileID]=p),{shift:v,placedGlyphBoxes:y}},we.prototype.placeLayerBucketPart=function(e,r,n){var i=this,a=e.parameters,o=a.bucket,s=a.layout,l=a.posMatrix,c=a.textLabelPlaneMatrix,u=a.labelToScreenMatrix,f=a.textPixelRatio,h=a.holdingForFade,p=a.collisionBoxArray,d=a.partiallyEvaluatedTextSize,g=a.collisionGroup,m=s.get(\"text-optional\"),v=s.get(\"icon-optional\"),y=s.get(\"text-allow-overlap\"),x=s.get(\"icon-allow-overlap\"),b=\"map\"===s.get(\"text-rotation-alignment\"),_=\"map\"===s.get(\"text-pitch-alignment\"),w=\"none\"!==s.get(\"icon-text-fit\"),T=\"viewport-y\"===s.get(\"symbol-z-order\"),k=y&&(x||!o.hasIconData()||v),A=x&&(y||!o.hasTextData()||m);!o.collisionArrays&&p&&o.deserializeCollisionBoxes(p);var M=function(e,a){if(!r[e.crossTileID])if(h)i.placements[e.crossTileID]=new me(!1,!1,!1);else{var p,T=!1,M=!1,S=!0,E=null,L={box:null,offscreen:null},C={box:null,offscreen:null},P=null,I=null,O=0,z=0,D=0;a.textFeatureIndex?O=a.textFeatureIndex:e.useRuntimeCollisionCircles&&(O=e.featureIndex),a.verticalTextFeatureIndex&&(z=a.verticalTextFeatureIndex);var R=a.textBox;if(R){var F=function(r){var n=t.WritingMode.horizontal;if(o.allowVerticalPlacement&&!r&&i.prevPlacement){var a=i.prevPlacement.placedOrientations[e.crossTileID];a&&(i.placedOrientations[e.crossTileID]=a,n=a,i.markUsedOrientation(o,n,e))}return n},B=function(r,n){if(o.allowVerticalPlacement&&e.numVerticalGlyphVertices>0&&a.verticalTextBox)for(var i=0,s=o.writingModes;i<s.length;i+=1){if(s[i]===t.WritingMode.vertical?(L=n(),C=L):L=r(),L&&L.box&&L.box.length)break}else L=r()};if(s.get(\"text-variable-anchor\")){var N=s.get(\"text-variable-anchor\");if(i.prevPlacement&&i.prevPlacement.variableOffsets[e.crossTileID]){var j=i.prevPlacement.variableOffsets[e.crossTileID];N.indexOf(j.anchor)>0&&(N=N.filter((function(t){return t!==j.anchor}))).unshift(j.anchor)}var U=function(t,r,n){for(var a=t.x2-t.x1,s=t.y2-t.y1,c=e.textBoxScale,u=w&&!x?r:null,h={box:[],offscreen:!1},p=y?2*N.length:N.length,d=0;d<p;++d){var m=N[d%N.length],v=d>=N.length,k=i.attemptAnchorPlacement(m,t,a,s,c,b,_,f,l,g,v,e,o,n,u);if(k&&(h=k.placedGlyphBoxes)&&h.box&&h.box.length){T=!0,E=k.shift;break}}return h};B((function(){return U(R,a.iconBox,t.WritingMode.horizontal)}),(function(){var r=a.verticalTextBox,n=L&&L.box&&L.box.length;return o.allowVerticalPlacement&&!n&&e.numVerticalGlyphVertices>0&&r?U(r,a.verticalIconBox,t.WritingMode.vertical):{box:null,offscreen:null}})),L&&(T=L.box,S=L.offscreen);var V=F(L&&L.box);if(!T&&i.prevPlacement){var q=i.prevPlacement.variableOffsets[e.crossTileID];q&&(i.variableOffsets[e.crossTileID]=q,i.markUsedJustification(o,q.anchor,e,V))}}else{var H=function(t,r){var n=i.collisionIndex.placeCollisionBox(t,y,f,l,g.predicate);return n&&n.box&&n.box.length&&(i.markUsedOrientation(o,r,e),i.placedOrientations[e.crossTileID]=r),n};B((function(){return H(R,t.WritingMode.horizontal)}),(function(){var r=a.verticalTextBox;return o.allowVerticalPlacement&&e.numVerticalGlyphVertices>0&&r?H(r,t.WritingMode.vertical):{box:null,offscreen:null}})),F(L&&L.box&&L.box.length)}}if(T=(p=L)&&p.box&&p.box.length>0,S=p&&p.offscreen,e.useRuntimeCollisionCircles){var G=o.text.placedSymbolArray.get(e.centerJustifiedTextSymbolIndex),Y=t.evaluateSizeForFeature(o.textSizeData,d,G),W=s.get(\"text-padding\"),X=e.collisionCircleDiameter;P=i.collisionIndex.placeCollisionCircles(y,G,o.lineVertexArray,o.glyphOffsetArray,Y,l,c,u,n,_,g.predicate,X,W),T=y||P.circles.length>0&&!P.collisionDetected,S=S&&P.offscreen}if(a.iconFeatureIndex&&(D=a.iconFeatureIndex),a.iconBox){var Z=function(t){var e=w&&E?_e(t,E.x,E.y,b,_,i.transform.angle):t;return i.collisionIndex.placeCollisionBox(e,x,f,l,g.predicate)};M=C&&C.box&&C.box.length&&a.verticalIconBox?(I=Z(a.verticalIconBox)).box.length>0:(I=Z(a.iconBox)).box.length>0,S=S&&I.offscreen}var J=m||0===e.numHorizontalGlyphVertices&&0===e.numVerticalGlyphVertices,K=v||0===e.numIconVertices;if(J||K?K?J||(M=M&&T):T=M&&T:M=T=M&&T,T&&p&&p.box&&(C&&C.box&&z?i.collisionIndex.insertCollisionBox(p.box,s.get(\"text-ignore-placement\"),o.bucketInstanceId,z,g.ID):i.collisionIndex.insertCollisionBox(p.box,s.get(\"text-ignore-placement\"),o.bucketInstanceId,O,g.ID)),M&&I&&i.collisionIndex.insertCollisionBox(I.box,s.get(\"icon-ignore-placement\"),o.bucketInstanceId,D,g.ID),P&&(T&&i.collisionIndex.insertCollisionCircles(P.circles,s.get(\"text-ignore-placement\"),o.bucketInstanceId,O,g.ID),n)){var Q=o.bucketInstanceId,$=i.collisionCircleArrays[Q];void 0===$&&($=i.collisionCircleArrays[Q]=new ve);for(var tt=0;tt<P.circles.length;tt+=4)$.circles.push(P.circles[tt+0]),$.circles.push(P.circles[tt+1]),$.circles.push(P.circles[tt+2]),$.circles.push(P.collisionDetected?1:0)}i.placements[e.crossTileID]=new me(T||k,M||A,S||o.justReloaded),r[e.crossTileID]=!0}};if(T)for(var S=o.getSortedSymbolIndexes(this.transform.angle),E=S.length-1;E>=0;--E){var L=S[E];M(o.symbolInstances.get(L),o.collisionArrays[L])}else for(var C=e.symbolInstanceStart;C<e.symbolInstanceEnd;C++)M(o.symbolInstances.get(C),o.collisionArrays[C]);if(n&&o.bucketInstanceId in this.collisionCircleArrays){var P=this.collisionCircleArrays[o.bucketInstanceId];t.invert(P.invProjMatrix,l),P.viewportMatrix=this.collisionIndex.getViewportMatrix()}o.justReloaded=!1},we.prototype.markUsedJustification=function(e,r,n,i){var a,o={left:n.leftJustifiedTextSymbolIndex,center:n.centerJustifiedTextSymbolIndex,right:n.rightJustifiedTextSymbolIndex};a=i===t.WritingMode.vertical?n.verticalPlacedTextSymbolIndex:o[t.getAnchorJustification(r)];for(var s=0,l=[n.leftJustifiedTextSymbolIndex,n.centerJustifiedTextSymbolIndex,n.rightJustifiedTextSymbolIndex,n.verticalPlacedTextSymbolIndex];s<l.length;s+=1){var c=l[s];c>=0&&(e.text.placedSymbolArray.get(c).crossTileID=a>=0&&c!==a?0:n.crossTileID)}},we.prototype.markUsedOrientation=function(e,r,n){for(var i=r===t.WritingMode.horizontal||r===t.WritingMode.horizontalOnly?r:0,a=r===t.WritingMode.vertical?r:0,o=0,s=[n.leftJustifiedTextSymbolIndex,n.centerJustifiedTextSymbolIndex,n.rightJustifiedTextSymbolIndex];o<s.length;o+=1){var l=s[o];e.text.placedSymbolArray.get(l).placedOrientation=i}n.verticalPlacedTextSymbolIndex&&(e.text.placedSymbolArray.get(n.verticalPlacedTextSymbolIndex).placedOrientation=a)},we.prototype.commit=function(t){this.commitTime=t,this.zoomAtLastRecencyCheck=this.transform.zoom;var e=this.prevPlacement,r=!1;this.prevZoomAdjustment=e?e.zoomAdjustment(this.transform.zoom):0;var n=e?e.symbolFadeChange(t):1,i=e?e.opacities:{},a=e?e.variableOffsets:{},o=e?e.placedOrientations:{};for(var s in this.placements){var l=this.placements[s],c=i[s];c?(this.opacities[s]=new ge(c,n,l.text,l.icon),r=r||l.text!==c.text.placed||l.icon!==c.icon.placed):(this.opacities[s]=new ge(null,n,l.text,l.icon,l.skipFade),r=r||l.text||l.icon)}for(var u in i){var f=i[u];if(!this.opacities[u]){var h=new ge(f,n,!1,!1);h.isHidden()||(this.opacities[u]=h,r=r||f.text.placed||f.icon.placed)}}for(var p in a)this.variableOffsets[p]||!this.opacities[p]||this.opacities[p].isHidden()||(this.variableOffsets[p]=a[p]);for(var d in o)this.placedOrientations[d]||!this.opacities[d]||this.opacities[d].isHidden()||(this.placedOrientations[d]=o[d]);r?this.lastPlacementChangeTime=t:\"number\"!=typeof this.lastPlacementChangeTime&&(this.lastPlacementChangeTime=e?e.lastPlacementChangeTime:t)},we.prototype.updateLayerOpacities=function(t,e){for(var r={},n=0,i=e;n<i.length;n+=1){var a=i[n],o=a.getBucket(t);o&&a.latestFeatureIndex&&t.id===o.layerIds[0]&&this.updateBucketOpacities(o,r,a.collisionBoxArray)}},we.prototype.updateBucketOpacities=function(e,r,n){var i=this;e.hasTextData()&&e.text.opacityVertexArray.clear(),e.hasIconData()&&e.icon.opacityVertexArray.clear(),e.hasIconCollisionBoxData()&&e.iconCollisionBox.collisionVertexArray.clear(),e.hasTextCollisionBoxData()&&e.textCollisionBox.collisionVertexArray.clear();var a=e.layers[0].layout,o=new ge(null,0,!1,!1,!0),s=a.get(\"text-allow-overlap\"),l=a.get(\"icon-allow-overlap\"),c=a.get(\"text-variable-anchor\"),u=\"map\"===a.get(\"text-rotation-alignment\"),f=\"map\"===a.get(\"text-pitch-alignment\"),h=\"none\"!==a.get(\"icon-text-fit\"),p=new ge(null,0,s&&(l||!e.hasIconData()||a.get(\"icon-optional\")),l&&(s||!e.hasTextData()||a.get(\"text-optional\")),!0);!e.collisionArrays&&n&&(e.hasIconCollisionBoxData()||e.hasTextCollisionBoxData())&&e.deserializeCollisionBoxes(n);for(var d=function(t,e,r){for(var n=0;n<e/4;n++)t.opacityVertexArray.emplaceBack(r)},g=function(n){var a=e.symbolInstances.get(n),s=a.numHorizontalGlyphVertices,l=a.numVerticalGlyphVertices,g=a.crossTileID,m=r[g],v=i.opacities[g];m?v=o:v||(v=p,i.opacities[g]=v),r[g]=!0;var y=s>0||l>0,x=a.numIconVertices>0,b=i.placedOrientations[a.crossTileID],_=b===t.WritingMode.vertical,w=b===t.WritingMode.horizontal||b===t.WritingMode.horizontalOnly;if(y){var T=Pe(v.text),k=_?Ie:T;d(e.text,s,k);var A=w?Ie:T;d(e.text,l,A);var M=v.text.isHidden();[a.rightJustifiedTextSymbolIndex,a.centerJustifiedTextSymbolIndex,a.leftJustifiedTextSymbolIndex].forEach((function(t){t>=0&&(e.text.placedSymbolArray.get(t).hidden=M||_?1:0)})),a.verticalPlacedTextSymbolIndex>=0&&(e.text.placedSymbolArray.get(a.verticalPlacedTextSymbolIndex).hidden=M||w?1:0);var S=i.variableOffsets[a.crossTileID];S&&i.markUsedJustification(e,S.anchor,a,b);var E=i.placedOrientations[a.crossTileID];E&&(i.markUsedJustification(e,\"left\",a,E),i.markUsedOrientation(e,E,a))}if(x){var L=Pe(v.icon),C=!(h&&a.verticalPlacedIconSymbolIndex&&_);if(a.placedIconSymbolIndex>=0){var P=C?L:Ie;d(e.icon,a.numIconVertices,P),e.icon.placedSymbolArray.get(a.placedIconSymbolIndex).hidden=v.icon.isHidden()}if(a.verticalPlacedIconSymbolIndex>=0){var I=C?Ie:L;d(e.icon,a.numVerticalIconVertices,I),e.icon.placedSymbolArray.get(a.verticalPlacedIconSymbolIndex).hidden=v.icon.isHidden()}}if(e.hasIconCollisionBoxData()||e.hasTextCollisionBoxData()){var O=e.collisionArrays[n];if(O){var z=new t.Point(0,0);if(O.textBox||O.verticalTextBox){var D=!0;if(c){var R=i.variableOffsets[g];R?(z=be(R.anchor,R.width,R.height,R.textOffset,R.textBoxScale),u&&z._rotate(f?i.transform.angle:-i.transform.angle)):D=!1}O.textBox&&Te(e.textCollisionBox.collisionVertexArray,v.text.placed,!D||_,z.x,z.y),O.verticalTextBox&&Te(e.textCollisionBox.collisionVertexArray,v.text.placed,!D||w,z.x,z.y)}var F=Boolean(!w&&O.verticalIconBox);O.iconBox&&Te(e.iconCollisionBox.collisionVertexArray,v.icon.placed,F,h?z.x:0,h?z.y:0),O.verticalIconBox&&Te(e.iconCollisionBox.collisionVertexArray,v.icon.placed,!F,h?z.x:0,h?z.y:0)}}},m=0;m<e.symbolInstances.length;m++)g(m);if(e.sortFeatures(this.transform.angle),this.retainedQueryData[e.bucketInstanceId]&&(this.retainedQueryData[e.bucketInstanceId].featureSortOrder=e.featureSortOrder),e.hasTextData()&&e.text.opacityVertexBuffer&&e.text.opacityVertexBuffer.updateData(e.text.opacityVertexArray),e.hasIconData()&&e.icon.opacityVertexBuffer&&e.icon.opacityVertexBuffer.updateData(e.icon.opacityVertexArray),e.hasIconCollisionBoxData()&&e.iconCollisionBox.collisionVertexBuffer&&e.iconCollisionBox.collisionVertexBuffer.updateData(e.iconCollisionBox.collisionVertexArray),e.hasTextCollisionBoxData()&&e.textCollisionBox.collisionVertexBuffer&&e.textCollisionBox.collisionVertexBuffer.updateData(e.textCollisionBox.collisionVertexArray),e.bucketInstanceId in this.collisionCircleArrays){var v=this.collisionCircleArrays[e.bucketInstanceId];e.placementInvProjMatrix=v.invProjMatrix,e.placementViewportMatrix=v.viewportMatrix,e.collisionCircleArray=v.circles,delete this.collisionCircleArrays[e.bucketInstanceId]}},we.prototype.symbolFadeChange=function(t){return 0===this.fadeDuration?1:(t-this.commitTime)/this.fadeDuration+this.prevZoomAdjustment},we.prototype.zoomAdjustment=function(t){return Math.max(0,(this.transform.zoom-t)/1.5)},we.prototype.hasTransitions=function(t){return this.stale||t-this.lastPlacementChangeTime<this.fadeDuration},we.prototype.stillRecent=function(t,e){var r=this.zoomAtLastRecencyCheck===e?1-this.zoomAdjustment(e):1;return this.zoomAtLastRecencyCheck=e,this.commitTime+this.fadeDuration*r>t},we.prototype.setStale=function(){this.stale=!0};var ke=Math.pow(2,25),Ae=Math.pow(2,24),Me=Math.pow(2,17),Se=Math.pow(2,16),Ee=Math.pow(2,9),Le=Math.pow(2,8),Ce=Math.pow(2,1);function Pe(t){if(0===t.opacity&&!t.placed)return 0;if(1===t.opacity&&t.placed)return 4294967295;var e=t.placed?1:0,r=Math.floor(127*t.opacity);return r*ke+e*Ae+r*Me+e*Se+r*Ee+e*Le+r*Ce+e}var Ie=0,Oe=function(t){this._sortAcrossTiles=\"viewport-y\"!==t.layout.get(\"symbol-z-order\")&&void 0!==t.layout.get(\"symbol-sort-key\").constantOr(1),this._currentTileIndex=0,this._currentPartIndex=0,this._seenCrossTileIDs={},this._bucketParts=[]};Oe.prototype.continuePlacement=function(t,e,r,n,i){for(var a=this._bucketParts;this._currentTileIndex<t.length;){var o=t[this._currentTileIndex];if(e.getBucketParts(a,n,o,this._sortAcrossTiles),this._currentTileIndex++,i())return!0}for(this._sortAcrossTiles&&(this._sortAcrossTiles=!1,a.sort((function(t,e){return t.sortKey-e.sortKey})));this._currentPartIndex<a.length;){var s=a[this._currentPartIndex];if(e.placeLayerBucketPart(s,this._seenCrossTileIDs,r),this._currentPartIndex++,i())return!0}return!1};var ze=function(t,e,r,n,i,a,o){this.placement=new we(t,i,a,o),this._currentPlacementIndex=e.length-1,this._forceFullPlacement=r,this._showCollisionBoxes=n,this._done=!1};ze.prototype.isDone=function(){return this._done},ze.prototype.continuePlacement=function(e,r,n){for(var i=this,a=t.browser.now(),o=function(){var e=t.browser.now()-a;return!i._forceFullPlacement&&e>2};this._currentPlacementIndex>=0;){var s=r[e[this._currentPlacementIndex]],l=this.placement.collisionIndex.transform.zoom;if(\"symbol\"===s.type&&(!s.minzoom||s.minzoom<=l)&&(!s.maxzoom||s.maxzoom>l)){if(this._inProgressLayer||(this._inProgressLayer=new Oe(s)),this._inProgressLayer.continuePlacement(n[s.source],this.placement,this._showCollisionBoxes,s,o))return;delete this._inProgressLayer}this._currentPlacementIndex--}this._done=!0},ze.prototype.commit=function(t){return this.placement.commit(t),this.placement};var De=512/t.EXTENT/2,Re=function(t,e,r){this.tileID=t,this.indexedSymbolInstances={},this.bucketInstanceId=r;for(var n=0;n<e.length;n++){var i=e.get(n),a=i.key;this.indexedSymbolInstances[a]||(this.indexedSymbolInstances[a]=[]),this.indexedSymbolInstances[a].push({crossTileID:i.crossTileID,coord:this.getScaledCoordinates(i,t)})}};Re.prototype.getScaledCoordinates=function(e,r){var n=r.canonical.z-this.tileID.canonical.z,i=De/Math.pow(2,n);return{x:Math.floor((r.canonical.x*t.EXTENT+e.anchorX)*i),y:Math.floor((r.canonical.y*t.EXTENT+e.anchorY)*i)}},Re.prototype.findMatches=function(t,e,r){for(var n=this.tileID.canonical.z<e.canonical.z?1:Math.pow(2,this.tileID.canonical.z-e.canonical.z),i=0;i<t.length;i++){var a=t.get(i);if(!a.crossTileID){var o=this.indexedSymbolInstances[a.key];if(o)for(var s=this.getScaledCoordinates(a,e),l=0,c=o;l<c.length;l+=1){var u=c[l];if(Math.abs(u.coord.x-s.x)<=n&&Math.abs(u.coord.y-s.y)<=n&&!r[u.crossTileID]){r[u.crossTileID]=!0,a.crossTileID=u.crossTileID;break}}}}};var Fe=function(){this.maxCrossTileID=0};Fe.prototype.generate=function(){return++this.maxCrossTileID};var Be=function(){this.indexes={},this.usedCrossTileIDs={},this.lng=0};Be.prototype.handleWrapJump=function(t){var e=Math.round((t-this.lng)/360);if(0!==e)for(var r in this.indexes){var n=this.indexes[r],i={};for(var a in n){var o=n[a];o.tileID=o.tileID.unwrapTo(o.tileID.wrap+e),i[o.tileID.key]=o}this.indexes[r]=i}this.lng=t},Be.prototype.addBucket=function(t,e,r){if(this.indexes[t.overscaledZ]&&this.indexes[t.overscaledZ][t.key]){if(this.indexes[t.overscaledZ][t.key].bucketInstanceId===e.bucketInstanceId)return!1;this.removeBucketCrossTileIDs(t.overscaledZ,this.indexes[t.overscaledZ][t.key])}for(var n=0;n<e.symbolInstances.length;n++){e.symbolInstances.get(n).crossTileID=0}this.usedCrossTileIDs[t.overscaledZ]||(this.usedCrossTileIDs[t.overscaledZ]={});var i=this.usedCrossTileIDs[t.overscaledZ];for(var a in this.indexes){var o=this.indexes[a];if(Number(a)>t.overscaledZ)for(var s in o){var l=o[s];l.tileID.isChildOf(t)&&l.findMatches(e.symbolInstances,t,i)}else{var c=o[t.scaledTo(Number(a)).key];c&&c.findMatches(e.symbolInstances,t,i)}}for(var u=0;u<e.symbolInstances.length;u++){var f=e.symbolInstances.get(u);f.crossTileID||(f.crossTileID=r.generate(),i[f.crossTileID]=!0)}return void 0===this.indexes[t.overscaledZ]&&(this.indexes[t.overscaledZ]={}),this.indexes[t.overscaledZ][t.key]=new Re(t,e.symbolInstances,e.bucketInstanceId),!0},Be.prototype.removeBucketCrossTileIDs=function(t,e){for(var r in e.indexedSymbolInstances)for(var n=0,i=e.indexedSymbolInstances[r];n<i.length;n+=1){var a=i[n];delete this.usedCrossTileIDs[t][a.crossTileID]}},Be.prototype.removeStaleBuckets=function(t){var e=!1;for(var r in this.indexes){var n=this.indexes[r];for(var i in n)t[n[i].bucketInstanceId]||(this.removeBucketCrossTileIDs(r,n[i]),delete n[i],e=!0)}return e};var Ne=function(){this.layerIndexes={},this.crossTileIDs=new Fe,this.maxBucketInstanceId=0,this.bucketsInCurrentPlacement={}};Ne.prototype.addLayer=function(t,e,r){var n=this.layerIndexes[t.id];void 0===n&&(n=this.layerIndexes[t.id]=new Be);var i=!1,a={};n.handleWrapJump(r);for(var o=0,s=e;o<s.length;o+=1){var l=s[o],c=l.getBucket(t);c&&t.id===c.layerIds[0]&&(c.bucketInstanceId||(c.bucketInstanceId=++this.maxBucketInstanceId),n.addBucket(l.tileID,c,this.crossTileIDs)&&(i=!0),a[c.bucketInstanceId]=!0)}return n.removeStaleBuckets(a)&&(i=!0),i},Ne.prototype.pruneUnusedLayers=function(t){var e={};for(var r in t.forEach((function(t){e[t]=!0})),this.layerIndexes)e[r]||delete this.layerIndexes[r]};var je=function(e,r){return t.emitValidationErrors(e,r&&r.filter((function(t){return\"source.canvas\"!==t.identifier})))},Ue=t.pick(Ut,[\"addLayer\",\"removeLayer\",\"setPaintProperty\",\"setLayoutProperty\",\"setFilter\",\"addSource\",\"removeSource\",\"setLayerZoomRange\",\"setLight\",\"setTransition\",\"setGeoJSONSourceData\"]),Ve=t.pick(Ut,[\"setCenter\",\"setZoom\",\"setBearing\",\"setPitch\"]),qe=function(){var e={},r=t.styleSpec.$version;for(var n in t.styleSpec.$root){var i=t.styleSpec.$root[n];if(i.required){var a=null;null!=(a=\"version\"===n?r:\"array\"===i.type?[]:{})&&(e[n]=a)}}return e}(),He=function(e){function r(n,i){var a=this;void 0===i&&(i={}),e.call(this),this.map=n,this.dispatcher=new k(Bt(),this),this.imageManager=new h,this.imageManager.setEventedParent(this),this.glyphManager=new x(n._requestManager,i.localIdeographFontFamily),this.lineAtlas=new T(256,512),this.crossTileSymbolIndex=new Ne,this._layers={},this._serializedLayers={},this._order=[],this.sourceCaches={},this.zoomHistory=new t.ZoomHistory,this._loaded=!1,this._availableImages=[],this._resetUpdates(),this.dispatcher.broadcast(\"setReferrer\",t.getReferrer());var o=this;this._rtlTextPluginCallback=r.registerForPluginStateChange((function(e){var r={pluginStatus:e.pluginStatus,pluginURL:e.pluginURL};o.dispatcher.broadcast(\"syncRTLPluginState\",r,(function(e,r){if((t.triggerPluginCompletionEvent(e),r)&&r.every((function(t){return t})))for(var n in o.sourceCaches)o.sourceCaches[n].reload()}))})),this.on(\"data\",(function(t){if(\"source\"===t.dataType&&\"metadata\"===t.sourceDataType){var e=a.sourceCaches[t.sourceId];if(e){var r=e.getSource();if(r&&r.vectorLayerIds)for(var n in a._layers){var i=a._layers[n];i.source===r.id&&a._validateLayer(i)}}}}))}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.loadURL=function(e,r){var n=this;void 0===r&&(r={}),this.fire(new t.Event(\"dataloading\",{dataType:\"style\"}));var i=\"boolean\"==typeof r.validate?r.validate:!t.isMapboxURL(e);e=this.map._requestManager.normalizeStyleURL(e,r.accessToken);var a=this.map._requestManager.transformRequest(e,t.ResourceType.Style);this._request=t.getJSON(a,(function(e,r){n._request=null,e?n.fire(new t.ErrorEvent(e)):r&&n._load(r,i)}))},r.prototype.loadJSON=function(e,r){var n=this;void 0===r&&(r={}),this.fire(new t.Event(\"dataloading\",{dataType:\"style\"})),this._request=t.browser.frame((function(){n._request=null,n._load(e,!1!==r.validate)}))},r.prototype.loadEmpty=function(){this.fire(new t.Event(\"dataloading\",{dataType:\"style\"})),this._load(qe,!1)},r.prototype._load=function(e,r){if(!r||!je(this,t.validateStyle(e))){for(var n in this._loaded=!0,this.stylesheet=e,e.sources)this.addSource(n,e.sources[n],{validate:!1});e.sprite?this._loadSprite(e.sprite):this.imageManager.setLoaded(!0),this.glyphManager.setURL(e.glyphs);var i=jt(this.stylesheet.layers);this._order=i.map((function(t){return t.id})),this._layers={},this._serializedLayers={};for(var a=0,o=i;a<o.length;a+=1){var s=o[a];(s=t.createStyleLayer(s)).setEventedParent(this,{layer:{id:s.id}}),this._layers[s.id]=s,this._serializedLayers[s.id]=s.serialize()}this.dispatcher.broadcast(\"setLayers\",this._serializeLayers(this._order)),this.light=new w(this.stylesheet.light),this.fire(new t.Event(\"data\",{dataType:\"style\"})),this.fire(new t.Event(\"style.load\"))}},r.prototype._loadSprite=function(e){var r=this;this._spriteRequest=function(e,r,n){var i,a,o,s=t.browser.devicePixelRatio>1?\"@2x\":\"\",l=t.getJSON(r.transformRequest(r.normalizeSpriteURL(e,s,\".json\"),t.ResourceType.SpriteJSON),(function(t,e){l=null,o||(o=t,i=e,u())})),c=t.getImage(r.transformRequest(r.normalizeSpriteURL(e,s,\".png\"),t.ResourceType.SpriteImage),(function(t,e){c=null,o||(o=t,a=e,u())}));function u(){if(o)n(o);else if(i&&a){var e=t.browser.getImageData(a),r={};for(var s in i){var l=i[s],c=l.width,u=l.height,f=l.x,h=l.y,p=l.sdf,d=l.pixelRatio,g=l.stretchX,m=l.stretchY,v=l.content,y=new t.RGBAImage({width:c,height:u});t.RGBAImage.copy(e,y,{x:f,y:h},{x:0,y:0},{width:c,height:u}),r[s]={data:y,pixelRatio:d,sdf:p,stretchX:g,stretchY:m,content:v}}n(null,r)}}return{cancel:function(){l&&(l.cancel(),l=null),c&&(c.cancel(),c=null)}}}(e,this.map._requestManager,(function(e,n){if(r._spriteRequest=null,e)r.fire(new t.ErrorEvent(e));else if(n)for(var i in n)r.imageManager.addImage(i,n[i]);r.imageManager.setLoaded(!0),r._availableImages=r.imageManager.listImages(),r.dispatcher.broadcast(\"setImages\",r._availableImages),r.fire(new t.Event(\"data\",{dataType:\"style\"}))}))},r.prototype._validateLayer=function(e){var r=this.sourceCaches[e.source];if(r){var n=e.sourceLayer;if(n){var i=r.getSource();(\"geojson\"===i.type||i.vectorLayerIds&&-1===i.vectorLayerIds.indexOf(n))&&this.fire(new t.ErrorEvent(new Error('Source layer \"'+n+'\" does not exist on source \"'+i.id+'\" as specified by style layer \"'+e.id+'\"')))}}},r.prototype.loaded=function(){if(!this._loaded)return!1;if(Object.keys(this._updatedSources).length)return!1;for(var t in this.sourceCaches)if(!this.sourceCaches[t].loaded())return!1;return!!this.imageManager.isLoaded()},r.prototype._serializeLayers=function(t){for(var e=[],r=0,n=t;r<n.length;r+=1){var i=n[r],a=this._layers[i];\"custom\"!==a.type&&e.push(a.serialize())}return e},r.prototype.hasTransitions=function(){if(this.light&&this.light.hasTransition())return!0;for(var t in this.sourceCaches)if(this.sourceCaches[t].hasTransition())return!0;for(var e in this._layers)if(this._layers[e].hasTransition())return!0;return!1},r.prototype._checkLoaded=function(){if(!this._loaded)throw new Error(\"Style is not done loading\")},r.prototype.update=function(e){if(this._loaded){var r=this._changed;if(this._changed){var n=Object.keys(this._updatedLayers),i=Object.keys(this._removedLayers);for(var a in(n.length||i.length)&&this._updateWorkerLayers(n,i),this._updatedSources){var o=this._updatedSources[a];\"reload\"===o?this._reloadSource(a):\"clear\"===o&&this._clearSource(a)}for(var s in this._updateTilesForChangedImages(),this._updatedPaintProps)this._layers[s].updateTransitions(e);this.light.updateTransitions(e),this._resetUpdates()}for(var l in this.sourceCaches)this.sourceCaches[l].used=!1;for(var c=0,u=this._order;c<u.length;c+=1){var f=u[c],h=this._layers[f];h.recalculate(e,this._availableImages),!h.isHidden(e.zoom)&&h.source&&(this.sourceCaches[h.source].used=!0)}this.light.recalculate(e),this.z=e.zoom,r&&this.fire(new t.Event(\"data\",{dataType:\"style\"}))}},r.prototype._updateTilesForChangedImages=function(){var t=Object.keys(this._changedImages);if(t.length){for(var e in this.sourceCaches)this.sourceCaches[e].reloadTilesForDependencies([\"icons\",\"patterns\"],t);this._changedImages={}}},r.prototype._updateWorkerLayers=function(t,e){this.dispatcher.broadcast(\"updateLayers\",{layers:this._serializeLayers(t),removedIds:e})},r.prototype._resetUpdates=function(){this._changed=!1,this._updatedLayers={},this._removedLayers={},this._updatedSources={},this._updatedPaintProps={},this._changedImages={}},r.prototype.setState=function(e){var r=this;if(this._checkLoaded(),je(this,t.validateStyle(e)))return!1;(e=t.clone$1(e)).layers=jt(e.layers);var n=Zt(this.serialize(),e).filter((function(t){return!(t.command in Ve)}));if(0===n.length)return!1;var i=n.filter((function(t){return!(t.command in Ue)}));if(i.length>0)throw new Error(\"Unimplemented: \"+i.map((function(t){return t.command})).join(\", \")+\".\");return n.forEach((function(t){\"setTransition\"!==t.command&&r[t.command].apply(r,t.args)})),this.stylesheet=e,!0},r.prototype.addImage=function(e,r){if(this.getImage(e))return this.fire(new t.ErrorEvent(new Error(\"An image with this name already exists.\")));this.imageManager.addImage(e,r),this._availableImages=this.imageManager.listImages(),this._changedImages[e]=!0,this._changed=!0,this.fire(new t.Event(\"data\",{dataType:\"style\"}))},r.prototype.updateImage=function(t,e){this.imageManager.updateImage(t,e)},r.prototype.getImage=function(t){return this.imageManager.getImage(t)},r.prototype.removeImage=function(e){if(!this.getImage(e))return this.fire(new t.ErrorEvent(new Error(\"No image with this name exists.\")));this.imageManager.removeImage(e),this._availableImages=this.imageManager.listImages(),this._changedImages[e]=!0,this._changed=!0,this.fire(new t.Event(\"data\",{dataType:\"style\"}))},r.prototype.listImages=function(){return this._checkLoaded(),this.imageManager.listImages()},r.prototype.addSource=function(e,r,n){var i=this;if(void 0===n&&(n={}),this._checkLoaded(),void 0!==this.sourceCaches[e])throw new Error(\"There is already a source with this ID\");if(!r.type)throw new Error(\"The type property must be defined, but the only the following properties were given: \"+Object.keys(r).join(\", \")+\".\");if(!([\"vector\",\"raster\",\"geojson\",\"video\",\"image\"].indexOf(r.type)>=0)||!this._validate(t.validateStyle.source,\"sources.\"+e,r,null,n)){this.map&&this.map._collectResourceTiming&&(r.collectResourceTiming=!0);var a=this.sourceCaches[e]=new Ct(e,r,this.dispatcher);a.style=this,a.setEventedParent(this,(function(){return{isSourceLoaded:i.loaded(),source:a.serialize(),sourceId:e}})),a.onAdd(this.map),this._changed=!0}},r.prototype.removeSource=function(e){if(this._checkLoaded(),void 0===this.sourceCaches[e])throw new Error(\"There is no source with this ID\");for(var r in this._layers)if(this._layers[r].source===e)return this.fire(new t.ErrorEvent(new Error('Source \"'+e+'\" cannot be removed while layer \"'+r+'\" is using it.')));var n=this.sourceCaches[e];delete this.sourceCaches[e],delete this._updatedSources[e],n.fire(new t.Event(\"data\",{sourceDataType:\"metadata\",dataType:\"source\",sourceId:e})),n.setEventedParent(null),n.clearTiles(),n.onRemove&&n.onRemove(this.map),this._changed=!0},r.prototype.setGeoJSONSourceData=function(t,e){this._checkLoaded(),this.sourceCaches[t].getSource().setData(e),this._changed=!0},r.prototype.getSource=function(t){return this.sourceCaches[t]&&this.sourceCaches[t].getSource()},r.prototype.addLayer=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var i=e.id;if(this.getLayer(i))this.fire(new t.ErrorEvent(new Error('Layer with id \"'+i+'\" already exists on this map')));else{var a;if(\"custom\"===e.type){if(je(this,t.validateCustomStyleLayer(e)))return;a=t.createStyleLayer(e)}else{if(\"object\"==typeof e.source&&(this.addSource(i,e.source),e=t.clone$1(e),e=t.extend(e,{source:i})),this._validate(t.validateStyle.layer,\"layers.\"+i,e,{arrayIndex:-1},n))return;a=t.createStyleLayer(e),this._validateLayer(a),a.setEventedParent(this,{layer:{id:i}}),this._serializedLayers[a.id]=a.serialize()}var o=r?this._order.indexOf(r):this._order.length;if(r&&-1===o)this.fire(new t.ErrorEvent(new Error('Layer with id \"'+r+'\" does not exist on this map.')));else{if(this._order.splice(o,0,i),this._layerOrderChanged=!0,this._layers[i]=a,this._removedLayers[i]&&a.source&&\"custom\"!==a.type){var s=this._removedLayers[i];delete this._removedLayers[i],s.type!==a.type?this._updatedSources[a.source]=\"clear\":(this._updatedSources[a.source]=\"reload\",this.sourceCaches[a.source].pause())}this._updateLayer(a),a.onAdd&&a.onAdd(this.map)}}},r.prototype.moveLayer=function(e,r){if(this._checkLoaded(),this._changed=!0,this._layers[e]){if(e!==r){var n=this._order.indexOf(e);this._order.splice(n,1);var i=r?this._order.indexOf(r):this._order.length;r&&-1===i?this.fire(new t.ErrorEvent(new Error('Layer with id \"'+r+'\" does not exist on this map.'))):(this._order.splice(i,0,e),this._layerOrderChanged=!0)}}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be moved.\")))},r.prototype.removeLayer=function(e){this._checkLoaded();var r=this._layers[e];if(r){r.setEventedParent(null);var n=this._order.indexOf(e);this._order.splice(n,1),this._layerOrderChanged=!0,this._changed=!0,this._removedLayers[e]=r,delete this._layers[e],delete this._serializedLayers[e],delete this._updatedLayers[e],delete this._updatedPaintProps[e],r.onRemove&&r.onRemove(this.map)}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be removed.\")))},r.prototype.getLayer=function(t){return this._layers[t]},r.prototype.hasLayer=function(t){return t in this._layers},r.prototype.setLayerZoomRange=function(e,r,n){this._checkLoaded();var i=this.getLayer(e);i?i.minzoom===r&&i.maxzoom===n||(null!=r&&(i.minzoom=r),null!=n&&(i.maxzoom=n),this._updateLayer(i)):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot have zoom extent.\")))},r.prototype.setFilter=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var i=this.getLayer(e);if(i){if(!t.deepEqual(i.filter,r))return null==r?(i.filter=void 0,void this._updateLayer(i)):void(this._validate(t.validateStyle.filter,\"layers.\"+i.id+\".filter\",r,null,n)||(i.filter=t.clone$1(r),this._updateLayer(i)))}else this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be filtered.\")))},r.prototype.getFilter=function(e){return t.clone$1(this.getLayer(e).filter)},r.prototype.setLayoutProperty=function(e,r,n,i){void 0===i&&(i={}),this._checkLoaded();var a=this.getLayer(e);a?t.deepEqual(a.getLayoutProperty(r),n)||(a.setLayoutProperty(r,n,i),this._updateLayer(a)):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be styled.\")))},r.prototype.getLayoutProperty=function(e,r){var n=this.getLayer(e);if(n)return n.getLayoutProperty(r);this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style.\")))},r.prototype.setPaintProperty=function(e,r,n,i){void 0===i&&(i={}),this._checkLoaded();var a=this.getLayer(e);a?t.deepEqual(a.getPaintProperty(r),n)||(a.setPaintProperty(r,n,i)&&this._updateLayer(a),this._changed=!0,this._updatedPaintProps[e]=!0):this.fire(new t.ErrorEvent(new Error(\"The layer '\"+e+\"' does not exist in the map's style and cannot be styled.\")))},r.prototype.getPaintProperty=function(t,e){return this.getLayer(t).getPaintProperty(e)},r.prototype.setFeatureState=function(e,r){this._checkLoaded();var n=e.source,i=e.sourceLayer,a=this.sourceCaches[n];if(void 0!==a){var o=a.getSource().type;\"geojson\"===o&&i?this.fire(new t.ErrorEvent(new Error(\"GeoJSON sources cannot have a sourceLayer parameter.\"))):\"vector\"!==o||i?(void 0===e.id&&this.fire(new t.ErrorEvent(new Error(\"The feature id parameter must be provided.\"))),a.setFeatureState(i,e.id,r)):this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+n+\"' does not exist in the map's style.\")))},r.prototype.removeFeatureState=function(e,r){this._checkLoaded();var n=e.source,i=this.sourceCaches[n];if(void 0!==i){var a=i.getSource().type,o=\"vector\"===a?e.sourceLayer:void 0;\"vector\"!==a||o?r&&\"string\"!=typeof e.id&&\"number\"!=typeof e.id?this.fire(new t.ErrorEvent(new Error(\"A feature id is requred to remove its specific state property.\"))):i.removeFeatureState(o,e.id,r):this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+n+\"' does not exist in the map's style.\")))},r.prototype.getFeatureState=function(e){this._checkLoaded();var r=e.source,n=e.sourceLayer,i=this.sourceCaches[r];if(void 0!==i){if(\"vector\"!==i.getSource().type||n)return void 0===e.id&&this.fire(new t.ErrorEvent(new Error(\"The feature id parameter must be provided.\"))),i.getFeatureState(n,e.id);this.fire(new t.ErrorEvent(new Error(\"The sourceLayer parameter must be provided for vector source types.\")))}else this.fire(new t.ErrorEvent(new Error(\"The source '\"+r+\"' does not exist in the map's style.\")))},r.prototype.getTransition=function(){return t.extend({duration:300,delay:0},this.stylesheet&&this.stylesheet.transition)},r.prototype.serialize=function(){return t.filterObject({version:this.stylesheet.version,name:this.stylesheet.name,metadata:this.stylesheet.metadata,light:this.stylesheet.light,center:this.stylesheet.center,zoom:this.stylesheet.zoom,bearing:this.stylesheet.bearing,pitch:this.stylesheet.pitch,sprite:this.stylesheet.sprite,glyphs:this.stylesheet.glyphs,transition:this.stylesheet.transition,sources:t.mapObject(this.sourceCaches,(function(t){return t.serialize()})),layers:this._serializeLayers(this._order)},(function(t){return void 0!==t}))},r.prototype._updateLayer=function(t){this._updatedLayers[t.id]=!0,t.source&&!this._updatedSources[t.source]&&\"raster\"!==this.sourceCaches[t.source].getSource().type&&(this._updatedSources[t.source]=\"reload\",this.sourceCaches[t.source].pause()),this._changed=!0},r.prototype._flattenAndSortRenderedFeatures=function(t){for(var e=this,r=function(t){return\"fill-extrusion\"===e._layers[t].type},n={},i=[],a=this._order.length-1;a>=0;a--){var o=this._order[a];if(r(o)){n[o]=a;for(var s=0,l=t;s<l.length;s+=1){var c=l[s][o];if(c)for(var u=0,f=c;u<f.length;u+=1){var h=f[u];i.push(h)}}}}i.sort((function(t,e){return e.intersectionZ-t.intersectionZ}));for(var p=[],d=this._order.length-1;d>=0;d--){var g=this._order[d];if(r(g))for(var m=i.length-1;m>=0;m--){var v=i[m].feature;if(n[v.layer.id]<d)break;p.push(v),i.pop()}else for(var y=0,x=t;y<x.length;y+=1){var b=x[y][g];if(b)for(var _=0,w=b;_<w.length;_+=1){var T=w[_];p.push(T.feature)}}}return p},r.prototype.queryRenderedFeatures=function(e,r,n){r&&r.filter&&this._validate(t.validateStyle.filter,\"queryRenderedFeatures.filter\",r.filter,null,r);var i={};if(r&&r.layers){if(!Array.isArray(r.layers))return this.fire(new t.ErrorEvent(new Error(\"parameters.layers must be an Array.\"))),[];for(var a=0,o=r.layers;a<o.length;a+=1){var s=o[a],l=this._layers[s];if(!l)return this.fire(new t.ErrorEvent(new Error(\"The layer '\"+s+\"' does not exist in the map's style and cannot be queried for features.\"))),[];i[l.source]=!0}}var c=[];for(var u in r.availableImages=this._availableImages,this.sourceCaches)r.layers&&!i[u]||c.push(F(this.sourceCaches[u],this._layers,this._serializedLayers,e,r,n));return this.placement&&c.push(function(t,e,r,n,i,a,o){for(var s={},l=a.queryRenderedSymbols(n),c=[],u=0,f=Object.keys(l).map(Number);u<f.length;u+=1){var h=f[u];c.push(o[h])}c.sort(B);for(var p=function(){var r=g[d],n=r.featureIndex.lookupSymbolFeatures(l[r.bucketInstanceId],e,r.bucketIndex,r.sourceLayerIndex,i.filter,i.layers,i.availableImages,t);for(var a in n){var o=s[a]=s[a]||[],c=n[a];c.sort((function(t,e){var n=r.featureSortOrder;if(n){var i=n.indexOf(t.featureIndex);return n.indexOf(e.featureIndex)-i}return e.featureIndex-t.featureIndex}));for(var u=0,f=c;u<f.length;u+=1){var h=f[u];o.push(h)}}},d=0,g=c;d<g.length;d+=1)p();var m=function(e){s[e].forEach((function(n){var i=n.feature,a=t[e],o=r[a.source].getFeatureState(i.layer[\"source-layer\"],i.id);i.source=i.layer.source,i.layer[\"source-layer\"]&&(i.sourceLayer=i.layer[\"source-layer\"]),i.state=o}))};for(var v in s)m(v);return s}(this._layers,this._serializedLayers,this.sourceCaches,e,r,this.placement.collisionIndex,this.placement.retainedQueryData)),this._flattenAndSortRenderedFeatures(c)},r.prototype.querySourceFeatures=function(e,r){r&&r.filter&&this._validate(t.validateStyle.filter,\"querySourceFeatures.filter\",r.filter,null,r);var n=this.sourceCaches[e];return n?function(t,e){for(var r=t.getRenderableIds().map((function(e){return t.getTileByID(e)})),n=[],i={},a=0;a<r.length;a++){var o=r[a],s=o.tileID.canonical.key;i[s]||(i[s]=!0,o.querySourceFeatures(n,e))}return n}(n,r):[]},r.prototype.addSourceType=function(t,e,n){return r.getSourceType(t)?n(new Error('A source type called \"'+t+'\" already exists.')):(r.setSourceType(t,e),e.workerSourceURL?void this.dispatcher.broadcast(\"loadWorkerSource\",{name:t,url:e.workerSourceURL},n):n(null,null))},r.prototype.getLight=function(){return this.light.getLight()},r.prototype.setLight=function(e,r){void 0===r&&(r={}),this._checkLoaded();var n=this.light.getLight(),i=!1;for(var a in e)if(!t.deepEqual(e[a],n[a])){i=!0;break}if(i){var o={now:t.browser.now(),transition:t.extend({duration:300,delay:0},this.stylesheet.transition)};this.light.setLight(e,r),this.light.updateTransitions(o)}},r.prototype._validate=function(e,r,n,i,a){return void 0===a&&(a={}),(!a||!1!==a.validate)&&je(this,e.call(t.validateStyle,t.extend({key:r,style:this.serialize(),value:n,styleSpec:t.styleSpec},i)))},r.prototype._remove=function(){for(var e in this._request&&(this._request.cancel(),this._request=null),this._spriteRequest&&(this._spriteRequest.cancel(),this._spriteRequest=null),t.evented.off(\"pluginStateChange\",this._rtlTextPluginCallback),this._layers){this._layers[e].setEventedParent(null)}for(var r in this.sourceCaches)this.sourceCaches[r].clearTiles(),this.sourceCaches[r].setEventedParent(null);this.imageManager.setEventedParent(null),this.setEventedParent(null),this.dispatcher.remove()},r.prototype._clearSource=function(t){this.sourceCaches[t].clearTiles()},r.prototype._reloadSource=function(t){this.sourceCaches[t].resume(),this.sourceCaches[t].reload()},r.prototype._updateSources=function(t){for(var e in this.sourceCaches)this.sourceCaches[e].update(t)},r.prototype._generateCollisionBoxes=function(){for(var t in this.sourceCaches)this._reloadSource(t)},r.prototype._updatePlacement=function(e,r,n,i,a){void 0===a&&(a=!1);for(var o=!1,s=!1,l={},c=0,u=this._order;c<u.length;c+=1){var f=u[c],h=this._layers[f];if(\"symbol\"===h.type){if(!l[h.source]){var p=this.sourceCaches[h.source];l[h.source]=p.getRenderableIds(!0).map((function(t){return p.getTileByID(t)})).sort((function(t,e){return e.tileID.overscaledZ-t.tileID.overscaledZ||(t.tileID.isLessThan(e.tileID)?-1:1)}))}var d=this.crossTileSymbolIndex.addLayer(h,l[h.source],e.center.lng);o=o||d}}if(this.crossTileSymbolIndex.pruneUnusedLayers(this._order),((a=a||this._layerOrderChanged||0===n)||!this.pauseablePlacement||this.pauseablePlacement.isDone()&&!this.placement.stillRecent(t.browser.now(),e.zoom))&&(this.pauseablePlacement=new ze(e,this._order,a,r,n,i,this.placement),this._layerOrderChanged=!1),this.pauseablePlacement.isDone()?this.placement.setStale():(this.pauseablePlacement.continuePlacement(this._order,this._layers,l),this.pauseablePlacement.isDone()&&(this.placement=this.pauseablePlacement.commit(t.browser.now()),s=!0),o&&this.pauseablePlacement.placement.setStale()),s||o)for(var g=0,m=this._order;g<m.length;g+=1){var v=m[g],y=this._layers[v];\"symbol\"===y.type&&this.placement.updateLayerOpacities(y,l[y.source])}return!this.pauseablePlacement.isDone()||this.placement.hasTransitions(t.browser.now())},r.prototype._releaseSymbolFadeTiles=function(){for(var t in this.sourceCaches)this.sourceCaches[t].releaseSymbolFadeTiles()},r.prototype.getImages=function(t,e,r){this.imageManager.getImages(e.icons,r),this._updateTilesForChangedImages();var n=this.sourceCaches[e.source];n&&n.setDependencies(e.tileID.key,e.type,e.icons)},r.prototype.getGlyphs=function(t,e,r){this.glyphManager.getGlyphs(e.stacks,r)},r.prototype.getResource=function(e,r,n){return t.makeRequest(r,n)},r}(t.Evented);He.getSourceType=function(t){return D[t]},He.setSourceType=function(t,e){D[t]=e},He.registerForPluginStateChange=t.registerForPluginStateChange;var Ge=t.createLayout([{name:\"a_pos\",type:\"Int16\",components:2}]),Ye=yr(\"#ifdef GL_ES\\nprecision mediump float;\\n#else\\n#if !defined(lowp)\\n#define lowp\\n#endif\\n#if !defined(mediump)\\n#define mediump\\n#endif\\n#if !defined(highp)\\n#define highp\\n#endif\\n#endif\",\"#ifdef GL_ES\\nprecision highp float;\\n#else\\n#if !defined(lowp)\\n#define lowp\\n#endif\\n#if !defined(mediump)\\n#define mediump\\n#endif\\n#if !defined(highp)\\n#define highp\\n#endif\\n#endif\\nvec2 unpack_float(const float packedValue) {int packedIntValue=int(packedValue);int v0=packedIntValue/256;return vec2(v0,packedIntValue-v0*256);}vec2 unpack_opacity(const float packedOpacity) {int intOpacity=int(packedOpacity)/2;return vec2(float(intOpacity)/127.0,mod(packedOpacity,2.0));}vec4 decode_color(const vec2 encodedColor) {return vec4(unpack_float(encodedColor[0])/255.0,unpack_float(encodedColor[1])/255.0\\n);}float unpack_mix_vec2(const vec2 packedValue,const float t) {return mix(packedValue[0],packedValue[1],t);}vec4 unpack_mix_color(const vec4 packedColors,const float t) {vec4 minColor=decode_color(vec2(packedColors[0],packedColors[1]));vec4 maxColor=decode_color(vec2(packedColors[2],packedColors[3]));return mix(minColor,maxColor,t);}vec2 get_pattern_pos(const vec2 pixel_coord_upper,const vec2 pixel_coord_lower,const vec2 pattern_size,const float tile_units_to_pixels,const vec2 pos) {vec2 offset=mod(mod(mod(pixel_coord_upper,pattern_size)*256.0,pattern_size)*256.0+pixel_coord_lower,pattern_size);return (tile_units_to_pixels*pos+offset)/pattern_size;}\"),We=yr(\"uniform vec4 u_color;uniform float u_opacity;void main() {gl_FragColor=u_color*u_opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}\"),Xe=yr(\"uniform vec2 u_pattern_tl_a;uniform vec2 u_pattern_br_a;uniform vec2 u_pattern_tl_b;uniform vec2 u_pattern_br_b;uniform vec2 u_texsize;uniform float u_mix;uniform float u_opacity;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(u_pattern_tl_a/u_texsize,u_pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(u_pattern_tl_b/u_texsize,u_pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_mix)*u_opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pattern_size_a;uniform vec2 u_pattern_size_b;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_scale_a;uniform float u_scale_b;uniform float u_tile_units_to_pixels;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_a*u_pattern_size_a,u_tile_units_to_pixels,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_b*u_pattern_size_b,u_tile_units_to_pixels,a_pos);}\"),Ze=yr(\"varying vec3 v_data;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define mediump float radius\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define highp vec4 stroke_color\\n#pragma mapbox: define mediump float stroke_width\\n#pragma mapbox: define lowp float stroke_opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize mediump float radius\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize highp vec4 stroke_color\\n#pragma mapbox: initialize mediump float stroke_width\\n#pragma mapbox: initialize lowp float stroke_opacity\\nvec2 extrude=v_data.xy;float extrude_length=length(extrude);lowp float antialiasblur=v_data.z;float antialiased_blur=-max(blur,antialiasblur);float opacity_t=smoothstep(0.0,antialiased_blur,extrude_length-1.0);float color_t=stroke_width < 0.01 ? 0.0 : smoothstep(antialiased_blur,0.0,extrude_length-radius/(radius+stroke_width));gl_FragColor=opacity_t*mix(color*opacity,stroke_color*stroke_opacity,color_t);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform bool u_scale_with_map;uniform bool u_pitch_with_map;uniform vec2 u_extrude_scale;uniform lowp float u_device_pixel_ratio;uniform highp float u_camera_to_center_distance;attribute vec2 a_pos;varying vec3 v_data;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define mediump float radius\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define highp vec4 stroke_color\\n#pragma mapbox: define mediump float stroke_width\\n#pragma mapbox: define lowp float stroke_opacity\\nvoid main(void) {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize mediump float radius\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize highp vec4 stroke_color\\n#pragma mapbox: initialize mediump float stroke_width\\n#pragma mapbox: initialize lowp float stroke_opacity\\nvec2 extrude=vec2(mod(a_pos,2.0)*2.0-1.0);vec2 circle_center=floor(a_pos*0.5);if (u_pitch_with_map) {vec2 corner_position=circle_center;if (u_scale_with_map) {corner_position+=extrude*(radius+stroke_width)*u_extrude_scale;} else {vec4 projected_center=u_matrix*vec4(circle_center,0,1);corner_position+=extrude*(radius+stroke_width)*u_extrude_scale*(projected_center.w/u_camera_to_center_distance);}gl_Position=u_matrix*vec4(corner_position,0,1);} else {gl_Position=u_matrix*vec4(circle_center,0,1);if (u_scale_with_map) {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*u_camera_to_center_distance;} else {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*gl_Position.w;}}lowp float antialiasblur=1.0/u_device_pixel_ratio/(radius+stroke_width);v_data=vec3(extrude.x,extrude.y,antialiasblur);}\"),Je=yr(\"void main() {gl_FragColor=vec4(1.0);}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}\"),Ke=yr(\"uniform highp float u_intensity;varying vec2 v_extrude;\\n#pragma mapbox: define highp float weight\\n#define GAUSS_COEF 0.3989422804014327\\nvoid main() {\\n#pragma mapbox: initialize highp float weight\\nfloat d=-0.5*3.0*3.0*dot(v_extrude,v_extrude);float val=weight*u_intensity*GAUSS_COEF*exp(d);gl_FragColor=vec4(val,1.0,1.0,1.0);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform float u_extrude_scale;uniform float u_opacity;uniform float u_intensity;attribute vec2 a_pos;varying vec2 v_extrude;\\n#pragma mapbox: define highp float weight\\n#pragma mapbox: define mediump float radius\\nconst highp float ZERO=1.0/255.0/16.0;\\n#define GAUSS_COEF 0.3989422804014327\\nvoid main(void) {\\n#pragma mapbox: initialize highp float weight\\n#pragma mapbox: initialize mediump float radius\\nvec2 unscaled_extrude=vec2(mod(a_pos,2.0)*2.0-1.0);float S=sqrt(-2.0*log(ZERO/weight/u_intensity/GAUSS_COEF))/3.0;v_extrude=S*unscaled_extrude;vec2 extrude=v_extrude*radius*u_extrude_scale;vec4 pos=vec4(floor(a_pos*0.5)+extrude,0,1);gl_Position=u_matrix*pos;}\"),Qe=yr(\"uniform sampler2D u_image;uniform sampler2D u_color_ramp;uniform float u_opacity;varying vec2 v_pos;void main() {float t=texture2D(u_image,v_pos).r;vec4 color=texture2D(u_color_ramp,vec2(t,0.5));gl_FragColor=color*u_opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(0.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_world;attribute vec2 a_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos*u_world,0,1);v_pos.x=a_pos.x;v_pos.y=1.0-a_pos.y;}\"),$e=yr(\"varying float v_placed;varying float v_notUsed;void main() {float alpha=0.5;gl_FragColor=vec4(1.0,0.0,0.0,1.0)*alpha;if (v_placed > 0.5) {gl_FragColor=vec4(0.0,0.0,1.0,0.5)*alpha;}if (v_notUsed > 0.5) {gl_FragColor*=.1;}}\",\"attribute vec2 a_pos;attribute vec2 a_anchor_pos;attribute vec2 a_extrude;attribute vec2 a_placed;attribute vec2 a_shift;uniform mat4 u_matrix;uniform vec2 u_extrude_scale;uniform float u_camera_to_center_distance;varying float v_placed;varying float v_notUsed;void main() {vec4 projectedPoint=u_matrix*vec4(a_anchor_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);gl_Position=u_matrix*vec4(a_pos,0.0,1.0);gl_Position.xy+=(a_extrude+a_shift)*u_extrude_scale*gl_Position.w*collision_perspective_ratio;v_placed=a_placed.x;v_notUsed=a_placed.y;}\"),tr=yr(\"varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;void main() {float alpha=0.5*min(v_perspective_ratio,1.0);float stroke_radius=0.9*max(v_perspective_ratio,1.0);float distance_to_center=length(v_extrude);float distance_to_edge=abs(distance_to_center-v_radius);float opacity_t=smoothstep(-stroke_radius,0.0,-distance_to_edge);vec4 color=mix(vec4(0.0,0.0,1.0,0.5),vec4(1.0,0.0,0.0,1.0),v_collision);gl_FragColor=color*alpha*opacity_t;}\",\"attribute vec2 a_pos;attribute float a_radius;attribute vec2 a_flags;uniform mat4 u_matrix;uniform mat4 u_inv_matrix;uniform vec2 u_viewport_size;uniform float u_camera_to_center_distance;varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;vec3 toTilePosition(vec2 screenPos) {vec4 rayStart=u_inv_matrix*vec4(screenPos,-1.0,1.0);vec4 rayEnd  =u_inv_matrix*vec4(screenPos, 1.0,1.0);rayStart.xyz/=rayStart.w;rayEnd.xyz  /=rayEnd.w;highp float t=(0.0-rayStart.z)/(rayEnd.z-rayStart.z);return mix(rayStart.xyz,rayEnd.xyz,t);}void main() {vec2 quadCenterPos=a_pos;float radius=a_radius;float collision=a_flags.x;float vertexIdx=a_flags.y;vec2 quadVertexOffset=vec2(mix(-1.0,1.0,float(vertexIdx >=2.0)),mix(-1.0,1.0,float(vertexIdx >=1.0 && vertexIdx <=2.0)));vec2 quadVertexExtent=quadVertexOffset*radius;vec3 tilePos=toTilePosition(quadCenterPos);vec4 clipPos=u_matrix*vec4(tilePos,1.0);highp float camera_to_anchor_distance=clipPos.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);float padding_factor=1.2;v_radius=radius;v_extrude=quadVertexExtent*padding_factor;v_perspective_ratio=collision_perspective_ratio;v_collision=collision;gl_Position=vec4(clipPos.xyz/clipPos.w,1.0)+vec4(quadVertexExtent*padding_factor/u_viewport_size*2.0,0.0,0.0);}\"),er=yr(\"uniform highp vec4 u_color;uniform sampler2D u_overlay;varying vec2 v_uv;void main() {vec4 overlay_color=texture2D(u_overlay,v_uv);gl_FragColor=mix(u_color,overlay_color,overlay_color.a);}\",\"attribute vec2 a_pos;varying vec2 v_uv;uniform mat4 u_matrix;uniform float u_overlay_scale;void main() {v_uv=a_pos/8192.0;gl_Position=u_matrix*vec4(a_pos*u_overlay_scale,0,1);}\"),rr=yr(\"#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float opacity\\ngl_FragColor=color*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float opacity\\ngl_Position=u_matrix*vec4(a_pos,0,1);}\"),nr=yr(\"varying vec2 v_pos;\\n#pragma mapbox: define highp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 outline_color\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=outline_color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"attribute vec2 a_pos;uniform mat4 u_matrix;uniform vec2 u_world;varying vec2 v_pos;\\n#pragma mapbox: define highp vec4 outline_color\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 outline_color\\n#pragma mapbox: initialize lowp float opacity\\ngl_Position=u_matrix*vec4(a_pos,0,1);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}\"),ir=yr(\"uniform vec2 u_texsize;uniform sampler2D u_image;uniform float u_fade;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);float dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=mix(color1,color2,u_fade)*alpha*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_world;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;gl_Position=u_matrix*vec4(a_pos,0,1);vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,a_pos);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}\"),ar=yr(\"uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_fade)*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileZoomRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileZoomRatio,a_pos);}\"),or=yr(\"varying vec4 v_color;void main() {gl_FragColor=v_color;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;uniform float u_vertical_gradient;uniform lowp float u_opacity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec4 v_color;\\n#pragma mapbox: define highp float base\\n#pragma mapbox: define highp float height\\n#pragma mapbox: define highp vec4 color\\nvoid main() {\\n#pragma mapbox: initialize highp float base\\n#pragma mapbox: initialize highp float height\\n#pragma mapbox: initialize highp vec4 color\\nvec3 normal=a_normal_ed.xyz;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);gl_Position=u_matrix*vec4(a_pos,t > 0.0 ? height : base,1);float colorvalue=color.r*0.2126+color.g*0.7152+color.b*0.0722;v_color=vec4(0.0,0.0,0.0,1.0);vec4 ambientlight=vec4(0.03,0.03,0.03,1.0);color+=ambientlight;float directional=clamp(dot(normal/16384.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((1.0-colorvalue+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_color.r+=clamp(color.r*directional*u_lightcolor.r,mix(0.0,0.3,1.0-u_lightcolor.r),1.0);v_color.g+=clamp(color.g*directional*u_lightcolor.g,mix(0.0,0.3,1.0-u_lightcolor.g),1.0);v_color.b+=clamp(color.b*directional*u_lightcolor.b,mix(0.0,0.3,1.0-u_lightcolor.b),1.0);v_color*=u_opacity;}\"),sr=yr(\"uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\\n#pragma mapbox: define lowp float base\\n#pragma mapbox: define lowp float height\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float base\\n#pragma mapbox: initialize lowp float height\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);vec4 mixedColor=mix(color1,color2,u_fade);gl_FragColor=mixedColor*v_lighting;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_height_factor;uniform vec3 u_scale;uniform float u_vertical_gradient;uniform lowp float u_opacity;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\\n#pragma mapbox: define lowp float base\\n#pragma mapbox: define lowp float height\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float base\\n#pragma mapbox: initialize lowp float height\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec3 normal=a_normal_ed.xyz;float edgedistance=a_normal_ed.w;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);float z=t > 0.0 ? height : base;gl_Position=u_matrix*vec4(a_pos,z,1);vec2 pos=normal.x==1.0 && normal.y==0.0 && normal.z==16384.0\\n? a_pos\\n: vec2(edgedistance,z*u_height_factor);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,pos);v_lighting=vec4(0.0,0.0,0.0,1.0);float directional=clamp(dot(normal/16383.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((0.5+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_lighting.rgb+=clamp(directional*u_lightcolor,mix(vec3(0.0),vec3(0.3),1.0-u_lightcolor),vec3(1.0));v_lighting*=u_opacity;}\"),lr=yr(\"#ifdef GL_ES\\nprecision highp float;\\n#endif\\nuniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_dimension;uniform float u_zoom;uniform float u_maxzoom;uniform vec4 u_unpack;float getElevation(vec2 coord,float bias) {vec4 data=texture2D(u_image,coord)*255.0;data.a=-1.0;return dot(data,u_unpack)/4.0;}void main() {vec2 epsilon=1.0/u_dimension;float a=getElevation(v_pos+vec2(-epsilon.x,-epsilon.y),0.0);float b=getElevation(v_pos+vec2(0,-epsilon.y),0.0);float c=getElevation(v_pos+vec2(epsilon.x,-epsilon.y),0.0);float d=getElevation(v_pos+vec2(-epsilon.x,0),0.0);float e=getElevation(v_pos,0.0);float f=getElevation(v_pos+vec2(epsilon.x,0),0.0);float g=getElevation(v_pos+vec2(-epsilon.x,epsilon.y),0.0);float h=getElevation(v_pos+vec2(0,epsilon.y),0.0);float i=getElevation(v_pos+vec2(epsilon.x,epsilon.y),0.0);float exaggeration=u_zoom < 2.0 ? 0.4 : u_zoom < 4.5 ? 0.35 : 0.3;vec2 deriv=vec2((c+f+f+i)-(a+d+d+g),(g+h+h+i)-(a+b+b+c))/ pow(2.0,(u_zoom-u_maxzoom)*exaggeration+19.2562-u_zoom);gl_FragColor=clamp(vec4(deriv.x/2.0+0.5,deriv.y/2.0+0.5,1.0,1.0),0.0,1.0);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_dimension;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);highp vec2 epsilon=1.0/u_dimension;float scale=(u_dimension.x-2.0)/u_dimension.x;v_pos=(a_texture_pos/8192.0)*scale+epsilon;}\"),cr=yr(\"uniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_latrange;uniform vec2 u_light;uniform vec4 u_shadow;uniform vec4 u_highlight;uniform vec4 u_accent;\\n#define PI 3.141592653589793\\nvoid main() {vec4 pixel=texture2D(u_image,v_pos);vec2 deriv=((pixel.rg*2.0)-1.0);float scaleFactor=cos(radians((u_latrange[0]-u_latrange[1])*(1.0-v_pos.y)+u_latrange[1]));float slope=atan(1.25*length(deriv)/scaleFactor);float aspect=deriv.x !=0.0 ? atan(deriv.y,-deriv.x) : PI/2.0*(deriv.y > 0.0 ? 1.0 :-1.0);float intensity=u_light.x;float azimuth=u_light.y+PI;float base=1.875-intensity*1.75;float maxValue=0.5*PI;float scaledSlope=intensity !=0.5 ? ((pow(base,slope)-1.0)/(pow(base,maxValue)-1.0))*maxValue : slope;float accent=cos(scaledSlope);vec4 accent_color=(1.0-accent)*u_accent*clamp(intensity*2.0,0.0,1.0);float shade=abs(mod((aspect+azimuth)/PI+0.5,2.0)-1.0);vec4 shade_color=mix(u_shadow,u_highlight,shade)*sin(scaledSlope)*clamp(intensity*2.0,0.0,1.0);gl_FragColor=accent_color*(1.0-shade_color.a)+shade_color;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos=a_texture_pos/8192.0;}\"),ur=yr(\"uniform lowp float u_device_pixel_ratio;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform vec2 u_units_to_pixels;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_linesofar;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}\"),fr=yr(\"uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;varying highp float v_lineprogress;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);vec4 color=texture2D(u_image,vec2(v_lineprogress,0.5));gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define MAX_LINE_DISTANCE 32767.0\\n#define scale 0.015873016\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_lineprogress;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_lineprogress=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0/MAX_LINE_DISTANCE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}\"),hr=yr(\"uniform lowp float u_device_pixel_ratio;uniform vec2 u_texsize;uniform float u_fade;uniform mediump vec3 u_scale;uniform sampler2D u_image;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;vec2 pattern_size_a=vec2(display_size_a.x*fromScale/tileZoomRatio,display_size_a.y);vec2 pattern_size_b=vec2(display_size_b.x*toScale/tileZoomRatio,display_size_b.y);float aspect_a=display_size_a.y/v_width;float aspect_b=display_size_b.y/v_width;float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float x_a=mod(v_linesofar/pattern_size_a.x*aspect_a,1.0);float x_b=mod(v_linesofar/pattern_size_b.x*aspect_b,1.0);float y=0.5*v_normal.y+0.5;vec2 texel_size=1.0/u_texsize;vec2 pos_a=mix(pattern_tl_a*texel_size-texel_size,pattern_br_a*texel_size+texel_size,vec2(x_a,y));vec2 pos_b=mix(pattern_tl_b*texel_size-texel_size,pattern_br_b*texel_size+texel_size,vec2(x_b,y));vec4 color=mix(texture2D(u_image,pos_a),texture2D(u_image,pos_b),u_fade);gl_FragColor=color*alpha*opacity;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\n#define LINE_DISTANCE_SCALE 2.0\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform vec2 u_units_to_pixels;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\n#pragma mapbox: define lowp vec4 pattern_from\\n#pragma mapbox: define lowp vec4 pattern_to\\n#pragma mapbox: define lowp float pixel_ratio_from\\n#pragma mapbox: define lowp float pixel_ratio_to\\nvoid main() {\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\n#pragma mapbox: initialize mediump vec4 pattern_from\\n#pragma mapbox: initialize mediump vec4 pattern_to\\n#pragma mapbox: initialize lowp float pixel_ratio_from\\n#pragma mapbox: initialize lowp float pixel_ratio_to\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_linesofar=a_linesofar;v_width2=vec2(outset,inset);v_width=floorwidth;}\"),pr=yr(\"uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;uniform float u_sdfgamma;uniform float u_mix;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float sdfdist_a=texture2D(u_image,v_tex_a).a;float sdfdist_b=texture2D(u_image,v_tex_b).a;float sdfdist=mix(sdfdist_a,sdfdist_b,u_mix);alpha*=smoothstep(0.5-u_sdfgamma/floorwidth,0.5+u_sdfgamma/floorwidth,sdfdist);gl_FragColor=color*(alpha*opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"\\n#define scale 0.015873016\\n#define LINE_DISTANCE_SCALE 2.0\\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_patternscale_a;uniform float u_tex_y_a;uniform vec2 u_patternscale_b;uniform float u_tex_y_b;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\\n#pragma mapbox: define highp vec4 color\\n#pragma mapbox: define lowp float blur\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define mediump float gapwidth\\n#pragma mapbox: define lowp float offset\\n#pragma mapbox: define mediump float width\\n#pragma mapbox: define lowp float floorwidth\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 color\\n#pragma mapbox: initialize lowp float blur\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize mediump float gapwidth\\n#pragma mapbox: initialize lowp float offset\\n#pragma mapbox: initialize mediump float width\\n#pragma mapbox: initialize lowp float floorwidth\\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_tex_a=vec2(a_linesofar*u_patternscale_a.x/floorwidth,normal.y*u_patternscale_a.y+u_tex_y_a);v_tex_b=vec2(a_linesofar*u_patternscale_b.x/floorwidth,normal.y*u_patternscale_b.y+u_tex_y_b);v_width2=vec2(outset,inset);}\"),dr=yr(\"uniform float u_fade_t;uniform float u_opacity;uniform sampler2D u_image0;uniform sampler2D u_image1;varying vec2 v_pos0;varying vec2 v_pos1;uniform float u_brightness_low;uniform float u_brightness_high;uniform float u_saturation_factor;uniform float u_contrast_factor;uniform vec3 u_spin_weights;void main() {vec4 color0=texture2D(u_image0,v_pos0);vec4 color1=texture2D(u_image1,v_pos1);if (color0.a > 0.0) {color0.rgb=color0.rgb/color0.a;}if (color1.a > 0.0) {color1.rgb=color1.rgb/color1.a;}vec4 color=mix(color0,color1,u_fade_t);color.a*=u_opacity;vec3 rgb=color.rgb;rgb=vec3(dot(rgb,u_spin_weights.xyz),dot(rgb,u_spin_weights.zxy),dot(rgb,u_spin_weights.yzx));float average=(color.r+color.g+color.b)/3.0;rgb+=(average-rgb)*u_saturation_factor;rgb=(rgb-0.5)*u_contrast_factor+0.5;vec3 u_high_vec=vec3(u_brightness_low,u_brightness_low,u_brightness_low);vec3 u_low_vec=vec3(u_brightness_high,u_brightness_high,u_brightness_high);gl_FragColor=vec4(mix(u_high_vec,u_low_vec,rgb)*color.a,color.a);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"uniform mat4 u_matrix;uniform vec2 u_tl_parent;uniform float u_scale_parent;uniform float u_buffer_scale;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos0;varying vec2 v_pos1;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos0=(((a_texture_pos/8192.0)-0.5)/u_buffer_scale )+0.5;v_pos1=(v_pos0*u_scale_parent)+u_tl_parent;}\"),gr=yr(\"uniform sampler2D u_texture;varying vec2 v_tex;varying float v_fade_opacity;\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\nlowp float alpha=opacity*v_fade_opacity;gl_FragColor=texture2D(u_texture,v_tex)*alpha;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform highp float u_camera_to_center_distance;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform float u_fade_change;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform vec2 u_texsize;varying vec2 v_tex;varying float v_fade_opacity;\\n#pragma mapbox: define lowp float opacity\\nvoid main() {\\n#pragma mapbox: initialize lowp float opacity\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;vec2 a_minFontScale=a_pixeloffset.zw/256.0;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*max(a_minFontScale,fontScale)+a_pxoffset/16.0),0.0,1.0);v_tex=a_tex/u_texsize;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;v_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));}\"),mr=yr(\"#define SDF_PX 8.0\\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;uniform bool u_is_text;varying vec2 v_data0;varying vec3 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nfloat EDGE_GAMMA=0.105/u_device_pixel_ratio;vec2 tex=v_data0.xy;float gamma_scale=v_data1.x;float size=v_data1.y;float fade_opacity=v_data1[2];float fontScale=u_is_text ? size/24.0 : size;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;varying vec2 v_data0;varying vec3 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale+a_pxoffset),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0=a_tex/u_texsize;v_data1=vec3(gamma_scale,size,interpolated_fade_opacity);}\"),vr=yr(\"#define SDF_PX 8.0\\n#define SDF 1.0\\n#define ICON 0.0\\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform sampler2D u_texture_icon;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;varying vec4 v_data0;varying vec4 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nfloat fade_opacity=v_data1[2];if (v_data1.w==ICON) {vec2 tex_icon=v_data0.zw;lowp float alpha=opacity*fade_opacity;gl_FragColor=texture2D(u_texture_icon,tex_icon)*alpha;\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\nreturn;}vec2 tex=v_data0.xy;float EDGE_GAMMA=0.105/u_device_pixel_ratio;float gamma_scale=v_data1.x;float size=v_data1.y;float fontScale=size/24.0;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\\n#ifdef OVERDRAW_INSPECTOR\\ngl_FragColor=vec4(1.0);\\n#endif\\n}\",\"const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;uniform vec2 u_texsize_icon;varying vec4 v_data0;varying vec4 v_data1;\\n#pragma mapbox: define highp vec4 fill_color\\n#pragma mapbox: define highp vec4 halo_color\\n#pragma mapbox: define lowp float opacity\\n#pragma mapbox: define lowp float halo_width\\n#pragma mapbox: define lowp float halo_blur\\nvoid main() {\\n#pragma mapbox: initialize highp vec4 fill_color\\n#pragma mapbox: initialize highp vec4 halo_color\\n#pragma mapbox: initialize lowp float opacity\\n#pragma mapbox: initialize lowp float halo_width\\n#pragma mapbox: initialize lowp float halo_blur\\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);float is_sdf=a_size[0]-2.0*a_size_min;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\\ncamera_to_anchor_distance/u_camera_to_center_distance :\\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=size/24.0;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0.xy=a_tex/u_texsize;v_data0.zw=a_tex/u_texsize_icon;v_data1=vec4(gamma_scale,size,interpolated_fade_opacity,is_sdf);}\");function yr(t,e){var r=/#pragma mapbox: ([\\w]+) ([\\w]+) ([\\w]+) ([\\w]+)/g,n={};return{fragmentSource:t=t.replace(r,(function(t,e,r,i,a){return n[a]=!0,\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\nvarying \"+r+\" \"+i+\" \"+a+\";\\n#else\\nuniform \"+r+\" \"+i+\" u_\"+a+\";\\n#endif\\n\":\"\\n#ifdef HAS_UNIFORM_u_\"+a+\"\\n    \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\"})),vertexSource:e=e.replace(r,(function(t,e,r,i,a){var o=\"float\"===i?\"vec2\":\"vec4\",s=a.match(/color/)?\"color\":o;return n[a]?\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\nuniform lowp float u_\"+a+\"_t;\\nattribute \"+r+\" \"+o+\" a_\"+a+\";\\nvarying \"+r+\" \"+i+\" \"+a+\";\\n#else\\nuniform \"+r+\" \"+i+\" u_\"+a+\";\\n#endif\\n\":\"vec4\"===s?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n    \"+a+\" = a_\"+a+\";\\n#else\\n    \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\":\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n    \"+a+\" = unpack_mix_\"+s+\"(a_\"+a+\", u_\"+a+\"_t);\\n#else\\n    \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\":\"define\"===e?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\nuniform lowp float u_\"+a+\"_t;\\nattribute \"+r+\" \"+o+\" a_\"+a+\";\\n#else\\nuniform \"+r+\" \"+i+\" u_\"+a+\";\\n#endif\\n\":\"vec4\"===s?\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n    \"+r+\" \"+i+\" \"+a+\" = a_\"+a+\";\\n#else\\n    \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\":\"\\n#ifndef HAS_UNIFORM_u_\"+a+\"\\n    \"+r+\" \"+i+\" \"+a+\" = unpack_mix_\"+s+\"(a_\"+a+\", u_\"+a+\"_t);\\n#else\\n    \"+r+\" \"+i+\" \"+a+\" = u_\"+a+\";\\n#endif\\n\"}))}}var xr=Object.freeze({__proto__:null,prelude:Ye,background:We,backgroundPattern:Xe,circle:Ze,clippingMask:Je,heatmap:Ke,heatmapTexture:Qe,collisionBox:$e,collisionCircle:tr,debug:er,fill:rr,fillOutline:nr,fillOutlinePattern:ir,fillPattern:ar,fillExtrusion:or,fillExtrusionPattern:sr,hillshadePrepare:lr,hillshade:cr,line:ur,lineGradient:fr,linePattern:hr,lineSDF:pr,raster:dr,symbolIcon:gr,symbolSDF:mr,symbolTextAndIcon:vr}),br=function(){this.boundProgram=null,this.boundLayoutVertexBuffer=null,this.boundPaintVertexBuffers=[],this.boundIndexBuffer=null,this.boundVertexOffset=null,this.boundDynamicVertexBuffer=null,this.vao=null};br.prototype.bind=function(t,e,r,n,i,a,o,s){this.context=t;for(var l=this.boundPaintVertexBuffers.length!==n.length,c=0;!l&&c<n.length;c++)this.boundPaintVertexBuffers[c]!==n[c]&&(l=!0);var u=!this.vao||this.boundProgram!==e||this.boundLayoutVertexBuffer!==r||l||this.boundIndexBuffer!==i||this.boundVertexOffset!==a||this.boundDynamicVertexBuffer!==o||this.boundDynamicVertexBuffer2!==s;!t.extVertexArrayObject||u?this.freshBind(e,r,n,i,a,o,s):(t.bindVertexArrayOES.set(this.vao),o&&o.bind(),i&&i.dynamicDraw&&i.bind(),s&&s.bind())},br.prototype.freshBind=function(t,e,r,n,i,a,o){var s,l=t.numAttributes,c=this.context,u=c.gl;if(c.extVertexArrayObject)this.vao&&this.destroy(),this.vao=c.extVertexArrayObject.createVertexArrayOES(),c.bindVertexArrayOES.set(this.vao),s=0,this.boundProgram=t,this.boundLayoutVertexBuffer=e,this.boundPaintVertexBuffers=r,this.boundIndexBuffer=n,this.boundVertexOffset=i,this.boundDynamicVertexBuffer=a,this.boundDynamicVertexBuffer2=o;else{s=c.currentNumAttributes||0;for(var f=l;f<s;f++)u.disableVertexAttribArray(f)}e.enableAttributes(u,t);for(var h=0,p=r;h<p.length;h+=1){p[h].enableAttributes(u,t)}a&&a.enableAttributes(u,t),o&&o.enableAttributes(u,t),e.bind(),e.setVertexAttribPointers(u,t,i);for(var d=0,g=r;d<g.length;d+=1){var m=g[d];m.bind(),m.setVertexAttribPointers(u,t,i)}a&&(a.bind(),a.setVertexAttribPointers(u,t,i)),n&&n.bind(),o&&(o.bind(),o.setVertexAttribPointers(u,t,i)),c.currentNumAttributes=l},br.prototype.destroy=function(){this.vao&&(this.context.extVertexArrayObject.deleteVertexArrayOES(this.vao),this.vao=null)};var _r=function(t,e,r,n,i){var a=t.gl;this.program=a.createProgram();var o=r?r.defines():[];i&&o.push(\"#define OVERDRAW_INSPECTOR;\");var s=o.concat(Ye.fragmentSource,e.fragmentSource).join(\"\\n\"),l=o.concat(Ye.vertexSource,e.vertexSource).join(\"\\n\"),c=a.createShader(a.FRAGMENT_SHADER);if(a.isContextLost())this.failedToCreate=!0;else{a.shaderSource(c,s),a.compileShader(c),a.attachShader(this.program,c);var u=a.createShader(a.VERTEX_SHADER);if(a.isContextLost())this.failedToCreate=!0;else{a.shaderSource(u,l),a.compileShader(u),a.attachShader(this.program,u);for(var f=r?r.layoutAttributes:[],h=0;h<f.length;h++)a.bindAttribLocation(this.program,h,f[h].name);a.linkProgram(this.program),a.deleteShader(u),a.deleteShader(c),this.numAttributes=a.getProgramParameter(this.program,a.ACTIVE_ATTRIBUTES),this.attributes={};for(var p={},d=0;d<this.numAttributes;d++){var g=a.getActiveAttrib(this.program,d);g&&(this.attributes[g.name]=a.getAttribLocation(this.program,g.name))}for(var m=a.getProgramParameter(this.program,a.ACTIVE_UNIFORMS),v=0;v<m;v++){var y=a.getActiveUniform(this.program,v);y&&(p[y.name]=a.getUniformLocation(this.program,y.name))}this.fixedUniforms=n(t,p),this.binderUniforms=r?r.getUniforms(t,p):[]}}};function wr(t,e,r){var n=1/pe(r,1,e.transform.tileZoom),i=Math.pow(2,r.tileID.overscaledZ),a=r.tileSize*Math.pow(2,e.transform.tileZoom)/i,o=a*(r.tileID.canonical.x+r.tileID.wrap*i),s=a*r.tileID.canonical.y;return{u_image:0,u_texsize:r.imageAtlasTexture.size,u_scale:[n,t.fromScale,t.toScale],u_fade:t.t,u_pixel_coord_upper:[o>>16,s>>16],u_pixel_coord_lower:[65535&o,65535&s]}}_r.prototype.draw=function(t,e,r,n,i,a,o,s,l,c,u,f,h,p,d,g){var m,v=t.gl;if(!this.failedToCreate){for(var y in t.program.set(this.program),t.setDepthMode(r),t.setStencilMode(n),t.setColorMode(i),t.setCullFace(a),this.fixedUniforms)this.fixedUniforms[y].set(o[y]);p&&p.setUniforms(t,this.binderUniforms,f,{zoom:h});for(var x=(m={},m[v.LINES]=2,m[v.TRIANGLES]=3,m[v.LINE_STRIP]=1,m)[e],b=0,_=u.get();b<_.length;b+=1){var w=_[b],T=w.vaos||(w.vaos={});(T[s]||(T[s]=new br)).bind(t,this,l,p?p.getPaintVertexBuffers():[],c,w.vertexOffset,d,g),v.drawElements(e,w.primitiveLength*x,v.UNSIGNED_SHORT,w.primitiveOffset*x*2)}}};var Tr=function(e,r,n,i){var a=r.style.light,o=a.properties.get(\"position\"),s=[o.x,o.y,o.z],l=t.create$1();\"viewport\"===a.properties.get(\"anchor\")&&t.fromRotation(l,-r.transform.angle),t.transformMat3(s,s,l);var c=a.properties.get(\"color\");return{u_matrix:e,u_lightpos:s,u_lightintensity:a.properties.get(\"intensity\"),u_lightcolor:[c.r,c.g,c.b],u_vertical_gradient:+n,u_opacity:i}},kr=function(e,r,n,i,a,o,s){return t.extend(Tr(e,r,n,i),wr(o,r,s),{u_height_factor:-Math.pow(2,a.overscaledZ)/s.tileSize/8})},Ar=function(t){return{u_matrix:t}},Mr=function(e,r,n,i){return t.extend(Ar(e),wr(n,r,i))},Sr=function(t,e){return{u_matrix:t,u_world:e}},Er=function(e,r,n,i,a){return t.extend(Mr(e,r,n,i),{u_world:a})},Lr=function(e,r,n,i){var a,o,s=e.transform;if(\"map\"===i.paint.get(\"circle-pitch-alignment\")){var l=pe(n,1,s.zoom);a=!0,o=[l,l]}else a=!1,o=s.pixelsToGLUnits;return{u_camera_to_center_distance:s.cameraToCenterDistance,u_scale_with_map:+(\"map\"===i.paint.get(\"circle-pitch-scale\")),u_matrix:e.translatePosMatrix(r.posMatrix,n,i.paint.get(\"circle-translate\"),i.paint.get(\"circle-translate-anchor\")),u_pitch_with_map:+a,u_device_pixel_ratio:t.browser.devicePixelRatio,u_extrude_scale:o}},Cr=function(t,e,r){var n=pe(r,1,e.zoom),i=Math.pow(2,e.zoom-r.tileID.overscaledZ),a=r.tileID.overscaleFactor();return{u_matrix:t,u_camera_to_center_distance:e.cameraToCenterDistance,u_pixels_to_tile_units:n,u_extrude_scale:[e.pixelsToGLUnits[0]/(n*i),e.pixelsToGLUnits[1]/(n*i)],u_overscale_factor:a}},Pr=function(t,e,r){return{u_matrix:t,u_inv_matrix:e,u_camera_to_center_distance:r.cameraToCenterDistance,u_viewport_size:[r.width,r.height]}},Ir=function(t,e,r){return void 0===r&&(r=1),{u_matrix:t,u_color:e,u_overlay:0,u_overlay_scale:r}},Or=function(t){return{u_matrix:t}},zr=function(t,e,r,n){return{u_matrix:t,u_extrude_scale:pe(e,1,r),u_intensity:n}};function Dr(e,r){var n=Math.pow(2,r.canonical.z),i=r.canonical.y;return[new t.MercatorCoordinate(0,i/n).toLngLat().lat,new t.MercatorCoordinate(0,(i+1)/n).toLngLat().lat]}var Rr=function(e,r,n){var i=e.transform;return{u_matrix:Ur(e,r,n),u_ratio:1/pe(r,1,i.zoom),u_device_pixel_ratio:t.browser.devicePixelRatio,u_units_to_pixels:[1/i.pixelsToGLUnits[0],1/i.pixelsToGLUnits[1]]}},Fr=function(e,r,n){return t.extend(Rr(e,r,n),{u_image:0})},Br=function(e,r,n,i){var a=e.transform,o=jr(r,a);return{u_matrix:Ur(e,r,n),u_texsize:r.imageAtlasTexture.size,u_ratio:1/pe(r,1,a.zoom),u_device_pixel_ratio:t.browser.devicePixelRatio,u_image:0,u_scale:[o,i.fromScale,i.toScale],u_fade:i.t,u_units_to_pixels:[1/a.pixelsToGLUnits[0],1/a.pixelsToGLUnits[1]]}},Nr=function(e,r,n,i,a){var o=e.transform,s=e.lineAtlas,l=jr(r,o),c=\"round\"===n.layout.get(\"line-cap\"),u=s.getDash(i.from,c),f=s.getDash(i.to,c),h=u.width*a.fromScale,p=f.width*a.toScale;return t.extend(Rr(e,r,n),{u_patternscale_a:[l/h,-u.height/2],u_patternscale_b:[l/p,-f.height/2],u_sdfgamma:s.width/(256*Math.min(h,p)*t.browser.devicePixelRatio)/2,u_image:0,u_tex_y_a:u.y,u_tex_y_b:f.y,u_mix:a.t})};function jr(t,e){return 1/pe(t,1,e.tileZoom)}function Ur(t,e,r){return t.translatePosMatrix(e.tileID.posMatrix,e,r.paint.get(\"line-translate\"),r.paint.get(\"line-translate-anchor\"))}var Vr=function(t,e,r,n,i){return{u_matrix:t,u_tl_parent:e,u_scale_parent:r,u_buffer_scale:1,u_fade_t:n.mix,u_opacity:n.opacity*i.paint.get(\"raster-opacity\"),u_image0:0,u_image1:1,u_brightness_low:i.paint.get(\"raster-brightness-min\"),u_brightness_high:i.paint.get(\"raster-brightness-max\"),u_saturation_factor:(o=i.paint.get(\"raster-saturation\"),o>0?1-1/(1.001-o):-o),u_contrast_factor:(a=i.paint.get(\"raster-contrast\"),a>0?1/(1-a):1+a),u_spin_weights:qr(i.paint.get(\"raster-hue-rotate\"))};var a,o};function qr(t){t*=Math.PI/180;var e=Math.sin(t),r=Math.cos(t);return[(2*r+1)/3,(-Math.sqrt(3)*e-r+1)/3,(Math.sqrt(3)*e-r+1)/3]}var Hr,Gr=function(t,e,r,n,i,a,o,s,l,c){var u=i.transform;return{u_is_size_zoom_constant:+(\"constant\"===t||\"source\"===t),u_is_size_feature_constant:+(\"constant\"===t||\"camera\"===t),u_size_t:e?e.uSizeT:0,u_size:e?e.uSize:0,u_camera_to_center_distance:u.cameraToCenterDistance,u_pitch:u.pitch/360*2*Math.PI,u_rotate_symbol:+r,u_aspect_ratio:u.width/u.height,u_fade_change:i.options.fadeDuration?i.symbolFadeChange:1,u_matrix:a,u_label_plane_matrix:o,u_coord_matrix:s,u_is_text:+l,u_pitch_with_map:+n,u_texsize:c,u_texture:0}},Yr=function(e,r,n,i,a,o,s,l,c,u,f){var h=a.transform;return t.extend(Gr(e,r,n,i,a,o,s,l,c,u),{u_gamma_scale:i?Math.cos(h._pitch)*h.cameraToCenterDistance:1,u_device_pixel_ratio:t.browser.devicePixelRatio,u_is_halo:+f})},Wr=function(e,r,n,i,a,o,s,l,c,u){return t.extend(Yr(e,r,n,i,a,o,s,l,!0,c,!0),{u_texsize_icon:u,u_texture_icon:1})},Xr=function(t,e,r){return{u_matrix:t,u_opacity:e,u_color:r}},Zr=function(e,r,n,i,a,o){return t.extend(function(t,e,r,n){var i=r.imageManager.getPattern(t.from.toString()),a=r.imageManager.getPattern(t.to.toString()),o=r.imageManager.getPixelSize(),s=o.width,l=o.height,c=Math.pow(2,n.tileID.overscaledZ),u=n.tileSize*Math.pow(2,r.transform.tileZoom)/c,f=u*(n.tileID.canonical.x+n.tileID.wrap*c),h=u*n.tileID.canonical.y;return{u_image:0,u_pattern_tl_a:i.tl,u_pattern_br_a:i.br,u_pattern_tl_b:a.tl,u_pattern_br_b:a.br,u_texsize:[s,l],u_mix:e.t,u_pattern_size_a:i.displaySize,u_pattern_size_b:a.displaySize,u_scale_a:e.fromScale,u_scale_b:e.toScale,u_tile_units_to_pixels:1/pe(n,1,r.transform.tileZoom),u_pixel_coord_upper:[f>>16,h>>16],u_pixel_coord_lower:[65535&f,65535&h]}}(i,o,n,a),{u_matrix:e,u_opacity:r})},Jr={fillExtrusion:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fillExtrusionPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_height_factor:new t.Uniform1f(e,r.u_height_factor),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fill:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},fillPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},fillOutline:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world)}},fillOutlinePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},circle:function(e,r){return{u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_scale_with_map:new t.Uniform1i(e,r.u_scale_with_map),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},collisionBox:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pixels_to_tile_units:new t.Uniform1f(e,r.u_pixels_to_tile_units),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_overscale_factor:new t.Uniform1f(e,r.u_overscale_factor)}},collisionCircle:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_inv_matrix:new t.UniformMatrix4f(e,r.u_inv_matrix),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_viewport_size:new t.Uniform2f(e,r.u_viewport_size)}},debug:function(e,r){return{u_color:new t.UniformColor(e,r.u_color),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_overlay:new t.Uniform1i(e,r.u_overlay),u_overlay_scale:new t.Uniform1f(e,r.u_overlay_scale)}},clippingMask:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmap:function(e,r){return{u_extrude_scale:new t.Uniform1f(e,r.u_extrude_scale),u_intensity:new t.Uniform1f(e,r.u_intensity),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmapTexture:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_color_ramp:new t.Uniform1i(e,r.u_color_ramp),u_opacity:new t.Uniform1f(e,r.u_opacity)}},hillshade:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_latrange:new t.Uniform2f(e,r.u_latrange),u_light:new t.Uniform2f(e,r.u_light),u_shadow:new t.UniformColor(e,r.u_shadow),u_highlight:new t.UniformColor(e,r.u_highlight),u_accent:new t.UniformColor(e,r.u_accent)}},hillshadePrepare:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_dimension:new t.Uniform2f(e,r.u_dimension),u_zoom:new t.Uniform1f(e,r.u_zoom),u_maxzoom:new t.Uniform1f(e,r.u_maxzoom),u_unpack:new t.Uniform4f(e,r.u_unpack)}},line:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels)}},lineGradient:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_image:new t.Uniform1i(e,r.u_image)}},linePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_texsize:new t.Uniform2f(e,r.u_texsize),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_image:new t.Uniform1i(e,r.u_image),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},lineSDF:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_patternscale_a:new t.Uniform2f(e,r.u_patternscale_a),u_patternscale_b:new t.Uniform2f(e,r.u_patternscale_b),u_sdfgamma:new t.Uniform1f(e,r.u_sdfgamma),u_image:new t.Uniform1i(e,r.u_image),u_tex_y_a:new t.Uniform1f(e,r.u_tex_y_a),u_tex_y_b:new t.Uniform1f(e,r.u_tex_y_b),u_mix:new t.Uniform1f(e,r.u_mix)}},raster:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_tl_parent:new t.Uniform2f(e,r.u_tl_parent),u_scale_parent:new t.Uniform1f(e,r.u_scale_parent),u_buffer_scale:new t.Uniform1f(e,r.u_buffer_scale),u_fade_t:new t.Uniform1f(e,r.u_fade_t),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image0:new t.Uniform1i(e,r.u_image0),u_image1:new t.Uniform1i(e,r.u_image1),u_brightness_low:new t.Uniform1f(e,r.u_brightness_low),u_brightness_high:new t.Uniform1f(e,r.u_brightness_high),u_saturation_factor:new t.Uniform1f(e,r.u_saturation_factor),u_contrast_factor:new t.Uniform1f(e,r.u_contrast_factor),u_spin_weights:new t.Uniform3f(e,r.u_spin_weights)}},symbolIcon:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture)}},symbolSDF:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture),u_gamma_scale:new t.Uniform1f(e,r.u_gamma_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_is_halo:new t.Uniform1i(e,r.u_is_halo)}},symbolTextAndIcon:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texsize_icon:new t.Uniform2f(e,r.u_texsize_icon),u_texture:new t.Uniform1i(e,r.u_texture),u_texture_icon:new t.Uniform1i(e,r.u_texture_icon),u_gamma_scale:new t.Uniform1f(e,r.u_gamma_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_is_halo:new t.Uniform1i(e,r.u_is_halo)}},background:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_color:new t.UniformColor(e,r.u_color)}},backgroundPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image:new t.Uniform1i(e,r.u_image),u_pattern_tl_a:new t.Uniform2f(e,r.u_pattern_tl_a),u_pattern_br_a:new t.Uniform2f(e,r.u_pattern_br_a),u_pattern_tl_b:new t.Uniform2f(e,r.u_pattern_tl_b),u_pattern_br_b:new t.Uniform2f(e,r.u_pattern_br_b),u_texsize:new t.Uniform2f(e,r.u_texsize),u_mix:new t.Uniform1f(e,r.u_mix),u_pattern_size_a:new t.Uniform2f(e,r.u_pattern_size_a),u_pattern_size_b:new t.Uniform2f(e,r.u_pattern_size_b),u_scale_a:new t.Uniform1f(e,r.u_scale_a),u_scale_b:new t.Uniform1f(e,r.u_scale_b),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_tile_units_to_pixels:new t.Uniform1f(e,r.u_tile_units_to_pixels)}}};function Kr(e,r,n,i,a,o,s){for(var l=e.context,c=l.gl,u=e.useProgram(\"collisionBox\"),f=[],h=0,p=0,d=0;d<i.length;d++){var g=i[d],m=r.getTile(g),v=m.getBucket(n);if(v){var y=g.posMatrix;0===a[0]&&0===a[1]||(y=e.translatePosMatrix(g.posMatrix,m,a,o));var x=s?v.textCollisionBox:v.iconCollisionBox,b=v.collisionCircleArray;if(b.length>0){var _=t.create(),w=y;t.mul(_,v.placementInvProjMatrix,e.transform.glCoordMatrix),t.mul(_,_,v.placementViewportMatrix),f.push({circleArray:b,circleOffset:p,transform:w,invTransform:_}),p=h+=b.length/4}x&&u.draw(l,c.LINES,At.disabled,Mt.disabled,e.colorModeForRenderPass(),Et.disabled,Cr(y,e.transform,m),n.id,x.layoutVertexBuffer,x.indexBuffer,x.segments,null,e.transform.zoom,null,null,x.collisionVertexBuffer)}}if(s&&f.length){var T=e.useProgram(\"collisionCircle\"),k=new t.StructArrayLayout2f1f2i16;k.resize(4*h),k._trim();for(var A=0,M=0,S=f;M<S.length;M+=1)for(var E=S[M],L=0;L<E.circleArray.length/4;L++){var C=4*L,P=E.circleArray[C+0],I=E.circleArray[C+1],O=E.circleArray[C+2],z=E.circleArray[C+3];k.emplace(A++,P,I,O,z,0),k.emplace(A++,P,I,O,z,1),k.emplace(A++,P,I,O,z,2),k.emplace(A++,P,I,O,z,3)}(!Hr||Hr.length<2*h)&&(Hr=function(e){var r=2*e,n=new t.StructArrayLayout3ui6;n.resize(r),n._trim();for(var i=0;i<r;i++){var a=6*i;n.uint16[a+0]=4*i+0,n.uint16[a+1]=4*i+1,n.uint16[a+2]=4*i+2,n.uint16[a+3]=4*i+2,n.uint16[a+4]=4*i+3,n.uint16[a+5]=4*i+0}return n}(h));for(var D=l.createIndexBuffer(Hr,!0),R=l.createVertexBuffer(k,t.collisionCircleLayout.members,!0),F=0,B=f;F<B.length;F+=1){var N=B[F],j=Pr(N.transform,N.invTransform,e.transform);T.draw(l,c.TRIANGLES,At.disabled,Mt.disabled,e.colorModeForRenderPass(),Et.disabled,j,n.id,R,D,t.SegmentVector.simpleSegment(0,2*N.circleOffset,N.circleArray.length,N.circleArray.length/2),null,e.transform.zoom,null,null,null)}R.destroy(),D.destroy()}}var Qr=t.identity(new Float32Array(16));function $r(e,r,n,i,a,o){var s=t.getAnchorAlignment(e),l=-(s.horizontalAlign-.5)*r,c=-(s.verticalAlign-.5)*n,u=t.evaluateVariableOffset(e,i);return new t.Point((l/a+u[0])*o,(c/a+u[1])*o)}function tn(e,r,n,i,a,o,s,l,c,u,f){var h=e.text.placedSymbolArray,p=e.text.dynamicLayoutVertexArray,d=e.icon.dynamicLayoutVertexArray,g={};p.clear();for(var m=0;m<h.length;m++){var v=h.get(m),y=e.allowVerticalPlacement&&!v.placedOrientation,x=v.hidden||!v.crossTileID||y?null:i[v.crossTileID];if(x){var b=new t.Point(v.anchorX,v.anchorY),_=te(b,n?l:s),w=ee(o.cameraToCenterDistance,_.signedDistanceFromCamera),T=a.evaluateSizeForFeature(e.textSizeData,u,v)*w/t.ONE_EM;n&&(T*=e.tilePixelRatio/c);for(var k=x.width,A=x.height,M=$r(x.anchor,k,A,x.textOffset,x.textBoxScale,T),S=n?te(b.add(M),s).point:_.point.add(r?M.rotate(-o.angle):M),E=e.allowVerticalPlacement&&v.placedOrientation===t.WritingMode.vertical?Math.PI/2:0,L=0;L<v.numGlyphs;L++)t.addDynamicAttributes(p,S,E);f&&v.associatedIconIndex>=0&&(g[v.associatedIconIndex]={shiftedAnchor:S,angle:E})}else ue(v.numGlyphs,p)}if(f){d.clear();for(var C=e.icon.placedSymbolArray,P=0;P<C.length;P++){var I=C.get(P);if(I.hidden)ue(I.numGlyphs,d);else{var O=g[P];if(O)for(var z=0;z<I.numGlyphs;z++)t.addDynamicAttributes(d,O.shiftedAnchor,O.angle);else ue(I.numGlyphs,d)}}e.icon.dynamicLayoutVertexBuffer.updateData(d)}e.text.dynamicLayoutVertexBuffer.updateData(p)}function en(t,e,r){return r.iconsInText&&e?\"symbolTextAndIcon\":t?\"symbolSDF\":\"symbolIcon\"}function rn(e,r,n,i,a,o,s,l,c,u,f,h){for(var p=e.context,d=p.gl,g=e.transform,m=\"map\"===l,v=\"map\"===c,y=m&&\"point\"!==n.layout.get(\"symbol-placement\"),x=m&&!v&&!y,b=void 0!==n.layout.get(\"symbol-sort-key\").constantOr(1),_=e.depthModeForSublayer(0,At.ReadOnly),w=n.layout.get(\"text-variable-anchor\"),T=[],k=0,A=i;k<A.length;k+=1){var M=A[k],S=r.getTile(M),E=S.getBucket(n);if(E){var L=a?E.text:E.icon;if(L&&L.segments.get().length){var C=L.programConfigurations.get(n.id),P=a||E.sdfIcons,I=a?E.textSizeData:E.iconSizeData,O=v||0!==g.pitch,z=e.useProgram(en(P,a,E),C),D=t.evaluateSizeForZoom(I,g.zoom),R=void 0,F=[0,0],B=void 0,N=void 0,j=null,U=void 0;if(a){if(B=S.glyphAtlasTexture,N=d.LINEAR,R=S.glyphAtlasTexture.size,E.iconsInText){F=S.imageAtlasTexture.size,j=S.imageAtlasTexture;var V=\"composite\"===I.kind||\"camera\"===I.kind;U=O||e.options.rotating||e.options.zooming||V?d.LINEAR:d.NEAREST}}else{var q=1!==n.layout.get(\"icon-size\").constantOr(0)||E.iconsNeedLinear;B=S.imageAtlasTexture,N=P||e.options.rotating||e.options.zooming||q||O?d.LINEAR:d.NEAREST,R=S.imageAtlasTexture.size}var H=pe(S,1,e.transform.zoom),G=Qt(M.posMatrix,v,m,e.transform,H),Y=$t(M.posMatrix,v,m,e.transform,H),W=w&&E.hasTextData(),X=\"none\"!==n.layout.get(\"icon-text-fit\")&&W&&E.hasIconData();y&&ne(E,M.posMatrix,e,a,G,Y,v,u);var Z=e.translatePosMatrix(M.posMatrix,S,o,s),J=y||a&&w||X?Qr:G,K=e.translatePosMatrix(Y,S,o,s,!0),Q=P&&0!==n.paint.get(a?\"text-halo-width\":\"icon-halo-width\").constantOr(1),$={program:z,buffers:L,uniformValues:P?E.iconsInText?Wr(I.kind,D,x,v,e,Z,J,K,R,F):Yr(I.kind,D,x,v,e,Z,J,K,a,R,!0):Gr(I.kind,D,x,v,e,Z,J,K,a,R),atlasTexture:B,atlasTextureIcon:j,atlasInterpolation:N,atlasInterpolationIcon:U,isSDF:P,hasHalo:Q};if(b)for(var tt=0,et=L.segments.get();tt<et.length;tt+=1){var rt=et[tt];T.push({segments:new t.SegmentVector([rt]),sortKey:rt.sortKey,state:$})}else T.push({segments:L.segments,sortKey:0,state:$})}}}b&&T.sort((function(t,e){return t.sortKey-e.sortKey}));for(var nt=0,it=T;nt<it.length;nt+=1){var at=it[nt],ot=at.state;if(p.activeTexture.set(d.TEXTURE0),ot.atlasTexture.bind(ot.atlasInterpolation,d.CLAMP_TO_EDGE),ot.atlasTextureIcon&&(p.activeTexture.set(d.TEXTURE1),ot.atlasTextureIcon&&ot.atlasTextureIcon.bind(ot.atlasInterpolationIcon,d.CLAMP_TO_EDGE)),ot.isSDF){var st=ot.uniformValues;ot.hasHalo&&(st.u_is_halo=1,nn(ot.buffers,at.segments,n,e,ot.program,_,f,h,st)),st.u_is_halo=0}nn(ot.buffers,at.segments,n,e,ot.program,_,f,h,ot.uniformValues)}}function nn(t,e,r,n,i,a,o,s,l){var c=n.context,u=c.gl;i.draw(c,u.TRIANGLES,a,o,s,Et.disabled,l,r.id,t.layoutVertexBuffer,t.indexBuffer,e,r.paint,n.transform.zoom,t.programConfigurations.get(r.id),t.dynamicLayoutVertexBuffer,t.opacityVertexBuffer)}function an(t,e,r,n,i,a,o){var s,l,c,u,f,h=t.context.gl,p=r.paint.get(\"fill-pattern\"),d=p&&p.constantOr(1),g=r.getCrossfadeParameters();o?(l=d&&!r.getPaintProperty(\"fill-outline-color\")?\"fillOutlinePattern\":\"fillOutline\",s=h.LINES):(l=d?\"fillPattern\":\"fill\",s=h.TRIANGLES);for(var m=0,v=n;m<v.length;m+=1){var y=v[m],x=e.getTile(y);if(!d||x.patternsLoaded()){var b=x.getBucket(r);if(b){var _=b.programConfigurations.get(r.id),w=t.useProgram(l,_);d&&(t.context.activeTexture.set(h.TEXTURE0),x.imageAtlasTexture.bind(h.LINEAR,h.CLAMP_TO_EDGE),_.updatePaintBuffers(g));var T=p.constantOr(null);if(T&&x.imageAtlas){var k=x.imageAtlas,A=k.patternPositions[T.to.toString()],M=k.patternPositions[T.from.toString()];A&&M&&_.setConstantPatternPositions(A,M)}var S=t.translatePosMatrix(y.posMatrix,x,r.paint.get(\"fill-translate\"),r.paint.get(\"fill-translate-anchor\"));if(o){u=b.indexBuffer2,f=b.segments2;var E=[h.drawingBufferWidth,h.drawingBufferHeight];c=\"fillOutlinePattern\"===l&&d?Er(S,t,g,x,E):Sr(S,E)}else u=b.indexBuffer,f=b.segments,c=d?Mr(S,t,g,x):Ar(S);w.draw(t.context,s,i,t.stencilModeForClipping(y),a,Et.disabled,c,r.id,b.layoutVertexBuffer,u,f,r.paint,t.transform.zoom,_)}}}}function on(t,e,r,n,i,a,o){for(var s=t.context,l=s.gl,c=r.paint.get(\"fill-extrusion-pattern\"),u=c.constantOr(1),f=r.getCrossfadeParameters(),h=r.paint.get(\"fill-extrusion-opacity\"),p=0,d=n;p<d.length;p+=1){var g=d[p],m=e.getTile(g),v=m.getBucket(r);if(v){var y=v.programConfigurations.get(r.id),x=t.useProgram(u?\"fillExtrusionPattern\":\"fillExtrusion\",y);u&&(t.context.activeTexture.set(l.TEXTURE0),m.imageAtlasTexture.bind(l.LINEAR,l.CLAMP_TO_EDGE),y.updatePaintBuffers(f));var b=c.constantOr(null);if(b&&m.imageAtlas){var _=m.imageAtlas,w=_.patternPositions[b.to.toString()],T=_.patternPositions[b.from.toString()];w&&T&&y.setConstantPatternPositions(w,T)}var k=t.translatePosMatrix(g.posMatrix,m,r.paint.get(\"fill-extrusion-translate\"),r.paint.get(\"fill-extrusion-translate-anchor\")),A=r.paint.get(\"fill-extrusion-vertical-gradient\"),M=u?kr(k,t,A,h,g,f,m):Tr(k,t,A,h);x.draw(s,s.gl.TRIANGLES,i,a,o,Et.backCCW,M,r.id,v.layoutVertexBuffer,v.indexBuffer,v.segments,r.paint,t.transform.zoom,y)}}}function sn(t,e,r,n,i,a){var o=t.context,s=o.gl,l=e.fbo;if(l){var c=t.useProgram(\"hillshade\");o.activeTexture.set(s.TEXTURE0),s.bindTexture(s.TEXTURE_2D,l.colorAttachment.get());var u=function(t,e,r){var n=r.paint.get(\"hillshade-shadow-color\"),i=r.paint.get(\"hillshade-highlight-color\"),a=r.paint.get(\"hillshade-accent-color\"),o=r.paint.get(\"hillshade-illumination-direction\")*(Math.PI/180);\"viewport\"===r.paint.get(\"hillshade-illumination-anchor\")&&(o-=t.transform.angle);var s=!t.options.moving;return{u_matrix:t.transform.calculatePosMatrix(e.tileID.toUnwrapped(),s),u_image:0,u_latrange:Dr(t,e.tileID),u_light:[r.paint.get(\"hillshade-exaggeration\"),o],u_shadow:n,u_highlight:i,u_accent:a}}(t,e,r);c.draw(o,s.TRIANGLES,n,i,a,Et.disabled,u,r.id,t.rasterBoundsBuffer,t.quadTriangleIndexBuffer,t.rasterBoundsSegments)}}function ln(e,r,n,i,a,o,s){var l=e.context,c=l.gl,u=r.dem;if(u&&u.data){var f=u.dim,h=u.stride,p=u.getPixels();if(l.activeTexture.set(c.TEXTURE1),l.pixelStoreUnpackPremultiplyAlpha.set(!1),r.demTexture=r.demTexture||e.getTileTexture(h),r.demTexture){var d=r.demTexture;d.update(p,{premultiply:!1}),d.bind(c.NEAREST,c.CLAMP_TO_EDGE)}else r.demTexture=new t.Texture(l,p,c.RGBA,{premultiply:!1}),r.demTexture.bind(c.NEAREST,c.CLAMP_TO_EDGE);l.activeTexture.set(c.TEXTURE0);var g=r.fbo;if(!g){var m=new t.Texture(l,{width:f,height:f,data:null},c.RGBA);m.bind(c.LINEAR,c.CLAMP_TO_EDGE),(g=r.fbo=l.createFramebuffer(f,f,!0)).colorAttachment.set(m.texture)}l.bindFramebuffer.set(g.framebuffer),l.viewport.set([0,0,f,f]),e.useProgram(\"hillshadePrepare\").draw(l,c.TRIANGLES,a,o,s,Et.disabled,function(e,r,n){var i=r.stride,a=t.create();return t.ortho(a,0,t.EXTENT,-t.EXTENT,0,0,1),t.translate(a,a,[0,-t.EXTENT,0]),{u_matrix:a,u_image:1,u_dimension:[i,i],u_zoom:e.overscaledZ,u_maxzoom:n,u_unpack:r.getUnpackVector()}}(r.tileID,u,i),n.id,e.rasterBoundsBuffer,e.quadTriangleIndexBuffer,e.rasterBoundsSegments),r.needsHillshadePrepare=!1}}function cn(e,r,n,i,a){var o=i.paint.get(\"raster-fade-duration\");if(o>0){var s=t.browser.now(),l=(s-e.timeAdded)/o,c=r?(s-r.timeAdded)/o:-1,u=n.getSource(),f=a.coveringZoomLevel({tileSize:u.tileSize,roundZoom:u.roundZoom}),h=!r||Math.abs(r.tileID.overscaledZ-f)>Math.abs(e.tileID.overscaledZ-f),p=h&&e.refreshedUponExpiration?1:t.clamp(h?l:1-c,0,1);return e.refreshedUponExpiration&&l>=1&&(e.refreshedUponExpiration=!1),r?{opacity:1,mix:1-p}:{opacity:p,mix:0}}return{opacity:1,mix:0}}var un=new t.Color(1,0,0,1),fn=new t.Color(0,1,0,1),hn=new t.Color(0,0,1,1),pn=new t.Color(1,0,1,1),dn=new t.Color(0,1,1,1);function gn(t){var e=t.transform.padding;mn(t,t.transform.height-(e.top||0),3,un),mn(t,e.bottom||0,3,fn),vn(t,e.left||0,3,hn),vn(t,t.transform.width-(e.right||0),3,pn);var r=t.transform.centerPoint;!function(t,e,r,n){yn(t,e-1,r-10,2,20,n),yn(t,e-10,r-1,20,2,n)}(t,r.x,t.transform.height-r.y,dn)}function mn(t,e,r,n){yn(t,0,e+r/2,t.transform.width,r,n)}function vn(t,e,r,n){yn(t,e-r/2,0,r,t.transform.height,n)}function yn(e,r,n,i,a,o){var s=e.context,l=s.gl;l.enable(l.SCISSOR_TEST),l.scissor(r*t.browser.devicePixelRatio,n*t.browser.devicePixelRatio,i*t.browser.devicePixelRatio,a*t.browser.devicePixelRatio),s.clear({color:o}),l.disable(l.SCISSOR_TEST)}function xn(e,r,n){var i=e.context,a=i.gl,o=n.posMatrix,s=e.useProgram(\"debug\"),l=At.disabled,c=Mt.disabled,u=e.colorModeForRenderPass();i.activeTexture.set(a.TEXTURE0),e.emptyTexture.bind(a.LINEAR,a.CLAMP_TO_EDGE),s.draw(i,a.LINE_STRIP,l,c,u,Et.disabled,Ir(o,t.Color.red),\"$debug\",e.debugBuffer,e.tileBorderIndexBuffer,e.debugSegments);var f=r.getTileByID(n.key).latestRawTileData,h=f&&f.byteLength||0,p=Math.floor(h/1024),d=r.getTile(n).tileSize,g=512/Math.min(d,512)*(n.overscaledZ/e.transform.zoom)*.5,m=n.canonical.toString();n.overscaledZ!==n.canonical.z&&(m+=\" => \"+n.overscaledZ),function(t,e){t.initDebugOverlayCanvas();var r=t.debugOverlayCanvas,n=t.context.gl,i=t.debugOverlayCanvas.getContext(\"2d\");i.clearRect(0,0,r.width,r.height),i.shadowColor=\"white\",i.shadowBlur=2,i.lineWidth=1.5,i.strokeStyle=\"white\",i.textBaseline=\"top\",i.font=\"bold 36px Open Sans, sans-serif\",i.fillText(e,5,5),i.strokeText(e,5,5),t.debugOverlayTexture.update(r),t.debugOverlayTexture.bind(n.LINEAR,n.CLAMP_TO_EDGE)}(e,m+\" \"+p+\"kb\"),s.draw(i,a.TRIANGLES,l,c,St.alphaBlended,Et.disabled,Ir(o,t.Color.transparent,g),\"$debug\",e.debugBuffer,e.quadTriangleIndexBuffer,e.debugSegments)}var bn={symbol:function(e,r,n,i,a){if(\"translucent\"===e.renderPass){var o=Mt.disabled,s=e.colorModeForRenderPass();n.layout.get(\"text-variable-anchor\")&&function(e,r,n,i,a,o,s){for(var l=r.transform,c=\"map\"===a,u=\"map\"===o,f=0,h=e;f<h.length;f+=1){var p=h[f],d=i.getTile(p),g=d.getBucket(n);if(g&&g.text&&g.text.segments.get().length){var m=g.textSizeData,v=t.evaluateSizeForZoom(m,l.zoom),y=pe(d,1,r.transform.zoom),x=Qt(p.posMatrix,u,c,r.transform,y),b=\"none\"!==n.layout.get(\"icon-text-fit\")&&g.hasIconData();if(v){var _=Math.pow(2,l.zoom-d.tileID.overscaledZ);tn(g,c,u,s,t.symbolSize,l,x,p.posMatrix,_,v,b)}}}}(i,e,n,r,n.layout.get(\"text-rotation-alignment\"),n.layout.get(\"text-pitch-alignment\"),a),0!==n.paint.get(\"icon-opacity\").constantOr(1)&&rn(e,r,n,i,!1,n.paint.get(\"icon-translate\"),n.paint.get(\"icon-translate-anchor\"),n.layout.get(\"icon-rotation-alignment\"),n.layout.get(\"icon-pitch-alignment\"),n.layout.get(\"icon-keep-upright\"),o,s),0!==n.paint.get(\"text-opacity\").constantOr(1)&&rn(e,r,n,i,!0,n.paint.get(\"text-translate\"),n.paint.get(\"text-translate-anchor\"),n.layout.get(\"text-rotation-alignment\"),n.layout.get(\"text-pitch-alignment\"),n.layout.get(\"text-keep-upright\"),o,s),r.map.showCollisionBoxes&&(Kr(e,r,n,i,n.paint.get(\"text-translate\"),n.paint.get(\"text-translate-anchor\"),!0),Kr(e,r,n,i,n.paint.get(\"icon-translate\"),n.paint.get(\"icon-translate-anchor\"),!1))}},circle:function(e,r,n,i){if(\"translucent\"===e.renderPass){var a=n.paint.get(\"circle-opacity\"),o=n.paint.get(\"circle-stroke-width\"),s=n.paint.get(\"circle-stroke-opacity\"),l=void 0!==n.layout.get(\"circle-sort-key\").constantOr(1);if(0!==a.constantOr(1)||0!==o.constantOr(1)&&0!==s.constantOr(1)){for(var c=e.context,u=c.gl,f=e.depthModeForSublayer(0,At.ReadOnly),h=Mt.disabled,p=e.colorModeForRenderPass(),d=[],g=0;g<i.length;g++){var m=i[g],v=r.getTile(m),y=v.getBucket(n);if(y){var x=y.programConfigurations.get(n.id),b={programConfiguration:x,program:e.useProgram(\"circle\",x),layoutVertexBuffer:y.layoutVertexBuffer,indexBuffer:y.indexBuffer,uniformValues:Lr(e,m,v,n)};if(l)for(var _=0,w=y.segments.get();_<w.length;_+=1){var T=w[_];d.push({segments:new t.SegmentVector([T]),sortKey:T.sortKey,state:b})}else d.push({segments:y.segments,sortKey:0,state:b})}}l&&d.sort((function(t,e){return t.sortKey-e.sortKey}));for(var k=0,A=d;k<A.length;k+=1){var M=A[k],S=M.state,E=S.programConfiguration,L=S.program,C=S.layoutVertexBuffer,P=S.indexBuffer,I=S.uniformValues,O=M.segments;L.draw(c,u.TRIANGLES,f,h,p,Et.disabled,I,n.id,C,P,O,n.paint,e.transform.zoom,E)}}}},heatmap:function(e,r,n,i){if(0!==n.paint.get(\"heatmap-opacity\"))if(\"offscreen\"===e.renderPass){var a=e.context,o=a.gl,s=Mt.disabled,l=new St([o.ONE,o.ONE],t.Color.transparent,[!0,!0,!0,!0]);!function(t,e,r){var n=t.gl;t.activeTexture.set(n.TEXTURE1),t.viewport.set([0,0,e.width/4,e.height/4]);var i=r.heatmapFbo;if(i)n.bindTexture(n.TEXTURE_2D,i.colorAttachment.get()),t.bindFramebuffer.set(i.framebuffer);else{var a=n.createTexture();n.bindTexture(n.TEXTURE_2D,a),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_S,n.CLAMP_TO_EDGE),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_T,n.CLAMP_TO_EDGE),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MIN_FILTER,n.LINEAR),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MAG_FILTER,n.LINEAR),i=r.heatmapFbo=t.createFramebuffer(e.width/4,e.height/4,!1),function(t,e,r,n){var i=t.gl,a=t.extRenderToTextureHalfFloat?t.extTextureHalfFloat.HALF_FLOAT_OES:i.UNSIGNED_BYTE;i.texImage2D(i.TEXTURE_2D,0,i.RGBA,e.width/4,e.height/4,0,i.RGBA,a,null),n.colorAttachment.set(r)}(t,e,a,i)}}(a,e,n),a.clear({color:t.Color.transparent});for(var c=0;c<i.length;c++){var u=i[c];if(!r.hasRenderableParent(u)){var f=r.getTile(u),h=f.getBucket(n);if(h){var p=h.programConfigurations.get(n.id),d=e.useProgram(\"heatmap\",p),g=e.transform.zoom;d.draw(a,o.TRIANGLES,At.disabled,s,l,Et.disabled,zr(u.posMatrix,f,g,n.paint.get(\"heatmap-intensity\")),n.id,h.layoutVertexBuffer,h.indexBuffer,h.segments,n.paint,e.transform.zoom,p)}}}a.viewport.set([0,0,e.width,e.height])}else\"translucent\"===e.renderPass&&(e.context.setColorMode(e.colorModeForRenderPass()),function(e,r){var n=e.context,i=n.gl,a=r.heatmapFbo;if(!a)return;n.activeTexture.set(i.TEXTURE0),i.bindTexture(i.TEXTURE_2D,a.colorAttachment.get()),n.activeTexture.set(i.TEXTURE1);var o=r.colorRampTexture;o||(o=r.colorRampTexture=new t.Texture(n,r.colorRamp,i.RGBA));o.bind(i.LINEAR,i.CLAMP_TO_EDGE),e.useProgram(\"heatmapTexture\").draw(n,i.TRIANGLES,At.disabled,Mt.disabled,e.colorModeForRenderPass(),Et.disabled,function(e,r,n,i){var a=t.create();t.ortho(a,0,e.width,e.height,0,0,1);var o=e.context.gl;return{u_matrix:a,u_world:[o.drawingBufferWidth,o.drawingBufferHeight],u_image:n,u_color_ramp:i,u_opacity:r.paint.get(\"heatmap-opacity\")}}(e,r,0,1),r.id,e.viewportBuffer,e.quadTriangleIndexBuffer,e.viewportSegments,r.paint,e.transform.zoom)}(e,n))},line:function(e,r,n,i){if(\"translucent\"===e.renderPass){var a=n.paint.get(\"line-opacity\"),o=n.paint.get(\"line-width\");if(0!==a.constantOr(1)&&0!==o.constantOr(1)){var s=e.depthModeForSublayer(0,At.ReadOnly),l=e.colorModeForRenderPass(),c=n.paint.get(\"line-dasharray\"),u=n.paint.get(\"line-pattern\"),f=u.constantOr(1),h=n.paint.get(\"line-gradient\"),p=n.getCrossfadeParameters(),d=f?\"linePattern\":c?\"lineSDF\":h?\"lineGradient\":\"line\",g=e.context,m=g.gl,v=!0;if(h){g.activeTexture.set(m.TEXTURE0);var y=n.gradientTexture;if(!n.gradient)return;y||(y=n.gradientTexture=new t.Texture(g,n.gradient,m.RGBA)),y.bind(m.LINEAR,m.CLAMP_TO_EDGE)}for(var x=0,b=i;x<b.length;x+=1){var _=b[x],w=r.getTile(_);if(!f||w.patternsLoaded()){var T=w.getBucket(n);if(T){var k=T.programConfigurations.get(n.id),A=e.context.program.get(),M=e.useProgram(d,k),S=v||M.program!==A,E=u.constantOr(null);if(E&&w.imageAtlas){var L=w.imageAtlas,C=L.patternPositions[E.to.toString()],P=L.patternPositions[E.from.toString()];C&&P&&k.setConstantPatternPositions(C,P)}var I=f?Br(e,w,n,p):c?Nr(e,w,n,c,p):h?Fr(e,w,n):Rr(e,w,n);f?(g.activeTexture.set(m.TEXTURE0),w.imageAtlasTexture.bind(m.LINEAR,m.CLAMP_TO_EDGE),k.updatePaintBuffers(p)):c&&(S||e.lineAtlas.dirty)&&(g.activeTexture.set(m.TEXTURE0),e.lineAtlas.bind(g)),M.draw(g,m.TRIANGLES,s,e.stencilModeForClipping(_),l,Et.disabled,I,n.id,T.layoutVertexBuffer,T.indexBuffer,T.segments,n.paint,e.transform.zoom,k),v=!1}}}}}},fill:function(e,r,n,i){var a=n.paint.get(\"fill-color\"),o=n.paint.get(\"fill-opacity\");if(0!==o.constantOr(1)){var s=e.colorModeForRenderPass(),l=n.paint.get(\"fill-pattern\"),c=e.opaquePassEnabledForLayer()&&!l.constantOr(1)&&1===a.constantOr(t.Color.transparent).a&&1===o.constantOr(0)?\"opaque\":\"translucent\";if(e.renderPass===c){var u=e.depthModeForSublayer(1,\"opaque\"===e.renderPass?At.ReadWrite:At.ReadOnly);an(e,r,n,i,u,s,!1)}if(\"translucent\"===e.renderPass&&n.paint.get(\"fill-antialias\")){var f=e.depthModeForSublayer(n.getPaintProperty(\"fill-outline-color\")?2:0,At.ReadOnly);an(e,r,n,i,f,s,!0)}}},\"fill-extrusion\":function(t,e,r,n){var i=r.paint.get(\"fill-extrusion-opacity\");if(0!==i&&\"translucent\"===t.renderPass){var a=new At(t.context.gl.LEQUAL,At.ReadWrite,t.depthRangeFor3D);if(1!==i||r.paint.get(\"fill-extrusion-pattern\").constantOr(1))on(t,e,r,n,a,Mt.disabled,St.disabled),on(t,e,r,n,a,t.stencilModeFor3D(),t.colorModeForRenderPass());else{var o=t.colorModeForRenderPass();on(t,e,r,n,a,Mt.disabled,o)}}},hillshade:function(t,e,r,n){if(\"offscreen\"===t.renderPass||\"translucent\"===t.renderPass){for(var i=t.context,a=e.getSource().maxzoom,o=t.depthModeForSublayer(0,At.ReadOnly),s=t.colorModeForRenderPass(),l=\"translucent\"===t.renderPass?t.stencilConfigForOverlap(n):[{},n],c=l[0],u=0,f=l[1];u<f.length;u+=1){var h=f[u],p=e.getTile(h);p.needsHillshadePrepare&&\"offscreen\"===t.renderPass?ln(t,p,r,a,o,Mt.disabled,s):\"translucent\"===t.renderPass&&sn(t,p,r,o,c[h.overscaledZ],s)}i.viewport.set([0,0,t.width,t.height])}},raster:function(t,e,r,n){if(\"translucent\"===t.renderPass&&0!==r.paint.get(\"raster-opacity\")&&n.length)for(var i=t.context,a=i.gl,o=e.getSource(),s=t.useProgram(\"raster\"),l=t.colorModeForRenderPass(),c=o instanceof I?[{},n]:t.stencilConfigForOverlap(n),u=c[0],f=c[1],h=f[f.length-1].overscaledZ,p=!t.options.moving,d=0,g=f;d<g.length;d+=1){var m=g[d],v=t.depthModeForSublayer(m.overscaledZ-h,1===r.paint.get(\"raster-opacity\")?At.ReadWrite:At.ReadOnly,a.LESS),y=e.getTile(m),x=t.transform.calculatePosMatrix(m.toUnwrapped(),p);y.registerFadeDuration(r.paint.get(\"raster-fade-duration\"));var b=e.findLoadedParent(m,0),_=cn(y,b,e,r,t.transform),w=void 0,T=void 0,k=\"nearest\"===r.paint.get(\"raster-resampling\")?a.NEAREST:a.LINEAR;i.activeTexture.set(a.TEXTURE0),y.texture.bind(k,a.CLAMP_TO_EDGE,a.LINEAR_MIPMAP_NEAREST),i.activeTexture.set(a.TEXTURE1),b?(b.texture.bind(k,a.CLAMP_TO_EDGE,a.LINEAR_MIPMAP_NEAREST),w=Math.pow(2,b.tileID.overscaledZ-y.tileID.overscaledZ),T=[y.tileID.canonical.x*w%1,y.tileID.canonical.y*w%1]):y.texture.bind(k,a.CLAMP_TO_EDGE,a.LINEAR_MIPMAP_NEAREST);var A=Vr(x,T||[0,0],w||1,_,r);o instanceof I?s.draw(i,a.TRIANGLES,v,Mt.disabled,l,Et.disabled,A,r.id,o.boundsBuffer,t.quadTriangleIndexBuffer,o.boundsSegments):s.draw(i,a.TRIANGLES,v,u[m.overscaledZ],l,Et.disabled,A,r.id,t.rasterBoundsBuffer,t.quadTriangleIndexBuffer,t.rasterBoundsSegments)}},background:function(t,e,r){var n=r.paint.get(\"background-color\"),i=r.paint.get(\"background-opacity\");if(0!==i){var a=t.context,o=a.gl,s=t.transform,l=s.tileSize,c=r.paint.get(\"background-pattern\");if(!t.isPatternMissing(c)){var u=!c&&1===n.a&&1===i&&t.opaquePassEnabledForLayer()?\"opaque\":\"translucent\";if(t.renderPass===u){var f=Mt.disabled,h=t.depthModeForSublayer(0,\"opaque\"===u?At.ReadWrite:At.ReadOnly),p=t.colorModeForRenderPass(),d=t.useProgram(c?\"backgroundPattern\":\"background\"),g=s.coveringTiles({tileSize:l});c&&(a.activeTexture.set(o.TEXTURE0),t.imageManager.bind(t.context));for(var m=r.getCrossfadeParameters(),v=0,y=g;v<y.length;v+=1){var x=y[v],b=t.transform.calculatePosMatrix(x.toUnwrapped()),_=c?Zr(b,i,t,c,{tileID:x,tileSize:l},m):Xr(b,i,n);d.draw(a,o.TRIANGLES,h,f,p,Et.disabled,_,r.id,t.tileExtentBuffer,t.quadTriangleIndexBuffer,t.tileExtentSegments)}}}}},debug:function(t,e,r){for(var n=0;n<r.length;n++)xn(t,e,r[n])},custom:function(t,e,r){var n=t.context,i=r.implementation;if(\"offscreen\"===t.renderPass){var a=i.prerender;a&&(t.setCustomLayerDefaults(),n.setColorMode(t.colorModeForRenderPass()),a.call(i,n.gl,t.transform.customLayerMatrix()),n.setDirty(),t.setBaseState())}else if(\"translucent\"===t.renderPass){t.setCustomLayerDefaults(),n.setColorMode(t.colorModeForRenderPass()),n.setStencilMode(Mt.disabled);var o=\"3d\"===i.renderingMode?new At(t.context.gl.LEQUAL,At.ReadWrite,t.depthRangeFor3D):t.depthModeForSublayer(0,At.ReadOnly);n.setDepthMode(o),i.render(n.gl,t.transform.customLayerMatrix()),n.setDirty(),t.setBaseState(),n.bindFramebuffer.set(null)}}},_n=function(t,e){this.context=new Lt(t),this.transform=e,this._tileTextures={},this.setup(),this.numSublayers=Ct.maxUnderzooming+Ct.maxOverzooming+1,this.depthEpsilon=1/Math.pow(2,16),this.crossTileSymbolIndex=new Ne,this.gpuTimers={}};_n.prototype.resize=function(e,r){if(this.width=e*t.browser.devicePixelRatio,this.height=r*t.browser.devicePixelRatio,this.context.viewport.set([0,0,this.width,this.height]),this.style)for(var n=0,i=this.style._order;n<i.length;n+=1){var a=i[n];this.style._layers[a].resize()}},_n.prototype.setup=function(){var e=this.context,r=new t.StructArrayLayout2i4;r.emplaceBack(0,0),r.emplaceBack(t.EXTENT,0),r.emplaceBack(0,t.EXTENT),r.emplaceBack(t.EXTENT,t.EXTENT),this.tileExtentBuffer=e.createVertexBuffer(r,Ge.members),this.tileExtentSegments=t.SegmentVector.simpleSegment(0,0,4,2);var n=new t.StructArrayLayout2i4;n.emplaceBack(0,0),n.emplaceBack(t.EXTENT,0),n.emplaceBack(0,t.EXTENT),n.emplaceBack(t.EXTENT,t.EXTENT),this.debugBuffer=e.createVertexBuffer(n,Ge.members),this.debugSegments=t.SegmentVector.simpleSegment(0,0,4,5);var i=new t.StructArrayLayout4i8;i.emplaceBack(0,0,0,0),i.emplaceBack(t.EXTENT,0,t.EXTENT,0),i.emplaceBack(0,t.EXTENT,0,t.EXTENT),i.emplaceBack(t.EXTENT,t.EXTENT,t.EXTENT,t.EXTENT),this.rasterBoundsBuffer=e.createVertexBuffer(i,P.members),this.rasterBoundsSegments=t.SegmentVector.simpleSegment(0,0,4,2);var a=new t.StructArrayLayout2i4;a.emplaceBack(0,0),a.emplaceBack(1,0),a.emplaceBack(0,1),a.emplaceBack(1,1),this.viewportBuffer=e.createVertexBuffer(a,Ge.members),this.viewportSegments=t.SegmentVector.simpleSegment(0,0,4,2);var o=new t.StructArrayLayout1ui2;o.emplaceBack(0),o.emplaceBack(1),o.emplaceBack(3),o.emplaceBack(2),o.emplaceBack(0),this.tileBorderIndexBuffer=e.createIndexBuffer(o);var s=new t.StructArrayLayout3ui6;s.emplaceBack(0,1,2),s.emplaceBack(2,1,3),this.quadTriangleIndexBuffer=e.createIndexBuffer(s),this.emptyTexture=new t.Texture(e,{width:1,height:1,data:new Uint8Array([0,0,0,0])},e.gl.RGBA);var l=this.context.gl;this.stencilClearMode=new Mt({func:l.ALWAYS,mask:0},0,255,l.ZERO,l.ZERO,l.ZERO)},_n.prototype.clearStencil=function(){var e=this.context,r=e.gl;this.nextStencilID=1,this.currentStencilSource=void 0;var n=t.create();t.ortho(n,0,this.width,this.height,0,0,1),t.scale(n,n,[r.drawingBufferWidth,r.drawingBufferHeight,0]),this.useProgram(\"clippingMask\").draw(e,r.TRIANGLES,At.disabled,this.stencilClearMode,St.disabled,Et.disabled,Or(n),\"$clipping\",this.viewportBuffer,this.quadTriangleIndexBuffer,this.viewportSegments)},_n.prototype._renderTileClippingMasks=function(t,e){if(this.currentStencilSource!==t.source&&t.isTileClipped()&&e&&e.length){this.currentStencilSource=t.source;var r=this.context,n=r.gl;this.nextStencilID+e.length>256&&this.clearStencil(),r.setColorMode(St.disabled),r.setDepthMode(At.disabled);var i=this.useProgram(\"clippingMask\");this._tileClippingMaskIDs={};for(var a=0,o=e;a<o.length;a+=1){var s=o[a],l=this._tileClippingMaskIDs[s.key]=this.nextStencilID++;i.draw(r,n.TRIANGLES,At.disabled,new Mt({func:n.ALWAYS,mask:0},l,255,n.KEEP,n.KEEP,n.REPLACE),St.disabled,Et.disabled,Or(s.posMatrix),\"$clipping\",this.tileExtentBuffer,this.quadTriangleIndexBuffer,this.tileExtentSegments)}}},_n.prototype.stencilModeFor3D=function(){this.currentStencilSource=void 0,this.nextStencilID+1>256&&this.clearStencil();var t=this.nextStencilID++,e=this.context.gl;return new Mt({func:e.NOTEQUAL,mask:255},t,255,e.KEEP,e.KEEP,e.REPLACE)},_n.prototype.stencilModeForClipping=function(t){var e=this.context.gl;return new Mt({func:e.EQUAL,mask:255},this._tileClippingMaskIDs[t.key],0,e.KEEP,e.KEEP,e.REPLACE)},_n.prototype.stencilConfigForOverlap=function(t){var e,r=this.context.gl,n=t.sort((function(t,e){return e.overscaledZ-t.overscaledZ})),i=n[n.length-1].overscaledZ,a=n[0].overscaledZ-i+1;if(a>1){this.currentStencilSource=void 0,this.nextStencilID+a>256&&this.clearStencil();for(var o={},s=0;s<a;s++)o[s+i]=new Mt({func:r.GEQUAL,mask:255},s+this.nextStencilID,255,r.KEEP,r.KEEP,r.REPLACE);return this.nextStencilID+=a,[o,n]}return[(e={},e[i]=Mt.disabled,e),n]},_n.prototype.colorModeForRenderPass=function(){var e=this.context.gl;if(this._showOverdrawInspector){return new St([e.CONSTANT_COLOR,e.ONE],new t.Color(1/8,1/8,1/8,0),[!0,!0,!0,!0])}return\"opaque\"===this.renderPass?St.unblended:St.alphaBlended},_n.prototype.depthModeForSublayer=function(t,e,r){if(!this.opaquePassEnabledForLayer())return At.disabled;var n=1-((1+this.currentLayer)*this.numSublayers+t)*this.depthEpsilon;return new At(r||this.context.gl.LEQUAL,e,[n,n])},_n.prototype.opaquePassEnabledForLayer=function(){return this.currentLayer<this.opaquePassCutoff},_n.prototype.render=function(e,r){var n=this;this.style=e,this.options=r,this.lineAtlas=e.lineAtlas,this.imageManager=e.imageManager,this.glyphManager=e.glyphManager,this.symbolFadeChange=e.placement.symbolFadeChange(t.browser.now()),this.imageManager.beginFrame();var i=this.style._order,a=this.style.sourceCaches;for(var o in a){var s=a[o];s.used&&s.prepare(this.context)}var l,c,u={},f={},h={};for(var p in a){var d=a[p];u[p]=d.getVisibleCoordinates(),f[p]=u[p].slice().reverse(),h[p]=d.getVisibleCoordinates(!0).reverse()}this.opaquePassCutoff=1/0;for(var g=0;g<i.length;g++){var m=i[g];if(this.style._layers[m].is3D()){this.opaquePassCutoff=g;break}}this.renderPass=\"offscreen\";for(var v=0,y=i;v<y.length;v+=1){var x=y[v],b=this.style._layers[x];if(b.hasOffscreenPass()&&!b.isHidden(this.transform.zoom)){var _=f[b.source];(\"custom\"===b.type||_.length)&&this.renderLayer(this,a[b.source],b,_)}}for(this.context.bindFramebuffer.set(null),this.context.clear({color:r.showOverdrawInspector?t.Color.black:t.Color.transparent,depth:1}),this.clearStencil(),this._showOverdrawInspector=r.showOverdrawInspector,this.depthRangeFor3D=[0,1-(e._order.length+2)*this.numSublayers*this.depthEpsilon],this.renderPass=\"opaque\",this.currentLayer=i.length-1;this.currentLayer>=0;this.currentLayer--){var w=this.style._layers[i[this.currentLayer]],T=a[w.source],k=u[w.source];this._renderTileClippingMasks(w,k),this.renderLayer(this,T,w,k)}for(this.renderPass=\"translucent\",this.currentLayer=0;this.currentLayer<i.length;this.currentLayer++){var A=this.style._layers[i[this.currentLayer]],M=a[A.source],S=(\"symbol\"===A.type?h:f)[A.source];this._renderTileClippingMasks(A,u[A.source]),this.renderLayer(this,M,A,S)}this.options.showTileBoundaries&&(t.values(this.style._layers).forEach((function(t){t.source&&!t.isHidden(n.transform.zoom)&&(t.source!==(c&&c.id)&&(c=n.style.sourceCaches[t.source]),(!l||l.getSource().maxzoom<c.getSource().maxzoom)&&(l=c))})),l&&bn.debug(this,l,l.getVisibleCoordinates()));this.options.showPadding&&gn(this),this.context.setDefault()},_n.prototype.renderLayer=function(t,e,r,n){r.isHidden(this.transform.zoom)||(\"background\"===r.type||\"custom\"===r.type||n.length)&&(this.id=r.id,this.gpuTimingStart(r),bn[r.type](t,e,r,n,this.style.placement.variableOffsets),this.gpuTimingEnd())},_n.prototype.gpuTimingStart=function(t){if(this.options.gpuTiming){var e=this.context.extTimerQuery,r=this.gpuTimers[t.id];r||(r=this.gpuTimers[t.id]={calls:0,cpuTime:0,query:e.createQueryEXT()}),r.calls++,e.beginQueryEXT(e.TIME_ELAPSED_EXT,r.query)}},_n.prototype.gpuTimingEnd=function(){if(this.options.gpuTiming){var t=this.context.extTimerQuery;t.endQueryEXT(t.TIME_ELAPSED_EXT)}},_n.prototype.collectGpuTimers=function(){var t=this.gpuTimers;return this.gpuTimers={},t},_n.prototype.queryGpuTimers=function(t){var e={};for(var r in t){var n=t[r],i=this.context.extTimerQuery,a=i.getQueryObjectEXT(n.query,i.QUERY_RESULT_EXT)/1e6;i.deleteQueryEXT(n.query),e[r]=a}return e},_n.prototype.translatePosMatrix=function(e,r,n,i,a){if(!n[0]&&!n[1])return e;var o=a?\"map\"===i?this.transform.angle:0:\"viewport\"===i?-this.transform.angle:0;if(o){var s=Math.sin(o),l=Math.cos(o);n=[n[0]*l-n[1]*s,n[0]*s+n[1]*l]}var c=[a?n[0]:pe(r,n[0],this.transform.zoom),a?n[1]:pe(r,n[1],this.transform.zoom),0],u=new Float32Array(16);return t.translate(u,e,c),u},_n.prototype.saveTileTexture=function(t){var e=this._tileTextures[t.size[0]];e?e.push(t):this._tileTextures[t.size[0]]=[t]},_n.prototype.getTileTexture=function(t){var e=this._tileTextures[t];return e&&e.length>0?e.pop():null},_n.prototype.isPatternMissing=function(t){if(!t)return!1;if(!t.from||!t.to)return!0;var e=this.imageManager.getPattern(t.from.toString()),r=this.imageManager.getPattern(t.to.toString());return!e||!r},_n.prototype.useProgram=function(t,e){this.cache=this.cache||{};var r=\"\"+t+(e?e.cacheKey:\"\")+(this._showOverdrawInspector?\"/overdraw\":\"\");return this.cache[r]||(this.cache[r]=new _r(this.context,xr[t],e,Jr[t],this._showOverdrawInspector)),this.cache[r]},_n.prototype.setCustomLayerDefaults=function(){this.context.unbindVAO(),this.context.cullFace.setDefault(),this.context.activeTexture.setDefault(),this.context.pixelStoreUnpack.setDefault(),this.context.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.context.pixelStoreUnpackFlipY.setDefault()},_n.prototype.setBaseState=function(){var t=this.context.gl;this.context.cullFace.set(!1),this.context.viewport.set([0,0,this.width,this.height]),this.context.blendEquation.set(t.FUNC_ADD)},_n.prototype.initDebugOverlayCanvas=function(){if(null==this.debugOverlayCanvas){this.debugOverlayCanvas=t.window.document.createElement(\"canvas\"),this.debugOverlayCanvas.width=512,this.debugOverlayCanvas.height=512;var e=this.context.gl;this.debugOverlayTexture=new t.Texture(this.context,this.debugOverlayCanvas,e.RGBA)}},_n.prototype.destroy=function(){this.emptyTexture.destroy(),this.debugOverlayTexture&&this.debugOverlayTexture.destroy()};var wn=function(t,e){this.points=t,this.planes=e};wn.fromInvProjectionMatrix=function(e,r,n){var i=Math.pow(2,n),a=[[-1,1,-1,1],[1,1,-1,1],[1,-1,-1,1],[-1,-1,-1,1],[-1,1,1,1],[1,1,1,1],[1,-1,1,1],[-1,-1,1,1]].map((function(r){return t.transformMat4([],r,e)})).map((function(e){return t.scale$1([],e,1/e[3]/r*i)})),o=[[0,1,2],[6,5,4],[0,3,7],[2,1,5],[3,2,6],[0,4,5]].map((function(e){var r=t.sub([],a[e[0]],a[e[1]]),n=t.sub([],a[e[2]],a[e[1]]),i=t.normalize([],t.cross([],r,n)),o=-t.dot(i,a[e[1]]);return i.concat(o)}));return new wn(a,o)};var Tn=function(e,r){this.min=e,this.max=r,this.center=t.scale$2([],t.add([],this.min,this.max),.5)};Tn.prototype.quadrant=function(e){for(var r=[e%2==0,e<2],n=t.clone$2(this.min),i=t.clone$2(this.max),a=0;a<r.length;a++)n[a]=r[a]?this.min[a]:this.center[a],i[a]=r[a]?this.center[a]:this.max[a];return i[2]=this.max[2],new Tn(n,i)},Tn.prototype.distanceX=function(t){return Math.max(Math.min(this.max[0],t[0]),this.min[0])-t[0]},Tn.prototype.distanceY=function(t){return Math.max(Math.min(this.max[1],t[1]),this.min[1])-t[1]},Tn.prototype.intersects=function(e){for(var r=[[this.min[0],this.min[1],0,1],[this.max[0],this.min[1],0,1],[this.max[0],this.max[1],0,1],[this.min[0],this.max[1],0,1]],n=!0,i=0;i<e.planes.length;i++){for(var a=e.planes[i],o=0,s=0;s<r.length;s++)o+=t.dot$1(a,r[s])>=0;if(0===o)return 0;o!==r.length&&(n=!1)}if(n)return 2;for(var l=0;l<3;l++){for(var c=Number.MAX_VALUE,u=-Number.MAX_VALUE,f=0;f<e.points.length;f++){var h=e.points[f][l]-this.min[l];c=Math.min(c,h),u=Math.max(u,h)}if(u<0||c>this.max[l]-this.min[l])return 0}return 1};var kn=function(t,e,r,n){if(void 0===t&&(t=0),void 0===e&&(e=0),void 0===r&&(r=0),void 0===n&&(n=0),isNaN(t)||t<0||isNaN(e)||e<0||isNaN(r)||r<0||isNaN(n)||n<0)throw new Error(\"Invalid value for edge-insets, top, bottom, left and right must all be numbers\");this.top=t,this.bottom=e,this.left=r,this.right=n};kn.prototype.interpolate=function(e,r,n){return null!=r.top&&null!=e.top&&(this.top=t.number(e.top,r.top,n)),null!=r.bottom&&null!=e.bottom&&(this.bottom=t.number(e.bottom,r.bottom,n)),null!=r.left&&null!=e.left&&(this.left=t.number(e.left,r.left,n)),null!=r.right&&null!=e.right&&(this.right=t.number(e.right,r.right,n)),this},kn.prototype.getCenter=function(e,r){var n=t.clamp((this.left+e-this.right)/2,0,e),i=t.clamp((this.top+r-this.bottom)/2,0,r);return new t.Point(n,i)},kn.prototype.equals=function(t){return this.top===t.top&&this.bottom===t.bottom&&this.left===t.left&&this.right===t.right},kn.prototype.clone=function(){return new kn(this.top,this.bottom,this.left,this.right)},kn.prototype.toJSON=function(){return{top:this.top,bottom:this.bottom,left:this.left,right:this.right}};var An=function(e,r,n,i,a){this.tileSize=512,this.maxValidLatitude=85.051129,this._renderWorldCopies=void 0===a||a,this._minZoom=e||0,this._maxZoom=r||22,this._minPitch=null==n?0:n,this._maxPitch=null==i?60:i,this.setMaxBounds(),this.width=0,this.height=0,this._center=new t.LngLat(0,0),this.zoom=0,this.angle=0,this._fov=.6435011087932844,this._pitch=0,this._unmodified=!0,this._edgeInsets=new kn,this._posMatrixCache={},this._alignedPosMatrixCache={}},Mn={minZoom:{configurable:!0},maxZoom:{configurable:!0},minPitch:{configurable:!0},maxPitch:{configurable:!0},renderWorldCopies:{configurable:!0},worldSize:{configurable:!0},centerOffset:{configurable:!0},size:{configurable:!0},bearing:{configurable:!0},pitch:{configurable:!0},fov:{configurable:!0},zoom:{configurable:!0},center:{configurable:!0},padding:{configurable:!0},centerPoint:{configurable:!0},unmodified:{configurable:!0},point:{configurable:!0}};An.prototype.clone=function(){var t=new An(this._minZoom,this._maxZoom,this._minPitch,this.maxPitch,this._renderWorldCopies);return t.tileSize=this.tileSize,t.latRange=this.latRange,t.width=this.width,t.height=this.height,t._center=this._center,t.zoom=this.zoom,t.angle=this.angle,t._fov=this._fov,t._pitch=this._pitch,t._unmodified=this._unmodified,t._edgeInsets=this._edgeInsets.clone(),t._calcMatrices(),t},Mn.minZoom.get=function(){return this._minZoom},Mn.minZoom.set=function(t){this._minZoom!==t&&(this._minZoom=t,this.zoom=Math.max(this.zoom,t))},Mn.maxZoom.get=function(){return this._maxZoom},Mn.maxZoom.set=function(t){this._maxZoom!==t&&(this._maxZoom=t,this.zoom=Math.min(this.zoom,t))},Mn.minPitch.get=function(){return this._minPitch},Mn.minPitch.set=function(t){this._minPitch!==t&&(this._minPitch=t,this.pitch=Math.max(this.pitch,t))},Mn.maxPitch.get=function(){return this._maxPitch},Mn.maxPitch.set=function(t){this._maxPitch!==t&&(this._maxPitch=t,this.pitch=Math.min(this.pitch,t))},Mn.renderWorldCopies.get=function(){return this._renderWorldCopies},Mn.renderWorldCopies.set=function(t){void 0===t?t=!0:null===t&&(t=!1),this._renderWorldCopies=t},Mn.worldSize.get=function(){return this.tileSize*this.scale},Mn.centerOffset.get=function(){return this.centerPoint._sub(this.size._div(2))},Mn.size.get=function(){return new t.Point(this.width,this.height)},Mn.bearing.get=function(){return-this.angle/Math.PI*180},Mn.bearing.set=function(e){var r=-t.wrap(e,-180,180)*Math.PI/180;this.angle!==r&&(this._unmodified=!1,this.angle=r,this._calcMatrices(),this.rotationMatrix=t.create$2(),t.rotate(this.rotationMatrix,this.rotationMatrix,this.angle))},Mn.pitch.get=function(){return this._pitch/Math.PI*180},Mn.pitch.set=function(e){var r=t.clamp(e,this.minPitch,this.maxPitch)/180*Math.PI;this._pitch!==r&&(this._unmodified=!1,this._pitch=r,this._calcMatrices())},Mn.fov.get=function(){return this._fov/Math.PI*180},Mn.fov.set=function(t){t=Math.max(.01,Math.min(60,t)),this._fov!==t&&(this._unmodified=!1,this._fov=t/180*Math.PI,this._calcMatrices())},Mn.zoom.get=function(){return this._zoom},Mn.zoom.set=function(t){var e=Math.min(Math.max(t,this.minZoom),this.maxZoom);this._zoom!==e&&(this._unmodified=!1,this._zoom=e,this.scale=this.zoomScale(e),this.tileZoom=Math.floor(e),this.zoomFraction=e-this.tileZoom,this._constrain(),this._calcMatrices())},Mn.center.get=function(){return this._center},Mn.center.set=function(t){t.lat===this._center.lat&&t.lng===this._center.lng||(this._unmodified=!1,this._center=t,this._constrain(),this._calcMatrices())},Mn.padding.get=function(){return this._edgeInsets.toJSON()},Mn.padding.set=function(t){this._edgeInsets.equals(t)||(this._unmodified=!1,this._edgeInsets.interpolate(this._edgeInsets,t,1),this._calcMatrices())},Mn.centerPoint.get=function(){return this._edgeInsets.getCenter(this.width,this.height)},An.prototype.isPaddingEqual=function(t){return this._edgeInsets.equals(t)},An.prototype.interpolatePadding=function(t,e,r){this._unmodified=!1,this._edgeInsets.interpolate(t,e,r),this._constrain(),this._calcMatrices()},An.prototype.coveringZoomLevel=function(t){var e=(t.roundZoom?Math.round:Math.floor)(this.zoom+this.scaleZoom(this.tileSize/t.tileSize));return Math.max(0,e)},An.prototype.getVisibleUnwrappedCoordinates=function(e){var r=[new t.UnwrappedTileID(0,e)];if(this._renderWorldCopies)for(var n=this.pointCoordinate(new t.Point(0,0)),i=this.pointCoordinate(new t.Point(this.width,0)),a=this.pointCoordinate(new t.Point(this.width,this.height)),o=this.pointCoordinate(new t.Point(0,this.height)),s=Math.floor(Math.min(n.x,i.x,a.x,o.x)),l=Math.floor(Math.max(n.x,i.x,a.x,o.x)),c=s-1;c<=l+1;c++)0!==c&&r.push(new t.UnwrappedTileID(c,e));return r},An.prototype.coveringTiles=function(e){var r=this.coveringZoomLevel(e),n=r;if(void 0!==e.minzoom&&r<e.minzoom)return[];void 0!==e.maxzoom&&r>e.maxzoom&&(r=e.maxzoom);var i=t.MercatorCoordinate.fromLngLat(this.center),a=Math.pow(2,r),o=[a*i.x,a*i.y,0],s=wn.fromInvProjectionMatrix(this.invProjMatrix,this.worldSize,r),l=e.minzoom||0;this.pitch<=60&&this._edgeInsets.top<.1&&(l=r);var c=function(t){return{aabb:new Tn([t*a,0,0],[(t+1)*a,a,0]),zoom:0,x:0,y:0,wrap:t,fullyVisible:!1}},u=[],f=[],h=r,p=e.reparseOverscaled?n:r;if(this._renderWorldCopies)for(var d=1;d<=3;d++)u.push(c(-d)),u.push(c(d));for(u.push(c(0));u.length>0;){var g=u.pop(),m=g.x,v=g.y,y=g.fullyVisible;if(!y){var x=g.aabb.intersects(s);if(0===x)continue;y=2===x}var b=g.aabb.distanceX(o),_=g.aabb.distanceY(o),w=Math.max(Math.abs(b),Math.abs(_)),T=3+(1<<h-g.zoom)-2;if(g.zoom===h||w>T&&g.zoom>=l)f.push({tileID:new t.OverscaledTileID(g.zoom===h?p:g.zoom,g.wrap,g.zoom,m,v),distanceSq:t.sqrLen([o[0]-.5-m,o[1]-.5-v])});else for(var k=0;k<4;k++){var A=(m<<1)+k%2,M=(v<<1)+(k>>1);u.push({aabb:g.aabb.quadrant(k),zoom:g.zoom+1,x:A,y:M,wrap:g.wrap,fullyVisible:y})}}return f.sort((function(t,e){return t.distanceSq-e.distanceSq})).map((function(t){return t.tileID}))},An.prototype.resize=function(t,e){this.width=t,this.height=e,this.pixelsToGLUnits=[2/t,-2/e],this._constrain(),this._calcMatrices()},Mn.unmodified.get=function(){return this._unmodified},An.prototype.zoomScale=function(t){return Math.pow(2,t)},An.prototype.scaleZoom=function(t){return Math.log(t)/Math.LN2},An.prototype.project=function(e){var r=t.clamp(e.lat,-this.maxValidLatitude,this.maxValidLatitude);return new t.Point(t.mercatorXfromLng(e.lng)*this.worldSize,t.mercatorYfromLat(r)*this.worldSize)},An.prototype.unproject=function(e){return new t.MercatorCoordinate(e.x/this.worldSize,e.y/this.worldSize).toLngLat()},Mn.point.get=function(){return this.project(this.center)},An.prototype.setLocationAtPoint=function(e,r){var n=this.pointCoordinate(r),i=this.pointCoordinate(this.centerPoint),a=this.locationCoordinate(e),o=new t.MercatorCoordinate(a.x-(n.x-i.x),a.y-(n.y-i.y));this.center=this.coordinateLocation(o),this._renderWorldCopies&&(this.center=this.center.wrap())},An.prototype.locationPoint=function(t){return this.coordinatePoint(this.locationCoordinate(t))},An.prototype.pointLocation=function(t){return this.coordinateLocation(this.pointCoordinate(t))},An.prototype.locationCoordinate=function(e){return t.MercatorCoordinate.fromLngLat(e)},An.prototype.coordinateLocation=function(t){return t.toLngLat()},An.prototype.pointCoordinate=function(e){var r=[e.x,e.y,0,1],n=[e.x,e.y,1,1];t.transformMat4(r,r,this.pixelMatrixInverse),t.transformMat4(n,n,this.pixelMatrixInverse);var i=r[3],a=n[3],o=r[0]/i,s=n[0]/a,l=r[1]/i,c=n[1]/a,u=r[2]/i,f=n[2]/a,h=u===f?0:(0-u)/(f-u);return new t.MercatorCoordinate(t.number(o,s,h)/this.worldSize,t.number(l,c,h)/this.worldSize)},An.prototype.coordinatePoint=function(e){var r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix),new t.Point(r[0]/r[3],r[1]/r[3])},An.prototype.getBounds=function(){return(new t.LngLatBounds).extend(this.pointLocation(new t.Point(0,0))).extend(this.pointLocation(new t.Point(this.width,0))).extend(this.pointLocation(new t.Point(this.width,this.height))).extend(this.pointLocation(new t.Point(0,this.height)))},An.prototype.getMaxBounds=function(){return this.latRange&&2===this.latRange.length&&this.lngRange&&2===this.lngRange.length?new t.LngLatBounds([this.lngRange[0],this.latRange[0]],[this.lngRange[1],this.latRange[1]]):null},An.prototype.setMaxBounds=function(t){t?(this.lngRange=[t.getWest(),t.getEast()],this.latRange=[t.getSouth(),t.getNorth()],this._constrain()):(this.lngRange=null,this.latRange=[-this.maxValidLatitude,this.maxValidLatitude])},An.prototype.calculatePosMatrix=function(e,r){void 0===r&&(r=!1);var n=e.key,i=r?this._alignedPosMatrixCache:this._posMatrixCache;if(i[n])return i[n];var a=e.canonical,o=this.worldSize/this.zoomScale(a.z),s=a.x+Math.pow(2,a.z)*e.wrap,l=t.identity(new Float64Array(16));return t.translate(l,l,[s*o,a.y*o,0]),t.scale(l,l,[o/t.EXTENT,o/t.EXTENT,1]),t.multiply(l,r?this.alignedProjMatrix:this.projMatrix,l),i[n]=new Float32Array(l),i[n]},An.prototype.customLayerMatrix=function(){return this.mercatorMatrix.slice()},An.prototype._constrain=function(){if(this.center&&this.width&&this.height&&!this._constraining){this._constraining=!0;var e,r,n,i,a=-90,o=90,s=-180,l=180,c=this.size,u=this._unmodified;if(this.latRange){var f=this.latRange;a=t.mercatorYfromLat(f[1])*this.worldSize,e=(o=t.mercatorYfromLat(f[0])*this.worldSize)-a<c.y?c.y/(o-a):0}if(this.lngRange){var h=this.lngRange;s=t.mercatorXfromLng(h[0])*this.worldSize,r=(l=t.mercatorXfromLng(h[1])*this.worldSize)-s<c.x?c.x/(l-s):0}var p=this.point,d=Math.max(r||0,e||0);if(d)return this.center=this.unproject(new t.Point(r?(l+s)/2:p.x,e?(o+a)/2:p.y)),this.zoom+=this.scaleZoom(d),this._unmodified=u,void(this._constraining=!1);if(this.latRange){var g=p.y,m=c.y/2;g-m<a&&(i=a+m),g+m>o&&(i=o-m)}if(this.lngRange){var v=p.x,y=c.x/2;v-y<s&&(n=s+y),v+y>l&&(n=l-y)}void 0===n&&void 0===i||(this.center=this.unproject(new t.Point(void 0!==n?n:p.x,void 0!==i?i:p.y))),this._unmodified=u,this._constraining=!1}},An.prototype._calcMatrices=function(){if(this.height){var e=this._fov/2,r=this.centerOffset;this.cameraToCenterDistance=.5/Math.tan(e)*this.height;var n=Math.PI/2+this._pitch,i=this._fov*(.5+r.y/this.height),a=Math.sin(i)*this.cameraToCenterDistance/Math.sin(t.clamp(Math.PI-n-i,.01,Math.PI-.01)),o=this.point,s=o.x,l=o.y,c=1.01*(Math.cos(Math.PI/2-this._pitch)*a+this.cameraToCenterDistance),u=this.height/50,f=new Float64Array(16);t.perspective(f,this._fov,this.width/this.height,u,c),f[8]=2*-r.x/this.width,f[9]=2*r.y/this.height,t.scale(f,f,[1,-1,1]),t.translate(f,f,[0,0,-this.cameraToCenterDistance]),t.rotateX(f,f,this._pitch),t.rotateZ(f,f,this.angle),t.translate(f,f,[-s,-l,0]),this.mercatorMatrix=t.scale([],f,[this.worldSize,this.worldSize,this.worldSize]),t.scale(f,f,[1,1,t.mercatorZfromAltitude(1,this.center.lat)*this.worldSize,1]),this.projMatrix=f,this.invProjMatrix=t.invert([],this.projMatrix);var h=this.width%2/2,p=this.height%2/2,d=Math.cos(this.angle),g=Math.sin(this.angle),m=s-Math.round(s)+d*h+g*p,v=l-Math.round(l)+d*p+g*h,y=new Float64Array(f);if(t.translate(y,y,[m>.5?m-1:m,v>.5?v-1:v,0]),this.alignedProjMatrix=y,f=t.create(),t.scale(f,f,[this.width/2,-this.height/2,1]),t.translate(f,f,[1,-1,0]),this.labelPlaneMatrix=f,f=t.create(),t.scale(f,f,[1,-1,1]),t.translate(f,f,[-1,-1,0]),t.scale(f,f,[2/this.width,2/this.height,1]),this.glCoordMatrix=f,this.pixelMatrix=t.multiply(new Float64Array(16),this.labelPlaneMatrix,this.projMatrix),!(f=t.invert(new Float64Array(16),this.pixelMatrix)))throw new Error(\"failed to invert matrix\");this.pixelMatrixInverse=f,this._posMatrixCache={},this._alignedPosMatrixCache={}}},An.prototype.maxPitchScaleFactor=function(){if(!this.pixelMatrixInverse)return 1;var e=this.pointCoordinate(new t.Point(0,0)),r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix)[3]/this.cameraToCenterDistance},An.prototype.getCameraPoint=function(){var e=this._pitch,r=Math.tan(e)*(this.cameraToCenterDistance||1);return this.centerPoint.add(new t.Point(0,r))},An.prototype.getCameraQueryGeometry=function(e){var r=this.getCameraPoint();if(1===e.length)return[e[0],r];for(var n=r.x,i=r.y,a=r.x,o=r.y,s=0,l=e;s<l.length;s+=1){var c=l[s];n=Math.min(n,c.x),i=Math.min(i,c.y),a=Math.max(a,c.x),o=Math.max(o,c.y)}return[new t.Point(n,i),new t.Point(a,i),new t.Point(a,o),new t.Point(n,o),new t.Point(n,i)]},Object.defineProperties(An.prototype,Mn);var Sn=function(e){var r,n,i,a,o;this._hashName=e&&encodeURIComponent(e),t.bindAll([\"_getCurrentHash\",\"_onHashChange\",\"_updateHash\"],this),this._updateHash=(r=this._updateHashUnthrottled.bind(this),n=300,i=!1,a=null,o=function(){a=null,i&&(r(),a=setTimeout(o,n),i=!1)},function(){return i=!0,a||o(),a})};Sn.prototype.addTo=function(e){return this._map=e,t.window.addEventListener(\"hashchange\",this._onHashChange,!1),this._map.on(\"moveend\",this._updateHash),this},Sn.prototype.remove=function(){return t.window.removeEventListener(\"hashchange\",this._onHashChange,!1),this._map.off(\"moveend\",this._updateHash),clearTimeout(this._updateHash()),delete this._map,this},Sn.prototype.getHashString=function(e){var r=this._map.getCenter(),n=Math.round(100*this._map.getZoom())/100,i=Math.ceil((n*Math.LN2+Math.log(512/360/.5))/Math.LN10),a=Math.pow(10,i),o=Math.round(r.lng*a)/a,s=Math.round(r.lat*a)/a,l=this._map.getBearing(),c=this._map.getPitch(),u=\"\";if(u+=e?\"/\"+o+\"/\"+s+\"/\"+n:n+\"/\"+s+\"/\"+o,(l||c)&&(u+=\"/\"+Math.round(10*l)/10),c&&(u+=\"/\"+Math.round(c)),this._hashName){var f=this._hashName,h=!1,p=t.window.location.hash.slice(1).split(\"&\").map((function(t){var e=t.split(\"=\")[0];return e===f?(h=!0,e+\"=\"+u):t})).filter((function(t){return t}));return h||p.push(f+\"=\"+u),\"#\"+p.join(\"&\")}return\"#\"+u},Sn.prototype._getCurrentHash=function(){var e,r=this,n=t.window.location.hash.replace(\"#\",\"\");return this._hashName?(n.split(\"&\").map((function(t){return t.split(\"=\")})).forEach((function(t){t[0]===r._hashName&&(e=t)})),(e&&e[1]||\"\").split(\"/\")):n.split(\"/\")},Sn.prototype._onHashChange=function(){var t=this._getCurrentHash();if(t.length>=3&&!t.some((function(t){return isNaN(t)}))){var e=this._map.dragRotate.isEnabled()&&this._map.touchZoomRotate.isEnabled()?+(t[3]||0):this._map.getBearing();return this._map.jumpTo({center:[+t[2],+t[1]],zoom:+t[0],bearing:e,pitch:+(t[4]||0)}),!0}return!1},Sn.prototype._updateHashUnthrottled=function(){var e=this.getHashString();try{t.window.history.replaceState(t.window.history.state,\"\",e)}catch(t){}};var En={linearity:.3,easing:t.bezier(0,0,.3,1)},Ln=t.extend({deceleration:2500,maxSpeed:1400},En),Cn=t.extend({deceleration:20,maxSpeed:1400},En),Pn=t.extend({deceleration:1e3,maxSpeed:360},En),In=t.extend({deceleration:1e3,maxSpeed:90},En),On=function(t){this._map=t,this.clear()};function zn(t,e){(!t.duration||t.duration<e.duration)&&(t.duration=e.duration,t.easing=e.easing)}function Dn(e,r,n){var i=n.maxSpeed,a=n.linearity,o=n.deceleration,s=t.clamp(e*a/(r/1e3),-i,i),l=Math.abs(s)/(o*a);return{easing:n.easing,duration:1e3*l,amount:s*(l/2)}}On.prototype.clear=function(){this._inertiaBuffer=[]},On.prototype.record=function(e){this._drainInertiaBuffer(),this._inertiaBuffer.push({time:t.browser.now(),settings:e})},On.prototype._drainInertiaBuffer=function(){for(var e=this._inertiaBuffer,r=t.browser.now();e.length>0&&r-e[0].time>160;)e.shift()},On.prototype._onMoveEnd=function(e){if(this._drainInertiaBuffer(),!(this._inertiaBuffer.length<2)){for(var r={zoom:0,bearing:0,pitch:0,pan:new t.Point(0,0),pinchAround:void 0,around:void 0},n=0,i=this._inertiaBuffer;n<i.length;n+=1){var a=i[n].settings;r.zoom+=a.zoomDelta||0,r.bearing+=a.bearingDelta||0,r.pitch+=a.pitchDelta||0,a.panDelta&&r.pan._add(a.panDelta),a.around&&(r.around=a.around),a.pinchAround&&(r.pinchAround=a.pinchAround)}var o=this._inertiaBuffer[this._inertiaBuffer.length-1].time-this._inertiaBuffer[0].time,s={};if(r.pan.mag()){var l=Dn(r.pan.mag(),o,t.extend({},Ln,e||{}));s.offset=r.pan.mult(l.amount/r.pan.mag()),s.center=this._map.transform.center,zn(s,l)}if(r.zoom){var c=Dn(r.zoom,o,Cn);s.zoom=this._map.transform.zoom+c.amount,zn(s,c)}if(r.bearing){var u=Dn(r.bearing,o,Pn);s.bearing=this._map.transform.bearing+t.clamp(u.amount,-179,179),zn(s,u)}if(r.pitch){var f=Dn(r.pitch,o,In);s.pitch=this._map.transform.pitch+f.amount,zn(s,f)}if(s.zoom||s.bearing){var h=void 0===r.pinchAround?r.around:r.pinchAround;s.around=h?this._map.unproject(h):this._map.getCenter()}return this.clear(),t.extend(s,{noMoveStart:!0})}};var Rn=function(e){function n(n,i,a,o){void 0===o&&(o={});var s=r.mousePos(i.getCanvasContainer(),a),l=i.unproject(s);e.call(this,n,t.extend({point:s,lngLat:l,originalEvent:a},o)),this._defaultPrevented=!1,this.target=i}e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n;var i={defaultPrevented:{configurable:!0}};return n.prototype.preventDefault=function(){this._defaultPrevented=!0},i.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(n.prototype,i),n}(t.Event),Fn=function(e){function n(n,i,a){var o=\"touchend\"===n?a.changedTouches:a.touches,s=r.touchPos(i.getCanvasContainer(),o),l=s.map((function(t){return i.unproject(t)})),c=s.reduce((function(t,e,r,n){return t.add(e.div(n.length))}),new t.Point(0,0)),u=i.unproject(c);e.call(this,n,{points:s,point:c,lngLats:l,lngLat:u,originalEvent:a}),this._defaultPrevented=!1}e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n;var i={defaultPrevented:{configurable:!0}};return n.prototype.preventDefault=function(){this._defaultPrevented=!0},i.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(n.prototype,i),n}(t.Event),Bn=function(t){function e(e,r,n){t.call(this,e,{originalEvent:n}),this._defaultPrevented=!1}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={defaultPrevented:{configurable:!0}};return e.prototype.preventDefault=function(){this._defaultPrevented=!0},r.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(e.prototype,r),e}(t.Event),Nn=function(t,e){this._map=t,this._clickTolerance=e.clickTolerance};Nn.prototype.reset=function(){delete this._mousedownPos},Nn.prototype.wheel=function(t){return this._firePreventable(new Bn(t.type,this._map,t))},Nn.prototype.mousedown=function(t,e){return this._mousedownPos=e,this._firePreventable(new Rn(t.type,this._map,t))},Nn.prototype.mouseup=function(t){this._map.fire(new Rn(t.type,this._map,t))},Nn.prototype.click=function(t,e){this._mousedownPos&&this._mousedownPos.dist(e)>=this._clickTolerance||this._map.fire(new Rn(t.type,this._map,t))},Nn.prototype.dblclick=function(t){return this._firePreventable(new Rn(t.type,this._map,t))},Nn.prototype.mouseover=function(t){this._map.fire(new Rn(t.type,this._map,t))},Nn.prototype.mouseout=function(t){this._map.fire(new Rn(t.type,this._map,t))},Nn.prototype.touchstart=function(t){return this._firePreventable(new Fn(t.type,this._map,t))},Nn.prototype.touchmove=function(t){this._map.fire(new Fn(t.type,this._map,t))},Nn.prototype.touchend=function(t){this._map.fire(new Fn(t.type,this._map,t))},Nn.prototype.touchcancel=function(t){this._map.fire(new Fn(t.type,this._map,t))},Nn.prototype._firePreventable=function(t){if(this._map.fire(t),t.defaultPrevented)return{}},Nn.prototype.isEnabled=function(){return!0},Nn.prototype.isActive=function(){return!1},Nn.prototype.enable=function(){},Nn.prototype.disable=function(){};var jn=function(t){this._map=t};jn.prototype.reset=function(){this._delayContextMenu=!1,delete this._contextMenuEvent},jn.prototype.mousemove=function(t){this._map.fire(new Rn(t.type,this._map,t))},jn.prototype.mousedown=function(){this._delayContextMenu=!0},jn.prototype.mouseup=function(){this._delayContextMenu=!1,this._contextMenuEvent&&(this._map.fire(new Rn(\"contextmenu\",this._map,this._contextMenuEvent)),delete this._contextMenuEvent)},jn.prototype.contextmenu=function(t){this._delayContextMenu?this._contextMenuEvent=t:this._map.fire(new Rn(t.type,this._map,t)),this._map.listens(\"contextmenu\")&&t.preventDefault()},jn.prototype.isEnabled=function(){return!0},jn.prototype.isActive=function(){return!1},jn.prototype.enable=function(){},jn.prototype.disable=function(){};var Un=function(t,e){this._map=t,this._el=t.getCanvasContainer(),this._container=t.getContainer(),this._clickTolerance=e.clickTolerance||1};function Vn(t,e){for(var r={},n=0;n<t.length;n++)r[t[n].identifier]=e[n];return r}Un.prototype.isEnabled=function(){return!!this._enabled},Un.prototype.isActive=function(){return!!this._active},Un.prototype.enable=function(){this.isEnabled()||(this._enabled=!0)},Un.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},Un.prototype.mousedown=function(t,e){this.isEnabled()&&t.shiftKey&&0===t.button&&(r.disableDrag(),this._startPos=this._lastPos=e,this._active=!0)},Un.prototype.mousemoveWindow=function(t,e){if(this._active){var n=e;if(!(this._lastPos.equals(n)||!this._box&&n.dist(this._startPos)<this._clickTolerance)){var i=this._startPos;this._lastPos=n,this._box||(this._box=r.create(\"div\",\"mapboxgl-boxzoom\",this._container),this._container.classList.add(\"mapboxgl-crosshair\"),this._fireEvent(\"boxzoomstart\",t));var a=Math.min(i.x,n.x),o=Math.max(i.x,n.x),s=Math.min(i.y,n.y),l=Math.max(i.y,n.y);r.setTransform(this._box,\"translate(\"+a+\"px,\"+s+\"px)\"),this._box.style.width=o-a+\"px\",this._box.style.height=l-s+\"px\"}}},Un.prototype.mouseupWindow=function(e,n){var i=this;if(this._active&&0===e.button){var a=this._startPos,o=n;if(this.reset(),r.suppressClick(),a.x!==o.x||a.y!==o.y)return this._map.fire(new t.Event(\"boxzoomend\",{originalEvent:e})),{cameraAnimation:function(t){return t.fitScreenCoordinates(a,o,i._map.getBearing(),{linear:!0})}};this._fireEvent(\"boxzoomcancel\",e)}},Un.prototype.keydown=function(t){this._active&&27===t.keyCode&&(this.reset(),this._fireEvent(\"boxzoomcancel\",t))},Un.prototype.reset=function(){this._active=!1,this._container.classList.remove(\"mapboxgl-crosshair\"),this._box&&(r.remove(this._box),this._box=null),r.enableDrag(),delete this._startPos,delete this._lastPos},Un.prototype._fireEvent=function(e,r){return this._map.fire(new t.Event(e,{originalEvent:r}))};var qn=function(t){this.reset(),this.numTouches=t.numTouches};qn.prototype.reset=function(){delete this.centroid,delete this.startTime,delete this.touches,this.aborted=!1},qn.prototype.touchstart=function(e,r,n){(this.centroid||n.length>this.numTouches)&&(this.aborted=!0),this.aborted||(void 0===this.startTime&&(this.startTime=e.timeStamp),n.length===this.numTouches&&(this.centroid=function(e){for(var r=new t.Point(0,0),n=0,i=e;n<i.length;n+=1){var a=i[n];r._add(a)}return r.div(e.length)}(r),this.touches=Vn(n,r)))},qn.prototype.touchmove=function(t,e,r){if(!this.aborted&&this.centroid){var n=Vn(r,e);for(var i in this.touches){var a=this.touches[i],o=n[i];(!o||o.dist(a)>30)&&(this.aborted=!0)}}},qn.prototype.touchend=function(t,e,r){if((!this.centroid||t.timeStamp-this.startTime>500)&&(this.aborted=!0),0===r.length){var n=!this.aborted&&this.centroid;if(this.reset(),n)return n}};var Hn=function(t){this.singleTap=new qn(t),this.numTaps=t.numTaps,this.reset()};Hn.prototype.reset=function(){this.lastTime=1/0,delete this.lastTap,this.count=0,this.singleTap.reset()},Hn.prototype.touchstart=function(t,e,r){this.singleTap.touchstart(t,e,r)},Hn.prototype.touchmove=function(t,e,r){this.singleTap.touchmove(t,e,r)},Hn.prototype.touchend=function(t,e,r){var n=this.singleTap.touchend(t,e,r);if(n){var i=t.timeStamp-this.lastTime<500,a=!this.lastTap||this.lastTap.dist(n)<30;if(i&&a||this.reset(),this.count++,this.lastTime=t.timeStamp,this.lastTap=n,this.count===this.numTaps)return this.reset(),n}};var Gn=function(){this._zoomIn=new Hn({numTouches:1,numTaps:2}),this._zoomOut=new Hn({numTouches:2,numTaps:1}),this.reset()};Gn.prototype.reset=function(){this._active=!1,this._zoomIn.reset(),this._zoomOut.reset()},Gn.prototype.touchstart=function(t,e,r){this._zoomIn.touchstart(t,e,r),this._zoomOut.touchstart(t,e,r)},Gn.prototype.touchmove=function(t,e,r){this._zoomIn.touchmove(t,e,r),this._zoomOut.touchmove(t,e,r)},Gn.prototype.touchend=function(t,e,r){var n=this,i=this._zoomIn.touchend(t,e,r),a=this._zoomOut.touchend(t,e,r);return i?(this._active=!0,t.preventDefault(),setTimeout((function(){return n.reset()}),0),{cameraAnimation:function(e){return e.easeTo({duration:300,zoom:e.getZoom()+1,around:e.unproject(i)},{originalEvent:t})}}):a?(this._active=!0,t.preventDefault(),setTimeout((function(){return n.reset()}),0),{cameraAnimation:function(e){return e.easeTo({duration:300,zoom:e.getZoom()-1,around:e.unproject(a)},{originalEvent:t})}}):void 0},Gn.prototype.touchcancel=function(){this.reset()},Gn.prototype.enable=function(){this._enabled=!0},Gn.prototype.disable=function(){this._enabled=!1,this.reset()},Gn.prototype.isEnabled=function(){return this._enabled},Gn.prototype.isActive=function(){return this._active};var Yn=function(t){this.reset(),this._clickTolerance=t.clickTolerance||1};Yn.prototype.reset=function(){this._active=!1,this._moved=!1,delete this._lastPoint,delete this._eventButton},Yn.prototype._correctButton=function(t,e){return!1},Yn.prototype._move=function(t,e){return{}},Yn.prototype.mousedown=function(t,e){if(!this._lastPoint){var n=r.mouseButton(t);this._correctButton(t,n)&&(this._lastPoint=e,this._eventButton=n)}},Yn.prototype.mousemoveWindow=function(t,e){var r=this._lastPoint;if(r&&(t.preventDefault(),this._moved||!(e.dist(r)<this._clickTolerance)))return this._moved=!0,this._lastPoint=e,this._move(r,e)},Yn.prototype.mouseupWindow=function(t){r.mouseButton(t)===this._eventButton&&(this._moved&&r.suppressClick(),this.reset())},Yn.prototype.enable=function(){this._enabled=!0},Yn.prototype.disable=function(){this._enabled=!1,this.reset()},Yn.prototype.isEnabled=function(){return this._enabled},Yn.prototype.isActive=function(){return this._active};var Wn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.mousedown=function(e,r){t.prototype.mousedown.call(this,e,r),this._lastPoint&&(this._active=!0)},e.prototype._correctButton=function(t,e){return 0===e&&!t.ctrlKey},e.prototype._move=function(t,e){return{around:e,panDelta:e.sub(t)}},e}(Yn),Xn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._correctButton=function(t,e){return 0===e&&t.ctrlKey||2===e},e.prototype._move=function(t,e){var r=.8*(e.x-t.x);if(r)return this._active=!0,{bearingDelta:r}},e.prototype.contextmenu=function(t){t.preventDefault()},e}(Yn),Zn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._correctButton=function(t,e){return 0===e&&t.ctrlKey||2===e},e.prototype._move=function(t,e){var r=-.5*(e.y-t.y);if(r)return this._active=!0,{pitchDelta:r}},e.prototype.contextmenu=function(t){t.preventDefault()},e}(Yn),Jn=function(t){this._minTouches=1,this._clickTolerance=t.clickTolerance||1,this.reset()};Jn.prototype.reset=function(){this._active=!1,this._touches={},this._sum=new t.Point(0,0)},Jn.prototype.touchstart=function(t,e,r){return this._calculateTransform(t,e,r)},Jn.prototype.touchmove=function(t,e,r){if(this._active)return t.preventDefault(),this._calculateTransform(t,e,r)},Jn.prototype.touchend=function(t,e,r){this._calculateTransform(t,e,r),this._active&&r.length<this._minTouches&&this.reset()},Jn.prototype.touchcancel=function(){this.reset()},Jn.prototype._calculateTransform=function(e,r,n){n.length>0&&(this._active=!0);var i=Vn(n,r),a=new t.Point(0,0),o=new t.Point(0,0),s=0;for(var l in i){var c=i[l],u=this._touches[l];u&&(a._add(c),o._add(c.sub(u)),s++,i[l]=c)}if(this._touches=i,!(s<this._minTouches)&&o.mag()){var f=o.div(s);if(this._sum._add(f),!(this._sum.mag()<this._clickTolerance))return{around:a.div(s),panDelta:f}}},Jn.prototype.enable=function(){this._enabled=!0},Jn.prototype.disable=function(){this._enabled=!1,this.reset()},Jn.prototype.isEnabled=function(){return this._enabled},Jn.prototype.isActive=function(){return this._active};var Kn=function(){this.reset()};function Qn(t,e,r){for(var n=0;n<t.length;n++)if(t[n].identifier===r)return e[n]}Kn.prototype.reset=function(){this._active=!1,delete this._firstTwoTouches},Kn.prototype._start=function(t){},Kn.prototype._move=function(t,e,r){return{}},Kn.prototype.touchstart=function(t,e,r){this._firstTwoTouches||r.length<2||(this._firstTwoTouches=[r[0].identifier,r[1].identifier],this._start([e[0],e[1]]))},Kn.prototype.touchmove=function(t,e,r){if(this._firstTwoTouches){t.preventDefault();var n=this._firstTwoTouches,i=n[0],a=n[1],o=Qn(r,e,i),s=Qn(r,e,a);if(o&&s){var l=this._aroundCenter?null:o.add(s).div(2);return this._move([o,s],l,t)}}},Kn.prototype.touchend=function(t,e,n){if(this._firstTwoTouches){var i=this._firstTwoTouches,a=i[0],o=i[1],s=Qn(n,e,a),l=Qn(n,e,o);s&&l||(this._active&&r.suppressClick(),this.reset())}},Kn.prototype.touchcancel=function(){this.reset()},Kn.prototype.enable=function(t){this._enabled=!0,this._aroundCenter=!!t&&\"center\"===t.around},Kn.prototype.disable=function(){this._enabled=!1,this.reset()},Kn.prototype.isEnabled=function(){return this._enabled},Kn.prototype.isActive=function(){return this._active};function $n(t,e){return Math.log(t/e)/Math.LN2}var ti=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),delete this._distance,delete this._startDistance},e.prototype._start=function(t){this._startDistance=this._distance=t[0].dist(t[1])},e.prototype._move=function(t,e){var r=this._distance;if(this._distance=t[0].dist(t[1]),this._active||!(Math.abs($n(this._distance,this._startDistance))<.1))return this._active=!0,{zoomDelta:$n(this._distance,r),pinchAround:e}},e}(Kn);function ei(t,e){return 180*t.angleWith(e)/Math.PI}var ri=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),delete this._minDiameter,delete this._startVector,delete this._vector},e.prototype._start=function(t){this._startVector=this._vector=t[0].sub(t[1]),this._minDiameter=t[0].dist(t[1])},e.prototype._move=function(t,e){var r=this._vector;if(this._vector=t[0].sub(t[1]),this._active||!this._isBelowThreshold(this._vector))return this._active=!0,{bearingDelta:ei(this._vector,r),pinchAround:e}},e.prototype._isBelowThreshold=function(t){this._minDiameter=Math.min(this._minDiameter,t.mag());var e=25/(Math.PI*this._minDiameter)*360,r=ei(t,this._startVector);return Math.abs(r)<e},e}(Kn);function ni(t){return Math.abs(t.y)>Math.abs(t.x)}var ii=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),this._valid=void 0,delete this._firstMove,delete this._lastPoints},e.prototype._start=function(t){this._lastPoints=t,ni(t[0].sub(t[1]))&&(this._valid=!1)},e.prototype._move=function(t,e,r){var n=t[0].sub(this._lastPoints[0]),i=t[1].sub(this._lastPoints[1]);if(this._valid=this.gestureBeginsVertically(n,i,r.timeStamp),this._valid){this._lastPoints=t,this._active=!0;return{pitchDelta:-.5*((n.y+i.y)/2)}}},e.prototype.gestureBeginsVertically=function(t,e,r){if(void 0!==this._valid)return this._valid;var n=t.mag()>=2,i=e.mag()>=2;if(n||i){if(!n||!i)return void 0===this._firstMove&&(this._firstMove=r),r-this._firstMove<100&&void 0;var a=t.y>0==e.y>0;return ni(t)&&ni(e)&&a}},e}(Kn),ai={panStep:100,bearingStep:15,pitchStep:10},oi=function(){var t=ai;this._panStep=t.panStep,this._bearingStep=t.bearingStep,this._pitchStep=t.pitchStep};function si(t){return t*(2-t)}oi.prototype.reset=function(){this._active=!1},oi.prototype.keydown=function(t){var e=this;if(!(t.altKey||t.ctrlKey||t.metaKey)){var r=0,n=0,i=0,a=0,o=0;switch(t.keyCode){case 61:case 107:case 171:case 187:r=1;break;case 189:case 109:case 173:r=-1;break;case 37:t.shiftKey?n=-1:(t.preventDefault(),a=-1);break;case 39:t.shiftKey?n=1:(t.preventDefault(),a=1);break;case 38:t.shiftKey?i=1:(t.preventDefault(),o=-1);break;case 40:t.shiftKey?i=-1:(t.preventDefault(),o=1);break;default:return}return{cameraAnimation:function(s){var l=s.getZoom();s.easeTo({duration:300,easeId:\"keyboardHandler\",easing:si,zoom:r?Math.round(l)+r*(t.shiftKey?2:1):l,bearing:s.getBearing()+n*e._bearingStep,pitch:s.getPitch()+i*e._pitchStep,offset:[-a*e._panStep,-o*e._panStep],center:s.getCenter()},{originalEvent:t})}}}},oi.prototype.enable=function(){this._enabled=!0},oi.prototype.disable=function(){this._enabled=!1,this.reset()},oi.prototype.isEnabled=function(){return this._enabled},oi.prototype.isActive=function(){return this._active};var li=function(e,r){this._map=e,this._el=e.getCanvasContainer(),this._handler=r,this._delta=0,this._defaultZoomRate=.01,this._wheelZoomRate=1/450,t.bindAll([\"_onWheel\",\"_onTimeout\",\"_onScrollFrame\",\"_onScrollFinished\"],this)};li.prototype.setZoomRate=function(t){this._defaultZoomRate=t},li.prototype.setWheelZoomRate=function(t){this._wheelZoomRate=t},li.prototype.isEnabled=function(){return!!this._enabled},li.prototype.isActive=function(){return!!this._active||void 0!==this._finishTimeout},li.prototype.isZooming=function(){return!!this._zooming},li.prototype.enable=function(t){this.isEnabled()||(this._enabled=!0,this._aroundCenter=t&&\"center\"===t.around)},li.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},li.prototype.wheel=function(e){if(this.isEnabled()){var r=e.deltaMode===t.window.WheelEvent.DOM_DELTA_LINE?40*e.deltaY:e.deltaY,n=t.browser.now(),i=n-(this._lastWheelEventTime||0);this._lastWheelEventTime=n,0!==r&&r%4.000244140625==0?this._type=\"wheel\":0!==r&&Math.abs(r)<4?this._type=\"trackpad\":i>400?(this._type=null,this._lastValue=r,this._timeout=setTimeout(this._onTimeout,40,e)):this._type||(this._type=Math.abs(i*r)<200?\"trackpad\":\"wheel\",this._timeout&&(clearTimeout(this._timeout),this._timeout=null,r+=this._lastValue)),e.shiftKey&&r&&(r/=4),this._type&&(this._lastWheelEvent=e,this._delta-=r,this._active||this._start(e)),e.preventDefault()}},li.prototype._onTimeout=function(t){this._type=\"wheel\",this._delta-=this._lastValue,this._active||this._start(t)},li.prototype._start=function(e){if(this._delta){this._frameId&&(this._frameId=null),this._active=!0,this.isZooming()||(this._zooming=!0),this._finishTimeout&&(clearTimeout(this._finishTimeout),delete this._finishTimeout);var n=r.mousePos(this._el,e);this._around=t.LngLat.convert(this._aroundCenter?this._map.getCenter():this._map.unproject(n)),this._aroundPoint=this._map.transform.locationPoint(this._around),this._frameId||(this._frameId=!0,this._handler._triggerRenderFrame())}},li.prototype.renderFrame=function(){return this._onScrollFrame()},li.prototype._onScrollFrame=function(){var e=this;if(this._frameId&&(this._frameId=null,this.isActive())){var r=this._map.transform;if(0!==this._delta){var n=\"wheel\"===this._type&&Math.abs(this._delta)>4.000244140625?this._wheelZoomRate:this._defaultZoomRate,i=2/(1+Math.exp(-Math.abs(this._delta*n)));this._delta<0&&0!==i&&(i=1/i);var a=\"number\"==typeof this._targetZoom?r.zoomScale(this._targetZoom):r.scale;this._targetZoom=Math.min(r.maxZoom,Math.max(r.minZoom,r.scaleZoom(a*i))),\"wheel\"===this._type&&(this._startZoom=r.zoom,this._easing=this._smoothOutEasing(200)),this._delta=0}var o,s=\"number\"==typeof this._targetZoom?this._targetZoom:r.zoom,l=this._startZoom,c=this._easing,u=!1;if(\"wheel\"===this._type&&l&&c){var f=Math.min((t.browser.now()-this._lastWheelEventTime)/200,1),h=c(f);o=t.number(l,s,h),f<1?this._frameId||(this._frameId=!0):u=!0}else o=s,u=!0;return this._active=!0,u&&(this._active=!1,this._finishTimeout=setTimeout((function(){e._zooming=!1,e._handler._triggerRenderFrame(),delete e._targetZoom,delete e._finishTimeout}),200)),{noInertia:!0,needsRenderFrame:!u,zoomDelta:o-r.zoom,around:this._aroundPoint,originalEvent:this._lastWheelEvent}}},li.prototype._smoothOutEasing=function(e){var r=t.ease;if(this._prevEase){var n=this._prevEase,i=(t.browser.now()-n.start)/n.duration,a=n.easing(i+.01)-n.easing(i),o=.27/Math.sqrt(a*a+1e-4)*.01,s=Math.sqrt(.0729-o*o);r=t.bezier(o,s,.25,1)}return this._prevEase={start:t.browser.now(),duration:e,easing:r},r},li.prototype.reset=function(){this._active=!1};var ci=function(t,e){this._clickZoom=t,this._tapZoom=e};ci.prototype.enable=function(){this._clickZoom.enable(),this._tapZoom.enable()},ci.prototype.disable=function(){this._clickZoom.disable(),this._tapZoom.disable()},ci.prototype.isEnabled=function(){return this._clickZoom.isEnabled()&&this._tapZoom.isEnabled()},ci.prototype.isActive=function(){return this._clickZoom.isActive()||this._tapZoom.isActive()};var ui=function(){this.reset()};ui.prototype.reset=function(){this._active=!1},ui.prototype.dblclick=function(t,e){return t.preventDefault(),{cameraAnimation:function(r){r.easeTo({duration:300,zoom:r.getZoom()+(t.shiftKey?-1:1),around:r.unproject(e)},{originalEvent:t})}}},ui.prototype.enable=function(){this._enabled=!0},ui.prototype.disable=function(){this._enabled=!1,this.reset()},ui.prototype.isEnabled=function(){return this._enabled},ui.prototype.isActive=function(){return this._active};var fi=function(){this._tap=new Hn({numTouches:1,numTaps:1}),this.reset()};fi.prototype.reset=function(){this._active=!1,delete this._swipePoint,delete this._swipeTouch,delete this._tapTime,this._tap.reset()},fi.prototype.touchstart=function(t,e,r){this._swipePoint||(this._tapTime&&t.timeStamp-this._tapTime>500&&this.reset(),this._tapTime?r.length>0&&(this._swipePoint=e[0],this._swipeTouch=r[0].identifier):this._tap.touchstart(t,e,r))},fi.prototype.touchmove=function(t,e,r){if(this._tapTime){if(this._swipePoint){if(r[0].identifier!==this._swipeTouch)return;var n=e[0],i=n.y-this._swipePoint.y;return this._swipePoint=n,t.preventDefault(),this._active=!0,{zoomDelta:i/128}}}else this._tap.touchmove(t,e,r)},fi.prototype.touchend=function(t,e,r){this._tapTime?this._swipePoint&&0===r.length&&this.reset():this._tap.touchend(t,e,r)&&(this._tapTime=t.timeStamp)},fi.prototype.touchcancel=function(){this.reset()},fi.prototype.enable=function(){this._enabled=!0},fi.prototype.disable=function(){this._enabled=!1,this.reset()},fi.prototype.isEnabled=function(){return this._enabled},fi.prototype.isActive=function(){return this._active};var hi=function(t,e,r){this._el=t,this._mousePan=e,this._touchPan=r};hi.prototype.enable=function(t){this._inertiaOptions=t||{},this._mousePan.enable(),this._touchPan.enable(),this._el.classList.add(\"mapboxgl-touch-drag-pan\")},hi.prototype.disable=function(){this._mousePan.disable(),this._touchPan.disable(),this._el.classList.remove(\"mapboxgl-touch-drag-pan\")},hi.prototype.isEnabled=function(){return this._mousePan.isEnabled()&&this._touchPan.isEnabled()},hi.prototype.isActive=function(){return this._mousePan.isActive()||this._touchPan.isActive()};var pi=function(t,e,r){this._pitchWithRotate=t.pitchWithRotate,this._mouseRotate=e,this._mousePitch=r};pi.prototype.enable=function(){this._mouseRotate.enable(),this._pitchWithRotate&&this._mousePitch.enable()},pi.prototype.disable=function(){this._mouseRotate.disable(),this._mousePitch.disable()},pi.prototype.isEnabled=function(){return this._mouseRotate.isEnabled()&&(!this._pitchWithRotate||this._mousePitch.isEnabled())},pi.prototype.isActive=function(){return this._mouseRotate.isActive()||this._mousePitch.isActive()};var di=function(t,e,r,n){this._el=t,this._touchZoom=e,this._touchRotate=r,this._tapDragZoom=n,this._rotationDisabled=!1,this._enabled=!0};di.prototype.enable=function(t){this._touchZoom.enable(t),this._rotationDisabled||this._touchRotate.enable(t),this._tapDragZoom.enable(),this._el.classList.add(\"mapboxgl-touch-zoom-rotate\")},di.prototype.disable=function(){this._touchZoom.disable(),this._touchRotate.disable(),this._tapDragZoom.disable(),this._el.classList.remove(\"mapboxgl-touch-zoom-rotate\")},di.prototype.isEnabled=function(){return this._touchZoom.isEnabled()&&(this._rotationDisabled||this._touchRotate.isEnabled())&&this._tapDragZoom.isEnabled()},di.prototype.isActive=function(){return this._touchZoom.isActive()||this._touchRotate.isActive()||this._tapDragZoom.isActive()},di.prototype.disableRotation=function(){this._rotationDisabled=!0,this._touchRotate.disable()},di.prototype.enableRotation=function(){this._rotationDisabled=!1,this._touchZoom.isEnabled()&&this._touchRotate.enable()};var gi=function(t){return t.zoom||t.drag||t.pitch||t.rotate},mi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(t.Event);function vi(t){return t.panDelta&&t.panDelta.mag()||t.zoomDelta||t.bearingDelta||t.pitchDelta}var yi=function(e,n){this._map=e,this._el=this._map.getCanvasContainer(),this._handlers=[],this._handlersById={},this._changes=[],this._inertia=new On(e),this._bearingSnap=n.bearingSnap,this._previousActiveHandlers={},this._eventsInProgress={},this._addDefaultHandlers(n),t.bindAll([\"handleEvent\",\"handleWindowEvent\"],this);var i=this._el;this._listeners=[[i,\"touchstart\",{passive:!1}],[i,\"touchmove\",{passive:!1}],[i,\"touchend\",void 0],[i,\"touchcancel\",void 0],[i,\"mousedown\",void 0],[i,\"mousemove\",void 0],[i,\"mouseup\",void 0],[t.window.document,\"mousemove\",{capture:!0}],[t.window.document,\"mouseup\",void 0],[i,\"mouseover\",void 0],[i,\"mouseout\",void 0],[i,\"dblclick\",void 0],[i,\"click\",void 0],[i,\"keydown\",{capture:!1}],[i,\"keyup\",void 0],[i,\"wheel\",{passive:!1}],[i,\"contextmenu\",void 0],[t.window,\"blur\",void 0]];for(var a=0,o=this._listeners;a<o.length;a+=1){var s=o[a],l=s[0],c=s[1],u=s[2];r.addEventListener(l,c,l===t.window.document?this.handleWindowEvent:this.handleEvent,u)}};yi.prototype.destroy=function(){for(var e=0,n=this._listeners;e<n.length;e+=1){var i=n[e],a=i[0],o=i[1],s=i[2];r.removeEventListener(a,o,a===t.window.document?this.handleWindowEvent:this.handleEvent,s)}},yi.prototype._addDefaultHandlers=function(t){var e=this._map,r=e.getCanvasContainer();this._add(\"mapEvent\",new Nn(e,t));var n=e.boxZoom=new Un(e,t);this._add(\"boxZoom\",n);var i=new Gn,a=new ui;e.doubleClickZoom=new ci(a,i),this._add(\"tapZoom\",i),this._add(\"clickZoom\",a);var o=new fi;this._add(\"tapDragZoom\",o);var s=e.touchPitch=new ii;this._add(\"touchPitch\",s);var l=new Xn(t),c=new Zn(t);e.dragRotate=new pi(t,l,c),this._add(\"mouseRotate\",l,[\"mousePitch\"]),this._add(\"mousePitch\",c,[\"mouseRotate\"]);var u=new Wn(t),f=new Jn(t);e.dragPan=new hi(r,u,f),this._add(\"mousePan\",u),this._add(\"touchPan\",f,[\"touchZoom\",\"touchRotate\"]);var h=new ri,p=new ti;e.touchZoomRotate=new di(r,p,h,o),this._add(\"touchRotate\",h,[\"touchPan\",\"touchZoom\"]),this._add(\"touchZoom\",p,[\"touchPan\",\"touchRotate\"]);var d=e.scrollZoom=new li(e,this);this._add(\"scrollZoom\",d,[\"mousePan\"]);var g=e.keyboard=new oi;this._add(\"keyboard\",g),this._add(\"blockableMapEvent\",new jn(e));for(var m=0,v=[\"boxZoom\",\"doubleClickZoom\",\"tapDragZoom\",\"touchPitch\",\"dragRotate\",\"dragPan\",\"touchZoomRotate\",\"scrollZoom\",\"keyboard\"];m<v.length;m+=1){var y=v[m];t.interactive&&t[y]&&e[y].enable(t[y])}},yi.prototype._add=function(t,e,r){this._handlers.push({handlerName:t,handler:e,allowed:r}),this._handlersById[t]=e},yi.prototype.stop=function(){if(!this._updatingCamera){for(var t=0,e=this._handlers;t<e.length;t+=1){e[t].handler.reset()}this._inertia.clear(),this._fireEvents({},{}),this._changes=[]}},yi.prototype.isActive=function(){for(var t=0,e=this._handlers;t<e.length;t+=1){if(e[t].handler.isActive())return!0}return!1},yi.prototype.isZooming=function(){return!!this._eventsInProgress.zoom||this._map.scrollZoom.isZooming()},yi.prototype.isRotating=function(){return!!this._eventsInProgress.rotate},yi.prototype.isMoving=function(){return Boolean(gi(this._eventsInProgress))||this.isZooming()},yi.prototype._blockedByActive=function(t,e,r){for(var n in t)if(n!==r&&(!e||e.indexOf(n)<0))return!0;return!1},yi.prototype.handleWindowEvent=function(t){this.handleEvent(t,t.type+\"Window\")},yi.prototype._getMapTouches=function(t){for(var e=[],r=0,n=t;r<n.length;r+=1){var i=n[r],a=i.target;this._el.contains(a)&&e.push(i)}return e},yi.prototype.handleEvent=function(t,e){if(\"blur\"!==t.type){this._updatingCamera=!0;for(var n=\"renderFrame\"===t.type?void 0:t,i={needsRenderFrame:!1},a={},o={},s=t.touches?this._getMapTouches(t.touches):void 0,l=s?r.touchPos(this._el,s):r.mousePos(this._el,t),c=0,u=this._handlers;c<u.length;c+=1){var f=u[c],h=f.handlerName,p=f.handler,d=f.allowed;if(p.isEnabled()){var g=void 0;this._blockedByActive(o,d,h)?p.reset():p[e||t.type]&&(g=p[e||t.type](t,l,s),this.mergeHandlerResult(i,a,g,h,n),g&&g.needsRenderFrame&&this._triggerRenderFrame()),(g||p.isActive())&&(o[h]=p)}}var m={};for(var v in this._previousActiveHandlers)o[v]||(m[v]=n);this._previousActiveHandlers=o,(Object.keys(m).length||vi(i))&&(this._changes.push([i,a,m]),this._triggerRenderFrame()),(Object.keys(o).length||vi(i))&&this._map._stop(!0),this._updatingCamera=!1;var y=i.cameraAnimation;y&&(this._inertia.clear(),this._fireEvents({},{}),this._changes=[],y(this._map))}else this.stop()},yi.prototype.mergeHandlerResult=function(e,r,n,i,a){if(n){t.extend(e,n);var o={handlerName:i,originalEvent:n.originalEvent||a};void 0!==n.zoomDelta&&(r.zoom=o),void 0!==n.panDelta&&(r.drag=o),void 0!==n.pitchDelta&&(r.pitch=o),void 0!==n.bearingDelta&&(r.rotate=o)}},yi.prototype._applyChanges=function(){for(var e={},r={},n={},i=0,a=this._changes;i<a.length;i+=1){var o=a[i],s=o[0],l=o[1],c=o[2];s.panDelta&&(e.panDelta=(e.panDelta||new t.Point(0,0))._add(s.panDelta)),s.zoomDelta&&(e.zoomDelta=(e.zoomDelta||0)+s.zoomDelta),s.bearingDelta&&(e.bearingDelta=(e.bearingDelta||0)+s.bearingDelta),s.pitchDelta&&(e.pitchDelta=(e.pitchDelta||0)+s.pitchDelta),void 0!==s.around&&(e.around=s.around),void 0!==s.pinchAround&&(e.pinchAround=s.pinchAround),s.noInertia&&(e.noInertia=s.noInertia),t.extend(r,l),t.extend(n,c)}this._updateMapTransform(e,r,n),this._changes=[]},yi.prototype._updateMapTransform=function(t,e,r){var n=this._map,i=n.transform;if(!vi(t))return this._fireEvents(e,r);var a=t.panDelta,o=t.zoomDelta,s=t.bearingDelta,l=t.pitchDelta,c=t.around,u=t.pinchAround;void 0!==u&&(c=u),n._stop(!0),c=c||n.transform.centerPoint;var f=i.pointLocation(a?c.sub(a):c);s&&(i.bearing+=s),l&&(i.pitch+=l),o&&(i.zoom+=o),i.setLocationAtPoint(f,c),this._map._update(),t.noInertia||this._inertia.record(t),this._fireEvents(e,r)},yi.prototype._fireEvents=function(e,r){var n=this,i=gi(this._eventsInProgress),a=gi(e),o={};for(var s in e){var l=e[s].originalEvent;this._eventsInProgress[s]||(o[s+\"start\"]=l),this._eventsInProgress[s]=e[s]}for(var c in!i&&a&&this._fireEvent(\"movestart\",a.originalEvent),o)this._fireEvent(c,o[c]);for(var u in e.rotate&&(this._bearingChanged=!0),a&&this._fireEvent(\"move\",a.originalEvent),e){var f=e[u].originalEvent;this._fireEvent(u,f)}var h,p={};for(var d in this._eventsInProgress){var g=this._eventsInProgress[d],m=g.handlerName,v=g.originalEvent;this._handlersById[m].isActive()||(delete this._eventsInProgress[d],h=r[m]||v,p[d+\"end\"]=h)}for(var y in p)this._fireEvent(y,p[y]);var x=gi(this._eventsInProgress);if((i||a)&&!x){this._updatingCamera=!0;var b=this._inertia._onMoveEnd(this._map.dragPan._inertiaOptions),_=function(t){return 0!==t&&-n._bearingSnap<t&&t<n._bearingSnap};b?(_(b.bearing||this._map.getBearing())&&(b.bearing=0),this._map.easeTo(b,{originalEvent:h})):(this._map.fire(new t.Event(\"moveend\",{originalEvent:h})),_(this._map.getBearing())&&this._map.resetNorth()),this._bearingChanged=!1,this._updatingCamera=!1}},yi.prototype._fireEvent=function(e,r){this._map.fire(new t.Event(e,r?{originalEvent:r}:{}))},yi.prototype._triggerRenderFrame=function(){var t=this;void 0===this._frameId&&(this._frameId=this._map._requestRenderFrame((function(e){delete t._frameId,t.handleEvent(new mi(\"renderFrame\",{timeStamp:e})),t._applyChanges()})))};var xi=function(e){function r(r,n){e.call(this),this._moving=!1,this._zooming=!1,this.transform=r,this._bearingSnap=n.bearingSnap,t.bindAll([\"_renderFrameCallback\"],this)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.getCenter=function(){return new t.LngLat(this.transform.center.lng,this.transform.center.lat)},r.prototype.setCenter=function(t,e){return this.jumpTo({center:t},e)},r.prototype.panBy=function(e,r,n){return e=t.Point.convert(e).mult(-1),this.panTo(this.transform.center,t.extend({offset:e},r),n)},r.prototype.panTo=function(e,r,n){return this.easeTo(t.extend({center:e},r),n)},r.prototype.getZoom=function(){return this.transform.zoom},r.prototype.setZoom=function(t,e){return this.jumpTo({zoom:t},e),this},r.prototype.zoomTo=function(e,r,n){return this.easeTo(t.extend({zoom:e},r),n)},r.prototype.zoomIn=function(t,e){return this.zoomTo(this.getZoom()+1,t,e),this},r.prototype.zoomOut=function(t,e){return this.zoomTo(this.getZoom()-1,t,e),this},r.prototype.getBearing=function(){return this.transform.bearing},r.prototype.setBearing=function(t,e){return this.jumpTo({bearing:t},e),this},r.prototype.getPadding=function(){return this.transform.padding},r.prototype.setPadding=function(t,e){return this.jumpTo({padding:t},e),this},r.prototype.rotateTo=function(e,r,n){return this.easeTo(t.extend({bearing:e},r),n)},r.prototype.resetNorth=function(e,r){return this.rotateTo(0,t.extend({duration:1e3},e),r),this},r.prototype.resetNorthPitch=function(e,r){return this.easeTo(t.extend({bearing:0,pitch:0,duration:1e3},e),r),this},r.prototype.snapToNorth=function(t,e){return Math.abs(this.getBearing())<this._bearingSnap?this.resetNorth(t,e):this},r.prototype.getPitch=function(){return this.transform.pitch},r.prototype.setPitch=function(t,e){return this.jumpTo({pitch:t},e),this},r.prototype.cameraForBounds=function(e,r){return e=t.LngLatBounds.convert(e),this._cameraForBoxAndBearing(e.getNorthWest(),e.getSouthEast(),0,r)},r.prototype._cameraForBoxAndBearing=function(e,r,n,i){var a={top:0,bottom:0,right:0,left:0};if(\"number\"==typeof(i=t.extend({padding:a,offset:[0,0],maxZoom:this.transform.maxZoom},i)).padding){var o=i.padding;i.padding={top:o,bottom:o,right:o,left:o}}i.padding=t.extend(a,i.padding);var s=this.transform,l=s.padding,c=s.project(t.LngLat.convert(e)),u=s.project(t.LngLat.convert(r)),f=c.rotate(-n*Math.PI/180),h=u.rotate(-n*Math.PI/180),p=new t.Point(Math.max(f.x,h.x),Math.max(f.y,h.y)),d=new t.Point(Math.min(f.x,h.x),Math.min(f.y,h.y)),g=p.sub(d),m=(s.width-(l.left+l.right+i.padding.left+i.padding.right))/g.x,v=(s.height-(l.top+l.bottom+i.padding.top+i.padding.bottom))/g.y;if(!(v<0||m<0)){var y=Math.min(s.scaleZoom(s.scale*Math.min(m,v)),i.maxZoom),x=t.Point.convert(i.offset),b=(i.padding.left-i.padding.right)/2,_=(i.padding.top-i.padding.bottom)/2,w=new t.Point(x.x+b,x.y+_).mult(s.scale/s.zoomScale(y));return{center:s.unproject(c.add(u).div(2).sub(w)),zoom:y,bearing:n}}t.warnOnce(\"Map cannot fit within canvas with the given bounds, padding, and/or offset.\")},r.prototype.fitBounds=function(t,e,r){return this._fitInternal(this.cameraForBounds(t,e),e,r)},r.prototype.fitScreenCoordinates=function(e,r,n,i,a){return this._fitInternal(this._cameraForBoxAndBearing(this.transform.pointLocation(t.Point.convert(e)),this.transform.pointLocation(t.Point.convert(r)),n,i),i,a)},r.prototype._fitInternal=function(e,r,n){return e?(delete(r=t.extend(e,r)).padding,r.linear?this.easeTo(r,n):this.flyTo(r,n)):this},r.prototype.jumpTo=function(e,r){this.stop();var n=this.transform,i=!1,a=!1,o=!1;return\"zoom\"in e&&n.zoom!==+e.zoom&&(i=!0,n.zoom=+e.zoom),void 0!==e.center&&(n.center=t.LngLat.convert(e.center)),\"bearing\"in e&&n.bearing!==+e.bearing&&(a=!0,n.bearing=+e.bearing),\"pitch\"in e&&n.pitch!==+e.pitch&&(o=!0,n.pitch=+e.pitch),null==e.padding||n.isPaddingEqual(e.padding)||(n.padding=e.padding),this.fire(new t.Event(\"movestart\",r)).fire(new t.Event(\"move\",r)),i&&this.fire(new t.Event(\"zoomstart\",r)).fire(new t.Event(\"zoom\",r)).fire(new t.Event(\"zoomend\",r)),a&&this.fire(new t.Event(\"rotatestart\",r)).fire(new t.Event(\"rotate\",r)).fire(new t.Event(\"rotateend\",r)),o&&this.fire(new t.Event(\"pitchstart\",r)).fire(new t.Event(\"pitch\",r)).fire(new t.Event(\"pitchend\",r)),this.fire(new t.Event(\"moveend\",r))},r.prototype.easeTo=function(e,r){var n=this;this._stop(!1,e.easeId),(!1===(e=t.extend({offset:[0,0],duration:500,easing:t.ease},e)).animate||!e.essential&&t.browser.prefersReducedMotion)&&(e.duration=0);var i=this.transform,a=this.getZoom(),o=this.getBearing(),s=this.getPitch(),l=this.getPadding(),c=\"zoom\"in e?+e.zoom:a,u=\"bearing\"in e?this._normalizeBearing(e.bearing,o):o,f=\"pitch\"in e?+e.pitch:s,h=\"padding\"in e?e.padding:i.padding,p=t.Point.convert(e.offset),d=i.centerPoint.add(p),g=i.pointLocation(d),m=t.LngLat.convert(e.center||g);this._normalizeCenter(m);var v,y,x=i.project(g),b=i.project(m).sub(x),_=i.zoomScale(c-a);e.around&&(v=t.LngLat.convert(e.around),y=i.locationPoint(v));var w={moving:this._moving,zooming:this._zooming,rotating:this._rotating,pitching:this._pitching};return this._zooming=this._zooming||c!==a,this._rotating=this._rotating||o!==u,this._pitching=this._pitching||f!==s,this._padding=!i.isPaddingEqual(h),this._easeId=e.easeId,this._prepareEase(r,e.noMoveStart,w),clearTimeout(this._easeEndTimeoutID),this._ease((function(e){if(n._zooming&&(i.zoom=t.number(a,c,e)),n._rotating&&(i.bearing=t.number(o,u,e)),n._pitching&&(i.pitch=t.number(s,f,e)),n._padding&&(i.interpolatePadding(l,h,e),d=i.centerPoint.add(p)),v)i.setLocationAtPoint(v,y);else{var g=i.zoomScale(i.zoom-a),m=c>a?Math.min(2,_):Math.max(.5,_),w=Math.pow(m,1-e),T=i.unproject(x.add(b.mult(e*w)).mult(g));i.setLocationAtPoint(i.renderWorldCopies?T.wrap():T,d)}n._fireMoveEvents(r)}),(function(t){n._afterEase(r,t)}),e),this},r.prototype._prepareEase=function(e,r,n){void 0===n&&(n={}),this._moving=!0,r||n.moving||this.fire(new t.Event(\"movestart\",e)),this._zooming&&!n.zooming&&this.fire(new t.Event(\"zoomstart\",e)),this._rotating&&!n.rotating&&this.fire(new t.Event(\"rotatestart\",e)),this._pitching&&!n.pitching&&this.fire(new t.Event(\"pitchstart\",e))},r.prototype._fireMoveEvents=function(e){this.fire(new t.Event(\"move\",e)),this._zooming&&this.fire(new t.Event(\"zoom\",e)),this._rotating&&this.fire(new t.Event(\"rotate\",e)),this._pitching&&this.fire(new t.Event(\"pitch\",e))},r.prototype._afterEase=function(e,r){if(!this._easeId||!r||this._easeId!==r){delete this._easeId;var n=this._zooming,i=this._rotating,a=this._pitching;this._moving=!1,this._zooming=!1,this._rotating=!1,this._pitching=!1,this._padding=!1,n&&this.fire(new t.Event(\"zoomend\",e)),i&&this.fire(new t.Event(\"rotateend\",e)),a&&this.fire(new t.Event(\"pitchend\",e)),this.fire(new t.Event(\"moveend\",e))}},r.prototype.flyTo=function(e,r){var n=this;if(!e.essential&&t.browser.prefersReducedMotion){var i=t.pick(e,[\"center\",\"zoom\",\"bearing\",\"pitch\",\"around\"]);return this.jumpTo(i,r)}this.stop(),e=t.extend({offset:[0,0],speed:1.2,curve:1.42,easing:t.ease},e);var a=this.transform,o=this.getZoom(),s=this.getBearing(),l=this.getPitch(),c=this.getPadding(),u=\"zoom\"in e?t.clamp(+e.zoom,a.minZoom,a.maxZoom):o,f=\"bearing\"in e?this._normalizeBearing(e.bearing,s):s,h=\"pitch\"in e?+e.pitch:l,p=\"padding\"in e?e.padding:a.padding,d=a.zoomScale(u-o),g=t.Point.convert(e.offset),m=a.centerPoint.add(g),v=a.pointLocation(m),y=t.LngLat.convert(e.center||v);this._normalizeCenter(y);var x=a.project(v),b=a.project(y).sub(x),_=e.curve,w=Math.max(a.width,a.height),T=w/d,k=b.mag();if(\"minZoom\"in e){var A=t.clamp(Math.min(e.minZoom,o,u),a.minZoom,a.maxZoom),M=w/a.zoomScale(A-o);_=Math.sqrt(M/k*2)}var S=_*_;function E(t){var e=(T*T-w*w+(t?-1:1)*S*S*k*k)/(2*(t?T:w)*S*k);return Math.log(Math.sqrt(e*e+1)-e)}function L(t){return(Math.exp(t)-Math.exp(-t))/2}function C(t){return(Math.exp(t)+Math.exp(-t))/2}var P=E(0),I=function(t){return C(P)/C(P+_*t)},O=function(t){return w*((C(P)*(L(e=P+_*t)/C(e))-L(P))/S)/k;var e},z=(E(1)-P)/_;if(Math.abs(k)<1e-6||!isFinite(z)){if(Math.abs(w-T)<1e-6)return this.easeTo(e,r);var D=T<w?-1:1;z=Math.abs(Math.log(T/w))/_,O=function(){return 0},I=function(t){return Math.exp(D*_*t)}}if(\"duration\"in e)e.duration=+e.duration;else{var R=\"screenSpeed\"in e?+e.screenSpeed/_:+e.speed;e.duration=1e3*z/R}return e.maxDuration&&e.duration>e.maxDuration&&(e.duration=0),this._zooming=!0,this._rotating=s!==f,this._pitching=h!==l,this._padding=!a.isPaddingEqual(p),this._prepareEase(r,!1),this._ease((function(e){var i=e*z,d=1/I(i);a.zoom=1===e?u:o+a.scaleZoom(d),n._rotating&&(a.bearing=t.number(s,f,e)),n._pitching&&(a.pitch=t.number(l,h,e)),n._padding&&(a.interpolatePadding(c,p,e),m=a.centerPoint.add(g));var v=1===e?y:a.unproject(x.add(b.mult(O(i))).mult(d));a.setLocationAtPoint(a.renderWorldCopies?v.wrap():v,m),n._fireMoveEvents(r)}),(function(){return n._afterEase(r)}),e),this},r.prototype.isEasing=function(){return!!this._easeFrameId},r.prototype.stop=function(){return this._stop()},r.prototype._stop=function(t,e){if(this._easeFrameId&&(this._cancelRenderFrame(this._easeFrameId),delete this._easeFrameId,delete this._onEaseFrame),this._onEaseEnd){var r=this._onEaseEnd;delete this._onEaseEnd,r.call(this,e)}if(!t){var n=this.handlers;n&&n.stop()}return this},r.prototype._ease=function(e,r,n){!1===n.animate||0===n.duration?(e(1),r()):(this._easeStart=t.browser.now(),this._easeOptions=n,this._onEaseFrame=e,this._onEaseEnd=r,this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback))},r.prototype._renderFrameCallback=function(){var e=Math.min((t.browser.now()-this._easeStart)/this._easeOptions.duration,1);this._onEaseFrame(this._easeOptions.easing(e)),e<1?this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback):this.stop()},r.prototype._normalizeBearing=function(e,r){e=t.wrap(e,-180,180);var n=Math.abs(e-r);return Math.abs(e-360-r)<n&&(e-=360),Math.abs(e+360-r)<n&&(e+=360),e},r.prototype._normalizeCenter=function(t){var e=this.transform;if(e.renderWorldCopies&&!e.lngRange){var r=t.lng-e.center.lng;t.lng+=r>180?-360:r<-180?360:0}},r}(t.Evented),bi=function(e){void 0===e&&(e={}),this.options=e,t.bindAll([\"_updateEditLink\",\"_updateData\",\"_updateCompact\"],this)};bi.prototype.getDefaultPosition=function(){return\"bottom-right\"},bi.prototype.onAdd=function(t){var e=this.options&&this.options.compact;return this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-attrib\"),this._innerContainer=r.create(\"div\",\"mapboxgl-ctrl-attrib-inner\",this._container),e&&this._container.classList.add(\"mapboxgl-compact\"),this._updateAttributions(),this._updateEditLink(),this._map.on(\"styledata\",this._updateData),this._map.on(\"sourcedata\",this._updateData),this._map.on(\"moveend\",this._updateEditLink),void 0===e&&(this._map.on(\"resize\",this._updateCompact),this._updateCompact()),this._container},bi.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"styledata\",this._updateData),this._map.off(\"sourcedata\",this._updateData),this._map.off(\"moveend\",this._updateEditLink),this._map.off(\"resize\",this._updateCompact),this._map=void 0,this._attribHTML=void 0},bi.prototype._updateEditLink=function(){var e=this._editLink;e||(e=this._editLink=this._container.querySelector(\".mapbox-improve-map\"));var r=[{key:\"owner\",value:this.styleOwner},{key:\"id\",value:this.styleId},{key:\"access_token\",value:this._map._requestManager._customAccessToken||t.config.ACCESS_TOKEN}];if(e){var n=r.reduce((function(t,e,n){return e.value&&(t+=e.key+\"=\"+e.value+(n<r.length-1?\"&\":\"\")),t}),\"?\");e.href=t.config.FEEDBACK_URL+\"/\"+n+(this._map._hash?this._map._hash.getHashString(!0):\"\"),e.rel=\"noopener nofollow\"}},bi.prototype._updateData=function(t){!t||\"metadata\"!==t.sourceDataType&&\"style\"!==t.dataType||(this._updateAttributions(),this._updateEditLink())},bi.prototype._updateAttributions=function(){if(this._map.style){var t=[];if(this.options.customAttribution&&(Array.isArray(this.options.customAttribution)?t=t.concat(this.options.customAttribution.map((function(t){return\"string\"!=typeof t?\"\":t}))):\"string\"==typeof this.options.customAttribution&&t.push(this.options.customAttribution)),this._map.style.stylesheet){var e=this._map.style.stylesheet;this.styleOwner=e.owner,this.styleId=e.id}var r=this._map.style.sourceCaches;for(var n in r){var i=r[n];if(i.used){var a=i.getSource();a.attribution&&t.indexOf(a.attribution)<0&&t.push(a.attribution)}}t.sort((function(t,e){return t.length-e.length}));var o=(t=t.filter((function(e,r){for(var n=r+1;n<t.length;n++)if(t[n].indexOf(e)>=0)return!1;return!0}))).join(\" | \");o!==this._attribHTML&&(this._attribHTML=o,t.length?(this._innerContainer.innerHTML=o,this._container.classList.remove(\"mapboxgl-attrib-empty\")):this._container.classList.add(\"mapboxgl-attrib-empty\"),this._editLink=null)}},bi.prototype._updateCompact=function(){this._map.getCanvasContainer().offsetWidth<=640?this._container.classList.add(\"mapboxgl-compact\"):this._container.classList.remove(\"mapboxgl-compact\")};var _i=function(){t.bindAll([\"_updateLogo\"],this),t.bindAll([\"_updateCompact\"],this)};_i.prototype.onAdd=function(t){this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl\");var e=r.create(\"a\",\"mapboxgl-ctrl-logo\");return e.target=\"_blank\",e.rel=\"noopener nofollow\",e.href=\"https://www.mapbox.com/\",e.setAttribute(\"aria-label\",this._map._getUIString(\"LogoControl.Title\")),e.setAttribute(\"rel\",\"noopener nofollow\"),this._container.appendChild(e),this._container.style.display=\"none\",this._map.on(\"sourcedata\",this._updateLogo),this._updateLogo(),this._map.on(\"resize\",this._updateCompact),this._updateCompact(),this._container},_i.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"sourcedata\",this._updateLogo),this._map.off(\"resize\",this._updateCompact)},_i.prototype.getDefaultPosition=function(){return\"bottom-left\"},_i.prototype._updateLogo=function(t){t&&\"metadata\"!==t.sourceDataType||(this._container.style.display=this._logoRequired()?\"block\":\"none\")},_i.prototype._logoRequired=function(){if(this._map.style){var t=this._map.style.sourceCaches;for(var e in t){if(t[e].getSource().mapbox_logo)return!0}return!1}},_i.prototype._updateCompact=function(){var t=this._container.children;if(t.length){var e=t[0];this._map.getCanvasContainer().offsetWidth<250?e.classList.add(\"mapboxgl-compact\"):e.classList.remove(\"mapboxgl-compact\")}};var wi=function(){this._queue=[],this._id=0,this._cleared=!1,this._currentlyRunning=!1};wi.prototype.add=function(t){var e=++this._id;return this._queue.push({callback:t,id:e,cancelled:!1}),e},wi.prototype.remove=function(t){for(var e=this._currentlyRunning,r=0,n=e?this._queue.concat(e):this._queue;r<n.length;r+=1){var i=n[r];if(i.id===t)return void(i.cancelled=!0)}},wi.prototype.run=function(t){void 0===t&&(t=0);var e=this._currentlyRunning=this._queue;this._queue=[];for(var r=0,n=e;r<n.length;r+=1){var i=n[r];if(!i.cancelled&&(i.callback(t),this._cleared))break}this._cleared=!1,this._currentlyRunning=!1},wi.prototype.clear=function(){this._currentlyRunning&&(this._cleared=!0),this._queue=[]};var Ti={\"FullscreenControl.Enter\":\"Enter fullscreen\",\"FullscreenControl.Exit\":\"Exit fullscreen\",\"GeolocateControl.FindMyLocation\":\"Find my location\",\"GeolocateControl.LocationNotAvailable\":\"Location not available\",\"LogoControl.Title\":\"Mapbox logo\",\"NavigationControl.ResetBearing\":\"Reset bearing to north\",\"NavigationControl.ZoomIn\":\"Zoom in\",\"NavigationControl.ZoomOut\":\"Zoom out\",\"ScaleControl.Feet\":\"ft\",\"ScaleControl.Meters\":\"m\",\"ScaleControl.Kilometers\":\"km\",\"ScaleControl.Miles\":\"mi\",\"ScaleControl.NauticalMiles\":\"nm\"},ki=t.window.HTMLImageElement,Ai=t.window.HTMLElement,Mi=t.window.ImageBitmap,Si={center:[0,0],zoom:0,bearing:0,pitch:0,minZoom:-2,maxZoom:22,minPitch:0,maxPitch:60,interactive:!0,scrollZoom:!0,boxZoom:!0,dragRotate:!0,dragPan:!0,keyboard:!0,doubleClickZoom:!0,touchZoomRotate:!0,touchPitch:!0,bearingSnap:7,clickTolerance:3,pitchWithRotate:!0,hash:!1,attributionControl:!0,failIfMajorPerformanceCaveat:!1,preserveDrawingBuffer:!1,trackResize:!0,renderWorldCopies:!0,refreshExpiredTiles:!0,maxTileCacheSize:null,localIdeographFontFamily:\"sans-serif\",transformRequest:null,accessToken:null,fadeDuration:300,crossSourceCollisions:!0},Ei=function(n){function i(e){var r=this;if(null!=(e=t.extend({},Si,e)).minZoom&&null!=e.maxZoom&&e.minZoom>e.maxZoom)throw new Error(\"maxZoom must be greater than or equal to minZoom\");if(null!=e.minPitch&&null!=e.maxPitch&&e.minPitch>e.maxPitch)throw new Error(\"maxPitch must be greater than or equal to minPitch\");if(null!=e.minPitch&&e.minPitch<0)throw new Error(\"minPitch must be greater than or equal to 0\");if(null!=e.maxPitch&&e.maxPitch>60)throw new Error(\"maxPitch must be less than or equal to 60\");var i=new An(e.minZoom,e.maxZoom,e.minPitch,e.maxPitch,e.renderWorldCopies);if(n.call(this,i,e),this._interactive=e.interactive,this._maxTileCacheSize=e.maxTileCacheSize,this._failIfMajorPerformanceCaveat=e.failIfMajorPerformanceCaveat,this._preserveDrawingBuffer=e.preserveDrawingBuffer,this._antialias=e.antialias,this._trackResize=e.trackResize,this._bearingSnap=e.bearingSnap,this._refreshExpiredTiles=e.refreshExpiredTiles,this._fadeDuration=e.fadeDuration,this._crossSourceCollisions=e.crossSourceCollisions,this._crossFadingFactor=1,this._collectResourceTiming=e.collectResourceTiming,this._renderTaskQueue=new wi,this._controls=[],this._mapId=t.uniqueId(),this._locale=t.extend({},Ti,e.locale),this._requestManager=new t.RequestManager(e.transformRequest,e.accessToken),\"string\"==typeof e.container){if(this._container=t.window.document.getElementById(e.container),!this._container)throw new Error(\"Container '\"+e.container+\"' not found.\")}else{if(!(e.container instanceof Ai))throw new Error(\"Invalid type: 'container' must be a String or HTMLElement.\");this._container=e.container}if(e.maxBounds&&this.setMaxBounds(e.maxBounds),t.bindAll([\"_onWindowOnline\",\"_onWindowResize\",\"_contextLost\",\"_contextRestored\"],this),this._setupContainer(),this._setupPainter(),void 0===this.painter)throw new Error(\"Failed to initialize WebGL.\");this.on(\"move\",(function(){return r._update(!1)})),this.on(\"moveend\",(function(){return r._update(!1)})),this.on(\"zoom\",(function(){return r._update(!0)})),void 0!==t.window&&(t.window.addEventListener(\"online\",this._onWindowOnline,!1),t.window.addEventListener(\"resize\",this._onWindowResize,!1)),this.handlers=new yi(this,e);var a=\"string\"==typeof e.hash&&e.hash||void 0;this._hash=e.hash&&new Sn(a).addTo(this),this._hash&&this._hash._onHashChange()||(this.jumpTo({center:e.center,zoom:e.zoom,bearing:e.bearing,pitch:e.pitch}),e.bounds&&(this.resize(),this.fitBounds(e.bounds,t.extend({},e.fitBoundsOptions,{duration:0})))),this.resize(),this._localIdeographFontFamily=e.localIdeographFontFamily,e.style&&this.setStyle(e.style,{localIdeographFontFamily:e.localIdeographFontFamily}),e.attributionControl&&this.addControl(new bi({customAttribution:e.customAttribution})),this.addControl(new _i,e.logoPosition),this.on(\"style.load\",(function(){r.transform.unmodified&&r.jumpTo(r.style.stylesheet)})),this.on(\"data\",(function(e){r._update(\"style\"===e.dataType),r.fire(new t.Event(e.dataType+\"data\",e))})),this.on(\"dataloading\",(function(e){r.fire(new t.Event(e.dataType+\"dataloading\",e))}))}n&&(i.__proto__=n),i.prototype=Object.create(n&&n.prototype),i.prototype.constructor=i;var a={showTileBoundaries:{configurable:!0},showPadding:{configurable:!0},showCollisionBoxes:{configurable:!0},showOverdrawInspector:{configurable:!0},repaint:{configurable:!0},vertices:{configurable:!0},version:{configurable:!0}};return i.prototype._getMapId=function(){return this._mapId},i.prototype.addControl=function(e,r){if(void 0===r&&e.getDefaultPosition&&(r=e.getDefaultPosition()),void 0===r&&(r=\"top-right\"),!e||!e.onAdd)return this.fire(new t.ErrorEvent(new Error(\"Invalid argument to map.addControl(). Argument must be a control with onAdd and onRemove methods.\")));var n=e.onAdd(this);this._controls.push(e);var i=this._controlPositions[r];return-1!==r.indexOf(\"bottom\")?i.insertBefore(n,i.firstChild):i.appendChild(n),this},i.prototype.removeControl=function(e){if(!e||!e.onRemove)return this.fire(new t.ErrorEvent(new Error(\"Invalid argument to map.removeControl(). Argument must be a control with onAdd and onRemove methods.\")));var r=this._controls.indexOf(e);return r>-1&&this._controls.splice(r,1),e.onRemove(this),this},i.prototype.resize=function(e){var r=this._containerDimensions(),n=r[0],i=r[1];this._resizeCanvas(n,i),this.transform.resize(n,i),this.painter.resize(n,i);var a=!this._moving;return a&&(this.stop(),this.fire(new t.Event(\"movestart\",e)).fire(new t.Event(\"move\",e))),this.fire(new t.Event(\"resize\",e)),a&&this.fire(new t.Event(\"moveend\",e)),this},i.prototype.getBounds=function(){return this.transform.getBounds()},i.prototype.getMaxBounds=function(){return this.transform.getMaxBounds()},i.prototype.setMaxBounds=function(e){return this.transform.setMaxBounds(t.LngLatBounds.convert(e)),this._update()},i.prototype.setMinZoom=function(t){if((t=null==t?-2:t)>=-2&&t<=this.transform.maxZoom)return this.transform.minZoom=t,this._update(),this.getZoom()<t&&this.setZoom(t),this;throw new Error(\"minZoom must be between -2 and the current maxZoom, inclusive\")},i.prototype.getMinZoom=function(){return this.transform.minZoom},i.prototype.setMaxZoom=function(t){if((t=null==t?22:t)>=this.transform.minZoom)return this.transform.maxZoom=t,this._update(),this.getZoom()>t&&this.setZoom(t),this;throw new Error(\"maxZoom must be greater than the current minZoom\")},i.prototype.getMaxZoom=function(){return this.transform.maxZoom},i.prototype.setMinPitch=function(t){if((t=null==t?0:t)<0)throw new Error(\"minPitch must be greater than or equal to 0\");if(t>=0&&t<=this.transform.maxPitch)return this.transform.minPitch=t,this._update(),this.getPitch()<t&&this.setPitch(t),this;throw new Error(\"minPitch must be between 0 and the current maxPitch, inclusive\")},i.prototype.getMinPitch=function(){return this.transform.minPitch},i.prototype.setMaxPitch=function(t){if((t=null==t?60:t)>60)throw new Error(\"maxPitch must be less than or equal to 60\");if(t>=this.transform.minPitch)return this.transform.maxPitch=t,this._update(),this.getPitch()>t&&this.setPitch(t),this;throw new Error(\"maxPitch must be greater than the current minPitch\")},i.prototype.getMaxPitch=function(){return this.transform.maxPitch},i.prototype.getRenderWorldCopies=function(){return this.transform.renderWorldCopies},i.prototype.setRenderWorldCopies=function(t){return this.transform.renderWorldCopies=t,this._update()},i.prototype.project=function(e){return this.transform.locationPoint(t.LngLat.convert(e))},i.prototype.unproject=function(e){return this.transform.pointLocation(t.Point.convert(e))},i.prototype.isMoving=function(){return this._moving||this.handlers.isMoving()},i.prototype.isZooming=function(){return this._zooming||this.handlers.isZooming()},i.prototype.isRotating=function(){return this._rotating||this.handlers.isRotating()},i.prototype._createDelegatedListener=function(t,e,r){var n,i=this;if(\"mouseenter\"===t||\"mouseover\"===t){var a=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){var o=i.getLayer(e)?i.queryRenderedFeatures(n.point,{layers:[e]}):[];o.length?a||(a=!0,r.call(i,new Rn(t,i,n.originalEvent,{features:o}))):a=!1},mouseout:function(){a=!1}}}}if(\"mouseleave\"===t||\"mouseout\"===t){var o=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){(i.getLayer(e)?i.queryRenderedFeatures(n.point,{layers:[e]}):[]).length?o=!0:o&&(o=!1,r.call(i,new Rn(t,i,n.originalEvent)))},mouseout:function(e){o&&(o=!1,r.call(i,new Rn(t,i,e.originalEvent)))}}}}return{layer:e,listener:r,delegates:(n={},n[t]=function(t){var n=i.getLayer(e)?i.queryRenderedFeatures(t.point,{layers:[e]}):[];n.length&&(t.features=n,r.call(i,t),delete t.features)},n)}},i.prototype.on=function(t,e,r){if(void 0===r)return n.prototype.on.call(this,t,e);var i=this._createDelegatedListener(t,e,r);for(var a in this._delegatedListeners=this._delegatedListeners||{},this._delegatedListeners[t]=this._delegatedListeners[t]||[],this._delegatedListeners[t].push(i),i.delegates)this.on(a,i.delegates[a]);return this},i.prototype.once=function(t,e,r){if(void 0===r)return n.prototype.once.call(this,t,e);var i=this._createDelegatedListener(t,e,r);for(var a in i.delegates)this.once(a,i.delegates[a]);return this},i.prototype.off=function(t,e,r){var i=this;if(void 0===r)return n.prototype.off.call(this,t,e);return this._delegatedListeners&&this._delegatedListeners[t]&&function(n){for(var a=n[t],o=0;o<a.length;o++){var s=a[o];if(s.layer===e&&s.listener===r){for(var l in s.delegates)i.off(l,s.delegates[l]);return a.splice(o,1),i}}}(this._delegatedListeners),this},i.prototype.queryRenderedFeatures=function(e,r){if(!this.style)return[];var n;if(void 0!==r||void 0===e||e instanceof t.Point||Array.isArray(e)||(r=e,e=void 0),r=r||{},(e=e||[[0,0],[this.transform.width,this.transform.height]])instanceof t.Point||\"number\"==typeof e[0])n=[t.Point.convert(e)];else{var i=t.Point.convert(e[0]),a=t.Point.convert(e[1]);n=[i,new t.Point(a.x,i.y),a,new t.Point(i.x,a.y),i]}return this.style.queryRenderedFeatures(n,r,this.transform)},i.prototype.querySourceFeatures=function(t,e){return this.style.querySourceFeatures(t,e)},i.prototype.setStyle=function(e,r){return!1!==(r=t.extend({},{localIdeographFontFamily:this._localIdeographFontFamily},r)).diff&&r.localIdeographFontFamily===this._localIdeographFontFamily&&this.style&&e?(this._diffStyle(e,r),this):(this._localIdeographFontFamily=r.localIdeographFontFamily,this._updateStyle(e,r))},i.prototype._getUIString=function(t){var e=this._locale[t];if(null==e)throw new Error(\"Missing UI string '\"+t+\"'\");return e},i.prototype._updateStyle=function(t,e){return this.style&&(this.style.setEventedParent(null),this.style._remove()),t?(this.style=new He(this,e||{}),this.style.setEventedParent(this,{style:this.style}),\"string\"==typeof t?this.style.loadURL(t):this.style.loadJSON(t),this):(delete this.style,this)},i.prototype._lazyInitEmptyStyle=function(){this.style||(this.style=new He(this,{}),this.style.setEventedParent(this,{style:this.style}),this.style.loadEmpty())},i.prototype._diffStyle=function(e,r){var n=this;if(\"string\"==typeof e){var i=this._requestManager.normalizeStyleURL(e),a=this._requestManager.transformRequest(i,t.ResourceType.Style);t.getJSON(a,(function(e,i){e?n.fire(new t.ErrorEvent(e)):i&&n._updateDiff(i,r)}))}else\"object\"==typeof e&&this._updateDiff(e,r)},i.prototype._updateDiff=function(e,r){try{this.style.setState(e)&&this._update(!0)}catch(n){t.warnOnce(\"Unable to perform style diff: \"+(n.message||n.error||n)+\".  Rebuilding the style from scratch.\"),this._updateStyle(e,r)}},i.prototype.getStyle=function(){if(this.style)return this.style.serialize()},i.prototype.isStyleLoaded=function(){return this.style?this.style.loaded():t.warnOnce(\"There is no style added to the map.\")},i.prototype.addSource=function(t,e){return this._lazyInitEmptyStyle(),this.style.addSource(t,e),this._update(!0)},i.prototype.isSourceLoaded=function(e){var r=this.style&&this.style.sourceCaches[e];if(void 0!==r)return r.loaded();this.fire(new t.ErrorEvent(new Error(\"There is no source with ID '\"+e+\"'\")))},i.prototype.areTilesLoaded=function(){var t=this.style&&this.style.sourceCaches;for(var e in t){var r=t[e]._tiles;for(var n in r){var i=r[n];if(\"loaded\"!==i.state&&\"errored\"!==i.state)return!1}}return!0},i.prototype.addSourceType=function(t,e,r){return this._lazyInitEmptyStyle(),this.style.addSourceType(t,e,r)},i.prototype.removeSource=function(t){return this.style.removeSource(t),this._update(!0)},i.prototype.getSource=function(t){return this.style.getSource(t)},i.prototype.addImage=function(e,r,n){void 0===n&&(n={});var i=n.pixelRatio;void 0===i&&(i=1);var a=n.sdf;void 0===a&&(a=!1);var o=n.stretchX,s=n.stretchY,l=n.content;this._lazyInitEmptyStyle();if(r instanceof ki||Mi&&r instanceof Mi){var c=t.browser.getImageData(r),u=c.width,f=c.height,h=c.data;this.style.addImage(e,{data:new t.RGBAImage({width:u,height:f},h),pixelRatio:i,stretchX:o,stretchY:s,content:l,sdf:a,version:0})}else{if(void 0===r.width||void 0===r.height)return this.fire(new t.ErrorEvent(new Error(\"Invalid arguments to map.addImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`\")));var p=r.width,d=r.height,g=r.data,m=r;this.style.addImage(e,{data:new t.RGBAImage({width:p,height:d},new Uint8Array(g)),pixelRatio:i,stretchX:o,stretchY:s,content:l,sdf:a,version:0,userImage:m}),m.onAdd&&m.onAdd(this,e)}},i.prototype.updateImage=function(e,r){var n=this.style.getImage(e);if(!n)return this.fire(new t.ErrorEvent(new Error(\"The map has no image with that id. If you are adding a new image use `map.addImage(...)` instead.\")));var i=r instanceof ki||Mi&&r instanceof Mi?t.browser.getImageData(r):r,a=i.width,o=i.height,s=i.data;if(void 0===a||void 0===o)return this.fire(new t.ErrorEvent(new Error(\"Invalid arguments to map.updateImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`\")));if(a!==n.data.width||o!==n.data.height)return this.fire(new t.ErrorEvent(new Error(\"The width and height of the updated image must be that same as the previous version of the image\")));var l=!(r instanceof ki||Mi&&r instanceof Mi);n.data.replace(s,l),this.style.updateImage(e,n)},i.prototype.hasImage=function(e){return e?!!this.style.getImage(e):(this.fire(new t.ErrorEvent(new Error(\"Missing required image id\"))),!1)},i.prototype.removeImage=function(t){this.style.removeImage(t)},i.prototype.loadImage=function(e,r){t.getImage(this._requestManager.transformRequest(e,t.ResourceType.Image),r)},i.prototype.listImages=function(){return this.style.listImages()},i.prototype.addLayer=function(t,e){return this._lazyInitEmptyStyle(),this.style.addLayer(t,e),this._update(!0)},i.prototype.moveLayer=function(t,e){return this.style.moveLayer(t,e),this._update(!0)},i.prototype.removeLayer=function(t){return this.style.removeLayer(t),this._update(!0)},i.prototype.getLayer=function(t){return this.style.getLayer(t)},i.prototype.setLayerZoomRange=function(t,e,r){return this.style.setLayerZoomRange(t,e,r),this._update(!0)},i.prototype.setFilter=function(t,e,r){return void 0===r&&(r={}),this.style.setFilter(t,e,r),this._update(!0)},i.prototype.getFilter=function(t){return this.style.getFilter(t)},i.prototype.setPaintProperty=function(t,e,r,n){return void 0===n&&(n={}),this.style.setPaintProperty(t,e,r,n),this._update(!0)},i.prototype.getPaintProperty=function(t,e){return this.style.getPaintProperty(t,e)},i.prototype.setLayoutProperty=function(t,e,r,n){return void 0===n&&(n={}),this.style.setLayoutProperty(t,e,r,n),this._update(!0)},i.prototype.getLayoutProperty=function(t,e){return this.style.getLayoutProperty(t,e)},i.prototype.setLight=function(t,e){return void 0===e&&(e={}),this._lazyInitEmptyStyle(),this.style.setLight(t,e),this._update(!0)},i.prototype.getLight=function(){return this.style.getLight()},i.prototype.setFeatureState=function(t,e){return this.style.setFeatureState(t,e),this._update()},i.prototype.removeFeatureState=function(t,e){return this.style.removeFeatureState(t,e),this._update()},i.prototype.getFeatureState=function(t){return this.style.getFeatureState(t)},i.prototype.getContainer=function(){return this._container},i.prototype.getCanvasContainer=function(){return this._canvasContainer},i.prototype.getCanvas=function(){return this._canvas},i.prototype._containerDimensions=function(){var t=0,e=0;return this._container&&(t=this._container.clientWidth||400,e=this._container.clientHeight||300),[t,e]},i.prototype._detectMissingCSS=function(){\"rgb(250, 128, 114)\"!==t.window.getComputedStyle(this._missingCSSCanary).getPropertyValue(\"background-color\")&&t.warnOnce(\"This page appears to be missing CSS declarations for Mapbox GL JS, which may cause the map to display incorrectly. Please ensure your page includes mapbox-gl.css, as described in https://www.mapbox.com/mapbox-gl-js/api/.\")},i.prototype._setupContainer=function(){var t=this._container;t.classList.add(\"mapboxgl-map\"),(this._missingCSSCanary=r.create(\"div\",\"mapboxgl-canary\",t)).style.visibility=\"hidden\",this._detectMissingCSS();var e=this._canvasContainer=r.create(\"div\",\"mapboxgl-canvas-container\",t);this._interactive&&e.classList.add(\"mapboxgl-interactive\"),this._canvas=r.create(\"canvas\",\"mapboxgl-canvas\",e),this._canvas.addEventListener(\"webglcontextlost\",this._contextLost,!1),this._canvas.addEventListener(\"webglcontextrestored\",this._contextRestored,!1),this._canvas.setAttribute(\"tabindex\",\"0\"),this._canvas.setAttribute(\"aria-label\",\"Map\");var n=this._containerDimensions();this._resizeCanvas(n[0],n[1]);var i=this._controlContainer=r.create(\"div\",\"mapboxgl-control-container\",t),a=this._controlPositions={};[\"top-left\",\"top-right\",\"bottom-left\",\"bottom-right\"].forEach((function(t){a[t]=r.create(\"div\",\"mapboxgl-ctrl-\"+t,i)}))},i.prototype._resizeCanvas=function(e,r){var n=t.browser.devicePixelRatio||1;this._canvas.width=n*e,this._canvas.height=n*r,this._canvas.style.width=e+\"px\",this._canvas.style.height=r+\"px\"},i.prototype._setupPainter=function(){var r=t.extend({},e.webGLContextAttributes,{failIfMajorPerformanceCaveat:this._failIfMajorPerformanceCaveat,preserveDrawingBuffer:this._preserveDrawingBuffer,antialias:this._antialias||!1}),n=this._canvas.getContext(\"webgl\",r)||this._canvas.getContext(\"experimental-webgl\",r);n?(this.painter=new _n(n,this.transform),t.webpSupported.testSupport(n)):this.fire(new t.ErrorEvent(new Error(\"Failed to initialize WebGL\")))},i.prototype._contextLost=function(e){e.preventDefault(),this._frame&&(this._frame.cancel(),this._frame=null),this.fire(new t.Event(\"webglcontextlost\",{originalEvent:e}))},i.prototype._contextRestored=function(e){this._setupPainter(),this.resize(),this._update(),this.fire(new t.Event(\"webglcontextrestored\",{originalEvent:e}))},i.prototype.loaded=function(){return!this._styleDirty&&!this._sourcesDirty&&!!this.style&&this.style.loaded()},i.prototype._update=function(t){return this.style?(this._styleDirty=this._styleDirty||t,this._sourcesDirty=!0,this.triggerRepaint(),this):this},i.prototype._requestRenderFrame=function(t){return this._update(),this._renderTaskQueue.add(t)},i.prototype._cancelRenderFrame=function(t){this._renderTaskQueue.remove(t)},i.prototype._render=function(e){var r,n=this,i=0,a=this.painter.context.extTimerQuery;if(this.listens(\"gpu-timing-frame\")&&(r=a.createQueryEXT(),a.beginQueryEXT(a.TIME_ELAPSED_EXT,r),i=t.browser.now()),this.painter.context.setDirty(),this.painter.setBaseState(),this._renderTaskQueue.run(e),!this._removed){var o=!1;if(this.style&&this._styleDirty){this._styleDirty=!1;var s=this.transform.zoom,l=t.browser.now();this.style.zoomHistory.update(s,l);var c=new t.EvaluationParameters(s,{now:l,fadeDuration:this._fadeDuration,zoomHistory:this.style.zoomHistory,transition:this.style.getTransition()}),u=c.crossFadingFactor();1===u&&u===this._crossFadingFactor||(o=!0,this._crossFadingFactor=u),this.style.update(c)}if(this.style&&this._sourcesDirty&&(this._sourcesDirty=!1,this.style._updateSources(this.transform)),this._placementDirty=this.style&&this.style._updatePlacement(this.painter.transform,this.showCollisionBoxes,this._fadeDuration,this._crossSourceCollisions),this.painter.render(this.style,{showTileBoundaries:this.showTileBoundaries,showOverdrawInspector:this._showOverdrawInspector,rotating:this.isRotating(),zooming:this.isZooming(),moving:this.isMoving(),fadeDuration:this._fadeDuration,showPadding:this.showPadding,gpuTiming:!!this.listens(\"gpu-timing-layer\")}),this.fire(new t.Event(\"render\")),this.loaded()&&!this._loaded&&(this._loaded=!0,this.fire(new t.Event(\"load\"))),this.style&&(this.style.hasTransitions()||o)&&(this._styleDirty=!0),this.style&&!this._placementDirty&&this.style._releaseSymbolFadeTiles(),this.listens(\"gpu-timing-frame\")){var f=t.browser.now()-i;a.endQueryEXT(a.TIME_ELAPSED_EXT,r),setTimeout((function(){var e=a.getQueryObjectEXT(r,a.QUERY_RESULT_EXT)/1e6;a.deleteQueryEXT(r),n.fire(new t.Event(\"gpu-timing-frame\",{cpuTime:f,gpuTime:e}))}),50)}if(this.listens(\"gpu-timing-layer\")){var h=this.painter.collectGpuTimers();setTimeout((function(){var e=n.painter.queryGpuTimers(h);n.fire(new t.Event(\"gpu-timing-layer\",{layerTimes:e}))}),50)}return this._sourcesDirty||this._styleDirty||this._placementDirty||this._repaint?this.triggerRepaint():!this.isMoving()&&this.loaded()&&(this._fullyLoaded||(this._fullyLoaded=!0),this.fire(new t.Event(\"idle\"))),this}},i.prototype.remove=function(){this._hash&&this._hash.remove();for(var e=0,r=this._controls;e<r.length;e+=1){r[e].onRemove(this)}this._controls=[],this._frame&&(this._frame.cancel(),this._frame=null),this._renderTaskQueue.clear(),this.painter.destroy(),this.handlers.destroy(),delete this.handlers,this.setStyle(null),void 0!==t.window&&(t.window.removeEventListener(\"resize\",this._onWindowResize,!1),t.window.removeEventListener(\"online\",this._onWindowOnline,!1));var n=this.painter.context.gl.getExtension(\"WEBGL_lose_context\");n&&n.loseContext(),Li(this._canvasContainer),Li(this._controlContainer),Li(this._missingCSSCanary),this._container.classList.remove(\"mapboxgl-map\"),this._removed=!0,this.fire(new t.Event(\"remove\"))},i.prototype.triggerRepaint=function(){var e=this;this.style&&!this._frame&&(this._frame=t.browser.frame((function(t){e._frame=null,e._render(t)})))},i.prototype._onWindowOnline=function(){this._update()},i.prototype._onWindowResize=function(t){this._trackResize&&this.resize({originalEvent:t})._update()},a.showTileBoundaries.get=function(){return!!this._showTileBoundaries},a.showTileBoundaries.set=function(t){this._showTileBoundaries!==t&&(this._showTileBoundaries=t,this._update())},a.showPadding.get=function(){return!!this._showPadding},a.showPadding.set=function(t){this._showPadding!==t&&(this._showPadding=t,this._update())},a.showCollisionBoxes.get=function(){return!!this._showCollisionBoxes},a.showCollisionBoxes.set=function(t){this._showCollisionBoxes!==t&&(this._showCollisionBoxes=t,t?this.style._generateCollisionBoxes():this._update())},a.showOverdrawInspector.get=function(){return!!this._showOverdrawInspector},a.showOverdrawInspector.set=function(t){this._showOverdrawInspector!==t&&(this._showOverdrawInspector=t,this._update())},a.repaint.get=function(){return!!this._repaint},a.repaint.set=function(t){this._repaint!==t&&(this._repaint=t,this.triggerRepaint())},a.vertices.get=function(){return!!this._vertices},a.vertices.set=function(t){this._vertices=t,this._update()},i.prototype._setCacheLimits=function(e,r){t.setCacheLimits(e,r)},a.version.get=function(){return t.version},Object.defineProperties(i.prototype,a),i}(xi);function Li(t){t.parentNode&&t.parentNode.removeChild(t)}var Ci={showCompass:!0,showZoom:!0,visualizePitch:!1},Pi=function(e){var n=this;this.options=t.extend({},Ci,e),this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),this._container.addEventListener(\"contextmenu\",(function(t){return t.preventDefault()})),this.options.showZoom&&(t.bindAll([\"_setButtonTitle\",\"_updateZoomButtons\"],this),this._zoomInButton=this._createButton(\"mapboxgl-ctrl-zoom-in\",(function(t){return n._map.zoomIn({},{originalEvent:t})})),r.create(\"span\",\"mapboxgl-ctrl-icon\",this._zoomInButton).setAttribute(\"aria-hidden\",!0),this._zoomOutButton=this._createButton(\"mapboxgl-ctrl-zoom-out\",(function(t){return n._map.zoomOut({},{originalEvent:t})})),r.create(\"span\",\"mapboxgl-ctrl-icon\",this._zoomOutButton).setAttribute(\"aria-hidden\",!0)),this.options.showCompass&&(t.bindAll([\"_rotateCompassArrow\"],this),this._compass=this._createButton(\"mapboxgl-ctrl-compass\",(function(t){n.options.visualizePitch?n._map.resetNorthPitch({},{originalEvent:t}):n._map.resetNorth({},{originalEvent:t})})),this._compassIcon=r.create(\"span\",\"mapboxgl-ctrl-icon\",this._compass),this._compassIcon.setAttribute(\"aria-hidden\",!0))};Pi.prototype._updateZoomButtons=function(){var t=this._map.getZoom();this._zoomInButton.disabled=t===this._map.getMaxZoom(),this._zoomOutButton.disabled=t===this._map.getMinZoom()},Pi.prototype._rotateCompassArrow=function(){var t=this.options.visualizePitch?\"scale(\"+1/Math.pow(Math.cos(this._map.transform.pitch*(Math.PI/180)),.5)+\") rotateX(\"+this._map.transform.pitch+\"deg) rotateZ(\"+this._map.transform.angle*(180/Math.PI)+\"deg)\":\"rotate(\"+this._map.transform.angle*(180/Math.PI)+\"deg)\";this._compassIcon.style.transform=t},Pi.prototype.onAdd=function(t){return this._map=t,this.options.showZoom&&(this._setButtonTitle(this._zoomInButton,\"ZoomIn\"),this._setButtonTitle(this._zoomOutButton,\"ZoomOut\"),this._map.on(\"zoom\",this._updateZoomButtons),this._updateZoomButtons()),this.options.showCompass&&(this._setButtonTitle(this._compass,\"ResetBearing\"),this.options.visualizePitch&&this._map.on(\"pitch\",this._rotateCompassArrow),this._map.on(\"rotate\",this._rotateCompassArrow),this._rotateCompassArrow(),this._handler=new Ii(this._map,this._compass,this.options.visualizePitch)),this._container},Pi.prototype.onRemove=function(){r.remove(this._container),this.options.showZoom&&this._map.off(\"zoom\",this._updateZoomButtons),this.options.showCompass&&(this.options.visualizePitch&&this._map.off(\"pitch\",this._rotateCompassArrow),this._map.off(\"rotate\",this._rotateCompassArrow),this._handler.off(),delete this._handler),delete this._map},Pi.prototype._createButton=function(t,e){var n=r.create(\"button\",t,this._container);return n.type=\"button\",n.addEventListener(\"click\",e),n},Pi.prototype._setButtonTitle=function(t,e){var r=this._map._getUIString(\"NavigationControl.\"+e);t.title=r,t.setAttribute(\"aria-label\",r)};var Ii=function(e,n,i){void 0===i&&(i=!1),this._clickTolerance=10,this.element=n,this.mouseRotate=new Xn({clickTolerance:e.dragRotate._mouseRotate._clickTolerance}),this.map=e,i&&(this.mousePitch=new Zn({clickTolerance:e.dragRotate._mousePitch._clickTolerance})),t.bindAll([\"mousedown\",\"mousemove\",\"mouseup\",\"touchstart\",\"touchmove\",\"touchend\",\"reset\"],this),r.addEventListener(n,\"mousedown\",this.mousedown),r.addEventListener(n,\"touchstart\",this.touchstart,{passive:!1}),r.addEventListener(n,\"touchmove\",this.touchmove),r.addEventListener(n,\"touchend\",this.touchend),r.addEventListener(n,\"touchcancel\",this.reset)};function Oi(e,r,n){if(e=new t.LngLat(e.lng,e.lat),r){var i=new t.LngLat(e.lng-360,e.lat),a=new t.LngLat(e.lng+360,e.lat),o=n.locationPoint(e).distSqr(r);n.locationPoint(i).distSqr(r)<o?e=i:n.locationPoint(a).distSqr(r)<o&&(e=a)}for(;Math.abs(e.lng-n.center.lng)>180;){var s=n.locationPoint(e);if(s.x>=0&&s.y>=0&&s.x<=n.width&&s.y<=n.height)break;e.lng>n.center.lng?e.lng-=360:e.lng+=360}return e}Ii.prototype.down=function(t,e){this.mouseRotate.mousedown(t,e),this.mousePitch&&this.mousePitch.mousedown(t,e),r.disableDrag()},Ii.prototype.move=function(t,e){var r=this.map,n=this.mouseRotate.mousemoveWindow(t,e);if(n&&n.bearingDelta&&r.setBearing(r.getBearing()+n.bearingDelta),this.mousePitch){var i=this.mousePitch.mousemoveWindow(t,e);i&&i.pitchDelta&&r.setPitch(r.getPitch()+i.pitchDelta)}},Ii.prototype.off=function(){var t=this.element;r.removeEventListener(t,\"mousedown\",this.mousedown),r.removeEventListener(t,\"touchstart\",this.touchstart,{passive:!1}),r.removeEventListener(t,\"touchmove\",this.touchmove),r.removeEventListener(t,\"touchend\",this.touchend),r.removeEventListener(t,\"touchcancel\",this.reset),this.offTemp()},Ii.prototype.offTemp=function(){r.enableDrag(),r.removeEventListener(t.window,\"mousemove\",this.mousemove),r.removeEventListener(t.window,\"mouseup\",this.mouseup)},Ii.prototype.mousedown=function(e){this.down(t.extend({},e,{ctrlKey:!0,preventDefault:function(){return e.preventDefault()}}),r.mousePos(this.element,e)),r.addEventListener(t.window,\"mousemove\",this.mousemove),r.addEventListener(t.window,\"mouseup\",this.mouseup)},Ii.prototype.mousemove=function(t){this.move(t,r.mousePos(this.element,t))},Ii.prototype.mouseup=function(t){this.mouseRotate.mouseupWindow(t),this.mousePitch&&this.mousePitch.mouseupWindow(t),this.offTemp()},Ii.prototype.touchstart=function(t){1!==t.targetTouches.length?this.reset():(this._startPos=this._lastPos=r.touchPos(this.element,t.targetTouches)[0],this.down({type:\"mousedown\",button:0,ctrlKey:!0,preventDefault:function(){return t.preventDefault()}},this._startPos))},Ii.prototype.touchmove=function(t){1!==t.targetTouches.length?this.reset():(this._lastPos=r.touchPos(this.element,t.targetTouches)[0],this.move({preventDefault:function(){return t.preventDefault()}},this._lastPos))},Ii.prototype.touchend=function(t){0===t.targetTouches.length&&this._startPos&&this._lastPos&&this._startPos.dist(this._lastPos)<this._clickTolerance&&this.element.click(),this.reset()},Ii.prototype.reset=function(){this.mouseRotate.reset(),this.mousePitch&&this.mousePitch.reset(),delete this._startPos,delete this._lastPos,this.offTemp()};var zi={center:\"translate(-50%,-50%)\",top:\"translate(-50%,0)\",\"top-left\":\"translate(0,0)\",\"top-right\":\"translate(-100%,0)\",bottom:\"translate(-50%,-100%)\",\"bottom-left\":\"translate(0,-100%)\",\"bottom-right\":\"translate(-100%,-100%)\",left:\"translate(0,-50%)\",right:\"translate(-100%,-50%)\"};function Di(t,e,r){var n=t.classList;for(var i in zi)n.remove(\"mapboxgl-\"+r+\"-anchor-\"+i);n.add(\"mapboxgl-\"+r+\"-anchor-\"+e)}var Ri,Fi=function(e){function n(n,i){var a=this;if(e.call(this),(n instanceof t.window.HTMLElement||i)&&(n=t.extend({element:n},i)),t.bindAll([\"_update\",\"_onMove\",\"_onUp\",\"_addDragHandler\",\"_onMapClick\",\"_onKeyPress\"],this),this._anchor=n&&n.anchor||\"center\",this._color=n&&n.color||\"#3FB1CE\",this._draggable=n&&n.draggable||!1,this._state=\"inactive\",this._rotation=n&&n.rotation||0,this._rotationAlignment=n&&n.rotationAlignment||\"auto\",this._pitchAlignment=n&&n.pitchAlignment&&\"auto\"!==n.pitchAlignment?n.pitchAlignment:this._rotationAlignment,n&&n.element)this._element=n.element,this._offset=t.Point.convert(n&&n.offset||[0,0]);else{this._defaultMarker=!0,this._element=r.create(\"div\"),this._element.setAttribute(\"aria-label\",\"Map marker\");var o=r.createNS(\"http://www.w3.org/2000/svg\",\"svg\");o.setAttributeNS(null,\"display\",\"block\"),o.setAttributeNS(null,\"height\",\"41px\"),o.setAttributeNS(null,\"width\",\"27px\"),o.setAttributeNS(null,\"viewBox\",\"0 0 27 41\");var s=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");s.setAttributeNS(null,\"stroke\",\"none\"),s.setAttributeNS(null,\"stroke-width\",\"1\"),s.setAttributeNS(null,\"fill\",\"none\"),s.setAttributeNS(null,\"fill-rule\",\"evenodd\");var l=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");l.setAttributeNS(null,\"fill-rule\",\"nonzero\");var c=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");c.setAttributeNS(null,\"transform\",\"translate(3.0, 29.0)\"),c.setAttributeNS(null,\"fill\",\"#000000\");for(var u=0,f=[{rx:\"10.5\",ry:\"5.25002273\"},{rx:\"10.5\",ry:\"5.25002273\"},{rx:\"9.5\",ry:\"4.77275007\"},{rx:\"8.5\",ry:\"4.29549936\"},{rx:\"7.5\",ry:\"3.81822308\"},{rx:\"6.5\",ry:\"3.34094679\"},{rx:\"5.5\",ry:\"2.86367051\"},{rx:\"4.5\",ry:\"2.38636864\"}];u<f.length;u+=1){var h=f[u],p=r.createNS(\"http://www.w3.org/2000/svg\",\"ellipse\");p.setAttributeNS(null,\"opacity\",\"0.04\"),p.setAttributeNS(null,\"cx\",\"10.5\"),p.setAttributeNS(null,\"cy\",\"5.80029008\"),p.setAttributeNS(null,\"rx\",h.rx),p.setAttributeNS(null,\"ry\",h.ry),c.appendChild(p)}var d=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");d.setAttributeNS(null,\"fill\",this._color);var g=r.createNS(\"http://www.w3.org/2000/svg\",\"path\");g.setAttributeNS(null,\"d\",\"M27,13.5 C27,19.074644 20.250001,27.000002 14.75,34.500002 C14.016665,35.500004 12.983335,35.500004 12.25,34.500002 C6.7499993,27.000002 0,19.222562 0,13.5 C0,6.0441559 6.0441559,0 13.5,0 C20.955844,0 27,6.0441559 27,13.5 Z\"),d.appendChild(g);var m=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");m.setAttributeNS(null,\"opacity\",\"0.25\"),m.setAttributeNS(null,\"fill\",\"#000000\");var v=r.createNS(\"http://www.w3.org/2000/svg\",\"path\");v.setAttributeNS(null,\"d\",\"M13.5,0 C6.0441559,0 0,6.0441559 0,13.5 C0,19.222562 6.7499993,27 12.25,34.5 C13,35.522727 14.016664,35.500004 14.75,34.5 C20.250001,27 27,19.074644 27,13.5 C27,6.0441559 20.955844,0 13.5,0 Z M13.5,1 C20.415404,1 26,6.584596 26,13.5 C26,15.898657 24.495584,19.181431 22.220703,22.738281 C19.945823,26.295132 16.705119,30.142167 13.943359,33.908203 C13.743445,34.180814 13.612715,34.322738 13.5,34.441406 C13.387285,34.322738 13.256555,34.180814 13.056641,33.908203 C10.284481,30.127985 7.4148684,26.314159 5.015625,22.773438 C2.6163816,19.232715 1,15.953538 1,13.5 C1,6.584596 6.584596,1 13.5,1 Z\"),m.appendChild(v);var y=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");y.setAttributeNS(null,\"transform\",\"translate(6.0, 7.0)\"),y.setAttributeNS(null,\"fill\",\"#FFFFFF\");var x=r.createNS(\"http://www.w3.org/2000/svg\",\"g\");x.setAttributeNS(null,\"transform\",\"translate(8.0, 8.0)\");var b=r.createNS(\"http://www.w3.org/2000/svg\",\"circle\");b.setAttributeNS(null,\"fill\",\"#000000\"),b.setAttributeNS(null,\"opacity\",\"0.25\"),b.setAttributeNS(null,\"cx\",\"5.5\"),b.setAttributeNS(null,\"cy\",\"5.5\"),b.setAttributeNS(null,\"r\",\"5.4999962\");var _=r.createNS(\"http://www.w3.org/2000/svg\",\"circle\");_.setAttributeNS(null,\"fill\",\"#FFFFFF\"),_.setAttributeNS(null,\"cx\",\"5.5\"),_.setAttributeNS(null,\"cy\",\"5.5\"),_.setAttributeNS(null,\"r\",\"5.4999962\"),x.appendChild(b),x.appendChild(_),l.appendChild(c),l.appendChild(d),l.appendChild(m),l.appendChild(y),l.appendChild(x),o.appendChild(l),this._element.appendChild(o),this._offset=t.Point.convert(n&&n.offset||[0,-14])}this._element.classList.add(\"mapboxgl-marker\"),this._element.addEventListener(\"dragstart\",(function(t){t.preventDefault()})),this._element.addEventListener(\"mousedown\",(function(t){t.preventDefault()})),this._element.addEventListener(\"focus\",(function(){var t=a._map.getContainer();t.scrollTop=0,t.scrollLeft=0})),Di(this._element,this._anchor,\"marker\"),this._popup=null}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.addTo=function(t){return this.remove(),this._map=t,t.getCanvasContainer().appendChild(this._element),t.on(\"move\",this._update),t.on(\"moveend\",this._update),this.setDraggable(this._draggable),this._update(),this._map.on(\"click\",this._onMapClick),this},n.prototype.remove=function(){return this._map&&(this._map.off(\"click\",this._onMapClick),this._map.off(\"move\",this._update),this._map.off(\"moveend\",this._update),this._map.off(\"mousedown\",this._addDragHandler),this._map.off(\"touchstart\",this._addDragHandler),this._map.off(\"mouseup\",this._onUp),this._map.off(\"touchend\",this._onUp),this._map.off(\"mousemove\",this._onMove),this._map.off(\"touchmove\",this._onMove),delete this._map),r.remove(this._element),this._popup&&this._popup.remove(),this},n.prototype.getLngLat=function(){return this._lngLat},n.prototype.setLngLat=function(e){return this._lngLat=t.LngLat.convert(e),this._pos=null,this._popup&&this._popup.setLngLat(this._lngLat),this._update(),this},n.prototype.getElement=function(){return this._element},n.prototype.setPopup=function(t){if(this._popup&&(this._popup.remove(),this._popup=null,this._element.removeEventListener(\"keypress\",this._onKeyPress),this._originalTabIndex||this._element.removeAttribute(\"tabindex\")),t){if(!(\"offset\"in t.options)){var e=Math.sqrt(Math.pow(13.5,2)/2);t.options.offset=this._defaultMarker?{top:[0,0],\"top-left\":[0,0],\"top-right\":[0,0],bottom:[0,-38.1],\"bottom-left\":[e,-1*(24.6+e)],\"bottom-right\":[-e,-1*(24.6+e)],left:[13.5,-24.6],right:[-13.5,-24.6]}:this._offset}this._popup=t,this._lngLat&&this._popup.setLngLat(this._lngLat),this._originalTabIndex=this._element.getAttribute(\"tabindex\"),this._originalTabIndex||this._element.setAttribute(\"tabindex\",\"0\"),this._element.addEventListener(\"keypress\",this._onKeyPress)}return this},n.prototype._onKeyPress=function(t){var e=t.code,r=t.charCode||t.keyCode;\"Space\"!==e&&\"Enter\"!==e&&32!==r&&13!==r||this.togglePopup()},n.prototype._onMapClick=function(t){var e=t.originalEvent.target,r=this._element;this._popup&&(e===r||r.contains(e))&&this.togglePopup()},n.prototype.getPopup=function(){return this._popup},n.prototype.togglePopup=function(){var t=this._popup;return t?(t.isOpen()?t.remove():t.addTo(this._map),this):this},n.prototype._update=function(t){if(this._map){this._map.transform.renderWorldCopies&&(this._lngLat=Oi(this._lngLat,this._pos,this._map.transform)),this._pos=this._map.project(this._lngLat)._add(this._offset);var e=\"\";\"viewport\"===this._rotationAlignment||\"auto\"===this._rotationAlignment?e=\"rotateZ(\"+this._rotation+\"deg)\":\"map\"===this._rotationAlignment&&(e=\"rotateZ(\"+(this._rotation-this._map.getBearing())+\"deg)\");var n=\"\";\"viewport\"===this._pitchAlignment||\"auto\"===this._pitchAlignment?n=\"rotateX(0deg)\":\"map\"===this._pitchAlignment&&(n=\"rotateX(\"+this._map.getPitch()+\"deg)\"),t&&\"moveend\"!==t.type||(this._pos=this._pos.round()),r.setTransform(this._element,zi[this._anchor]+\" translate(\"+this._pos.x+\"px, \"+this._pos.y+\"px) \"+n+\" \"+e)}},n.prototype.getOffset=function(){return this._offset},n.prototype.setOffset=function(e){return this._offset=t.Point.convert(e),this._update(),this},n.prototype._onMove=function(e){this._pos=e.point.sub(this._positionDelta),this._lngLat=this._map.unproject(this._pos),this.setLngLat(this._lngLat),this._element.style.pointerEvents=\"none\",\"pending\"===this._state&&(this._state=\"active\",this.fire(new t.Event(\"dragstart\"))),this.fire(new t.Event(\"drag\"))},n.prototype._onUp=function(){this._element.style.pointerEvents=\"auto\",this._positionDelta=null,this._map.off(\"mousemove\",this._onMove),this._map.off(\"touchmove\",this._onMove),\"active\"===this._state&&this.fire(new t.Event(\"dragend\")),this._state=\"inactive\"},n.prototype._addDragHandler=function(t){this._element.contains(t.originalEvent.target)&&(t.preventDefault(),this._positionDelta=t.point.sub(this._pos).add(this._offset),this._state=\"pending\",this._map.on(\"mousemove\",this._onMove),this._map.on(\"touchmove\",this._onMove),this._map.once(\"mouseup\",this._onUp),this._map.once(\"touchend\",this._onUp))},n.prototype.setDraggable=function(t){return this._draggable=!!t,this._map&&(t?(this._map.on(\"mousedown\",this._addDragHandler),this._map.on(\"touchstart\",this._addDragHandler)):(this._map.off(\"mousedown\",this._addDragHandler),this._map.off(\"touchstart\",this._addDragHandler))),this},n.prototype.isDraggable=function(){return this._draggable},n.prototype.setRotation=function(t){return this._rotation=t||0,this._update(),this},n.prototype.getRotation=function(){return this._rotation},n.prototype.setRotationAlignment=function(t){return this._rotationAlignment=t||\"auto\",this._update(),this},n.prototype.getRotationAlignment=function(){return this._rotationAlignment},n.prototype.setPitchAlignment=function(t){return this._pitchAlignment=t&&\"auto\"!==t?t:this._rotationAlignment,this._update(),this},n.prototype.getPitchAlignment=function(){return this._pitchAlignment},n}(t.Evented),Bi={positionOptions:{enableHighAccuracy:!1,maximumAge:0,timeout:6e3},fitBoundsOptions:{maxZoom:15},trackUserLocation:!1,showAccuracyCircle:!0,showUserLocation:!0};var Ni=0,ji=!1,Ui=function(e){function n(r){e.call(this),this.options=t.extend({},Bi,r),t.bindAll([\"_onSuccess\",\"_onError\",\"_onZoom\",\"_finish\",\"_setupUI\",\"_updateCamera\",\"_updateMarker\"],this)}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.onAdd=function(e){var n;return this._map=e,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),n=this._setupUI,void 0!==Ri?n(Ri):void 0!==t.window.navigator.permissions?t.window.navigator.permissions.query({name:\"geolocation\"}).then((function(t){Ri=\"denied\"!==t.state,n(Ri)})):(Ri=!!t.window.navigator.geolocation,n(Ri)),this._container},n.prototype.onRemove=function(){void 0!==this._geolocationWatchID&&(t.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0),this.options.showUserLocation&&this._userLocationDotMarker&&this._userLocationDotMarker.remove(),this.options.showAccuracyCircle&&this._accuracyCircleMarker&&this._accuracyCircleMarker.remove(),r.remove(this._container),this._map.off(\"zoom\",this._onZoom),this._map=void 0,Ni=0,ji=!1},n.prototype._isOutOfMapMaxBounds=function(t){var e=this._map.getMaxBounds(),r=t.coords;return e&&(r.longitude<e.getWest()||r.longitude>e.getEast()||r.latitude<e.getSouth()||r.latitude>e.getNorth())},n.prototype._setErrorState=function(){switch(this._watchState){case\"WAITING_ACTIVE\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\");break;case\"ACTIVE_LOCK\":this._watchState=\"ACTIVE_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\");break;case\"BACKGROUND\":this._watchState=\"BACKGROUND_ERROR\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\")}},n.prototype._onSuccess=function(e){if(this._map){if(this._isOutOfMapMaxBounds(e))return this._setErrorState(),this.fire(new t.Event(\"outofmaxbounds\",e)),this._updateMarker(),void this._finish();if(this.options.trackUserLocation)switch(this._lastKnownPosition=e,this._watchState){case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"BACKGROUND\":case\"BACKGROUND_ERROR\":this._watchState=\"BACKGROUND\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\")}this.options.showUserLocation&&\"OFF\"!==this._watchState&&this._updateMarker(e),this.options.trackUserLocation&&\"ACTIVE_LOCK\"!==this._watchState||this._updateCamera(e),this.options.showUserLocation&&this._dotElement.classList.remove(\"mapboxgl-user-location-dot-stale\"),this.fire(new t.Event(\"geolocate\",e)),this._finish()}},n.prototype._updateCamera=function(e){var r=new t.LngLat(e.coords.longitude,e.coords.latitude),n=e.coords.accuracy,i=this._map.getBearing(),a=t.extend({bearing:i},this.options.fitBoundsOptions);this._map.fitBounds(r.toBounds(n),a,{geolocateSource:!0})},n.prototype._updateMarker=function(e){if(e){var r=new t.LngLat(e.coords.longitude,e.coords.latitude);this._accuracyCircleMarker.setLngLat(r).addTo(this._map),this._userLocationDotMarker.setLngLat(r).addTo(this._map),this._accuracy=e.coords.accuracy,this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()}else this._userLocationDotMarker.remove(),this._accuracyCircleMarker.remove()},n.prototype._updateCircleRadius=function(){var t=this._map._container.clientHeight/2,e=this._map.unproject([0,t]),r=this._map.unproject([1,t]),n=e.distanceTo(r),i=Math.ceil(2*this._accuracy/n);this._circleElement.style.width=i+\"px\",this._circleElement.style.height=i+\"px\"},n.prototype._onZoom=function(){this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()},n.prototype._onError=function(e){if(this._map){if(this.options.trackUserLocation)if(1===e.code){this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this._geolocateButton.disabled=!0;var r=this._map._getUIString(\"GeolocateControl.LocationNotAvailable\");this._geolocateButton.title=r,this._geolocateButton.setAttribute(\"aria-label\",r),void 0!==this._geolocationWatchID&&this._clearWatch()}else{if(3===e.code&&ji)return;this._setErrorState()}\"OFF\"!==this._watchState&&this.options.showUserLocation&&this._dotElement.classList.add(\"mapboxgl-user-location-dot-stale\"),this.fire(new t.Event(\"error\",e)),this._finish()}},n.prototype._finish=function(){this._timeoutId&&clearTimeout(this._timeoutId),this._timeoutId=void 0},n.prototype._setupUI=function(e){var n=this;if(this._container.addEventListener(\"contextmenu\",(function(t){return t.preventDefault()})),this._geolocateButton=r.create(\"button\",\"mapboxgl-ctrl-geolocate\",this._container),r.create(\"span\",\"mapboxgl-ctrl-icon\",this._geolocateButton).setAttribute(\"aria-hidden\",!0),this._geolocateButton.type=\"button\",!1===e){t.warnOnce(\"Geolocation support is not available so the GeolocateControl will be disabled.\");var i=this._map._getUIString(\"GeolocateControl.LocationNotAvailable\");this._geolocateButton.disabled=!0,this._geolocateButton.title=i,this._geolocateButton.setAttribute(\"aria-label\",i)}else{var a=this._map._getUIString(\"GeolocateControl.FindMyLocation\");this._geolocateButton.title=a,this._geolocateButton.setAttribute(\"aria-label\",a)}this.options.trackUserLocation&&(this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this._watchState=\"OFF\"),this.options.showUserLocation&&(this._dotElement=r.create(\"div\",\"mapboxgl-user-location-dot\"),this._userLocationDotMarker=new Fi(this._dotElement),this._circleElement=r.create(\"div\",\"mapboxgl-user-location-accuracy-circle\"),this._accuracyCircleMarker=new Fi({element:this._circleElement,pitchAlignment:\"map\"}),this.options.trackUserLocation&&(this._watchState=\"OFF\"),this._map.on(\"zoom\",this._onZoom)),this._geolocateButton.addEventListener(\"click\",this.trigger.bind(this)),this._setup=!0,this.options.trackUserLocation&&this._map.on(\"movestart\",(function(e){var r=e.originalEvent&&\"resize\"===e.originalEvent.type;e.geolocateSource||\"ACTIVE_LOCK\"!==n._watchState||r||(n._watchState=\"BACKGROUND\",n._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\"),n._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),n.fire(new t.Event(\"trackuserlocationend\")))}))},n.prototype.trigger=function(){if(!this._setup)return t.warnOnce(\"Geolocate control triggered before added to a map\"),!1;if(this.options.trackUserLocation){switch(this._watchState){case\"OFF\":this._watchState=\"WAITING_ACTIVE\",this.fire(new t.Event(\"trackuserlocationstart\"));break;case\"WAITING_ACTIVE\":case\"ACTIVE_LOCK\":case\"ACTIVE_ERROR\":case\"BACKGROUND_ERROR\":Ni--,ji=!1,this._watchState=\"OFF\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-active-error\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background-error\"),this.fire(new t.Event(\"trackuserlocationend\"));break;case\"BACKGROUND\":this._watchState=\"ACTIVE_LOCK\",this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-background\"),this._lastKnownPosition&&this._updateCamera(this._lastKnownPosition),this.fire(new t.Event(\"trackuserlocationstart\"))}switch(this._watchState){case\"WAITING_ACTIVE\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"ACTIVE_LOCK\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active\");break;case\"ACTIVE_ERROR\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-active-error\");break;case\"BACKGROUND\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background\");break;case\"BACKGROUND_ERROR\":this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-background-error\")}if(\"OFF\"===this._watchState&&void 0!==this._geolocationWatchID)this._clearWatch();else if(void 0===this._geolocationWatchID){var e;this._geolocateButton.classList.add(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"true\"),++Ni>1?(e={maximumAge:6e5,timeout:0},ji=!0):(e=this.options.positionOptions,ji=!1),this._geolocationWatchID=t.window.navigator.geolocation.watchPosition(this._onSuccess,this._onError,e)}}else t.window.navigator.geolocation.getCurrentPosition(this._onSuccess,this._onError,this.options.positionOptions),this._timeoutId=setTimeout(this._finish,1e4);return!0},n.prototype._clearWatch=function(){t.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0,this._geolocateButton.classList.remove(\"mapboxgl-ctrl-geolocate-waiting\"),this._geolocateButton.setAttribute(\"aria-pressed\",\"false\"),this.options.showUserLocation&&this._updateMarker(null)},n}(t.Evented),Vi={maxWidth:100,unit:\"metric\"},qi=function(e){this.options=t.extend({},Vi,e),t.bindAll([\"_onMove\",\"setUnit\"],this)};function Hi(t,e,r){var n=r&&r.maxWidth||100,i=t._container.clientHeight/2,a=t.unproject([0,i]),o=t.unproject([n,i]),s=a.distanceTo(o);if(r&&\"imperial\"===r.unit){var l=3.2808*s;if(l>5280)Gi(e,n,l/5280,t._getUIString(\"ScaleControl.Miles\"));else Gi(e,n,l,t._getUIString(\"ScaleControl.Feet\"))}else if(r&&\"nautical\"===r.unit){Gi(e,n,s/1852,t._getUIString(\"ScaleControl.NauticalMiles\"))}else s>=1e3?Gi(e,n,s/1e3,t._getUIString(\"ScaleControl.Kilometers\")):Gi(e,n,s,t._getUIString(\"ScaleControl.Meters\"))}function Gi(t,e,r,n){var i,a,o,s=(i=r,a=Math.pow(10,(\"\"+Math.floor(i)).length-1),o=(o=i/a)>=10?10:o>=5?5:o>=3?3:o>=2?2:o>=1?1:function(t){var e=Math.pow(10,Math.ceil(-Math.log(t)/Math.LN10));return Math.round(t*e)/e}(o),a*o),l=s/r;t.style.width=e*l+\"px\",t.innerHTML=s+\"&nbsp;\"+n}qi.prototype.getDefaultPosition=function(){return\"bottom-left\"},qi.prototype._onMove=function(){Hi(this._map,this._container,this.options)},qi.prototype.onAdd=function(t){return this._map=t,this._container=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-scale\",t.getContainer()),this._map.on(\"move\",this._onMove),this._onMove(),this._container},qi.prototype.onRemove=function(){r.remove(this._container),this._map.off(\"move\",this._onMove),this._map=void 0},qi.prototype.setUnit=function(t){this.options.unit=t,Hi(this._map,this._container,this.options)};var Yi=function(e){this._fullscreen=!1,e&&e.container&&(e.container instanceof t.window.HTMLElement?this._container=e.container:t.warnOnce(\"Full screen control 'container' must be a DOM element.\")),t.bindAll([\"_onClickFullscreen\",\"_changeIcon\"],this),\"onfullscreenchange\"in t.window.document?this._fullscreenchange=\"fullscreenchange\":\"onmozfullscreenchange\"in t.window.document?this._fullscreenchange=\"mozfullscreenchange\":\"onwebkitfullscreenchange\"in t.window.document?this._fullscreenchange=\"webkitfullscreenchange\":\"onmsfullscreenchange\"in t.window.document&&(this._fullscreenchange=\"MSFullscreenChange\")};Yi.prototype.onAdd=function(e){return this._map=e,this._container||(this._container=this._map.getContainer()),this._controlContainer=r.create(\"div\",\"mapboxgl-ctrl mapboxgl-ctrl-group\"),this._checkFullscreenSupport()?this._setupUI():(this._controlContainer.style.display=\"none\",t.warnOnce(\"This device does not support fullscreen mode.\")),this._controlContainer},Yi.prototype.onRemove=function(){r.remove(this._controlContainer),this._map=null,t.window.document.removeEventListener(this._fullscreenchange,this._changeIcon)},Yi.prototype._checkFullscreenSupport=function(){return!!(t.window.document.fullscreenEnabled||t.window.document.mozFullScreenEnabled||t.window.document.msFullscreenEnabled||t.window.document.webkitFullscreenEnabled)},Yi.prototype._setupUI=function(){var e=this._fullscreenButton=r.create(\"button\",\"mapboxgl-ctrl-fullscreen\",this._controlContainer);r.create(\"span\",\"mapboxgl-ctrl-icon\",e).setAttribute(\"aria-hidden\",!0),e.type=\"button\",this._updateTitle(),this._fullscreenButton.addEventListener(\"click\",this._onClickFullscreen),t.window.document.addEventListener(this._fullscreenchange,this._changeIcon)},Yi.prototype._updateTitle=function(){var t=this._getTitle();this._fullscreenButton.setAttribute(\"aria-label\",t),this._fullscreenButton.title=t},Yi.prototype._getTitle=function(){return this._map._getUIString(this._isFullscreen()?\"FullscreenControl.Exit\":\"FullscreenControl.Enter\")},Yi.prototype._isFullscreen=function(){return this._fullscreen},Yi.prototype._changeIcon=function(){(t.window.document.fullscreenElement||t.window.document.mozFullScreenElement||t.window.document.webkitFullscreenElement||t.window.document.msFullscreenElement)===this._container!==this._fullscreen&&(this._fullscreen=!this._fullscreen,this._fullscreenButton.classList.toggle(\"mapboxgl-ctrl-shrink\"),this._fullscreenButton.classList.toggle(\"mapboxgl-ctrl-fullscreen\"),this._updateTitle())},Yi.prototype._onClickFullscreen=function(){this._isFullscreen()?t.window.document.exitFullscreen?t.window.document.exitFullscreen():t.window.document.mozCancelFullScreen?t.window.document.mozCancelFullScreen():t.window.document.msExitFullscreen?t.window.document.msExitFullscreen():t.window.document.webkitCancelFullScreen&&t.window.document.webkitCancelFullScreen():this._container.requestFullscreen?this._container.requestFullscreen():this._container.mozRequestFullScreen?this._container.mozRequestFullScreen():this._container.msRequestFullscreen?this._container.msRequestFullscreen():this._container.webkitRequestFullscreen&&this._container.webkitRequestFullscreen()};var Wi={closeButton:!0,closeOnClick:!0,className:\"\",maxWidth:\"240px\"},Xi=function(e){function n(r){e.call(this),this.options=t.extend(Object.create(Wi),r),t.bindAll([\"_update\",\"_onClose\",\"remove\",\"_onMouseMove\",\"_onMouseUp\",\"_onDrag\"],this)}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.addTo=function(e){return this._map&&this.remove(),this._map=e,this.options.closeOnClick&&this._map.on(\"click\",this._onClose),this.options.closeOnMove&&this._map.on(\"move\",this._onClose),this._map.on(\"remove\",this.remove),this._update(),this._trackPointer?(this._map.on(\"mousemove\",this._onMouseMove),this._map.on(\"mouseup\",this._onMouseUp),this._container&&this._container.classList.add(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.add(\"mapboxgl-track-pointer\")):this._map.on(\"move\",this._update),this.fire(new t.Event(\"open\")),this},n.prototype.isOpen=function(){return!!this._map},n.prototype.remove=function(){return this._content&&r.remove(this._content),this._container&&(r.remove(this._container),delete this._container),this._map&&(this._map.off(\"move\",this._update),this._map.off(\"move\",this._onClose),this._map.off(\"click\",this._onClose),this._map.off(\"remove\",this.remove),this._map.off(\"mousemove\",this._onMouseMove),this._map.off(\"mouseup\",this._onMouseUp),this._map.off(\"drag\",this._onDrag),delete this._map),this.fire(new t.Event(\"close\")),this},n.prototype.getLngLat=function(){return this._lngLat},n.prototype.setLngLat=function(e){return this._lngLat=t.LngLat.convert(e),this._pos=null,this._trackPointer=!1,this._update(),this._map&&(this._map.on(\"move\",this._update),this._map.off(\"mousemove\",this._onMouseMove),this._container&&this._container.classList.remove(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.remove(\"mapboxgl-track-pointer\")),this},n.prototype.trackPointer=function(){return this._trackPointer=!0,this._pos=null,this._update(),this._map&&(this._map.off(\"move\",this._update),this._map.on(\"mousemove\",this._onMouseMove),this._map.on(\"drag\",this._onDrag),this._container&&this._container.classList.add(\"mapboxgl-popup-track-pointer\"),this._map._canvasContainer.classList.add(\"mapboxgl-track-pointer\")),this},n.prototype.getElement=function(){return this._container},n.prototype.setText=function(e){return this.setDOMContent(t.window.document.createTextNode(e))},n.prototype.setHTML=function(e){var r,n=t.window.document.createDocumentFragment(),i=t.window.document.createElement(\"body\");for(i.innerHTML=e;r=i.firstChild;)n.appendChild(r);return this.setDOMContent(n)},n.prototype.getMaxWidth=function(){return this._container&&this._container.style.maxWidth},n.prototype.setMaxWidth=function(t){return this.options.maxWidth=t,this._update(),this},n.prototype.setDOMContent=function(t){return this._createContent(),this._content.appendChild(t),this._update(),this},n.prototype.addClassName=function(t){this._container&&this._container.classList.add(t)},n.prototype.removeClassName=function(t){this._container&&this._container.classList.remove(t)},n.prototype.toggleClassName=function(t){if(this._container)return this._container.classList.toggle(t)},n.prototype._createContent=function(){this._content&&r.remove(this._content),this._content=r.create(\"div\",\"mapboxgl-popup-content\",this._container),this.options.closeButton&&(this._closeButton=r.create(\"button\",\"mapboxgl-popup-close-button\",this._content),this._closeButton.type=\"button\",this._closeButton.setAttribute(\"aria-label\",\"Close popup\"),this._closeButton.innerHTML=\"&#215;\",this._closeButton.addEventListener(\"click\",this._onClose))},n.prototype._onMouseUp=function(t){this._update(t.point)},n.prototype._onMouseMove=function(t){this._update(t.point)},n.prototype._onDrag=function(t){this._update(t.point)},n.prototype._update=function(e){var n=this,i=this._lngLat||this._trackPointer;if(this._map&&i&&this._content&&(this._container||(this._container=r.create(\"div\",\"mapboxgl-popup\",this._map.getContainer()),this._tip=r.create(\"div\",\"mapboxgl-popup-tip\",this._container),this._container.appendChild(this._content),this.options.className&&this.options.className.split(\" \").forEach((function(t){return n._container.classList.add(t)})),this._trackPointer&&this._container.classList.add(\"mapboxgl-popup-track-pointer\")),this.options.maxWidth&&this._container.style.maxWidth!==this.options.maxWidth&&(this._container.style.maxWidth=this.options.maxWidth),this._map.transform.renderWorldCopies&&!this._trackPointer&&(this._lngLat=Oi(this._lngLat,this._pos,this._map.transform)),!this._trackPointer||e)){var a=this._pos=this._trackPointer&&e?e:this._map.project(this._lngLat),o=this.options.anchor,s=function e(r){if(r){if(\"number\"==typeof r){var n=Math.round(Math.sqrt(.5*Math.pow(r,2)));return{center:new t.Point(0,0),top:new t.Point(0,r),\"top-left\":new t.Point(n,n),\"top-right\":new t.Point(-n,n),bottom:new t.Point(0,-r),\"bottom-left\":new t.Point(n,-n),\"bottom-right\":new t.Point(-n,-n),left:new t.Point(r,0),right:new t.Point(-r,0)}}if(r instanceof t.Point||Array.isArray(r)){var i=t.Point.convert(r);return{center:i,top:i,\"top-left\":i,\"top-right\":i,bottom:i,\"bottom-left\":i,\"bottom-right\":i,left:i,right:i}}return{center:t.Point.convert(r.center||[0,0]),top:t.Point.convert(r.top||[0,0]),\"top-left\":t.Point.convert(r[\"top-left\"]||[0,0]),\"top-right\":t.Point.convert(r[\"top-right\"]||[0,0]),bottom:t.Point.convert(r.bottom||[0,0]),\"bottom-left\":t.Point.convert(r[\"bottom-left\"]||[0,0]),\"bottom-right\":t.Point.convert(r[\"bottom-right\"]||[0,0]),left:t.Point.convert(r.left||[0,0]),right:t.Point.convert(r.right||[0,0])}}return e(new t.Point(0,0))}(this.options.offset);if(!o){var l,c=this._container.offsetWidth,u=this._container.offsetHeight;l=a.y+s.bottom.y<u?[\"top\"]:a.y>this._map.transform.height-u?[\"bottom\"]:[],a.x<c/2?l.push(\"left\"):a.x>this._map.transform.width-c/2&&l.push(\"right\"),o=0===l.length?\"bottom\":l.join(\"-\")}var f=a.add(s[o]).round();r.setTransform(this._container,zi[o]+\" translate(\"+f.x+\"px,\"+f.y+\"px)\"),Di(this._container,o,\"popup\")}},n.prototype._onClose=function(){this.remove()},n}(t.Evented);var Zi={version:t.version,supported:e,setRTLTextPlugin:t.setRTLTextPlugin,getRTLTextPluginStatus:t.getRTLTextPluginStatus,Map:Ei,NavigationControl:Pi,GeolocateControl:Ui,AttributionControl:bi,ScaleControl:qi,FullscreenControl:Yi,Popup:Xi,Marker:Fi,Style:He,LngLat:t.LngLat,LngLatBounds:t.LngLatBounds,Point:t.Point,MercatorCoordinate:t.MercatorCoordinate,Evented:t.Evented,config:t.config,prewarm:function(){Bt().acquire(zt)},clearPrewarmedResources:function(){var t=Rt;t&&(t.isPreloaded()&&1===t.numActive()?(t.release(zt),Rt=null):console.warn(\"Could not clear WebWorkers since there are active Map instances that still reference it. The pre-warmed WebWorker pool can only be cleared when all map instances have been removed with map.remove()\"))},get accessToken(){return t.config.ACCESS_TOKEN},set accessToken(e){t.config.ACCESS_TOKEN=e},get baseApiUrl(){return t.config.API_URL},set baseApiUrl(e){t.config.API_URL=e},get workerCount(){return Dt.workerCount},set workerCount(t){Dt.workerCount=t},get maxParallelImageRequests(){return t.config.MAX_PARALLEL_IMAGE_REQUESTS},set maxParallelImageRequests(e){t.config.MAX_PARALLEL_IMAGE_REQUESTS=e},clearStorage:function(e){t.clearTileCache(e)},workerUrl:\"\"};return Zi})),r}))},{}],462:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=1<<t+1,r=new Array(e),n=0;n<e;++n)r[n]=a(t,n);return r};var n=t(\"convex-hull\");function i(t,e,r){for(var n=new Array(t),i=0;i<t;++i)n[i]=0,i===e&&(n[i]+=.5),i===r&&(n[i]+=.5);return n}function a(t,e){if(0===e||e===(1<<t+1)-1)return[];for(var r=[],a=[],o=0;o<=t;++o)if(e&1<<o){r.push(i(t,o-1,o-1)),a.push(null);for(var s=0;s<=t;++s)~e&1<<s&&(r.push(i(t,o-1,s-1)),a.push([o,s]))}var l=n(r),c=[];t:for(o=0;o<l.length;++o){var u=l[o],f=[];for(s=0;s<u.length;++s){if(!a[u[s]])continue t;f.push(a[u[s]].slice())}c.push(f)}return c}},{\"convex-hull\":141}],463:[function(t,e,r){var n=t(\"./normalize\"),i=t(\"gl-mat4/create\"),a=t(\"gl-mat4/clone\"),o=t(\"gl-mat4/determinant\"),s=t(\"gl-mat4/invert\"),l=t(\"gl-mat4/transpose\"),c={length:t(\"gl-vec3/length\"),normalize:t(\"gl-vec3/normalize\"),dot:t(\"gl-vec3/dot\"),cross:t(\"gl-vec3/cross\")},u=i(),f=i(),h=[0,0,0,0],p=[[0,0,0],[0,0,0],[0,0,0]],d=[0,0,0];function g(t,e,r,n,i){t[0]=e[0]*n+r[0]*i,t[1]=e[1]*n+r[1]*i,t[2]=e[2]*n+r[2]*i}e.exports=function(t,e,r,i,m,v){if(e||(e=[0,0,0]),r||(r=[0,0,0]),i||(i=[0,0,0]),m||(m=[0,0,0,1]),v||(v=[0,0,0,1]),!n(u,t))return!1;if(a(f,u),f[3]=0,f[7]=0,f[11]=0,f[15]=1,Math.abs(o(f)<1e-8))return!1;var y,x,b,_,w,T,k,A=u[3],M=u[7],S=u[11],E=u[12],L=u[13],C=u[14],P=u[15];if(0!==A||0!==M||0!==S){if(h[0]=A,h[1]=M,h[2]=S,h[3]=P,!s(f,f))return!1;l(f,f),y=m,b=f,_=(x=h)[0],w=x[1],T=x[2],k=x[3],y[0]=b[0]*_+b[4]*w+b[8]*T+b[12]*k,y[1]=b[1]*_+b[5]*w+b[9]*T+b[13]*k,y[2]=b[2]*_+b[6]*w+b[10]*T+b[14]*k,y[3]=b[3]*_+b[7]*w+b[11]*T+b[15]*k}else m[0]=m[1]=m[2]=0,m[3]=1;if(e[0]=E,e[1]=L,e[2]=C,function(t,e){t[0][0]=e[0],t[0][1]=e[1],t[0][2]=e[2],t[1][0]=e[4],t[1][1]=e[5],t[1][2]=e[6],t[2][0]=e[8],t[2][1]=e[9],t[2][2]=e[10]}(p,u),r[0]=c.length(p[0]),c.normalize(p[0],p[0]),i[0]=c.dot(p[0],p[1]),g(p[1],p[1],p[0],1,-i[0]),r[1]=c.length(p[1]),c.normalize(p[1],p[1]),i[0]/=r[1],i[1]=c.dot(p[0],p[2]),g(p[2],p[2],p[0],1,-i[1]),i[2]=c.dot(p[1],p[2]),g(p[2],p[2],p[1],1,-i[2]),r[2]=c.length(p[2]),c.normalize(p[2],p[2]),i[1]/=r[2],i[2]/=r[2],c.cross(d,p[1],p[2]),c.dot(p[0],d)<0)for(var I=0;I<3;I++)r[I]*=-1,p[I][0]*=-1,p[I][1]*=-1,p[I][2]*=-1;return v[0]=.5*Math.sqrt(Math.max(1+p[0][0]-p[1][1]-p[2][2],0)),v[1]=.5*Math.sqrt(Math.max(1-p[0][0]+p[1][1]-p[2][2],0)),v[2]=.5*Math.sqrt(Math.max(1-p[0][0]-p[1][1]+p[2][2],0)),v[3]=.5*Math.sqrt(Math.max(1+p[0][0]+p[1][1]+p[2][2],0)),p[2][1]>p[1][2]&&(v[0]=-v[0]),p[0][2]>p[2][0]&&(v[1]=-v[1]),p[1][0]>p[0][1]&&(v[2]=-v[2]),!0}},{\"./normalize\":464,\"gl-mat4/clone\":284,\"gl-mat4/create\":286,\"gl-mat4/determinant\":287,\"gl-mat4/invert\":299,\"gl-mat4/transpose\":312,\"gl-vec3/cross\":368,\"gl-vec3/dot\":373,\"gl-vec3/length\":383,\"gl-vec3/normalize\":390}],464:[function(t,e,r){e.exports=function(t,e){var r=e[15];if(0===r)return!1;for(var n=1/r,i=0;i<16;i++)t[i]=e[i]*n;return!0}},{}],465:[function(t,e,r){var n=t(\"gl-vec3/lerp\"),i=t(\"mat4-recompose\"),a=t(\"mat4-decompose\"),o=t(\"gl-mat4/determinant\"),s=t(\"quat-slerp\"),l=f(),c=f(),u=f();function f(){return{translate:h(),scale:h(1),skew:h(),perspective:[0,0,0,1],quaternion:[0,0,0,1]}}function 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n.identity(t),n.fromRotationTranslation(t,s,e),t[3]=o[0],t[7]=o[1],t[11]=o[2],t[15]=o[3],n.identity(i),0!==a[2]&&(i[9]=a[2],n.multiply(t,t,i)),0!==a[1]&&(i[9]=0,i[8]=a[1],n.multiply(t,t,i)),0!==a[0]&&(i[8]=0,i[4]=a[0],n.multiply(t,t,i)),n.scale(t,t,r),t}},{\"gl-mat4/create\":286,\"gl-mat4/fromRotationTranslation\":290,\"gl-mat4/identity\":297,\"gl-mat4/multiply\":301,\"gl-mat4/scale\":309,\"gl-mat4/translate\":311}],467:[function(t,e,r){\"use strict\";e.exports=Math.log2||function(t){return Math.log(t)*Math.LOG2E}},{}],468:[function(t,e,r){\"use strict\";var n=t(\"binary-search-bounds\"),i=t(\"mat4-interpolate\"),a=t(\"gl-mat4/invert\"),o=t(\"gl-mat4/rotateX\"),s=t(\"gl-mat4/rotateY\"),l=t(\"gl-mat4/rotateZ\"),c=t(\"gl-mat4/lookAt\"),u=t(\"gl-mat4/translate\"),f=(t(\"gl-mat4/scale\"),t(\"gl-vec3/normalize\")),h=[0,0,0];function 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i=this.computedMatrix,a=i[0],o=i[4],s=i[8],u=i[1],f=i[5],h=i[9],p=i[2],d=i[6],g=i[10],m=e*a+r*u,v=e*o+r*f,y=e*s+r*h,x=-(d*y-g*v),b=-(g*m-p*y),_=-(p*v-d*m),w=Math.sqrt(Math.max(0,1-Math.pow(x,2)-Math.pow(b,2)-Math.pow(_,2))),T=c(x,b,_,w);T>1e-6?(x/=T,b/=T,_/=T,w/=T):(x=b=_=0,w=1);var k=this.computedRotation,A=k[0],M=k[1],S=k[2],E=k[3],L=A*w+E*x+M*_-S*b,C=M*w+E*b+S*x-A*_,P=S*w+E*_+A*b-M*x,I=E*w-A*x-M*b-S*_;if(n){x=p,b=d,_=g;var O=Math.sin(n)/l(x,b,_);x*=O,b*=O,_*=O,I=I*(w=Math.cos(e))-(L=L*w+I*x+C*_-P*b)*x-(C=C*w+I*b+P*x-L*_)*b-(P=P*w+I*_+L*b-C*x)*_}var z=c(L,C,P,I);z>1e-6?(L/=z,C/=z,P/=z,I/=z):(L=C=P=0,I=1),this.rotation.set(t,L,C,P,I)},h.lookAt=function(t,e,r,n){this.recalcMatrix(t),r=r||this.computedCenter,e=e||this.computedEye,n=n||this.computedUp;var a=this.computedMatrix;i(a,e,r,n);var o=this.computedRotation;s(o,a[0],a[1],a[2],a[4],a[5],a[6],a[8],a[9],a[10]),u(o,o),this.rotation.set(t,o[0],o[1],o[2],o[3]);for(var l=0,c=0;c<3;++c)l+=Math.pow(r[c]-e[c],2);this.radius.set(t,.5*Math.log(Math.max(l,1e-6))),this.center.set(t,r[0],r[1],r[2])},h.translate=function(t,e,r,n){this.center.move(t,e||0,r||0,n||0)},h.setMatrix=function(t,e){var r=this.computedRotation;s(r,e[0],e[1],e[2],e[4],e[5],e[6],e[8],e[9],e[10]),u(r,r),this.rotation.set(t,r[0],r[1],r[2],r[3]);var n=this.computedMatrix;o(n,e);var i=n[15];if(Math.abs(i)>1e-6){var a=n[12]/i,l=n[13]/i,c=n[14]/i;this.recalcMatrix(t);var f=Math.exp(this.computedRadius[0]);this.center.set(t,a-n[2]*f,l-n[6]*f,c-n[10]*f),this.radius.idle(t)}else this.center.idle(t),this.radius.idle(t)},h.setDistance=function(t,e){e>0&&this.radius.set(t,Math.log(e))},h.setDistanceLimits=function(t,e){t=t>0?Math.log(t):-1/0,e=e>0?Math.log(e):1/0,e=Math.max(e,t),this.radius.bounds[0][0]=t,this.radius.bounds[1][0]=e},h.getDistanceLimits=function(t){var e=this.radius.bounds;return 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+       "/*!\n",
+       " * pad-left <https://github.com/jonschlinkert/pad-left>\n",
+       " *\n",
+       " * Copyright (c) 2014-2015, Jon Schlinkert.\n",
+       " * Licensed under the MIT license.\n",
+       " */\n",
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+       "/*\n",
+       " * @copyright 2016 Sean Connelly (@voidqk), http://syntheti.cc\n",
+       " * @license MIT\n",
+       " * @preserve Project Home: https://github.com/voidqk/polybooljs\n",
+       " */\n",
+       "var n,i=t(\"./lib/build-log\"),a=t(\"./lib/epsilon\"),o=t(\"./lib/intersecter\"),s=t(\"./lib/segment-chainer\"),l=t(\"./lib/segment-selector\"),c=t(\"./lib/geojson\"),u=!1,f=a();function h(t,e,r){var i=n.segments(t),a=n.segments(e),o=r(n.combine(i,a));return n.polygon(o)}n={buildLog:function(t){return!0===t?u=i():!1===t&&(u=!1),!1!==u&&u.list},epsilon:function(t){return f.epsilon(t)},segments:function(t){var e=o(!0,f,u);return 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a=n[t],o=n[i],s=a[a.length-1],l=a[a.length-2],c=o[0],u=o[1];e.pointsCollinear(l,s,c)&&(r&&r.chainRemoveTail(t,s),a.pop(),s=l),e.pointsCollinear(s,c,u)&&(r&&r.chainRemoveHead(i,c),o.shift()),r&&r.chainJoin(t,i),n[t]=a.concat(o),n.splice(i,1)}})),i}},{}],511:[function(t,e,r){function n(t,e,r){var n=[];return t.forEach((function(t){var i=(t.myFill.above?8:0)+(t.myFill.below?4:0)+(t.otherFill&&t.otherFill.above?2:0)+(t.otherFill&&t.otherFill.below?1:0);0!==e[i]&&n.push({id:r?r.segmentId():-1,start:t.start,end:t.end,myFill:{above:1===e[i],below:2===e[i]},otherFill:null})})),r&&r.selected(n),n}var i={union:function(t,e){return n(t,[0,2,1,0,2,2,0,0,1,0,1,0,0,0,0,0],e)},intersect:function(t,e){return n(t,[0,0,0,0,0,2,0,2,0,0,1,1,0,2,1,0],e)},difference:function(t,e){return n(t,[0,0,0,0,2,0,2,0,1,1,0,0,0,1,2,0],e)},differenceRev:function(t,e){return n(t,[0,2,1,0,0,0,1,1,0,2,0,2,0,0,0,0],e)},xor:function(t,e){return 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n=e,i=0;i<r.length;)if(t[n++]!==r[i++])return!1;return!0},r.str2arr=function(t,e){var r=[],n=0;if(e&&\"hex\"===e)for(;n<t.length;)r.push(parseInt(t.slice(n,n+2),16)),n+=2;else for(;n<t.length;n++)r.push(255&t.charCodeAt(n));return r},r.readUInt16LE=function(t,e){return t[e]|t[e+1]<<8},r.readUInt16BE=function(t,e){return t[e+1]|t[e]<<8},r.readUInt32LE=function(t,e){return t[e]|t[e+1]<<8|t[e+2]<<16|16777216*t[e+3]},r.readUInt32BE=function(t,e){return t[e+3]|t[e+2]<<8|t[e+1]<<16|16777216*t[e]},o.prototype=Object.create(Error.prototype),o.prototype.constructor=o,r.ProbeError=o},{stream:569,\"stream-parser\":585}],514:[function(t,e,r){\"use strict\";function n(t,e){var r=new Error(t);return r.code=e,r}function i(t){try{return decodeURIComponent(escape(t))}catch(e){return t}}function a(t,e,r){this.input=t.subarray(e,r),this.start=e;var i=String.fromCharCode.apply(null,this.input.subarray(0,4));if(\"II*\\0\"!==i&&\"MM\\0*\"!==i)throw n(\"invalid TIFF 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0}},a.prototype.exif_format_read=function(t,e){var r;switch(t){case 1:case 2:return r=this.input[e];case 6:return(r=this.input[e])|33554430*(128&r);case 3:return r=this.read_uint16(e);case 8:return(r=this.read_uint16(e))|131070*(32768&r);case 4:return r=this.read_uint32(e);case 9:return 0|(r=this.read_uint32(e));case 5:case 10:case 11:case 12:case 7:default:return null}},a.prototype.scan_ifd=function(t,e,r){var a=this.read_uint16(e);e+=2;for(var o=0;o<a;o++){var s=this.read_uint16(e),l=this.read_uint16(e+2),c=this.read_uint32(e+4),u=this.exif_format_length(l),f=c*u,h=f<=4?e+8:this.read_uint32(e+8),p=!1;if(h+f>this.input.length)throw n(\"unexpected EOF\",\"EBADDATA\");for(var d=[],g=h,m=0;m<c;m++,g+=u){var v=this.exif_format_read(l,g);if(null===v){d=null;break}d.push(v)}if(Array.isArray(d)&&2===l&&(d=i(String.fromCharCode.apply(null,d)))&&\"\\0\"===d[d.length-1]&&(d=d.slice(0,-1)),this.is_subifd_link(t,s)&&Array.isArray(d)&&Number.isInteger(d[0])&&d[0]>0&&(this.ifds_to_read.push({id:s,offset:d[0]}),p=!0),!1===r({is_big_endian:this.big_endian,ifd:t,tag:s,format:l,count:c,entry_offset:e+this.start,data_length:f,data_offset:h+this.start,value:d,is_subifd_link:p}))return void(this.aborted=!0);e+=12}0===t&&this.ifds_to_read.push({id:1,offset:this.read_uint32(e)})},e.exports.ExifParser=a,e.exports.get_orientation=function(t){var e=0;try{return new a(t,0,t.length).each((function(t){if(0===t.ifd&&274===t.tag&&Array.isArray(t.value))return e=t.value[0],!1})),e}catch(t){return-1}}},{}],515:[function(t,e,r){\"use strict\";var n=t(\"./common\").readUInt16BE,i=t(\"./common\").readUInt32BE;function a(t,e){if(t.length<4+e)return null;var r=i(t,e);return t.length<r+e||r<8?null:{boxtype:String.fromCharCode.apply(null,t.slice(e+4,e+8)),data:t.slice(e+8,e+r),end:e+r}}function o(t,e){for(var r=0;;){var n=a(t,r);if(!n)break;switch(n.boxtype){case\"ispe\":e.sizes.push({width:i(n.data,4),height:i(n.data,8)});break;case\"irot\":e.transforms.push({type:\"irot\",value:3&n.data[0]});break;case\"imir\":e.transforms.push({type:\"imir\",value:1&n.data[0]})}r=n.end}}function s(t,e,r){for(var n=0,i=0;i<r;i++)n=256*n+(t[e+i]||0);return n}function l(t,e){for(var r=t[4]>>4&15,i=15&t[4],a=t[5]>>4&15,o=n(t,6),l=8,c=0;c<o;c++){var u=n(t,l),f=n(t,l+=2),h=s(t,l+=2,a),p=n(t,l+=a);if(l+=2,0===f&&1===p){var d=s(t,l,r),g=s(t,l+r,i);e.item_loc[u]={length:g,offset:d+h}}l+=p*(r+i)}}function c(t,e){for(var r=n(t,4),i=6,o=0;o<r;o++){var s=a(t,i);if(!s)break;if(\"infe\"===s.boxtype){for(var l=n(s.data,4),c=\"\",u=8;u<s.data.length&&s.data[u];u++)c+=String.fromCharCode(s.data[u]);e.item_inf[c]=l}i=s.end}}function u(t,e){for(var r=0;;){var n=a(t,r);if(!n)break;\"ipco\"===n.boxtype&&o(n.data,e),r=n.end}}e.exports.unbox=a,e.exports.readSizeFromMeta=function(t){var e={sizes:[],transforms:[],item_inf:{},item_loc:{}};if(function(t,e){for(var r=4;;){var n=a(t,r);if(!n)break;\"iprp\"===n.boxtype&&u(n.data,e),\"iloc\"===n.boxtype&&l(n.data,e),\"iinf\"===n.boxtype&&c(n.data,e),r=n.end}}(t,e),e.sizes.length){var r,n,i,o=(r=e.sizes,n=r.reduce((function(t,e){return t.width>e.width||t.width===e.width&&t.height>e.height?t:e})),i=r.reduce((function(t,e){return t.height>e.height||t.height===e.height&&t.width>e.width?t:e})),n.width>i.height||n.width===i.height&&n.height>i.width?n:i),s=1;e.transforms.forEach((function(t){var e={1:6,2:5,3:8,4:7,5:4,6:3,7:2,8:1},r={1:4,2:3,3:2,4:1,5:6,6:5,7:8,8:7};if(\"imir\"===t.type&&(s=0===t.value?r[s]:e[s=e[s=r[s]]]),\"irot\"===t.type)for(var n=0;n<t.value;n++)s=e[s]}));var f=null;return e.item_inf.Exif&&(f=e.item_loc[e.item_inf.Exif]),{width:o.width,height:o.height,orientation:e.transforms.length?s:null,variants:e.sizes,exif_location:f}}},e.exports.getMimeType=function(t){var e=String.fromCharCode.apply(null,t.slice(0,4)),r={};r[e]=!0;for(var n=8;n<t.length;n+=4)r[String.fromCharCode.apply(null,t.slice(n,n+4))]=!0;if(r.mif1||r.msf1||r.miaf)return\"avif\"===e||\"avis\"===e||\"avio\"===e?{type:\"avif\",mime:\"image/avif\"}:\"heic\"===e||\"heix\"===e?{type:\"heic\",mime:\"image/heic\"}:\"hevc\"===e||\"hevx\"===e?{type:\"heic\",mime:\"image/heic-sequence\"}:r.avif||r.avis?{type:\"avif\",mime:\"image/avif\"}:r.heic||r.heix||r.hevc||r.hevx||r.heis?r.msf1?{type:\"heif\",mime:\"image/heif-sequence\"}:{type:\"heif\",mime:\"image/heif\"}:{type:\"avif\",mime:\"image/avif\"}}},{\"./common\":513}],516:[function(t,e,r){\"use strict\";var n=t(\"../common\").str2arr,i=t(\"../common\").sliceEq,a=t(\"../common\").readUInt32BE,o=t(\"../miaf_utils\"),s=t(\"../exif_utils\"),l=n(\"ftyp\");e.exports=function(t){if(i(t,4,l)){var e=o.unbox(t,0);if(e){var r=o.getMimeType(e.data);if(r){for(var n,c=e.end;;){var u=o.unbox(t,c);if(!u)break;if(c=u.end,\"mdat\"===u.boxtype)return;if(\"meta\"===u.boxtype){n=u.data;break}}if(n){var f=o.readSizeFromMeta(n);if(f){var h={width:f.width,height:f.height,type:r.type,mime:r.mime,wUnits:\"px\",hUnits:\"px\"};if(f.variants.length>1&&(h.variants=f.variants),f.orientation&&(h.orientation=f.orientation),f.exif_location&&f.exif_location.offset+f.exif_location.length<=t.length){var p=a(t,f.exif_location.offset),d=t.slice(f.exif_location.offset+p+4,f.exif_location.offset+f.exif_location.length),g=s.get_orientation(d);g>0&&(h.orientation=g)}return h}}}}}}},{\"../common\":513,\"../exif_utils\":514,\"../miaf_utils\":515}],517:[function(t,e,r){\"use strict\";var n=t(\"../common\").str2arr,i=t(\"../common\").sliceEq,a=t(\"../common\").readUInt16LE,o=n(\"BM\");e.exports=function(t){if(!(t.length<26)&&i(t,0,o))return{width:a(t,18),height:a(t,22),type:\"bmp\",mime:\"image/bmp\",wUnits:\"px\",hUnits:\"px\"}}},{\"../common\":513}],518:[function(t,e,r){\"use strict\";var n=t(\"../common\").str2arr,i=t(\"../common\").sliceEq,a=t(\"../common\").readUInt16LE,o=n(\"GIF87a\"),s=n(\"GIF89a\");e.exports=function(t){if(!(t.length<10)&&(i(t,0,o)||i(t,0,s)))return{width:a(t,6),height:a(t,8),type:\"gif\",mime:\"image/gif\",wUnits:\"px\",hUnits:\"px\"}}},{\"../common\":513}],519:[function(t,e,r){\"use strict\";var n=t(\"../common\").readUInt16LE;e.exports=function(t){var e=n(t,0),r=n(t,2),i=n(t,4);if(0===e&&1===r&&i){for(var a=[],o={width:0,height:0},s=0;s<i;s++){var 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n=t(\"color-normalize\"),i=t(\"array-bounds\"),a=t(\"object-assign\"),o=t(\"glslify\"),s=t(\"pick-by-alias\"),l=t(\"flatten-vertex-data\"),c=t(\"earcut\"),u=t(\"array-normalize\"),f=t(\"to-float32\"),h=f.float32,p=f.fract32,d=t(\"es6-weak-map\"),g=t(\"parse-rect\"),m=t(\"array-find-index\");function v(t,e){if(!(this instanceof v))return new v(t,e);if(\"function\"==typeof t?(e||(e={}),e.regl=t):e=t,e.length&&(e.positions=e),!(t=e.regl).hasExtension(\"ANGLE_instanced_arrays\"))throw Error(\"regl-error2d: `ANGLE_instanced_arrays` extension should be enabled\");this.gl=t._gl,this.regl=t,this.passes=[],this.shaders=v.shaders.has(t)?v.shaders.get(t):v.shaders.set(t,v.createShaders(t)).get(t),this.update(e)}e.exports=v,v.dashMult=2,v.maxPatternLength=256,v.precisionThreshold=3e6,v.maxPoints=1e4,v.maxLines=2048,v.shaders=new d,v.createShaders=function(t){var e,r=t.buffer({usage:\"static\",type:\"float\",data:[0,1,0,0,1,1,1,0]}),n={primitive:\"triangle strip\",instances:t.prop(\"count\"),count:4,offset:0,uniforms:{miterMode:function(t,e){return\"round\"===e.join?2:1},miterLimit:t.prop(\"miterLimit\"),scale:t.prop(\"scale\"),scaleFract:t.prop(\"scaleFract\"),translateFract:t.prop(\"translateFract\"),translate:t.prop(\"translate\"),thickness:t.prop(\"thickness\"),dashPattern:t.prop(\"dashTexture\"),opacity:t.prop(\"opacity\"),pixelRatio:t.context(\"pixelRatio\"),id:t.prop(\"id\"),dashSize:t.prop(\"dashLength\"),viewport:function(t,e){return[e.viewport.x,e.viewport.y,t.viewportWidth,t.viewportHeight]},depth:t.prop(\"depth\")},blend:{enable:!0,color:[0,0,0,0],equation:{rgb:\"add\",alpha:\"add\"},func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:\"one minus dst alpha\",dstAlpha:\"one\"}},depth:{enable:function(t,e){return!e.overlay}},stencil:{enable:!1},scissor:{enable:!0,box:t.prop(\"viewport\")},viewport:t.prop(\"viewport\")},i=t(a({vert:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 aCoord, bCoord, aCoordFract, bCoordFract;\\nattribute vec4 color;\\nattribute float lineEnd, lineTop;\\n\\nuniform vec2 scale, scaleFract, translate, translateFract;\\nuniform float thickness, pixelRatio, id, depth;\\nuniform vec4 viewport;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\n\\nvec2 project(vec2 position, vec2 positionFract, vec2 scale, vec2 scaleFract, vec2 translate, vec2 translateFract) {\\n\\t// the order is important\\n\\treturn position * scale + translate\\n       + positionFract * scale + translateFract\\n       + position * scaleFract\\n       + positionFract * scaleFract;\\n}\\n\\nvoid main() {\\n\\tfloat lineStart = 1. - lineEnd;\\n\\tfloat lineOffset = lineTop * 2. - 1.;\\n\\n\\tvec2 diff = (bCoord + bCoordFract - aCoord - aCoordFract);\\n\\ttangent = normalize(diff * scale * viewport.zw);\\n\\tvec2 normal = vec2(-tangent.y, tangent.x);\\n\\n\\tvec2 position = project(aCoord, aCoordFract, scale, scaleFract, translate, translateFract) * lineStart\\n\\t\\t+ project(bCoord, bCoordFract, scale, scaleFract, translate, translateFract) * lineEnd\\n\\n\\t\\t+ thickness * normal * .5 * lineOffset / viewport.zw;\\n\\n\\tgl_Position = vec4(position * 2.0 - 1.0, depth, 1);\\n\\n\\tfragColor = color / 255.;\\n}\\n\"]),frag:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D dashPattern;\\n\\nuniform float dashSize, pixelRatio, thickness, opacity, id;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\n\\nvoid main() {\\n\\tfloat alpha = 1.;\\n\\n\\tfloat t = fract(dot(tangent, gl_FragCoord.xy) / dashSize) * .5 + .25;\\n\\tfloat dash = texture2D(dashPattern, vec2(t, .5)).r;\\n\\n\\tgl_FragColor = fragColor;\\n\\tgl_FragColor.a *= alpha * opacity * dash;\\n}\\n\"]),attributes:{lineEnd:{buffer:r,divisor:0,stride:8,offset:0},lineTop:{buffer:r,divisor:0,stride:8,offset:4},aCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:8,divisor:1},bCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:16,divisor:1},aCoordFract:{buffer:t.prop(\"positionFractBuffer\"),stride:8,offset:8,divisor:1},bCoordFract:{buffer:t.prop(\"positionFractBuffer\"),stride:8,offset:16,divisor:1},color:{buffer:t.prop(\"colorBuffer\"),stride:4,offset:0,divisor:1}}},n));try{e=t(a({cull:{enable:!0,face:\"back\"},vert:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 aCoord, bCoord, nextCoord, prevCoord;\\nattribute vec4 aColor, bColor;\\nattribute float lineEnd, lineTop;\\n\\nuniform vec2 scale, translate;\\nuniform float thickness, pixelRatio, id, depth;\\nuniform vec4 viewport;\\nuniform float miterLimit, miterMode;\\n\\nvarying vec4 fragColor;\\nvarying vec4 startCutoff, endCutoff;\\nvarying vec2 tangent;\\nvarying vec2 startCoord, endCoord;\\nvarying float enableStartMiter, enableEndMiter;\\n\\nconst float REVERSE_THRESHOLD = -.875;\\nconst float MIN_DIFF = 1e-6;\\n\\n// TODO: possible optimizations: avoid overcalculating all for vertices and calc just one instead\\n// TODO: precalculate dot products, normalize things beforehead etc.\\n// TODO: refactor to rectangular algorithm\\n\\nfloat distToLine(vec2 p, vec2 a, vec2 b) {\\n\\tvec2 diff = b - a;\\n\\tvec2 perp = normalize(vec2(-diff.y, diff.x));\\n\\treturn dot(p - a, perp);\\n}\\n\\nbool isNaN( float val ){\\n  return ( val < 0.0 || 0.0 < val || val == 0.0 ) ? false : true;\\n}\\n\\nvoid main() {\\n\\tvec2 aCoord = aCoord, bCoord = bCoord, prevCoord = prevCoord, nextCoord = nextCoord;\\n\\n  vec2 adjustedScale;\\n  adjustedScale.x = (abs(scale.x) < MIN_DIFF) ? MIN_DIFF : scale.x;\\n  adjustedScale.y = (abs(scale.y) < MIN_DIFF) ? MIN_DIFF : scale.y;\\n\\n  vec2 scaleRatio = adjustedScale * viewport.zw;\\n\\tvec2 normalWidth = thickness / scaleRatio;\\n\\n\\tfloat lineStart = 1. - lineEnd;\\n\\tfloat lineBot = 1. - lineTop;\\n\\n\\tfragColor = (lineStart * aColor + lineEnd * bColor) / 255.;\\n\\n\\tif (isNaN(aCoord.x) || isNaN(aCoord.y) || isNaN(bCoord.x) || isNaN(bCoord.y)) return;\\n\\n\\tif (aCoord == prevCoord) prevCoord = aCoord + normalize(bCoord - aCoord);\\n\\tif (bCoord == nextCoord) nextCoord = bCoord - normalize(bCoord - aCoord);\\n\\n\\tvec2 prevDiff = aCoord - prevCoord;\\n\\tvec2 currDiff = bCoord - aCoord;\\n\\tvec2 nextDiff = nextCoord - bCoord;\\n\\n\\tvec2 prevTangent = normalize(prevDiff * scaleRatio);\\n\\tvec2 currTangent = normalize(currDiff * scaleRatio);\\n\\tvec2 nextTangent = normalize(nextDiff * scaleRatio);\\n\\n\\tvec2 prevNormal = vec2(-prevTangent.y, prevTangent.x);\\n\\tvec2 currNormal = vec2(-currTangent.y, currTangent.x);\\n\\tvec2 nextNormal = vec2(-nextTangent.y, nextTangent.x);\\n\\n\\tvec2 startJoinDirection = normalize(prevTangent - currTangent);\\n\\tvec2 endJoinDirection = normalize(currTangent - nextTangent);\\n\\n\\t// collapsed/unidirectional segment cases\\n\\t// FIXME: there should be more elegant solution\\n\\tvec2 prevTanDiff = abs(prevTangent - currTangent);\\n\\tvec2 nextTanDiff = abs(nextTangent - currTangent);\\n\\tif (max(prevTanDiff.x, prevTanDiff.y) < MIN_DIFF) {\\n\\t\\tstartJoinDirection = currNormal;\\n\\t}\\n\\tif (max(nextTanDiff.x, nextTanDiff.y) < MIN_DIFF) {\\n\\t\\tendJoinDirection = currNormal;\\n\\t}\\n\\tif (aCoord == bCoord) {\\n\\t\\tendJoinDirection = startJoinDirection;\\n\\t\\tcurrNormal = prevNormal;\\n\\t\\tcurrTangent = prevTangent;\\n\\t}\\n\\n\\ttangent = currTangent;\\n\\n\\t//calculate join shifts relative to normals\\n\\tfloat startJoinShift = dot(currNormal, startJoinDirection);\\n\\tfloat endJoinShift = dot(currNormal, endJoinDirection);\\n\\n\\tfloat startMiterRatio = abs(1. / startJoinShift);\\n\\tfloat endMiterRatio = abs(1. / endJoinShift);\\n\\n\\tvec2 startJoin = startJoinDirection * startMiterRatio;\\n\\tvec2 endJoin = endJoinDirection * endMiterRatio;\\n\\n\\tvec2 startTopJoin, startBotJoin, endTopJoin, endBotJoin;\\n\\tstartTopJoin = sign(startJoinShift) * startJoin * .5;\\n\\tstartBotJoin = -startTopJoin;\\n\\n\\tendTopJoin = sign(endJoinShift) * endJoin * .5;\\n\\tendBotJoin = -endTopJoin;\\n\\n\\tvec2 aTopCoord = aCoord + normalWidth * startTopJoin;\\n\\tvec2 bTopCoord = bCoord + normalWidth * endTopJoin;\\n\\tvec2 aBotCoord = aCoord + normalWidth * startBotJoin;\\n\\tvec2 bBotCoord = bCoord + normalWidth * endBotJoin;\\n\\n\\t//miter anti-clipping\\n\\tfloat baClipping = distToLine(bCoord, aCoord, aBotCoord) / dot(normalize(normalWidth * endBotJoin), normalize(normalWidth.yx * vec2(-startBotJoin.y, startBotJoin.x)));\\n\\tfloat abClipping = distToLine(aCoord, bCoord, bTopCoord) / dot(normalize(normalWidth * startBotJoin), normalize(normalWidth.yx * vec2(-endBotJoin.y, endBotJoin.x)));\\n\\n\\t//prevent close to reverse direction switch\\n\\tbool prevReverse = dot(currTangent, prevTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, prevNormal)) * min(length(prevDiff), length(currDiff)) <  length(normalWidth * currNormal);\\n\\tbool nextReverse = dot(currTangent, nextTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, nextNormal)) * min(length(nextDiff), length(currDiff)) <  length(normalWidth * currNormal);\\n\\n\\tif (prevReverse) {\\n\\t\\t//make join rectangular\\n\\t\\tvec2 miterShift = normalWidth * startJoinDirection * miterLimit * .5;\\n\\t\\tfloat normalAdjust = 1. - min(miterLimit / startMiterRatio, 1.);\\n\\t\\taBotCoord = aCoord + miterShift - normalAdjust * normalWidth * currNormal * .5;\\n\\t\\taTopCoord = aCoord + miterShift + normalAdjust * normalWidth * currNormal * .5;\\n\\t}\\n\\telse if (!nextReverse && baClipping > 0. && baClipping < length(normalWidth * endBotJoin)) {\\n\\t\\t//handle miter clipping\\n\\t\\tbTopCoord -= normalWidth * endTopJoin;\\n\\t\\tbTopCoord += normalize(endTopJoin * normalWidth) * baClipping;\\n\\t}\\n\\n\\tif (nextReverse) {\\n\\t\\t//make join rectangular\\n\\t\\tvec2 miterShift = normalWidth * endJoinDirection * miterLimit * .5;\\n\\t\\tfloat normalAdjust = 1. - min(miterLimit / endMiterRatio, 1.);\\n\\t\\tbBotCoord = bCoord + miterShift - normalAdjust * normalWidth * currNormal * .5;\\n\\t\\tbTopCoord = bCoord + miterShift + normalAdjust * normalWidth * currNormal * .5;\\n\\t}\\n\\telse if (!prevReverse && abClipping > 0. && abClipping < length(normalWidth * startBotJoin)) {\\n\\t\\t//handle miter clipping\\n\\t\\taBotCoord -= normalWidth * startBotJoin;\\n\\t\\taBotCoord += normalize(startBotJoin * normalWidth) * abClipping;\\n\\t}\\n\\n\\tvec2 aTopPosition = (aTopCoord) * adjustedScale + translate;\\n\\tvec2 aBotPosition = (aBotCoord) * adjustedScale + translate;\\n\\n\\tvec2 bTopPosition = (bTopCoord) * adjustedScale + translate;\\n\\tvec2 bBotPosition = (bBotCoord) * adjustedScale + translate;\\n\\n\\t//position is normalized 0..1 coord on the screen\\n\\tvec2 position = (aTopPosition * lineTop + aBotPosition * lineBot) * lineStart + (bTopPosition * lineTop + bBotPosition * lineBot) * lineEnd;\\n\\n\\tstartCoord = aCoord * scaleRatio + translate * viewport.zw + viewport.xy;\\n\\tendCoord = bCoord * scaleRatio + translate * viewport.zw + viewport.xy;\\n\\n\\tgl_Position = vec4(position  * 2.0 - 1.0, depth, 1);\\n\\n\\tenableStartMiter = step(dot(currTangent, prevTangent), .5);\\n\\tenableEndMiter = step(dot(currTangent, nextTangent), .5);\\n\\n\\t//bevel miter cutoffs\\n\\tif (miterMode == 1.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tvec2 startMiterWidth = vec2(startJoinDirection) * thickness * miterLimit * .5;\\n\\t\\t\\tstartCutoff = vec4(aCoord, aCoord);\\n\\t\\t\\tstartCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio;\\n\\t\\t\\tstartCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tstartCutoff += viewport.xyxy;\\n\\t\\t\\tstartCutoff += startMiterWidth.xyxy;\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tvec2 endMiterWidth = vec2(endJoinDirection) * thickness * miterLimit * .5;\\n\\t\\t\\tendCutoff = vec4(bCoord, bCoord);\\n\\t\\t\\tendCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x)  / scaleRatio;\\n\\t\\t\\tendCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tendCutoff += viewport.xyxy;\\n\\t\\t\\tendCutoff += endMiterWidth.xyxy;\\n\\t\\t}\\n\\t}\\n\\n\\t//round miter cutoffs\\n\\telse if (miterMode == 2.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tvec2 startMiterWidth = vec2(startJoinDirection) * thickness * abs(dot(startJoinDirection, currNormal)) * .5;\\n\\t\\t\\tstartCutoff = vec4(aCoord, aCoord);\\n\\t\\t\\tstartCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio;\\n\\t\\t\\tstartCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tstartCutoff += viewport.xyxy;\\n\\t\\t\\tstartCutoff += startMiterWidth.xyxy;\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tvec2 endMiterWidth = vec2(endJoinDirection) * thickness * abs(dot(endJoinDirection, currNormal)) * .5;\\n\\t\\t\\tendCutoff = vec4(bCoord, bCoord);\\n\\t\\t\\tendCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x)  / scaleRatio;\\n\\t\\t\\tendCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\\n\\t\\t\\tendCutoff += viewport.xyxy;\\n\\t\\t\\tendCutoff += endMiterWidth.xyxy;\\n\\t\\t}\\n\\t}\\n}\\n\"]),frag:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nuniform sampler2D dashPattern;\\nuniform float dashSize, pixelRatio, thickness, opacity, id, miterMode;\\n\\nvarying vec4 fragColor;\\nvarying vec2 tangent;\\nvarying vec4 startCutoff, endCutoff;\\nvarying vec2 startCoord, endCoord;\\nvarying float enableStartMiter, enableEndMiter;\\n\\nfloat distToLine(vec2 p, vec2 a, vec2 b) {\\n\\tvec2 diff = b - a;\\n\\tvec2 perp = normalize(vec2(-diff.y, diff.x));\\n\\treturn dot(p - a, perp);\\n}\\n\\nvoid main() {\\n\\tfloat alpha = 1., distToStart, distToEnd;\\n\\tfloat cutoff = thickness * .5;\\n\\n\\t//bevel miter\\n\\tif (miterMode == 1.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tdistToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw);\\n\\t\\t\\tif (distToStart < -1.) {\\n\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\treturn;\\n\\t\\t\\t}\\n\\t\\t\\talpha *= min(max(distToStart + 1., 0.), 1.);\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tdistToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw);\\n\\t\\t\\tif (distToEnd < -1.) {\\n\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\treturn;\\n\\t\\t\\t}\\n\\t\\t\\talpha *= min(max(distToEnd + 1., 0.), 1.);\\n\\t\\t}\\n\\t}\\n\\n\\t// round miter\\n\\telse if (miterMode == 2.) {\\n\\t\\tif (enableStartMiter == 1.) {\\n\\t\\t\\tdistToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw);\\n\\t\\t\\tif (distToStart < 0.) {\\n\\t\\t\\t\\tfloat radius = length(gl_FragCoord.xy - startCoord);\\n\\n\\t\\t\\t\\tif(radius > cutoff + .5) {\\n\\t\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\t\\treturn;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\talpha -= smoothstep(cutoff - .5, cutoff + .5, radius);\\n\\t\\t\\t}\\n\\t\\t}\\n\\n\\t\\tif (enableEndMiter == 1.) {\\n\\t\\t\\tdistToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw);\\n\\t\\t\\tif (distToEnd < 0.) {\\n\\t\\t\\t\\tfloat radius = length(gl_FragCoord.xy - endCoord);\\n\\n\\t\\t\\t\\tif(radius > cutoff + .5) {\\n\\t\\t\\t\\t\\tdiscard;\\n\\t\\t\\t\\t\\treturn;\\n\\t\\t\\t\\t}\\n\\n\\t\\t\\t\\talpha -= smoothstep(cutoff - .5, cutoff + .5, radius);\\n\\t\\t\\t}\\n\\t\\t}\\n\\t}\\n\\n\\tfloat t = fract(dot(tangent, gl_FragCoord.xy) / dashSize) * .5 + .25;\\n\\tfloat dash = texture2D(dashPattern, vec2(t, .5)).r;\\n\\n\\tgl_FragColor = fragColor;\\n\\tgl_FragColor.a *= alpha * opacity * dash;\\n}\\n\"]),attributes:{lineEnd:{buffer:r,divisor:0,stride:8,offset:0},lineTop:{buffer:r,divisor:0,stride:8,offset:4},aColor:{buffer:t.prop(\"colorBuffer\"),stride:4,offset:0,divisor:1},bColor:{buffer:t.prop(\"colorBuffer\"),stride:4,offset:4,divisor:1},prevCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:0,divisor:1},aCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:8,divisor:1},bCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:16,divisor:1},nextCoord:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:24,divisor:1}}},n))}catch(t){e=i}return{fill:t({primitive:\"triangle\",elements:function(t,e){return e.triangles},offset:0,vert:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute vec2 position, positionFract;\\n\\nuniform vec4 color;\\nuniform vec2 scale, scaleFract, translate, translateFract;\\nuniform float pixelRatio, id;\\nuniform vec4 viewport;\\nuniform float opacity;\\n\\nvarying vec4 fragColor;\\n\\nconst float MAX_LINES = 256.;\\n\\nvoid main() {\\n\\tfloat depth = (MAX_LINES - 4. - id) / (MAX_LINES);\\n\\n\\tvec2 position = position * scale + translate\\n       + positionFract * scale + translateFract\\n       + position * scaleFract\\n       + positionFract * scaleFract;\\n\\n\\tgl_Position = vec4(position * 2.0 - 1.0, depth, 1);\\n\\n\\tfragColor = color / 255.;\\n\\tfragColor.a *= opacity;\\n}\\n\"]),frag:o([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n\\tgl_FragColor = fragColor;\\n}\\n\"]),uniforms:{scale:t.prop(\"scale\"),color:t.prop(\"fill\"),scaleFract:t.prop(\"scaleFract\"),translateFract:t.prop(\"translateFract\"),translate:t.prop(\"translate\"),opacity:t.prop(\"opacity\"),pixelRatio:t.context(\"pixelRatio\"),id:t.prop(\"id\"),viewport:function(t,e){return[e.viewport.x,e.viewport.y,t.viewportWidth,t.viewportHeight]}},attributes:{position:{buffer:t.prop(\"positionBuffer\"),stride:8,offset:8},positionFract:{buffer:t.prop(\"positionFractBuffer\"),stride:8,offset:8}},blend:n.blend,depth:{enable:!1},scissor:n.scissor,stencil:n.stencil,viewport:n.viewport}),rect:i,miter:e}},v.defaults={dashes:null,join:\"miter\",miterLimit:1,thickness:10,cap:\"square\",color:\"black\",opacity:1,overlay:!1,viewport:null,range:null,close:!1,fill:null},v.prototype.render=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];e.length&&(t=this).update.apply(t,e),this.draw()},v.prototype.draw=function(){for(var t=this,e=[],r=arguments.length;r--;)e[r]=arguments[r];return(e.length?e:this.passes).forEach((function(e,r){var n;if(e&&Array.isArray(e))return(n=t).draw.apply(n,e);\"number\"==typeof e&&(e=t.passes[e]),e&&e.count>1&&e.opacity&&(t.regl._refresh(),e.fill&&e.triangles&&e.triangles.length>2&&t.shaders.fill(e),e.thickness&&(e.scale[0]*e.viewport.width>v.precisionThreshold||e.scale[1]*e.viewport.height>v.precisionThreshold||\"rect\"===e.join||!e.join&&(e.thickness<=2||e.count>=v.maxPoints)?t.shaders.rect(e):t.shaders.miter(e)))})),this},v.prototype.update=function(t){var e=this;if(t){null!=t.length?\"number\"==typeof t[0]&&(t=[{positions:t}]):Array.isArray(t)||(t=[t]);var r=this.regl,o=this.gl;if(t.forEach((function(t,f){var d=e.passes[f];if(void 0!==t)if(null!==t){if(\"number\"==typeof t[0]&&(t={positions:t}),t=s(t,{positions:\"positions points data coords\",thickness:\"thickness lineWidth lineWidths line-width linewidth width stroke-width strokewidth strokeWidth\",join:\"lineJoin linejoin 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l=f({},o);l.frag=h([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor, fragBorderColor;\\n\\nuniform float opacity;\\nvarying float fragBorderRadius, fragWidth;\\n\\nfloat smoothStep(float edge0, float edge1, float x) {\\n\\tfloat t;\\n\\tt = clamp((x - edge0) / (edge1 - edge0), 0.0, 1.0);\\n\\treturn t * t * (3.0 - 2.0 * t);\\n}\\n\\nvoid main() {\\n\\tfloat radius, alpha = 1.0, delta = fragWidth;\\n\\n\\tradius = length(2.0 * gl_PointCoord.xy - 1.0);\\n\\n\\tif (radius > 1.0 + delta) {\\n\\t\\tdiscard;\\n\\t}\\n\\n\\talpha -= smoothstep(1.0 - delta, 1.0 + delta, radius);\\n\\n\\tfloat borderRadius = fragBorderRadius;\\n\\tfloat ratio = smoothstep(borderRadius - delta, borderRadius + delta, radius);\\n\\tvec4 color = mix(fragColor, fragBorderColor, ratio);\\n\\tcolor.a *= alpha * opacity;\\n\\tgl_FragColor = color;\\n}\\n\"]),l.vert=h([\"precision highp float;\\n#define GLSLIFY 1\\n\\nattribute float x, y, xFract, yFract;\\nattribute float size, 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borderSize * maxSize / 255.;\\n\\n  gl_PointSize = (size + borderSize) * pointSizeScale;\\n\\n  vec2 pos = (position + translate) * scale\\n      + (positionFract + translateFract) * scale\\n      + (position + translate) * scaleFract\\n      + (positionFract + translateFract) * scaleFract;\\n\\n  gl_Position = vec4(pos * 2. - 1., 0., 1.);\\n\\n  fragBorderRadius = 1. - 2. * borderSize / (size + borderSize);\\n  fragColor = color;\\n  fragBorderColor = borderColor.a == 0. || borderSize == 0. ? vec4(color.rgb, 0.) : borderColor;\\n  fragWidth = 1. / gl_PointSize;\\n}\\n\"]),m&&(l.frag=l.frag.replace(\"smoothstep\",\"smoothStep\"),s.frag=s.frag.replace(\"smoothstep\",\"smoothStep\")),this.drawCircle=t(l)}b.defaults={color:\"black\",borderColor:\"transparent\",borderSize:0,size:12,opacity:1,marker:void 0,viewport:null,range:null,pixelSize:null,count:0,offset:0,bounds:null,positions:[],snap:1e4},b.prototype.render=function(){return 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r?[f({},e,{markerTexture:this.markerTextures[t],activation:s[t],count:r.length,elements:r,offset:0})]:[f({},e,{markerTexture:this.markerTextures[t],activation:s[t],offset:0})];var u=[],h=a.range(i,{lod:!0,px:[(i[2]-i[0])/o.width,(i[3]-i[1])/o.height]});if(r){for(var p=s[t].data,d=new Uint8Array(c),g=0;g<r.length;g++){var m=r[g];d[m]=p?p[m]:1}l.subdata(d)}for(var v=h.length;v--;){var y=n(h[v],2),x=y[0],b=y[1];u.push(f({},e,{markerTexture:this.markerTextures[t],activation:r?l:s[t],offset:x,count:b-x}))}return u},b.prototype.update=function(){for(var t=this,e=arguments.length,r=new Array(e),n=0;n<e;n++)r[n]=arguments[n];if(r.length){1===r.length&&Array.isArray(r[0])&&(r=r[0]);var i=this.groups,a=this.gl,o=this.regl,s=this.maxSize,c=this.maxColors,h=this.palette;this.groups=i=r.map((function(e,r){var n=i[r];if(void 0===e)return n;null===e?e={positions:null}:\"function\"==typeof e?e={ondraw:e}:\"number\"==typeof e[0]&&(e={positions:e}),null===(e=p(e,{positions:\"positions data 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t.x.length?e.xAttr={buffer:o.buffer(t.x),offset:0,stride:4,count:t.x.length}:e.xAttr={buffer:t.x.buffer,offset:4*t.x.offset||0,stride:4*(t.x.stride||1),count:t.x.count},t.y.length?e.yAttr={buffer:o.buffer(t.y),offset:0,stride:4,count:t.y.length}:e.yAttr={buffer:t.y.buffer,offset:4*t.y.offset||0,stride:4*(t.y.stride||1),count:t.y.count},e.count=Math.max(e.xAttr.count,e.yAttr.count),t;t=g(t,\"float64\");var c=e.count=Math.floor(t.length/2),f=e.bounds=c?l(t,2):null;if(r.range||e.range||(delete e.range,r.range=f),r.marker||e.marker||(delete e.marker,r.marker=null),n&&(!0===n||c>n)?e.tree=u(t,{bounds:f}):n&&n.length&&(e.tree=n),e.tree){var h={primitive:\"points\",usage:\"static\",data:e.tree,type:\"uint32\"};e.elements?e.elements(h):e.elements=o.elements(h)}var p=v.float32(t);return i({data:p,usage:\"dynamic\"}),a({data:v.fract32(t,p),usage:\"dynamic\"}),s({data:new Uint8Array(c),type:\"uint8\",usage:\"stream\"}),t}},{marker:function(e,r,n){var 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E,L=n,C=L.count,P=L.color,I=L.borderColor,O=L.colorBuffer;if(t.tooManyColors){if(P.length||I.length){E=new Uint8Array(8*C);for(var z=0;z<C;z++){var D=P[z];E[8*z]=h[4*D],E[8*z+1]=h[4*D+1],E[8*z+2]=h[4*D+2],E[8*z+3]=h[4*D+3];var R=I[z];E[8*z+4]=h[4*R],E[8*z+5]=h[4*R+1],E[8*z+6]=h[4*R+2],E[8*z+7]=h[4*R+3]}}}else if(P.length||I.length){E=new Uint8Array(4*C+2);for(var F=0;F<C;F++)null!=P[F]&&(E[4*F]=P[F]%c,E[4*F+1]=Math.floor(P[F]/c)),null!=I[F]&&(E[4*F+2]=I[F]%c,E[4*F+3]=Math.floor(I[F]/c))}O({data:E||new Uint8Array(0),type:\"uint8\",usage:\"dynamic\"})}return n}))}},b.prototype.addMarker=function(t){var e,r=this.markerTextures,n=this.regl,i=this.markerCache,a=null==t?0:i.indexOf(t);if(a>=0)return a;if(t instanceof Uint8Array||t instanceof Uint8ClampedArray)e=t;else{e=new Uint8Array(t.length);for(var o=0,s=t.length;o<s;o++)e[o]=255*t[o]}var l=Math.floor(Math.sqrt(e.length));return 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i=.25*(t=t.slice()).length%e;i<n*e;i++)t.push(0,0,0,0);r.height<n&&r.resize(e,n),r.subimage({width:Math.min(.25*t.length,e),height:n,data:t},0,0)}},b.prototype.destroy=function(){return this.groups.forEach((function(t){t.sizeBuffer.destroy(),t.positionBuffer.destroy(),t.positionFractBuffer.destroy(),t.colorBuffer.destroy(),t.activation.forEach((function(t){return t&&t.destroy&&t.destroy()})),t.selectionBuffer.destroy(),t.elements&&t.elements.destroy()})),this.groups.length=0,this.paletteTexture.destroy(),this.markerTextures.forEach((function(t){return t&&t.destroy&&t.destroy()})),this};var _=t(\"object-assign\");e.exports=function(t,e){var r=new x(t,e),n=r.render.bind(r);return 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s.length>2?(s[0],s[2],n=s[1],i=s[3]):s.length?(n=s[0],i=s[1]):(s.x,n=s.y,s.x+s.width,i=s.y+s.height),l.length>2?(a=l[0],o=l[2],l[1],l[3]):l.length?(a=l[0],o=l[1]):(a=l.x,l.y,o=l.x+l.width,l.y+l.height),[a,n,o,i]}function p(t){if(\"number\"==typeof t)return[t,t,t,t];if(2===t.length)return[t[0],t[1],t[0],t[1]];var e=l(t);return[e.x,e.y,e.x+e.width,e.y+e.height]}e.exports=u,u.prototype.render=function(){for(var t,e=this,r=[],n=arguments.length;n--;)r[n]=arguments[n];return r.length&&(t=this).update.apply(t,r),this.regl.attributes.preserveDrawingBuffer?this.draw():(this.dirty?null==this.planned&&(this.planned=o((function(){e.draw(),e.dirty=!0,e.planned=null}))):(this.draw(),this.dirty=!0,o((function(){e.dirty=!1}))),this)},u.prototype.update=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];if(e.length){for(var n=0;n<e.length;n++)this.updateItem(n,e[n]);this.traces=this.traces.filter(Boolean);for(var i=[],a=0,o=0;o<this.traces.length;o++){for(var s=this.traces[o],l=this.traces[o].passes,c=0;c<l.length;c++)i.push(this.passes[l[c]]);s.passOffset=a,a+=s.passes.length}return(t=this.scatter).update.apply(t,i),this}},u.prototype.updateItem=function(t,e){var r=this.regl;if(null===e)return this.traces[t]=null,this;if(!e)return this;var n,o=i(e,{data:\"data items columns rows values dimensions samples x\",snap:\"snap cluster\",size:\"sizes size radius\",color:\"colors color fill fill-color fillColor\",opacity:\"opacity alpha transparency opaque\",borderSize:\"borderSizes borderSize border-size bordersize borderWidth borderWidths border-width borderwidth stroke-width strokeWidth strokewidth outline\",borderColor:\"borderColors borderColor bordercolor stroke stroke-color strokeColor\",marker:\"markers marker shape\",range:\"range ranges databox dataBox\",viewport:\"viewport viewBox viewbox\",domain:\"domain domains area areas\",padding:\"pad padding paddings pads margin margins\",transpose:\"transpose transposed\",diagonal:\"diagonal diag 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u=0;u<s.columns;u++)s.bounds[u]=a(o.data[u],1)}o.range&&(s.range=o.range,n=s.range&&\"number\"!=typeof s.range[0]),o.domain&&(s.domain=o.domain);var d=!1;null!=o.padding&&(Array.isArray(o.padding)&&o.padding.length===s.columns&&\"number\"==typeof o.padding[o.padding.length-1]?(s.padding=o.padding.map(p),d=!0):s.padding=p(o.padding));var g=s.columns,m=s.count,v=s.viewport.width,y=s.viewport.height,x=s.viewport.x,b=s.viewport.y,_=v/g,w=y/g;s.passes=[];for(var T=0;T<g;T++)for(var k=0;k<g;k++)if((s.diagonal||k!==T)&&(s.upper||!(T>k))&&(s.lower||!(T<k))){var A=f(s.id,T,k),M=this.passes[A]||(this.passes[A]={});if(o.data&&(o.transpose?M.positions={x:{buffer:s.buffer,offset:k,count:m,stride:g},y:{buffer:s.buffer,offset:T,count:m,stride:g}}:M.positions={x:{buffer:s.buffer,offset:k*m,count:m},y:{buffer:s.buffer,offset:T*m,count:m}},M.bounds=h(s.bounds,T,k)),o.domain||o.viewport||o.data){var S=d?h(s.padding,T,k):s.padding;if(s.domain){var E=h(s.domain,T,k),L=E[0],C=E[1],P=E[2],I=E[3];M.viewport=[x+L*v+S[0],b+C*y+S[1],x+P*v-S[2],b+I*y-S[3]]}else M.viewport=[x+k*_+_*S[0],b+T*w+w*S[1],x+(k+1)*_-_*S[2],b+(T+1)*w-w*S[3]]}o.color&&(M.color=s.color),o.size&&(M.size=s.size),o.marker&&(M.marker=s.marker),o.borderSize&&(M.borderSize=s.borderSize),o.borderColor&&(M.borderColor=s.borderColor),o.opacity&&(M.opacity=s.opacity),o.range&&(M.range=n?h(s.range,T,k):s.range||M.bounds),s.passes.push(A)}return this},u.prototype.draw=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];if(e.length){for(var n=[],i=0;i<e.length;i++)if(\"number\"==typeof e[i]){var a=this.traces[e[i]],o=a.passes,l=a.passOffset;n.push.apply(n,s(l,l+o.length))}else if(e[i].length){var c=e[i],u=this.traces[i],f=u.passes,h=u.passOffset;f=f.map((function(t,e){n[h+e]=c}))}(t=this.scatter).draw.apply(t,n)}else this.scatter.draw();return this},u.prototype.destroy=function(){return 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+       "/*!\n",
+       " * repeat-string <https://github.com/jonschlinkert/repeat-string>\n",
+       " *\n",
+       " * Copyright (c) 2014-2015, Jon Schlinkert.\n",
+       " * Licensed under the MIT License.\n",
+       " */\n",
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i=this._validate(t,e,r,n.local.invalidDate);return{yearType:(this.leapYear(i)?\"embolismic\":\"common\")+\" \"+[\"deficient\",\"regular\",\"complete\"][this.daysInYear(i)%10-3]}},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=i.year(),e=i.month(),r=i.day();var a=t<=0?t+1:t,o=this.jdEpoch+this._delay1(a)+this._delay2(a)+r+1;if(e<7){for(var s=7;s<=this.monthsInYear(t);s++)o+=this.daysInMonth(t,s);for(s=1;s<e;s++)o+=this.daysInMonth(t,s)}else for(s=7;s<e;s++)o+=this.daysInMonth(t,s);return o},_delay1:function(t){var e=Math.floor((235*t-234)/19),r=12084+13753*e,n=29*e+Math.floor(r/25920);return o(3*(n+1),7)<3&&n++,n},_delay2:function(t){var e=this._delay1(t-1),r=this._delay1(t);return this._delay1(t+1)-r==356?2:r-e==382?1:0},fromJD:function(t){t=Math.floor(t)+.5;for(var e=Math.floor(98496*(t-this.jdEpoch)/35975351)-1;t>=this.toJD(-1===e?1:e+1,7,1);)e++;for(var r=t<this.toJD(e,1,1)?7:1;t>this.toJD(e,r,this.daysInMonth(e,r));)r++;var n=t-this.toJD(e,r,1)+1;return 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e=Math.floor((30*(t-this.jdEpoch)+10646)/10631);e=e<=0?e-1:e;var r=Math.min(12,Math.ceil((t-29-this.toJD(e,1,1))/29.5)+1),n=t-this.toJD(e,r,1)+1;return this.newDate(e,r,n)}}),n.calendars.islamic=a},{\"../main\":644,\"object-assign\":487}],636:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new 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this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),!1},formatYear:function(t){t=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year();var e=Math.floor(t/400);return t%=400,t+=t<0?400:0,e+\".\"+Math.floor(t/20)+\".\"+t%20},forYear:function(t){if((t=t.split(\".\")).length<3)throw\"Invalid Mayan year\";for(var e=0,r=0;r<t.length;r++){var n=parseInt(t[r],10);if(Math.abs(n)>19||r>0&&n<0)throw\"Invalid Mayan year\";e=20*e+n}return e},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),18},weekOfYear:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate),0},daysInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),360},daysInMonth:function(t,e){return this._validate(t,e,this.minDay,n.local.invalidMonth),20},daysInWeek:function(){return 5},dayOfWeek:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate).day()},weekDay:function(t,e,r){return 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e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return 682*((e.year()-(e.year()>0?474:473))%2820+474+38)%2816<682},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-(n.dayOfWeek()+1)%7,\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(12===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=i.year(),e=i.month(),r=i.day();var a=t-(t>=0?474:473),s=474+o(a,2820);return r+(e<=7?31*(e-1):30*(e-1)+6)+Math.floor((682*s-110)/2816)+365*(s-1)+1029983*Math.floor(a/2820)+this.jdEpoch-1},fromJD:function(t){var e=(t=Math.floor(t)+.5)-this.toJD(475,1,1),r=Math.floor(e/1029983),n=o(e,1029983),i=2820;if(1029982!==n){var a=Math.floor(n/366),s=o(n,366);i=Math.floor((2134*a+2816*s+2815)/1028522)+a+1}var l=i+2820*r+474;l=l<=0?l-1:l;var 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i=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);t=this._t2gYear(i.year());return a.weekOfYear(t,i.month(),i.day())},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(2===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate);t=this._t2gYear(i.year());return a.toJD(t,i.month(),i.day())},fromJD:function(t){var e=a.fromJD(t),r=this._g2tYear(e.year());return this.newDate(r,e.month(),e.day())},_t2gYear:function(t){return t+this.yearsOffset+(t>=-this.yearsOffset&&t<=-1?1:0)},_g2tYear:function(t){return t-this.yearsOffset-(t>=1&&t<=this.yearsOffset?1:0)}}),n.calendars.taiwan=o},{\"../main\":644,\"object-assign\":487}],642:[function(t,e,r){var n=t(\"../main\"),i=t(\"object-assign\"),a=n.instance();function 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n=t(\"../main\"),i=t(\"object-assign\");function a(t){this.local=this.regionalOptions[t||\"\"]||this.regionalOptions[\"\"]}a.prototype=new n.baseCalendar,i(a.prototype,{name:\"UmmAlQura\",hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{\"\":{name:\"Umm al-Qura\",epochs:[\"BH\",\"AH\"],monthNames:[\"Al-Muharram\",\"Safar\",\"Rabi' al-awwal\",\"Rabi' Al-Thani\",\"Jumada Al-Awwal\",\"Jumada Al-Thani\",\"Rajab\",\"Sha'aban\",\"Ramadan\",\"Shawwal\",\"Dhu al-Qi'dah\",\"Dhu al-Hijjah\"],monthNamesShort:[\"Muh\",\"Saf\",\"Rab1\",\"Rab2\",\"Jum1\",\"Jum2\",\"Raj\",\"Sha'\",\"Ram\",\"Shaw\",\"DhuQ\",\"DhuH\"],dayNames:[\"Yawm al-Ahad\",\"Yawm al-Ithnain\",\"Yawm al-Thal\\u0101th\\u0101\\u2019\",\"Yawm al-Arba\\u2018\\u0101\\u2019\",\"Yawm al-Kham\\u012bs\",\"Yawm al-Jum\\u2018a\",\"Yawm al-Sabt\"],dayNamesMin:[\"Ah\",\"Ith\",\"Th\",\"Ar\",\"Kh\",\"Ju\",\"Sa\"],digits:null,dateFormat:\"yyyy/mm/dd\",firstDay:6,isRTL:!0}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return 355===this.daysInYear(e.year())},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),\"d\"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){for(var e=0,r=1;r<=12;r++)e+=this.daysInMonth(t,r);return e},daysInMonth:function(t,e){for(var r=this._validate(t,e,this.minDay,n.local.invalidMonth).toJD()-24e5+.5,i=0,a=0;a<o.length;a++){if(o[a]>r)return o[i]-o[i-1];i++}return 30},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var i=this._validate(t,e,r,n.local.invalidDate),a=12*(i.year()-1)+i.month()-15292;return i.day()+o[a-1]-1+24e5-.5},fromJD:function(t){for(var e=t-24e5+.5,r=0,n=0;n<o.length&&!(o[n]>e);n++)r++;var i=r+15292,a=Math.floor((i-1)/12),s=a+1,l=i-12*a,c=e-o[r-1]+1;return this.newDate(s,l,c)},isValid:function(t,e,r){var i=n.baseCalendar.prototype.isValid.apply(this,arguments);return i&&(i=(t=null!=t.year?t.year:t)>=1276&&t<=1500),i},_validate:function(t,e,r,i){var a=n.baseCalendar.prototype._validate.apply(this,arguments);if(a.year<1276||a.year>1500)throw i.replace(/\\{0\\}/,this.local.name);return a}}),n.calendars.ummalqura=a;var 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n=t(\"object-assign\");function i(){this.regionalOptions=[],this.regionalOptions[\"\"]={invalidCalendar:\"Calendar {0} not found\",invalidDate:\"Invalid {0} date\",invalidMonth:\"Invalid {0} month\",invalidYear:\"Invalid {0} year\",differentCalendars:\"Cannot mix {0} and {1} dates\"},this.local=this.regionalOptions[\"\"],this.calendars={},this._localCals={}}function a(t,e,r,n){if(this._calendar=t,this._year=e,this._month=r,this._day=n,0===this._calendar._validateLevel&&!this._calendar.isValid(this._year,this._month,this._day))throw(c.local.invalidDate||c.regionalOptions[\"\"].invalidDate).replace(/\\{0\\}/,this._calendar.local.name)}function o(t,e){return\"000000\".substring(0,e-(t=\"\"+t).length)+t}function s(){this.shortYearCutoff=\"+10\"}function l(t){this.local=this.regionalOptions[t]||this.regionalOptions[\"\"]}n(i.prototype,{instance:function(t,e){t=(t||\"gregorian\").toLowerCase(),e=e||\"\";var r=this._localCals[t+\"-\"+e];if(!r&&this.calendars[t]&&(r=new this.calendars[t](e),this._localCals[t+\"-\"+e]=r),!r)throw(this.local.invalidCalendar||this.regionalOptions[\"\"].invalidCalendar).replace(/\\{0\\}/,t);return r},newDate:function(t,e,r,n,i){return(n=(null!=t&&t.year?t.calendar():\"string\"==typeof n?this.instance(n,i):n)||this.instance()).newDate(t,e,r)},substituteDigits:function(t){return function(e){return(e+\"\").replace(/[0-9]/g,(function(e){return t[e]}))}},substituteChineseDigits:function(t,e){return function(r){for(var n=\"\",i=0;r>0;){var a=r%10;n=(0===a?\"\":t[a]+e[i])+n,i++,r=Math.floor(r/10)}return 0===n.indexOf(t[1]+e[1])&&(n=n.substr(1)),n||t[0]}}}),n(a.prototype,{newDate:function(t,e,r){return this._calendar.newDate(null==t?this:t,e,r)},year:function(t){return 0===arguments.length?this._year:this.set(t,\"y\")},month:function(t){return 0===arguments.length?this._month:this.set(t,\"m\")},day:function(t){return 0===arguments.length?this._day:this.set(t,\"d\")},date:function(t,e,r){if(!this._calendar.isValid(t,e,r))throw(c.local.invalidDate||c.regionalOptions[\"\"].invalidDate).replace(/\\{0\\}/,this._calendar.local.name);return this._year=t,this._month=e,this._day=r,this},leapYear:function(){return this._calendar.leapYear(this)},epoch:function(){return this._calendar.epoch(this)},formatYear:function(){return this._calendar.formatYear(this)},monthOfYear:function(){return this._calendar.monthOfYear(this)},weekOfYear:function(){return this._calendar.weekOfYear(this)},daysInYear:function(){return this._calendar.daysInYear(this)},dayOfYear:function(){return this._calendar.dayOfYear(this)},daysInMonth:function(){return this._calendar.daysInMonth(this)},dayOfWeek:function(){return this._calendar.dayOfWeek(this)},weekDay:function(){return this._calendar.weekDay(this)},extraInfo:function(){return this._calendar.extraInfo(this)},add:function(t,e){return this._calendar.add(this,t,e)},set:function(t,e){return this._calendar.set(this,t,e)},compareTo:function(t){if(this._calendar.name!==t._calendar.name)throw(c.local.differentCalendars||c.regionalOptions[\"\"].differentCalendars).replace(/\\{0\\}/,this._calendar.local.name).replace(/\\{1\\}/,t._calendar.local.name);var e=this._year!==t._year?this._year-t._year:this._month!==t._month?this.monthOfYear()-t.monthOfYear():this._day-t._day;return 0===e?0:e<0?-1:1},calendar:function(){return this._calendar},toJD:function(){return this._calendar.toJD(this)},fromJD:function(t){return this._calendar.fromJD(t)},toJSDate:function(){return this._calendar.toJSDate(this)},fromJSDate:function(t){return this._calendar.fromJSDate(t)},toString:function(){return(this.year()<0?\"-\":\"\")+o(Math.abs(this.year()),4)+\"-\"+o(this.month(),2)+\"-\"+o(this.day(),2)}}),n(s.prototype,{_validateLevel:0,newDate:function(t,e,r){return null==t?this.today():(t.year&&(this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate),r=t.day(),e=t.month(),t=t.year()),new a(this,t,e,r))},today:function(){return this.fromJSDate(new Date)},epoch:function(t){return this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear).year()<0?this.local.epochs[0]:this.local.epochs[1]},formatYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear);return(e.year()<0?\"-\":\"\")+o(Math.abs(e.year()),4)},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear),12},monthOfYear:function(t,e){var r=this._validate(t,e,this.minDay,c.local.invalidMonth||c.regionalOptions[\"\"].invalidMonth);return(r.month()+this.monthsInYear(r)-this.firstMonth)%this.monthsInYear(r)+this.minMonth},fromMonthOfYear:function(t,e){var r=(e+this.firstMonth-2*this.minMonth)%this.monthsInYear(t)+this.minMonth;return this._validate(t,r,this.minDay,c.local.invalidMonth||c.regionalOptions[\"\"].invalidMonth),r},daysInYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[\"\"].invalidYear);return this.leapYear(e)?366:365},dayOfYear:function(t,e,r){var n=this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate);return n.toJD()-this.newDate(n.year(),this.fromMonthOfYear(n.year(),this.minMonth),this.minDay).toJD()+1},daysInWeek:function(){return 7},dayOfWeek:function(t,e,r){var n=this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate);return(Math.floor(this.toJD(n))+2)%this.daysInWeek()},extraInfo:function(t,e,r){return this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate),{}},add:function(t,e,r){return this._validate(t,this.minMonth,this.minDay,c.local.invalidDate||c.regionalOptions[\"\"].invalidDate),this._correctAdd(t,this._add(t,e,r),e,r)},_add:function(t,e,r){if(this._validateLevel++,\"d\"===r||\"w\"===r){var n=t.toJD()+e*(\"w\"===r?this.daysInWeek():1),i=t.calendar().fromJD(n);return this._validateLevel--,[i.year(),i.month(),i.day()]}try{var a=t.year()+(\"y\"===r?e:0),o=t.monthOfYear()+(\"m\"===r?e:0);i=t.day();\"y\"===r?(t.month()!==this.fromMonthOfYear(a,o)&&(o=this.newDate(a,t.month(),this.minDay).monthOfYear()),o=Math.min(o,this.monthsInYear(a)),i=Math.min(i,this.daysInMonth(a,this.fromMonthOfYear(a,o)))):\"m\"===r&&(!function(t){for(;o<t.minMonth;)a--,o+=t.monthsInYear(a);for(var e=t.monthsInYear(a);o>e-1+t.minMonth;)a++,o-=e,e=t.monthsInYear(a)}(this),i=Math.min(i,this.daysInMonth(a,this.fromMonthOfYear(a,o))));var s=[a,this.fromMonthOfYear(a,o),i];return this._validateLevel--,s}catch(t){throw 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r,s,l=o(t,e),c=l.on,u=l.off.concat(l.explicitOff),f={},h=t._fullLayout.annotations;if(!c.length&&!u.length)return;for(r=0;r<c.length;r++)(s=a(t.layout,\"annotations\",h[c[r]])).modifyItem(\"visible\",!0),n.extendFlat(f,s.getUpdateObj());for(r=0;r<u.length;r++)(s=a(t.layout,\"annotations\",h[u[r]])).modifyItem(\"visible\",!1),n.extendFlat(f,s.getUpdateObj());return i.call(\"update\",t,{},f)}}},{\"../../lib\":803,\"../../plot_api/plot_template\":843,\"../../registry\":931}],652:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../color\");e.exports=function(t,e,r,a){a(\"opacity\");var o=a(\"bgcolor\"),s=a(\"bordercolor\"),l=i.opacity(s);a(\"borderpad\");var c=a(\"borderwidth\"),u=a(\"showarrow\");if(a(\"text\",u?\" \":r._dfltTitle.annotation),a(\"textangle\"),n.coerceFont(a,\"font\",r.font),a(\"width\"),a(\"align\"),a(\"height\")&&a(\"valign\"),u){var f,h,p=a(\"arrowside\");-1!==p.indexOf(\"end\")&&(f=a(\"arrowhead\"),h=a(\"arrowsize\")),-1!==p.indexOf(\"start\")&&(a(\"startarrowhead\",f),a(\"startarrowsize\",h)),a(\"arrowcolor\",l?e.bordercolor:i.defaultLine),a(\"arrowwidth\",2*(l&&c||1)),a(\"standoff\"),a(\"startstandoff\")}var d=a(\"hovertext\"),g=r.hoverlabel||{};if(d){var m=a(\"hoverlabel.bgcolor\",g.bgcolor||(i.opacity(o)?i.rgb(o):i.defaultLine)),v=a(\"hoverlabel.bordercolor\",g.bordercolor||i.contrast(m));n.coerceFont(a,\"hoverlabel.font\",{family:g.font.family,size:g.font.size,color:g.font.color||v})}a(\"captureevents\",!!d)}},{\"../../lib\":803,\"../color\":666}],653:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),i=t(\"../../lib/to_log_range\");e.exports=function(t,e,r,a){e=e||{};var o=\"log\"===r&&\"linear\"===e.type,s=\"linear\"===r&&\"log\"===e.type;if(o||s)for(var l,c,u=t._fullLayout.annotations,f=e._id.charAt(0),h=0;h<u.length;h++)l=u[h],c=\"annotations[\"+h+\"].\",l[f+\"ref\"]===e._id&&p(f),l[\"a\"+f+\"ref\"]===e._id&&p(\"a\"+f);function p(t){var r=l[t],s=null;s=o?i(r,e.range):Math.pow(10,r),n(s)||(s=null),a(c+t,s)}}},{\"../../lib/to_log_range\":831,\"fast-isnumeric\":249}],654:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../plots/cartesian/axes\"),a=t(\"../../plots/array_container_defaults\"),o=t(\"./common_defaults\"),s=t(\"./attributes\");function l(t,e,r){function a(r,i){return n.coerce(t,e,s,r,i)}var l=a(\"visible\"),c=a(\"clicktoshow\");if(l||c){o(t,e,r,a);for(var u=e.showarrow,f=[\"x\",\"y\"],h=[-10,-30],p={_fullLayout:r},d=0;d<2;d++){var g=f[d],m=i.coerceRef(t,e,p,g,\"\",\"paper\");if(\"paper\"!==m)i.getFromId(p,m)._annIndices.push(e._index);if(i.coercePosition(e,p,a,m,g,.5),u){var v=\"a\"+g,y=i.coerceRef(t,e,p,v,\"pixel\",[\"pixel\",\"paper\"]);\"pixel\"!==y&&y!==m&&(y=e[v]=\"pixel\");var x=\"pixel\"===y?h[d]:.4;i.coercePosition(e,p,a,y,v,x)}a(g+\"anchor\"),a(g+\"shift\")}if(n.noneOrAll(t,e,[\"x\",\"y\"]),u&&n.noneOrAll(t,e,[\"ax\",\"ay\"]),c){var b=a(\"xclick\"),_=a(\"yclick\");e._xclick=void 0===b?e.x:i.cleanPosition(b,p,e.xref),e._yclick=void 0===_?e.y:i.cleanPosition(_,p,e.yref)}}}e.exports=function(t,e){a(t,e,{name:\"annotations\",handleItemDefaults:l})}},{\"../../lib\":803,\"../../plots/array_container_defaults\":849,\"../../plots/cartesian/axes\":854,\"./attributes\":649,\"./common_defaults\":652}],655:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"../../registry\"),a=t(\"../../plots/plots\"),o=t(\"../../lib\"),s=o.strTranslate,l=t(\"../../plots/cartesian/axes\"),c=t(\"../color\"),u=t(\"../drawing\"),f=t(\"../fx\"),h=t(\"../../lib/svg_text_utils\"),p=t(\"../../lib/setcursor\"),d=t(\"../dragelement\"),g=t(\"../../plot_api/plot_template\").arrayEditor,m=t(\"./draw_arrow_head\");function v(t,e){var r=t._fullLayout.annotations[e]||{},n=l.getFromId(t,r.xref),i=l.getFromId(t,r.yref);n&&n.setScale(),i&&i.setScale(),x(t,r,e,!1,n,i)}function y(t,e,r,n,i){var a=i[r],o=i[r+\"ref\"],s=-1!==r.indexOf(\"y\"),c=\"domain\"===l.getRefType(o),u=s?n.h:n.w;return t?c?a+(s?-e:e)/t._length:t.p2r(t.r2p(a)+e):a+(s?-e:e)/u}function x(t,e,r,a,v,x){var b,_,w=t._fullLayout,T=t._fullLayout._size,k=t._context.edits;a?(b=\"annotation-\"+a,_=a+\".annotations\"):(b=\"annotation\",_=\"annotations\");var A=g(t.layout,_,e),M=A.modifyBase,S=A.modifyItem,E=A.getUpdateObj;w._infolayer.selectAll(\".\"+b+'[data-index=\"'+r+'\"]').remove();var L=\"clip\"+w._uid+\"_ann\"+r;if(e._input&&!1!==e.visible){var C={x:{},y:{}},P=+e.textangle||0,I=w._infolayer.append(\"g\").classed(b,!0).attr(\"data-index\",String(r)).style(\"opacity\",e.opacity),O=I.append(\"g\").classed(\"annotation-text-g\",!0),z=k[e.showarrow?\"annotationTail\":\"annotationPosition\"],D=e.captureevents||k.annotationText||z,R=O.append(\"g\").style(\"pointer-events\",D?\"all\":null).call(p,\"pointer\").on(\"click\",(function(){t._dragging=!1,t.emit(\"plotly_clickannotation\",Y(n.event))}));e.hovertext&&R.on(\"mouseover\",(function(){var r=e.hoverlabel,n=r.font,i=this.getBoundingClientRect(),a=t.getBoundingClientRect();f.loneHover({x0:i.left-a.left,x1:i.right-a.left,y:(i.top+i.bottom)/2-a.top,text:e.hovertext,color:r.bgcolor,borderColor:r.bordercolor,fontFamily:n.family,fontSize:n.size,fontColor:n.color},{container:w._hoverlayer.node(),outerContainer:w._paper.node(),gd:t})})).on(\"mouseout\",(function(){f.loneUnhover(w._hoverlayer.node())}));var F=e.borderwidth,B=e.borderpad,N=F+B,j=R.append(\"rect\").attr(\"class\",\"bg\").style(\"stroke-width\",F+\"px\").call(c.stroke,e.bordercolor).call(c.fill,e.bgcolor),U=e.width||e.height,V=w._topclips.selectAll(\"#\"+L).data(U?[0]:[]);V.enter().append(\"clipPath\").classed(\"annclip\",!0).attr(\"id\",L).append(\"rect\"),V.exit().remove();var q=e.font,H=w._meta?o.templateString(e.text,w._meta):e.text,G=R.append(\"text\").classed(\"annotation-text\",!0).text(H);k.annotationText?G.call(h.makeEditable,{delegate:R,gd:t}).call(W).on(\"edit\",(function(r){e.text=r,this.call(W),S(\"text\",r),v&&v.autorange&&M(v._name+\".autorange\",!0),x&&x.autorange&&M(x._name+\".autorange\",!0),i.call(\"_guiRelayout\",t,E())})):G.call(W)}else n.selectAll(\"#\"+L).remove();function Y(t){var n={index:r,annotation:e._input,fullAnnotation:e,event:t};return a&&(n.subplotId=a),n}function W(r){return r.call(u.font,q).attr({\"text-anchor\":{left:\"start\",right:\"end\"}[e.align]||\"middle\"}),h.convertToTspans(r,t,X),r}function X(){var r=G.selectAll(\"a\");1===r.size()&&r.text()===G.text()&&R.insert(\"a\",\":first-child\").attr({\"xlink:xlink:href\":r.attr(\"xlink:href\"),\"xlink:xlink:show\":r.attr(\"xlink:show\")}).style({cursor:\"pointer\"}).node().appendChild(j.node());var n=R.select(\".annotation-text-math-group\"),f=!n.empty(),g=u.bBox((f?n:G).node()),b=g.width,_=g.height,A=e.width||b,D=e.height||_,B=Math.round(A+2*N),q=Math.round(D+2*N);function H(t,e){return\"auto\"===e&&(e=t<1/3?\"left\":t>2/3?\"right\":\"center\"),{center:0,middle:0,left:.5,bottom:-.5,right:-.5,top:.5}[e]}for(var W=!1,X=[\"x\",\"y\"],Z=0;Z<X.length;Z++){var J,K,Q,$,tt,et=X[Z],rt=e[et+\"ref\"]||et,nt=e[\"a\"+et+\"ref\"],it={x:v,y:x}[et],at=(P+(\"x\"===et?0:-90))*Math.PI/180,ot=B*Math.cos(at),st=q*Math.sin(at),lt=Math.abs(ot)+Math.abs(st),ct=e[et+\"anchor\"],ut=e[et+\"shift\"]*(\"x\"===et?1:-1),ft=C[et],ht=l.getRefType(rt);if(it&&\"domain\"!==ht){var pt=it.r2fraction(e[et]);(pt<0||pt>1)&&(nt===rt?((pt=it.r2fraction(e[\"a\"+et]))<0||pt>1)&&(W=!0):W=!0),J=it._offset+it.r2p(e[et]),$=.5}else{var dt=\"domain\"===ht;\"x\"===et?(Q=e[et],J=dt?it._offset+it._length*Q:J=T.l+T.w*Q):(Q=1-e[et],J=dt?it._offset+it._length*Q:J=T.t+T.h*Q),$=e.showarrow?.5:Q}if(e.showarrow){ft.head=J;var gt=e[\"a\"+et];if(tt=ot*H(.5,e.xanchor)-st*H(.5,e.yanchor),nt===rt){var mt=l.getRefType(nt);\"domain\"===mt?(\"y\"===et&&(gt=1-gt),ft.tail=it._offset+it._length*gt):\"paper\"===mt?\"y\"===et?(gt=1-gt,ft.tail=T.t+T.h*gt):ft.tail=T.l+T.w*gt:ft.tail=it._offset+it.r2p(gt),K=tt}else ft.tail=J+gt,K=tt+gt;ft.text=ft.tail+tt;var vt=w[\"x\"===et?\"width\":\"height\"];if(\"paper\"===rt&&(ft.head=o.constrain(ft.head,1,vt-1)),\"pixel\"===nt){var yt=-Math.max(ft.tail-3,ft.text),xt=Math.min(ft.tail+3,ft.text)-vt;yt>0?(ft.tail+=yt,ft.text+=yt):xt>0&&(ft.tail-=xt,ft.text-=xt)}ft.tail+=ut,ft.head+=ut}else K=tt=lt*H($,ct),ft.text=J+tt;ft.text+=ut,tt+=ut,K+=ut,e[\"_\"+et+\"padplus\"]=lt/2+K,e[\"_\"+et+\"padminus\"]=lt/2-K,e[\"_\"+et+\"size\"]=lt,e[\"_\"+et+\"shift\"]=tt}if(W)R.remove();else{var bt=0,_t=0;if(\"left\"!==e.align&&(bt=(A-b)*(\"center\"===e.align?.5:1)),\"top\"!==e.valign&&(_t=(D-_)*(\"middle\"===e.valign?.5:1)),f)n.select(\"svg\").attr({x:N+bt-1,y:N+_t}).call(u.setClipUrl,U?L:null,t);else{var wt=N+_t-g.top,Tt=N+bt-g.left;G.call(h.positionText,Tt,wt).call(u.setClipUrl,U?L:null,t)}V.select(\"rect\").call(u.setRect,N,N,A,D),j.call(u.setRect,F/2,F/2,B-F,q-F),R.call(u.setTranslate,Math.round(C.x.text-B/2),Math.round(C.y.text-q/2)),O.attr({transform:\"rotate(\"+P+\",\"+C.x.text+\",\"+C.y.text+\")\"});var kt,At=function(r,n){I.selectAll(\".annotation-arrow-g\").remove();var l=C.x.head,f=C.y.head,h=C.x.tail+r,p=C.y.tail+n,g=C.x.text+r,b=C.y.text+n,_=o.rotationXYMatrix(P,g,b),w=o.apply2DTransform(_),A=o.apply2DTransform2(_),L=+j.attr(\"width\"),z=+j.attr(\"height\"),D=g-.5*L,F=D+L,B=b-.5*z,N=B+z,U=[[D,B,D,N],[D,N,F,N],[F,N,F,B],[F,B,D,B]].map(A);if(!U.reduce((function(t,e){return t^!!o.segmentsIntersect(l,f,l+1e6,f+1e6,e[0],e[1],e[2],e[3])}),!1)){U.forEach((function(t){var e=o.segmentsIntersect(h,p,l,f,t[0],t[1],t[2],t[3]);e&&(h=e.x,p=e.y)}));var V=e.arrowwidth,q=e.arrowcolor,H=e.arrowside,G=I.append(\"g\").style({opacity:c.opacity(q)}).classed(\"annotation-arrow-g\",!0),Y=G.append(\"path\").attr(\"d\",\"M\"+h+\",\"+p+\"L\"+l+\",\"+f).style(\"stroke-width\",V+\"px\").call(c.stroke,c.rgb(q));if(m(Y,H,e),k.annotationPosition&&Y.node().parentNode&&!a){var W=l,X=f;if(e.standoff){var Z=Math.sqrt(Math.pow(l-h,2)+Math.pow(f-p,2));W+=e.standoff*(h-l)/Z,X+=e.standoff*(p-f)/Z}var 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n.coerce(t,e,s,r,i)}function c(t){var n=t+\"axis\",a={_fullLayout:{}};return a._fullLayout[n]=r[n],i.coercePosition(e,a,l,t,t,.5)}l(\"visible\")&&(o(t,e,a.fullLayout,l),c(\"x\"),c(\"y\"),c(\"z\"),n.noneOrAll(t,e,[\"x\",\"y\",\"z\"]),e.xref=\"x\",e.yref=\"y\",e.zref=\"z\",l(\"xanchor\"),l(\"yanchor\"),l(\"xshift\"),l(\"yshift\"),e.showarrow&&(e.axref=\"pixel\",e.ayref=\"pixel\",l(\"ax\",-10),l(\"ay\",-30),n.noneOrAll(t,e,[\"ax\",\"ay\"])))}e.exports=function(t,e,r){a(t,e,{name:\"annotations\",handleItemDefaults:l,fullLayout:r.fullLayout})}},{\"../../lib\":803,\"../../plots/array_container_defaults\":849,\"../../plots/cartesian/axes\":854,\"../annotations/common_defaults\":652,\"./attributes\":658}],661:[function(t,e,r){\"use strict\";var n=t(\"../annotations/draw\").drawRaw,i=t(\"../../plots/gl3d/project\"),a=[\"x\",\"y\",\"z\"];e.exports=function(t){for(var e=t.fullSceneLayout,r=t.dataScale,o=e.annotations,s=0;s<o.length;s++){for(var l=o[s],c=!1,u=0;u<3;u++){var 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g={xcalendar:p(d(\"x\"))},m=i.extendFlat({},g,{ycalendar:p(d(\"y\"))}),v=i.extendFlat({},m,{zcalendar:p(d(\"z\"))}),y=p([\"Sets the calendar system to use for `range` and `tick0`\",\"if this is a date axis. 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B,V,q,H,G,Y,W,X,Z,J,K,Q,$,tt=[],et=[],rt={hLinePoint:null,vLinePoint:null},nt=!1;if(Array.isArray(e))for(S=\"array\",q=0;q<e.length;q++)(G=t.calcdata[e[q].curveNumber||0])&&(Y=G[0].trace,\"skip\"!==G[0].trace.hoverinfo&&(et.push(G),\"h\"===Y.orientation&&(nt=!0)));else{for(H=0;H<t.calcdata.length;H++)G=t.calcdata[H],\"skip\"!==(Y=G[0].trace).hoverinfo&&v.isTraceInSubplots(Y,s)&&(et.push(G),\"h\"===Y.orientation&&(nt=!0));var it,at;if(!e.target)it=\"xpx\"in e?e.xpx:b[0]._length/2,at=\"ypx\"in e?e.ypx:_[0]._length/2;else{if(!1===c.triggerHandler(t,\"plotly_beforehover\",e))return;var ot=e.composedPath&&e.composedPath()[0];ot||(ot=e.target);var st=ot.getBoundingClientRect();it=e.clientX-st.left,at=e.clientY-st.top,l._calcInverseTransform(t);var lt=o.apply3DTransform(l._invTransform)(it,at);if(it=lt[0],at=lt[1],it<0||it>b[0]._length||at<0||at>_[0]._length)return d.unhoverRaw(t,e)}if(e.pointerX=it+b[0]._offset,e.pointerY=at+_[0]._offset,B=\"xval\"in e?v.flat(s,e.xval):v.p2c(b,it),V=\"yval\"in e?v.flat(s,e.yval):v.p2c(_,at),!i(B[0])||!i(V[0]))return o.warn(\"Fx.hover failed\",e,t),d.unhoverRaw(t,e)}var ct=1/0;function ut(t,r){for(H=0;H<et.length;H++)if((G=et[H])&&G[0]&&G[0].trace&&!0===(Y=G[0].trace).visible&&0!==Y._length&&-1===[\"carpet\",\"contourcarpet\"].indexOf(Y._module.name)){if(\"splom\"===Y.type?W=s[X=0]:(W=v.getSubplot(Y),X=s.indexOf(W)),Z=S,v.isUnifiedHover(Z)&&(Z=Z.charAt(0)),Q={cd:G,trace:Y,xa:b[X],ya:_[X],maxHoverDistance:P,maxSpikeDistance:O,index:!1,distance:Math.min(ct,P),spikeDistance:1/0,xSpike:void 0,ySpike:void 0,color:p.defaultLine,name:Y.name,x0:void 0,x1:void 0,y0:void 0,y1:void 0,xLabelVal:void 0,yLabelVal:void 0,zLabelVal:void 0,text:void 0},l[W]&&(Q.subplot=l[W]._subplot),l._splomScenes&&l._splomScenes[Y.uid]&&(Q.scene=l._splomScenes[Y.uid]),$=tt.length,\"array\"===Z){var n=e[H];\"pointNumber\"in n?(Q.index=n.pointNumber,Z=\"closest\"):(Z=\"\",\"xval\"in n&&(J=n.xval,Z=\"x\"),\"yval\"in 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x=y[0];i(x.x0)&&i(x.y0)&&(h=ht(x),(!rt.hLinePoint||rt.hLinePoint.spikeDistance>h.spikeDistance)&&(rt.hLinePoint=h))}}}}}function ft(t,e,r){for(var n,i=null,a=1/0,o=0;o<t.length;o++)n=t[o].spikeDistance,r&&0===o&&(n=-1/0),n<=a&&n<=e&&(i=t[o],a=n);return i}function ht(t){return t?{xa:t.xa,ya:t.ya,x:void 0!==t.xSpike?t.xSpike:(t.x0+t.x1)/2,y:void 0!==t.ySpike?t.ySpike:(t.y0+t.y1)/2,distance:t.distance,spikeDistance:t.spikeDistance,curveNumber:t.trace.index,color:t.color,pointNumber:t.index}:null}ut();var pt={fullLayout:l,container:l._hoverlayer,event:e},dt=t._spikepoints,gt={vLinePoint:rt.vLinePoint,hLinePoint:rt.hLinePoint};t._spikepoints=gt;var mt=function(){tt.sort((function(t,e){return t.distance-e.distance})),tt=function(t,e){for(var r=e.charAt(0),n=[],i=[],a=[],o=0;o<t.length;o++){var s=t[o];m.traceIs(s.trace,\"bar-like\")||m.traceIs(s.trace,\"box-violin\")?a.push(s):s.trace[r+\"period\"]?i.push(s):n.push(s)}return n.concat(i).concat(a)}(tt,S)};mt();var vt=S.charAt(0),yt=(\"x\"===vt||\"y\"===vt)&&tt[0]&&L[tt[0].trace.type];if(g&&0!==O&&0!==tt.length){var xt=ft(tt.filter((function(t){return t.ya.showspikes})),O,yt);rt.hLinePoint=ht(xt);var bt=ft(tt.filter((function(t){return t.xa.showspikes})),O,yt);rt.vLinePoint=ht(bt)}if(0===tt.length){var _t=d.unhoverRaw(t,e);return!g||null===rt.hLinePoint&&null===rt.vLinePoint||F(dt)&&R(t,rt,pt),_t}g&&F(dt)&&R(t,rt,pt);if(v.isXYhover(Z)&&0!==tt[0].length&&\"splom\"!==tt[0].trace.type){var wt=tt[0],Tt=(tt=E[wt.trace.type]?tt.filter((function(t){return t.trace.index===wt.trace.index})):[wt]).length,kt=N(\"x\",wt,l),At=N(\"y\",wt,l);ut(kt,At);var Mt,St=[],Et={},Lt=0,Ct=function(t){var e=E[t.trace.type]?C(t):t.trace.index;if(Et[e]){var r=Et[e]-1,n=St[r];r>0&&Math.abs(t.distance)<Math.abs(n.distance)&&(St[r]=t)}else Lt++,Et[e]=Lt,St.push(t)};for(Mt=0;Mt<Tt;Mt++)Ct(tt[Mt]);for(Mt=tt.length-1;Mt>Tt-1;Mt--)Ct(tt[Mt]);tt=St,mt()}var Pt=t._hoverdata,It=[],Ot=j(t),zt=U(t);for(q=0;q<tt.length;q++){var Dt=tt[q],Rt=v.makeEventData(Dt,Dt.trace,Dt.cd);if(!1!==Dt.hovertemplate){var Ft=!1;Dt.cd[Dt.index]&&Dt.cd[Dt.index].ht&&(Ft=Dt.cd[Dt.index].ht),Dt.hovertemplate=Ft||Dt.trace.hovertemplate||!1}if(Dt.xa&&Dt.ya){var Bt=Dt.x0+Dt.xa._offset,Nt=Dt.x1+Dt.xa._offset,jt=Dt.y0+Dt.ya._offset,Ut=Dt.y1+Dt.ya._offset,Vt=Math.min(Bt,Nt),qt=Math.max(Bt,Nt),Ht=Math.min(jt,Ut),Gt=Math.max(jt,Ut);Rt.bbox={x0:Vt+zt,x1:qt+zt,y0:Ht+Ot,y1:Gt+Ot}}Dt.eventData=[Rt],It.push(Rt)}t._hoverdata=It;var Yt=\"y\"===S&&(et.length>1||tt.length>1)||\"closest\"===S&&nt&&tt.length>1,Wt=p.combine(l.plot_bgcolor||p.background,l.paper_bgcolor),Xt=I(tt,{gd:t,hovermode:S,rotateLabels:Yt,bgColor:Wt,container:l._hoverlayer,outerContainer:l._paper.node(),commonLabelOpts:l.hoverlabel,hoverdistance:l.hoverdistance});v.isUnifiedHover(S)||(!function(t,e,r){var n,i,a,o,s,l,c,u=0,f=1,h=t.size(),p=new Array(h),d=0;function g(t){var e=t[0],r=t[t.length-1];if(i=e.pmin-e.pos-e.dp+e.size,a=r.pos+r.dp+r.size-e.pmax,i>.01){for(s=t.length-1;s>=0;s--)t[s].dp+=i;n=!1}if(!(a<.01)){if(i<-.01){for(s=t.length-1;s>=0;s--)t[s].dp-=a;n=!1}if(n){var c=0;for(o=0;o<t.length;o++)(l=t[o]).pos+l.dp+l.size>e.pmax&&c++;for(o=t.length-1;o>=0&&!(c<=0);o--)(l=t[o]).pos>e.pmax-1&&(l.del=!0,c--);for(o=0;o<t.length&&!(c<=0);o++)if((l=t[o]).pos<e.pmin+1)for(l.del=!0,c--,a=2*l.size,s=t.length-1;s>=0;s--)t[s].dp-=a;for(o=t.length-1;o>=0&&!(c<=0);o--)(l=t[o]).pos+l.dp+l.size>e.pmax&&(l.del=!0,c--)}}}t.each((function(t){var n=t[e],i=\"x\"===n._id.charAt(0),a=n.range;0===d&&a&&a[0]>a[1]!==i&&(f=-1),p[d++]=[{datum:t,traceIndex:t.trace.index,dp:0,pos:t.pos,posref:t.posref,size:t.by*(i?T:1)/2,pmin:0,pmax:i?r.width:r.height}]})),p.sort((function(t,e){return t[0].posref-e[0].posref||f*(e[0].traceIndex-t[0].traceIndex)}));for(;!n&&u<=h;){for(u++,n=!0,o=0;o<p.length-1;){var m=p[o],v=p[o+1],y=m[m.length-1],x=v[0];if((i=y.pos+y.dp+y.size-x.pos-x.dp+x.size)>.01&&y.pmin===x.pmin&&y.pmax===x.pmax){for(s=v.length-1;s>=0;s--)v[s].dp+=i;for(m.push.apply(m,v),p.splice(o+1,1),c=0,s=m.length-1;s>=0;s--)c+=m[s].dp;for(a=c/m.length,s=m.length-1;s>=0;s--)m[s].dp-=a;n=!1}else o++}p.forEach(g)}for(o=p.length-1;o>=0;o--){var b=p[o];for(s=b.length-1;s>=0;s--){var _=b[s],w=_.datum;w.offset=_.dp,w.del=_.del}}}(Xt,Yt?\"xa\":\"ya\",l),z(Xt,Yt,l._invScaleX,l._invScaleY));if(e.target&&e.target.tagName){var Zt=m.getComponentMethod(\"annotations\",\"hasClickToShow\")(t,It);f(n.select(e.target),Zt?\"pointer\":\"\")}if(!e.target||a||!function(t,e,r){if(!r||r.length!==t._hoverdata.length)return!0;for(var n=r.length-1;n>=0;n--){var i=r[n],a=t._hoverdata[n];if(i.curveNumber!==a.curveNumber||String(i.pointNumber)!==String(a.pointNumber)||String(i.pointNumbers)!==String(a.pointNumbers))return!0}return!1}(t,0,Pt))return;Pt&&t.emit(\"plotly_unhover\",{event:e,points:Pt});t.emit(\"plotly_hover\",{event:e,points:t._hoverdata,xaxes:b,yaxes:_,xvals:B,yvals:V})}(t,e,r,a)}))},r.loneHover=function(t,e){var r=!0;Array.isArray(t)||(r=!1,t=[t]);var i=e.gd,a=j(i),o=U(i),s=I(t.map((function(t){var r=t._x0||t.x0||t.x||0,n=t._x1||t.x1||t.x||0,s=t._y0||t.y0||t.y||0,l=t._y1||t.y1||t.y||0,c=t.eventData;if(c){var u=Math.min(r,n),f=Math.max(r,n),h=Math.min(s,l),d=Math.max(s,l),g=t.trace;if(m.traceIs(g,\"gl3d\")){var v=i._fullLayout[g.scene]._scene.container,y=v.offsetLeft,x=v.offsetTop;u+=y,f+=y,h+=x,d+=x}c.bbox={x0:u+o,x1:f+o,y0:h+a,y1:d+a},e.inOut_bbox&&e.inOut_bbox.push(c.bbox)}else c=!1;return{color:t.color||p.defaultLine,x0:t.x0||t.x||0,x1:t.x1||t.x||0,y0:t.y0||t.y||0,y1:t.y1||t.y||0,xLabel:t.xLabel,yLabel:t.yLabel,zLabel:t.zLabel,text:t.text,name:t.name,idealAlign:t.idealAlign,borderColor:t.borderColor,fontFamily:t.fontFamily,fontSize:t.fontSize,fontColor:t.fontColor,nameLength:t.nameLength,textAlign:t.textAlign,trace:t.trace||{index:0,hoverinfo:\"\"},xa:{_offset:0},ya:{_offset:0},index:0,hovertemplate:t.hovertemplate||!1,hovertemplateLabels:t.hovertemplateLabels||!1,eventData:c}})),{gd:i,hovermode:\"closest\",rotateLabels:!1,bgColor:e.bgColor||p.background,container:n.select(e.container),outerContainer:e.outerContainer||e.container}),l=0,c=0;return s.sort((function(t,e){return t.y0-e.y0})).each((function(t,r){var n=t.y0-t.by/2;t.offset=n-5<l?l-n+5:0,l=n+t.by+t.offset,r===e.anchorIndex&&(c=t.offset)})).each((function(t){t.offset-=c})),z(s,!1,i._fullLayout._invScaleX,i._fullLayout._invScaleY),r?s:s.node()};var P=/<extra>([\\s\\S]*)<\\/extra>/;function I(t,e){var r=e.gd,i=r._fullLayout,a=e.hovermode,c=e.rotateLabels,f=e.bgColor,d=e.container,g=e.outerContainer,w=e.commonLabelOpts||{},T=e.fontFamily||y.HOVERFONT,k=e.fontSize||y.HOVERFONTSIZE,A=t[0],E=A.xa,L=A.ya,P=a.charAt(0),I=A[P+\"Label\"],z=g.getBoundingClientRect(),D=z.top,R=z.width,F=z.height,B=void 0!==I&&A.distance<=e.hoverdistance&&(\"x\"===a||\"y\"===a);if(B){var N,j,U=!0;for(N=0;N<t.length;N++)if(U&&void 0===t[N].zLabel&&(U=!1),j=t[N].hoverinfo||t[N].trace.hoverinfo){var V=Array.isArray(j)?j:j.split(\"+\");if(-1===V.indexOf(\"all\")&&-1===V.indexOf(a)){B=!1;break}}U&&(B=!1)}var q=d.selectAll(\"g.axistext\").data(B?[0]:[]);if(q.enter().append(\"g\").classed(\"axistext\",!0),q.exit().remove(),q.each((function(){var t=n.select(this),e=o.ensureSingle(t,\"path\",\"\",(function(t){t.style({\"stroke-width\":\"1px\"})})),l=o.ensureSingle(t,\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),c=w.bgcolor||p.defaultLine,f=w.bordercolor||p.contrast(c),d=p.contrast(c),g={family:w.font.family||T,size:w.font.size||k,color:w.font.color||d};e.style({fill:c,stroke:f}),l.text(I).call(h.font,g).call(u.positionText,0,0).call(u.convertToTspans,r),t.attr(\"transform\",\"\");var m,v,y=l.node().getBoundingClientRect();if(\"x\"===a){var x=\"top\"===E.side?\"-\":\"\";l.attr(\"text-anchor\",\"middle\").call(u.positionText,0,\"top\"===E.side?D-y.bottom-M-S:D-y.top+M+S),m=E._offset+(A.x0+A.x1)/2,v=L._offset+(\"top\"===E.side?0:L._length);var b=y.width/2+S;m<b?(m=b,e.attr(\"d\",\"M-\"+(b-M)+\",0L-\"+(b-2*M)+\",\"+x+M+\"H\"+(S+y.width/2)+\"v\"+x+(2*S+y.height)+\"H-\"+b+\"V\"+x+M+\"Z\")):m>i.width-b?(m=i.width-b,e.attr(\"d\",\"M\"+(b-M)+\",0L\"+b+\",\"+x+M+\"v\"+x+(2*S+y.height)+\"H-\"+b+\"V\"+x+M+\"H\"+(b-2*M)+\"Z\")):e.attr(\"d\",\"M0,0L\"+M+\",\"+x+M+\"H\"+(S+y.width/2)+\"v\"+x+(2*S+y.height)+\"H-\"+(S+y.width/2)+\"V\"+x+M+\"H-\"+M+\"Z\")}else{var _,C,P;\"right\"===L.side?(_=\"start\",C=1,P=\"\",m=E._offset+E._length):(_=\"end\",C=-1,P=\"-\",m=E._offset),v=L._offset+(A.y0+A.y1)/2,l.attr(\"text-anchor\",_),e.attr(\"d\",\"M0,0L\"+P+M+\",\"+M+\"V\"+(S+y.height/2)+\"h\"+P+(2*S+y.width)+\"V-\"+(S+y.height/2)+\"H\"+P+M+\"V-\"+M+\"Z\");var O,z=y.height/2,R=D-y.top-z,F=\"clip\"+i._uid+\"commonlabel\"+L._id;if(m<y.width+2*S+M){O=\"M-\"+(M+S)+\"-\"+z+\"h-\"+(y.width-S)+\"V\"+z+\"h\"+(y.width-S)+\"Z\";var B=y.width-m+S;u.positionText(l,B,R),\"end\"===_&&l.selectAll(\"tspan\").each((function(){var 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r=e.currentTarget;r.setAttribute(\"data-attr\",\"zoom\"),r.setAttribute(\"data-val\",\"reset\"),f(t,e),r.setAttribute(\"data-attr\",\"resetLastSave\"),p(t,e),x(t,\"geo\"),x(t,\"mapbox\")}},u.toggleSpikelines={name:\"toggleSpikelines\",title:function(t){return c(t,\"Toggle Spike Lines\")},icon:o.spikeline,attr:\"_cartesianSpikesEnabled\",val:\"on\",click:function(t){var e=t._fullLayout,r=e._cartesianSpikesEnabled;e._cartesianSpikesEnabled=\"on\"===r?\"off\":\"on\",n.call(\"_guiRelayout\",t,function(t){for(var e=\"on\"===t._fullLayout._cartesianSpikesEnabled,r=a.list(t,null,!0),n={},i=0;i<r.length;i++){var o=r[i];n[o._name+\".showspikes\"]=!!e||o._showSpikeInitial}return n}(t))}},u.resetViewMapbox={name:\"resetViewMapbox\",_cat:\"resetView\",title:function(t){return c(t,\"Reset view\")},attr:\"reset\",icon:o.home,click:function(t){x(t,\"mapbox\")}},u.zoomInMapbox={name:\"zoomInMapbox\",_cat:\"zoomin\",title:function(t){return c(t,\"Zoom 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n=t(\"../../lib\"),i=t(\"../color\"),a=t(\"../../plot_api/plot_template\"),o=t(\"./attributes\");e.exports=function(t,e){var r=t.modebar||{},s=a.newContainer(e,\"modebar\");function l(t,e){return n.coerce(r,s,o,t,e)}l(\"orientation\"),l(\"bgcolor\",i.addOpacity(e.paper_bgcolor,.5));var c=i.contrast(i.rgb(e.modebar.bgcolor));l(\"color\",i.addOpacity(c,.3)),l(\"activecolor\",i.addOpacity(c,.7)),l(\"uirevision\",e.uirevision),l(\"add\"),l(\"remove\")}},{\"../../lib\":803,\"../../plot_api/plot_template\":843,\"../color\":666,\"./attributes\":725}],729:[function(t,e,r){\"use strict\";e.exports={moduleType:\"component\",name:\"modebar\",layoutAttributes:t(\"./attributes\"),supplyLayoutDefaults:t(\"./defaults\"),manage:t(\"./manage\")}},{\"./attributes\":725,\"./defaults\":728,\"./manage\":730}],730:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/axis_ids\"),i=t(\"../../traces/scatter/subtypes\"),a=t(\"../../registry\"),o=t(\"../fx/helpers\").isUnifiedHover,s=t(\"./modebar\"),l=t(\"./buttons\"),c=t(\"./constants\").DRAW_MODES;e.exports=function(t){var e=t._fullLayout,r=t._context,u=e._modeBar;if(r.displayModeBar||r.watermark){if(!Array.isArray(r.modeBarButtonsToRemove))throw new Error([\"*modeBarButtonsToRemove* configuration options\",\"must be an array.\"].join(\" \"));if(!Array.isArray(r.modeBarButtonsToAdd))throw new Error([\"*modeBarButtonsToAdd* configuration options\",\"must be an array.\"].join(\" \"));var f,h=r.modeBarButtons;f=Array.isArray(h)&&h.length?function(t){for(var e=0;e<t.length;e++)for(var r=t[e],n=0;n<r.length;n++){var i=r[n];if(\"string\"==typeof i){if(void 0===l[i])throw new Error([\"*modeBarButtons* configuration options\",\"invalid button name\"].join(\" \"));t[e][n]=l[i]}}return t}(h):!r.displayModeBar&&r.watermark?[]:function(t){var e=t._fullLayout,r=t._fullData,s=t._context;function u(t,e){if(\"string\"==typeof e){if(e.toLowerCase()===t.toLowerCase())return!0}else{var r=e.name,n=e._cat||e.name;if(r===t||n===t.toLowerCase())return!0}return!1}var f=e.modebar.add;\"string\"==typeof f&&(f=[f]);var h=e.modebar.remove;\"string\"==typeof h&&(h=[h]);var p=s.modeBarButtonsToAdd.concat(f.filter((function(t){for(var e=0;e<s.modeBarButtonsToRemove.length;e++)if(u(t,s.modeBarButtonsToRemove[e]))return!1;return!0}))),d=s.modeBarButtonsToRemove.concat(h.filter((function(t){for(var e=0;e<s.modeBarButtonsToAdd.length;e++)if(u(t,s.modeBarButtonsToAdd[e]))return!1;return!0}))),g=e._has(\"cartesian\"),m=e._has(\"gl3d\"),v=e._has(\"geo\"),y=e._has(\"pie\"),x=e._has(\"funnelarea\"),b=e._has(\"gl2d\"),_=e._has(\"ternary\"),w=e._has(\"mapbox\"),T=e._has(\"polar\"),k=e._has(\"sankey\"),A=function(t){for(var e=n.list({_fullLayout:t},null,!0),r=0;r<e.length;r++)if(!e[r].fixedrange)return!1;return!0}(e),M=o(e.hovermode),S=[];function 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t.match(n.segmentRE).forEach((function(t){var a=e[t.charAt(0)].drawn;if(void 0!==a){var o=t.substr(1).match(n.paramRE);!o||o.length<a||r.push(i.cleanNumber(o[a]))}})),r},r.getDataToPixel=function(t,e,n,i){var a,o=t._fullLayout._size;if(e)if(\"domain\"===i)a=function(t){return e._length*(n?1-t:t)+e._offset};else{var s=r.shapePositionToRange(e);a=function(t){return e._offset+e.r2p(s(t,!0))},\"date\"===e.type&&(a=r.decodeDate(a))}else a=n?function(t){return o.t+o.h*(1-t)}:function(t){return o.l+o.w*t};return a},r.getPixelToData=function(t,e,n,i){var a,o=t._fullLayout._size;if(e)if(\"domain\"===i)a=function(t){var r=(t-e._offset)/e._length;return n?1-r:r};else{var s=r.rangeToShapePosition(e);a=function(t){return s(e.p2r(t-e._offset))}}else a=n?function(t){return 1-(t-o.t)/o.h}:function(t){return(t-o.l)/o.w};return a},r.roundPositionForSharpStrokeRendering=function(t,e){var r=1===Math.round(e%2),n=Math.round(t);return r?n+.5:n},r.makeOptionsAndPlotinfo=function(t,e){var r=t._fullLayout.shapes[e]||{},n=t._fullLayout._plots[r.xref+r.yref];return!!n?n._hadPlotinfo=!0:(n={},r.xref&&\"paper\"!==r.xref&&(n.xaxis=t._fullLayout[r.xref+\"axis\"]),r.yref&&\"paper\"!==r.yref&&(n.yaxis=t._fullLayout[r.yref+\"axis\"])),n.xsizemode=r.xsizemode,n.ysizemode=r.ysizemode,n.xanchor=r.xanchor,n.yanchor=r.yanchor,{options:r,plotinfo:n}}},{\"../../lib\":803,\"./constants\":748}],758:[function(t,e,r){\"use strict\";var n=t(\"./draw\");e.exports={moduleType:\"component\",name:\"shapes\",layoutAttributes:t(\"./attributes\"),supplyLayoutDefaults:t(\"./defaults\"),supplyDrawNewShapeDefaults:t(\"./draw_newshape/defaults\"),includeBasePlot:t(\"../../plots/cartesian/include_components\")(\"shapes\"),calcAutorange:t(\"./calc_autorange\"),draw:n.draw,drawOne:n.drawOne}},{\"../../plots/cartesian/include_components\":867,\"./attributes\":746,\"./calc_autorange\":747,\"./defaults\":749,\"./draw\":750,\"./draw_newshape/defaults\":753}],759:[function(t,e,r){\"use strict\";var n=t(\"../../plots/font_attributes\"),i=t(\"../../plots/pad_attributes\"),a=t(\"../../lib/extend\").extendDeepAll,o=t(\"../../plot_api/edit_types\").overrideAll,s=t(\"../../plots/animation_attributes\"),l=t(\"../../plot_api/plot_template\").templatedArray,c=t(\"./constants\"),u=l(\"step\",{visible:{valType:\"boolean\",dflt:!0},method:{valType:\"enumerated\",values:[\"restyle\",\"relayout\",\"animate\",\"update\",\"skip\"],dflt:\"restyle\"},args:{valType:\"info_array\",freeLength:!0,items:[{valType:\"any\"},{valType:\"any\"},{valType:\"any\"}]},label:{valType:\"string\"},value:{valType:\"string\"},execute:{valType:\"boolean\",dflt:!0}});e.exports=o(l(\"slider\",{visible:{valType:\"boolean\",dflt:!0},active:{valType:\"number\",min:0,dflt:0},steps:u,lenmode:{valType:\"enumerated\",values:[\"fraction\",\"pixels\"],dflt:\"fraction\"},len:{valType:\"number\",min:0,dflt:1},x:{valType:\"number\",min:-2,max:3,dflt:0},pad:a(i({editType:\"arraydraw\"}),{},{t:{dflt:20}}),xanchor:{valType:\"enumerated\",values:[\"auto\",\"left\",\"center\",\"right\"],dflt:\"left\"},y:{valType:\"number\",min:-2,max:3,dflt:0},yanchor:{valType:\"enumerated\",values:[\"auto\",\"top\",\"middle\",\"bottom\"],dflt:\"top\"},transition:{duration:{valType:\"number\",min:0,dflt:150},easing:{valType:\"enumerated\",values:s.transition.easing.values,dflt:\"cubic-in-out\"}},currentvalue:{visible:{valType:\"boolean\",dflt:!0},xanchor:{valType:\"enumerated\",values:[\"left\",\"center\",\"right\"],dflt:\"left\"},offset:{valType:\"number\",dflt:10},prefix:{valType:\"string\"},suffix:{valType:\"string\"},font:n({})},font:n({}),activebgcolor:{valType:\"color\",dflt:c.gripBgActiveColor},bgcolor:{valType:\"color\",dflt:c.railBgColor},bordercolor:{valType:\"color\",dflt:c.railBorderColor},borderwidth:{valType:\"number\",min:0,dflt:c.railBorderWidth},ticklen:{valType:\"number\",min:0,dflt:c.tickLength},tickcolor:{valType:\"color\",dflt:c.tickColor},tickwidth:{valType:\"number\",min:0,dflt:1},minorticklen:{valType:\"number\",min:0,dflt:c.minorTickLength}}),\"arraydraw\",\"from-root\")},{\"../../lib/extend\":793,\"../../plot_api/edit_types\":836,\"../../plot_api/plot_template\":843,\"../../plots/animation_attributes\":848,\"../../plots/font_attributes\":883,\"../../plots/pad_attributes\":916,\"./constants\":760}],760:[function(t,e,r){\"use strict\";e.exports={name:\"sliders\",containerClassName:\"slider-container\",groupClassName:\"slider-group\",inputAreaClass:\"slider-input-area\",railRectClass:\"slider-rail-rect\",railTouchRectClass:\"slider-rail-touch-rect\",gripRectClass:\"slider-grip-rect\",tickRectClass:\"slider-tick-rect\",inputProxyClass:\"slider-input-proxy\",labelsClass:\"slider-labels\",labelGroupClass:\"slider-label-group\",labelClass:\"slider-label\",currentValueClass:\"slider-current-value\",railHeight:5,menuIndexAttrName:\"slider-active-index\",autoMarginIdRoot:\"slider-\",minWidth:30,minHeight:30,textPadX:40,arrowOffsetX:4,railRadius:2,railWidth:5,railBorder:4,railBorderWidth:1,railBorderColor:\"#bec8d9\",railBgColor:\"#f8fafc\",railInset:8,stepInset:10,gripRadius:10,gripWidth:20,gripHeight:20,gripBorder:20,gripBorderWidth:1,gripBorderColor:\"#bec8d9\",gripBgColor:\"#f6f8fa\",gripBgActiveColor:\"#dbdde0\",labelPadding:8,labelOffset:0,tickWidth:1,tickColor:\"#333\",tickOffset:25,tickLength:7,minorTickOffset:25,minorTickColor:\"#333\",minorTickLength:4,currentValuePadding:8,currentValueInset:0}},{}],761:[function(t,e,r){\"use 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r=x(y,e,t.label),n=r.node()&&o.bBox(r.node())||{width:0,height:0},i=c.lineCount(r);u.currentValueMaxWidth=Math.max(u.currentValueMaxWidth,Math.ceil(n.width)),u.currentValueHeight=Math.max(u.currentValueHeight,Math.ceil(n.height)),u.currentValueMaxLines=Math.max(u.currentValueMaxLines,i)})),u.currentValueTotalHeight=u.currentValueHeight+e.currentvalue.offset,y.remove()}u.height=u.currentValueTotalHeight+f.tickOffset+e.ticklen+f.labelOffset+u.labelHeight+e.pad.t+e.pad.b;var b=\"left\";s.isRightAnchor(e)&&(u.lx-=u.outerLength,b=\"right\"),s.isCenterAnchor(e)&&(u.lx-=u.outerLength/2,b=\"center\");var w=\"top\";s.isBottomAnchor(e)&&(u.ly-=u.height,w=\"bottom\"),s.isMiddleAnchor(e)&&(u.ly-=u.height/2,w=\"middle\"),u.outerLength=Math.ceil(u.outerLength),u.height=Math.ceil(u.height),u.lx=Math.round(u.lx),u.ly=Math.round(u.ly);var T={y:e.y,b:u.height*g[w],t:u.height*d[w]};\"fraction\"===e.lenmode?(T.l=0,T.xl=e.x-e.len*d[b],T.r=0,T.xr=e.x+e.len*g[b]):(T.x=e.x,T.l=u.outerLength*d[b],T.r=u.outerLength*g[b]),i.autoMargin(t,m(e),T)}function x(t,e,r){if(e.currentvalue.visible){var n,i,a=e._dims;switch(e.currentvalue.xanchor){case\"right\":n=a.inputAreaLength-f.currentValueInset-a.currentValueMaxWidth,i=\"left\";break;case\"center\":n=.5*a.inputAreaLength,i=\"middle\";break;default:n=f.currentValueInset,i=\"left\"}var l=s.ensureSingle(t,\"text\",f.labelClass,(function(t){t.attr({\"text-anchor\":i,\"data-notex\":1})})),u=e.currentvalue.prefix?e.currentvalue.prefix:\"\";if(\"string\"==typeof r)u+=r;else{var h=e.steps[e.active].label,d=e._gd._fullLayout._meta;d&&(h=s.templateString(h,d)),u+=h}e.currentvalue.suffix&&(u+=e.currentvalue.suffix),l.call(o.font,e.currentvalue.font).text(u).call(c.convertToTspans,e._gd);var g=c.lineCount(l),m=(a.currentValueMaxLines+1-g)*e.currentvalue.font.size*p;return c.positionText(l,n,m),l}}function b(t,e,r){s.ensureSingle(t,\"rect\",f.gripRectClass,(function(n){n.call(A,e,t,r).style(\"pointer-events\",\"all\")})).attr({width:f.gripWidth,height:f.gripHeight,rx:f.gripRadius,ry:f.gripRadius}).call(a.stroke,r.bordercolor).call(a.fill,r.bgcolor).style(\"stroke-width\",r.borderwidth+\"px\")}function _(t,e,r){var n=s.ensureSingle(t,\"text\",f.labelClass,(function(t){t.attr({\"text-anchor\":\"middle\",\"data-notex\":1})})),i=e.step.label,a=r._gd._fullLayout._meta;return a&&(i=s.templateString(i,a)),n.call(o.font,r.font).text(i).call(c.convertToTspans,r._gd),n}function w(t,e){var r=s.ensureSingle(t,\"g\",f.labelsClass),i=e._dims,a=r.selectAll(\"g.\"+f.labelGroupClass).data(i.labelSteps);a.enter().append(\"g\").classed(f.labelGroupClass,!0),a.exit().remove(),a.each((function(t){var r=n.select(this);r.call(_,t,e),o.setTranslate(r,E(e,t.fraction),f.tickOffset+e.ticklen+e.font.size*p+f.labelOffset+i.currentValueTotalHeight)}))}function T(t,e,r,n,i){var a=Math.round(n*(r._stepCount-1)),o=r._visibleSteps[a]._index;o!==r.active&&k(t,e,r,o,!0,i)}function k(t,e,r,n,a,o){var s=r.active;r.active=n,u(t.layout,f.name,r).applyUpdate(\"active\",n);var l=r.steps[r.active];e.call(S,r,o),e.call(x,r),t.emit(\"plotly_sliderchange\",{slider:r,step:r.steps[r.active],interaction:a,previousActive:s}),l&&l.method&&a&&(e._nextMethod?(e._nextMethod.step=l,e._nextMethod.doCallback=a,e._nextMethod.doTransition=o):(e._nextMethod={step:l,doCallback:a,doTransition:o},e._nextMethodRaf=window.requestAnimationFrame((function(){var r=e._nextMethod.step;r.method&&(r.execute&&i.executeAPICommand(t,r.method,r.args),e._nextMethod=null,e._nextMethodRaf=null)}))))}function A(t,e,r){var i=r.node(),o=n.select(e);function s(){return r.data()[0]}function l(){var t=s();e.emit(\"plotly_sliderstart\",{slider:t});var l=r.select(\".\"+f.gripRectClass);n.event.stopPropagation(),n.event.preventDefault(),l.call(a.fill,t.activebgcolor);var c=L(t,n.mouse(i)[0]);function u(){var t=s(),a=L(t,n.mouse(i)[0]);T(e,r,t,a,!1)}function h(){var t=s();t._dragging=!1,l.call(a.fill,t.bgcolor),o.on(\"mouseup\",null),o.on(\"mousemove\",null),o.on(\"touchend\",null),o.on(\"touchmove\",null),e.emit(\"plotly_sliderend\",{slider:t,step:t.steps[t.active]})}T(e,r,t,c,!0),t._dragging=!0,o.on(\"mousemove\",u),o.on(\"touchmove\",u),o.on(\"mouseup\",h),o.on(\"touchend\",h)}t.on(\"mousedown\",l),t.on(\"touchstart\",l)}function M(t,e){var r=t.selectAll(\"rect.\"+f.tickRectClass).data(e._visibleSteps),i=e._dims;r.enter().append(\"rect\").classed(f.tickRectClass,!0),r.exit().remove(),r.attr({width:e.tickwidth+\"px\",\"shape-rendering\":\"crispEdges\"}),r.each((function(t,r){var s=r%i.labelStride==0,l=n.select(this);l.attr({height:s?e.ticklen:e.minorticklen}).call(a.fill,e.tickcolor),o.setTranslate(l,E(e,r/(e._stepCount-1))-.5*e.tickwidth,(s?f.tickOffset:f.minorTickOffset)+i.currentValueTotalHeight)}))}function S(t,e,r){for(var 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o=e.length===r.length;if(!i&&!o)return{fullReplot:!0,calc:!0};var s,l,c=T.traceFlags();c.arrays={},c.nChanges=0,c.nChangesAnim=0;var u={getValObject:function(t){var e=f.getTraceValObject(l,t);return!l._module.animatable&&e.anim&&(e.anim=!1),e},flags:c,immutable:n,transition:i,newDataRevision:a,gd:t},p={};for(s=0;s<e.length;s++)if(r[s]){if(l=r[s]._fullInput,h.hasMakesDataTransform(l)&&(l=r[s]),p[l.uid])continue;p[l.uid]=1,it(e[s]._fullInput,l,[],u)}(c.calc||c.plot)&&(c.fullReplot=!0);i&&c.nChanges&&c.nChangesAnim&&(c.anim=c.nChanges===c.nChangesAnim&&o?\"all\":\"some\");return c}(t,c,v,x,b,A);if(X(t)&&(k.layoutReplot=!0),S.calc||k.calc){t.calcdata=void 0;for(var E=Object.getOwnPropertyNames(y),C=0;C<E.length;C++){var P=E[C],I=P.substring(0,5);if(\"xaxis\"===I||\"yaxis\"===I){var O=y[P]._emptyCategories;O&&O()}}}else h.supplyDefaultsUpdateCalc(t.calcdata,v);var z=[];if(a&&(t._transitionData={},h.createTransitionData(t),z.push((function(){return 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t.dtick=e>.3?\"D2\":\"D1\"}else\"category\"===t.type||\"multicategory\"===t.type?(t.tick0=0,t.dtick=Math.ceil(Math.max(e,1))):At(t)?(t.tick0=0,r=1,t.dtick=ot(e,r,at)):(t.tick0=0,r=n(10),t.dtick=ot(e,r,$));if(0===t.dtick&&(t.dtick=1),!i(t.dtick)&&\"string\"!=typeof t.dtick){var f=t.dtick;throw t.dtick=1,\"ax.dtick error: \"+String(f)}},V.tickIncrement=function(t,e,r,a){var o=r?-1:1;if(i(e))return s.increment(t,o*e);var l=e.charAt(0),c=o*Number(e.substr(1));if(\"M\"===l)return s.incrementMonth(t,c,a);if(\"L\"===l)return Math.log(Math.pow(10,t)+c)/Math.LN10;if(\"D\"===l){var u=\"D2\"===e?it:nt,f=t+.01*o,h=s.roundUp(s.mod(f,1),u,r);return Math.floor(f)+Math.log(n.round(Math.pow(10,h),1))/Math.LN10}throw\"unrecognized dtick \"+String(e)},V.tickFirst=function(t,e){var r=t.r2l||Number,a=s.simpleMap(t.range,r,void 0,void 0,e),o=a[1]<a[0],l=o?Math.floor:Math.ceil,c=X(a)[0],u=t.dtick,f=r(t.tick0);if(i(u)){var 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h=s.simpleMap(t.range,t.r2l),p=(Math.abs(h[1]-h[0])-(t._lBreaks||0))/1e4;for(a=0;a<t.ticktext.length&&!(Math.abs(e-f(t.tickvals[a]))<p);a++);if(a<t.ticktext.length)return o.text=String(t.ticktext[a]),o}function d(n){if(void 0===n)return!0;if(r)return\"none\"===n;var i={first:t._tmin,last:t._tmax}[n];return\"all\"!==n&&e!==i}var g=r?\"never\":\"none\"!==t.exponentformat&&d(t.showexponent)?\"hide\":\"\";if(\"date\"===u?function(t,e,r,n){var a=t._tickround,o=r&&t.hoverformat||V.getTickFormat(t);n&&(a=i(a)?4:{y:\"m\",m:\"d\",d:\"M\",M:\"S\",S:4}[a]);var l,c=s.formatDate(e.x,o,a,t._dateFormat,t.calendar,t._extraFormat),u=c.indexOf(\"\\n\");-1!==u&&(l=c.substr(u+1),c=c.substr(0,u));n&&(\"00:00:00\"===c||\"00:00\"===c?(c=l,l=\"\"):8===c.length&&(c=c.replace(/:00$/,\"\")));if(l)if(r)\"d\"===a?c+=\", \"+l:c=l+(c?\", \"+c:\"\");else if(t._inCalcTicks&&t._prevDateHead===l){var f=St(t),h=t._realSide||t.side;(!f&&\"top\"===h||f&&\"bottom\"===h)&&(c+=\"<br> \")}else 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a=n._fullLayout._zoomlayer.selectAll(\".select-outline-\"+r.id);if(a&&n._fullLayout._drawing){var o=v(a,t);o&&i.call(\"_guiRelayout\",n,{shapes:o}),n._fullLayout._drawing=!1}}r.selection={},r.selection.selectionDefs=t.selectionDefs=[],r.selection.mergedPolygons=t.mergedPolygons=[]}function N(t,e,r,n){var i,a,o,s=[],l=e.map((function(t){return t._id})),c=r.map((function(t){return t._id}));for(o=0;o<t.calcdata.length;o++)if(!0===(a=(i=t.calcdata[o])[0].trace).visible&&a._module&&a._module.selectPoints)if(!n||a.subplot!==n&&a.geo!==n)if(\"splom\"===a.type&&a._xaxes[l[0]]&&a._yaxes[c[0]]){var u=h(a._module,i,e[0],r[0]);u.scene=t._fullLayout._splomScenes[a.uid],s.push(u)}else if(\"sankey\"===a.type){var f=h(a._module,i,e[0],r[0]);s.push(f)}else{if(-1===l.indexOf(a.xaxis))continue;if(-1===c.indexOf(a.yaxis))continue;s.push(h(a._module,i,_(t,a.xaxis),_(t,a.yaxis)))}else s.push(h(a._module,i,e[0],r[0]));return s;function h(t,e,r,n){return{_module:t,cd:e,xaxis:r,yaxis:n}}}function j(t){var e=t.searchInfo.cd[0].trace,r=t.pointNumber,n=t.pointNumbers,i=n.length>0?n[0]:r;return!!e.selectedpoints&&e.selectedpoints.indexOf(i)>-1}function U(t,e,r){var n,a,o,s;for(n=0;n<e.length;n++){var l=e[n].cd[0].trace._fullInput,c=t._fullLayout._tracePreGUI[l.uid]||{};void 0===c.selectedpoints&&(c.selectedpoints=l._input.selectedpoints||null)}if(r){var u=r.points||[];for(n=0;n<e.length;n++)(s=e[n].cd[0].trace)._input.selectedpoints=s._fullInput.selectedpoints=[],s._fullInput!==s&&(s.selectedpoints=[]);for(n=0;n<u.length;n++){var f=u[n],h=f.data,p=f.fullData;f.pointIndices?([].push.apply(h.selectedpoints,f.pointIndices),s._fullInput!==s&&[].push.apply(p.selectedpoints,f.pointIndices)):(h.selectedpoints.push(f.pointIndex),s._fullInput!==s&&p.selectedpoints.push(f.pointIndex))}}else for(n=0;n<e.length;n++)delete(s=e[n].cd[0].trace).selectedpoints,delete s._input.selectedpoints,s._fullInput!==s&&delete s._fullInput.selectedpoints;var d=!1;for(n=0;n<e.length;n++){s=(o=(a=e[n]).cd)[0].trace,i.traceIs(s,\"regl\")&&(d=!0);var g=a._module,m=g.styleOnSelect||g.style;m&&(m(t,o,o[0].node3),o[0].nodeRangePlot3&&m(t,o,o[0].nodeRangePlot3))}d&&(w(t),T(t))}function V(t,e){if(Array.isArray(t))for(var r=e.cd,n=e.cd[0].trace,i=0;i<t.length;i++)t[i]=l(t[i],n,r);return t}function q(t,e){for(var r=[],n=0;n<t.length;n++){r[n]=[];for(var i=0;i<t[n].length;i++){r[n][i]=[],r[n][i][0]=i?\"L\":\"M\";for(var a=0;a<t[n][i].length;a++)r[n][i].push(t[n][i][a])}e||r[n].push([\"Z\",r[n][0][1],r[n][0][2]])}return r}e.exports={prepSelect:function(t,e,r,i,l){var c=u(l),v=f(l),x=p(l),_=h(l),w=d(l),T=\"drawcircle\"===l,E=\"drawline\"===l||T,L=i.gd,z=L._fullLayout,D=z._zoomlayer,j=i.element.getBoundingClientRect(),H=i.plotinfo,G=I(H),Y=e-j.left,W=r-j.top;z._calcInverseTransform(L);var X=y.apply3DTransform(z._invTransform)(Y,W);Y=X[0],W=X[1];var 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n=t(\"@plotly/d3\"),i=t(\"d3-geo\"),a=i.geoPath,o=i.geoDistance,s=t(\"d3-geo-projection\"),l=t(\"../../registry\"),c=t(\"../../lib\"),u=c.strTranslate,f=t(\"../../components/color\"),h=t(\"../../components/drawing\"),p=t(\"../../components/fx\"),d=t(\"../plots\"),g=t(\"../cartesian/axes\"),m=t(\"../cartesian/autorange\").getAutoRange,v=t(\"../../components/dragelement\"),y=t(\"../cartesian/select\").prepSelect,x=t(\"../cartesian/select\").clearSelect,b=t(\"../cartesian/select\").selectOnClick,_=t(\"./zoom\"),w=t(\"./constants\"),T=t(\"../../lib/geo_location_utils\"),k=t(\"../../lib/topojson_utils\"),A=t(\"topojson-client\").feature;function 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i=t[n],a=i[0].trace;\"choropleth\"===a.type&&(this.hasChoropleth=!0),!0===a.visible&&a._length>0&&a._module.calcGeoJSON(i,e)}if(!this.updateProjection(t,e)){this.viewInitial&&this.scope===r.scope||this.saveViewInitial(r),this.scope=r.scope,this.updateBaseLayers(e,r),this.updateDims(e,r),this.updateFx(e,r),d.generalUpdatePerTraceModule(this.graphDiv,this,t,r);var o=this.layers.frontplot.select(\".scatterlayer\");this.dataPoints.point=o.selectAll(\".point\"),this.dataPoints.text=o.selectAll(\"text\"),this.dataPaths.line=o.selectAll(\".js-line\");var s=this.layers.backplot.select(\".choroplethlayer\");this.dataPaths.choropleth=s.selectAll(\"path\"),this.render()}},S.updateProjection=function(t,e){var r=this.graphDiv,n=e[this.id],l=e._size,u=n.domain,f=n.projection,h=n.lonaxis,p=n.lataxis,d=h._ax,g=p._ax,v=this.projection=function(t){var e=t.projection,r=e.type,n=w.projNames[r];n=\"geo\"+c.titleCase(n);for(var l=(i[n]||s[n])(),u=t._isSatellite?180*Math.acos(1/e.distance)/Math.PI:t._isClipped?w.lonaxisSpan[r]/2:null,f=[\"center\",\"rotate\",\"parallels\",\"clipExtent\"],h=function(t){return t?l:[]},p=0;p<f.length;p++){var d=f[p];\"function\"!=typeof l[d]&&(l[d]=h)}l.isLonLatOverEdges=function(t){if(null===l(t))return!0;if(u){var e=l.rotate();return o(t,[-e[0],-e[1]])>u*Math.PI/180}return!1},l.getPath=function(){return a().projection(l)},l.getBounds=function(t){return l.getPath().bounds(t)},l.precision(w.precision),t._isSatellite&&l.tilt(e.tilt).distance(e.distance);u&&l.clipAngle(u-w.clipPad);return l}(n),y=[[l.l+l.w*u.x[0],l.t+l.h*(1-u.y[1])],[l.l+l.w*u.x[1],l.t+l.h*(1-u.y[0])]],x=n.center||{},b=f.rotation||{},_=h.range||[],T=p.range||[];if(n.fitbounds){d._length=y[1][0]-y[0][0],g._length=y[1][1]-y[0][1],d.range=m(r,d),g.range=m(r,g);var k=(d.range[0]+d.range[1])/2,A=(g.range[0]+g.range[1])/2;if(n._isScoped)x={lon:k,lat:A};else if(n._isClipped){x={lon:k,lat:A},b={lon:k,lat:A,roll:b.roll};var M=f.type,S=w.lonaxisSpan[M]/2||180,L=w.lataxisSpan[M]/2||90;_=[k-S,k+S],T=[A-L,A+L]}else x={lon:k,lat:A},b={lon:k,lat:b.lat,roll:b.roll}}v.center([x.lon-b.lon,x.lat-b.lat]).rotate([-b.lon,-b.lat,b.roll]).parallels(f.parallels);var C=E(_,T);v.fitExtent(y,C);var P=this.bounds=v.getBounds(C),I=this.fitScale=v.scale(),O=v.translate();if(n.fitbounds){var z=v.getBounds(E(d.range,g.range)),D=Math.min((P[1][0]-P[0][0])/(z[1][0]-z[0][0]),(P[1][1]-P[0][1])/(z[1][1]-z[0][1]));isFinite(D)?v.scale(D*I):c.warn(\"Something went wrong during\"+this.id+\"fitbounds computations.\")}else v.scale(f.scale*I);var R=this.midPt=[(P[0][0]+P[1][0])/2,(P[0][1]+P[1][1])/2];if(v.translate([O[0]+(R[0]-O[0]),O[1]+(R[1]-O[1])]).clipExtent(P),n._isAlbersUsa){var F=v([x.lon,x.lat]),B=v.translate();v.translate([B[0]-(F[0]-B[0]),B[1]-(F[1]-B[1])])}},S.updateBaseLayers=function(t,e){var r=this,i=r.topojson,a=r.layers,o=r.basePaths;function s(t){return\"lonaxis\"===t||\"lataxis\"===t}function l(t){return Boolean(w.lineLayers[t])}function c(t){return Boolean(w.fillLayers[t])}var u=(this.hasChoropleth?w.layersForChoropleth:w.layers).filter((function(t){return l(t)||c(t)?e[\"show\"+t]:!s(t)||e[t].showgrid})),p=r.framework.selectAll(\".layer\").data(u,String);p.exit().each((function(t){delete a[t],delete o[t],n.select(this).remove()})),p.enter().append(\"g\").attr(\"class\",(function(t){return\"layer \"+t})).each((function(t){var e=a[t]=n.select(this);\"bg\"===t?r.bgRect=e.append(\"rect\").style(\"pointer-events\",\"all\"):s(t)?o[t]=e.append(\"path\").style(\"fill\",\"none\"):\"backplot\"===t?e.append(\"g\").classed(\"choroplethlayer\",!0):\"frontplot\"===t?e.append(\"g\").classed(\"scatterlayer\",!0):l(t)?o[t]=e.append(\"path\").style(\"fill\",\"none\").style(\"stroke-miterlimit\",2):c(t)&&(o[t]=e.append(\"path\").style(\"stroke\",\"none\"))})),p.order(),p.each((function(r){var n=o[r],a=w.layerNameToAdjective[r];\"frame\"===r?n.datum(w.sphereSVG):l(r)||c(r)?n.datum(A(i,i.objects[r])):s(r)&&n.datum(function(t,e,r){var n,i,a,o=e[t],s=w.scopeDefaults[e.scope];\"lonaxis\"===t?(n=s.lonaxisRange,i=s.lataxisRange,a=function(t,e){return[t,e]}):\"lataxis\"===t&&(n=s.lataxisRange,i=s.lonaxisRange,a=function(t,e){return[e,t]});var l={type:\"linear\",range:[n[0],n[1]-1e-6],tick0:o.tick0,dtick:o.dtick};g.setConvert(l,r);var c=g.calcTicks(l);e.isScoped||\"lonaxis\"!==t||c.pop();for(var u=c.length,f=new Array(u),h=0;h<u;h++)for(var p=c[h].x,d=f[h]=[],m=i[0];m<i[1]+2.5;m+=2.5)d.push(a(p,m));return{type:\"MultiLineString\",coordinates:f}}(r,e,t)).call(f.stroke,e[r].gridcolor).call(h.dashLine,\"\",e[r].gridwidth),l(r)?n.call(f.stroke,e[a+\"color\"]).call(h.dashLine,\"\",e[a+\"width\"]):c(r)&&n.call(f.fill,e[a+\"color\"])}))},S.updateDims=function(t,e){var r=this.bounds,n=(e.framewidth||0)/2,i=r[0][0]-n,a=r[0][1]-n,o=r[1][0]-i+n,s=r[1][1]-a+n;h.setRect(this.clipRect,i,a,o,s),this.bgRect.call(h.setRect,i,a,o,s).call(f.fill,e.bgcolor),this.xaxis._offset=i,this.xaxis._length=o,this.yaxis._offset=a,this.yaxis._length=s},S.updateFx=function(t,e){var r=this,i=r.graphDiv,a=r.bgRect,o=t.dragmode,s=t.clickmode;if(!r.isStatic){var u;\"select\"===o?u=function(t,e){(t.range={})[r.id]=[h([e.xmin,e.ymin]),h([e.xmax,e.ymax])]}:\"lasso\"===o&&(u=function(t,e,n){(t.lassoPoints={})[r.id]=n.filtered.map(h)});var f={element:r.bgRect.node(),gd:i,plotinfo:{id:r.id,xaxis:r.xaxis,yaxis:r.yaxis,fillRangeItems:u},xaxes:[r.xaxis],yaxes:[r.yaxis],subplot:r.id,clickFn:function(t){2===t&&x(i)}};\"pan\"===o?(a.node().onmousedown=null,a.call(_(r,e)),a.on(\"dblclick.zoom\",(function(){var t=r.viewInitial,e={};for(var n in 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v=n/(f[2]-f[0])*(l[2]-l[0])+l[0],y=i/(f[3]-f[1])*(l[3]-l[1])+l[1];c.boxInited||(c.boxStart[0]=v,c.boxStart[1]=y,c.dragStart[0]=n,c.dragStart[1]=i),c.boxEnd[0]=v,c.boxEnd[1]=y,c.boxInited=!0,c.boxEnabled||c.boxStart[0]===c.boxEnd[0]&&c.boxStart[1]===c.boxEnd[1]||(c.boxEnabled=!0);var x=Math.abs(c.dragStart[0]-n)<g,b=Math.abs(c.dragStart[1]-i)<g;if(!function(){for(var e=t.graphDiv._fullLayout._axisConstraintGroups,r=t.xaxis._id,n=t.yaxis._id,i=0;i<e.length;i++)if(-1!==e[i][r]){if(-1!==e[i][n])return!0;break}return!1}()||x&&b)x&&(c.boxEnd[0]=c.boxStart[0]),b&&(c.boxEnd[1]=c.boxStart[1]);else{a=c.boxEnd[0]-c.boxStart[0],s=c.boxEnd[1]-c.boxStart[1];var _=(l[3]-l[1])/(l[2]-l[0]);Math.abs(a*_)>Math.abs(s)?(c.boxEnd[1]=c.boxStart[1]+Math.abs(a)*_*(s>=0?1:-1),c.boxEnd[1]<l[1]?(c.boxEnd[1]=l[1],c.boxEnd[0]=c.boxStart[0]+(l[1]-c.boxStart[1])/Math.abs(_)):c.boxEnd[1]>l[3]&&(c.boxEnd[1]=l[3],c.boxEnd[0]=c.boxStart[0]+(l[3]-c.boxStart[1])/Math.abs(_))):(c.boxEnd[0]=c.boxStart[0]+Math.abs(s)/_*(a>=0?1:-1),c.boxEnd[0]<l[0]?(c.boxEnd[0]=l[0],c.boxEnd[1]=c.boxStart[1]+(l[0]-c.boxStart[0])*Math.abs(_)):c.boxEnd[0]>l[2]&&(c.boxEnd[0]=l[2],c.boxEnd[1]=c.boxStart[1]+(l[2]-c.boxStart[0])*Math.abs(_)))}}else c.boxEnabled?(a=c.boxStart[0]!==c.boxEnd[0],s=c.boxStart[1]!==c.boxEnd[1],a||s?(a&&(m(0,c.boxStart[0],c.boxEnd[0]),t.xaxis.autorange=!1),s&&(m(1,c.boxStart[1],c.boxEnd[1]),t.yaxis.autorange=!1),t.relayoutCallback()):t.glplot.setDirty(),c.boxEnabled=!1,c.boxInited=!1):c.boxInited&&(c.boxInited=!1);break;case\"pan\":c.boxEnabled=!1,c.boxInited=!1,e?(c.panning||(c.dragStart[0]=n,c.dragStart[1]=i),Math.abs(c.dragStart[0]-n)<d&&(n=c.dragStart[0]),Math.abs(c.dragStart[1]-i)<d&&(i=c.dragStart[1]),a=(h-n)*(l[2]-l[0])/(r.viewBox[2]-r.viewBox[0]),s=(p-i)*(l[3]-l[1])/(r.viewBox[3]-r.viewBox[1]),l[0]+=a,l[2]+=a,l[1]+=s,l[3]+=s,t.setRanges(l),c.panning=!0,c.lastInputTime=Date.now(),u(),t.cameraChanged(),t.handleAnnotations()):c.panning&&(c.panning=!1,t.relayoutCallback())}c.lastPos[0]=n,c.lastPos[1]=i}return c.mouseListener=n(e,f),e.addEventListener(\"touchstart\",(function(t){var r=a(t.changedTouches[0],e);f(0,r[0],r[1]),f(1,r[0],r[1]),t.preventDefault()}),!!s&&{passive:!1}),e.addEventListener(\"touchmove\",(function(t){t.preventDefault();var r=a(t.changedTouches[0],e);f(1,r[0],r[1]),t.preventDefault()}),!!s&&{passive:!1}),e.addEventListener(\"touchend\",(function(t){f(0,c.lastPos[0],c.lastPos[1]),t.preventDefault()}),!!s&&{passive:!1}),c.wheelListener=i(e,(function(e,n){if(!t.scrollZoom)return!1;var i=t.calcDataBox(),a=r.viewBox,o=c.lastPos[0],s=c.lastPos[1],l=Math.exp(5*n/(a[3]-a[1])),f=o/(a[2]-a[0])*(i[2]-i[0])+i[0],h=s/(a[3]-a[1])*(i[3]-i[1])+i[1];return i[0]=(i[0]-f)*l+f,i[2]=(i[2]-f)*l+f,i[1]=(i[1]-h)*l+h,i[3]=(i[3]-h)*l+h,t.setRanges(i),c.lastInputTime=Date.now(),u(),t.cameraChanged(),t.handleAnnotations(),t.relayoutCallback(),!0}),!0),c}},{\"../cartesian/constants\":861,\"has-passive-events\":444,\"mouse-change\":470,\"mouse-event-offset\":471,\"mouse-wheel\":473}],893:[function(t,e,r){\"use strict\";var n=t(\"../cartesian/axes\"),i=t(\"../../lib/str2rgbarray\");function a(t){this.scene=t,this.gl=t.gl,this.pixelRatio=t.pixelRatio,this.screenBox=[0,0,1,1],this.viewBox=[0,0,1,1],this.dataBox=[-1,-1,1,1],this.borderLineEnable=[!1,!1,!1,!1],this.borderLineWidth=[1,1,1,1],this.borderLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.ticks=[[],[]],this.tickEnable=[!0,!0,!1,!1],this.tickPad=[15,15,15,15],this.tickAngle=[0,0,0,0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickMarkLength=[0,0,0,0],this.tickMarkWidth=[0,0,0,0],this.tickMarkColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labels=[\"x\",\"y\"],this.labelEnable=[!0,!0,!1,!1],this.labelAngle=[0,Math.PI/2,0,3*Math.PI/2],this.labelPad=[15,15,15,15],this.labelSize=[12,12],this.labelFont=[\"sans-serif\",\"sans-serif\"],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.title=\"\",this.titleEnable=!0,this.titleCenter=[0,0,0,0],this.titleAngle=0,this.titleColor=[0,0,0,1],this.titleFont=\"sans-serif\",this.titleSize=18,this.gridLineEnable=[!0,!0],this.gridLineColor=[[0,0,0,.5],[0,0,0,.5]],this.gridLineWidth=[1,1],this.zeroLineEnable=[!0,!0],this.zeroLineWidth=[1,1],this.zeroLineColor=[[0,0,0,1],[0,0,0,1]],this.borderColor=[0,0,0,0],this.backgroundColor=[0,0,0,0],this.static=this.scene.staticPlot}var o=a.prototype,s=[\"xaxis\",\"yaxis\"];o.merge=function(t){var e,r,n,a,o,l,c,u,f,h,p;for(this.titleEnable=!1,this.backgroundColor=i(t.plot_bgcolor),h=0;h<2;++h){var d=(e=s[h]).charAt(0);for(n=(r=t[this.scene[e]._name]).title.text===this.scene.fullLayout._dfltTitle[d]?\"\":r.title.text,p=0;p<=2;p+=2)this.labelEnable[h+p]=!1,this.labels[h+p]=n,this.labelColor[h+p]=i(r.title.font.color),this.labelFont[h+p]=r.title.font.family,this.labelSize[h+p]=r.title.font.size,this.labelPad[h+p]=this.getLabelPad(e,r),this.tickEnable[h+p]=!1,this.tickColor[h+p]=i((r.tickfont||{}).color),this.tickAngle[h+p]=\"auto\"===r.tickangle?0:Math.PI*-r.tickangle/180,this.tickPad[h+p]=this.getTickPad(r),this.tickMarkLength[h+p]=0,this.tickMarkWidth[h+p]=r.tickwidth||0,this.tickMarkColor[h+p]=i(r.tickcolor),this.borderLineEnable[h+p]=!1,this.borderLineColor[h+p]=i(r.linecolor),this.borderLineWidth[h+p]=r.linewidth||0;c=this.hasSharedAxis(r),o=this.hasAxisInDfltPos(e,r)&&!c,l=this.hasAxisInAltrPos(e,r)&&!c,a=r.mirror||!1,u=c?-1!==String(a).indexOf(\"all\"):!!a,f=c?\"allticks\"===a:-1!==String(a).indexOf(\"ticks\"),o?this.labelEnable[h]=!0:l&&(this.labelEnable[h+2]=!0),o?this.tickEnable[h]=r.showticklabels:l&&(this.tickEnable[h+2]=r.showticklabels),(o||u)&&(this.borderLineEnable[h]=r.showline),(l||u)&&(this.borderLineEnable[h+2]=r.showline),(o||f)&&(this.tickMarkLength[h]=this.getTickMarkLength(r)),(l||f)&&(this.tickMarkLength[h+2]=this.getTickMarkLength(r)),this.gridLineEnable[h]=r.showgrid,this.gridLineColor[h]=i(r.gridcolor),this.gridLineWidth[h]=r.gridwidth,this.zeroLineEnable[h]=r.zeroline,this.zeroLineColor[h]=i(r.zerolinecolor),this.zeroLineWidth[h]=r.zerolinewidth}},o.hasSharedAxis=function(t){var e=this.scene,r=e.fullLayout._subplots.gl2d;return 0!==n.findSubplotsWithAxis(r,t).indexOf(e.id)},o.hasAxisInDfltPos=function(t,e){var r=e.side;return\"xaxis\"===t?\"bottom\"===r:\"yaxis\"===t?\"left\"===r:void 0},o.hasAxisInAltrPos=function(t,e){var r=e.side;return\"xaxis\"===t?\"top\"===r:\"yaxis\"===t?\"right\"===r:void 0},o.getLabelPad=function(t,e){var r=e.title.font.size,n=e.showticklabels;return\"xaxis\"===t?\"top\"===e.side?r*(1.5+(n?1:0))-10:r*(1.5+(n?.5:0))-10:\"yaxis\"===t?\"right\"===e.side?10+r*(1.5+(n?1:.5)):10+r*(1.5+(n?.5:0)):void 0},o.getTickPad=function(t){return\"outside\"===t.ticks?10+t.ticklen:15},o.getTickMarkLength=function(t){if(!t.ticks)return 0;var e=t.ticklen;return\"inside\"===t.ticks?-e:e},e.exports=function(t){return new a(t)}},{\"../../lib/str2rgbarray\":828,\"../cartesian/axes\":854}],894:[function(t,e,r){\"use strict\";var n=t(\"../../plot_api/edit_types\").overrideAll,i=t(\"./scene2d\"),a=t(\"../layout_attributes\"),o=t(\"../../constants/xmlns_namespaces\"),s=t(\"../cartesian/constants\"),l=t(\"../cartesian\"),c=t(\"../../components/fx/layout_attributes\"),u=t(\"../get_data\").getSubplotData;r.name=\"gl2d\",r.attr=[\"xaxis\",\"yaxis\"],r.idRoot=[\"x\",\"y\"],r.idRegex=s.idRegex,r.attrRegex=s.attrRegex,r.attributes=t(\"../cartesian/attributes\"),r.supplyLayoutDefaults=function(t,e,r){e._has(\"cartesian\")||l.supplyLayoutDefaults(t,e,r)},r.layoutAttrOverrides=n(l.layoutAttributes,\"plot\",\"from-root\"),r.baseLayoutAttrOverrides=n({plot_bgcolor:a.plot_bgcolor,hoverlabel:c.hoverlabel},\"plot\",\"nested\"),r.plot=function(t){for(var e=t._fullLayout,r=t._fullData,n=e._subplots.gl2d,a=0;a<n.length;a++){var o=n[a],s=e._plots[o],l=u(r,\"gl2d\",o),c=s._scene2d;void 0===c&&(c=new i({id:o,graphDiv:t,container:t.querySelector(\".gl-container\"),staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio},e),s._scene2d=c),c.plot(l,t.calcdata,e,t.layout)}},r.clean=function(t,e,r,n){for(var i=n._subplots.gl2d||[],a=0;a<i.length;a++){var o=i[a],s=n._plots[o];if(s._scene2d){var c=u(t,\"gl2d\",o);0===c.length&&(s._scene2d.destroy(),delete n._plots[o])}}l.clean.apply(this,arguments)},r.drawFramework=function(t){t._context.staticPlot||l.drawFramework(t)},r.toSVG=function(t){for(var e=t._fullLayout,r=e._subplots.gl2d,n=0;n<r.length;n++){var i=e._plots[r[n]]._scene2d,a=i.toImage(\"png\");e._glimages.append(\"svg:image\").attr({xmlns:o.svg,\"xlink:href\":a,x:0,y:0,width:\"100%\",height:\"100%\",preserveAspectRatio:\"none\"}),i.destroy()}},r.updateFx=function(t){for(var e=t._fullLayout,r=e._subplots.gl2d,n=0;n<r.length;n++){e._plots[r[n]]._scene2d.updateFx(e.dragmode)}}},{\"../../components/fx/layout_attributes\":707,\"../../constants/xmlns_namespaces\":780,\"../../plot_api/edit_types\":836,\"../cartesian\":868,\"../cartesian/attributes\":852,\"../cartesian/constants\":861,\"../get_data\":891,\"../layout_attributes\":908,\"./scene2d\":895}],895:[function(t,e,r){\"use strict\";var n,i,a=t(\"../../registry\"),o=t(\"../../plots/cartesian/axes\"),s=t(\"../../components/fx\"),l=t(\"gl-plot2d\"),c=t(\"gl-spikes2d\"),u=t(\"gl-select-box\"),f=t(\"webgl-context\"),h=t(\"./convert\"),p=t(\"./camera\"),d=t(\"../../lib/show_no_webgl_msg\"),g=t(\"../cartesian/constraints\"),m=g.enforce,v=g.clean,y=t(\"../cartesian/autorange\").doAutoRange,x=t(\"../../components/dragelement/helpers\"),b=x.drawMode,_=x.selectMode,w=[\"xaxis\",\"yaxis\"],T=t(\"../cartesian/constants\").SUBPLOT_PATTERN;function k(t,e){this.container=t.container,this.graphDiv=t.graphDiv,this.pixelRatio=t.plotGlPixelRatio||window.devicePixelRatio,this.id=t.id,this.staticPlot=!!t.staticPlot,this.scrollZoom=this.graphDiv._context._scrollZoom.cartesian,this.fullData=null,this.updateRefs(e),this.makeFramework(),this.stopped||(this.glplotOptions=h(this),this.glplotOptions.merge(e),this.glplot=l(this.glplotOptions),this.camera=p(this),this.traces={},this.spikes=c(this.glplot),this.selectBox=u(this.glplot,{innerFill:!1,outerFill:!0}),this.lastButtonState=0,this.pickResult=null,this.isMouseOver=!0,this.stopped=!1,this.redraw=this.draw.bind(this),this.redraw())}e.exports=k;var A=k.prototype;A.makeFramework=function(){if(this.staticPlot){if(!(i||(n=document.createElement(\"canvas\"),i=f({canvas:n,preserveDrawingBuffer:!1,premultipliedAlpha:!0,antialias:!0}))))throw new Error(\"Error creating static canvas/context for image server\");this.canvas=n,this.gl=i}else{var t=this.container.querySelector(\".gl-canvas-focus\"),e=f({canvas:t,preserveDrawingBuffer:!0,premultipliedAlpha:!0});if(!e)return d(this),void(this.stopped=!0);this.canvas=t,this.gl=e}var r=this.canvas;r.style.width=\"100%\",r.style.height=\"100%\",r.style.position=\"absolute\",r.style.top=\"0px\",r.style.left=\"0px\",r.style[\"pointer-events\"]=\"none\",this.updateSize(r);var a=this.svgContainer=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");a.style.position=\"absolute\",a.style.top=a.style.left=\"0px\",a.style.width=a.style.height=\"100%\",a.style[\"z-index\"]=20,a.style[\"pointer-events\"]=\"none\";var o=this.mouseContainer=document.createElement(\"div\");o.style.position=\"absolute\",o.style[\"pointer-events\"]=\"auto\",this.pickCanvas=this.container.querySelector(\".gl-canvas-pick\");var s=this.container;s.appendChild(a),s.appendChild(o);var l=this;o.addEventListener(\"mouseout\",(function(){l.isMouseOver=!1,l.unhover()})),o.addEventListener(\"mouseover\",(function(){l.isMouseOver=!0}))},A.toImage=function(t){t||(t=\"png\"),this.stopped=!0,this.staticPlot&&this.container.appendChild(n),this.updateSize(this.canvas);var e=this.glplot.gl,r=e.drawingBufferWidth,i=e.drawingBufferHeight;e.clearColor(1,1,1,0),e.clear(e.COLOR_BUFFER_BIT|e.DEPTH_BUFFER_BIT),this.glplot.setDirty(),this.glplot.draw(),e.bindFramebuffer(e.FRAMEBUFFER,null);var a=new Uint8Array(r*i*4);e.readPixels(0,0,r,i,e.RGBA,e.UNSIGNED_BYTE,a);for(var o=0,s=i-1;o<s;++o,--s)for(var l=0;l<r;++l)for(var c=0;c<4;++c){var u=a[4*(r*o+l)+c];a[4*(r*o+l)+c]=a[4*(r*s+l)+c],a[4*(r*s+l)+c]=u}var f=document.createElement(\"canvas\");f.width=r,f.height=i;var h,p=f.getContext(\"2d\"),d=p.createImageData(r,i);switch(d.data.set(a),p.putImageData(d,0,0),t){case\"jpeg\":h=f.toDataURL(\"image/jpeg\");break;case\"webp\":h=f.toDataURL(\"image/webp\");break;default:h=f.toDataURL(\"image/png\")}return this.staticPlot&&this.container.removeChild(n),h},A.updateSize=function(t){t||(t=this.canvas);var e=this.pixelRatio,r=this.fullLayout,n=r.width,i=r.height,a=0|Math.ceil(e*n),o=0|Math.ceil(e*i);return t.width===a&&t.height===o||(t.width=a,t.height=o),t},A.computeTickMarks=function(){this.xaxis.setScale(),this.yaxis.setScale();for(var t=[o.calcTicks(this.xaxis),o.calcTicks(this.yaxis)],e=0;e<2;++e)for(var r=0;r<t[e].length;++r)t[e][r].text=t[e][r].text+\"\";return t},A.updateRefs=function(t){this.fullLayout=t;var e=this.id.match(T),r=\"xaxis\"+e[1],n=\"yaxis\"+e[2];this.xaxis=this.fullLayout[r],this.yaxis=this.fullLayout[n]},A.relayoutCallback=function(){var t=this.graphDiv,e=this.xaxis,r=this.yaxis,n=t.layout,i={},o=i[e._name+\".range\"]=e.range.slice(),s=i[r._name+\".range\"]=r.range.slice();i[e._name+\".autorange\"]=e.autorange,i[r._name+\".autorange\"]=r.autorange,a.call(\"_storeDirectGUIEdit\",t.layout,t._fullLayout._preGUI,i);var l=n[e._name];l.range=o,l.autorange=e.autorange;var c=n[r._name];c.range=s,c.autorange=r.autorange,i.lastInputTime=this.camera.lastInputTime,t.emit(\"plotly_relayout\",i)},A.cameraChanged=function(){var t=this.camera;this.glplot.setDataBox(this.calcDataBox());var e=this.computeTickMarks();(function(t,e){for(var r=0;r<2;++r){var n=t[r],i=e[r];if(n.length!==i.length)return!0;for(var a=0;a<n.length;++a)if(n[a].x!==i[a].x)return!0}return!1})(e,this.glplotOptions.ticks)&&(this.glplotOptions.ticks=e,this.glplotOptions.dataBox=t.dataBox,this.glplot.update(this.glplotOptions),this.handleAnnotations())},A.handleAnnotations=function(){for(var t=this.graphDiv,e=this.fullLayout.annotations,r=0;r<e.length;r++){var n=e[r];n.xref===this.xaxis._id&&n.yref===this.yaxis._id&&a.getComponentMethod(\"annotations\",\"drawOne\")(t,r)}},A.destroy=function(){if(this.glplot){var t=this.traces;t&&Object.keys(t).map((function(e){t[e].dispose(),delete t[e]})),this.glplot.dispose(),this.container.removeChild(this.svgContainer),this.container.removeChild(this.mouseContainer),this.fullData=null,this.glplot=null,this.stopped=!0,this.camera.mouseListener.enabled=!1,this.mouseContainer.removeEventListener(\"wheel\",this.camera.wheelListener),this.camera=null}},A.plot=function(t,e,r){var n=this.glplot;this.updateRefs(r),this.xaxis.clearCalc(),this.yaxis.clearCalc(),this.updateTraces(t,e),this.updateFx(r.dragmode);var i=r.width,a=r.height;this.updateSize(this.canvas);var o=this.glplotOptions;o.merge(r),o.screenBox=[0,0,i,a];var s={_fullLayout:{_axisConstraintGroups:r._axisConstraintGroups,xaxis:this.xaxis,yaxis:this.yaxis,_size:r._size}};v(s,this.xaxis),v(s,this.yaxis);var l,c,u=r._size,f=this.xaxis.domain,h=this.yaxis.domain;for(o.viewBox=[u.l+f[0]*u.w,u.b+h[0]*u.h,i-u.r-(1-f[1])*u.w,a-u.t-(1-h[1])*u.h],this.mouseContainer.style.width=u.w*(f[1]-f[0])+\"px\",this.mouseContainer.style.height=u.h*(h[1]-h[0])+\"px\",this.mouseContainer.height=u.h*(h[1]-h[0]),this.mouseContainer.style.left=u.l+f[0]*u.w+\"px\",this.mouseContainer.style.top=u.t+(1-h[1])*u.h+\"px\",c=0;c<2;++c)(l=this[w[c]])._length=o.viewBox[c+2]-o.viewBox[c],y(this.graphDiv,l),l.setScale();m(s),o.ticks=this.computeTickMarks(),o.dataBox=this.calcDataBox(),o.merge(r),n.update(o),this.glplot.draw()},A.calcDataBox=function(){var t=this.xaxis,e=this.yaxis,r=t.range,n=e.range,i=t.r2l,a=e.r2l;return[i(r[0]),a(n[0]),i(r[1]),a(n[1])]},A.setRanges=function(t){var e=this.xaxis,r=this.yaxis,n=e.l2r,i=r.l2r;e.range=[n(t[0]),n(t[2])],r.range=[i(t[1]),i(t[3])]},A.updateTraces=function(t,e){var r,n,i,a=Object.keys(this.traces);this.fullData=t;t:for(r=0;r<a.length;r++){var o=a[r],s=this.traces[o];for(n=0;n<t.length;n++)if((i=t[n]).uid===o&&i.type===s.type)continue t;s.dispose(),delete this.traces[o]}for(r=0;r<t.length;r++){i=t[r];var l=e[r],c=this.traces[i.uid];c?c.update(i,l):(c=i._module.plot(this,i,l),this.traces[i.uid]=c)}this.glplot.objects.sort((function(t,e){return t._trace.index-e._trace.index}))},A.updateFx=function(t){_(t)||b(t)?(this.pickCanvas.style[\"pointer-events\"]=\"none\",this.mouseContainer.style[\"pointer-events\"]=\"none\"):(this.pickCanvas.style[\"pointer-events\"]=\"auto\",this.mouseContainer.style[\"pointer-events\"]=\"auto\"),this.mouseContainer.style.cursor=\"pan\"===t?\"move\":\"zoom\"===t?\"crosshair\":null},A.emitPointAction=function(t,e){for(var r,n=t.trace.uid,i=t.pointIndex,a=0;a<this.fullData.length;a++)this.fullData[a].uid===n&&(r=this.fullData[a]);var o={x:t.traceCoord[0],y:t.traceCoord[1],curveNumber:r.index,pointNumber:i,data:r._input,fullData:this.fullData,xaxis:this.xaxis,yaxis:this.yaxis};s.appendArrayPointValue(o,r,i),this.graphDiv.emit(e,{points:[o]})},A.draw=function(){if(!this.stopped){requestAnimationFrame(this.redraw);var t=this.glplot,e=this.camera,r=e.mouseListener,n=1===this.lastButtonState&&0===r.buttons,i=this.fullLayout;this.lastButtonState=r.buttons,this.cameraChanged();var a,o=r.x*t.pixelRatio,l=this.canvas.height-t.pixelRatio*r.y;if(e.boxEnabled&&\"zoom\"===i.dragmode){this.selectBox.enabled=!0;for(var c=this.selectBox.selectBox=[Math.min(e.boxStart[0],e.boxEnd[0]),Math.min(e.boxStart[1],e.boxEnd[1]),Math.max(e.boxStart[0],e.boxEnd[0]),Math.max(e.boxStart[1],e.boxEnd[1])],u=0;u<2;u++)e.boxStart[u]===e.boxEnd[u]&&(c[u]=t.dataBox[u],c[u+2]=t.dataBox[u+2]);t.setDirty()}else if(!e.panning&&this.isMouseOver){this.selectBox.enabled=!1;var f=i._size,h=this.xaxis.domain,p=this.yaxis.domain,d=(a=t.pick(o/t.pixelRatio+f.l+h[0]*f.w,l/t.pixelRatio-(f.t+(1-p[1])*f.h)))&&a.object._trace.handlePick(a);if(d&&n&&this.emitPointAction(d,\"plotly_click\"),a&&\"skip\"!==a.object._trace.hoverinfo&&i.hovermode&&d&&(!this.lastPickResult||this.lastPickResult.traceUid!==d.trace.uid||this.lastPickResult.dataCoord[0]!==d.dataCoord[0]||this.lastPickResult.dataCoord[1]!==d.dataCoord[1])){var g=d;this.lastPickResult={traceUid:d.trace?d.trace.uid:null,dataCoord:d.dataCoord.slice()},this.spikes.update({center:a.dataCoord}),g.screenCoord=[((t.viewBox[2]-t.viewBox[0])*(a.dataCoord[0]-t.dataBox[0])/(t.dataBox[2]-t.dataBox[0])+t.viewBox[0])/t.pixelRatio,(this.canvas.height-(t.viewBox[3]-t.viewBox[1])*(a.dataCoord[1]-t.dataBox[1])/(t.dataBox[3]-t.dataBox[1])-t.viewBox[1])/t.pixelRatio],this.emitPointAction(d,\"plotly_hover\");var m=this.fullData[g.trace.index]||{},v=g.pointIndex,y=s.castHoverinfo(m,i,v);if(y&&\"all\"!==y){var x=y.split(\"+\");-1===x.indexOf(\"x\")&&(g.traceCoord[0]=void 0),-1===x.indexOf(\"y\")&&(g.traceCoord[1]=void 0),-1===x.indexOf(\"z\")&&(g.traceCoord[2]=void 0),-1===x.indexOf(\"text\")&&(g.textLabel=void 0),-1===x.indexOf(\"name\")&&(g.name=void 0)}s.loneHover({x:g.screenCoord[0],y:g.screenCoord[1],xLabel:this.hoverFormatter(\"xaxis\",g.traceCoord[0]),yLabel:this.hoverFormatter(\"yaxis\",g.traceCoord[1]),zLabel:g.traceCoord[2],text:g.textLabel,name:g.name,color:s.castHoverOption(m,v,\"bgcolor\")||g.color,borderColor:s.castHoverOption(m,v,\"bordercolor\"),fontFamily:s.castHoverOption(m,v,\"font.family\"),fontSize:s.castHoverOption(m,v,\"font.size\"),fontColor:s.castHoverOption(m,v,\"font.color\"),nameLength:s.castHoverOption(m,v,\"namelength\"),textAlign:s.castHoverOption(m,v,\"align\")},{container:this.svgContainer,gd:this.graphDiv})}}a||this.unhover(),t.draw()}},A.unhover=function(){this.lastPickResult&&(this.spikes.update({}),this.lastPickResult=null,this.graphDiv.emit(\"plotly_unhover\"),s.loneUnhover(this.svgContainer))},A.hoverFormatter=function(t,e){if(void 0!==e){var r=this[t];return o.tickText(r,r.c2l(e),\"hover\").text}}},{\"../../components/dragelement/helpers\":684,\"../../components/fx\":706,\"../../lib/show_no_webgl_msg\":825,\"../../plots/cartesian/axes\":854,\"../../registry\":931,\"../cartesian/autorange\":853,\"../cartesian/constants\":861,\"../cartesian/constraints\":862,\"./camera\":892,\"./convert\":893,\"gl-plot2d\":322,\"gl-select-box\":337,\"gl-spikes2d\":346,\"webgl-context\":629}],896:[function(t,e,r){\"use strict\";var n=t(\"../../plot_api/edit_types\").overrideAll,i=t(\"../../components/fx/layout_attributes\"),a=t(\"./scene\"),o=t(\"../get_data\").getSubplotData,s=t(\"../../lib\"),l=t(\"../../constants/xmlns_namespaces\");r.name=\"gl3d\",r.attr=\"scene\",r.idRoot=\"scene\",r.idRegex=r.attrRegex=s.counterRegex(\"scene\"),r.attributes=t(\"./layout/attributes\"),r.layoutAttributes=t(\"./layout/layout_attributes\"),r.baseLayoutAttrOverrides=n({hoverlabel:i.hoverlabel},\"plot\",\"nested\"),r.supplyLayoutDefaults=t(\"./layout/defaults\"),r.plot=function(t){for(var e=t._fullLayout,r=t._fullData,n=e._subplots.gl3d,i=0;i<n.length;i++){var s=n[i],l=o(r,\"gl3d\",s),c=e[s],u=c.camera,f=c._scene;f||(f=new a({id:s,graphDiv:t,container:t.querySelector(\".gl-container\"),staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio,camera:u},e),c._scene=f),f.viewInitial||(f.viewInitial={up:{x:u.up.x,y:u.up.y,z:u.up.z},eye:{x:u.eye.x,y:u.eye.y,z:u.eye.z},center:{x:u.center.x,y:u.center.y,z:u.center.z}}),f.plot(l,e,t.layout)}},r.clean=function(t,e,r,n){for(var i=n._subplots.gl3d||[],a=0;a<i.length;a++){var o=i[a];!e[o]&&n[o]._scene&&(n[o]._scene.destroy(),n._infolayer&&n._infolayer.selectAll(\".annotation-\"+o).remove())}},r.toSVG=function(t){for(var e=t._fullLayout,r=e._subplots.gl3d,n=e._size,i=0;i<r.length;i++){var a=e[r[i]],o=a.domain,s=a._scene,c=s.toImage(\"png\");e._glimages.append(\"svg:image\").attr({xmlns:l.svg,\"xlink:href\":c,x:n.l+n.w*o.x[0],y:n.t+n.h*(1-o.y[1]),width:n.w*(o.x[1]-o.x[0]),height:n.h*(o.y[1]-o.y[0]),preserveAspectRatio:\"none\"}),s.destroy()}},r.cleanId=function(t){if(t.match(/^scene[0-9]*$/)){var e=t.substr(5);return\"1\"===e&&(e=\"\"),\"scene\"+e}},r.updateFx=function(t){for(var e=t._fullLayout,r=e._subplots.gl3d,n=0;n<r.length;n++){e[r[n]]._scene.updateFx(e.dragmode,e.hovermode)}}},{\"../../components/fx/layout_attributes\":707,\"../../constants/xmlns_namespaces\":780,\"../../lib\":803,\"../../plot_api/edit_types\":836,\"../get_data\":891,\"./layout/attributes\":897,\"./layout/defaults\":901,\"./layout/layout_attributes\":902,\"./scene\":906}],897:[function(t,e,r){\"use strict\";e.exports={scene:{valType:\"subplotid\",dflt:\"scene\",editType:\"calc+clearAxisTypes\"}}},{}],898:[function(t,e,r){\"use strict\";var n=t(\"../../../components/color\"),i=t(\"../../cartesian/layout_attributes\"),a=t(\"../../../lib/extend\").extendFlat,o=t(\"../../../plot_api/edit_types\").overrideAll;e.exports=o({visible:i.visible,showspikes:{valType:\"boolean\",dflt:!0},spikesides:{valType:\"boolean\",dflt:!0},spikethickness:{valType:\"number\",min:0,dflt:2},spikecolor:{valType:\"color\",dflt:n.defaultLine},showbackground:{valType:\"boolean\",dflt:!1},backgroundcolor:{valType:\"color\",dflt:\"rgba(204, 204, 204, 0.5)\"},showaxeslabels:{valType:\"boolean\",dflt:!0},color:i.color,categoryorder:i.categoryorder,categoryarray:i.categoryarray,title:{text:i.title.text,font:i.title.font},type:a({},i.type,{values:[\"-\",\"linear\",\"log\",\"date\",\"category\"]}),autotypenumbers:i.autotypenumbers,autorange:i.autorange,rangemode:i.rangemode,range:a({},i.range,{items:[{valType:\"any\",editType:\"plot\",impliedEdits:{\"^autorange\":!1}},{valType:\"any\",editType:\"plot\",impliedEdits:{\"^autorange\":!1}}],anim:!1}),tickmode:i.tickmode,nticks:i.nticks,tick0:i.tick0,dtick:i.dtick,tickvals:i.tickvals,ticktext:i.ticktext,ticks:i.ticks,mirror:i.mirror,ticklen:i.ticklen,tickwidth:i.tickwidth,tickcolor:i.tickcolor,showticklabels:i.showticklabels,tickfont:i.tickfont,tickangle:i.tickangle,tickprefix:i.tickprefix,showtickprefix:i.showtickprefix,ticksuffix:i.ticksuffix,showticksuffix:i.showticksuffix,showexponent:i.showexponent,exponentformat:i.exponentformat,minexponent:i.minexponent,separatethousands:i.separatethousands,tickformat:i.tickformat,tickformatstops:i.tickformatstops,hoverformat:i.hoverformat,showline:i.showline,linecolor:i.linecolor,linewidth:i.linewidth,showgrid:i.showgrid,gridcolor:a({},i.gridcolor,{dflt:\"rgb(204, 204, 204)\"}),gridwidth:i.gridwidth,zeroline:i.zeroline,zerolinecolor:i.zerolinecolor,zerolinewidth:i.zerolinewidth,_deprecated:{title:i._deprecated.title,titlefont:i._deprecated.titlefont}},\"plot\",\"from-root\")},{\"../../../components/color\":666,\"../../../lib/extend\":793,\"../../../plot_api/edit_types\":836,\"../../cartesian/layout_attributes\":869}],899:[function(t,e,r){\"use strict\";var n=t(\"tinycolor2\").mix,i=t(\"../../../lib\"),a=t(\"../../../plot_api/plot_template\"),o=t(\"./axis_attributes\"),s=t(\"../../cartesian/type_defaults\"),l=t(\"../../cartesian/axis_defaults\"),c=[\"xaxis\",\"yaxis\",\"zaxis\"];e.exports=function(t,e,r){var u,f;function h(t,e){return i.coerce(u,f,o,t,e)}for(var p=0;p<c.length;p++){var d=c[p];u=t[d]||{},(f=a.newContainer(e,d))._id=d[0]+r.scene,f._name=d,s(u,f,h,r),l(u,f,h,{font:r.font,letter:d[0],data:r.data,showGrid:!0,noTickson:!0,noTicklabelmode:!0,noTicklabelposition:!0,noTicklabeloverflow:!0,bgColor:r.bgColor,calendar:r.calendar},r.fullLayout),h(\"gridcolor\",n(f.color,r.bgColor,13600/187).toRgbString()),h(\"title.text\",d[0]),f.setScale=i.noop,h(\"showspikes\")&&(h(\"spikesides\"),h(\"spikethickness\"),h(\"spikecolor\",f.color)),h(\"showaxeslabels\"),h(\"showbackground\")&&h(\"backgroundcolor\")}}},{\"../../../lib\":803,\"../../../plot_api/plot_template\":843,\"../../cartesian/axis_defaults\":856,\"../../cartesian/type_defaults\":880,\"./axis_attributes\":898,tinycolor2:598}],900:[function(t,e,r){\"use strict\";var n=t(\"../../../lib/str2rgbarray\"),i=t(\"../../../lib\"),a=[\"xaxis\",\"yaxis\",\"zaxis\"];function o(){this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.tickEnable=[!0,!0,!0],this.tickFont=[\"sans-serif\",\"sans-serif\",\"sans-serif\"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[18,18,18],this.labels=[\"x\",\"y\",\"z\"],this.labelEnable=[!0,!0,!0],this.labelFont=[\"Open Sans\",\"Open Sans\",\"Open Sans\"],this.labelSize=[20,20,20],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[30,30,30],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[10,10,10],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!0,!0,!0],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._defaultTickPad=this.tickPad.slice(),this._defaultLabelPad=this.labelPad.slice(),this._defaultLineTickLength=this.lineTickLength.slice()}o.prototype.merge=function(t,e){for(var r=0;r<3;++r){var o=e[a[r]];o.visible?(this.labels[r]=t._meta?i.templateString(o.title.text,t._meta):o.title.text,\"font\"in o.title&&(o.title.font.color&&(this.labelColor[r]=n(o.title.font.color)),o.title.font.family&&(this.labelFont[r]=o.title.font.family),o.title.font.size&&(this.labelSize[r]=o.title.font.size)),\"showline\"in o&&(this.lineEnable[r]=o.showline),\"linecolor\"in o&&(this.lineColor[r]=n(o.linecolor)),\"linewidth\"in o&&(this.lineWidth[r]=o.linewidth),\"showgrid\"in o&&(this.gridEnable[r]=o.showgrid),\"gridcolor\"in o&&(this.gridColor[r]=n(o.gridcolor)),\"gridwidth\"in o&&(this.gridWidth[r]=o.gridwidth),\"log\"===o.type?this.zeroEnable[r]=!1:\"zeroline\"in o&&(this.zeroEnable[r]=o.zeroline),\"zerolinecolor\"in o&&(this.zeroLineColor[r]=n(o.zerolinecolor)),\"zerolinewidth\"in o&&(this.zeroLineWidth[r]=o.zerolinewidth),\"ticks\"in o&&o.ticks?this.lineTickEnable[r]=!0:this.lineTickEnable[r]=!1,\"ticklen\"in o&&(this.lineTickLength[r]=this._defaultLineTickLength[r]=o.ticklen),\"tickcolor\"in o&&(this.lineTickColor[r]=n(o.tickcolor)),\"tickwidth\"in o&&(this.lineTickWidth[r]=o.tickwidth),\"tickangle\"in o&&(this.tickAngle[r]=\"auto\"===o.tickangle?-3600:Math.PI*-o.tickangle/180),\"showticklabels\"in o&&(this.tickEnable[r]=o.showticklabels),\"tickfont\"in o&&(o.tickfont.color&&(this.tickColor[r]=n(o.tickfont.color)),o.tickfont.family&&(this.tickFont[r]=o.tickfont.family),o.tickfont.size&&(this.tickSize[r]=o.tickfont.size)),\"mirror\"in o?-1!==[\"ticks\",\"all\",\"allticks\"].indexOf(o.mirror)?(this.lineTickMirror[r]=!0,this.lineMirror[r]=!0):!0===o.mirror?(this.lineTickMirror[r]=!1,this.lineMirror[r]=!0):(this.lineTickMirror[r]=!1,this.lineMirror[r]=!1):this.lineMirror[r]=!1,\"showbackground\"in o&&!1!==o.showbackground?(this.backgroundEnable[r]=!0,this.backgroundColor[r]=n(o.backgroundcolor)):this.backgroundEnable[r]=!1):(this.tickEnable[r]=!1,this.labelEnable[r]=!1,this.lineEnable[r]=!1,this.lineTickEnable[r]=!1,this.gridEnable[r]=!1,this.zeroEnable[r]=!1,this.backgroundEnable[r]=!1)}},e.exports=function(t,e){var r=new o;return r.merge(t,e),r}},{\"../../../lib\":803,\"../../../lib/str2rgbarray\":828}],901:[function(t,e,r){\"use strict\";var n=t(\"../../../lib\"),i=t(\"../../../components/color\"),a=t(\"../../../registry\"),o=t(\"../../subplot_defaults\"),s=t(\"./axis_defaults\"),l=t(\"./layout_attributes\"),c=t(\"../../get_data\").getSubplotData;function u(t,e,r,n){for(var o=r(\"bgcolor\"),l=i.combine(o,n.paper_bgcolor),u=[\"up\",\"center\",\"eye\"],f=0;f<u.length;f++)r(\"camera.\"+u[f]+\".x\"),r(\"camera.\"+u[f]+\".y\"),r(\"camera.\"+u[f]+\".z\");r(\"camera.projection.type\");var h=!!r(\"aspectratio.x\")&&!!r(\"aspectratio.y\")&&!!r(\"aspectratio.z\"),p=r(\"aspectmode\",h?\"manual\":\"auto\");h||(t.aspectratio=e.aspectratio={x:1,y:1,z:1},\"manual\"===p&&(e.aspectmode=\"auto\"),t.aspectmode=e.aspectmode);var d=c(n.fullData,\"gl3d\",n.id);s(t,e,{font:n.font,scene:n.id,data:d,bgColor:l,calendar:n.calendar,autotypenumbersDflt:n.autotypenumbersDflt,fullLayout:n.fullLayout}),a.getComponentMethod(\"annotations3d\",\"handleDefaults\")(t,e,n);var g=n.getDfltFromLayout(\"dragmode\");if(!1!==g&&!g)if(g=\"orbit\",t.camera&&t.camera.up){var m=t.camera.up.x,v=t.camera.up.y,y=t.camera.up.z;0!==y&&(m&&v&&y?y/Math.sqrt(m*m+v*v+y*y)>.999&&(g=\"turntable\"):g=\"turntable\")}else g=\"turntable\";r(\"dragmode\",g),r(\"hovermode\",n.getDfltFromLayout(\"hovermode\"))}e.exports=function(t,e,r){var i=e._basePlotModules.length>1;o(t,e,r,{type:\"gl3d\",attributes:l,handleDefaults:u,fullLayout:e,font:e.font,fullData:r,getDfltFromLayout:function(e){if(!i)return n.validate(t[e],l[e])?t[e]:void 0},autotypenumbersDflt:e.autotypenumbers,paper_bgcolor:e.paper_bgcolor,calendar:e.calendar})}},{\"../../../components/color\":666,\"../../../lib\":803,\"../../../registry\":931,\"../../get_data\":891,\"../../subplot_defaults\":925,\"./axis_defaults\":899,\"./layout_attributes\":902}],902:[function(t,e,r){\"use strict\";var n=t(\"./axis_attributes\"),i=t(\"../../domain\").attributes,a=t(\"../../../lib/extend\").extendFlat,o=t(\"../../../lib\").counterRegex;function s(t,e,r){return{x:{valType:\"number\",dflt:t,editType:\"camera\"},y:{valType:\"number\",dflt:e,editType:\"camera\"},z:{valType:\"number\",dflt:r,editType:\"camera\"},editType:\"camera\"}}e.exports={_arrayAttrRegexps:[o(\"scene\",\".annotations\",!0)],bgcolor:{valType:\"color\",dflt:\"rgba(0,0,0,0)\",editType:\"plot\"},camera:{up:a(s(0,0,1),{}),center:a(s(0,0,0),{}),eye:a(s(1.25,1.25,1.25),{}),projection:{type:{valType:\"enumerated\",values:[\"perspective\",\"orthographic\"],dflt:\"perspective\",editType:\"calc\"},editType:\"calc\"},editType:\"camera\"},domain:i({name:\"scene\",editType:\"plot\"}),aspectmode:{valType:\"enumerated\",values:[\"auto\",\"cube\",\"data\",\"manual\"],dflt:\"auto\",editType:\"plot\",impliedEdits:{\"aspectratio.x\":void 0,\"aspectratio.y\":void 0,\"aspectratio.z\":void 0}},aspectratio:{x:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},y:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},z:{valType:\"number\",min:0,editType:\"plot\",impliedEdits:{\"^aspectmode\":\"manual\"}},editType:\"plot\",impliedEdits:{aspectmode:\"manual\"}},xaxis:n,yaxis:n,zaxis:n,dragmode:{valType:\"enumerated\",values:[\"orbit\",\"turntable\",\"zoom\",\"pan\",!1],editType:\"plot\"},hovermode:{valType:\"enumerated\",values:[\"closest\",!1],dflt:\"closest\",editType:\"modebar\"},uirevision:{valType:\"any\",editType:\"none\"},editType:\"plot\",_deprecated:{cameraposition:{valType:\"info_array\",editType:\"camera\"}}}},{\"../../../lib\":803,\"../../../lib/extend\":793,\"../../domain\":882,\"./axis_attributes\":898}],903:[function(t,e,r){\"use strict\";var n=t(\"../../../lib/str2rgbarray\"),i=[\"xaxis\",\"yaxis\",\"zaxis\"];function a(){this.enabled=[!0,!0,!0],this.colors=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.drawSides=[!0,!0,!0],this.lineWidth=[1,1,1]}a.prototype.merge=function(t){for(var e=0;e<3;++e){var r=t[i[e]];r.visible?(this.enabled[e]=r.showspikes,this.colors[e]=n(r.spikecolor),this.drawSides[e]=r.spikesides,this.lineWidth[e]=r.spikethickness):(this.enabled[e]=!1,this.drawSides[e]=!1)}},e.exports=function(t){var e=new a;return e.merge(t),e}},{\"../../../lib/str2rgbarray\":828}],904:[function(t,e,r){\"use strict\";e.exports=function(t){for(var e=t.axesOptions,r=t.glplot.axesPixels,s=t.fullSceneLayout,l=[[],[],[]],c=0;c<3;++c){var u=s[a[c]];if(u._length=(r[c].hi-r[c].lo)*r[c].pixelsPerDataUnit/t.dataScale[c],Math.abs(u._length)===1/0||isNaN(u._length))l[c]=[];else{u._input_range=u.range.slice(),u.range[0]=r[c].lo/t.dataScale[c],u.range[1]=r[c].hi/t.dataScale[c],u._m=1/(t.dataScale[c]*r[c].pixelsPerDataUnit),u.range[0]===u.range[1]&&(u.range[0]-=1,u.range[1]+=1);var f=u.tickmode;if(\"auto\"===u.tickmode){u.tickmode=\"linear\";var h=u.nticks||i.constrain(u._length/40,4,9);n.autoTicks(u,Math.abs(u.range[1]-u.range[0])/h)}for(var p=n.calcTicks(u,{msUTC:!0}),d=0;d<p.length;++d)p[d].x=p[d].x*t.dataScale[c],\"date\"===u.type&&(p[d].text=p[d].text.replace(/\\<br\\>/g,\" \"));l[c]=p,u.tickmode=f}}e.ticks=l;for(c=0;c<3;++c){o[c]=.5*(t.glplot.bounds[0][c]+t.glplot.bounds[1][c]);for(d=0;d<2;++d)e.bounds[d][c]=t.glplot.bounds[d][c]}t.contourLevels=function(t){for(var e=new Array(3),r=0;r<3;++r){for(var n=t[r],i=new Array(n.length),a=0;a<n.length;++a)i[a]=n[a].x;e[r]=i}return e}(l)};var n=t(\"../../cartesian/axes\"),i=t(\"../../../lib\"),a=[\"xaxis\",\"yaxis\",\"zaxis\"],o=[0,0,0]},{\"../../../lib\":803,\"../../cartesian/axes\":854}],905:[function(t,e,r){\"use strict\";function n(t,e){var r,n,i=[0,0,0,0];for(r=0;r<4;++r)for(n=0;n<4;++n)i[n]+=t[4*r+n]*e[r];return i}e.exports=function(t,e){return n(t.projection,n(t.view,n(t.model,[e[0],e[1],e[2],1])))}},{}],906:[function(t,e,r){\"use strict\";var n,i,a=t(\"gl-plot3d\"),o=a.createCamera,s=a.createScene,l=t(\"webgl-context\"),c=t(\"has-passive-events\"),u=t(\"../../registry\"),f=t(\"../../lib\"),h=f.preserveDrawingBuffer(),p=t(\"../../plots/cartesian/axes\"),d=t(\"../../components/fx\"),g=t(\"../../lib/str2rgbarray\"),m=t(\"../../lib/show_no_webgl_msg\"),v=t(\"./project\"),y=t(\"./layout/convert\"),x=t(\"./layout/spikes\"),b=t(\"./layout/tick_marks\");function _(t,e){var r=document.createElement(\"div\"),n=t.container;this.graphDiv=t.graphDiv;var i=document.createElementNS(\"http://www.w3.org/2000/svg\",\"svg\");i.style.position=\"absolute\",i.style.top=i.style.left=\"0px\",i.style.width=i.style.height=\"100%\",i.style[\"z-index\"]=20,i.style[\"pointer-events\"]=\"none\",r.appendChild(i),this.svgContainer=i,r.id=t.id,r.style.position=\"absolute\",r.style.top=r.style.left=\"0px\",r.style.width=r.style.height=\"100%\",n.appendChild(r),this.fullLayout=e,this.id=t.id||\"scene\",this.fullSceneLayout=e[this.id],this.plotArgs=[[],{},{}],this.axesOptions=y(e,e[this.id]),this.spikeOptions=x(e[this.id]),this.container=r,this.staticMode=!!t.staticPlot,this.pixelRatio=this.pixelRatio||t.plotGlPixelRatio||2,this.dataScale=[1,1,1],this.contourLevels=[[],[],[]],this.convertAnnotations=u.getComponentMethod(\"annotations3d\",\"convert\"),this.drawAnnotations=u.getComponentMethod(\"annotations3d\",\"draw\"),this.initializeGLPlot()}var w=_.prototype;w.prepareOptions=function(){var t={canvas:this.canvas,gl:this.gl,glOptions:{preserveDrawingBuffer:h,premultipliedAlpha:!0,antialias:!0},container:this.container,axes:this.axesOptions,spikes:this.spikeOptions,pickRadius:10,snapToData:!0,autoScale:!0,autoBounds:!1,cameraObject:this.camera,pixelRatio:this.pixelRatio};if(this.staticMode){if(!(i||(n=document.createElement(\"canvas\"),i=l({canvas:n,preserveDrawingBuffer:!0,premultipliedAlpha:!0,antialias:!0}))))throw new Error(\"error creating static canvas/context for image server\");t.gl=i,t.canvas=n}return t};var T=!0;w.tryCreatePlot=function(){var t=this.prepareOptions(),e=!0;try{this.glplot=s(t)}catch(r){if(this.staticMode||!T||h)e=!1;else{f.warn([\"webgl setup failed possibly due to\",\"false preserveDrawingBuffer config.\",\"The mobile/tablet device may not be detected by is-mobile module.\",\"Enabling preserveDrawingBuffer in second attempt to create webgl scene...\"].join(\" \"));try{h=t.glOptions.preserveDrawingBuffer=!0,this.glplot=s(t)}catch(r){h=t.glOptions.preserveDrawingBuffer=!1,e=!1}}}return T=!1,e},w.initializeGLCamera=function(){var t=this.fullSceneLayout.camera,e=\"orthographic\"===t.projection.type;this.camera=o(this.container,{center:[t.center.x,t.center.y,t.center.z],eye:[t.eye.x,t.eye.y,t.eye.z],up:[t.up.x,t.up.y,t.up.z],_ortho:e,zoomMin:.01,zoomMax:100,mode:\"orbit\"})},w.initializeGLPlot=function(){var t=this;if(t.initializeGLCamera(),!t.tryCreatePlot())return m(t);t.traces={},t.make4thDimension();var e=t.graphDiv,r=e.layout,n=function(){var e={};return t.isCameraChanged(r)&&(e[t.id+\".camera\"]=t.getCamera()),t.isAspectChanged(r)&&(e[t.id+\".aspectratio\"]=t.glplot.getAspectratio(),\"manual\"!==r[t.id].aspectmode&&(t.fullSceneLayout.aspectmode=r[t.id].aspectmode=e[t.id+\".aspectmode\"]=\"manual\")),e},i=function(t){if(!1!==t.fullSceneLayout.dragmode){var e=n();t.saveLayout(r),t.graphDiv.emit(\"plotly_relayout\",e)}};return t.glplot.canvas&&(t.glplot.canvas.addEventListener(\"mouseup\",(function(){i(t)})),t.glplot.canvas.addEventListener(\"wheel\",(function(r){if(e._context._scrollZoom.gl3d){if(t.camera._ortho){var n=r.deltaX>r.deltaY?1.1:1/1.1,a=t.glplot.getAspectratio();t.glplot.setAspectratio({x:n*a.x,y:n*a.y,z:n*a.z})}i(t)}}),!!c&&{passive:!1}),t.glplot.canvas.addEventListener(\"mousemove\",(function(){if(!1!==t.fullSceneLayout.dragmode&&0!==t.camera.mouseListener.buttons){var e=n();t.graphDiv.emit(\"plotly_relayouting\",e)}})),t.staticMode||t.glplot.canvas.addEventListener(\"webglcontextlost\",(function(r){e&&e.emit&&e.emit(\"plotly_webglcontextlost\",{event:r,layer:t.id})}),!1)),t.glplot.oncontextloss=function(){t.recoverContext()},t.glplot.onrender=function(){t.render()},!0},w.render=function(){var t,e=this,r=e.graphDiv,n=e.svgContainer,i=e.container.getBoundingClientRect();r._fullLayout._calcInverseTransform(r);var a=r._fullLayout._invScaleX,o=r._fullLayout._invScaleY,s=i.width*a,l=i.height*o;n.setAttributeNS(null,\"viewBox\",\"0 0 \"+s+\" \"+l),n.setAttributeNS(null,\"width\",s),n.setAttributeNS(null,\"height\",l),b(e),e.glplot.axes.update(e.axesOptions);for(var c,u=Object.keys(e.traces),h=null,g=e.glplot.selection,m=0;m<u.length;++m)\"skip\"!==(t=e.traces[u[m]]).data.hoverinfo&&t.handlePick(g)&&(h=t),t.setContourLevels&&t.setContourLevels();function y(t,r,n){var i=e.fullSceneLayout[t+\"axis\"];return\"log\"!==i.type&&(r=i.d2l(r)),p.hoverLabelText(i,r,n)}if(null!==h){var x=v(e.glplot.cameraParams,g.dataCoordinate);t=h.data;var _,w=r._fullData[t.index],T=g.index,k={xLabel:y(\"x\",g.traceCoordinate[0],t.xhoverformat),yLabel:y(\"y\",g.traceCoordinate[1],t.yhoverformat),zLabel:y(\"z\",g.traceCoordinate[2],t.zhoverformat)},A=d.castHoverinfo(w,e.fullLayout,T),M=(A||\"\").split(\"+\"),S=A&&\"all\"===A;w.hovertemplate||S||(-1===M.indexOf(\"x\")&&(k.xLabel=void 0),-1===M.indexOf(\"y\")&&(k.yLabel=void 0),-1===M.indexOf(\"z\")&&(k.zLabel=void 0),-1===M.indexOf(\"text\")&&(g.textLabel=void 0),-1===M.indexOf(\"name\")&&(h.name=void 0));var E=[];\"cone\"===t.type||\"streamtube\"===t.type?(k.uLabel=y(\"x\",g.traceCoordinate[3],t.uhoverformat),(S||-1!==M.indexOf(\"u\"))&&E.push(\"u: \"+k.uLabel),k.vLabel=y(\"y\",g.traceCoordinate[4],t.vhoverformat),(S||-1!==M.indexOf(\"v\"))&&E.push(\"v: \"+k.vLabel),k.wLabel=y(\"z\",g.traceCoordinate[5],t.whoverformat),(S||-1!==M.indexOf(\"w\"))&&E.push(\"w: \"+k.wLabel),k.normLabel=g.traceCoordinate[6].toPrecision(3),(S||-1!==M.indexOf(\"norm\"))&&E.push(\"norm: \"+k.normLabel),\"streamtube\"===t.type&&(k.divergenceLabel=g.traceCoordinate[7].toPrecision(3),(S||-1!==M.indexOf(\"divergence\"))&&E.push(\"divergence: \"+k.divergenceLabel)),g.textLabel&&E.push(g.textLabel),_=E.join(\"<br>\")):\"isosurface\"===t.type||\"volume\"===t.type?(k.valueLabel=p.hoverLabelText(e._mockAxis,e._mockAxis.d2l(g.traceCoordinate[3]),t.valuehoverformat),E.push(\"value: \"+k.valueLabel),g.textLabel&&E.push(g.textLabel),_=E.join(\"<br>\")):_=g.textLabel;var L={x:g.traceCoordinate[0],y:g.traceCoordinate[1],z:g.traceCoordinate[2],data:w._input,fullData:w,curveNumber:w.index,pointNumber:T};d.appendArrayPointValue(L,w,T),t._module.eventData&&(L=w._module.eventData(L,g,w,{},T));var C={points:[L]};if(e.fullSceneLayout.hovermode){var P=[];d.loneHover({trace:w,x:(.5+.5*x[0]/x[3])*s,y:(.5-.5*x[1]/x[3])*l,xLabel:k.xLabel,yLabel:k.yLabel,zLabel:k.zLabel,text:_,name:h.name,color:d.castHoverOption(w,T,\"bgcolor\")||h.color,borderColor:d.castHoverOption(w,T,\"bordercolor\"),fontFamily:d.castHoverOption(w,T,\"font.family\"),fontSize:d.castHoverOption(w,T,\"font.size\"),fontColor:d.castHoverOption(w,T,\"font.color\"),nameLength:d.castHoverOption(w,T,\"namelength\"),textAlign:d.castHoverOption(w,T,\"align\"),hovertemplate:f.castOption(w,T,\"hovertemplate\"),hovertemplateLabels:f.extendFlat({},L,k),eventData:[L]},{container:n,gd:r,inOut_bbox:P}),L.bbox=P[0]}g.buttons&&g.distance<5?r.emit(\"plotly_click\",C):r.emit(\"plotly_hover\",C),c=C}else d.loneUnhover(n),r.emit(\"plotly_unhover\",c);e.drawAnnotations(e)},w.recoverContext=function(){var t=this;t.glplot.dispose();var e=function(){t.glplot.gl.isContextLost()?requestAnimationFrame(e):t.initializeGLPlot()?t.plot.apply(t,t.plotArgs):f.error(\"Catastrophic and unrecoverable WebGL error. Context lost.\")};requestAnimationFrame(e)};var k=[\"xaxis\",\"yaxis\",\"zaxis\"];function A(t,e,r){for(var n=t.fullSceneLayout,i=0;i<3;i++){var a=k[i],o=a.charAt(0),s=n[a],l=e[o],c=e[o+\"calendar\"],u=e[\"_\"+o+\"length\"];if(f.isArrayOrTypedArray(l))for(var h,p=0;p<(u||l.length);p++)if(f.isArrayOrTypedArray(l[p]))for(var d=0;d<l[p].length;++d)h=s.d2l(l[p][d],0,c),!isNaN(h)&&isFinite(h)&&(r[0][i]=Math.min(r[0][i],h),r[1][i]=Math.max(r[1][i],h));else h=s.d2l(l[p],0,c),!isNaN(h)&&isFinite(h)&&(r[0][i]=Math.min(r[0][i],h),r[1][i]=Math.max(r[1][i],h));else r[0][i]=Math.min(r[0][i],0),r[1][i]=Math.max(r[1][i],u-1)}}w.plot=function(t,e,r){if(this.plotArgs=[t,e,r],!this.glplot.contextLost){var n,i,a,o,s,l,c=e[this.id],u=r[this.id];this.fullLayout=e,this.fullSceneLayout=c,this.axesOptions.merge(e,c),this.spikeOptions.merge(c),this.setViewport(c),this.updateFx(c.dragmode,c.hovermode),this.camera.enableWheel=this.graphDiv._context._scrollZoom.gl3d,this.glplot.setClearColor(g(c.bgcolor)),this.setConvert(s),t?Array.isArray(t)||(t=[t]):t=[];var f=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(a=0;a<t.length;++a)!0===(n=t[a]).visible&&0!==n._length&&A(this,n,f);!function(t,e){for(var r=t.fullSceneLayout,n=r.annotations||[],i=0;i<3;i++)for(var a=k[i],o=a.charAt(0),s=r[a],l=0;l<n.length;l++){var c=n[l];if(c.visible){var u=s.r2l(c[o]);!isNaN(u)&&isFinite(u)&&(e[0][i]=Math.min(e[0][i],u),e[1][i]=Math.max(e[1][i],u))}}}(this,f);var h=[1,1,1];for(o=0;o<3;++o)f[1][o]===f[0][o]?h[o]=1:h[o]=1/(f[1][o]-f[0][o]);for(this.dataScale=h,this.convertAnnotations(this),a=0;a<t.length;++a)!0===(n=t[a]).visible&&0!==n._length&&((i=this.traces[n.uid])?i.data.type===n.type?i.update(n):(i.dispose(),i=n._module.plot(this,n),this.traces[n.uid]=i):(i=n._module.plot(this,n),this.traces[n.uid]=i),i.name=n.name);var p=Object.keys(this.traces);t:for(a=0;a<p.length;++a){for(o=0;o<t.length;++o)if(t[o].uid===p[a]&&!0===t[o].visible&&0!==t[o]._length)continue t;(i=this.traces[p[a]]).dispose(),delete this.traces[p[a]]}this.glplot.objects.sort((function(t,e){return t._trace.data.index-e._trace.data.index}));var d,m=[[0,0,0],[0,0,0]],v=[],y={};for(a=0;a<3;++a){if((l=(s=c[k[a]]).type)in y?(y[l].acc*=h[a],y[l].count+=1):y[l]={acc:h[a],count:1},s.autorange){m[0][a]=1/0,m[1][a]=-1/0;var x=this.glplot.objects,b=this.fullSceneLayout.annotations||[],_=s._name.charAt(0);for(o=0;o<x.length;o++){var w=x[o],T=w.bounds,M=w._trace.data._pad||0;\"ErrorBars\"===w.constructor.name&&s._lowerLogErrorBound?m[0][a]=Math.min(m[0][a],s._lowerLogErrorBound):m[0][a]=Math.min(m[0][a],T[0][a]/h[a]-M),m[1][a]=Math.max(m[1][a],T[1][a]/h[a]+M)}for(o=0;o<b.length;o++){var S=b[o];if(S.visible){var E=s.r2l(S[_]);m[0][a]=Math.min(m[0][a],E),m[1][a]=Math.max(m[1][a],E)}}if(\"rangemode\"in s&&\"tozero\"===s.rangemode&&(m[0][a]=Math.min(m[0][a],0),m[1][a]=Math.max(m[1][a],0)),m[0][a]>m[1][a])m[0][a]=-1,m[1][a]=1;else{var L=m[1][a]-m[0][a];m[0][a]-=L/32,m[1][a]+=L/32}if(\"reversed\"===s.autorange){var C=m[0][a];m[0][a]=m[1][a],m[1][a]=C}}else{var P=s.range;m[0][a]=s.r2l(P[0]),m[1][a]=s.r2l(P[1])}m[0][a]===m[1][a]&&(m[0][a]-=1,m[1][a]+=1),v[a]=m[1][a]-m[0][a],this.glplot.setBounds(a,{min:m[0][a]*h[a],max:m[1][a]*h[a]})}var I=c.aspectmode;if(\"cube\"===I)d=[1,1,1];else if(\"manual\"===I){var O=c.aspectratio;d=[O.x,O.y,O.z]}else{if(\"auto\"!==I&&\"data\"!==I)throw new Error(\"scene.js aspectRatio was not one of the enumerated types\");var z=[1,1,1];for(a=0;a<3;++a){var D=y[l=(s=c[k[a]]).type];z[a]=Math.pow(D.acc,1/D.count)/h[a]}d=\"data\"===I||Math.max.apply(null,z)/Math.min.apply(null,z)<=4?z:[1,1,1]}c.aspectratio.x=u.aspectratio.x=d[0],c.aspectratio.y=u.aspectratio.y=d[1],c.aspectratio.z=u.aspectratio.z=d[2],this.glplot.setAspectratio(c.aspectratio),this.viewInitial.aspectratio||(this.viewInitial.aspectratio={x:c.aspectratio.x,y:c.aspectratio.y,z:c.aspectratio.z}),this.viewInitial.aspectmode||(this.viewInitial.aspectmode=c.aspectmode);var R=c.domain||null,F=e._size||null;if(R&&F){var B=this.container.style;B.position=\"absolute\",B.left=F.l+R.x[0]*F.w+\"px\",B.top=F.t+(1-R.y[1])*F.h+\"px\",B.width=F.w*(R.x[1]-R.x[0])+\"px\",B.height=F.h*(R.y[1]-R.y[0])+\"px\"}this.glplot.redraw()}},w.destroy=function(){this.glplot&&(this.camera.mouseListener.enabled=!1,this.container.removeEventListener(\"wheel\",this.camera.wheelListener),this.camera=null,this.glplot.dispose(),this.container.parentNode.removeChild(this.container),this.glplot=null)},w.getCamera=function(){var t;return this.camera.view.recalcMatrix(this.camera.view.lastT()),{up:{x:(t=this.camera).up[0],y:t.up[1],z:t.up[2]},center:{x:t.center[0],y:t.center[1],z:t.center[2]},eye:{x:t.eye[0],y:t.eye[1],z:t.eye[2]},projection:{type:!0===t._ortho?\"orthographic\":\"perspective\"}}},w.setViewport=function(t){var e,r=t.camera;this.camera.lookAt.apply(this,[[(e=r).eye.x,e.eye.y,e.eye.z],[e.center.x,e.center.y,e.center.z],[e.up.x,e.up.y,e.up.z]]),this.glplot.setAspectratio(t.aspectratio),\"orthographic\"===r.projection.type!==this.camera._ortho&&(this.glplot.redraw(),this.glplot.clearRGBA(),this.glplot.dispose(),this.initializeGLPlot())},w.isCameraChanged=function(t){var e=this.getCamera(),r=f.nestedProperty(t,this.id+\".camera\").get();function n(t,e,r,n){var i=[\"up\",\"center\",\"eye\"],a=[\"x\",\"y\",\"z\"];return e[i[r]]&&t[i[r]][a[n]]===e[i[r]][a[n]]}var i=!1;if(void 0===r)i=!0;else{for(var a=0;a<3;a++)for(var o=0;o<3;o++)if(!n(e,r,a,o)){i=!0;break}(!r.projection||e.projection&&e.projection.type!==r.projection.type)&&(i=!0)}return i},w.isAspectChanged=function(t){var e=this.glplot.getAspectratio(),r=f.nestedProperty(t,this.id+\".aspectratio\").get();return void 0===r||r.x!==e.x||r.y!==e.y||r.z!==e.z},w.saveLayout=function(t){var e,r,n,i,a,o,s=this.fullLayout,l=this.isCameraChanged(t),c=this.isAspectChanged(t),h=l||c;if(h){var p={};if(l&&(e=this.getCamera(),n=(r=f.nestedProperty(t,this.id+\".camera\")).get(),p[this.id+\".camera\"]=n),c&&(i=this.glplot.getAspectratio(),o=(a=f.nestedProperty(t,this.id+\".aspectratio\")).get(),p[this.id+\".aspectratio\"]=o),u.call(\"_storeDirectGUIEdit\",t,s._preGUI,p),l)r.set(e),f.nestedProperty(s,this.id+\".camera\").set(e);if(c)a.set(i),f.nestedProperty(s,this.id+\".aspectratio\").set(i),this.glplot.redraw()}return h},w.updateFx=function(t,e){var r=this.camera;if(r)if(\"orbit\"===t)r.mode=\"orbit\",r.keyBindingMode=\"rotate\";else if(\"turntable\"===t){r.up=[0,0,1],r.mode=\"turntable\",r.keyBindingMode=\"rotate\";var n=this.graphDiv,i=n._fullLayout,a=this.fullSceneLayout.camera,o=a.up.x,s=a.up.y,l=a.up.z;if(l/Math.sqrt(o*o+s*s+l*l)<.999){var c=this.id+\".camera.up\",h={x:0,y:0,z:1},p={};p[c]=h;var d=n.layout;u.call(\"_storeDirectGUIEdit\",d,i._preGUI,p),a.up=h,f.nestedProperty(d,c).set(h)}}else r.keyBindingMode=t;this.fullSceneLayout.hovermode=e},w.toImage=function(t){t||(t=\"png\"),this.staticMode&&this.container.appendChild(n),this.glplot.redraw();var e=this.glplot.gl,r=e.drawingBufferWidth,i=e.drawingBufferHeight;e.bindFramebuffer(e.FRAMEBUFFER,null);var a=new Uint8Array(r*i*4);e.readPixels(0,0,r,i,e.RGBA,e.UNSIGNED_BYTE,a),function(t,e,r){for(var n=0,i=r-1;n<i;++n,--i)for(var a=0;a<e;++a)for(var o=0;o<4;++o){var s=4*(e*n+a)+o,l=4*(e*i+a)+o,c=t[s];t[s]=t[l],t[l]=c}}(a,r,i),function(t,e,r){for(var n=0;n<r;++n)for(var i=0;i<e;++i){var a=4*(e*n+i),o=t[a+3];if(o>0)for(var s=255/o,l=0;l<3;++l)t[a+l]=Math.min(s*t[a+l],255)}}(a,r,i);var o=document.createElement(\"canvas\");o.width=r,o.height=i;var 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strict\";e.exports=function(t,e,r,n){n=n||t.length;for(var i=new Array(n),a=0;a<n;a++)i[a]=[t[a],e[a],r[a]];return i}},{}],908:[function(t,e,r){\"use strict\";var n=t(\"./font_attributes\"),i=t(\"./animation_attributes\"),a=t(\"../components/color/attributes\"),o=t(\"../components/shapes/draw_newshape/attributes\"),s=t(\"./pad_attributes\"),l=t(\"../lib/extend\").extendFlat,c=n({editType:\"calc\"});c.family.dflt='\"Open Sans\", verdana, arial, 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n=t(\"../../lib/sort_object_keys\"),i='\\xa9 <a target=\"_blank\" href=\"https://www.openstreetmap.org/copyright\">OpenStreetMap</a> contributors',a=['\\xa9 <a target=\"_blank\" href=\"https://carto.com/\">Carto</a>',i].join(\" \"),o=['Map tiles by <a target=\"_blank\" href=\"https://stamen.com\">Stamen Design</a>','under <a target=\"_blank\" href=\"https://creativecommons.org/licenses/by/3.0\">CC BY 3.0</a>',\"|\",'Data by <a target=\"_blank\" href=\"https://openstreetmap.org\">OpenStreetMap</a> contributors','under <a target=\"_blank\" href=\"https://www.openstreetmap.org/copyright\">ODbL</a>'].join(\" 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t&&(-1!==p.styleValuesMapbox.indexOf(t)||0===t.indexOf(\"mapbox://\"))}r.name=\"mapbox\",r.attr=\"subplot\",r.idRoot=\"mapbox\",r.idRegex=r.attrRegex=i.counterRegex(\"mapbox\"),r.attributes={subplot:{valType:\"subplotid\",dflt:\"mapbox\",editType:\"calc\"}},r.layoutAttributes=t(\"./layout_attributes\"),r.supplyLayoutDefaults=t(\"./layout_defaults\"),r.plot=function(t){var e=t._fullLayout,r=t.calcdata,a=e._subplots.mapbox;if(n.version!==p.requiredVersion)throw new Error(p.wrongVersionErrorMsg);var o=function(t,e){var r=t._fullLayout;if(\"\"===t._context.mapboxAccessToken)return\"\";for(var n=[],a=[],o=!1,s=!1,l=0;l<e.length;l++){var c=r[e[l]],u=c.accesstoken;d(c.style)&&(u?i.pushUnique(n,u):(d(c._input.style)&&(i.error(\"Uses Mapbox map style, but did not set an access token.\"),o=!0),s=!0)),u&&i.pushUnique(a,u)}if(s){var f=o?p.noAccessTokenErrorMsg:p.missingStyleErrorMsg;throw i.error(f),new Error(f)}return 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g=c.select(s._subplot.div);if(!(null===g.select(\".mapboxgl-ctrl-logo\").node().offsetParent)){var m=e._glimages.append(\"g\");m.attr(\"transform\",a(n.l+n.w*h.x[0]+10,n.t+n.h*(1-h.y[0])-31)),m.append(\"path\").attr(\"d\",p.mapboxLogo.path0).style({opacity:.9,fill:\"#ffffff\",\"enable-background\":\"new\"}),m.append(\"path\").attr(\"d\",p.mapboxLogo.path1).style(\"opacity\",.35).style(\"enable-background\",\"new\"),m.append(\"path\").attr(\"d\",p.mapboxLogo.path2).style(\"opacity\",.35).style(\"enable-background\",\"new\"),m.append(\"polygon\").attr(\"points\",p.mapboxLogo.polygon).style({opacity:.9,fill:\"#ffffff\",\"enable-background\":\"new\"})}var v=g.select(\".mapboxgl-ctrl-attrib\").text().replace(\"Improve this map\",\"\"),y=e._glimages.append(\"g\"),x=y.append(\"text\");x.text(v).classed(\"static-attribution\",!0).attr({\"font-size\":12,\"font-family\":\"Arial\",color:\"rgba(0, 0, 0, 0.75)\",\"text-anchor\":\"end\",\"data-unformatted\":v});var 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n=t(\"../../lib\"),i=t(\"../../lib/svg_text_utils\").sanitizeHTML,a=t(\"./convert_text_opts\"),o=t(\"./constants\");function s(t,e){this.subplot=t,this.uid=t.uid+\"-\"+e,this.index=e,this.idSource=\"source-\"+this.uid,this.idLayer=o.layoutLayerPrefix+this.uid,this.sourceType=null,this.source=null,this.layerType=null,this.below=null,this.visible=!1}var l=s.prototype;function c(t){if(!t.visible)return!1;var e=t.source;if(Array.isArray(e)&&e.length>0){for(var r=0;r<e.length;r++)if(\"string\"!=typeof e[r]||0===e[r].length)return!1;return!0}return n.isPlainObject(e)||\"string\"==typeof e&&e.length>0}function u(t){var e={},r={};switch(t.type){case\"circle\":n.extendFlat(r,{\"circle-radius\":t.circle.radius,\"circle-color\":t.color,\"circle-opacity\":t.opacity});break;case\"line\":n.extendFlat(r,{\"line-width\":t.line.width,\"line-color\":t.color,\"line-opacity\":t.opacity,\"line-dasharray\":t.line.dash});break;case\"fill\":n.extendFlat(r,{\"fill-color\":t.color,\"fill-outline-color\":t.fill.outlinecolor,\"fill-opacity\":t.opacity});break;case\"symbol\":var i=t.symbol,o=a(i.textposition,i.iconsize);n.extendFlat(e,{\"icon-image\":i.icon+\"-15\",\"icon-size\":i.iconsize/10,\"text-field\":i.text,\"text-size\":i.textfont.size,\"text-anchor\":o.anchor,\"text-offset\":o.offset,\"symbol-placement\":i.placement}),n.extendFlat(r,{\"icon-color\":t.color,\"text-color\":i.textfont.color,\"text-opacity\":t.opacity});break;case\"raster\":n.extendFlat(r,{\"raster-fade-duration\":0,\"raster-opacity\":t.opacity})}return{layout:e,paint:r}}l.update=function(t){this.visible?this.needsNewImage(t)?this.updateImage(t):this.needsNewSource(t)?(this.removeLayer(),this.updateSource(t),this.updateLayer(t)):this.needsNewLayer(t)?this.updateLayer(t):this.updateStyle(t):(this.updateSource(t),this.updateLayer(t)),this.visible=c(t)},l.needsNewImage=function(t){return this.subplot.map.getSource(this.idSource)&&\"image\"===this.sourceType&&\"image\"===t.sourcetype&&(this.source!==t.source||JSON.stringify(this.coordinates)!==JSON.stringify(t.coordinates))},l.needsNewSource=function(t){return this.sourceType!==t.sourcetype||JSON.stringify(this.source)!==JSON.stringify(t.source)||this.layerType!==t.type},l.needsNewLayer=function(t){return this.layerType!==t.type||this.below!==this.subplot.belowLookup[\"layout-\"+this.index]},l.lookupBelow=function(){return this.subplot.belowLookup[\"layout-\"+this.index]},l.updateImage=function(t){this.subplot.map.getSource(this.idSource).updateImage({url:t.source,coordinates:t.coordinates});var e=this.findFollowingMapboxLayerId(this.lookupBelow());null!==e&&this.subplot.map.moveLayer(this.idLayer,e)},l.updateSource=function(t){var e=this.subplot.map;if(e.getSource(this.idSource)&&e.removeSource(this.idSource),this.sourceType=t.sourcetype,this.source=t.source,c(t)){var r=function(t){var e,r=t.sourcetype,n=t.source,a={type:r};\"geojson\"===r?e=\"data\":\"vector\"===r?e=\"string\"==typeof n?\"url\":\"tiles\":\"raster\"===r?(e=\"tiles\",a.tileSize=256):\"image\"===r&&(e=\"url\",a.coordinates=t.coordinates);a[e]=n,t.sourceattribution&&(a.attribution=i(t.sourceattribution));return a}(t);e.addSource(this.idSource,r)}},l.findFollowingMapboxLayerId=function(t){if(\"traces\"===t)for(var e=this.subplot.getMapLayers(),r=0;r<e.length;r++){var n=e[r].id;if(\"string\"==typeof n&&0===n.indexOf(o.traceLayerPrefix)){t=n;break}}return t},l.updateLayer=function(t){var e=this.subplot,r=u(t),n=this.lookupBelow(),i=this.findFollowingMapboxLayerId(n);this.removeLayer(),c(t)&&e.addLayer({id:this.idLayer,source:this.idSource,\"source-layer\":t.sourcelayer||\"\",type:t.type,minzoom:t.minzoom,maxzoom:t.maxzoom,layout:r.layout,paint:r.paint},i),this.layerType=t.type,this.below=n},l.updateStyle=function(t){if(c(t)){var 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strict\";var n=t(\"../../lib\"),i=t(\"../subplot_defaults\"),a=t(\"../array_container_defaults\"),o=t(\"./layout_attributes\");function s(t,e,r,n){r(\"accesstoken\",n.accessToken),r(\"style\"),r(\"center.lon\"),r(\"center.lat\"),r(\"zoom\"),r(\"bearing\"),r(\"pitch\"),a(t,e,{name:\"layers\",handleItemDefaults:l}),e._input=t}function l(t,e){function r(r,i){return n.coerce(t,e,o.layers,r,i)}if(r(\"visible\")){var i,a=r(\"sourcetype\"),s=\"raster\"===a||\"image\"===a;r(\"source\"),r(\"sourceattribution\"),\"vector\"===a&&r(\"sourcelayer\"),\"image\"===a&&r(\"coordinates\"),s&&(i=\"raster\");var l=r(\"type\",i);s&&\"raster\"!==l&&(l=e.type=\"raster\",n.log(\"Source types *raster* and *image* must drawn *raster* layer 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n=t(\"mapbox-gl/dist/mapbox-gl-unminified\"),i=t(\"../../lib\"),a=t(\"../../lib/geo_location_utils\"),o=t(\"../../registry\"),s=t(\"../cartesian/axes\"),l=t(\"../../components/dragelement\"),c=t(\"../../components/fx\"),u=t(\"../../components/dragelement/helpers\"),f=u.rectMode,h=u.drawMode,p=u.selectMode,d=t(\"../cartesian/select\").prepSelect,g=t(\"../cartesian/select\").clearSelect,m=t(\"../cartesian/select\").clearSelectionsCache,v=t(\"../cartesian/select\").selectOnClick,y=t(\"./constants\"),x=t(\"./layers\");function b(t,e){this.id=e,this.gd=t;var r=t._fullLayout,n=t._context;this.container=r._glcontainer.node(),this.isStatic=n.staticPlot,this.uid=r._uid+\"-\"+this.id,this.div=null,this.xaxis=null,this.yaxis=null,this.createFramework(r),this.map=null,this.accessToken=null,this.styleObj=null,this.traceHash={},this.layerList=[],this.belowLookup={},this.dragging=!1,this.wheeling=!1}var _=b.prototype;_.plot=function(t,e,r){var n,i=this,a=e[i.id];i.map&&a.accesstoken!==i.accessToken&&(i.map.remove(),i.map=null,i.styleObj=null,i.traceHash={},i.layerList=[]),n=i.map?new Promise((function(r,n){i.updateMap(t,e,r,n)})):new Promise((function(r,n){i.createMap(t,e,r,n)})),r.push(n)},_.createMap=function(t,e,r,i){var o=this,s=e[o.id],l=o.styleObj=T(s.style);o.accessToken=s.accesstoken;var c=o.map=new n.Map({container:o.div,style:l.style,center:A(s.center),zoom:s.zoom,bearing:s.bearing,pitch:s.pitch,interactive:!o.isStatic,preserveDrawingBuffer:o.isStatic,doubleClickZoom:!1,boxZoom:!1,attributionControl:!1}).addControl(new n.AttributionControl({compact:!0}));c._canvas.style.left=\"0px\",c._canvas.style.top=\"0px\",o.rejectOnError(i),o.isStatic||o.initFx(t,e);var u=[];u.push(new Promise((function(t){c.once(\"load\",t)}))),u=u.concat(a.fetchTraceGeoData(t)),Promise.all(u).then((function(){o.fillBelowLookup(t,e),o.updateData(t),o.updateLayout(e),o.resolveOnRender(r)})).catch(i)},_.updateMap=function(t,e,r,n){var i=this,o=i.map,s=e[this.id];i.rejectOnError(n);var l=[],c=T(s.style);JSON.stringify(i.styleObj)!==JSON.stringify(c)&&(i.styleObj=c,o.setStyle(c.style),i.traceHash={},l.push(new Promise((function(t){o.once(\"styledata\",t)})))),l=l.concat(a.fetchTraceGeoData(t)),Promise.all(l).then((function(){i.fillBelowLookup(t,e),i.updateData(t),i.updateLayout(e),i.resolveOnRender(r)})).catch(n)},_.fillBelowLookup=function(t,e){var r,n,i=e[this.id].layers,a=this.belowLookup={},o=!1;for(r=0;r<t.length;r++){var s=t[r][0].trace,l=s._module;\"string\"==typeof s.below?n=s.below:l.getBelow&&(n=l.getBelow(s,this)),\"\"===n&&(o=!0),a[\"trace-\"+s.uid]=n||\"\"}for(r=0;r<i.length;r++){var c=i[r];n=\"string\"==typeof c.below?c.below:o?\"traces\":\"\",a[\"layout-\"+r]=n}var u,f,h={};for(u in a)h[n=a[u]]?h[n].push(u):h[n]=[u];for(n in h){var p=h[n];if(p.length>1)for(r=0;r<p.length;r++)0===(u=p[r]).indexOf(\"trace-\")?(f=u.split(\"trace-\")[1],this.traceHash[f]&&(this.traceHash[f].below=null)):0===u.indexOf(\"layout-\")&&(f=u.split(\"layout-\")[1],this.layerList[f]&&(this.layerList[f].below=null))}};var w={choroplethmapbox:0,densitymapbox:1,scattermapbox:2};function T(t){var e={};return i.isPlainObject(t)?(e.id=t.id,e.style=t):\"string\"==typeof t?(e.id=t,-1!==y.styleValuesMapbox.indexOf(t)?e.style=k(t):y.stylesNonMapbox[t]?e.style=y.stylesNonMapbox[t]:e.style=t):(e.id=y.styleValueDflt,e.style=k(y.styleValueDflt)),e.transition={duration:0,delay:0},e}function k(t){return y.styleUrlPrefix+t+\"-\"+y.styleUrlSuffix}function A(t){return[t.lon,t.lat]}_.updateData=function(t){var e,r,n,i,a=this.traceHash,o=t.slice().sort((function(t,e){return w[t[0].trace.type]-w[e[0].trace.type]}));for(n=0;n<o.length;n++){var s=o[n],l=!1;(e=a[(r=s[0].trace).uid])&&(e.type===r.type?(e.update(s),l=!0):e.dispose()),!l&&r._module&&(a[r.uid]=r._module.plot(this,s))}var c=Object.keys(a);t:for(n=0;n<c.length;n++){var u=c[n];for(i=0;i<t.length;i++)if(u===(r=t[i][0].trace).uid)continue t;(e=a[u]).dispose(),delete a[u]}},_.updateLayout=function(t){var e=this.map,r=t[this.id];this.dragging||this.wheeling||(e.setCenter(A(r.center)),e.setZoom(r.zoom),e.setBearing(r.bearing),e.setPitch(r.pitch)),this.updateLayers(t),this.updateFramework(t),this.updateFx(t),this.map.resize(),this.gd._context._scrollZoom.mapbox?e.scrollZoom.enable():e.scrollZoom.disable()},_.resolveOnRender=function(t){var e=this.map;e.on(\"render\",(function r(){e.loaded()&&(e.off(\"render\",r),setTimeout(t,10))}))},_.rejectOnError=function(t){var e=this.map;function r(){t(new Error(y.mapOnErrorMsg))}e.once(\"error\",r),e.once(\"style.error\",r),e.once(\"source.error\",r),e.once(\"tile.error\",r),e.once(\"layer.error\",r)},_.createFramework=function(t){var e=this,r=e.div=document.createElement(\"div\");r.id=e.uid,r.style.position=\"absolute\",e.container.appendChild(r),e.xaxis={_id:\"x\",c2p:function(t){return e.project(t).x}},e.yaxis={_id:\"y\",c2p:function(t){return e.project(t).y}},e.updateFramework(t),e.mockAxis={type:\"linear\",showexponent:\"all\",exponentformat:\"B\"},s.setConvert(e.mockAxis,t)},_.initFx=function(t,e){var r=this,n=r.gd,i=r.map;function a(){c.loneUnhover(e._hoverlayer)}function s(){var t=r.getView();n.emit(\"plotly_relayouting\",r.getViewEditsWithDerived(t))}i.on(\"moveend\",(function(t){if(r.map){var e=n._fullLayout;if(t.originalEvent||r.wheeling){var i=e[r.id];o.call(\"_storeDirectGUIEdit\",n.layout,e._preGUI,r.getViewEdits(i));var a=r.getView();i._input.center=i.center=a.center,i._input.zoom=i.zoom=a.zoom,i._input.bearing=i.bearing=a.bearing,i._input.pitch=i.pitch=a.pitch,n.emit(\"plotly_relayout\",r.getViewEditsWithDerived(a))}t.originalEvent&&\"mouseup\"===t.originalEvent.type?r.dragging=!1:r.wheeling&&(r.wheeling=!1),e._rehover&&e._rehover()}})),i.on(\"wheel\",(function(){r.wheeling=!0})),i.on(\"mousemove\",(function(t){var e=r.div.getBoundingClientRect(),a=[t.originalEvent.offsetX,t.originalEvent.offsetY];t.target.getBoundingClientRect=function(){return e},r.xaxis.p2c=function(){return i.unproject(a).lng},r.yaxis.p2c=function(){return 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\"+d,m=o(\"title.text\",g);e._hovertitle=m===g?m:d,a.coerceFont(o,\"title.font\",{family:r.font.family,size:a.bigFont(r.font.size),color:p}),o(\"min\"),c(t,e,o,\"linear\"),s(t,e,o,\"linear\",{}),l(t,e,o,{outerTicks:!0}),o(\"showticklabels\")&&(a.coerceFont(o,\"tickfont\",{family:r.font.family,size:r.font.size,color:p}),o(\"tickangle\"),o(\"tickformat\")),u(t,e,o,{dfltColor:h,bgColor:r.bgColor,blend:60,showLine:!0,showGrid:!0,noZeroLine:!0,attributes:i}),o(\"hoverformat\"),o(\"layer\")}e.exports=function(t,e,r){o(t,e,r,{type:\"ternary\",attributes:f,handleDefaults:p,font:e.font,paper_bgcolor:e.paper_bgcolor})}},{\"../../components/color\":666,\"../../lib\":803,\"../../plot_api/plot_template\":843,\"../cartesian/line_grid_defaults\":871,\"../cartesian/tick_label_defaults\":876,\"../cartesian/tick_mark_defaults\":877,\"../cartesian/tick_value_defaults\":878,\"../subplot_defaults\":925,\"./layout_attributes\":928}],930:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"tinycolor2\"),a=t(\"../../registry\"),o=t(\"../../lib\"),s=o.strTranslate,l=o._,c=t(\"../../components/color\"),u=t(\"../../components/drawing\"),f=t(\"../cartesian/set_convert\"),h=t(\"../../lib/extend\").extendFlat,p=t(\"../plots\"),d=t(\"../cartesian/axes\"),g=t(\"../../components/dragelement\"),m=t(\"../../components/fx\"),v=t(\"../../components/dragelement/helpers\"),y=v.freeMode,x=v.rectMode,b=t(\"../../components/titles\"),_=t(\"../cartesian/select\").prepSelect,w=t(\"../cartesian/select\").selectOnClick,T=t(\"../cartesian/select\").clearSelect,k=t(\"../cartesian/select\").clearSelectionsCache,A=t(\"../cartesian/constants\");function M(t,e){this.id=t.id,this.graphDiv=t.graphDiv,this.init(e),this.makeFramework(e),this.aTickLayout=null,this.bTickLayout=null,this.cTickLayout=null}e.exports=M;var S=M.prototype;S.init=function(t){this.container=t._ternarylayer,this.defs=t._defs,this.layoutId=t._uid,this.traceHash={},this.layers={}},S.plot=function(t,e){var r=e[this.id],n=e._size;this._hasClipOnAxisFalse=!1;for(var i=0;i<t.length;i++){if(!1===t[i][0].trace.cliponaxis){this._hasClipOnAxisFalse=!0;break}}this.updateLayers(r),this.adjustLayout(r,n),p.generalUpdatePerTraceModule(this.graphDiv,this,t,r),this.layers.plotbg.select(\"path\").call(c.fill,r.bgcolor)},S.makeFramework=function(t){var e=this.graphDiv,r=t[this.id],n=this.clipId=\"clip\"+this.layoutId+this.id,i=this.clipIdRelative=\"clip-relative\"+this.layoutId+this.id;this.clipDef=o.ensureSingleById(t._clips,\"clipPath\",n,(function(t){t.append(\"path\").attr(\"d\",\"M0,0Z\")})),this.clipDefRelative=o.ensureSingleById(t._clips,\"clipPath\",i,(function(t){t.append(\"path\").attr(\"d\",\"M0,0Z\")})),this.plotContainer=o.ensureSingle(this.container,\"g\",this.id),this.updateLayers(r),u.setClipUrl(this.layers.backplot,n,e),u.setClipUrl(this.layers.grids,n,e)},S.updateLayers=function(t){var e=this.layers,r=[\"draglayer\",\"plotbg\",\"backplot\",\"grids\"];\"below traces\"===t.aaxis.layer&&r.push(\"aaxis\",\"aline\"),\"below traces\"===t.baxis.layer&&r.push(\"baxis\",\"bline\"),\"below traces\"===t.caxis.layer&&r.push(\"caxis\",\"cline\"),r.push(\"frontplot\"),\"above traces\"===t.aaxis.layer&&r.push(\"aaxis\",\"aline\"),\"above traces\"===t.baxis.layer&&r.push(\"baxis\",\"bline\"),\"above traces\"===t.caxis.layer&&r.push(\"caxis\",\"cline\");var i=this.plotContainer.selectAll(\"g.toplevel\").data(r,String),a=[\"agrid\",\"bgrid\",\"cgrid\"];i.enter().append(\"g\").attr(\"class\",(function(t){return\"toplevel \"+t})).each((function(t){var r=n.select(this);e[t]=r,\"frontplot\"===t?r.append(\"g\").classed(\"scatterlayer\",!0):\"backplot\"===t?r.append(\"g\").classed(\"maplayer\",!0):\"plotbg\"===t?r.append(\"path\").attr(\"d\",\"M0,0Z\"):\"aline\"===t||\"bline\"===t||\"cline\"===t?r.append(\"path\"):\"grids\"===t&&a.forEach((function(t){e[t]=r.append(\"g\").classed(\"grid \"+t,!0)}))})),i.order()};var E=Math.sqrt(4/3);S.adjustLayout=function(t,e){var r,n,i,a,o,l,p=this,d=t.domain,g=(d.x[0]+d.x[1])/2,m=(d.y[0]+d.y[1])/2,v=d.x[1]-d.x[0],y=d.y[1]-d.y[0],x=v*e.w,b=y*e.h,_=t.sum,w=t.aaxis.min,T=t.baxis.min,k=t.caxis.min;x>E*b?i=(a=b)*E:a=(i=x)/E,o=v*i/x,l=y*a/b,r=e.l+e.w*g-i/2,n=e.t+e.h*(1-m)-a/2,p.x0=r,p.y0=n,p.w=i,p.h=a,p.sum=_,p.xaxis={type:\"linear\",range:[w+2*k-_,_-w-2*T],domain:[g-o/2,g+o/2],_id:\"x\"},f(p.xaxis,p.graphDiv._fullLayout),p.xaxis.setScale(),p.xaxis.isPtWithinRange=function(t){return t.a>=p.aaxis.range[0]&&t.a<=p.aaxis.range[1]&&t.b>=p.baxis.range[1]&&t.b<=p.baxis.range[0]&&t.c>=p.caxis.range[1]&&t.c<=p.caxis.range[0]},p.yaxis={type:\"linear\",range:[w,_-T-k],domain:[m-l/2,m+l/2],_id:\"y\"},f(p.yaxis,p.graphDiv._fullLayout),p.yaxis.setScale(),p.yaxis.isPtWithinRange=function(){return!0};var A=p.yaxis.domain[0],M=p.aaxis=h({},t.aaxis,{range:[w,_-T-k],side:\"left\",tickangle:(+t.aaxis.tickangle||0)-30,domain:[A,A+l*E],anchor:\"free\",position:0,_id:\"y\",_length:i});f(M,p.graphDiv._fullLayout),M.setScale();var S=p.baxis=h({},t.baxis,{range:[_-w-k,T],side:\"bottom\",domain:p.xaxis.domain,anchor:\"free\",position:0,_id:\"x\",_length:i});f(S,p.graphDiv._fullLayout),S.setScale();var L=p.caxis=h({},t.caxis,{range:[_-w-T,k],side:\"right\",tickangle:(+t.caxis.tickangle||0)+30,domain:[A,A+l*E],anchor:\"free\",position:0,_id:\"y\",_length:i});f(L,p.graphDiv._fullLayout),L.setScale();var C=\"M\"+r+\",\"+(n+a)+\"h\"+i+\"l-\"+i/2+\",-\"+a+\"Z\";p.clipDef.select(\"path\").attr(\"d\",C),p.layers.plotbg.select(\"path\").attr(\"d\",C);var P=\"M0,\"+a+\"h\"+i+\"l-\"+i/2+\",-\"+a+\"Z\";p.clipDefRelative.select(\"path\").attr(\"d\",P);var I=s(r,n);p.plotContainer.selectAll(\".scatterlayer,.maplayer\").attr(\"transform\",I),p.clipDefRelative.select(\"path\").attr(\"transform\",null);var O=s(r-S._offset,n+a);p.layers.baxis.attr(\"transform\",O),p.layers.bgrid.attr(\"transform\",O);var z=s(r+i/2,n)+\"rotate(30)\"+s(0,-M._offset);p.layers.aaxis.attr(\"transform\",z),p.layers.agrid.attr(\"transform\",z);var D=s(r+i/2,n)+\"rotate(-30)\"+s(0,-L._offset);p.layers.caxis.attr(\"transform\",D),p.layers.cgrid.attr(\"transform\",D),p.drawAxes(!0),p.layers.aline.select(\"path\").attr(\"d\",M.showline?\"M\"+r+\",\"+(n+a)+\"l\"+i/2+\",-\"+a:\"M0,0\").call(c.stroke,M.linecolor||\"#000\").style(\"stroke-width\",(M.linewidth||0)+\"px\"),p.layers.bline.select(\"path\").attr(\"d\",S.showline?\"M\"+r+\",\"+(n+a)+\"h\"+i:\"M0,0\").call(c.stroke,S.linecolor||\"#000\").style(\"stroke-width\",(S.linewidth||0)+\"px\"),p.layers.cline.select(\"path\").attr(\"d\",L.showline?\"M\"+(r+i/2)+\",\"+n+\"l\"+i/2+\",\"+a:\"M0,0\").call(c.stroke,L.linecolor||\"#000\").style(\"stroke-width\",(L.linewidth||0)+\"px\"),p.graphDiv._context.staticPlot||p.initInteractions(),u.setClipUrl(p.layers.frontplot,p._hasClipOnAxisFalse?null:p.clipId,p.graphDiv)},S.drawAxes=function(t){var e=this.graphDiv,r=this.id.substr(7)+\"title\",n=this.layers,i=this.aaxis,a=this.baxis,o=this.caxis;if(this.drawAx(i),this.drawAx(a),this.drawAx(o),t){var s=Math.max(i.showticklabels?i.tickfont.size/2:0,(o.showticklabels?.75*o.tickfont.size:0)+(\"outside\"===o.ticks?.87*o.ticklen:0)),c=(a.showticklabels?a.tickfont.size:0)+(\"outside\"===a.ticks?a.ticklen:0)+3;n[\"a-title\"]=b.draw(e,\"a\"+r,{propContainer:i,propName:this.id+\".aaxis.title\",placeholder:l(e,\"Click to enter Component A title\"),attributes:{x:this.x0+this.w/2,y:this.y0-i.title.font.size/3-s,\"text-anchor\":\"middle\"}}),n[\"b-title\"]=b.draw(e,\"b\"+r,{propContainer:a,propName:this.id+\".baxis.title\",placeholder:l(e,\"Click to enter Component B title\"),attributes:{x:this.x0-c,y:this.y0+this.h+.83*a.title.font.size+c,\"text-anchor\":\"middle\"}}),n[\"c-title\"]=b.draw(e,\"c\"+r,{propContainer:o,propName:this.id+\".caxis.title\",placeholder:l(e,\"Click to enter Component C title\"),attributes:{x:this.x0+this.w+c,y:this.y0+this.h+.83*o.title.font.size+c,\"text-anchor\":\"middle\"}})}},S.drawAx=function(t){var e,r=this.graphDiv,n=t._name,i=n.charAt(0),a=t._id,s=this.layers[n],l=i+\"tickLayout\",c=(e=t).ticks+String(e.ticklen)+String(e.showticklabels);this[l]!==c&&(s.selectAll(\".\"+a+\"tick\").remove(),this[l]=c),t.setScale();var u=d.calcTicks(t),f=d.clipEnds(t,u),h=d.makeTransTickFn(t),p=d.getTickSigns(t)[2],g=o.deg2rad(30),m=p*(t.linewidth||1)/2,v=p*t.ticklen,y=this.w,x=this.h,b=\"b\"===i?\"M0,\"+m+\"l\"+Math.sin(g)*v+\",\"+Math.cos(g)*v:\"M\"+m+\",0l\"+Math.cos(g)*v+\",\"+-Math.sin(g)*v,_={a:\"M0,0l\"+x+\",-\"+y/2,b:\"M0,0l-\"+y/2+\",-\"+x,c:\"M0,0l-\"+x+\",\"+y/2}[i];d.drawTicks(r,t,{vals:\"inside\"===t.ticks?f:u,layer:s,path:b,transFn:h,crisp:!1}),d.drawGrid(r,t,{vals:f,layer:this.layers[i+\"grid\"],path:_,transFn:h,crisp:!1}),d.drawLabels(r,t,{vals:u,layer:s,transFn:h,labelFns:d.makeLabelFns(t,0,30)})};var L=A.MINZOOM/2+.87,C=\"m-0.87,.5h\"+L+\"v3h-\"+(L+5.2)+\"l\"+(L/2+2.6)+\",-\"+(.87*L+4.5)+\"l2.6,1.5l-\"+L/2+\",\"+.87*L+\"Z\",P=\"m0.87,.5h-\"+L+\"v3h\"+(L+5.2)+\"l-\"+(L/2+2.6)+\",-\"+(.87*L+4.5)+\"l-2.6,1.5l\"+L/2+\",\"+.87*L+\"Z\",I=\"m0,1l\"+L/2+\",\"+.87*L+\"l2.6,-1.5l-\"+(L/2+2.6)+\",-\"+(.87*L+4.5)+\"l-\"+(L/2+2.6)+\",\"+(.87*L+4.5)+\"l2.6,1.5l\"+L/2+\",-\"+.87*L+\"Z\",O=!0;function z(t){n.select(t).selectAll(\".zoombox,.js-zoombox-backdrop,.js-zoombox-menu,.zoombox-corners\").remove()}S.clearSelect=function(){k(this.dragOptions),T(this.dragOptions.gd)},S.initInteractions=function(){var t,e,r,n,f,h,p,d,v,b,T,k,M=this,S=M.layers.plotbg.select(\"path\").node(),L=M.graphDiv,D=L._fullLayout._zoomlayer;function R(t){var e={};return e[M.id+\".aaxis.min\"]=t.a,e[M.id+\".baxis.min\"]=t.b,e[M.id+\".caxis.min\"]=t.c,e}function F(t,e){var r=L._fullLayout.clickmode;z(L),2===t&&(L.emit(\"plotly_doubleclick\",null),a.call(\"_guiRelayout\",L,R({a:0,b:0,c:0}))),r.indexOf(\"select\")>-1&&1===t&&w(e,L,[M.xaxis],[M.yaxis],M.id,M.dragOptions),r.indexOf(\"event\")>-1&&m.click(L,e,M.id)}function B(t,e){return 1-e/M.h}function N(t,e){return 1-(t+(M.h-e)/Math.sqrt(3))/M.w}function j(t,e){return(t-(M.h-e)/Math.sqrt(3))/M.w}function U(i,a){var o=r+i*t,s=n+a*e,l=Math.max(0,Math.min(1,B(0,n),B(0,s))),c=Math.max(0,Math.min(1,N(r,n),N(o,s))),u=Math.max(0,Math.min(1,j(r,n),j(o,s))),g=(l/2+u)*M.w,m=(1-l/2-c)*M.w,y=(g+m)/2,x=m-g,_=(1-l)*M.h,w=_-x/E;x<A.MINZOOM?(p=f,T.attr(\"d\",v),k.attr(\"d\",\"M0,0Z\")):(p={a:f.a+l*h,b:f.b+c*h,c:f.c+u*h},T.attr(\"d\",v+\"M\"+g+\",\"+_+\"H\"+m+\"L\"+y+\",\"+w+\"L\"+g+\",\"+_+\"Z\"),k.attr(\"d\",\"M\"+r+\",\"+n+\"m0.5,0.5h5v-2h-5v-5h-2v5h-5v2h5v5h2ZM\"+g+\",\"+_+C+\"M\"+m+\",\"+_+P+\"M\"+y+\",\"+w+I)),b||(T.transition().style(\"fill\",d>.2?\"rgba(0,0,0,0.4)\":\"rgba(255,255,255,0.3)\").duration(200),k.transition().style(\"opacity\",1).duration(200),b=!0),L.emit(\"plotly_relayouting\",R(p))}function V(){z(L),p!==f&&(a.call(\"_guiRelayout\",L,R(p)),O&&L.data&&L._context.showTips&&(o.notifier(l(L,\"Double-click to zoom back out\"),\"long\"),O=!1))}function q(t,e){var r=t/M.xaxis._m,n=e/M.yaxis._m,i=[(p={a:f.a-n,b:f.b+(r+n)/2,c:f.c-(r-n)/2}).a,p.b,p.c].sort(o.sorterAsc),a=i.indexOf(p.a),l=i.indexOf(p.b),c=i.indexOf(p.c);i[0]<0&&(i[1]+i[0]/2<0?(i[2]+=i[0]+i[1],i[0]=i[1]=0):(i[2]+=i[0]/2,i[1]+=i[0]/2,i[0]=0),p={a:i[a],b:i[l],c:i[c]},e=(f.a-p.a)*M.yaxis._m,t=(f.c-p.c-f.b+p.b)*M.xaxis._m);var h=s(M.x0+t,M.y0+e);M.plotContainer.selectAll(\".scatterlayer,.maplayer\").attr(\"transform\",h);var d=s(-t,-e);M.clipDefRelative.select(\"path\").attr(\"transform\",d),M.aaxis.range=[p.a,M.sum-p.b-p.c],M.baxis.range=[M.sum-p.a-p.c,p.b],M.caxis.range=[M.sum-p.a-p.b,p.c],M.drawAxes(!1),M._hasClipOnAxisFalse&&M.plotContainer.select(\".scatterlayer\").selectAll(\".trace\").call(u.hideOutsideRangePoints,M),L.emit(\"plotly_relayouting\",R(p))}function H(){a.call(\"_guiRelayout\",L,R(p))}this.dragOptions={element:S,gd:L,plotinfo:{id:M.id,domain:L._fullLayout[M.id].domain,xaxis:M.xaxis,yaxis:M.yaxis},subplot:M.id,prepFn:function(a,l,u){M.dragOptions.xaxes=[M.xaxis],M.dragOptions.yaxes=[M.yaxis],t=L._fullLayout._invScaleX,e=L._fullLayout._invScaleY;var g=M.dragOptions.dragmode=L._fullLayout.dragmode;y(g)?M.dragOptions.minDrag=1:M.dragOptions.minDrag=void 0,\"zoom\"===g?(M.dragOptions.moveFn=U,M.dragOptions.clickFn=F,M.dragOptions.doneFn=V,function(t,e,a){var l=S.getBoundingClientRect();r=e-l.left,n=a-l.top,L._fullLayout._calcInverseTransform(L);var u=L._fullLayout._invTransform,g=o.apply3DTransform(u)(r,n);r=g[0],n=g[1],f={a:M.aaxis.range[0],b:M.baxis.range[1],c:M.caxis.range[1]},p=f,h=M.aaxis.range[1]-f.a,d=i(M.graphDiv._fullLayout[M.id].bgcolor).getLuminance(),v=\"M0,\"+M.h+\"L\"+M.w/2+\", 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n=t(\"../../components/fx\"),i=t(\"../../lib\"),a=t(\"../bar/hover\").getTraceColor,o=i.fillText,s=t(\"../scatterpolar/hover\").makeHoverPointText,l=t(\"../../plots/polar/helpers\").isPtInsidePolygon;e.exports=function(t,e,r){var c=t.cd,u=c[0].trace,f=t.subplot,h=f.radialAxis,p=f.angularAxis,d=f.vangles,g=d?l:i.isPtInsideSector,m=t.maxHoverDistance,v=p._period||2*Math.PI,y=Math.abs(h.g2p(Math.sqrt(e*e+r*r))),x=Math.atan2(r,e);h.range[0]>h.range[1]&&(x+=Math.PI);if(n.getClosest(c,(function(t){return g(y,x,[t.rp0,t.rp1],[t.thetag0,t.thetag1],d)?m+Math.min(1,Math.abs(t.thetag1-t.thetag0)/v)-1+(t.rp1-y)/(t.rp1-t.rp0)-1:1/0}),t),!1!==t.index){var b=c[t.index];t.x0=t.x1=b.ct[0],t.y0=t.y1=b.ct[1];var _=i.extendFlat({},b,{r:b.s,theta:b.p});return o(b,u,t),s(_,u,f,t),t.hovertemplate=u.hovertemplate,t.color=a(u,b),t.xLabelVal=t.yLabelVal=void 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n=t(\"../scatter/attributes\"),i=t(\"../bar/attributes\"),a=t(\"../../components/color/attributes\"),o=t(\"../../plots/cartesian/axis_format_attributes\").axisHoverFormat,s=t(\"../../plots/template_attributes\").hovertemplateAttrs,l=t(\"../../lib/extend\").extendFlat,c=n.marker,u=c.line;e.exports={y:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},x:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},x0:{valType:\"any\",editType:\"calc+clearAxisTypes\"},y0:{valType:\"any\",editType:\"calc+clearAxisTypes\"},dx:{valType:\"number\",editType:\"calc\"},dy:{valType:\"number\",editType:\"calc\"},xperiod:n.xperiod,yperiod:n.yperiod,xperiod0:n.xperiod0,yperiod0:n.yperiod0,xperiodalignment:n.xperiodalignment,yperiodalignment:n.yperiodalignment,xhoverformat:o(\"x\"),yhoverformat:o(\"y\"),name:{valType:\"string\",editType:\"calc+clearAxisTypes\"},q1:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},median:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},q3:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},lowerfence:{valType:\"data_array\",editType:\"calc\"},upperfence:{valType:\"data_array\",editType:\"calc\"},notched:{valType:\"boolean\",editType:\"calc\"},notchwidth:{valType:\"number\",min:0,max:.5,dflt:.25,editType:\"calc\"},notchspan:{valType:\"data_array\",editType:\"calc\"},boxpoints:{valType:\"enumerated\",values:[\"all\",\"outliers\",\"suspectedoutliers\",!1],editType:\"calc\"},jitter:{valType:\"number\",min:0,max:1,editType:\"calc\"},pointpos:{valType:\"number\",min:-2,max:2,editType:\"calc\"},boxmean:{valType:\"enumerated\",values:[!0,\"sd\",!1],editType:\"calc\"},mean:{valType:\"data_array\",editType:\"calc\"},sd:{valType:\"data_array\",editType:\"calc\"},orientation:{valType:\"enumerated\",values:[\"v\",\"h\"],editType:\"calc+clearAxisTypes\"},quartilemethod:{valType:\"enumerated\",values:[\"linear\",\"exclusive\",\"inclusive\"],dflt:\"linear\",editType:\"calc\"},width:{valType:\"number\",min:0,dflt:0,editType:\"calc\"},marker:{outliercolor:{valType:\"color\",dflt:\"rgba(0, 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f={xaxis:0,yaxis:1,zaxis:2},h={tip:1,tail:0,cm:.25,center:.5},p={tip:1,tail:1,cm:.75,center:.5};function d(t,e){var r=t.fullSceneLayout,i=t.dataScale,c={};function u(t,e){var n=r[e],o=i[f[e]];return a(t,(function(t){return n.d2l(t)*o}))}c.vectors=l(u(e.u,\"xaxis\"),u(e.v,\"yaxis\"),u(e.w,\"zaxis\"),e._len),c.positions=l(u(e.x,\"xaxis\"),u(e.y,\"yaxis\"),u(e.z,\"zaxis\"),e._len);var d=s(e);c.colormap=o(e),c.vertexIntensityBounds=[d.min/e._normMax,d.max/e._normMax],c.coneOffset=h[e.anchor],\"scaled\"===e.sizemode?c.coneSize=e.sizeref||.5:c.coneSize=e.sizeref&&e._normMax?e.sizeref/e._normMax:.5;var g=n(c),m=e.lightposition;return g.lightPosition=[m.x,m.y,m.z],g.ambient=e.lighting.ambient,g.diffuse=e.lighting.diffuse,g.specular=e.lighting.specular,g.roughness=e.lighting.roughness,g.fresnel=e.lighting.fresnel,g.opacity=e.opacity,e._pad=p[e.anchor]*g.vectorScale*g.coneScale*e._normMax,g}u.update=function(t){this.data=t;var 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n=t(\"../heatmap/attributes\"),i=t(\"../scatter/attributes\"),a=t(\"../../plots/cartesian/axis_format_attributes\"),o=a.axisHoverFormat,s=a.descriptionOnlyNumbers,l=t(\"../../components/colorscale/attributes\"),c=t(\"../../components/drawing/attributes\").dash,u=t(\"../../plots/font_attributes\"),f=t(\"../../lib/extend\").extendFlat,h=t(\"../../constants/filter_ops\"),p=h.COMPARISON_OPS2,d=h.INTERVAL_OPS,g=i.line;e.exports=f({z:n.z,x:n.x,x0:n.x0,dx:n.dx,y:n.y,y0:n.y0,dy:n.dy,xperiod:n.xperiod,yperiod:n.yperiod,xperiod0:i.xperiod0,yperiod0:i.yperiod0,xperiodalignment:n.xperiodalignment,yperiodalignment:n.yperiodalignment,text:n.text,hovertext:n.hovertext,transpose:n.transpose,xtype:n.xtype,ytype:n.ytype,xhoverformat:o(\"x\"),yhoverformat:o(\"y\"),zhoverformat:o(\"z\",1),hovertemplate:n.hovertemplate,hoverongaps:n.hoverongaps,connectgaps:f({},n.connectgaps,{}),fillcolor:{valType:\"color\",editType:\"calc\"},autocontour:{valType:\"boolean\",dflt:!0,editType:\"calc\",impliedEdits:{\"contours.start\":void 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r=t.marker,i=e.mc||r.color,a=e.mlc||r.line.color,o=e.mlw||r.line.width;if(n(i))return i;if(n(a)&&o)return a}(u,h),[l]}}},{\"../../components/color\":666,\"../../lib\":803,\"../bar/hover\":948}],1071:[function(t,e,r){\"use 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s=r||n.select(t).selectAll(\"g.funnellayer\").selectAll(\"g.trace\");l(t,s,\"funnel\"),s.style(\"opacity\",(function(t){return t[0].trace.opacity})),s.each((function(e){var r=n.select(this),s=e[0].trace;r.selectAll(\".point > path\").each((function(t){if(!t.isBlank){var e=s.marker;n.select(this).call(a.fill,t.mc||e.color).call(a.stroke,t.mlc||e.line.color).call(i.dashLine,e.line.dash,t.mlw||e.line.width).style(\"opacity\",s.selectedpoints&&!t.selected?o:1)}})),c(r,s,t),r.selectAll(\".regions\").each((function(){n.select(this).selectAll(\"path\").style(\"stroke-width\",0).call(a.fill,s.connector.fillcolor)})),r.selectAll(\".lines\").each((function(){var t=s.connector.line;i.lineGroupStyle(n.select(this).selectAll(\"path\"),t.width,t.color,t.dash)}))}))}}},{\"../../components/color\":666,\"../../components/drawing\":688,\"../../constants/interactions\":778,\"../bar/style\":955,\"../bar/uniform_text\":957,\"@plotly/d3\":58}],1076:[function(t,e,r){\"use strict\";var n=t(\"../pie/attributes\"),i=t(\"../../plots/attributes\"),a=t(\"../../plots/domain\").attributes,o=t(\"../../plots/template_attributes\").hovertemplateAttrs,s=t(\"../../plots/template_attributes\").texttemplateAttrs,l=t(\"../../lib/extend\").extendFlat;e.exports={labels:n.labels,label0:n.label0,dlabel:n.dlabel,values:n.values,marker:{colors:n.marker.colors,line:{color:l({},n.marker.line.color,{dflt:null}),width:l({},n.marker.line.width,{dflt:1}),editType:\"calc\"},editType:\"calc\"},text:n.text,hovertext:n.hovertext,scalegroup:l({},n.scalegroup,{}),textinfo:l({},n.textinfo,{flags:[\"label\",\"text\",\"value\",\"percent\"]}),texttemplate:s({editType:\"plot\"},{keys:[\"label\",\"color\",\"value\",\"text\",\"percent\"]}),hoverinfo:l({},i.hoverinfo,{flags:[\"label\",\"text\",\"value\",\"percent\",\"name\"]}),hovertemplate:o({},{keys:[\"label\",\"color\",\"value\",\"text\",\"percent\"]}),textposition:l({},n.textposition,{values:[\"inside\",\"none\"],dflt:\"inside\"}),textfont:n.textfont,insidetextfont:n.insidetextfont,title:{text:n.title.text,font:n.title.font,position:l({},n.title.position,{values:[\"top 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n=t(\"../../lib\"),i=t(\"./attributes\"),a=t(\"../../plots/domain\").defaults,o=t(\"../bar/defaults\").handleText,s=t(\"../pie/defaults\").handleLabelsAndValues;e.exports=function(t,e,r,l){function c(r,a){return n.coerce(t,e,i,r,a)}var u=c(\"labels\"),f=c(\"values\"),h=s(u,f),p=h.len;if(e._hasLabels=h.hasLabels,e._hasValues=h.hasValues,!e._hasLabels&&e._hasValues&&(c(\"label0\"),c(\"dlabel\")),p){e._length=p,c(\"marker.line.width\")&&c(\"marker.line.color\",l.paper_bgcolor),c(\"marker.colors\"),c(\"scalegroup\");var d,g=c(\"text\"),m=c(\"texttemplate\");if(m||(d=c(\"textinfo\",Array.isArray(g)?\"text+percent\":\"percent\")),c(\"hovertext\"),c(\"hovertemplate\"),m||d&&\"none\"!==d){var v=c(\"textposition\");o(t,e,l,c,v,{moduleHasSelected:!1,moduleHasUnselected:!1,moduleHasConstrain:!1,moduleHasCliponaxis:!1,moduleHasTextangle:!1,moduleHasInsideanchor:!1})}a(e,l,c),c(\"title.text\")&&(c(\"title.position\"),n.coerceFont(c,\"title.font\",l.font)),c(\"aspectratio\"),c(\"baseratio\")}else e.visible=!1}},{\"../../lib\":803,\"../../plots/domain\":882,\"../bar/defaults\":945,\"../pie/defaults\":1195,\"./attributes\":1076}],1080:[function(t,e,r){\"use strict\";e.exports={moduleType:\"trace\",name:\"funnelarea\",basePlotModule:t(\"./base_plot\"),categories:[\"pie-like\",\"funnelarea\",\"showLegend\"],attributes:t(\"./attributes\"),layoutAttributes:t(\"./layout_attributes\"),supplyDefaults:t(\"./defaults\"),supplyLayoutDefaults:t(\"./layout_defaults\"),calc:t(\"./calc\").calc,crossTraceCalc:t(\"./calc\").crossTraceCalc,plot:t(\"./plot\"),style:t(\"./style\"),styleOne:t(\"../pie/style_one\"),meta:{}}},{\"../pie/style_one\":1203,\"./attributes\":1076,\"./base_plot\":1077,\"./calc\":1078,\"./defaults\":1079,\"./layout_attributes\":1081,\"./layout_defaults\":1082,\"./plot\":1083,\"./style\":1084}],1081:[function(t,e,r){\"use strict\";var n=t(\"../pie/layout_attributes\").hiddenlabels;e.exports={hiddenlabels:n,funnelareacolorway:{valType:\"colorlist\",editType:\"calc\"},extendfunnelareacolors:{valType:\"boolean\",dflt:!0,editType:\"calc\"}}},{\"../pie/layout_attributes\":1199}],1082:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"./layout_attributes\");e.exports=function(t,e){function r(r,a){return n.coerce(t,e,i,r,a)}r(\"hiddenlabels\"),r(\"funnelareacolorway\",e.colorway),r(\"extendfunnelareacolors\")}},{\"../../lib\":803,\"./layout_attributes\":1081}],1083:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"../../components/drawing\"),a=t(\"../../lib\"),o=a.strScale,s=a.strTranslate,l=t(\"../../lib/svg_text_utils\"),c=t(\"../bar/plot\").toMoveInsideBar,u=t(\"../bar/uniform_text\"),f=u.recordMinTextSize,h=u.clearMinTextSize,p=t(\"../pie/helpers\"),d=t(\"../pie/plot\"),g=d.attachFxHandlers,m=d.determineInsideTextFont,v=d.layoutAreas,y=d.prerenderTitles,x=d.positionTitleOutside,b=d.formatSliceLabel;function _(t,e){return\"l\"+(e[0]-t[0])+\",\"+(e[1]-t[1])}e.exports=function(t,e){var r=t._fullLayout;h(\"funnelarea\",r),y(e,t),v(e,r._size),a.makeTraceGroups(r._funnelarealayer,e,\"trace\").each((function(e){var u=n.select(this),h=e[0],d=h.trace;!function(t){if(!t.length)return;var e=t[0],r=e.trace,n=r.aspectratio,i=r.baseratio;i>.999&&(i=.999);var a,o=Math.pow(i,2),s=e.vTotal,l=s,c=s*o/(1-o)/s;function u(){var t,e={x:t=Math.sqrt(c),y:-t};return[e.x,e.y]}var f,h,p=[];for(p.push(u()),f=t.length-1;f>-1;f--)if(!(h=t[f]).hidden){var d=h.v/l;c+=d,p.push(u())}var 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w=\"M\"+(u+o.TR[0])+\",\"+(v+o.TR[1])+_(o.TR,o.BR)+_(o.BR,o.BL)+_(o.BL,o.TL)+\"Z\";x.attr(\"d\",w),b(t,o,h);var T=p.castOption(d.textposition,o.pts),k=y.selectAll(\"g.slicetext\").data(o.text&&\"none\"!==T?[0]:[]);k.enter().append(\"g\").classed(\"slicetext\",!0),k.exit().remove(),k.each((function(){var h=a.ensureSingle(n.select(this),\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),p=a.ensureUniformFontSize(t,m(d,o,r.font));h.text(o.text).attr({class:\"slicetext\",transform:\"\",\"text-anchor\":\"middle\"}).call(i.font,p).call(l.convertToTspans,t);var g,y,x,b=i.bBox(h.node()),_=Math.min(o.BL[1],o.BR[1])+v,w=Math.max(o.TL[1],o.TR[1])+v;y=Math.max(o.TL[0],o.BL[0])+u,x=Math.min(o.TR[0],o.BR[0])+u,(g=c(y,x,_,w,b,{isHorizontal:!0,constrained:!0,angle:0,anchor:\"middle\"})).fontSize=p.size,f(d.type,g,r),e[s].transform=g,h.attr(\"transform\",a.getTextTransform(g))}))}}));var 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0===e.delta.font.size&&(e.delta.font.size=(e._hasNumber?.5:1)*(m||l.defaultNumberFontSize),w[1]=!0),d(\"delta.reference\",e.value),d(\"delta.relative\"),d(\"delta.valueformat\",e.delta.relative?\"2%\":\"\"),d(\"delta.increasing.symbol\"),d(\"delta.increasing.color\"),d(\"delta.decreasing.symbol\"),d(\"delta.decreasing.color\"),d(\"delta.position\"),v=e.delta.font.size),e._scaleNumbers=(!e._hasNumber||w[0])&&(!e._hasDelta||w[1])||!1,d(\"title.font.color\",p.font.color),d(\"title.font.family\",p.font.family),d(\"title.font.size\",.25*(m||v||l.defaultNumberFontSize)),d(\"title.text\"),e._hasGauge){(y=t.gauge)||(y={}),x=o.newContainer(e,\"gauge\"),T(\"shape\"),(e._isBullet=\"bullet\"===e.gauge.shape)||d(\"title.align\",\"center\"),(e._isAngular=\"angular\"===e.gauge.shape)||d(\"align\",\"center\"),T(\"bgcolor\",p.paper_bgcolor),T(\"borderwidth\"),T(\"bordercolor\"),T(\"bar.color\"),T(\"bar.line.color\"),T(\"bar.line.width\"),T(\"bar.thickness\",l.valueThickness*(\"bullet\"===e.gauge.shape?.5:1)),s(y,x,{name:\"steps\",handleItemDefaults:h}),T(\"threshold.value\"),T(\"threshold.thickness\"),T(\"threshold.line.width\"),T(\"threshold.line.color\"),b={},y&&(b=y.axis||{}),_=o.newContainer(x,\"axis\"),k(\"visible\"),e._range=k(\"range\",e._range);var A={outerTicks:!0};c(b,_,k,\"linear\"),f(b,_,k,\"linear\",A),u(b,_,k,A)}else d(\"title.align\",\"center\"),d(\"align\",\"center\"),e._isAngular=e._isBullet=!1;e._length=null}}},{\"../../lib\":803,\"../../plot_api/plot_template\":843,\"../../plots/array_container_defaults\":849,\"../../plots/cartesian/tick_label_defaults\":876,\"../../plots/cartesian/tick_mark_defaults\":877,\"../../plots/cartesian/tick_value_defaults\":878,\"../../plots/domain\":882,\"./attributes\":1147,\"./constants.js\":1150}],1152:[function(t,e,r){\"use strict\";e.exports={moduleType:\"trace\",name:\"indicator\",basePlotModule:t(\"./base_plot\"),categories:[\"svg\",\"noOpacity\",\"noHover\"],animatable:!0,attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\").supplyDefaults,calc:t(\"./calc\").calc,plot:t(\"./plot\"),meta:{}}},{\"./attributes\":1147,\"./base_plot\":1148,\"./calc\":1149,\"./defaults\":1151,\"./plot\":1153}],1153:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"d3-interpolate\").interpolate,a=t(\"d3-interpolate\").interpolateNumber,o=t(\"../../lib\"),s=o.strScale,l=o.strTranslate,c=o.rad2deg,u=t(\"../../constants/alignment\").MID_SHIFT,f=t(\"../../components/drawing\"),h=t(\"./constants\"),p=t(\"../../lib/svg_text_utils\"),d=t(\"../../plots/cartesian/axes\"),g=t(\"../../plots/cartesian/axis_defaults\"),m=t(\"../../plots/cartesian/position_defaults\"),v=t(\"../../plots/cartesian/layout_attributes\"),y=t(\"../../components/color\"),x={left:\"start\",center:\"middle\",right:\"end\"},b={left:0,center:.5,right:1},_=/[yzafpn\\xb5mkMGTPEZY]/;function w(t){return t&&t.duration>0}function T(t){t.each((function(t){y.stroke(n.select(this),t.line.color)})).each((function(t){y.fill(n.select(this),t.color)})).style(\"stroke-width\",(function(t){return t.line.width}))}function k(t,e,r){var n=t._fullLayout,i=o.extendFlat({type:\"linear\",ticks:\"outside\",range:r,showline:!0},e),a={type:\"linear\",_id:\"x\"+e._id},s={letter:\"x\",font:n.font,noHover:!0,noTickson:!0};function l(t,e){return o.coerce(i,a,v,t,e)}return g(i,a,l,s,n),m(i,a,l,s),a}function A(t,e,r){return[Math.min(e/t.width,r/t.height),t,e+\"x\"+r]}function M(t,e,r,i){var a=document.createElementNS(\"http://www.w3.org/2000/svg\",\"text\"),o=n.select(a);return o.text(t).attr(\"x\",0).attr(\"y\",0).attr(\"text-anchor\",r).attr(\"data-unformatted\",t).call(p.convertToTspans,i).call(f.font,e),f.bBox(o.node())}function S(t,e,r,n,i,a){var s=\"_cache\"+e;t[s]&&t[s].key===i||(t[s]={key:i,value:r});var l=o.aggNums(a,null,[t[s].value,n],2);return t[s].value=l,l}e.exports=function(t,e,r,g){var m,v=t._fullLayout;w(r)&&g&&(m=g()),o.makeTraceGroups(v._indicatorlayer,e,\"trace\").each((function(e){var g,E,L,C,P,I=e[0].trace,O=n.select(this),z=I._hasGauge,D=I._isAngular,R=I._isBullet,F=I.domain,B={w:v._size.w*(F.x[1]-F.x[0]),h:v._size.h*(F.y[1]-F.y[0]),l:v._size.l+v._size.w*F.x[0],r:v._size.r+v._size.w*(1-F.x[1]),t:v._size.t+v._size.h*(1-F.y[1]),b:v._size.b+v._size.h*F.y[0]},N=B.l+B.w/2,j=B.t+B.h/2,U=Math.min(B.w/2,B.h),V=h.innerRadius*U,q=I.align||\"center\";if(E=j,z){if(D&&(g=N,E=j+U/2,L=function(t){return function(t,e){var r=Math.sqrt(t.width/2*(t.width/2)+t.height*t.height);return[e/r,t,e]}(t,.9*V)}),R){var H=h.bulletPadding,G=1-h.bulletNumberDomainSize+H;g=B.l+(G+(1-G)*b[q])*B.w,L=function(t){return A(t,(h.bulletNumberDomainSize-H)*B.w,B.h)}}}else g=B.l+b[q]*B.w,L=function(t){return A(t,B.w,B.h)};!function(t,e,r,i){var c,u,h,g=r[0].trace,m=i.numbersX,v=i.numbersY,T=g.align||\"center\",A=x[T],E=i.transitionOpts,L=i.onComplete,C=o.ensureSingle(e,\"g\",\"numbers\"),P=[];g._hasNumber&&P.push(\"number\");g._hasDelta&&(P.push(\"delta\"),\"left\"===g.delta.position&&P.reverse());var I=C.selectAll(\"text\").data(P);function O(e,r,n,i){if(!e.match(\"s\")||n>=0==i>=0||r(n).slice(-1).match(_)||r(i).slice(-1).match(_))return r;var a=e.slice().replace(\"s\",\"f\").replace(/\\d+/,(function(t){return parseInt(t)-1})),o=k(t,{tickformat:a});return function(t){return Math.abs(t)<1?d.tickText(o,t).text:r(t)}}I.enter().append(\"text\"),I.attr(\"text-anchor\",(function(){return A})).attr(\"class\",(function(t){return t})).attr(\"x\",null).attr(\"y\",null).attr(\"dx\",null).attr(\"dy\",null),I.exit().remove();var z,D=g.mode+g.align;g._hasDelta&&(z=function(){var e=k(t,{tickformat:g.delta.valueformat},g._range);e.setScale(),d.prepTicks(e);var i=function(t){return d.tickText(e,t).text},o=function(t){return g.delta.relative?t.relativeDelta:t.delta},s=function(t,e){return 0===t||\"number\"!=typeof t||isNaN(t)?\"-\":(t>0?g.delta.increasing.symbol:g.delta.decreasing.symbol)+e(t)},l=function(t){return t.delta>=0?g.delta.increasing.color:g.delta.decreasing.color};void 0===g._deltaLastValue&&(g._deltaLastValue=o(r[0]));var c=C.select(\"text.delta\");function h(){c.text(s(o(r[0]),i)).call(y.fill,l(r[0])).call(p.convertToTspans,t)}return c.call(f.font,g.delta.font).call(y.fill,l({delta:g._deltaLastValue})),w(E)?c.transition().duration(E.duration).ease(E.easing).tween(\"text\",(function(){var t=n.select(this),e=o(r[0]),c=g._deltaLastValue,u=O(g.delta.valueformat,i,c,e),f=a(c,e);return g._deltaLastValue=e,function(e){t.text(s(f(e),u)),t.call(y.fill,l({delta:f(e)}))}})).each(\"end\",(function(){h(),L&&L()})).each(\"interrupt\",(function(){h(),L&&L()})):h(),u=M(s(o(r[0]),i),g.delta.font,A,t),c}(),D+=g.delta.position+g.delta.font.size+g.delta.font.family+g.delta.valueformat,D+=g.delta.increasing.symbol+g.delta.decreasing.symbol,h=u);g._hasNumber&&(!function(){var e=k(t,{tickformat:g.number.valueformat},g._range);e.setScale(),d.prepTicks(e);var i=function(t){return d.tickText(e,t).text},o=g.number.suffix,s=g.number.prefix,l=C.select(\"text.number\");function u(){var e=\"number\"==typeof r[0].y?s+i(r[0].y)+o:\"-\";l.text(e).call(f.font,g.number.font).call(p.convertToTspans,t)}w(E)?l.transition().duration(E.duration).ease(E.easing).each(\"end\",(function(){u(),L&&L()})).each(\"interrupt\",(function(){u(),L&&L()})).attrTween(\"text\",(function(){var t=n.select(this),e=a(r[0].lastY,r[0].y);g._lastValue=r[0].y;var l=O(g.number.valueformat,i,r[0].lastY,r[0].y);return function(r){t.text(s+l(e(r))+o)}})):u(),c=M(s+i(r[0].y)+o,g.number.font,A,t)}(),D+=g.number.font.size+g.number.font.family+g.number.valueformat+g.number.suffix+g.number.prefix,h=c);if(g._hasDelta&&g._hasNumber){var R,F,B=[(c.left+c.right)/2,(c.top+c.bottom)/2],N=[(u.left+u.right)/2,(u.top+u.bottom)/2],j=.75*g.delta.font.size;\"left\"===g.delta.position&&(R=S(g,\"deltaPos\",0,-1*(c.width*b[g.align]+u.width*(1-b[g.align])+j),D,Math.min),F=B[1]-N[1],h={width:c.width+u.width+j,height:Math.max(c.height,u.height),left:u.left+R,right:c.right,top:Math.min(c.top,u.top+F),bottom:Math.max(c.bottom,u.bottom+F)}),\"right\"===g.delta.position&&(R=S(g,\"deltaPos\",0,c.width*(1-b[g.align])+u.width*b[g.align]+j,D,Math.max),F=B[1]-N[1],h={width:c.width+u.width+j,height:Math.max(c.height,u.height),left:c.left,right:u.right+R,top:Math.min(c.top,u.top+F),bottom:Math.max(c.bottom,u.bottom+F)}),\"bottom\"===g.delta.position&&(R=null,F=u.height,h={width:Math.max(c.width,u.width),height:c.height+u.height,left:Math.min(c.left,u.left),right:Math.max(c.right,u.right),top:c.bottom-c.height,bottom:c.bottom+u.height}),\"top\"===g.delta.position&&(R=null,F=c.top,h={width:Math.max(c.width,u.width),height:c.height+u.height,left:Math.min(c.left,u.left),right:Math.max(c.right,u.right),top:c.bottom-c.height-u.height,bottom:c.bottom}),z.attr({dx:R,dy:F})}(g._hasNumber||g._hasDelta)&&C.attr(\"transform\",(function(){var t=i.numbersScaler(h);D+=t[2];var e,r=S(g,\"numbersScale\",1,t[0],D,Math.min);g._scaleNumbers||(r=1),e=g._isAngular?v-r*h.bottom:v-r*(h.top+h.bottom)/2,g._numbersTop=r*h.top+e;var n=h[T];\"center\"===T&&(n=(h.left+h.right)/2);var a=m-r*n;return a=S(g,\"numbersTranslate\",0,a,D,Math.max),l(a,e)+s(r)}))}(t,O,e,{numbersX:g,numbersY:E,numbersScaler:L,transitionOpts:r,onComplete:m}),z&&(C={range:I.gauge.axis.range,color:I.gauge.bgcolor,line:{color:I.gauge.bordercolor,width:0},thickness:1},P={range:I.gauge.axis.range,color:\"rgba(0, 0, 0, 0)\",line:{color:I.gauge.bordercolor,width:I.gauge.borderwidth},thickness:1});var Y=O.selectAll(\"g.angular\").data(D?e:[]);Y.exit().remove();var W=O.selectAll(\"g.angularaxis\").data(D?e:[]);W.exit().remove(),D&&function(t,e,r,a){var o,s,f,h,p=r[0].trace,g=a.size,m=a.radius,v=a.innerRadius,y=a.gaugeBg,x=a.gaugeOutline,b=[g.l+g.w/2,g.t+g.h/2+m/2],_=a.gauge,A=a.layer,M=a.transitionOpts,S=a.onComplete,E=Math.PI/2;function L(t){var e=p.gauge.axis.range[0],r=(t-e)/(p.gauge.axis.range[1]-e)*Math.PI-E;return r<-E?-E:r>E?E:r}function C(t){return n.svg.arc().innerRadius((v+m)/2-t/2*(m-v)).outerRadius((v+m)/2+t/2*(m-v)).startAngle(-E)}function P(t){t.attr(\"d\",(function(t){return C(t.thickness).startAngle(L(t.range[0])).endAngle(L(t.range[1]))()}))}_.enter().append(\"g\").classed(\"angular\",!0),_.attr(\"transform\",l(b[0],b[1])),A.enter().append(\"g\").classed(\"angularaxis\",!0).classed(\"crisp\",!0),A.selectAll(\"g.xangularaxistick,path,text\").remove(),(o=k(t,p.gauge.axis)).type=\"linear\",o.range=p.gauge.axis.range,o._id=\"xangularaxis\",o.ticklabeloverflow=\"allow\",o.setScale();var I=function(t){return(o.range[0]-t.x)/(o.range[1]-o.range[0])*Math.PI+Math.PI},O={},z=d.makeLabelFns(o,0).labelStandoff;O.xFn=function(t){var e=I(t);return Math.cos(e)*z},O.yFn=function(t){var e=I(t),r=Math.sin(e)>0?.2:1;return-Math.sin(e)*(z+t.fontSize*r)+Math.abs(Math.cos(e))*(t.fontSize*u)},O.anchorFn=function(t){var e=I(t),r=Math.cos(e);return Math.abs(r)<.1?\"middle\":r>0?\"start\":\"end\"},O.heightFn=function(t,e,r){var n=I(t);return-.5*(1+Math.sin(n))*r};var D=function(t){return l(b[0]+m*Math.cos(t),b[1]-m*Math.sin(t))};f=function(t){return D(I(t))};if(s=d.calcTicks(o),h=d.getTickSigns(o)[2],o.visible){h=\"inside\"===o.ticks?-1:1;var R=(o.linewidth||1)/2;d.drawTicks(t,o,{vals:s,layer:A,path:\"M\"+h*R+\",0h\"+h*o.ticklen,transFn:function(t){var e=I(t);return D(e)+\"rotate(\"+-c(e)+\")\"}}),d.drawLabels(t,o,{vals:s,layer:A,transFn:f,labelFns:O})}var F=[y].concat(p.gauge.steps),B=_.selectAll(\"g.bg-arc\").data(F);B.enter().append(\"g\").classed(\"bg-arc\",!0).append(\"path\"),B.select(\"path\").call(P).call(T),B.exit().remove();var N=C(p.gauge.bar.thickness),j=_.selectAll(\"g.value-arc\").data([p.gauge.bar]);j.enter().append(\"g\").classed(\"value-arc\",!0).append(\"path\");var U=j.select(\"path\");w(M)?(U.transition().duration(M.duration).ease(M.easing).each(\"end\",(function(){S&&S()})).each(\"interrupt\",(function(){S&&S()})).attrTween(\"d\",(V=N,q=L(r[0].lastY),H=L(r[0].y),function(){var t=i(q,H);return function(e){return V.endAngle(t(e))()}})),p._lastValue=r[0].y):U.attr(\"d\",\"number\"==typeof r[0].y?N.endAngle(L(r[0].y)):\"M0,0Z\");var V,q,H;U.call(T),j.exit().remove(),F=[];var G=p.gauge.threshold.value;(G||0===G)&&F.push({range:[G,G],color:p.gauge.threshold.color,line:{color:p.gauge.threshold.line.color,width:p.gauge.threshold.line.width},thickness:p.gauge.threshold.thickness});var Y=_.selectAll(\"g.threshold-arc\").data(F);Y.enter().append(\"g\").classed(\"threshold-arc\",!0).append(\"path\"),Y.select(\"path\").call(P).call(T),Y.exit().remove();var W=_.selectAll(\"g.gauge-outline\").data([x]);W.enter().append(\"g\").classed(\"gauge-outline\",!0).append(\"path\"),W.select(\"path\").call(P).call(T),W.exit().remove()}(t,0,e,{radius:U,innerRadius:V,gauge:Y,layer:W,size:B,gaugeBg:C,gaugeOutline:P,transitionOpts:r,onComplete:m});var X=O.selectAll(\"g.bullet\").data(R?e:[]);X.exit().remove();var Z=O.selectAll(\"g.bulletaxis\").data(R?e:[]);Z.exit().remove(),R&&function(t,e,r,n){var i,a,o,s,c,u=r[0].trace,f=n.gauge,p=n.layer,g=n.gaugeBg,m=n.gaugeOutline,v=n.size,x=u.domain,b=n.transitionOpts,_=n.onComplete;f.enter().append(\"g\").classed(\"bullet\",!0),f.attr(\"transform\",l(v.l,v.t)),p.enter().append(\"g\").classed(\"bulletaxis\",!0).classed(\"crisp\",!0),p.selectAll(\"g.xbulletaxistick,path,text\").remove();var A=v.h,M=u.gauge.bar.thickness*A,S=x.x[0],E=x.x[0]+(x.x[1]-x.x[0])*(u._hasNumber||u._hasDelta?1-h.bulletNumberDomainSize:1);(i=k(t,u.gauge.axis))._id=\"xbulletaxis\",i.domain=[S,E],i.setScale(),a=d.calcTicks(i),o=d.makeTransTickFn(i),s=d.getTickSigns(i)[2],c=v.t+v.h,i.visible&&(d.drawTicks(t,i,{vals:\"inside\"===i.ticks?d.clipEnds(i,a):a,layer:p,path:d.makeTickPath(i,c,s),transFn:o}),d.drawLabels(t,i,{vals:a,layer:p,transFn:o,labelFns:d.makeLabelFns(i,c)}));function L(t){t.attr(\"width\",(function(t){return Math.max(0,i.c2p(t.range[1])-i.c2p(t.range[0]))})).attr(\"x\",(function(t){return i.c2p(t.range[0])})).attr(\"y\",(function(t){return.5*(1-t.thickness)*A})).attr(\"height\",(function(t){return t.thickness*A}))}var C=[g].concat(u.gauge.steps),P=f.selectAll(\"g.bg-bullet\").data(C);P.enter().append(\"g\").classed(\"bg-bullet\",!0).append(\"rect\"),P.select(\"rect\").call(L).call(T),P.exit().remove();var I=f.selectAll(\"g.value-bullet\").data([u.gauge.bar]);I.enter().append(\"g\").classed(\"value-bullet\",!0).append(\"rect\"),I.select(\"rect\").attr(\"height\",M).attr(\"y\",(A-M)/2).call(T),w(b)?I.select(\"rect\").transition().duration(b.duration).ease(b.easing).each(\"end\",(function(){_&&_()})).each(\"interrupt\",(function(){_&&_()})).attr(\"width\",Math.max(0,i.c2p(Math.min(u.gauge.axis.range[1],r[0].y)))):I.select(\"rect\").attr(\"width\",\"number\"==typeof r[0].y?Math.max(0,i.c2p(Math.min(u.gauge.axis.range[1],r[0].y))):0);I.exit().remove();var O=r.filter((function(){return u.gauge.threshold.value||0===u.gauge.threshold.value})),z=f.selectAll(\"g.threshold-bullet\").data(O);z.enter().append(\"g\").classed(\"threshold-bullet\",!0).append(\"line\"),z.select(\"line\").attr(\"x1\",i.c2p(u.gauge.threshold.value)).attr(\"x2\",i.c2p(u.gauge.threshold.value)).attr(\"y1\",(1-u.gauge.threshold.thickness)/2*A).attr(\"y2\",(1-(1-u.gauge.threshold.thickness)/2)*A).call(y.stroke,u.gauge.threshold.line.color).style(\"stroke-width\",u.gauge.threshold.line.width),z.exit().remove();var D=f.selectAll(\"g.gauge-outline\").data([m]);D.enter().append(\"g\").classed(\"gauge-outline\",!0).append(\"rect\"),D.select(\"rect\").call(L).call(T),D.exit().remove()}(t,0,e,{gauge:X,layer:Z,size:B,gaugeBg:C,gaugeOutline:P,transitionOpts:r,onComplete:m});var J=O.selectAll(\"text.title\").data(e);J.exit().remove(),J.enter().append(\"text\").classed(\"title\",!0),J.attr(\"text-anchor\",(function(){return 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n=t(\"../../components/colorscale/attributes\"),i=t(\"../../plots/cartesian/axis_format_attributes\").axisHoverFormat,a=t(\"../../plots/template_attributes\").hovertemplateAttrs,o=t(\"../mesh3d/attributes\"),s=t(\"../../plots/attributes\"),l=t(\"../../lib/extend\").extendFlat,c=t(\"../../plot_api/edit_types\").overrideAll;var 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n=t(\"../../components/colorscale/attributes\"),i=t(\"../../plots/cartesian/axis_format_attributes\").axisHoverFormat,a=t(\"../../plots/template_attributes\").hovertemplateAttrs,o=t(\"../surface/attributes\"),s=t(\"../../plots/attributes\"),l=t(\"../../lib/extend\").extendFlat;e.exports=l({x:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},y:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},z:{valType:\"data_array\",editType:\"calc+clearAxisTypes\"},i:{valType:\"data_array\",editType:\"calc\"},j:{valType:\"data_array\",editType:\"calc\"},k:{valType:\"data_array\",editType:\"calc\"},text:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"calc\"},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"calc\"},hovertemplate:a({editType:\"calc\"}),xhoverformat:i(\"x\"),yhoverformat:i(\"y\"),zhoverformat:i(\"z\"),delaunayaxis:{valType:\"enumerated\",values:[\"x\",\"y\",\"z\"],dflt:\"z\",editType:\"calc\"},alphahull:{valType:\"number\",dflt:-1,editType:\"calc\"},intensity:{valType:\"data_array\",editType:\"calc\"},intensitymode:{valType:\"enumerated\",values:[\"vertex\",\"cell\"],dflt:\"vertex\",editType:\"calc\"},color:{valType:\"color\",editType:\"calc\"},vertexcolor:{valType:\"data_array\",editType:\"calc\"},facecolor:{valType:\"data_array\",editType:\"calc\"},transforms:void 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n=t(\"../../components/colorscale/calc\");e.exports=function(t,e){e.intensity&&n(t,e,{vals:e.intensity,containerStr:\"\",cLetter:\"c\"})}},{\"../../components/colorscale/calc\":674}],1161:[function(t,e,r){\"use strict\";var n=t(\"gl-mesh3d\"),i=t(\"delaunay-triangulate\"),a=t(\"alpha-shape\"),o=t(\"convex-hull\"),s=t(\"../../lib/gl_format_color\").parseColorScale,l=t(\"../../lib/str2rgbarray\"),c=t(\"../../components/colorscale\").extractOpts,u=t(\"../../plots/gl3d/zip3\");function f(t,e,r){this.scene=t,this.uid=r,this.mesh=e,this.name=\"\",this.color=\"#fff\",this.data=null,this.showContour=!1}var h=f.prototype;function p(t){for(var e=[],r=t.length,n=0;n<r;n++)e[n]=l(t[n]);return e}function d(t,e,r,n){for(var i=[],a=e.length,o=0;o<a;o++)i[o]=t.d2l(e[o],0,n)*r;return i}function g(t){for(var e=[],r=t.length,n=0;n<r;n++)e[n]=Math.round(t[n]);return e}function m(t,e){for(var r=t.length,n=0;n<r;n++)if(t[n]<=-.5||t[n]>=e-.5)return!1;return!0}h.handlePick=function(t){if(t.object===this.mesh){var e=t.index=t.data.index;t.data._cellCenter?t.traceCoordinate=t.data.dataCoordinate:t.traceCoordinate=[this.data.x[e],this.data.y[e],this.data.z[e]];var r=this.data.hovertext||this.data.text;return Array.isArray(r)&&void 0!==r[e]?t.textLabel=r[e]:r&&(t.textLabel=r),!0}},h.update=function(t){var e=this.scene,r=e.fullSceneLayout;this.data=t;var n,f=t.x.length,h=u(d(r.xaxis,t.x,e.dataScale[0],t.xcalendar),d(r.yaxis,t.y,e.dataScale[1],t.ycalendar),d(r.zaxis,t.z,e.dataScale[2],t.zcalendar));if(t.i&&t.j&&t.k){if(t.i.length!==t.j.length||t.j.length!==t.k.length||!m(t.i,f)||!m(t.j,f)||!m(t.k,f))return;n=u(g(t.i),g(t.j),g(t.k))}else n=0===t.alphahull?o(h):t.alphahull>0?a(t.alphahull,h):function(t,e){for(var r=[\"x\",\"y\",\"z\"].indexOf(t),n=[],a=e.length,o=0;o<a;o++)n[o]=[e[o][(r+1)%3],e[o][(r+2)%3]];return i(n)}(t.delaunayaxis,h);var v={positions:h,cells:n,lightPosition:[t.lightposition.x,t.lightposition.y,t.lightposition.z],ambient:t.lighting.ambient,diffuse:t.lighting.diffuse,specular:t.lighting.specular,roughness:t.lighting.roughness,fresnel:t.lighting.fresnel,vertexNormalsEpsilon:t.lighting.vertexnormalsepsilon,faceNormalsEpsilon:t.lighting.facenormalsepsilon,opacity:t.opacity,contourEnable:t.contour.show,contourColor:l(t.contour.color).slice(0,3),contourWidth:t.contour.width,useFacetNormals:t.flatshading};if(t.intensity){var y=c(t);this.color=\"#fff\";var x=t.intensitymode;v[x+\"Intensity\"]=t.intensity,v[x+\"IntensityBounds\"]=[y.min,y.max],v.colormap=s(t)}else t.vertexcolor?(this.color=t.vertexcolor[0],v.vertexColors=p(t.vertexcolor)):t.facecolor?(this.color=t.facecolor[0],v.cellColors=p(t.facecolor)):(this.color=t.color,v.meshColor=l(t.color));this.mesh.update(v)},h.dispose=function(){this.scene.glplot.remove(this.mesh),this.mesh.dispose()},e.exports=function(t,e){var r=t.glplot.gl,i=n({gl:r}),a=new f(t,i,e.uid);return i._trace=a,a.update(e),t.glplot.add(i),a}},{\"../../components/colorscale\":678,\"../../lib/gl_format_color\":799,\"../../lib/str2rgbarray\":828,\"../../plots/gl3d/zip3\":907,\"alpha-shape\":75,\"convex-hull\":141,\"delaunay-triangulate\":180,\"gl-mesh3d\":315}],1162:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),i=t(\"../../lib\"),a=t(\"../../components/colorscale/defaults\"),o=t(\"./attributes\");e.exports=function(t,e,r,s){function l(r,n){return i.coerce(t,e,o,r,n)}function c(t){var e=t.map((function(t){var e=l(t);return e&&i.isArrayOrTypedArray(e)?e:null}));return e.every((function(t){return 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n=t(\"../../lib\").extendFlat,i=t(\"../scatter/attributes\"),a=t(\"../../plots/cartesian/axis_format_attributes\").axisHoverFormat,o=t(\"../../components/drawing/attributes\").dash,s=t(\"../../components/fx/attributes\"),l=t(\"../../constants/delta.js\"),c=l.INCREASING.COLOR,u=l.DECREASING.COLOR,f=i.line;function 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E=S.enter().append(\"rect\").attr(\"class\",\"bandrect\").attr(\"stroke-opacity\",0).attr(\"fill\",(function(t){return t.color})).attr(\"fill-opacity\",0);S.attr(\"fill\",(function(t){return t.color})).attr(\"width\",(function(t){return t.width})).attr(\"height\",(function(t){return t.height})).attr(\"y\",(function(t){return t.y})).attr(\"cursor\",(function(t){return\"fixed\"===t.parcatsViewModel.arrangement?\"default\":\"perpendicular\"===t.parcatsViewModel.arrangement?\"ns-resize\":\"move\"})),k(E),S.exit().remove(),M.append(\"text\").attr(\"class\",\"catlabel\").attr(\"pointer-events\",\"none\");var z=e._fullLayout.paper_bgcolor;A.select(\"text.catlabel\").attr(\"text-anchor\",(function(t){return d(t)?\"start\":\"end\"})).attr(\"alignment-baseline\",\"middle\").style(\"text-shadow\",f.makeTextShadow(z)).style(\"fill\",\"rgb(0, 0, 0)\").attr(\"x\",(function(t){return d(t)?t.width+5:-5})).attr(\"y\",(function(t){return t.height/2})).text((function(t){return t.model.categoryLabel})).each((function(t){c.font(n.select(this),t.parcatsViewModel.categorylabelfont),f.convertToTspans(n.select(this),e)})),M.append(\"text\").attr(\"class\",\"dimlabel\"),A.select(\"text.dimlabel\").attr(\"text-anchor\",\"middle\").attr(\"alignment-baseline\",\"baseline\").attr(\"cursor\",(function(t){return\"fixed\"===t.parcatsViewModel.arrangement?\"default\":\"ew-resize\"})).attr(\"x\",(function(t){return t.width/2})).attr(\"y\",-5).text((function(t,e){return 0===e?t.parcatsViewModel.model.dimensions[t.model.dimensionInd].dimensionLabel:null})).each((function(t){c.font(n.select(this),t.parcatsViewModel.labelfont)})),A.selectAll(\"rect.bandrect\").on(\"mouseover\",L).on(\"mouseout\",C),A.exit().remove(),w.call(n.behavior.drag().origin((function(t){return{x:t.x,y:0}})).on(\"dragstart\",P).on(\"drag\",I).on(\"dragend\",O)),u.each((function(t){t.traceSelection=n.select(this),t.pathSelection=n.select(this).selectAll(\"g.paths\").selectAll(\"path.path\"),t.dimensionSelection=n.select(this).selectAll(\"g.dimensions\").selectAll(\"g.dimension\")})),u.exit().remove()}function p(t){return t.key}function d(t){var e=t.parcatsViewModel.dimensions.length,r=t.parcatsViewModel.dimensions[e-1].model.dimensionInd;return t.model.dimensionInd===r}function g(t,e){return t.model.rawColor>e.model.rawColor?1:t.model.rawColor<e.model.rawColor?-1:0}function m(t){if(!t.parcatsViewModel.dragDimension&&-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")){s.raiseToTop(this),w(n.select(this));var e=y(t),r=x(t);if(t.parcatsViewModel.graphDiv.emit(\"plotly_hover\",{points:e,event:n.event,constraints:r}),-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"none\")){var i,a,l,c=n.mouse(this)[0],f=t.parcatsViewModel.graphDiv,h=t.parcatsViewModel.trace,p=f._fullLayout,d=p._paperdiv.node().getBoundingClientRect(),g=t.parcatsViewModel.graphDiv.getBoundingClientRect();for(l=0;l<t.leftXs.length-1;l++)if(t.leftXs[l]+t.dimWidths[l]-2<=c&&c<=t.leftXs[l+1]+2){var m=t.parcatsViewModel.dimensions[l],v=t.parcatsViewModel.dimensions[l+1];i=(m.x+m.width+v.x)/2,a=(t.topYs[l]+t.topYs[l+1]+t.height)/2;break}var b=t.parcatsViewModel.x+i,_=t.parcatsViewModel.y+a,T=u.mostReadable(t.model.color,[\"black\",\"white\"]),k=t.model.count,A=k/t.parcatsViewModel.model.count,M={countLabel:k,probabilityLabel:A.toFixed(3)},S=[];-1!==t.parcatsViewModel.hoverinfoItems.indexOf(\"count\")&&S.push([\"Count:\",M.countLabel].join(\" \")),-1!==t.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")&&S.push([\"P:\",M.probabilityLabel].join(\" \"));var E=S.join(\"<br>\"),L=n.mouse(f)[0];o.loneHover({trace:h,x:b-d.left+g.left,y:_-d.top+g.top,text:E,color:t.model.color,borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", monospace',fontSize:10,fontColor:T,idealAlign:L<b?\"right\":\"left\",hovertemplate:(h.line||{}).hovertemplate,hovertemplateLabels:M,eventData:[{data:h._input,fullData:h,count:k,probability:A}]},{container:p._hoverlayer.node(),outerContainer:p._paper.node(),gd:f})}}}function v(t){if(!t.parcatsViewModel.dragDimension&&(_(n.select(this)),o.loneUnhover(t.parcatsViewModel.graphDiv._fullLayout._hoverlayer.node()),t.parcatsViewModel.pathSelection.sort(g),-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\"))){var e=y(t),r=x(t);t.parcatsViewModel.graphDiv.emit(\"plotly_unhover\",{points:e,event:n.event,constraints:r})}}function y(t){for(var e=[],r=z(t.parcatsViewModel),n=0;n<t.model.valueInds.length;n++){var i=t.model.valueInds[n];e.push({curveNumber:r,pointNumber:i})}return e}function x(t){for(var e={},r=t.parcatsViewModel.model.dimensions,n=0;n<r.length;n++){var i=r[n],a=i.categories[t.model.categoryInds[n]];e[i.containerInd]=a.categoryValue}return void 0!==t.model.rawColor&&(e.color=t.model.rawColor),e}function b(t){if(-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")){var e=y(t),r=x(t);t.parcatsViewModel.graphDiv.emit(\"plotly_click\",{points:e,event:n.event,constraints:r})}}function _(t){t.attr(\"fill\",(function(t){return t.model.color})).attr(\"fill-opacity\",.6).attr(\"stroke\",\"lightgray\").attr(\"stroke-width\",.2).attr(\"stroke-opacity\",1)}function w(t){t.attr(\"fill-opacity\",.8).attr(\"stroke\",(function(t){return u.mostReadable(t.model.color,[\"black\",\"white\"])})).attr(\"stroke-width\",.3)}function T(t){t.select(\"rect.catrect\").attr(\"stroke\",\"black\").attr(\"stroke-width\",1).attr(\"stroke-opacity\",1)}function k(t){t.attr(\"stroke\",\"black\").attr(\"stroke-width\",.2).attr(\"stroke-opacity\",1).attr(\"fill-opacity\",1)}function A(t){var e=t.parcatsViewModel.pathSelection,r=t.categoryViewModel.model.dimensionInd,n=t.categoryViewModel.model.categoryInd;return e.filter((function(e){return e.model.categoryInds[r]===n&&e.model.color===t.color}))}function M(t,e,r){var i=n.select(t).datum(),a=i.categoryViewModel.model,o=i.parcatsViewModel.graphDiv,s=n.select(t.parentNode).selectAll(\"rect.bandrect\"),l=[];s.each((function(t){A(t).each((function(t){Array.prototype.push.apply(l,y(t))}))}));var c={};c[a.dimensionInd]=a.categoryValue,o.emit(e,{points:l,event:r,constraints:c})}function S(t,e,r){var i=n.select(t).datum(),a=i.categoryViewModel.model,o=i.parcatsViewModel.graphDiv,s=A(i),l=[];s.each((function(t){Array.prototype.push.apply(l,y(t))}));var c={};c[a.dimensionInd]=a.categoryValue,void 0!==i.rawColor&&(c.color=i.rawColor),o.emit(e,{points:l,event:r,constraints:c})}function E(t,e,r){t._fullLayout._calcInverseTransform(t);var i,a,o=t._fullLayout._invScaleX,s=t._fullLayout._invScaleY,l=n.select(r.parentNode).select(\"rect.catrect\"),c=l.node().getBoundingClientRect(),u=l.datum(),f=u.parcatsViewModel,h=f.model.dimensions[u.model.dimensionInd],p=f.trace,d=c.top+c.height/2;f.dimensions.length>1&&h.displayInd===f.dimensions.length-1?(i=c.left,a=\"left\"):(i=c.left+c.width,a=\"right\");var g=u.model.count,m=u.model.categoryLabel,v=g/u.parcatsViewModel.model.count,y={countLabel:g,categoryLabel:m,probabilityLabel:v.toFixed(3)},x=[];-1!==u.parcatsViewModel.hoverinfoItems.indexOf(\"count\")&&x.push([\"Count:\",y.countLabel].join(\" \")),-1!==u.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")&&x.push([\"P(\"+y.categoryLabel+\"):\",y.probabilityLabel].join(\" \"));var b=x.join(\"<br>\");return{trace:p,x:o*(i-e.left),y:s*(d-e.top),text:b,color:\"lightgray\",borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", monospace',fontSize:12,fontColor:\"black\",idealAlign:a,hovertemplate:p.hovertemplate,hovertemplateLabels:y,eventData:[{data:p._input,fullData:p,count:g,category:m,probability:v}]}}function L(t){if(!t.parcatsViewModel.dragDimension&&-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")){if(n.mouse(this)[1]<-1)return;var e,r=t.parcatsViewModel.graphDiv,i=r._fullLayout,a=i._paperdiv.node().getBoundingClientRect(),l=t.parcatsViewModel.hoveron;if(\"color\"===l?(!function(t){var e=n.select(t).datum(),r=A(e);w(r),r.each((function(){s.raiseToTop(this)})),n.select(t.parentNode).selectAll(\"rect.bandrect\").filter((function(t){return t.color===e.color})).each((function(){s.raiseToTop(this),n.select(this).attr(\"stroke\",\"black\").attr(\"stroke-width\",1.5)}))}(this),S(this,\"plotly_hover\",n.event)):(!function(t){n.select(t.parentNode).selectAll(\"rect.bandrect\").each((function(t){var e=A(t);w(e),e.each((function(){s.raiseToTop(this)}))})),n.select(t.parentNode).select(\"rect.catrect\").attr(\"stroke\",\"black\").attr(\"stroke-width\",2.5)}(this),M(this,\"plotly_hover\",n.event)),-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"none\"))\"category\"===l?e=E(r,a,this):\"color\"===l?e=function(t,e,r){t._fullLayout._calcInverseTransform(t);var i,a,o=t._fullLayout._invScaleX,s=t._fullLayout._invScaleY,l=r.getBoundingClientRect(),c=n.select(r).datum(),f=c.categoryViewModel,h=f.parcatsViewModel,p=h.model.dimensions[f.model.dimensionInd],d=h.trace,g=l.y+l.height/2;h.dimensions.length>1&&p.displayInd===h.dimensions.length-1?(i=l.left,a=\"left\"):(i=l.left+l.width,a=\"right\");var m=f.model.categoryLabel,v=c.parcatsViewModel.model.count,y=0;c.categoryViewModel.bands.forEach((function(t){t.color===c.color&&(y+=t.count)}));var x=f.model.count,b=0;h.pathSelection.each((function(t){t.model.color===c.color&&(b+=t.model.count)}));var _=y/v,w=y/b,T=y/x,k={countLabel:v,categoryLabel:m,probabilityLabel:_.toFixed(3)},A=[];-1!==f.parcatsViewModel.hoverinfoItems.indexOf(\"count\")&&A.push([\"Count:\",k.countLabel].join(\" \")),-1!==f.parcatsViewModel.hoverinfoItems.indexOf(\"probability\")&&(A.push(\"P(color \\u2229 \"+m+\"): \"+k.probabilityLabel),A.push(\"P(\"+m+\" | color): \"+w.toFixed(3)),A.push(\"P(color | \"+m+\"): \"+T.toFixed(3)));var M=A.join(\"<br>\"),S=u.mostReadable(c.color,[\"black\",\"white\"]);return{trace:d,x:o*(i-e.left),y:s*(g-e.top),text:M,color:c.color,borderColor:\"black\",fontFamily:'Monaco, \"Courier New\", monospace',fontColor:S,fontSize:10,idealAlign:a,hovertemplate:d.hovertemplate,hovertemplateLabels:k,eventData:[{data:d._input,fullData:d,category:m,count:v,probability:_,categorycount:x,colorcount:b,bandcolorcount:y}]}}(r,a,this):\"dimension\"===l&&(e=function(t,e,r){var i=[];return n.select(r.parentNode.parentNode).selectAll(\"g.category\").select(\"rect.catrect\").each((function(){i.push(E(t,e,this))})),i}(r,a,this)),e&&o.loneHover(e,{container:i._hoverlayer.node(),outerContainer:i._paper.node(),gd:r})}}function C(t){var e=t.parcatsViewModel;if(!e.dragDimension&&(_(e.pathSelection),T(e.dimensionSelection.selectAll(\"g.category\")),k(e.dimensionSelection.selectAll(\"g.category\").selectAll(\"rect.bandrect\")),o.loneUnhover(e.graphDiv._fullLayout._hoverlayer.node()),e.pathSelection.sort(g),-1===e.hoverinfoItems.indexOf(\"skip\"))){\"color\"===t.parcatsViewModel.hoveron?S(this,\"plotly_unhover\",n.event):M(this,\"plotly_unhover\",n.event)}}function P(t){\"fixed\"!==t.parcatsViewModel.arrangement&&(t.dragDimensionDisplayInd=t.model.displayInd,t.initialDragDimensionDisplayInds=t.parcatsViewModel.model.dimensions.map((function(t){return t.displayInd})),t.dragHasMoved=!1,t.dragCategoryDisplayInd=null,n.select(this).selectAll(\"g.category\").select(\"rect.catrect\").each((function(e){var r=n.mouse(this)[0],i=n.mouse(this)[1];-2<=r&&r<=e.width+2&&-2<=i&&i<=e.height+2&&(t.dragCategoryDisplayInd=e.model.displayInd,t.initialDragCategoryDisplayInds=t.model.categories.map((function(t){return t.displayInd})),e.model.dragY=e.y,s.raiseToTop(this.parentNode),n.select(this.parentNode).selectAll(\"rect.bandrect\").each((function(e){e.y<i&&i<=e.y+e.height&&(t.potentialClickBand=this)})))})),t.parcatsViewModel.dragDimension=t,o.loneUnhover(t.parcatsViewModel.graphDiv._fullLayout._hoverlayer.node()))}function I(t){if(\"fixed\"!==t.parcatsViewModel.arrangement&&(t.dragHasMoved=!0,null!==t.dragDimensionDisplayInd)){var e=t.dragDimensionDisplayInd,r=e-1,i=e+1,a=t.parcatsViewModel.dimensions[e];if(null!==t.dragCategoryDisplayInd){var o=a.categories[t.dragCategoryDisplayInd];o.model.dragY+=n.event.dy;var s=o.model.dragY,l=o.model.displayInd,c=a.categories,u=c[l-1],f=c[l+1];void 0!==u&&s<u.y+u.height/2&&(o.model.displayInd=u.model.displayInd,u.model.displayInd=l),void 0!==f&&s+o.height>f.y+f.height/2&&(o.model.displayInd=f.model.displayInd,f.model.displayInd=l),t.dragCategoryDisplayInd=o.model.displayInd}if(null===t.dragCategoryDisplayInd||\"freeform\"===t.parcatsViewModel.arrangement){a.model.dragX=n.event.x;var h=t.parcatsViewModel.dimensions[r],p=t.parcatsViewModel.dimensions[i];void 0!==h&&a.model.dragX<h.x+h.width&&(a.model.displayInd=h.model.displayInd,h.model.displayInd=e),void 0!==p&&a.model.dragX+a.width>p.x&&(a.model.displayInd=p.model.displayInd,p.model.displayInd=t.dragDimensionDisplayInd),t.dragDimensionDisplayInd=a.model.displayInd}j(t.parcatsViewModel),N(t.parcatsViewModel),R(t.parcatsViewModel),D(t.parcatsViewModel)}}function O(t){if(\"fixed\"!==t.parcatsViewModel.arrangement&&null!==t.dragDimensionDisplayInd){n.select(this).selectAll(\"text\").attr(\"font-weight\",\"normal\");var e={},r=z(t.parcatsViewModel),i=t.parcatsViewModel.model.dimensions.map((function(t){return t.displayInd})),o=t.initialDragDimensionDisplayInds.some((function(t,e){return t!==i[e]}));o&&i.forEach((function(r,n){var i=t.parcatsViewModel.model.dimensions[n].containerInd;e[\"dimensions[\"+i+\"].displayindex\"]=r}));var s=!1;if(null!==t.dragCategoryDisplayInd){var l=t.model.categories.map((function(t){return t.displayInd}));if(s=t.initialDragCategoryDisplayInds.some((function(t,e){return t!==l[e]}))){var c=t.model.categories.slice().sort((function(t,e){return t.displayInd-e.displayInd})),u=c.map((function(t){return t.categoryValue})),f=c.map((function(t){return t.categoryLabel}));e[\"dimensions[\"+t.model.containerInd+\"].categoryarray\"]=[u],e[\"dimensions[\"+t.model.containerInd+\"].ticktext\"]=[f],e[\"dimensions[\"+t.model.containerInd+\"].categoryorder\"]=\"array\"}}if(-1===t.parcatsViewModel.hoverinfoItems.indexOf(\"skip\")&&!t.dragHasMoved&&t.potentialClickBand&&(\"color\"===t.parcatsViewModel.hoveron?S(t.potentialClickBand,\"plotly_click\",n.event.sourceEvent):M(t.potentialClickBand,\"plotly_click\",n.event.sourceEvent)),t.model.dragX=null,null!==t.dragCategoryDisplayInd)t.parcatsViewModel.dimensions[t.dragDimensionDisplayInd].categories[t.dragCategoryDisplayInd].model.dragY=null,t.dragCategoryDisplayInd=null;t.dragDimensionDisplayInd=null,t.parcatsViewModel.dragDimension=null,t.dragHasMoved=null,t.potentialClickBand=null,j(t.parcatsViewModel),N(t.parcatsViewModel),n.transition().duration(300).ease(\"cubic-in-out\").each((function(){R(t.parcatsViewModel,!0),D(t.parcatsViewModel,!0)})).each(\"end\",(function(){(o||s)&&a.restyle(t.parcatsViewModel.graphDiv,e,[r])}))}}function z(t){for(var e,r=t.graphDiv._fullData,n=0;n<r.length;n++)if(t.key===r[n].uid){e=n;break}return e}function D(t,e){var r;void 0===e&&(e=!1),t.pathSelection.data((function(t){return t.paths}),p),(r=t.pathSelection,e?r.transition():r).attr(\"d\",(function(t){return t.svgD}))}function R(t,e){function r(t){return e?t.transition():t}void 0===e&&(e=!1),t.dimensionSelection.data((function(t){return t.dimensions}),p);var i=t.dimensionSelection.selectAll(\"g.category\").data((function(t){return t.categories}),p);r(t.dimensionSelection).attr(\"transform\",(function(t){return l(t.x,0)})),r(i).attr(\"transform\",(function(t){return l(0,t.y)})),i.select(\".dimlabel\").text((function(t,e){return 0===e?t.parcatsViewModel.model.dimensions[t.model.dimensionInd].dimensionLabel:null})),i.select(\".catlabel\").attr(\"text-anchor\",(function(t){return d(t)?\"start\":\"end\"})).attr(\"x\",(function(t){return d(t)?t.width+5:-5})).each((function(t){var e,r;d(t)?(e=t.width+5,r=\"start\"):(e=-5,r=\"end\"),n.select(this).selectAll(\"tspan\").attr(\"x\",e).attr(\"text-anchor\",r)}));var a=i.selectAll(\"rect.bandrect\").data((function(t){return t.bands}),p),o=a.enter().append(\"rect\").attr(\"class\",\"bandrect\").attr(\"cursor\",\"move\").attr(\"stroke-opacity\",0).attr(\"fill\",(function(t){return t.color})).attr(\"fill-opacity\",0);a.attr(\"fill\",(function(t){return t.color})).attr(\"width\",(function(t){return t.width})).attr(\"height\",(function(t){return t.height})).attr(\"y\",(function(t){return t.y})),k(o),a.each((function(){s.raiseToTop(this)})),a.exit().remove()}function F(t,e,r){var n,i=r[0],a=e.margin||{l:80,r:80,t:100,b:80},o=i.trace,s=o.domain,l=e.width,c=e.height,u=Math.floor(l*(s.x[1]-s.x[0])),f=Math.floor(c*(s.y[1]-s.y[0])),h=s.x[0]*l+a.l,p=e.height-s.y[1]*e.height+a.t,d=o.line.shape;n=\"all\"===o.hoverinfo?[\"count\",\"probability\"]:(o.hoverinfo||\"\").split(\"+\");var g={trace:o,key:o.uid,model:i,x:h,y:p,width:u,height:f,hoveron:o.hoveron,hoverinfoItems:n,arrangement:o.arrangement,bundlecolors:o.bundlecolors,sortpaths:o.sortpaths,labelfont:o.labelfont,categorylabelfont:o.tickfont,pathShape:d,dragDimension:null,margin:a,paths:[],dimensions:[],graphDiv:t,traceSelection:null,pathSelection:null,dimensionSelection:null};return i.dimensions&&(j(g),N(g)),g}function B(t,e,r,n,a){var o,s,l=[],c=[];for(s=0;s<r.length-1;s++)o=i(r[s]+t[s],t[s+1]),l.push(o(a)),c.push(o(1-a));var u=\"M \"+t[0]+\",\"+e[0];for(u+=\"l\"+r[0]+\",0 \",s=1;s<r.length;s++)u+=\"C\"+l[s-1]+\",\"+e[s-1]+\" \"+c[s-1]+\",\"+e[s]+\" \"+t[s]+\",\"+e[s],u+=\"l\"+r[s]+\",0 \";for(u+=\"l0,\"+n+\" \",u+=\"l -\"+r[r.length-1]+\",0 \",s=r.length-2;s>=0;s--)u+=\"C\"+c[s]+\",\"+(e[s+1]+n)+\" \"+l[s]+\",\"+(e[s]+n)+\" \"+(t[s]+r[s])+\",\"+(e[s]+n),u+=\"l-\"+r[s]+\",0 \";return u+=\"Z\"}function N(t){var e=t.dimensions,r=t.model,n=e.map((function(t){return t.categories.map((function(t){return t.y}))})),i=t.model.dimensions.map((function(t){return t.categories.map((function(t){return t.displayInd}))})),a=t.model.dimensions.map((function(t){return t.displayInd})),o=t.dimensions.map((function(t){return t.model.dimensionInd})),s=e.map((function(t){return t.x})),l=e.map((function(t){return t.width})),c=[];for(var u in r.paths)r.paths.hasOwnProperty(u)&&c.push(r.paths[u]);function f(t){var e=t.categoryInds.map((function(t,e){return i[e][t]}));return o.map((function(t){return e[t]}))}c.sort((function(e,r){var n=f(e),i=f(r);return\"backward\"===t.sortpaths&&(n.reverse(),i.reverse()),n.push(e.valueInds[0]),i.push(r.valueInds[0]),t.bundlecolors&&(n.unshift(e.rawColor),i.unshift(r.rawColor)),n<i?-1:n>i?1:0}));for(var h=new Array(c.length),p=e[0].model.count,d=e[0].categories.map((function(t){return t.height})).reduce((function(t,e){return t+e})),g=0;g<c.length;g++){var m,v=c[g];m=p>0?d*(v.count/p):0;for(var y,x=new Array(n.length),b=0;b<v.categoryInds.length;b++){var _=v.categoryInds[b],w=i[b][_],T=a[b];x[T]=n[T][w],n[T][w]+=m;var k=t.dimensions[T].categories[w],A=k.bands.length,M=k.bands[A-1];if(void 0===M||v.rawColor!==M.rawColor){var S=void 0===M?0:M.y+M.height;k.bands.push({key:S,color:v.color,rawColor:v.rawColor,height:m,width:k.width,count:v.count,y:S,categoryViewModel:k,parcatsViewModel:t})}else{var E=k.bands[A-1];E.height+=m,E.count+=v.count}}y=\"hspline\"===t.pathShape?B(s,x,l,m,.5):B(s,x,l,m,0),h[g]={key:v.valueInds[0],model:v,height:m,leftXs:s,topYs:x,dimWidths:l,svgD:y,parcatsViewModel:t}}t.paths=h}function j(t){var e=t.model.dimensions.map((function(t){return{displayInd:t.displayInd,dimensionInd:t.dimensionInd}}));e.sort((function(t,e){return t.displayInd-e.displayInd}));var r=[];for(var n in e){var i=e[n].dimensionInd,a=t.model.dimensions[i];r.push(U(t,a))}t.dimensions=r}function U(t,e){var r,n=t.model.dimensions.length,i=e.displayInd;r=40+(n>1?(t.width-80-16)/(n-1):0)*i;var a,o,s,l,c,u=[],f=t.model.maxCats,h=e.categories.length,p=e.count,d=t.height-8*(f-1),g=8*(f-h)/2,m=e.categories.map((function(t){return{displayInd:t.displayInd,categoryInd:t.categoryInd}}));for(m.sort((function(t,e){return t.displayInd-e.displayInd})),c=0;c<h;c++)l=m[c].categoryInd,o=e.categories[l],a=p>0?o.count/p*d:0,s={key:o.valueInds[0],model:o,width:16,height:a,y:null!==o.dragY?o.dragY:g,bands:[],parcatsViewModel:t},g=g+a+8,u.push(s);return{key:e.dimensionInd,x:null!==e.dragX?e.dragX:r,y:0,width:16,model:e,categories:u,parcatsViewModel:t,dragCategoryDisplayInd:null,dragDimensionDisplayInd:null,initialDragDimensionDisplayInds:null,initialDragCategoryDisplayInds:null,dragHasMoved:null,potentialClickBand:null}}e.exports=function(t,e,r,n){h(r,t,n,e)}},{\"../../components/drawing\":688,\"../../components/fx\":706,\"../../lib\":803,\"../../lib/svg_text_utils\":829,\"../../plot_api/plot_api\":840,\"@plotly/d3\":58,\"d3-interpolate\":171,tinycolor2:598}],1179:[function(t,e,r){\"use 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n=t(\"../../components/colorscale/attributes\"),i=t(\"../../plots/cartesian/layout_attributes\"),a=t(\"../../plots/font_attributes\"),o=t(\"../../plots/domain\").attributes,s=t(\"../../lib/extend\").extendFlat,l=t(\"../../plot_api/plot_template\").templatedArray;e.exports={domain:o({name:\"parcoords\",trace:!0,editType:\"plot\"}),labelangle:{valType:\"angle\",dflt:0,editType:\"plot\"},labelside:{valType:\"enumerated\",values:[\"top\",\"bottom\"],dflt:\"top\",editType:\"plot\"},labelfont:a({editType:\"plot\"}),tickfont:a({editType:\"plot\"}),rangefont:a({editType:\"plot\"}),dimensions:l(\"dimension\",{label:{valType:\"string\",editType:\"plot\"},tickvals:s({},i.tickvals,{editType:\"plot\"}),ticktext:s({},i.ticktext,{editType:\"plot\"}),tickformat:s({},i.tickformat,{editType:\"plot\"}),visible:{valType:\"boolean\",dflt:!0,editType:\"plot\"},range:{valType:\"info_array\",items:[{valType:\"number\",editType:\"plot\"},{valType:\"number\",editType:\"plot\"}],editType:\"plot\"},constraintrange:{valType:\"info_array\",freeLength:!0,dimensions:\"1-2\",items:[{valType:\"any\",editType:\"plot\"},{valType:\"any\",editType:\"plot\"}],editType:\"plot\"},multiselect:{valType:\"boolean\",dflt:!0,editType:\"plot\"},values:{valType:\"data_array\",editType:\"calc\"},editType:\"calc\"}),line:s({editType:\"calc\"},n(\"line\",{colorscaleDflt:\"Viridis\",autoColorDflt:!1,editTypeOverride:\"calc\"}))}},{\"../../components/colorscale/attributes\":673,\"../../lib/extend\":793,\"../../plot_api/plot_template\":843,\"../../plots/cartesian/layout_attributes\":869,\"../../plots/domain\":882,\"../../plots/font_attributes\":883}],1181:[function(t,e,r){\"use 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r=e.brush,n=r.filter,a=r.svgBrush;a._dragging||(T(t,e),w(t,e),e.brush.svgBrush.wasDragged=!1),a._dragging=!1,i.event.sourceEvent.stopPropagation();var o=a.grabbingBar;if(a.grabbingBar=!1,a.grabLocation=void 0,e.parent.inBrushDrag=!1,y(),!a.wasDragged)return a.wasDragged=void 0,a.clickableOrdinalRange?r.filterSpecified&&e.multiselect?a.extent.push(a.clickableOrdinalRange):(a.extent=[a.clickableOrdinalRange],r.filterSpecified=!0):o?(a.extent=a.stayingIntervals,0===a.extent.length&&M(r)):M(r),a.brushCallback(e),b(t.parentNode),void a.brushEndCallback(r.filterSpecified?n.getConsolidated():[]);var s=function(){n.set(n.getConsolidated())};if(e.ordinal){var l=e.unitTickvals;l[l.length-1]<l[0]&&l.reverse(),a.newExtent=[p(0,l,a.newExtent[0],a.stayingIntervals),p(1,l,a.newExtent[1],a.stayingIntervals)];var c=a.newExtent[1]>a.newExtent[0];a.extent=a.stayingIntervals.concat(c?[a.newExtent]:[]),a.extent.length||M(r),a.brushCallback(e),c?b(t.parentNode,s):(s(),b(t.parentNode))}else 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t.slice()}))}(e).slice();e.filter.set(r),o()}),brushEndCallback:a}}},ensureAxisBrush:function(t,e){var r=t.selectAll(\".\"+n.cn.axisBrush).data(o,a);r.enter().append(\"g\").classed(n.cn.axisBrush,!0),function(t,e){var r=t.selectAll(\".background\").data(o);r.enter().append(\"rect\").classed(\"background\",!0).call(d).call(g).style(\"pointer-events\",\"auto\").attr(\"transform\",l(0,n.verticalPadding)),r.call(k).attr(\"height\",(function(t){return t.height-n.verticalPadding}));var i=t.selectAll(\".highlight-shadow\").data(o);i.enter().append(\"line\").classed(\"highlight-shadow\",!0).attr(\"x\",-n.bar.width/2).attr(\"stroke-width\",n.bar.width+n.bar.strokeWidth).attr(\"stroke\",e).attr(\"opacity\",n.bar.strokeOpacity).attr(\"stroke-linecap\",\"butt\"),i.attr(\"y1\",(function(t){return t.height})).call(x);var a=t.selectAll(\".highlight\").data(o);a.enter().append(\"line\").classed(\"highlight\",!0).attr(\"x\",-n.bar.width/2).attr(\"stroke-width\",n.bar.width-n.bar.strokeWidth).attr(\"stroke\",n.bar.fillColor).attr(\"opacity\",n.bar.fillOpacity).attr(\"stroke-linecap\",\"butt\"),a.attr(\"y1\",(function(t){return t.height})).call(x)}(r,e)},cleanRanges:function(t,e){if(Array.isArray(t[0])?(t=t.map((function(t){return t.sort(s)})),t=e.multiselect?S(t.sort(A)):[t[0]]):t=[t.sort(s)],e.tickvals){var r=e.tickvals.slice().sort(s);if(!(t=t.map((function(t){var e=[p(0,r,t[0],[]),p(1,r,t[1],[])];if(e[1]>e[0])return e})).filter((function(t){return t}))).length)return}return t.length>1?t:t[0]}}},{\"../../lib\":803,\"../../lib/gup\":800,\"./constants\":1184,\"@plotly/d3\":58}],1182:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"../../plots/get_data\").getModuleCalcData,a=t(\"./plot\"),o=t(\"../../constants/xmlns_namespaces\");r.name=\"parcoords\",r.plot=function(t){var e=i(t.calcdata,\"parcoords\")[0];e.length&&a(t,e)},r.clean=function(t,e,r,n){var i=n._has&&n._has(\"parcoords\"),a=e._has&&e._has(\"parcoords\");i&&!a&&(n._paperdiv.selectAll(\".parcoords\").remove(),n._glimages.selectAll(\"*\").remove())},r.toSVG=function(t){var e=t._fullLayout._glimages,r=n.select(t).selectAll(\".svg-container\");r.filter((function(t,e){return e===r.size()-1})).selectAll(\".gl-canvas-context, .gl-canvas-focus\").each((function(){var t=this.toDataURL(\"image/png\");e.append(\"svg:image\").attr({xmlns:o.svg,\"xlink:href\":t,preserveAspectRatio:\"none\",x:0,y:0,width:this.style.width,height:this.style.height})})),window.setTimeout((function(){n.selectAll(\"#filterBarPattern\").attr(\"id\",\"filterBarPattern\")}),60)}},{\"../../constants/xmlns_namespaces\":780,\"../../plots/get_data\":891,\"./plot\":1191,\"@plotly/d3\":58}],1183:[function(t,e,r){\"use strict\";var n=t(\"../../lib\").isArrayOrTypedArray,i=t(\"../../components/colorscale\"),a=t(\"../../lib/gup\").wrap;e.exports=function(t,e){var r,o;return i.hasColorscale(e,\"line\")&&n(e.line.color)?(r=e.line.color,o=i.extractOpts(e.line).colorscale,i.calc(t,e,{vals:r,containerStr:\"line\",cLetter:\"c\"})):(r=function(t){for(var e=new Array(t),r=0;r<t;r++)e[r]=.5;return e}(e._length),o=[[0,e.line.color],[1,e.line.color]]),a({lineColor:r,cscale:o})}},{\"../../components/colorscale\":678,\"../../lib\":803,\"../../lib/gup\":800}],1184:[function(t,e,r){\"use 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n=t(\"../../lib\").isTypedArray;r.convertTypedArray=function(t){return n(t)?Array.prototype.slice.call(t):t},r.isOrdinal=function(t){return!!t.tickvals},r.isVisible=function(t){return t.visible||!(\"visible\"in t)}},{\"../../lib\":803}],1187:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),calc:t(\"./calc\"),plot:t(\"./plot\"),colorbar:{container:\"line\",min:\"cmin\",max:\"cmax\"},moduleType:\"trace\",name:\"parcoords\",basePlotModule:t(\"./base_plot\"),categories:[\"gl\",\"regl\",\"noOpacity\",\"noHover\"],meta:{}}},{\"./attributes\":1180,\"./base_plot\":1182,\"./calc\":1183,\"./defaults\":1185,\"./plot\":1191}],1188:[function(t,e,r){\"use strict\";var n=t(\"glslify\"),i=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nattribute vec4 p01_04, p05_08, p09_12, p13_16,\\n               p17_20, p21_24, p25_28, p29_32,\\n               p33_36, p37_40, p41_44, p45_48,\\n               p49_52, p53_56, p57_60, colors;\\n\\nuniform mat4 dim0A, dim1A, dim0B, dim1B, dim0C, dim1C, dim0D, dim1D,\\n             loA, hiA, loB, hiB, loC, hiC, loD, hiD;\\n\\nuniform vec2 resolution, viewBoxPos, viewBoxSize;\\nuniform float maskHeight;\\nuniform float drwLayer; // 0: context, 1: focus, 2: pick\\nuniform vec4 contextColor;\\nuniform sampler2D maskTexture, palette;\\n\\nbool isPick    = (drwLayer > 1.5);\\nbool isContext = (drwLayer < 0.5);\\n\\nconst vec4 ZEROS = vec4(0.0, 0.0, 0.0, 0.0);\\nconst vec4 UNITS = vec4(1.0, 1.0, 1.0, 1.0);\\n\\nfloat val(mat4 p, mat4 v) {\\n    return dot(matrixCompMult(p, v) * UNITS, UNITS);\\n}\\n\\nfloat axisY(float ratio, mat4 A, mat4 B, mat4 C, mat4 D) {\\n    float y1 = val(A, dim0A) + val(B, dim0B) + val(C, dim0C) + val(D, dim0D);\\n    float y2 = val(A, dim1A) + val(B, dim1B) + val(C, dim1C) + val(D, dim1D);\\n    return y1 * (1.0 - ratio) + y2 * ratio;\\n}\\n\\nint iMod(int a, int b) {\\n    return a - b * (a / b);\\n}\\n\\nbool fOutside(float p, float lo, float hi) {\\n    return (lo < hi) && (lo > p || p > hi);\\n}\\n\\nbool vOutside(vec4 p, vec4 lo, vec4 hi) {\\n    return (\\n        fOutside(p[0], lo[0], hi[0]) ||\\n        fOutside(p[1], lo[1], hi[1]) ||\\n        fOutside(p[2], lo[2], hi[2]) ||\\n        fOutside(p[3], lo[3], hi[3])\\n    );\\n}\\n\\nbool mOutside(mat4 p, mat4 lo, mat4 hi) {\\n    return (\\n        vOutside(p[0], lo[0], hi[0]) ||\\n        vOutside(p[1], lo[1], hi[1]) ||\\n        vOutside(p[2], lo[2], hi[2]) ||\\n        vOutside(p[3], lo[3], hi[3])\\n    );\\n}\\n\\nbool outsideBoundingBox(mat4 A, mat4 B, mat4 C, mat4 D) {\\n    return mOutside(A, loA, hiA) ||\\n           mOutside(B, loB, hiB) ||\\n           mOutside(C, loC, hiC) ||\\n           mOutside(D, loD, hiD);\\n}\\n\\nbool outsideRasterMask(mat4 A, mat4 B, mat4 C, mat4 D) {\\n    mat4 pnts[4];\\n    pnts[0] = A;\\n    pnts[1] = B;\\n    pnts[2] = C;\\n    pnts[3] = D;\\n\\n    for(int i = 0; i < 4; ++i) {\\n        for(int j = 0; j < 4; ++j) {\\n            for(int k = 0; k < 4; ++k) {\\n                if(0 == iMod(\\n                    int(255.0 * texture2D(maskTexture,\\n                        vec2(\\n                            (float(i * 2 + j / 2) + 0.5) / 8.0,\\n                            (pnts[i][j][k] * (maskHeight - 1.0) + 1.0) / maskHeight\\n                        ))[3]\\n                    ) / int(pow(2.0, float(iMod(j * 4 + k, 8)))),\\n                    2\\n                )) return true;\\n            }\\n        }\\n    }\\n    return false;\\n}\\n\\nvec4 position(bool isContext, float v, mat4 A, mat4 B, mat4 C, mat4 D) {\\n    float x = 0.5 * sign(v) + 0.5;\\n    float y = axisY(x, A, B, C, D);\\n    float z = 1.0 - abs(v);\\n\\n    z += isContext ? 0.0 : 2.0 * float(\\n        outsideBoundingBox(A, B, C, D) ||\\n        outsideRasterMask(A, B, C, D)\\n    );\\n\\n    return vec4(\\n        2.0 * (vec2(x, y) * viewBoxSize + viewBoxPos) / resolution - 1.0,\\n        z,\\n        1.0\\n    );\\n}\\n\\nvoid main() {\\n    mat4 A = mat4(p01_04, p05_08, p09_12, p13_16);\\n    mat4 B = mat4(p17_20, p21_24, p25_28, p29_32);\\n    mat4 C = mat4(p33_36, p37_40, p41_44, p45_48);\\n    mat4 D = mat4(p49_52, p53_56, p57_60, ZEROS);\\n\\n    float v = colors[3];\\n\\n    gl_Position = position(isContext, v, A, B, C, D);\\n\\n    fragColor =\\n        isContext ? vec4(contextColor) :\\n        isPick ? vec4(colors.rgb, 1.0) : texture2D(palette, vec2(abs(v), 0.5));\\n}\\n\"]),a=n([\"precision highp float;\\n#define GLSLIFY 1\\n\\nvarying vec4 fragColor;\\n\\nvoid main() {\\n    gl_FragColor = fragColor;\\n}\\n\"]),o=t(\"./constants\").maxDimensionCount,s=t(\"../../lib\"),l=new Uint8Array(4),c=new Uint8Array(4),u={shape:[256,1],format:\"rgba\",type:\"uint8\",mag:\"nearest\",min:\"nearest\"};function f(t,e,r,n,i){var a=t._gl;a.enable(a.SCISSOR_TEST),a.scissor(e,r,n,i),t.clear({color:[0,0,0,0],depth:1})}function h(t,e,r,n,i,a){var o=a.key;r.drawCompleted||(!function(t){t.read({x:0,y:0,width:1,height:1,data:l})}(t),r.drawCompleted=!0),function s(l){var c=Math.min(n,i-l*n);0===l&&(window.cancelAnimationFrame(r.currentRafs[o]),delete r.currentRafs[o],f(t,a.scissorX,a.scissorY,a.scissorWidth,a.viewBoxSize[1])),r.clearOnly||(a.count=2*c,a.offset=2*l*n,e(a),l*n+c<i&&(r.currentRafs[o]=window.requestAnimationFrame((function(){s(l+1)}))),r.drawCompleted=!1)}(0)}function p(t,e){for(var r=new Array(256),n=0;n<256;n++)r[n]=t(n/255).concat(e);return r}function d(t,e){return(t>>>8*e)%256/255}function g(t,e,r){for(var n=new Array(8*e),i=0,a=0;a<e;a++)for(var o=0;o<2;o++)for(var s=0;s<4;s++){var l=4*t+s,c=r[64*a+l];63===l&&0===o&&(c*=-1),n[i++]=c}return n}function m(t){var e=\"0\"+t;return e.substr(e.length-2)}function v(t){return t<o?\"p\"+m(t+1)+\"_\"+m(t+4):\"colors\"}function y(t,e,r,n,i,a,o,l,c,u,f,h,p,d){for(var g=[[],[]],m=0;m<64;m++)g[0][m]=m===i?1:0,g[1][m]=m===a?1:0;o*=d,l*=d,c*=d,u*=d;var v=t.lines.canvasOverdrag*d,y=t.domain,x=t.canvasWidth*d,b=t.canvasHeight*d,_=t.pad.l*d,w=t.pad.b*d,T=t.layoutHeight*d,k=t.layoutWidth*d,A=t.deselectedLines.color;return s.extendFlat({key:f,resolution:[x,b],viewBoxPos:[o+v,l],viewBoxSize:[c,u],i0:i,i1:a,dim0A:g[0].slice(0,16),dim0B:g[0].slice(16,32),dim0C:g[0].slice(32,48),dim0D:g[0].slice(48,64),dim1A:g[1].slice(0,16),dim1B:g[1].slice(16,32),dim1C:g[1].slice(32,48),dim1D:g[1].slice(48,64),drwLayer:h,contextColor:[A[0]/255,A[1]/255,A[2]/255,A[3]<1?A[3]:Math.max(1/255,Math.pow(1/t.lines.color.length,1/3))],scissorX:(n===e?0:o+v)+(_-v)+k*y.x[0],scissorWidth:(n===r?x-o+v:c+.5)+(n===e?o+v:0),scissorY:l+w+T*y.y[0],scissorHeight:u,viewportX:_-v+k*y.x[0],viewportY:w+T*y.y[0],viewportWidth:x,viewportHeight:b},p)}function x(t){var e=Math.max(0,Math.floor(2047*t[0]),0),r=Math.min(2047,Math.ceil(2047*t[1]),2047);return[Math.min(e,r),Math.max(e,r)]}e.exports=function(t,e){var r,n,l,m,b,_=e.context,w=e.pick,T=e.regl,k=T._gl,A=k.getParameter(k.ALIASED_LINE_WIDTH_RANGE),M=Math.max(A[0],Math.min(A[1],e.viewModel.plotGlPixelRatio)),S={currentRafs:{},drawCompleted:!0,clearOnly:!1},E=function(t){for(var e={},r=0;r<=o;r+=4)e[v(r)]=t.buffer({usage:\"dynamic\",type:\"float\",data:new Uint8Array(0)});return e}(T),L=T.texture(u),C=[];I(e);var P=T({profile:!1,blend:{enable:_,func:{srcRGB:\"src alpha\",dstRGB:\"one minus src alpha\",srcAlpha:1,dstAlpha:1},equation:{rgb:\"add\",alpha:\"add\"},color:[0,0,0,0]},depth:{enable:!_,mask:!0,func:\"less\",range:[0,1]},cull:{enable:!0,face:\"back\"},scissor:{enable:!0,box:{x:T.prop(\"scissorX\"),y:T.prop(\"scissorY\"),width:T.prop(\"scissorWidth\"),height:T.prop(\"scissorHeight\")}},viewport:{x:T.prop(\"viewportX\"),y:T.prop(\"viewportY\"),width:T.prop(\"viewportWidth\"),height:T.prop(\"viewportHeight\")},dither:!1,vert:i,frag:a,primitive:\"lines\",lineWidth:M,attributes:E,uniforms:{resolution:T.prop(\"resolution\"),viewBoxPos:T.prop(\"viewBoxPos\"),viewBoxSize:T.prop(\"viewBoxSize\"),dim0A:T.prop(\"dim0A\"),dim1A:T.prop(\"dim1A\"),dim0B:T.prop(\"dim0B\"),dim1B:T.prop(\"dim1B\"),dim0C:T.prop(\"dim0C\"),dim1C:T.prop(\"dim1C\"),dim0D:T.prop(\"dim0D\"),dim1D:T.prop(\"dim1D\"),loA:T.prop(\"loA\"),hiA:T.prop(\"hiA\"),loB:T.prop(\"loB\"),hiB:T.prop(\"hiB\"),loC:T.prop(\"loC\"),hiC:T.prop(\"hiC\"),loD:T.prop(\"loD\"),hiD:T.prop(\"hiD\"),palette:L,contextColor:T.prop(\"contextColor\"),maskTexture:T.prop(\"maskTexture\"),drwLayer:T.prop(\"drwLayer\"),maskHeight:T.prop(\"maskHeight\")},offset:T.prop(\"offset\"),count:T.prop(\"count\")});function I(t){r=t.model,n=t.viewModel,l=n.dimensions.slice(),m=l[0]?l[0].values.length:0;var e=r.lines,i=w?e.color.map((function(t,r){return r/e.color.length})):e.color,a=function(t,e,r){for(var n,i=new Array(t*(o+4)),a=0,s=0;s<t;s++){for(var l=0;l<o;l++)i[a++]=l<e.length?e[l].paddedUnitValues[s]:.5;i[a++]=d(s,2),i[a++]=d(s,1),i[a++]=d(s,0),i[a++]=(n=r[s],Math.max(1e-6,Math.min(.999999,n)))}return i}(m,l,i);!function(t,e,r){for(var n=0;n<=o;n+=4)t[v(n)](g(n/4,e,r))}(E,m,a),_||w||(L=T.texture(s.extendFlat({data:p(r.unitToColor,255)},u)))}return{render:function(t,e,n){var i,a,o,s=t.length,c=1/0,u=-1/0;for(i=0;i<s;i++)t[i].dim0.canvasX<c&&(c=t[i].dim0.canvasX,a=i),t[i].dim1.canvasX>u&&(u=t[i].dim1.canvasX,o=i);0===s&&f(T,0,0,r.canvasWidth,r.canvasHeight);var p=function(t){var e,r,n,i=[[],[]];for(n=0;n<64;n++){var a=!t&&n<l.length?l[n].brush.filter.getBounds():[-1/0,1/0];i[0][n]=a[0],i[1][n]=a[1]}var o=new Array(16384);for(e=0;e<16384;e++)o[e]=255;if(!t)for(e=0;e<l.length;e++){var s=e%8,c=(e-s)/8,u=Math.pow(2,s),f=l[e].brush.filter.get();if(!(f.length<2)){var h=x(f[0])[1];for(r=1;r<f.length;r++){var p=x(f[r]);for(n=h+1;n<p[0];n++)o[8*n+c]&=~u;h=Math.max(h,p[1])}}}var d={shape:[8,2048],format:\"alpha\",type:\"uint8\",mag:\"nearest\",min:\"nearest\",data:o};return b?b(d):b=T.texture(d),{maskTexture:b,maskHeight:2048,loA:i[0].slice(0,16),loB:i[0].slice(16,32),loC:i[0].slice(32,48),loD:i[0].slice(48,64),hiA:i[1].slice(0,16),hiB:i[1].slice(16,32),hiC:i[1].slice(32,48),hiD:i[1].slice(48,64)}}(_);for(i=0;i<s;i++){var d=t[i],g=d.dim0.crossfilterDimensionIndex,v=d.dim1.crossfilterDimensionIndex,k=d.canvasX,A=d.canvasY,M=k+d.panelSizeX,E=d.plotGlPixelRatio;if(e||!C[g]||C[g][0]!==k||C[g][1]!==M){C[g]=[k,M];var L=y(r,a,o,i,g,v,k,A,d.panelSizeX,d.panelSizeY,d.dim0.crossfilterDimensionIndex,_?0:w?2:1,p,E);S.clearOnly=n;var I=e?r.lines.blockLineCount:m;h(T,P,S,I,m,L)}}},readPixel:function(t,e){return T.read({x:t,y:e,width:1,height:1,data:c}),c},readPixels:function(t,e,r,n){var i=new Uint8Array(4*r*n);return T.read({x:t,y:e,width:r,height:n,data:i}),i},destroy:function(){for(var e in t.style[\"pointer-events\"]=\"none\",L.destroy(),b&&b.destroy(),E)E[e].destroy()},update:I}}},{\"../../lib\":803,\"./constants\":1184,glslify:442}],1189:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n){var i,a;for(n||(n=1/0),i=0;i<e.length;i++)(a=e[i]).visible&&(n=Math.min(n,a[r].length));for(n===1/0&&(n=0),t._length=n,i=0;i<e.length;i++)(a=e[i]).visible&&(a._length=n);return n}},{}],1190:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"../../lib\"),a=i.numberFormat,o=t(\"color-rgba\"),s=t(\"../../plots/cartesian/axes\"),l=i.strRotate,c=i.strTranslate,u=t(\"../../lib/svg_text_utils\"),f=t(\"../../components/drawing\"),h=t(\"../../components/colorscale\"),p=t(\"../../lib/gup\"),d=p.keyFun,g=p.repeat,m=p.unwrap,v=t(\"./helpers\"),y=t(\"./constants\"),x=t(\"./axisbrush\"),b=t(\"./lines\");function _(t,e,r){return i.aggNums(t,null,e,r)}function w(t,e){return k(_(Math.min,t,e),_(Math.max,t,e))}function T(t){var e=t.range;return e?k(e[0],e[1]):w(t.values,t._length)}function k(t,e){return!isNaN(t)&&isFinite(t)||(t=0),!isNaN(e)&&isFinite(e)||(e=0),t===e&&(0===t?(t-=1,e+=1):(t*=.9,e*=1.1)),[t,e]}function A(t,e,r,i,o){var s,l,c=T(r);return i?n.scale.ordinal().domain(i.map((s=a(r.tickformat),l=o,l?function(t,e){var r=l[e];return null==r?s(t):r}:s))).range(i.map((function(r){var n=(r-c[0])/(c[1]-c[0]);return t-e+n*(2*e-t)}))):n.scale.linear().domain(c).range([t-e,e])}function M(t){if(t.tickvals){var e=T(t);return n.scale.ordinal().domain(t.tickvals).range(t.tickvals.map((function(t){return(t-e[0])/(e[1]-e[0])})))}}function S(t){var e=t.map((function(t){return t[0]})),r=t.map((function(t){var e=o(t[1]);return n.rgb(\"rgb(\"+e[0]+\",\"+e[1]+\",\"+e[2]+\")\")})),i=\"rgb\".split(\"\").map((function(t){return n.scale.linear().clamp(!0).domain(e).range(r.map((i=t,function(t){return t[i]})));var i}));return function(t){return i.map((function(e){return e(t)}))}}function E(t){return t.dimensions.some((function(t){return t.brush.filterSpecified}))}function L(t,e,r){var a=m(e),s=a.trace,l=v.convertTypedArray(a.lineColor),c=s.line,u={color:o(y.deselectedLineColor)},f=h.extractOpts(c),p=f.reversescale?h.flipScale(a.cscale):a.cscale,d=s.domain,g=s.dimensions,x=t.width,b=s.labelangle,_=s.labelside,w=s.labelfont,k=s.tickfont,A=s.rangefont,M=i.extendDeepNoArrays({},c,{color:l.map(n.scale.linear().domain(T({values:l,range:[f.min,f.max],_length:s._length}))),blockLineCount:y.blockLineCount,canvasOverdrag:y.overdrag*y.canvasPixelRatio}),E=Math.floor(x*(d.x[1]-d.x[0])),L=Math.floor(t.height*(d.y[1]-d.y[0])),C=t.margin||{l:80,r:80,t:100,b:80},P=E,I=L;return{key:r,colCount:g.filter(v.isVisible).length,dimensions:g,tickDistance:y.tickDistance,unitToColor:S(p),lines:M,deselectedLines:u,labelAngle:b,labelSide:_,labelFont:w,tickFont:k,rangeFont:A,layoutWidth:x,layoutHeight:t.height,domain:d,translateX:d.x[0]*x,translateY:t.height-d.y[1]*t.height,pad:C,canvasWidth:P*y.canvasPixelRatio+2*M.canvasOverdrag,canvasHeight:I*y.canvasPixelRatio,width:P,height:I,canvasPixelRatio:y.canvasPixelRatio}}function C(t,e,r){var o=r.width,s=r.height,l=r.dimensions,c=r.canvasPixelRatio,u=function(t){return o*t/Math.max(1,r.colCount-1)},f=y.verticalPadding/s,h=function(t,e){return n.scale.linear().range([e,t-e])}(s,y.verticalPadding),p={key:r.key,xScale:u,model:r,inBrushDrag:!1},d={};return p.dimensions=l.filter(v.isVisible).map((function(o,l){var g=function(t,e){return n.scale.linear().domain(T(t)).range([e,1-e])}(o,f),m=d[o.label];d[o.label]=(m||0)+1;var b=o.label+(m?\"__\"+m:\"\"),_=o.constraintrange,w=_&&_.length;w&&!Array.isArray(_[0])&&(_=[_]);var k=w?_.map((function(t){return t.map(g)})):[[-1/0,1/0]],S=o.values;S.length>o._length&&(S=S.slice(0,o._length));var L,C=o.tickvals;function P(t,e){return{val:t,text:L[e]}}function I(t,e){return t.val-e.val}if(Array.isArray(C)&&C.length){L=o.ticktext,Array.isArray(L)&&L.length?L.length>C.length?L=L.slice(0,C.length):C.length>L.length&&(C=C.slice(0,L.length)):L=C.map(a(o.tickformat));for(var O=1;O<C.length;O++)if(C[O]<C[O-1]){for(var z=C.map(P).sort(I),D=0;D<C.length;D++)C[D]=z[D].val,L[D]=z[D].text;break}}else C=void 0;return S=v.convertTypedArray(S),{key:b,label:o.label,tickFormat:o.tickformat,tickvals:C,ticktext:L,ordinal:v.isOrdinal(o),multiselect:o.multiselect,xIndex:l,crossfilterDimensionIndex:l,visibleIndex:o._index,height:s,values:S,paddedUnitValues:S.map(g),unitTickvals:C&&C.map(g),xScale:u,x:u(l),canvasX:u(l)*c,unitToPaddedPx:h,domainScale:A(s,y.verticalPadding,o,C,L),ordinalScale:M(o),parent:p,model:r,brush:x.makeBrush(t,w,k,(function(){t.linePickActive(!1)}),(function(){var e=p;e.focusLayer&&e.focusLayer.render(e.panels,!0);var r=E(e);!t.contextShown()&&r?(e.contextLayer&&e.contextLayer.render(e.panels,!0),t.contextShown(!0)):t.contextShown()&&!r&&(e.contextLayer&&e.contextLayer.render(e.panels,!0,!0),t.contextShown(!1))}),(function(r){if(p.focusLayer.render(p.panels,!0),p.pickLayer&&p.pickLayer.render(p.panels,!0),t.linePickActive(!0),e&&e.filterChanged){var n=g.invert,a=r.map((function(t){return t.map(n).sort(i.sorterAsc)})).sort((function(t,e){return t[0]-e[0]}));e.filterChanged(p.key,o._index,a)}}))}})),p}function P(t){t.classed(y.cn.axisExtentText,!0).attr(\"text-anchor\",\"middle\").style(\"cursor\",\"default\")}function I(t,e){var r=\"top\"===e?1:-1,n=t*Math.PI/180;return{dir:r,dx:Math.sin(n),dy:Math.cos(n),degrees:t}}function O(t,e,r){for(var n=e.panels||(e.panels=[]),i=t.data(),a=0;a<i.length-1;a++){var o=n[a]||(n[a]={}),s=i[a],l=i[a+1];o.dim0=s,o.dim1=l,o.canvasX=s.canvasX,o.panelSizeX=l.canvasX-s.canvasX,o.panelSizeY=e.model.canvasHeight,o.y=0,o.canvasY=0,o.plotGlPixelRatio=r}}function z(t,e){return s.tickText(t._ax,e,!1).text}function D(t,e){if(t.ordinal)return\"\";var r=t.domainScale.domain(),n=r[e?r.length-1:0];return z(t.model.dimensions[t.visibleIndex],n)}e.exports=function(t,e,r,a){var o=t._fullLayout,h=o._toppaper,p=o._glcontainer,_=t._context.plotGlPixelRatio,T=t._fullLayout.paper_bgcolor;!function(t){for(var e=0;e<t.length;e++)for(var 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n=t(\"../../plots/attributes\"),i=t(\"../../plots/domain\").attributes,a=t(\"../../plots/font_attributes\"),o=t(\"../../components/color/attributes\"),s=t(\"../../plots/template_attributes\").hovertemplateAttrs,l=t(\"../../plots/template_attributes\").texttemplateAttrs,c=t(\"../../lib/extend\").extendFlat,u=a({editType:\"plot\",arrayOk:!0,colorEditType:\"plot\"});e.exports={labels:{valType:\"data_array\",editType:\"calc\"},label0:{valType:\"number\",dflt:0,editType:\"calc\"},dlabel:{valType:\"number\",dflt:1,editType:\"calc\"},values:{valType:\"data_array\",editType:\"calc\"},marker:{colors:{valType:\"data_array\",editType:\"calc\"},line:{color:{valType:\"color\",dflt:o.defaultLine,arrayOk:!0,editType:\"style\"},width:{valType:\"number\",min:0,dflt:0,arrayOk:!0,editType:\"style\"},editType:\"calc\"},editType:\"calc\"},text:{valType:\"data_array\",editType:\"plot\"},hovertext:{valType:\"string\",dflt:\"\",arrayOk:!0,editType:\"style\"},scalegroup:{valType:\"string\",dflt:\"\",editType:\"calc\"},textinfo:{valType:\"flaglist\",flags:[\"label\",\"text\",\"value\",\"percent\"],extras:[\"none\"],editType:\"calc\"},hoverinfo:c({},n.hoverinfo,{flags:[\"label\",\"text\",\"value\",\"percent\",\"name\"]}),hovertemplate:s({},{keys:[\"label\",\"color\",\"value\",\"percent\",\"text\"]}),texttemplate:l({editType:\"plot\"},{keys:[\"label\",\"color\",\"value\",\"percent\",\"text\"]}),textposition:{valType:\"enumerated\",values:[\"inside\",\"outside\",\"auto\",\"none\"],dflt:\"auto\",arrayOk:!0,editType:\"plot\"},textfont:c({},u,{}),insidetextorientation:{valType:\"enumerated\",values:[\"horizontal\",\"radial\",\"tangential\",\"auto\"],dflt:\"auto\",editType:\"plot\"},insidetextfont:c({},u,{}),outsidetextfont:c({},u,{}),automargin:{valType:\"boolean\",dflt:!1,editType:\"plot\"},title:{text:{valType:\"string\",dflt:\"\",editType:\"plot\"},font:c({},u,{}),position:{valType:\"enumerated\",values:[\"top 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r,i,a=[],o=t._fullLayout,l=o.hiddenlabels||[],c=e.labels,u=e.marker.colors||[],f=e.values,h=e._length,p=e._hasValues&&h;if(e.dlabel)for(c=new Array(h),r=0;r<h;r++)c[r]=String(e.label0+r*e.dlabel);var d={},g=s(o[\"_\"+e.type+\"colormap\"]),m=0,v=!1;for(r=0;r<h;r++){var y,x,b;if(p){if(y=f[r],!n(y))continue;if((y=+y)<0)continue}else y=1;void 0!==(x=c[r])&&\"\"!==x||(x=r);var _=d[x=String(x)];void 0===_?(d[x]=a.length,(b=-1!==l.indexOf(x))||(m+=y),a.push({v:y,label:x,color:g(u[r],x),i:r,pts:[r],hidden:b})):(v=!0,(i=a[_]).v+=y,i.pts.push(r),i.hidden||(m+=y),!1===i.color&&u[r]&&(i.color=g(u[r],x)))}return(\"funnelarea\"===e.type?v:e.sort)&&a.sort((function(t,e){return e.v-t.v})),a[0]&&(a[0].vTotal=m),a},crossTraceCalc:function(t,e){var r=(e||{}).type;r||(r=\"pie\");var n=t._fullLayout,i=t.calcdata,a=n[r+\"colorway\"],s=n[\"_\"+r+\"colormap\"];n[\"extend\"+r+\"colors\"]&&(a=l(a,o));for(var c=0,u=0;u<i.length;u++){var f=i[u];if(f[0].trace.type===r)for(var h=0;h<f.length;h++){var p=f[h];!1===p.color&&(s[p.label]?p.color=s[p.label]:(s[p.label]=p.color=a[c%a.length],c++))}}},makePullColorFn:s,generateExtendedColors:l}},{\"../../components/color\":666,\"fast-isnumeric\":249,tinycolor2:598}],1195:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),i=t(\"../../lib\"),a=t(\"./attributes\"),o=t(\"../../plots/domain\").defaults,s=t(\"../bar/defaults\").handleText;function l(t,e){var r=Array.isArray(t),a=i.isArrayOrTypedArray(e),o=Math.min(r?t.length:1/0,a?e.length:1/0);if(isFinite(o)||(o=0),o&&a){for(var s,l=0;l<o;l++){var c=e[l];if(n(c)&&c>0){s=!0;break}}s||(o=0)}return{hasLabels:r,hasValues:a,len:o}}e.exports={handleLabelsAndValues:l,supplyDefaults:function(t,e,r,n){function c(r,n){return i.coerce(t,e,a,r,n)}var u=l(c(\"labels\"),c(\"values\")),f=u.len;if(e._hasLabels=u.hasLabels,e._hasValues=u.hasValues,!e._hasLabels&&e._hasValues&&(c(\"label0\"),c(\"dlabel\")),f){e._length=f,c(\"marker.line.width\")&&c(\"marker.line.color\"),c(\"marker.colors\"),c(\"scalegroup\");var h,p=c(\"text\"),d=c(\"texttemplate\");if(d||(h=c(\"textinfo\",Array.isArray(p)?\"text+percent\":\"percent\")),c(\"hovertext\"),c(\"hovertemplate\"),d||h&&\"none\"!==h){var g=c(\"textposition\");s(t,e,n,c,g,{moduleHasSelected:!1,moduleHasUnselected:!1,moduleHasConstrain:!1,moduleHasCliponaxis:!1,moduleHasTextangle:!1,moduleHasInsideanchor:!1}),(Array.isArray(g)||\"auto\"===g||\"outside\"===g)&&c(\"automargin\"),(\"inside\"===g||\"auto\"===g||Array.isArray(g))&&c(\"insidetextorientation\")}o(e,n,c);var m=c(\"hole\");if(c(\"title.text\")){var v=c(\"title.position\",m?\"middle center\":\"top center\");m||\"middle center\"!==v||(e.title.position=\"top center\"),i.coerceFont(c,\"title.font\",n.font)}c(\"sort\"),c(\"direction\"),c(\"rotation\"),c(\"pull\")}else e.visible=!1}}},{\"../../lib\":803,\"../../plots/domain\":882,\"../bar/defaults\":945,\"./attributes\":1192,\"fast-isnumeric\":249}],1196:[function(t,e,r){\"use strict\";var n=t(\"../../components/fx/helpers\").appendArrayMultiPointValues;e.exports=function(t,e){var r={curveNumber:e.index,pointNumbers:t.pts,data:e._input,fullData:e,label:t.label,color:t.color,value:t.v,percent:t.percent,text:t.text,bbox:t.bbox,v:t.v};return 1===t.pts.length&&(r.pointNumber=r.i=t.pts[0]),n(r,e,t.pts),\"funnelarea\"===e.type&&(delete r.v,delete r.i),r}},{\"../../components/fx/helpers\":702}],1197:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");function i(t){return-1!==t.indexOf(\"e\")?t.replace(/[.]?0+e/,\"e\"):-1!==t.indexOf(\".\")?t.replace(/[.]?0+$/,\"\"):t}r.formatPiePercent=function(t,e){var r=i((100*t).toPrecision(3));return n.numSeparate(r,e)+\"%\"},r.formatPieValue=function(t,e){var r=i(t.toPrecision(10));return n.numSeparate(r,e)},r.getFirstFilled=function(t,e){if(Array.isArray(t))for(var r=0;r<e.length;r++){var n=t[e[r]];if(n||0===n||\"\"===n)return n}},r.castOption=function(t,e){return Array.isArray(t)?r.getFirstFilled(t,e):t||void 0},r.getRotationAngle=function(t){return(\"auto\"===t?0:t)*Math.PI/180}},{\"../../lib\":803}],1198:[function(t,e,r){\"use strict\";e.exports={attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\").supplyDefaults,supplyLayoutDefaults:t(\"./layout_defaults\"),layoutAttributes:t(\"./layout_attributes\"),calc:t(\"./calc\").calc,crossTraceCalc:t(\"./calc\").crossTraceCalc,plot:t(\"./plot\").plot,style:t(\"./style\"),styleOne:t(\"./style_one\"),moduleType:\"trace\",name:\"pie\",basePlotModule:t(\"./base_plot\"),categories:[\"pie-like\",\"pie\",\"showLegend\"],meta:{}}},{\"./attributes\":1192,\"./base_plot\":1193,\"./calc\":1194,\"./defaults\":1195,\"./layout_attributes\":1199,\"./layout_defaults\":1200,\"./plot\":1201,\"./style\":1202,\"./style_one\":1203}],1199:[function(t,e,r){\"use strict\";e.exports={hiddenlabels:{valType:\"data_array\",editType:\"calc\"},piecolorway:{valType:\"colorlist\",editType:\"calc\"},extendpiecolors:{valType:\"boolean\",dflt:!0,editType:\"calc\"}}},{}],1200:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"./layout_attributes\");e.exports=function(t,e){function r(r,a){return n.coerce(t,e,i,r,a)}r(\"hiddenlabels\"),r(\"piecolorway\",e.colorway),r(\"extendpiecolors\")}},{\"../../lib\":803,\"./layout_attributes\":1199}],1201:[function(t,e,r){\"use strict\";var n=t(\"@plotly/d3\"),i=t(\"../../plots/plots\"),a=t(\"../../components/fx\"),o=t(\"../../components/color\"),s=t(\"../../components/drawing\"),l=t(\"../../lib\"),c=l.strScale,u=l.strTranslate,f=t(\"../../lib/svg_text_utils\"),h=t(\"../bar/uniform_text\"),p=h.recordMinTextSize,d=h.clearMinTextSize,g=t(\"../bar/constants\").TEXTPAD,m=t(\"./helpers\"),v=t(\"./event_data\"),y=t(\"../../lib\").isValidTextValue;function x(t,e,r){var i=r[0],o=i.cx,s=i.cy,c=i.trace,u=\"funnelarea\"===c.type;\"_hasHoverLabel\"in c||(c._hasHoverLabel=!1),\"_hasHoverEvent\"in c||(c._hasHoverEvent=!1),t.on(\"mouseover\",(function(t){var r=e._fullLayout,f=e._fullData[c.index];if(!e._dragging&&!1!==r.hovermode){var h=f.hoverinfo;if(Array.isArray(h)&&(h=a.castHoverinfo({hoverinfo:[m.castOption(h,t.pts)],_module:c._module},r,0)),\"all\"===h&&(h=\"label+text+value+percent+name\"),f.hovertemplate||\"none\"!==h&&\"skip\"!==h&&h){var p=t.rInscribed||0,d=o+t.pxmid[0]*(1-p),g=s+t.pxmid[1]*(1-p),y=r.separators,x=[];if(h&&-1!==h.indexOf(\"label\")&&x.push(t.label),t.text=m.castOption(f.hovertext||f.text,t.pts),h&&-1!==h.indexOf(\"text\")){var b=t.text;l.isValidTextValue(b)&&x.push(b)}t.value=t.v,t.valueLabel=m.formatPieValue(t.v,y),h&&-1!==h.indexOf(\"value\")&&x.push(t.valueLabel),t.percent=t.v/i.vTotal,t.percentLabel=m.formatPiePercent(t.percent,y),h&&-1!==h.indexOf(\"percent\")&&x.push(t.percentLabel);var _=f.hoverlabel,w=_.font,T=[];a.loneHover({trace:c,x0:d-p*i.r,x1:d+p*i.r,y:g,_x0:u?o+t.TL[0]:d-p*i.r,_x1:u?o+t.TR[0]:d+p*i.r,_y0:u?s+t.TL[1]:g-p*i.r,_y1:u?s+t.BL[1]:g+p*i.r,text:x.join(\"<br>\"),name:f.hovertemplate||-1!==h.indexOf(\"name\")?f.name:void 0,idealAlign:t.pxmid[0]<0?\"left\":\"right\",color:m.castOption(_.bgcolor,t.pts)||t.color,borderColor:m.castOption(_.bordercolor,t.pts),fontFamily:m.castOption(w.family,t.pts),fontSize:m.castOption(w.size,t.pts),fontColor:m.castOption(w.color,t.pts),nameLength:m.castOption(_.namelength,t.pts),textAlign:m.castOption(_.align,t.pts),hovertemplate:m.castOption(f.hovertemplate,t.pts),hovertemplateLabels:t,eventData:[v(t,f)]},{container:r._hoverlayer.node(),outerContainer:r._paper.node(),gd:e,inOut_bbox:T}),t.bbox=T[0],c._hasHoverLabel=!0}c._hasHoverEvent=!0,e.emit(\"plotly_hover\",{points:[v(t,f)],event:n.event})}})),t.on(\"mouseout\",(function(t){var r=e._fullLayout,i=e._fullData[c.index],o=n.select(this).datum();c._hasHoverEvent&&(t.originalEvent=n.event,e.emit(\"plotly_unhover\",{points:[v(o,i)],event:n.event}),c._hasHoverEvent=!1),c._hasHoverLabel&&(a.loneUnhover(r._hoverlayer.node()),c._hasHoverLabel=!1)})),t.on(\"click\",(function(t){var r=e._fullLayout,i=e._fullData[c.index];e._dragging||!1===r.hovermode||(e._hoverdata=[v(t,i)],a.click(e,n.event))}))}function b(t,e,r){var n=m.castOption(t.insidetextfont.color,e.pts);!n&&t._input.textfont&&(n=m.castOption(t._input.textfont.color,e.pts));var i=m.castOption(t.insidetextfont.family,e.pts)||m.castOption(t.textfont.family,e.pts)||r.family,a=m.castOption(t.insidetextfont.size,e.pts)||m.castOption(t.textfont.size,e.pts)||r.size;return{color:n||o.contrast(e.color),family:i,size:a}}function _(t,e){for(var r,n,i=0;i<t.length;i++)if((n=(r=t[i][0]).trace).title.text){var a=n.title.text;n._meta&&(a=l.templateString(a,n._meta));var o=s.tester.append(\"text\").attr(\"data-notex\",1).text(a).call(s.font,n.title.font).call(f.convertToTspans,e),c=s.bBox(o.node(),!0);r.titleBox={width:c.width,height:c.height},o.remove()}}function w(t,e,r){var n=r.r||e.rpx1,i=e.rInscribed;if(e.startangle===e.stopangle)return{rCenter:1-i,scale:0,rotate:0,textPosAngle:0};var a,o=e.ring,s=1===o&&Math.abs(e.startangle-e.stopangle)===2*Math.PI,l=e.halfangle,c=e.midangle,u=r.trace.insidetextorientation,f=\"horizontal\"===u,h=\"tangential\"===u,p=\"radial\"===u,d=\"auto\"===u,g=[];if(!d){var m,v=function(r,i){if(function(t,e){var r=t.startangle,n=t.stopangle;return r>e&&e>n||r<e&&e<n}(e,r)){var s=Math.abs(r-e.startangle),l=Math.abs(r-e.stopangle),c=s<l?s:l;(a=\"tan\"===i?k(t,n,o,c,0):T(t,n,o,c,Math.PI/2)).textPosAngle=r,g.push(a)}};if(f||h){for(m=4;m>=-4;m-=2)v(Math.PI*m,\"tan\");for(m=4;m>=-4;m-=2)v(Math.PI*(m+1),\"tan\")}if(f||p){for(m=4;m>=-4;m-=2)v(Math.PI*(m+1.5),\"rad\");for(m=4;m>=-4;m-=2)v(Math.PI*(m+.5),\"rad\")}}if(s||d||f){var y=Math.sqrt(t.width*t.width+t.height*t.height);if((a={scale:i*n*2/y,rCenter:1-i,rotate:0}).textPosAngle=(e.startangle+e.stopangle)/2,a.scale>=1)return a;g.push(a)}(d||p)&&((a=T(t,n,o,l,c)).textPosAngle=(e.startangle+e.stopangle)/2,g.push(a)),(d||h)&&((a=k(t,n,o,l,c)).textPosAngle=(e.startangle+e.stopangle)/2,g.push(a));for(var x=0,b=0,_=0;_<g.length;_++){var w=g[_].scale;if(b<w&&(b=w,x=_),!d&&b>=1)break}return g[x]}function T(t,e,r,n,i){e=Math.max(0,e-2*g);var a=t.width/t.height,o=S(a,n,e,r);return{scale:2*o/t.height,rCenter:A(a,o/e),rotate:M(i)}}function k(t,e,r,n,i){e=Math.max(0,e-2*g);var a=t.height/t.width,o=S(a,n,e,r);return{scale:2*o/t.width,rCenter:A(a,o/e),rotate:M(i+Math.PI/2)}}function A(t,e){return Math.cos(e)-t*e}function M(t){return(180/Math.PI*t+720)%180-90}function S(t,e,r,n){var i=t+1/(2*Math.tan(e));return r*Math.min(1/(Math.sqrt(i*i+.5)+i),n/(Math.sqrt(t*t+n/2)+t))}function E(t,e){return t.v!==e.vTotal||e.trace.hole?Math.min(1/(1+1/Math.sin(t.halfangle)),t.ring/2):1}function L(t,e){var r=e.pxmid[0],n=e.pxmid[1],i=t.width/2,a=t.height/2;return r<0&&(i*=-1),n<0&&(a*=-1),{scale:1,rCenter:1,rotate:0,x:i+Math.abs(a)*(i>0?1:-1)/2,y:a/(1+r*r/(n*n)),outside:!0}}function C(t,e){var r,n,i,a=t.trace,o={x:t.cx,y:t.cy},s={tx:0,ty:0};s.ty+=a.title.font.size,i=I(a),-1!==a.title.position.indexOf(\"top\")?(o.y-=(1+i)*t.r,s.ty-=t.titleBox.height):-1!==a.title.position.indexOf(\"bottom\")&&(o.y+=(1+i)*t.r);var l,c,u=(l=t.r,c=t.trace.aspectratio,l/(void 0===c?1:c)),f=e.w*(a.domain.x[1]-a.domain.x[0])/2;return-1!==a.title.position.indexOf(\"left\")?(f+=u,o.x-=(1+i)*u,s.tx+=t.titleBox.width/2):-1!==a.title.position.indexOf(\"center\")?f*=2:-1!==a.title.position.indexOf(\"right\")&&(f+=u,o.x+=(1+i)*u,s.tx-=t.titleBox.width/2),r=f/t.titleBox.width,n=P(t,e)/t.titleBox.height,{x:o.x,y:o.y,scale:Math.min(r,n),tx:s.tx,ty:s.ty}}function P(t,e){var r=t.trace,n=e.h*(r.domain.y[1]-r.domain.y[0]);return Math.min(t.titleBox.height,n/2)}function I(t){var e,r=t.pull;if(!r)return 0;if(Array.isArray(r))for(r=0,e=0;e<t.pull.length;e++)t.pull[e]>r&&(r=t.pull[e]);return r}function O(t,e){for(var r=[],n=0;n<t.length;n++){var i=t[n][0],a=i.trace,o=a.domain,s=e.w*(o.x[1]-o.x[0]),l=e.h*(o.y[1]-o.y[0]);a.title.text&&\"middle center\"!==a.title.position&&(l-=P(i,e));var c=s/2,u=l/2;\"funnelarea\"!==a.type||a.scalegroup||(u/=a.aspectratio),i.r=Math.min(c,u)/(1+I(a)),i.cx=e.l+e.w*(a.domain.x[1]+a.domain.x[0])/2,i.cy=e.t+e.h*(1-a.domain.y[0])-l/2,a.title.text&&-1!==a.title.position.indexOf(\"bottom\")&&(i.cy-=P(i,e)),a.scalegroup&&-1===r.indexOf(a.scalegroup)&&r.push(a.scalegroup)}!function(t,e){for(var r,n,i,a=0;a<e.length;a++){var o=1/0,s=e[a];for(n=0;n<t.length;n++)if(r=t[n][0],(i=r.trace).scalegroup===s){var l;if(\"pie\"===i.type)l=r.r*r.r;else if(\"funnelarea\"===i.type){var c,u;i.aspectratio>1?(c=r.r,u=c/i.aspectratio):(u=r.r,c=u*i.aspectratio),c*=(1+i.baseratio)/2,l=c*u}o=Math.min(o,l/r.vTotal)}for(n=0;n<t.length;n++)if(r=t[n][0],(i=r.trace).scalegroup===s){var f=o*r.vTotal;\"funnelarea\"===i.type&&(f/=(1+i.baseratio)/2,f/=i.aspectratio),r.r=Math.sqrt(f)}}}(t,r)}function z(t,e){return[t*Math.sin(e),-t*Math.cos(e)]}function D(t,e,r){var n=t._fullLayout,i=r.trace,a=i.texttemplate,o=i.textinfo;if(!a&&o&&\"none\"!==o){var s,c=o.split(\"+\"),u=function(t){return-1!==c.indexOf(t)},f=u(\"label\"),h=u(\"text\"),p=u(\"value\"),d=u(\"percent\"),g=n.separators;if(s=f?[e.label]:[],h){var v=m.getFirstFilled(i.text,e.pts);y(v)&&s.push(v)}p&&s.push(m.formatPieValue(e.v,g)),d&&s.push(m.formatPiePercent(e.v/r.vTotal,g)),e.text=s.join(\"<br>\")}if(a){var x=l.castOption(i,e.i,\"texttemplate\");if(x){var b=function(t){return{label:t.label,value:t.v,valueLabel:m.formatPieValue(t.v,n.separators),percent:t.v/r.vTotal,percentLabel:m.formatPiePercent(t.v/r.vTotal,n.separators),color:t.color,text:t.text,customdata:l.castOption(i,t.i,\"customdata\")}}(e),_=m.getFirstFilled(i.text,e.pts);(y(_)||\"\"===_)&&(b.text=_),e.text=l.texttemplateString(x,b,t._fullLayout._d3locale,b,i._meta||{})}else e.text=\"\"}}function R(t,e){var r=t.rotate*Math.PI/180,n=Math.cos(r),i=Math.sin(r),a=(e.left+e.right)/2,o=(e.top+e.bottom)/2;t.textX=a*n-o*i,t.textY=a*i+o*n,t.noCenter=!0}e.exports={plot:function(t,e){var r=t._fullLayout,a=r._size;d(\"pie\",r),_(e,t),O(e,a);var h=l.makeTraceGroups(r._pielayer,e,\"trace\").each((function(e){var h=n.select(this),d=e[0],g=d.trace;!function(t){var e,r,n,i=t[0],a=i.r,o=i.trace,s=m.getRotationAngle(o.rotation),l=2*Math.PI/i.vTotal,c=\"px0\",u=\"px1\";if(\"counterclockwise\"===o.direction){for(e=0;e<t.length&&t[e].hidden;e++);if(e===t.length)return;s+=l*t[e].v,l*=-1,c=\"px1\",u=\"px0\"}for(n=z(a,s),e=0;e<t.length;e++)(r=t[e]).hidden||(r[c]=n,r.startangle=s,s+=l*r.v/2,r.pxmid=z(a,s),r.midangle=s,s+=l*r.v/2,n=z(a,s),r.stopangle=s,r[u]=n,r.largeArc=r.v>i.vTotal/2?1:0,r.halfangle=Math.PI*Math.min(r.v/i.vTotal,.5),r.ring=1-o.hole,r.rInscribed=E(r,i))}(e),h.attr(\"stroke-linejoin\",\"round\"),h.each((function(){var v=n.select(this).selectAll(\"g.slice\").data(e);v.enter().append(\"g\").classed(\"slice\",!0),v.exit().remove();var y=[[[],[]],[[],[]]],_=!1;v.each((function(i,a){if(i.hidden)n.select(this).selectAll(\"path,g\").remove();else{i.pointNumber=i.i,i.curveNumber=g.index,y[i.pxmid[1]<0?0:1][i.pxmid[0]<0?0:1].push(i);var o=d.cx,c=d.cy,u=n.select(this),h=u.selectAll(\"path.surface\").data([i]);if(h.enter().append(\"path\").classed(\"surface\",!0).style({\"pointer-events\":\"all\"}),u.call(x,t,e),g.pull){var v=+m.castOption(g.pull,i.pts)||0;v>0&&(o+=v*i.pxmid[0],c+=v*i.pxmid[1])}i.cxFinal=o,i.cyFinal=c;var T=g.hole;if(i.v===d.vTotal){var k=\"M\"+(o+i.px0[0])+\",\"+(c+i.px0[1])+C(i.px0,i.pxmid,!0,1)+C(i.pxmid,i.px0,!0,1)+\"Z\";T?h.attr(\"d\",\"M\"+(o+T*i.px0[0])+\",\"+(c+T*i.px0[1])+C(i.px0,i.pxmid,!1,T)+C(i.pxmid,i.px0,!1,T)+\"Z\"+k):h.attr(\"d\",k)}else{var A=C(i.px0,i.px1,!0,1);if(T){var M=1-T;h.attr(\"d\",\"M\"+(o+T*i.px1[0])+\",\"+(c+T*i.px1[1])+C(i.px1,i.px0,!1,T)+\"l\"+M*i.px0[0]+\",\"+M*i.px0[1]+A+\"Z\")}else h.attr(\"d\",\"M\"+o+\",\"+c+\"l\"+i.px0[0]+\",\"+i.px0[1]+A+\"Z\")}D(t,i,d);var S=m.castOption(g.textposition,i.pts),E=u.selectAll(\"g.slicetext\").data(i.text&&\"none\"!==S?[0]:[]);E.enter().append(\"g\").classed(\"slicetext\",!0),E.exit().remove(),E.each((function(){var u=l.ensureSingle(n.select(this),\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),h=l.ensureUniformFontSize(t,\"outside\"===S?function(t,e,r){var n=m.castOption(t.outsidetextfont.color,e.pts)||m.castOption(t.textfont.color,e.pts)||r.color,i=m.castOption(t.outsidetextfont.family,e.pts)||m.castOption(t.textfont.family,e.pts)||r.family,a=m.castOption(t.outsidetextfont.size,e.pts)||m.castOption(t.textfont.size,e.pts)||r.size;return{color:n,family:i,size:a}}(g,i,r.font):b(g,i,r.font));u.text(i.text).attr({class:\"slicetext\",transform:\"\",\"text-anchor\":\"middle\"}).call(s.font,h).call(f.convertToTspans,t);var v,y=s.bBox(u.node());if(\"outside\"===S)v=L(y,i);else if(v=w(y,i,d),\"auto\"===S&&v.scale<1){var x=l.ensureUniformFontSize(t,g.outsidetextfont);u.call(s.font,x),v=L(y=s.bBox(u.node()),i)}var T=v.textPosAngle,k=void 0===T?i.pxmid:z(d.r,T);if(v.targetX=o+k[0]*v.rCenter+(v.x||0),v.targetY=c+k[1]*v.rCenter+(v.y||0),R(v,y),v.outside){var A=v.targetY;i.yLabelMin=A-y.height/2,i.yLabelMid=A,i.yLabelMax=A+y.height/2,i.labelExtraX=0,i.labelExtraY=0,_=!0}v.fontSize=h.size,p(g.type,v,r),e[a].transform=v,u.attr(\"transform\",l.getTextTransform(v))}))}function C(t,e,r,n){var a=n*(e[0]-t[0]),o=n*(e[1]-t[1]);return\"a\"+n*d.r+\",\"+n*d.r+\" 0 \"+i.largeArc+(r?\" 1 \":\" 0 \")+a+\",\"+o}}));var T=n.select(this).selectAll(\"g.titletext\").data(g.title.text?[0]:[]);if(T.enter().append(\"g\").classed(\"titletext\",!0),T.exit().remove(),T.each((function(){var e,r=l.ensureSingle(n.select(this),\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),i=g.title.text;g._meta&&(i=l.templateString(i,g._meta)),r.text(i).attr({class:\"titletext\",transform:\"\",\"text-anchor\":\"middle\"}).call(s.font,g.title.font).call(f.convertToTspans,t),e=\"middle center\"===g.title.position?function(t){var 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i=n.datum().link.label;n.style(\"fill-opacity\",(function(t){if(!t.link.concentrationscale)return.4})),i&&h(e,t).selectAll(\".\"+c.sankeyLink).filter((function(t){return t.link.label===i})).style(\"fill-opacity\",(function(t){if(!t.link.concentrationscale)return.4})),r&&h(e,t).selectAll(\".\"+c.sankeyNode).filter(m(t)).call(v)}function b(t,e,r,n){var i=n.datum().link.label;n.style(\"fill-opacity\",(function(t){return t.tinyColorAlpha})),i&&h(e,t).selectAll(\".\"+c.sankeyLink).filter((function(t){return t.link.label===i})).style(\"fill-opacity\",(function(t){return t.tinyColorAlpha})),r&&h(e,t).selectAll(c.sankeyNode).filter(m(t)).call(y)}function _(t,e){var r=t.hoverlabel||{},n=i.nestedProperty(r,e).get();return!Array.isArray(n)&&n}e.exports=function(t,e){for(var r=t._fullLayout,i=r._paper,h=r._size,g=0;g<t._fullData.length;g++)if(t._fullData[g].visible&&t._fullData[g].type===c.sankey&&!t._fullData[g]._viewInitial){var m=t._fullData[g].node;t._fullData[g]._viewInitial={node:{groups:m.groups.slice(),x:m.x.slice(),y:m.y.slice()}}}var w=u(t,\"source:\")+\" \",T=u(t,\"target:\")+\" \",k=u(t,\"concentration:\")+\" \",A=u(t,\"incoming flow count:\")+\" \",M=u(t,\"outgoing flow count:\")+\" \";o(t,i,e,{width:h.w,height:h.h,margin:{t:h.t,r:h.r,b:h.b,l:h.l}},{linkEvents:{hover:function(e,r,i){!1!==t._fullLayout.hovermode&&(n.select(e).call(x.bind(0,r,i,!0)),\"skip\"!==r.link.trace.link.hoverinfo&&(r.link.fullData=r.link.trace,t.emit(\"plotly_hover\",{event:n.event,points:[r.link]})))},follow:function(e,i){if(!1!==t._fullLayout.hovermode){var o=i.link.trace.link;if(\"none\"!==o.hoverinfo&&\"skip\"!==o.hoverinfo){for(var c=[],u=0,h=0;h<i.flow.links.length;h++){var g=i.flow.links[h];if(\"closest\"!==t._fullLayout.hovermode||i.link.pointNumber===g.pointNumber){i.link.pointNumber===g.pointNumber&&(u=h),g.fullData=g.trace,o=i.link.trace.link;var m=y(g),v={valueLabel:a(i.valueFormat)(g.value)+i.valueSuffix};c.push({x:m[0],y:m[1],name:v.valueLabel,text:[g.label||\"\",w+g.source.label,T+g.target.label,g.concentrationscale?k+a(\"%0.2f\")(g.flow.labelConcentration):\"\"].filter(f).join(\"<br>\"),color:_(o,\"bgcolor\")||l.addOpacity(g.color,1),borderColor:_(o,\"bordercolor\"),fontFamily:_(o,\"font.family\"),fontSize:_(o,\"font.size\"),fontColor:_(o,\"font.color\"),nameLength:_(o,\"namelength\"),textAlign:_(o,\"align\"),idealAlign:n.event.x<m[0]?\"right\":\"left\",hovertemplate:o.hovertemplate,hovertemplateLabels:v,eventData:[g]})}}s.loneHover(c,{container:r._hoverlayer.node(),outerContainer:r._paper.node(),gd:t,anchorIndex:u}).each((function(){i.link.concentrationscale||p(this,.65),d(this)}))}}function y(t){var e,r;t.circular?(e=(t.circularPathData.leftInnerExtent+t.circularPathData.rightInnerExtent)/2,r=t.circularPathData.verticalFullExtent):(e=(t.source.x1+t.target.x0)/2,r=(t.y0+t.y1)/2);var n=[e,r];return\"v\"===t.trace.orientation&&n.reverse(),n[0]+=i.parent.translateX,n[1]+=i.parent.translateY,n}},unhover:function(e,i,a){!1!==t._fullLayout.hovermode&&(n.select(e).call(b.bind(0,i,a,!0)),\"skip\"!==i.link.trace.link.hoverinfo&&(i.link.fullData=i.link.trace,t.emit(\"plotly_unhover\",{event:n.event,points:[i.link]})),s.loneUnhover(r._hoverlayer.node()))},select:function(e,r){var i=r.link;i.originalEvent=n.event,t._hoverdata=[i],s.click(t,{target:!0})}},nodeEvents:{hover:function(e,r,i){!1!==t._fullLayout.hovermode&&(n.select(e).call(v,r,i),\"skip\"!==r.node.trace.node.hoverinfo&&(r.node.fullData=r.node.trace,t.emit(\"plotly_hover\",{event:n.event,points:[r.node]})))},follow:function(e,i){if(!1!==t._fullLayout.hovermode){var o=i.node.trace.node;if(\"none\"!==o.hoverinfo&&\"skip\"!==o.hoverinfo){var l=n.select(e).select(\".\"+c.nodeRect),u=t._fullLayout._paperdiv.node().getBoundingClientRect(),h=l.node().getBoundingClientRect(),g=h.left-2-u.left,m=h.right+2-u.left,v=h.top+h.height/4-u.top,y={valueLabel:a(i.valueFormat)(i.node.value)+i.valueSuffix};i.node.fullData=i.node.trace,t._fullLayout._calcInverseTransform(t);var x=t._fullLayout._invScaleX,b=t._fullLayout._invScaleY,w=s.loneHover({x0:x*g,x1:x*m,y:b*v,name:a(i.valueFormat)(i.node.value)+i.valueSuffix,text:[i.node.label,A+i.node.targetLinks.length,M+i.node.sourceLinks.length].filter(f).join(\"<br>\"),color:_(o,\"bgcolor\")||i.tinyColorHue,borderColor:_(o,\"bordercolor\"),fontFamily:_(o,\"font.family\"),fontSize:_(o,\"font.size\"),fontColor:_(o,\"font.color\"),nameLength:_(o,\"namelength\"),textAlign:_(o,\"align\"),idealAlign:\"left\",hovertemplate:o.hovertemplate,hovertemplateLabels:y,eventData:[i.node]},{container:r._hoverlayer.node(),outerContainer:r._paper.node(),gd:t});p(w,.85),d(w)}}},unhover:function(e,i,a){!1!==t._fullLayout.hovermode&&(n.select(e).call(y,i,a),\"skip\"!==i.node.trace.node.hoverinfo&&(i.node.fullData=i.node.trace,t.emit(\"plotly_unhover\",{event:n.event,points:[i.node]})),s.loneUnhover(r._hoverlayer.node()))},select:function(e,r,i){var 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n,i=y(e),a=i.trace,u=a.domain,f=\"h\"===a.orientation,p=a.node.pad,d=a.node.thickness,g=t.width*(u.x[1]-u.x[0]),m=t.height*(u.y[1]-u.y[0]),v=i._nodes,x=i._links,b=i.circular;(n=b?s.sankeyCircular().circularLinkGap(0):o.sankey()).iterations(l.sankeyIterations).size(f?[g,m]:[m,g]).nodeWidth(d).nodePadding(p).nodeId((function(t){return t.pointNumber})).nodes(v).links(x);var _,w,T,k=n();for(var A in n.nodePadding()<p&&h.warn(\"node.pad was reduced to \",n.nodePadding(),\" to fit within the figure.\"),i._groupLookup){var M,S=parseInt(i._groupLookup[A]);for(_=0;_<k.nodes.length;_++)if(k.nodes[_].pointNumber===S){M=k.nodes[_];break}if(M){var E={pointNumber:parseInt(A),x0:M.x0,x1:M.x1,y0:M.y0,y1:M.y1,partOfGroup:!0,sourceLinks:[],targetLinks:[]};k.nodes.unshift(E),M.childrenNodes.unshift(E)}}if(function(){for(_=0;_<k.nodes.length;_++){var t,e,r=k.nodes[_],n={};for(w=0;w<r.targetLinks.length;w++)t=(e=r.targetLinks[w]).source.pointNumber+\":\"+e.target.pointNumber,n.hasOwnProperty(t)||(n[t]=[]),n[t].push(e);var i=Object.keys(n);for(w=0;w<i.length;w++){var a=n[t=i[w]],o=0,s={};for(T=0;T<a.length;T++)s[(e=a[T]).label]||(s[e.label]=0),s[e.label]+=e.value,o+=e.value;for(T=0;T<a.length;T++)(e=a[T]).flow={value:o,labelConcentration:s[e.label]/o,concentration:e.value/o,links:a},e.concentrationscale&&(e.color=c(e.concentrationscale(e.flow.labelConcentration)))}var l=0;for(w=0;w<r.sourceLinks.length;w++)l+=r.sourceLinks[w].value;for(w=0;w<r.sourceLinks.length;w++)(e=r.sourceLinks[w]).concentrationOut=e.value/l;var u=0;for(w=0;w<r.targetLinks.length;w++)u+=r.targetLinks[w].value;for(w=0;w<r.targetLinks.length;w++)(e=r.targetLinks[w]).concenrationIn=e.value/u}}(),a.node.x.length&&a.node.y.length){for(_=0;_<Math.min(a.node.x.length,a.node.y.length,k.nodes.length);_++)if(a.node.x[_]&&a.node.y[_]){var L=[a.node.x[_]*g,a.node.y[_]*m];k.nodes[_].x0=L[0]-d/2,k.nodes[_].x1=L[0]+d/2;var C=k.nodes[_].y1-k.nodes[_].y0;k.nodes[_].y0=L[1]-C/2,k.nodes[_].y1=L[1]+C/2}if(\"snap\"===a.arrangement)!function(t){t.forEach((function(t){var e,r,n,i=0,a=t.length;for(t.sort((function(t,e){return t.y0-e.y0})),n=0;n<a;++n)(e=t[n]).y0>=i||(r=i-e.y0)>1e-6&&(e.y0+=r,e.y1+=r),i=e.y1+p}))}(function(t){var e,r,n=t.map((function(t,e){return{x0:t.x0,index:e}})).sort((function(t,e){return t.x0-e.x0})),i=[],a=-1,o=-1/0;for(_=0;_<n.length;_++){var s=t[n[_].index];s.x0>o+d&&(a+=1,e=s.x0),o=s.x0,i[a]||(i[a]=[]),i[a].push(s),r=e-s.x0,s.x0+=r,s.x1+=r}return 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e.trace=t.trace,e.curveNumber=t.trace.index,{circular:t.circular,key:i,traceId:t.key,pointNumber:e.pointNumber,link:e,tinyColorHue:u.tinyRGB(n),tinyColorAlpha:n.getAlpha(),linkPath:M,linkLineColor:t.linkLineColor,linkLineWidth:t.linkLineWidth,valueFormat:t.valueFormat,valueSuffix:t.valueSuffix,sankey:t.sankey,parent:t,interactionState:t.interactionState,flow:e.flow}}function M(){return function(t){if(t.link.circular)return e=t.link,r=e.width/2,n=e.circularPathData,\"top\"===e.circularLinkType?\"M \"+n.targetX+\" \"+(n.targetY+r)+\" L\"+n.rightInnerExtent+\" \"+(n.targetY+r)+\"A\"+(n.rightLargeArcRadius+r)+\" \"+(n.rightSmallArcRadius+r)+\" 0 0 1 \"+(n.rightFullExtent-r)+\" \"+(n.targetY-n.rightSmallArcRadius)+\"L\"+(n.rightFullExtent-r)+\" \"+n.verticalRightInnerExtent+\"A\"+(n.rightLargeArcRadius+r)+\" \"+(n.rightLargeArcRadius+r)+\" 0 0 1 \"+n.rightInnerExtent+\" \"+(n.verticalFullExtent-r)+\"L\"+n.leftInnerExtent+\" \"+(n.verticalFullExtent-r)+\"A\"+(n.leftLargeArcRadius+r)+\" \"+(n.leftLargeArcRadius+r)+\" 0 0 1 \"+(n.leftFullExtent+r)+\" \"+n.verticalLeftInnerExtent+\"L\"+(n.leftFullExtent+r)+\" \"+(n.sourceY-n.leftSmallArcRadius)+\"A\"+(n.leftLargeArcRadius+r)+\" \"+(n.leftSmallArcRadius+r)+\" 0 0 1 \"+n.leftInnerExtent+\" \"+(n.sourceY+r)+\"L\"+n.sourceX+\" \"+(n.sourceY+r)+\"L\"+n.sourceX+\" \"+(n.sourceY-r)+\"L\"+n.leftInnerExtent+\" \"+(n.sourceY-r)+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftSmallArcRadius-r)+\" 0 0 0 \"+(n.leftFullExtent-r)+\" \"+(n.sourceY-n.leftSmallArcRadius)+\"L\"+(n.leftFullExtent-r)+\" \"+n.verticalLeftInnerExtent+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftLargeArcRadius-r)+\" 0 0 0 \"+n.leftInnerExtent+\" \"+(n.verticalFullExtent+r)+\"L\"+n.rightInnerExtent+\" \"+(n.verticalFullExtent+r)+\"A\"+(n.rightLargeArcRadius-r)+\" \"+(n.rightLargeArcRadius-r)+\" 0 0 0 \"+(n.rightFullExtent+r)+\" \"+n.verticalRightInnerExtent+\"L\"+(n.rightFullExtent+r)+\" \"+(n.targetY-n.rightSmallArcRadius)+\"A\"+(n.rightLargeArcRadius-r)+\" 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\"+(n.sourceY+r)+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftSmallArcRadius-r)+\" 0 0 1 \"+(n.leftFullExtent-r)+\" \"+(n.sourceY+n.leftSmallArcRadius)+\"L\"+(n.leftFullExtent-r)+\" \"+n.verticalLeftInnerExtent+\"A\"+(n.leftLargeArcRadius-r)+\" \"+(n.leftLargeArcRadius-r)+\" 0 0 1 \"+n.leftInnerExtent+\" \"+(n.verticalFullExtent-r)+\"L\"+n.rightInnerExtent+\" \"+(n.verticalFullExtent-r)+\"A\"+(n.rightLargeArcRadius-r)+\" \"+(n.rightLargeArcRadius-r)+\" 0 0 1 \"+(n.rightFullExtent+r)+\" \"+n.verticalRightInnerExtent+\"L\"+(n.rightFullExtent+r)+\" \"+(n.targetY+n.rightSmallArcRadius)+\"A\"+(n.rightLargeArcRadius-r)+\" \"+(n.rightSmallArcRadius-r)+\" 0 0 1 \"+n.rightInnerExtent+\" \"+(n.targetY+r)+\"L\"+n.targetX+\" \"+(n.targetY+r)+\"Z\";var e,r,n,a=t.link.source.x1,o=t.link.target.x0,s=i(a,o),l=s(.5),c=s(.5),u=t.link.y0-t.link.width/2,f=t.link.y0+t.link.width/2,h=t.link.y1-t.link.width/2,p=t.link.y1+t.link.width/2;return\"M\"+a+\",\"+u+\"C\"+l+\",\"+u+\" \"+c+\",\"+h+\" 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e.group&&(s=h.randstr()),e.trace=t.trace,e.curveNumber=t.trace.index,{index:e.pointNumber,key:s,partOfGroup:e.partOfGroup||!1,group:e.group,traceId:t.key,trace:t.trace,node:e,nodePad:t.nodePad,nodeLineColor:t.nodeLineColor,nodeLineWidth:t.nodeLineWidth,textFont:t.textFont,size:t.horizontal?t.height:t.width,visibleWidth:Math.ceil(a),visibleHeight:o,zoneX:-n,zoneY:-i,zoneWidth:a+2*n,zoneHeight:o+2*i,labelY:t.horizontal?e.dy/2+1:e.dx/2+1,left:1===e.originalLayer,sizeAcross:t.width,forceLayouts:t.forceLayouts,horizontal:t.horizontal,darkBackground:r.getBrightness()<=128,tinyColorHue:u.tinyRGB(r),tinyColorAlpha:r.getAlpha(),valueFormat:t.valueFormat,valueSuffix:t.valueSuffix,sankey:t.sankey,graph:t.graph,arrangement:t.arrangement,uniqueNodeLabelPathId:[t.guid,t.key,s].join(\"_\"),interactionState:t.interactionState,figure:t}}function E(t){t.attr(\"transform\",(function(t){return p(t.node.x0.toFixed(3),t.node.y0.toFixed(3))}))}function L(t){t.call(E)}function 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n=t(\"../../components/colorscale/helpers\").hasColorscale,i=t(\"../../components/colorscale/calc\"),a=t(\"./subtypes\");e.exports=function(t,e){a.hasLines(e)&&n(e,\"line\")&&i(t,e,{vals:e.line.color,containerStr:\"line\",cLetter:\"c\"}),a.hasMarkers(e)&&(n(e,\"marker\")&&i(t,e,{vals:e.marker.color,containerStr:\"marker\",cLetter:\"c\"}),n(e,\"marker.line\")&&i(t,e,{vals:e.marker.line.color,containerStr:\"marker.line\",cLetter:\"c\"}))}},{\"../../components/colorscale/calc\":674,\"../../components/colorscale/helpers\":677,\"./subtypes\":1243}],1222:[function(t,e,r){\"use strict\";e.exports={PTS_LINESONLY:20,minTolerance:.2,toleranceGrowth:10,maxScreensAway:20,eventDataKeys:[]}},{}],1223:[function(t,e,r){\"use strict\";var n=t(\"./calc\");function i(t,e,r,n,i,a,o){i[n]=!0;var s={i:null,gap:!0,s:0};if(s[o]=r,t.splice(e,0,s),e&&r===t[e-1][o]){var l=t[e-1];s.s=l.s,s.i=l.i,s.gap=l.gap}else a&&(s.s=function(t,e,r,n){var i=t[e-1],a=t[e+1];return 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n=t(\"../../components/color\"),i=t(\"../../lib\").isArrayOrTypedArray;e.exports=function(t,e,r,a){var o=!1;if(e.marker){var s=e.marker.color,l=(e.marker.line||{}).color;s&&!i(s)?o=s:l&&!i(l)&&(o=l)}a(\"fillcolor\",n.addOpacity((e.line||{}).color||o||r,.5))}},{\"../../components/color\":666,\"../../lib\":803}],1227:[function(t,e,r){\"use strict\";var n=t(\"../../plots/cartesian/axes\");e.exports=function(t,e,r){var i={},a={_fullLayout:r},o=n.getFromTrace(a,e,\"x\"),s=n.getFromTrace(a,e,\"y\");return i.xLabel=n.tickText(o,o.c2l(t.x),!0).text,i.yLabel=n.tickText(s,s.c2l(t.y),!0).text,i}},{\"../../plots/cartesian/axes\":854}],1228:[function(t,e,r){\"use strict\";var n=t(\"../../components/color\"),i=t(\"./subtypes\");e.exports=function(t,e){var r,a;if(\"lines\"===t.mode)return(r=t.line.color)&&n.opacity(r)?r:t.fillcolor;if(\"none\"===t.mode)return t.fill?t.fillcolor:\"\";var 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d=t.opacity;if(t.marker&&t.marker.opacity&&(d*=t.marker.opacity),r={gl:this.scene.glplot.gl,position:p.position,color:p.scatterColor,size:p.scatterSize,glyph:p.scatterMarker,opacity:d,orthographic:!0,lineWidth:p.scatterLineWidth,lineColor:p.scatterLineColor,project:p.project,projectScale:p.projectScale,projectOpacity:p.projectOpacity},-1!==this.mode.indexOf(\"markers\")?this.scatterPlot?this.scatterPlot.update(r):(this.scatterPlot=i(r),this.scatterPlot._trace=this,this.scatterPlot.highlightScale=1,this.scene.glplot.add(this.scatterPlot)):this.scatterPlot&&(this.scene.glplot.remove(this.scatterPlot),this.scatterPlot.dispose(),this.scatterPlot=null),c={gl:this.scene.glplot.gl,position:p.position,glyph:p.text,color:p.textColor,size:p.textSize,angle:p.textAngle,alignment:p.textOffset,font:p.textFont,orthographic:!0,lineWidth:0,project:!1,opacity:t.opacity},this.textLabels=t.hovertext||t.text,-1!==this.mode.indexOf(\"text\")?this.textMarkers?this.textMarkers.update(c):(this.textMarkers=i(c),this.textMarkers._trace=this,this.textMarkers.highlightScale=1,this.scene.glplot.add(this.textMarkers)):this.textMarkers&&(this.scene.glplot.remove(this.textMarkers),this.textMarkers.dispose(),this.textMarkers=null),l={gl:this.scene.glplot.gl,position:p.position,color:p.errorColor,error:p.errorBounds,lineWidth:p.errorLineWidth,capSize:p.errorCapSize,opacity:t.opacity},this.errorBars?p.errorBounds?this.errorBars.update(l):(this.scene.glplot.remove(this.errorBars),this.errorBars.dispose(),this.errorBars=null):p.errorBounds&&(this.errorBars=a(l),this.errorBars._trace=this,this.scene.glplot.add(this.errorBars)),p.delaunayAxis>=0){var g=function(t,e,r){var n,i=(r+1)%3,a=(r+2)%3,o=[],l=[];for(n=0;n<t.length;++n){var c=t[n];!isNaN(c[i])&&isFinite(c[i])&&!isNaN(c[a])&&isFinite(c[a])&&(o.push([c[i],c[a]]),l.push(n))}var u=s(o);for(n=0;n<u.length;++n)for(var f=u[n],h=0;h<f.length;++h)f[h]=l[f[h]];return{positions:t,cells:u,meshColor:e}}(p.position,p.delaunayColor,p.delaunayAxis);g.opacity=t.opacity,this.delaunayMesh?this.delaunayMesh.update(g):(g.gl=u,this.delaunayMesh=o(g),this.delaunayMesh._trace=this,this.scene.glplot.add(this.delaunayMesh))}else this.delaunayMesh&&(this.scene.glplot.remove(this.delaunayMesh),this.delaunayMesh.dispose(),this.delaunayMesh=null)},y.dispose=function(){this.linePlot&&(this.scene.glplot.remove(this.linePlot),this.linePlot.dispose()),this.scatterPlot&&(this.scene.glplot.remove(this.scatterPlot),this.scatterPlot.dispose()),this.errorBars&&(this.scene.glplot.remove(this.errorBars),this.errorBars.dispose()),this.textMarkers&&(this.scene.glplot.remove(this.textMarkers),this.textMarkers.dispose()),this.delaunayMesh&&(this.scene.glplot.remove(this.delaunayMesh),this.delaunayMesh.dispose())},e.exports=function(t,e){var r=new v(t,e.uid);return r.update(e),r}},{\"../../components/fx/helpers\":702,\"../../constants/gl3d_dashes\":776,\"../../constants/gl3d_markers\":777,\"../../lib\":803,\"../../lib/gl_format_color\":799,\"../../lib/str2rgbarray\":828,\"../../plots/cartesian/axes\":854,\"../scatter/make_bubble_size_func\":1235,\"./calc_errors\":1248,\"delaunay-triangulate\":180,\"gl-error3d\":273,\"gl-line3d\":281,\"gl-mesh3d\":315,\"gl-scatter3d\":334}],1250:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),i=t(\"../../lib\"),a=t(\"../scatter/subtypes\"),o=t(\"../scatter/marker_defaults\"),s=t(\"../scatter/line_defaults\"),l=t(\"../scatter/text_defaults\"),c=t(\"./attributes\");e.exports=function(t,e,r,u){function f(r,n){return i.coerce(t,e,c,r,n)}if(function(t,e,r,i){var a=0,o=r(\"x\"),s=r(\"y\"),l=r(\"z\");n.getComponentMethod(\"calendars\",\"handleTraceDefaults\")(t,e,[\"x\",\"y\",\"z\"],i),o&&s&&l&&(a=Math.min(o.length,s.length,l.length),e._length=e._xlength=e._ylength=e._zlength=a);return 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strict\";e.exports={plot:t(\"./convert\"),attributes:t(\"./attributes\"),markerSymbols:t(\"../../constants/gl3d_markers\"),supplyDefaults:t(\"./defaults\"),colorbar:[{container:\"marker\",min:\"cmin\",max:\"cmax\"},{container:\"line\",min:\"cmin\",max:\"cmax\"}],calc:t(\"./calc\"),moduleType:\"trace\",name:\"scatter3d\",basePlotModule:t(\"../../plots/gl3d\"),categories:[\"gl3d\",\"symbols\",\"showLegend\",\"scatter-like\"],meta:{}}},{\"../../constants/gl3d_markers\":777,\"../../plots/gl3d\":896,\"./attributes\":1246,\"./calc\":1247,\"./convert\":1249,\"./defaults\":1250}],1252:[function(t,e,r){\"use strict\";var n=t(\"../scatter/attributes\"),i=t(\"../../plots/attributes\"),a=t(\"../../plots/template_attributes\").hovertemplateAttrs,o=t(\"../../plots/template_attributes\").texttemplateAttrs,s=t(\"../../components/colorscale/attributes\"),l=t(\"../../lib/extend\").extendFlat,c=n.marker,u=n.line,f=c.line;e.exports={carpet:{valType:\"string\",editType:\"calc\"},a:{valType:\"data_array\",editType:\"calc\"},b:{valType:\"data_array\",editType:\"calc\"},mode:l({},n.mode,{dflt:\"markers\"}),text:l({},n.text,{}),texttemplate:o({editType:\"plot\"},{keys:[\"a\",\"b\",\"text\"]}),hovertext:l({},n.hovertext,{}),line:{color:u.color,width:u.width,dash:u.dash,shape:l({},u.shape,{values:[\"linear\",\"spline\"]}),smoothing:u.smoothing,editType:\"calc\"},connectgaps:n.connectgaps,fill:l({},n.fill,{values:[\"none\",\"toself\",\"tonext\"],dflt:\"none\"}),fillcolor:n.fillcolor,marker:l({symbol:c.symbol,opacity:c.opacity,maxdisplayed:c.maxdisplayed,size:c.size,sizeref:c.sizeref,sizemin:c.sizemin,sizemode:c.sizemode,line:l({width:f.width,editType:\"calc\"},s(\"marker.line\")),gradient:c.gradient,editType:\"calc\"},s(\"marker\")),textfont:n.textfont,textposition:n.textposition,selected:n.selected,unselected:n.unselected,hoverinfo:l({},i.hoverinfo,{flags:[\"a\",\"b\",\"text\",\"name\"]}),hoveron:n.hoveron,hovertemplate:a()}},{\"../../components/colorscale/attributes\":673,\"../../lib/extend\":793,\"../../plots/attributes\":850,\"../../plots/template_attributes\":926,\"../scatter/attributes\":1218}],1253:[function(t,e,r){\"use 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n=t(\"../../lib\"),i=t(\"../scatter/constants\"),a=t(\"../scatter/subtypes\"),o=t(\"../scatter/marker_defaults\"),s=t(\"../scatter/line_defaults\"),l=t(\"../scatter/line_shape_defaults\"),c=t(\"../scatter/text_defaults\"),u=t(\"../scatter/fillcolor_defaults\"),f=t(\"./attributes\");e.exports=function(t,e,r,h){function p(r,i){return n.coerce(t,e,f,r,i)}p(\"carpet\"),e.xaxis=\"x\",e.yaxis=\"y\";var d=p(\"a\"),g=p(\"b\"),m=Math.min(d.length,g.length);if(m){e._length=m,p(\"text\"),p(\"texttemplate\"),p(\"hovertext\"),p(\"mode\",m<i.PTS_LINESONLY?\"lines+markers\":\"lines\"),a.hasLines(e)&&(s(t,e,r,h,p),l(t,e,p),p(\"connectgaps\")),a.hasMarkers(e)&&o(t,e,r,h,p,{gradient:!0}),a.hasText(e)&&c(t,e,h,p);var v=[];(a.hasMarkers(e)||a.hasText(e))&&(p(\"marker.maxdisplayed\"),v.push(\"points\")),p(\"fill\"),\"none\"!==e.fill&&(u(t,e,r,p),a.hasLines(e)||l(t,e,p)),\"tonext\"!==e.fill&&\"toself\"!==e.fill||v.push(\"fills\"),\"fills\"!==p(\"hoveron\",v.join(\"+\")||\"points\")&&p(\"hovertemplate\"),n.coerceSelectionMarkerOpacity(e,p)}else e.visible=!1}},{\"../../lib\":803,\"../scatter/constants\":1222,\"../scatter/fillcolor_defaults\":1226,\"../scatter/line_defaults\":1231,\"../scatter/line_shape_defaults\":1233,\"../scatter/marker_defaults\":1237,\"../scatter/subtypes\":1243,\"../scatter/text_defaults\":1244,\"./attributes\":1252}],1255:[function(t,e,r){\"use strict\";e.exports=function(t,e,r,n,i){var a=n[i];return t.a=a.a,t.b=a.b,t.y=a.y,t}},{}],1256:[function(t,e,r){\"use strict\";e.exports=function(t,e){var r={},n=e._carpet,i=n.ab2ij([t.a,t.b]),a=Math.floor(i[0]),o=i[0]-a,s=Math.floor(i[1]),l=i[1]-s,c=n.evalxy([],a,s,o,l);return r.yLabel=c[1].toFixed(3),r}},{}],1257:[function(t,e,r){\"use 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n=t(\"../../plots/template_attributes\").hovertemplateAttrs,i=t(\"../../plots/template_attributes\").texttemplateAttrs,a=t(\"../scatter/attributes\"),o=t(\"../../plots/attributes\"),s=t(\"../../components/colorscale/attributes\"),l=t(\"../../components/drawing/attributes\").dash,c=t(\"../../lib/extend\").extendFlat,u=t(\"../../plot_api/edit_types\").overrideAll,f=a.marker,h=a.line,p=f.line;e.exports=u({lon:{valType:\"data_array\"},lat:{valType:\"data_array\"},locations:{valType:\"data_array\"},locationmode:{valType:\"enumerated\",values:[\"ISO-3\",\"USA-states\",\"country 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n=t(\"../../lib\"),i=t(\"../scatter/subtypes\"),a=t(\"../scatter/marker_defaults\"),o=t(\"../scatter/line_defaults\"),s=t(\"../scatter/text_defaults\"),l=t(\"../scatter/fillcolor_defaults\"),c=t(\"./attributes\");e.exports=function(t,e,r,u){function f(r,i){return n.coerce(t,e,c,r,i)}var h,p=f(\"locations\");if(p&&p.length){var d,g=f(\"geojson\");(\"string\"==typeof g&&\"\"!==g||n.isPlainObject(g))&&(d=\"geojson-id\"),\"geojson-id\"===f(\"locationmode\",d)&&f(\"featureidkey\"),h=p.length}else{var 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t.lonLabel=b.lonLabel,t.latLabel=b.latLabel,t.color=a(c,g),t.extraText=function(t,e,r,n){if(t.hovertemplate)return;var i=e.hi||t.hoverinfo,a=\"all\"===i?s.hoverinfo.flags:i.split(\"+\"),l=-1!==a.indexOf(\"location\")&&Array.isArray(t.locations),c=-1!==a.indexOf(\"lon\"),u=-1!==a.indexOf(\"lat\"),f=-1!==a.indexOf(\"text\"),h=[];function p(t){return t+\"\\xb0\"}l?h.push(e.loc):c&&u?h.push(\"(\"+p(r.latLabel)+\", \"+p(r.lonLabel)+\")\"):c?h.push(n.lon+p(r.lonLabel)):u&&h.push(n.lat+p(r.latLabel));f&&o(e,t,h);return h.join(\"<br>\")}(c,g,t,l[0].t.labels),t.hovertemplate=c.hovertemplate,[t]}}},{\"../../components/fx\":706,\"../../constants/numerical\":779,\"../../lib\":803,\"../scatter/get_trace_color\":1228,\"./attributes\":1260}],1266:[function(t,e,r){\"use 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n=t(\"@plotly/d3\"),i=t(\"../../lib\"),a=t(\"../../lib/topojson_utils\").getTopojsonFeatures,o=t(\"../../lib/geojson_utils\"),s=t(\"../../lib/geo_location_utils\"),l=t(\"../../plots/cartesian/autorange\").findExtremes,c=t(\"../../constants/numerical\").BADNUM,u=t(\"../scatter/calc\").calcMarkerSize,f=t(\"../scatter/subtypes\"),h=t(\"./style\");e.exports={calcGeoJSON:function(t,e){var r,n,i=t[0].trace,o=e[i.geo],f=o._subplot,h=i._length;if(Array.isArray(i.locations)){var p=i.locationmode,d=\"geojson-id\"===p?s.extractTraceFeature(t):a(i,f.topojson);for(r=0;r<h;r++){n=t[r];var g=\"geojson-id\"===p?n.fOut:s.locationToFeature(p,n.loc,d);n.lonlat=g?g.properties.ct:[c,c]}}var m,v,y={padded:!0};if(\"geojson\"===o.fitbounds&&\"geojson-id\"===i.locationmode){var x=s.computeBbox(s.getTraceGeojson(i));m=[x[0],x[2]],v=[x[1],x[3]]}else{for(m=new Array(h),v=new 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s=o.calcTraceToLineCoords(e),c=\"none\"!==a.fill?o.makePolygon(s):o.makeLine(s);r.selectAll(\"path.js-line\").data([{geojson:c,trace:a}]).enter().append(\"path\").classed(\"js-line\",!0).style(\"stroke-miterlimit\",2)}f.hasMarkers(a)&&r.selectAll(\"path.point\").data(i.identity).enter().append(\"path\").classed(\"point\",!0).each((function(t){l(t,this)})),f.hasText(a)&&r.selectAll(\"g\").data(i.identity).enter().append(\"g\").append(\"text\").each((function(t){l(t,this)})),h(t,e)}))}}},{\"../../constants/numerical\":779,\"../../lib\":803,\"../../lib/geo_location_utils\":796,\"../../lib/geojson_utils\":797,\"../../lib/topojson_utils\":832,\"../../plots/cartesian/autorange\":853,\"../scatter/calc\":1219,\"../scatter/subtypes\":1243,\"./style\":1269,\"@plotly/d3\":58}],1268:[function(t,e,r){\"use strict\";var n=t(\"../scatter/subtypes\"),i=t(\"../../constants/numerical\").BADNUM;e.exports=function(t,e){var 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e=n.select(this),r=t.trace,o=r.line||{};e.call(a.stroke,o.color).call(i.dashLine,o.dash||\"\",o.width||0),\"none\"!==r.fill&&e.call(a.fill,r.fillcolor)}))}(t,e)}},{\"../../components/color\":666,\"../../components/drawing\":688,\"../scatter/style\":1242,\"@plotly/d3\":58}],1270:[function(t,e,r){\"use strict\";var n=t(\"../../plots/attributes\"),i=t(\"../scatter/attributes\"),a=t(\"../../plots/cartesian/axis_format_attributes\").axisHoverFormat,o=t(\"../../components/colorscale/attributes\"),s=t(\"../../lib/sort_object_keys\"),l=t(\"../../lib/extend\").extendFlat,c=t(\"../../plot_api/edit_types\").overrideAll,u=t(\"./constants\").DASHES,f=i.line,h=i.marker,p=h.line,d=e.exports=c({x:i.x,x0:i.x0,dx:i.dx,y:i.y,y0:i.y0,dy:i.dy,xperiod:i.xperiod,yperiod:i.yperiod,xperiod0:i.xperiod0,yperiod0:i.yperiod0,xperiodalignment:i.xperiodalignment,yperiodalignment:i.yperiodalignment,xhoverformat:a(\"x\"),yhoverformat:a(\"y\"),text:i.text,hovertext:i.hovertext,textposition:i.textposition,textfont:i.textfont,mode:{valType:\"flaglist\",flags:[\"lines\",\"markers\",\"text\"],extras:[\"none\"]},line:{color:f.color,width:f.width,shape:{valType:\"enumerated\",values:[\"linear\",\"hv\",\"vh\",\"hvh\",\"vhv\"],dflt:\"linear\",editType:\"plot\"},dash:{valType:\"enumerated\",values:s(u),dflt:\"solid\"}},marker:l({},o(\"marker\"),{symbol:h.symbol,size:h.size,sizeref:h.sizeref,sizemin:h.sizemin,sizemode:h.sizemode,opacity:h.opacity,colorbar:h.colorbar,line:l({},o(\"marker.line\"),{width:p.width})}),connectgaps:i.connectgaps,fill:l({},i.fill,{dflt:\"none\"}),fillcolor:i.fillcolor,selected:{marker:i.selected.marker,textfont:i.selected.textfont},unselected:{marker:i.unselected.marker,textfont:i.unselected.textfont},opacity:n.opacity},\"calc\",\"nested\");d.x.editType=d.y.editType=d.x0.editType=d.y0.editType=\"calc+clearAxisTypes\",d.hovertemplate=i.hovertemplate,d.texttemplate=i.texttemplate},{\"../../components/colorscale/attributes\":673,\"../../lib/extend\":793,\"../../lib/sort_object_keys\":826,\"../../plot_api/edit_types\":836,\"../../plots/attributes\":850,\"../../plots/cartesian/axis_format_attributes\":857,\"../scatter/attributes\":1218,\"./constants\":1272}],1271:[function(t,e,r){\"use 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T=y-_,k=y+w;p[v+u[0]]=x-i.c2l(T),p[v+u[1]]=i.c2l(k)-x,p[v+u[2]]=0,p[v+u[3]]=0,d=Math.min(d,y-_),g=Math.max(g,y+w)}}}h[a]={positions:r,errors:p,_bnds:[d,g]}}}return p(i,l),p(a,u),h},textPosition:function(t,e,r,n){var i,a=e._length,o={};if(f.hasMarkers(e)){var s=r.font,l=r.align,c=r.baseline;for(o.offset=new Array(a),i=0;i<a;i++){var u=n.sizes?n.sizes[i]:n.size,h=Array.isArray(s)?s[i].size:s.size,p=Array.isArray(l)?l.length>1?l[i]:l[0]:l,d=Array.isArray(c)?c.length>1?c[i]:c[0]:c,g=m[p],v=m[d],y=u?u/.8+1:0,x=-v*y-.5*v;o.offset[i]=[g*y/h,x/h]}}return o}}},{\"../../components/drawing\":688,\"../../components/fx/helpers\":702,\"../../constants/interactions\":778,\"../../lib\":803,\"../../lib/gl_format_color\":799,\"../../plots/cartesian/axis_ids\":858,\"../../registry\":931,\"../scatter/make_bubble_size_func\":1235,\"../scatter/subtypes\":1243,\"./constants\":1272,\"./helpers\":1277,\"color-normalize\":131,\"fast-isnumeric\":249,\"svg-path-sdf\":595}],1274:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../registry\"),a=t(\"./helpers\"),o=t(\"./attributes\"),s=t(\"../scatter/constants\"),l=t(\"../scatter/subtypes\"),c=t(\"../scatter/xy_defaults\"),u=t(\"../scatter/period_defaults\"),f=t(\"../scatter/marker_defaults\"),h=t(\"../scatter/line_defaults\"),p=t(\"../scatter/fillcolor_defaults\"),d=t(\"../scatter/text_defaults\");e.exports=function(t,e,r,g){function m(r,i){return n.coerce(t,e,o,r,i)}var v=!!t.marker&&a.isOpenSymbol(t.marker.symbol),y=l.isBubble(t),x=c(t,e,g,m);if(x){u(t,e,g,m),m(\"xhoverformat\"),m(\"yhoverformat\");var b=x<s.PTS_LINESONLY?\"lines+markers\":\"lines\";m(\"text\"),m(\"hovertext\"),m(\"hovertemplate\"),m(\"mode\",b),l.hasLines(e)&&(m(\"connectgaps\"),h(t,e,r,g,m),m(\"line.shape\")),l.hasMarkers(e)&&(f(t,e,r,g,m),m(\"marker.line.width\",v||y?1:0)),l.hasText(e)&&(m(\"texttemplate\"),d(t,e,g,m));var _=(e.line||{}).color,w=(e.marker||{}).color;m(\"fill\"),\"none\"!==e.fill&&p(t,e,r,m);var T=i.getComponentMethod(\"errorbars\",\"supplyDefaults\");T(t,e,_||w||r,{axis:\"y\"}),T(t,e,_||w||r,{axis:\"x\",inherit:\"y\"}),n.coerceSelectionMarkerOpacity(e,m)}else e.visible=!1}},{\"../../lib\":803,\"../../registry\":931,\"../scatter/constants\":1222,\"../scatter/fillcolor_defaults\":1226,\"../scatter/line_defaults\":1231,\"../scatter/marker_defaults\":1237,\"../scatter/period_defaults\":1238,\"../scatter/subtypes\":1243,\"../scatter/text_defaults\":1244,\"../scatter/xy_defaults\":1245,\"./attributes\":1270,\"./helpers\":1277}],1275:[function(t,e,r){\"use strict\";var n=t(\"../../lib\"),i=t(\"../../components/color\"),a=t(\"../../constants/interactions\").DESELECTDIM;e.exports={styleTextSelection:function(t){var e,r,o=t[0],s=o.trace,l=o.t,c=l._scene,u=l.index,f=c.selectBatch[u],h=c.unselectBatch[u],p=c.textOptions[u],d=c.textSelectedOptions[u]||{},g=c.textUnselectedOptions[u]||{},m=n.extendFlat({},p);if(f.length||h.length){var v=d.color,y=g.color,x=p.color,b=Array.isArray(x);for(m.color=new Array(s._length),e=0;e<f.length;e++)r=f[e],m.color[r]=v||(b?x[r]:x);for(e=0;e<h.length;e++){r=h[e];var _=b?x[r]:x;m.color[r]=y||(v?_:i.addOpacity(_,a))}}c.glText[u].update(m)}}},{\"../../components/color\":666,\"../../constants/interactions\":778,\"../../lib\":803}],1276:[function(t,e,r){\"use strict\";var n=t(\"../scatter/format_labels\");e.exports=function(t,e,r){var i=t.i;return\"x\"in t||(t.x=e._x[i]),\"y\"in t||(t.y=e._y[i]),n(t,e,r)}},{\"../scatter/format_labels\":1227}],1277:[function(t,e,r){\"use strict\";var n=t(\"./constants\");r.isOpenSymbol=function(t){return\"string\"==typeof t?n.OPEN_RE.test(t):t%200>100},r.isDotSymbol=function(t){return\"string\"==typeof t?n.DOT_RE.test(t):t>200}},{\"./constants\":1272}],1278:[function(t,e,r){\"use strict\";var n=t(\"../../registry\"),i=t(\"../../lib\"),a=t(\"../scatter/get_trace_color\");function o(t,e,r,o){var s=t.xa,l=t.ya,c=t.distance,u=t.dxy,f=t.index,h={pointNumber:f,x:e[f],y:r[f]};h.tx=Array.isArray(o.text)?o.text[f]:o.text,h.htx=Array.isArray(o.hovertext)?o.hovertext[f]:o.hovertext,h.data=Array.isArray(o.customdata)?o.customdata[f]:o.customdata,h.tp=Array.isArray(o.textposition)?o.textposition[f]:o.textposition;var p=o.textfont;p&&(h.ts=i.isArrayOrTypedArray(p.size)?p.size[f]:p.size,h.tc=Array.isArray(p.color)?p.color[f]:p.color,h.tf=Array.isArray(p.family)?p.family[f]:p.family);var d=o.marker;d&&(h.ms=i.isArrayOrTypedArray(d.size)?d.size[f]:d.size,h.mo=i.isArrayOrTypedArray(d.opacity)?d.opacity[f]:d.opacity,h.mx=i.isArrayOrTypedArray(d.symbol)?d.symbol[f]:d.symbol,h.mc=i.isArrayOrTypedArray(d.color)?d.color[f]:d.color);var g=d&&d.line;g&&(h.mlc=Array.isArray(g.color)?g.color[f]:g.color,h.mlw=i.isArrayOrTypedArray(g.width)?g.width[f]:g.width);var m=d&&d.gradient;m&&\"none\"!==m.type&&(h.mgt=Array.isArray(m.type)?m.type[f]:m.type,h.mgc=Array.isArray(m.color)?m.color[f]:m.color);var v=s.c2p(h.x,!0),y=l.c2p(h.y,!0),x=h.mrc||1,b=o.hoverlabel;b&&(h.hbg=Array.isArray(b.bgcolor)?b.bgcolor[f]:b.bgcolor,h.hbc=Array.isArray(b.bordercolor)?b.bordercolor[f]:b.bordercolor,h.hts=i.isArrayOrTypedArray(b.font.size)?b.font.size[f]:b.font.size,h.htc=Array.isArray(b.font.color)?b.font.color[f]:b.font.color,h.htf=Array.isArray(b.font.family)?b.font.family[f]:b.font.family,h.hnl=i.isArrayOrTypedArray(b.namelength)?b.namelength[f]:b.namelength);var _=o.hoverinfo;_&&(h.hi=Array.isArray(_)?_[f]:_);var w=o.hovertemplate;w&&(h.ht=Array.isArray(w)?w[f]:w);var T={};T[t.index]=h;var k=o._origX,A=o._origY,M=i.extendFlat({},t,{color:a(o,h),x0:v-x,x1:v+x,xLabelVal:k?k[f]:h.x,y0:y-x,y1:y+x,yLabelVal:A?A[f]:h.y,cd:T,distance:c,spikeDistance:u,hovertemplate:h.ht});return h.htx?M.text=h.htx:h.tx?M.text=h.tx:o.text&&(M.text=o.text),i.fillText(h,o,M),n.getComponentMethod(\"errorbars\",\"hoverInfo\")(h,o,M),M}e.exports={hoverPoints:function(t,e,r,n){var i,a,s,l,c,u,f,h,p,d,g=t.cd,m=g[0].t,v=g[0].trace,y=t.xa,x=t.ya,b=m.x,_=m.y,w=y.c2p(e),T=x.c2p(r),k=t.distance;if(m.tree){var A=y.p2c(w-k),M=y.p2c(w+k),S=x.p2c(T-k),E=x.p2c(T+k);i=\"x\"===n?m.tree.range(Math.min(A,M),Math.min(x._rl[0],x._rl[1]),Math.max(A,M),Math.max(x._rl[0],x._rl[1])):m.tree.range(Math.min(A,M),Math.min(S,E),Math.max(A,M),Math.max(S,E))}else i=m.ids;var L=k;if(\"x\"===n){var C=!!v.xperiodalignment,P=!!v.yperiodalignment;for(u=0;u<i.length;u++){if(l=b[a=i[u]],f=Math.abs(y.c2p(l)-w),C){var I=y.c2p(v._xStarts[a]),O=y.c2p(v._xEnds[a]);f=w>=Math.min(I,O)&&w<=Math.max(I,O)?0:1/0}if(f<L){if(L=f,c=_[a],h=x.c2p(c)-T,P){var z=x.c2p(v._yStarts[a]),D=x.c2p(v._yEnds[a]);h=T>=Math.min(z,D)&&T<=Math.max(z,D)?0:1/0}d=Math.sqrt(f*f+h*h),s=i[u]}}}else for(u=i.length-1;u>-1;u--)l=b[a=i[u]],c=_[a],f=y.c2p(l)-w,h=x.c2p(c)-T,(p=Math.sqrt(f*f+h*h))<L&&(L=d=p,s=a);return t.index=s,t.distance=L,t.dxy=d,void 0===s?[t]:[o(t,b,_,v)]},calcHover:o}},{\"../../lib\":803,\"../../registry\":931,\"../scatter/get_trace_color\":1228}],1279:[function(t,e,r){\"use strict\";var n=t(\"./hover\");e.exports={moduleType:\"trace\",name:\"scattergl\",basePlotModule:t(\"../../plots/cartesian\"),categories:[\"gl\",\"regl\",\"cartesian\",\"symbols\",\"errorBarsOK\",\"showLegend\",\"scatter-like\"],attributes:t(\"./attributes\"),supplyDefaults:t(\"./defaults\"),crossTraceDefaults:t(\"../scatter/cross_trace_defaults\"),colorbar:t(\"../scatter/marker_colorbar\"),formatLabels:t(\"./format_labels\"),calc:t(\"./calc\"),plot:t(\"./plot\"),hoverPoints:n.hoverPoints,selectPoints:t(\"./select\"),meta:{}}},{\"../../plots/cartesian\":868,\"../scatter/cross_trace_defaults\":1224,\"../scatter/marker_colorbar\":1236,\"./attributes\":1270,\"./calc\":1271,\"./defaults\":1274,\"./format_labels\":1276,\"./hover\":1278,\"./plot\":1280,\"./select\":1282}],1280:[function(t,e,r){\"use strict\";var n=t(\"regl-scatter2d\"),i=t(\"regl-line2d\"),a=t(\"regl-error2d\"),o=t(\"gl-text\"),s=t(\"../../lib\"),l=t(\"../../components/dragelement/helpers\").selectMode,c=t(\"../../lib/prepare_regl\"),u=t(\"../scatter/subtypes\"),f=t(\"../scatter/link_traces\"),h=t(\"./edit_style\").styleTextSelection;function p(t,e,r,n){var i=t._size,a=t.width*n,o=t.height*n,s=i.l*n,l=i.b*n,c=i.r*n,u=i.t*n,f=i.w*n,h=i.h*n;return[s+e.domain[0]*f,l+r.domain[0]*h,a-c-(1-e.domain[1])*f,o-u-(1-r.domain[1])*h]}e.exports=function(t,e,r){if(r.length){var d,g,m=t._fullLayout,v=e._scene,y=e.xaxis,x=e.yaxis;if(v)if(c(t,[\"ANGLE_instanced_arrays\",\"OES_element_index_uint\"])){var b=v.count,_=m._glcanvas.data()[0].regl;if(f(t,e,r),v.dirty){if(!0===v.error2d&&(v.error2d=a(_)),!0===v.line2d&&(v.line2d=i(_)),!0===v.scatter2d&&(v.scatter2d=n(_)),!0===v.fill2d&&(v.fill2d=i(_)),!0===v.glText)for(v.glText=new Array(b),d=0;d<b;d++)v.glText[d]=new o(_);if(v.glText){if(b>v.glText.length){var w=b-v.glText.length;for(d=0;d<w;d++)v.glText.push(new o(_))}else if(b<v.glText.length){var T=v.glText.length-b;v.glText.splice(b,T).forEach((function(t){t.destroy()}))}for(d=0;d<b;d++)v.glText[d].update(v.textOptions[d])}if(v.line2d&&(v.line2d.update(v.lineOptions),v.lineOptions=v.lineOptions.map((function(t){if(t&&t.positions){for(var e=t.positions,r=0;r<e.length&&(isNaN(e[r])||isNaN(e[r+1]));)r+=2;for(var n=e.length-2;n>r&&(isNaN(e[n])||isNaN(e[n+1]));)n-=2;t.positions=e.slice(r,n+2)}return t})),v.line2d.update(v.lineOptions)),v.error2d){var k=(v.errorXOptions||[]).concat(v.errorYOptions||[]);v.error2d.update(k)}v.scatter2d&&v.scatter2d.update(v.markerOptions),v.fillOrder=s.repeat(null,b),v.fill2d&&(v.fillOptions=v.fillOptions.map((function(t,e){var n=r[e];if(t&&n&&n[0]&&n[0].trace){var i,a,o=n[0],s=o.trace,l=o.t,c=v.lineOptions[e],u=[];s._ownfill&&u.push(e),s._nexttrace&&u.push(e+1),u.length&&(v.fillOrder[e]=u);var f,h,p=[],d=c&&c.positions||l.positions;if(\"tozeroy\"===s.fill){for(f=0;f<d.length&&isNaN(d[f+1]);)f+=2;for(h=d.length-2;h>f&&isNaN(d[h+1]);)h-=2;0!==d[f+1]&&(p=[d[f],0]),p=p.concat(d.slice(f,h+2)),0!==d[h+1]&&(p=p.concat([d[h],0]))}else if(\"tozerox\"===s.fill){for(f=0;f<d.length&&isNaN(d[f]);)f+=2;for(h=d.length-2;h>f&&isNaN(d[h]);)h-=2;0!==d[f]&&(p=[0,d[f+1]]),p=p.concat(d.slice(f,h+2)),0!==d[h]&&(p=p.concat([0,d[h+1]]))}else if(\"toself\"===s.fill||\"tonext\"===s.fill){for(p=[],i=0,t.splitNull=!0,a=0;a<d.length;a+=2)(isNaN(d[a])||isNaN(d[a+1]))&&((p=p.concat(d.slice(i,a))).push(d[i],d[i+1]),p.push(null,null),i=a+2);p=p.concat(d.slice(i)),i&&p.push(d[i],d[i+1])}else{var g=s._nexttrace;if(g){var m=v.lineOptions[e+1];if(m){var y=m.positions;if(\"tonexty\"===s.fill){for(p=d.slice(),e=Math.floor(y.length/2);e--;){var x=y[2*e],b=y[2*e+1];isNaN(x)||isNaN(b)||p.push(x,b)}t.fill=g.fillcolor}}}}if(s._prevtrace&&\"tonext\"===s._prevtrace.fill){var _=v.lineOptions[e-1].positions,w=p.length/2,T=[i=w];for(a=0;a<_.length;a+=2)(isNaN(_[a])||isNaN(_[a+1]))&&(T.push(a/2+w+1),i=a+2);p=p.concat(_),t.hole=T}return t.fillmode=s.fill,t.opacity=s.opacity,t.positions=p,t}})),v.fill2d.update(v.fillOptions))}var A=m.dragmode,M=l(A),S=m.clickmode.indexOf(\"select\")>-1;for(d=0;d<b;d++){var E=r[d][0],L=E.trace,C=E.t,P=C.index,I=L._length,O=C.x,z=C.y;if(L.selectedpoints||M||S){if(M||(M=!0),L.selectedpoints){var D=v.selectBatch[P]=s.selIndices2selPoints(L),R={};for(g=0;g<D.length;g++)R[D[g]]=1;var F=[];for(g=0;g<I;g++)R[g]||F.push(g);v.unselectBatch[P]=F}var B=C.xpx=new Array(I),N=C.ypx=new Array(I);for(g=0;g<I;g++)B[g]=y.c2p(O[g]),N[g]=x.c2p(z[g])}else C.xpx=C.ypx=null}if(M){if(v.select2d||(v.select2d=n(m._glcanvas.data()[1].regl)),v.scatter2d){var j=new Array(b);for(d=0;d<b;d++)j[d]=v.selectBatch[d].length||v.unselectBatch[d].length?v.markerUnselectedOptions[d]:{};v.scatter2d.update(j)}v.select2d&&(v.select2d.update(v.markerOptions),v.select2d.update(v.markerSelectedOptions)),v.glText&&r.forEach((function(t){var e=((t||[])[0]||{}).trace||{};u.hasText(e)&&h(t)}))}else v.scatter2d&&v.scatter2d.update(v.markerOptions);var U={viewport:p(m,y,x,t._context.plotGlPixelRatio),range:[(y._rl||y.range)[0],(x._rl||x.range)[0],(y._rl||y.range)[1],(x._rl||x.range)[1]]},V=s.repeat(U,v.count);v.fill2d&&v.fill2d.update(V),v.line2d&&v.line2d.update(V),v.error2d&&v.error2d.update(V.concat(V)),v.scatter2d&&v.scatter2d.update(V),v.select2d&&v.select2d.update(V),v.glText&&v.glText.forEach((function(t){t.update(U)}))}else v.init()}}},{\"../../components/dragelement/helpers\":684,\"../../lib\":803,\"../../lib/prepare_regl\":816,\"../scatter/link_traces\":1234,\"../scatter/subtypes\":1243,\"./edit_style\":1275,\"gl-text\":355,\"regl-error2d\":536,\"regl-line2d\":537,\"regl-scatter2d\":538}],1281:[function(t,e,r){\"use strict\";var n=t(\"../../lib\");e.exports=function(t,e){var r=e._scene,i={count:0,dirty:!0,lineOptions:[],fillOptions:[],markerOptions:[],markerSelectedOptions:[],markerUnselectedOptions:[],errorXOptions:[],errorYOptions:[],textOptions:[],textSelectedOptions:[],textUnselectedOptions:[],selectBatch:[],unselectBatch:[]},a={fill2d:!1,scatter2d:!1,error2d:!1,line2d:!1,glText:!1,select2d:!1};return e._scene||((r=e._scene={}).init=function(){n.extendFlat(r,a,i)},r.init(),r.update=function(t){var e=n.repeat(t,r.count);if(r.fill2d&&r.fill2d.update(e),r.scatter2d&&r.scatter2d.update(e),r.line2d&&r.line2d.update(e),r.error2d&&r.error2d.update(e.concat(e)),r.select2d&&r.select2d.update(e),r.glText)for(var i=0;i<r.count;i++)r.glText[i].update(t)},r.draw=function(){for(var t=r.count,e=r.fill2d,i=r.error2d,a=r.line2d,o=r.scatter2d,s=r.glText,l=r.select2d,c=r.selectBatch,u=r.unselectBatch,f=0;f<t;f++){if(e&&r.fillOrder[f]&&e.draw(r.fillOrder[f]),a&&r.lineOptions[f]&&a.draw(f),i&&(r.errorXOptions[f]&&i.draw(f),r.errorYOptions[f]&&i.draw(f+t)),o&&r.markerOptions[f])if(u[f].length){var h=n.repeat([],r.count);h[f]=u[f],o.draw(h)}else c[f].length||o.draw(f);s[f]&&r.textOptions[f]&&s[f].render()}l&&l.draw(c),r.dirty=!1},r.destroy=function(){r.fill2d&&r.fill2d.destroy&&r.fill2d.destroy(),r.scatter2d&&r.scatter2d.destroy&&r.scatter2d.destroy(),r.error2d&&r.error2d.destroy&&r.error2d.destroy(),r.line2d&&r.line2d.destroy&&r.line2d.destroy(),r.select2d&&r.select2d.destroy&&r.select2d.destroy(),r.glText&&r.glText.forEach((function(t){t.destroy&&t.destroy()})),r.lineOptions=null,r.fillOptions=null,r.markerOptions=null,r.markerSelectedOptions=null,r.markerUnselectedOptions=null,r.errorXOptions=null,r.errorYOptions=null,r.textOptions=null,r.textSelectedOptions=null,r.textUnselectedOptions=null,r.selectBatch=null,r.unselectBatch=null,e._scene=null}),r.dirty||n.extendFlat(r,i),r}},{\"../../lib\":803}],1282:[function(t,e,r){\"use strict\";var n=t(\"../scatter/subtypes\"),i=t(\"./edit_style\").styleTextSelection;e.exports=function(t,e){var r=t.cd,a=t.xaxis,o=t.yaxis,s=[],l=r[0].trace,c=r[0].t,u=l._length,f=c.x,h=c.y,p=c._scene,d=c.index;if(!p)return s;var g=n.hasText(l),m=n.hasMarkers(l),v=!m&&!g;if(!0!==l.visible||v)return s;var y=[],x=[];if(!1!==e&&!e.degenerate)for(var b=0;b<u;b++)e.contains([c.xpx[b],c.ypx[b]],!1,b,t)?(y.push(b),s.push({pointNumber:b,x:a.c2d(f[b]),y:o.c2d(h[b])})):x.push(b);if(m){var _=p.scatter2d;if(y.length||x.length){if(!p.selectBatch[d].length&&!p.unselectBatch[d].length){var w=new Array(p.count);w[d]=p.markerUnselectedOptions[d],_.update.apply(_,w)}}else{var T=new Array(p.count);T[d]=p.markerOptions[d],_.update.apply(_,T)}}return p.selectBatch[d]=y,p.unselectBatch[d]=x,g&&i(r),s}},{\"../scatter/subtypes\":1243,\"./edit_style\":1275}],1283:[function(t,e,r){\"use strict\";var n=t(\"../../plots/template_attributes\").hovertemplateAttrs,i=t(\"../../plots/template_attributes\").texttemplateAttrs,a=t(\"../scattergeo/attributes\"),o=t(\"../scatter/attributes\"),s=t(\"../../plots/mapbox/layout_attributes\"),l=t(\"../../plots/attributes\"),c=t(\"../../components/colorscale/attributes\"),u=t(\"../../lib/extend\").extendFlat,f=t(\"../../plot_api/edit_types\").overrideAll,h=a.line,p=a.marker;e.exports=f({lon:a.lon,lat:a.lat,mode:u({},o.mode,{dflt:\"markers\"}),text:u({},o.text,{}),texttemplate:i({editType:\"plot\"},{keys:[\"lat\",\"lon\",\"text\"]}),hovertext:u({},o.hovertext,{}),line:{color:h.color,width:h.width},connectgaps:o.connectgaps,marker:u({symbol:{valType:\"string\",dflt:\"circle\",arrayOk:!0},angle:{valType:\"number\",dflt:\"auto\",arrayOk:!0},allowoverlap:{valType:\"boolean\",dflt:!1},opacity:p.opacity,size:p.size,sizeref:p.sizeref,sizemin:p.sizemin,sizemode:p.sizemode},c(\"marker\")),fill:a.fill,fillcolor:o.fillcolor,textfont:s.layers.symbol.textfont,textposition:s.layers.symbol.textposition,below:{valType:\"string\"},selected:{marker:o.selected.marker},unselected:{marker:o.unselected.marker},hoverinfo:u({},l.hoverinfo,{flags:[\"lon\",\"lat\",\"text\",\"name\"]}),hovertemplate:n()},\"calc\",\"nested\")},{\"../../components/colorscale/attributes\":673,\"../../lib/extend\":793,\"../../plot_api/edit_types\":836,\"../../plots/attributes\":850,\"../../plots/mapbox/layout_attributes\":913,\"../../plots/template_attributes\":926,\"../scatter/attributes\":1218,\"../scattergeo/attributes\":1260}],1284:[function(t,e,r){\"use strict\";var n=t(\"fast-isnumeric\"),i=t(\"../../lib\"),a=t(\"../../constants/numerical\").BADNUM,o=t(\"../../lib/geojson_utils\"),s=t(\"../../components/colorscale\"),l=t(\"../../components/drawing\"),c=t(\"../scatter/make_bubble_size_func\"),u=t(\"../scatter/subtypes\"),f=t(\"../../plots/mapbox/convert_text_opts\"),h=t(\"../../components/fx/helpers\").appendArrayPointValue,p=t(\"../../lib/svg_text_utils\").NEWLINES,d=t(\"../../lib/svg_text_utils\").BR_TAG_ALL;function g(){return{geojson:o.makeBlank(),layout:{visibility:\"none\"},paint:{}}}function m(t,e){return i.isArrayOrTypedArray(t)?e?function(e){return n(t[e])?+t[e]:0}:function(e){return t[e]}:t?function(){return t}:v}function v(){return\"\"}function y(t){return t[0]===a}e.exports=function(t,e){var r,a=e[0].trace,x=!0===a.visible&&0!==a._length,b=\"none\"!==a.fill,_=u.hasLines(a),w=u.hasMarkers(a),T=u.hasText(a),k=w&&\"circle\"===a.marker.symbol,A=w&&\"circle\"!==a.marker.symbol,M=g(),S=g(),E=g(),L=g(),C={fill:M,line:S,circle:E,symbol:L};if(!x)return C;if((b||_)&&(r=o.calcTraceToLineCoords(e)),b&&(M.geojson=o.makePolygon(r),M.layout.visibility=\"visible\",i.extendFlat(M.paint,{\"fill-color\":a.fillcolor})),_&&(S.geojson=o.makeLine(r),S.layout.visibility=\"visible\",i.extendFlat(S.paint,{\"line-width\":a.line.width,\"line-color\":a.line.color,\"line-opacity\":a.opacity})),k){var P=function(t){var e,r,a,o,u=t[0].trace,f=u.marker,h=u.selectedpoints,p=i.isArrayOrTypedArray(f.color),d=i.isArrayOrTypedArray(f.size),g=i.isArrayOrTypedArray(f.opacity);function m(t){return u.opacity*t}p&&(r=s.hasColorscale(u,\"marker\")?s.makeColorScaleFuncFromTrace(f):i.identity);d&&(a=c(u));g&&(o=function(t){return m(n(t)?+i.constrain(t,0,1):0)});var v,x=[];for(e=0;e<t.length;e++){var b=t[e],_=b.lonlat;if(!y(_)){var w={};r&&(w.mcc=b.mcc=r(b.mc)),a&&(w.mrc=b.mrc=a(b.ms)),o&&(w.mo=o(b.mo)),h&&(w.selected=b.selected||0),x.push({type:\"Feature\",geometry:{type:\"Point\",coordinates:_},properties:w})}}if(h)for(v=l.makeSelectedPointStyleFns(u),e=0;e<x.length;e++){var T=x[e].properties;v.selectedOpacityFn&&(T.mo=m(v.selectedOpacityFn(T))),v.selectedColorFn&&(T.mcc=v.selectedColorFn(T)),v.selectedSizeFn&&(T.mrc=v.selectedSizeFn(T))}return{geojson:{type:\"FeatureCollection\",features:x},mcc:p||v&&v.selectedColorFn?{type:\"identity\",property:\"mcc\"}:f.color,mrc:d||v&&v.selectedSizeFn?{type:\"identity\",property:\"mrc\"}:(k=f.size,k/2),mo:g||v&&v.selectedOpacityFn?{type:\"identity\",property:\"mo\"}:m(f.opacity)};var k}(e);E.geojson=P.geojson,E.layout.visibility=\"visible\",i.extendFlat(E.paint,{\"circle-color\":P.mcc,\"circle-radius\":P.mrc,\"circle-opacity\":P.mo})}if((A||T)&&(L.geojson=function(t,e){for(var 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n=t(\"../../lib\"),i=t(\"../scatter/subtypes\"),a=t(\"../scatter/marker_defaults\"),o=t(\"../scatter/line_defaults\"),s=t(\"../scatter/line_shape_defaults\"),l=t(\"../scatter/text_defaults\"),c=t(\"../scatter/fillcolor_defaults\"),u=t(\"../scatter/constants\").PTS_LINESONLY,f=t(\"./attributes\");function h(t,e,r,n){var i,a=n(\"r\"),o=n(\"theta\");if(a)o?i=Math.min(a.length,o.length):(i=a.length,n(\"theta0\"),n(\"dtheta\"));else{if(!o)return 0;i=e.theta.length,n(\"r0\"),n(\"dr\")}return e._length=i,i}e.exports={handleRThetaDefaults:h,supplyDefaults:function(t,e,r,p){function d(r,i){return n.coerce(t,e,f,r,i)}var g=h(t,e,p,d);if(g){d(\"thetaunit\"),d(\"mode\",g<u?\"lines+markers\":\"lines\"),d(\"text\"),d(\"hovertext\"),\"fills\"!==e.hoveron&&d(\"hovertemplate\"),i.hasLines(e)&&(o(t,e,r,p,d),s(t,e,d),d(\"connectgaps\")),i.hasMarkers(e)&&a(t,e,r,p,d,{gradient:!0}),i.hasText(e)&&(d(\"texttemplate\"),l(t,e,p,d));var 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e,r,i,a,s,l,c,u,f,h,p,d,g=t._x,m=t._y,v=t._z,y=t._len,x=-1/0,b=1/0,_=-1/0,w=1/0,T=-1/0,k=1/0,A=\"\";for(y&&(c=g[0],f=m[0],p=v[0]),y>1&&(u=g[y-1],h=m[y-1],d=v[y-1]),e=0;e<y;e++)x=Math.max(x,g[e]),b=Math.min(b,g[e]),_=Math.max(_,m[e]),w=Math.min(w,m[e]),T=Math.max(T,v[e]),k=Math.min(k,v[e]),a||g[e]===c||(a=!0,A+=\"x\"),s||m[e]===f||(s=!0,A+=\"y\"),l||v[e]===p||(l=!0,A+=\"z\");a||(A+=\"x\"),s||(A+=\"y\"),l||(A+=\"z\");var M=o(t._x),S=o(t._y),E=o(t._z);A=(A=(A=A.replace(\"x\",(c>u?\"-\":\"+\")+\"x\")).replace(\"y\",(f>h?\"-\":\"+\")+\"y\")).replace(\"z\",(p>d?\"-\":\"+\")+\"z\");var L=function(){y=0,M=[],S=[],E=[]};(!y||y<M.length*S.length*E.length)&&L();var C=function(t){return\"x\"===t?g:\"y\"===t?m:v},P=function(t){return\"x\"===t?M:\"y\"===t?S:E},I=function(t){return t[y-1]<t[0]?-1:1},O=C(A[1]),z=C(A[3]),D=C(A[5]),R=P(A[1]).length,F=P(A[3]).length,B=P(A[5]).length,N=!1,j=function(t,e,r){return 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0},{\"../../components/color\":666,\"../../components/colorscale/attributes\":673,\"../../lib/extend\":793,\"../../plot_api/edit_types\":836,\"../../plots/attributes\":850,\"../../plots/cartesian/axis_format_attributes\":857,\"../../plots/template_attributes\":926}],1343:[function(t,e,r){\"use strict\";var n=t(\"../../components/colorscale/calc\");e.exports=function(t,e){e.surfacecolor?n(t,e,{vals:e.surfacecolor,containerStr:\"\",cLetter:\"c\"}):n(t,e,{vals:e.z,containerStr:\"\",cLetter:\"c\"})}},{\"../../components/colorscale/calc\":674}],1344:[function(t,e,r){\"use strict\";var n=t(\"gl-surface3d\"),i=t(\"ndarray\"),a=t(\"ndarray-linear-interpolate\").d2,o=t(\"../heatmap/interp2d\"),s=t(\"../heatmap/find_empties\"),l=t(\"../../lib\").isArrayOrTypedArray,c=t(\"../../lib/gl_format_color\").parseColorScale,u=t(\"../../lib/str2rgbarray\"),f=t(\"../../components/colorscale\").extractOpts;function h(t,e,r){this.scene=t,this.uid=r,this.surface=e,this.data=null,this.showContour=[!1,!1,!1],this.contourStart=[null,null,null],this.contourEnd=[null,null,null],this.contourSize=[0,0,0],this.minValues=[1/0,1/0,1/0],this.maxValues=[-1/0,-1/0,-1/0],this.dataScaleX=1,this.dataScaleY=1,this.refineData=!0,this.objectOffset=[0,0,0]}var p=h.prototype;p.getXat=function(t,e,r,n){var i=l(this.data.x)?l(this.data.x[0])?this.data.x[e][t]:this.data.x[t]:t;return void 0===r?i:n.d2l(i,0,r)},p.getYat=function(t,e,r,n){var i=l(this.data.y)?l(this.data.y[0])?this.data.y[e][t]:this.data.y[e]:e;return void 0===r?i:n.d2l(i,0,r)},p.getZat=function(t,e,r,n){var i=this.data.z[e][t];return null===i&&this.data.connectgaps&&this.data._interpolatedZ&&(i=this.data._interpolatedZ[e][t]),void 0===r?i:n.d2l(i,0,r)},p.handlePick=function(t){if(t.object===this.surface){var e=(t.data.index[0]-1)/this.dataScaleX-1,r=(t.data.index[1]-1)/this.dataScaleY-1,n=Math.max(Math.min(Math.round(e),this.data.z[0].length-1),0),i=Math.max(Math.min(Math.round(r),this.data._ylength-1),0);t.index=[n,i],t.traceCoordinate=[this.getXat(n,i),this.getYat(n,i),this.getZat(n,i)],t.dataCoordinate=[this.getXat(n,i,this.data.xcalendar,this.scene.fullSceneLayout.xaxis),this.getYat(n,i,this.data.ycalendar,this.scene.fullSceneLayout.yaxis),this.getZat(n,i,this.data.zcalendar,this.scene.fullSceneLayout.zaxis)];for(var a=0;a<3;a++){var o=t.dataCoordinate[a];null!=o&&(t.dataCoordinate[a]*=this.scene.dataScale[a])}var s=this.data.hovertext||this.data.text;return Array.isArray(s)&&s[i]&&void 0!==s[i][n]?t.textLabel=s[i][n]:t.textLabel=s||\"\",t.data.dataCoordinate=t.dataCoordinate.slice(),this.surface.highlight(t.data),this.scene.glplot.spikes.position=t.dataCoordinate,!0}};var 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g(t,e){if(t<e)return 0;for(var r=0;0===Math.floor(t%e);)t/=e,r++;return r}function m(t){for(var e=[],r=0;r<d.length;r++){var n=d[r];e.push(g(t,n))}return e}function v(t){for(var e=m(t),r=t,n=0;n<d.length;n++)if(e[n]>0){r=d[n];break}return r}function y(t,e){if(!(t<1||e<1)){for(var r=m(t),n=m(e),i=1,a=0;a<d.length;a++)i*=Math.pow(d[a],Math.max(r[a],n[a]));return i}}p.calcXnums=function(t){var e,r=[];for(e=1;e<t;e++){var n=this.getXat(e-1,0),i=this.getXat(e,0);r[e-1]=i!==n&&null!=n&&null!=i?Math.abs(i-n):0}var a=0;for(e=1;e<t;e++)a+=r[e-1];for(e=1;e<t;e++)0===r[e-1]?r[e-1]=1:r[e-1]=Math.round(a/r[e-1]);return r},p.calcYnums=function(t){var e,r=[];for(e=1;e<t;e++){var n=this.getYat(0,e-1),i=this.getYat(0,e);r[e-1]=i!==n&&null!=n&&null!=i?Math.abs(i-n):0}var a=0;for(e=1;e<t;e++)a+=r[e-1];for(e=1;e<t;e++)0===r[e-1]?r[e-1]=1:r[e-1]=Math.round(a/r[e-1]);return r};var x=[1,2,4,6,12,24,36,48,60,120,180,240,360,720,840,1260],b=x[9],_=x[13];function w(t,e,r){var n=r[8]+r[2]*e[0]+r[5]*e[1];return t[0]=(r[6]+r[0]*e[0]+r[3]*e[1])/n,t[1]=(r[7]+r[1]*e[0]+r[4]*e[1])/n,t}function T(t,e,r){return function(t,e,r,n){for(var i=[0,0],o=t.shape[0],s=t.shape[1],l=0;l<o;l++)for(var c=0;c<s;c++)r(i,[l,c],n),t.set(l,c,a(e,i[0],i[1]))}(t,e,w,r),t}function k(t,e){for(var r=!1,n=0;n<t.length;n++)if(e===t[n]){r=!0;break}!1===r&&t.push(e)}p.estimateScale=function(t,e){for(var r=1+function(t){if(0!==t.length){for(var e=1,r=0;r<t.length;r++)e=y(e,t[r]);return e}}(0===e?this.calcXnums(t):this.calcYnums(t));r<b;)r*=2;for(;r>_;)r--,r/=v(r),++r<b&&(r=_);var n=Math.round(r/t);return n>1?n:1},p.refineCoords=function(t){for(var e=this.dataScaleX,r=this.dataScaleY,n=t[0].shape[0],a=t[0].shape[1],o=0|Math.floor(t[0].shape[0]*e+1),s=0|Math.floor(t[0].shape[1]*r+1),l=1+n+1,c=1+a+1,u=i(new Float32Array(l*c),[l,c]),f=[1/e,0,0,0,1/r,0,0,0,1],h=0;h<t.length;++h){this.surface.padField(u,t[h]);var p=i(new Float32Array(o*s),[o,s]);T(p,u,f),t[h]=p}},p.setContourLevels=function(){var t,e,r,n=[[],[],[]],i=[!1,!1,!1],a=!1;for(t=0;t<3;++t)if(this.showContour[t]&&(a=!0,this.contourSize[t]>0&&null!==this.contourStart[t]&&null!==this.contourEnd[t]&&this.contourEnd[t]>this.contourStart[t]))for(i[t]=!0,e=this.contourStart[t];e<this.contourEnd[t];e+=this.contourSize[t])r=e*this.scene.dataScale[t],k(n[t],r);if(a){var o=[[],[],[]];for(t=0;t<3;++t)this.showContour[t]&&(o[t]=i[t]?n[t]:this.scene.contourLevels[t]);this.surface.update({levels:o})}},p.update=function(t){var e,r,n,a,l=this.scene,h=l.fullSceneLayout,p=this.surface,d=c(t),g=l.dataScale,m=t.z[0].length,v=t._ylength,y=l.contourLevels;this.data=t;var x=[];for(e=0;e<3;e++)for(x[e]=[],r=0;r<m;r++)x[e][r]=[];for(r=0;r<m;r++)for(n=0;n<v;n++)x[0][r][n]=this.getXat(r,n,t.xcalendar,h.xaxis),x[1][r][n]=this.getYat(r,n,t.ycalendar,h.yaxis),x[2][r][n]=this.getZat(r,n,t.zcalendar,h.zaxis);if(t.connectgaps)for(t._emptypoints=s(x[2]),o(x[2],t._emptypoints),t._interpolatedZ=[],r=0;r<m;r++)for(t._interpolatedZ[r]=[],n=0;n<v;n++)t._interpolatedZ[r][n]=x[2][r][n];for(e=0;e<3;e++)for(r=0;r<m;r++)for(n=0;n<v;n++)null==(a=x[e][r][n])?x[e][r][n]=NaN:a=x[e][r][n]*=g[e];for(e=0;e<3;e++)for(r=0;r<m;r++)for(n=0;n<v;n++)null!=(a=x[e][r][n])&&(this.minValues[e]>a&&(this.minValues[e]=a),this.maxValues[e]<a&&(this.maxValues[e]=a));for(e=0;e<3;e++)this.objectOffset[e]=.5*(this.minValues[e]+this.maxValues[e]);for(e=0;e<3;e++)for(r=0;r<m;r++)for(n=0;n<v;n++)null!=(a=x[e][r][n])&&(x[e][r][n]-=this.objectOffset[e]);var b=[i(new Float32Array(m*v),[m,v]),i(new Float32Array(m*v),[m,v]),i(new Float32Array(m*v),[m,v])];for(e=0;e<3;e++)for(r=0;r<m;r++)for(n=0;n<v;n++)b[e].set(r,n,x[e][r][n]);x=[];var w={colormap:d,levels:[[],[],[]],showContour:[!0,!0,!0],showSurface:!t.hidesurface,contourProject:[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],contourWidth:[1,1,1],contourColor:[[1,1,1,1],[1,1,1,1],[1,1,1,1]],contourTint:[1,1,1],dynamicColor:[[1,1,1,1],[1,1,1,1],[1,1,1,1]],dynamicWidth:[1,1,1],dynamicTint:[1,1,1],opacityscale:t.opacityscale,opacity:t.opacity},T=f(t);if(w.intensityBounds=[T.min,T.max],t.surfacecolor){var k=i(new Float32Array(m*v),[m,v]);for(r=0;r<m;r++)for(n=0;n<v;n++)k.set(r,n,t.surfacecolor[n][r]);b.push(k)}else w.intensityBounds[0]*=g[2],w.intensityBounds[1]*=g[2];(_<b[0].shape[0]||_<b[0].shape[1])&&(this.refineData=!1),!0===this.refineData&&(this.dataScaleX=this.estimateScale(b[0].shape[0],0),this.dataScaleY=this.estimateScale(b[0].shape[1],1),1===this.dataScaleX&&1===this.dataScaleY||this.refineCoords(b)),t.surfacecolor&&(w.intensity=b.pop());var A=[!0,!0,!0],M=[\"x\",\"y\",\"z\"];for(e=0;e<3;++e){var S=t.contours[M[e]];A[e]=S.highlight,w.showContour[e]=S.show||S.highlight,w.showContour[e]&&(w.contourProject[e]=[S.project.x,S.project.y,S.project.z],S.show?(this.showContour[e]=!0,w.levels[e]=y[e],p.highlightColor[e]=w.contourColor[e]=u(S.color),S.usecolormap?p.highlightTint[e]=w.contourTint[e]=0:p.highlightTint[e]=w.contourTint[e]=1,w.contourWidth[e]=S.width,this.contourStart[e]=S.start,this.contourEnd[e]=S.end,this.contourSize[e]=S.size):(this.showContour[e]=!1,this.contourStart[e]=null,this.contourEnd[e]=null,this.contourSize[e]=0),S.highlight&&(w.dynamicColor[e]=u(S.highlightcolor),w.dynamicWidth[e]=S.highlightwidth))}(function(t){var e=t[0].rgb,r=t[t.length-1].rgb;return e[0]===r[0]&&e[1]===r[1]&&e[2]===r[2]&&e[3]===r[3]})(d)&&(w.vertexColor=!0),w.objectOffset=this.objectOffset,w.coords=b,p.update(w),p.visible=t.visible,p.enableDynamic=A,p.enableHighlight=A,p.snapToData=!0,\"lighting\"in 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i=n(\"opacityscale\");\"max\"===i?e.opacityscale=[[0,.1],[1,1]]:\"min\"===i?e.opacityscale=[[0,1],[1,.1]]:\"extremes\"===i?e.opacityscale=function(t,e){for(var r=[],n=0;n<32;n++){var i=n/31,a=e+(1-e)*(1-Math.pow(Math.sin(t*i*Math.PI),2));r.push([i,Math.max(0,Math.min(1,a))])}return r}(1,.1):function(t){var e=0;if(!Array.isArray(t)||t.length<2)return!1;if(!t[0]||!t[t.length-1])return!1;if(0!=+t[0][0]||1!=+t[t.length-1][0])return!1;for(var r=0;r<t.length;r++){var n=t[r];if(2!==n.length||+n[0]<e)return!1;e=+n[0]}return!0}(i)||(e.opacityscale=void 0)}function l(t,e,r){e in t&&!(r in t)&&(t[r]=t[e])}e.exports={supplyDefaults:function(t,e,r,c){var u,f;function h(r,n){return i.coerce(t,e,o,r,n)}var 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n=t(\"../../plots/template_attributes\").hovertemplateAttrs,i=t(\"../../plots/template_attributes\").texttemplateAttrs,a=t(\"../../components/colorscale/attributes\"),o=t(\"../../plots/domain\").attributes,s=t(\"../pie/attributes\"),l=t(\"../sunburst/attributes\"),c=t(\"./constants\"),u=t(\"../../lib/extend\").extendFlat;e.exports={labels:l.labels,parents:l.parents,values:l.values,branchvalues:l.branchvalues,count:l.count,level:l.level,maxdepth:l.maxdepth,tiling:{packing:{valType:\"enumerated\",values:[\"squarify\",\"binary\",\"dice\",\"slice\",\"slice-dice\",\"dice-slice\"],dflt:\"squarify\",editType:\"plot\"},squarifyratio:{valType:\"number\",min:1,dflt:1,editType:\"plot\"},flip:{valType:\"flaglist\",flags:[\"x\",\"y\"],dflt:\"\",editType:\"plot\"},pad:{valType:\"number\",min:0,dflt:3,editType:\"plot\"},editType:\"calc\"},marker:u({pad:{t:{valType:\"number\",min:0,editType:\"plot\"},l:{valType:\"number\",min:0,editType:\"plot\"},r:{valType:\"number\",min:0,editType:\"plot\"},b:{valType:\"number\",min:0,editType:\"plot\"},editType:\"calc\"},colors:l.marker.colors,depthfade:{valType:\"enumerated\",values:[!0,!1,\"reversed\"],editType:\"style\"},line:l.marker.line,editType:\"calc\"},a(\"marker\",{colorAttr:\"colors\",anim:!1})),pathbar:{visible:{valType:\"boolean\",dflt:!0,editType:\"plot\"},side:{valType:\"enumerated\",values:[\"top\",\"bottom\"],dflt:\"top\",editType:\"plot\"},edgeshape:{valType:\"enumerated\",values:[\">\",\"<\",\"|\",\"/\",\"\\\\\"],dflt:\">\",editType:\"plot\"},thickness:{valType:\"number\",min:12,editType:\"plot\"},textfont:u({},s.textfont,{}),editType:\"calc\"},text:s.text,textinfo:l.textinfo,texttemplate:i({editType:\"plot\"},{keys:c.eventDataKeys.concat([\"label\",\"value\"])}),hovertext:s.hovertext,hoverinfo:l.hoverinfo,hovertemplate:n({},{keys:c.eventDataKeys}),textfont:s.textfont,insidetextfont:s.insidetextfont,outsidetextfont:u({},s.outsidetextfont,{}),textposition:{valType:\"enumerated\",values:[\"top 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h=n.select(this),p=i.ensureSingle(h,\"path\",\"surface\",(function(t){t.style(\"pointer-events\",\"all\")}));w?p.transition().attrTween(\"d\",(function(t){var e=k(t,!0,M,[g,m]);return function(t){return x(e(t))}})):p.attr(\"d\",x),h.call(f,r,t,e,{styleOne:l,eventDataKeys:c.eventDataKeys,transitionTime:c.CLICK_TRANSITION_TIME,transitionEasing:c.CLICK_TRANSITION_EASING}).call(u.setSliceCursor,t,{hideOnRoot:!1,hideOnLeaves:!1,isTransitioning:t._transitioning}),p.call(l,s,L,{hovered:!1}),s._text=(u.getPtLabel(s)||\"\").split(\"<br>\").join(\" \")||\"\";var d=i.ensureSingle(h,\"g\",\"slicetext\"),T=i.ensureSingle(d,\"text\",\"\",(function(t){t.attr(\"data-notex\",1)})),E=i.ensureUniformFontSize(t,u.determineTextFont(L,s,S.font,{onPathbar:!0}));T.text(s._text||\" 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g=d.width,m=d.height,v=d.viewX,y=d.viewY,x=d.pathSlice,b=d.toMoveInsideSlice,_=d.strTransform,w=d.hasTransition,T=d.handleSlicesExit,k=d.makeUpdateSliceInterpolator,A=d.makeUpdateTextInterpolator,M=d.prevEntry,S=t._fullLayout,E=e[0].trace,L=-1!==E.textposition.indexOf(\"left\"),C=-1!==E.textposition.indexOf(\"right\"),P=-1!==E.textposition.indexOf(\"bottom\"),I=!P&&!E.marker.pad.t||P&&!E.marker.pad.b,O=s(r,[g,m],{packing:E.tiling.packing,squarifyratio:E.tiling.squarifyratio,flipX:E.tiling.flip.indexOf(\"x\")>-1,flipY:E.tiling.flip.indexOf(\"y\")>-1,pad:{inner:E.tiling.pad,top:E.marker.pad.t,left:E.marker.pad.l,right:E.marker.pad.r,bottom:E.marker.pad.b}}).descendants(),z=1/0,D=-1/0;O.forEach((function(t){var e=t.depth;e>=E._maxDepth?(t.x0=t.x1=(t.x0+t.x1)/2,t.y0=t.y1=(t.y0+t.y1)/2):(z=Math.min(z,e),D=Math.max(D,e))})),p=p.data(O,u.getPtId),E._maxVisibleLayers=isFinite(D)?D-z+1:0,p.enter().append(\"g\").classed(\"slice\",!0),T(p,!1,{},[g,m],x),p.order();var R=null;if(w&&M){var 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of individuals by Hours of work in the income category  \"},\"xaxis\":{\"anchor\":\"y\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"age\"}},\"yaxis\":{\"anchor\":\"x\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"Hours\"}}},                        {\"responsive\": true}                    ).then(function(){\n",
+       "                            \n",
+       "var gd = document.getElementById('fb69a68d-eb4d-49cc-8c8f-edce0a0fdbde');\n",
+       "var x = new MutationObserver(function (mutations, observer) {{\n",
+       "        var display = window.getComputedStyle(gd).display;\n",
+       "        if (!display || display === 'none') {{\n",
+       "            console.log([gd, 'removed!']);\n",
+       "            Plotly.purge(gd);\n",
+       "            observer.disconnect();\n",
+       "        }}\n",
+       "}});\n",
+       "\n",
+       "// Listen for the removal of the full notebook cells\n",
+       "var notebookContainer = gd.closest('#notebook-container');\n",
+       "if (notebookContainer) {{\n",
+       "    x.observe(notebookContainer, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "// Listen for the clearing of the current output cell\n",
+       "var outputEl = gd.closest('.output');\n",
+       "if (outputEl) {{\n",
+       "    x.observe(outputEl, {childList: true});\n",
+       "}}\n",
+       "\n",
+       "                        })                };                });            </script>        </div>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "data=df.groupby(['age','income']).apply(lambda x:x['hours.per.week'].count()).reset_index(name='Hours')\n",
+    "px.line(data,x='age',y='Hours',color='income',title='age of individuals by Hours of work in the income category  ')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "People earning <=50k tend to work for high no. of hours at a young age and the no. of hours decreases as the age increases but still they work for more no. of hours even at a later age as compared to people earning >50K"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:55.329131Z",
+     "iopub.status.busy": "2021-07-05T16:35:55.328782Z",
+     "iopub.status.idle": "2021-07-05T16:35:55.863048Z",
+     "shell.execute_reply": "2021-07-05T16:35:55.862084Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:55.329098Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'Average age')"
+      ]
+     },
+     "execution_count": 44,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(6,8))\n",
+    "sns.barplot(x='income',y='age',hue='sex',data=df)\n",
+    "plt.ylabel('Average age')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "As the age increases  people are paid more but males are paid more than females."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:56.69911Z",
+     "iopub.status.busy": "2021-07-05T16:35:56.698698Z",
+     "iopub.status.idle": "2021-07-05T16:35:57.757925Z",
+     "shell.execute_reply": "2021-07-05T16:35:57.757022Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:56.699075Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([0, 1, 2, 3, 4, 5, 6, 7, 8]),\n",
+       " [Text(0, 0, '?'),\n",
+       "  Text(1, 0, 'Private'),\n",
+       "  Text(2, 0, 'State-gov'),\n",
+       "  Text(3, 0, 'Federal-gov'),\n",
+       "  Text(4, 0, 'Self-emp-not-inc'),\n",
+       "  Text(5, 0, 'Self-emp-inc'),\n",
+       "  Text(6, 0, 'Local-gov'),\n",
+       "  Text(7, 0, 'Without-pay'),\n",
+       "  Text(8, 0, 'Never-worked')])"
+      ]
+     },
+     "execution_count": 45,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 431.75x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.factorplot(x='workclass',y='education.num',hue='income',data=df)\n",
+    "plt.xticks(rotation=90)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Some people belonging to a particular workclass might have less education and some workclass might require more education level, but no matter whatever workclass, people in the same workclass, if they have higher education level they earn more. It is also to be noticed that there is no person from without pay and never worked workclass category who earn more than 50k which is logical."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:57.75946Z",
+     "iopub.status.busy": "2021-07-05T16:35:57.759213Z",
+     "iopub.status.idle": "2021-07-05T16:35:58.453812Z",
+     "shell.execute_reply": "2021-07-05T16:35:58.452815Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:57.759436Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([0, 1]), [Text(0, 0, 'Female'), Text(1, 0, 'Male')])"
+      ]
+     },
+     "execution_count": 46,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 431.75x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.factorplot(x='sex',y='education.num',hue='income',data=df)\n",
+    "plt.xticks(rotation=90)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Females with higher education level earn equal to men having less education level than them irrespective of any income category they fall."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:58.456052Z",
+     "iopub.status.busy": "2021-07-05T16:35:58.455657Z",
+     "iopub.status.idle": "2021-07-05T16:35:59.403398Z",
+     "shell.execute_reply": "2021-07-05T16:35:59.402704Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:58.456003Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([0, 1, 2, 3, 4]),\n",
+       " [Text(0, 0, 'White'),\n",
+       "  Text(1, 0, 'Black'),\n",
+       "  Text(2, 0, 'Asian-Pac-Islander'),\n",
+       "  Text(3, 0, 'Other'),\n",
+       "  Text(4, 0, 'Amer-Indian-Eskimo')])"
+      ]
+     },
+     "execution_count": 47,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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CkONgXjVNysn24Z+Lktque8Mxd8Ybj1SNVj1h0G1wwzQ467+ht6Jw/zcvCBvFvjI4dFUOvQbmfKWuSkkoJbaq0qI7nPksXPJx+IZaaPYn8NhAeP5sWPxtbOHF7pvX4KsHwv1aDeH0Ian17V12LLsGdDsazvgP3Pgd/PJOaN276PzG1TDuaXjiKLi3T9gdfeWc+OKVtKXEVtXa7gvnvwHnD4U2+xa1T38bHuwHr/4KVvwQW3ixWPY9vFFsq5QTH4BdOsUXjyRe3aaw36Vw2Qi48mvofx3Ub1l0fvksGH4r/GtveOpYmPCcls5IlVFiS5SOh8AlH4U6fM27R40exuLuzYW3bwwTUNLdprWhuPGm6EOr3zXbn3Un6alFdzjiL3D9N3DOK2FngZxiWxH98Cm8fkXoqnztitDLUVCw/dcT2QEV5EskM9jj2NA9M+lFGPH30PVSsBlGPwoTnoX9L4f+10KdJnFHW/Xc4a3fwNKp4bhdPxj453hjkvhk50CXw8Nt/crQPT3xeZj7dTi/eS1MfC7cGrWDfc4MN13dSwXpii0ZsrLD1Oerx8LR/4B6LUL75nXw2V3w733g07vC1U06GftkUdHcei3C5pbZNeKNSaqHOo0h9yIY/H74uzjoRmjYtuj8qjnwyR1hLO7xo2DsU7BhVVzRSopRYkumnJqw/2Vw3YSwLUutRqF9wyr46P/gnt4w6tEwLT7VLRgP7/4u3LeskNQatoo3JqmemnWGgX+CX08OY9P7nLX1LgNzvwrbGt3ZFV4eDDM+VCEEKZMSWxxq1oODb4RfT4RfXA850ezAnxfDOzfCfbkw8b+p+8e7bnmoRJEfJejD/gQdDoo3Jqn+srLC2PRJD4VZlSc8EPbmK5S3IWxv9J9T4O694IM/h13XRUpQYotTnSZw+C3hCq7vJZAVDXmu/BFe+1UoNDvt7dRa81NQAK9dXjSNu+ugsBu2SEXUagC9z4EL34LrJsGhf4Am7YvOr1kIn/8L7t8PHj0s9HRoxw2JKLFVBw1ahpJFV48JJYgKiw0snQr/PRseOxxmjYw1xHL7/G74/r1wv/Hu4dt3ln7NZCc02R0O/R1cOwEuejcUaq7ZoOj8/LGhp+Of3cIM3OnDIH/zdl9O0p8+caqTph3g5Efgis+h2zFF7fPHwNPHw9MnhD/i6mr2J2HHA4DsWlFx4zSc7SnxMIPd+8EJ94WuypMfg44D2PJFMH8TTB0Kz58Bd+0R6rwuKqWOpaQ9JbbqaNe94KznYPCHW48xzBoRul1eOLf6jS2sXgAvX1xUL/Po/wete8UakqSxmnWh52lw/uthfdzAP0OzrkXn1y6Fr+6Hh34Rbl8+AD8vjS1cSS4ltupst75wwZtw3mtblyaa+iY8cAC8fmUowpxIT58YisE+feL2H5O/OSS1tdEHxz5nwb4XJjYukUKN2sBBv4GrRoWiCLmDoXajovOLJsN7v4e7usPzZ8G3Q9Nj5rFslxZoV3dm0Omw0OUydWjo6lv2XbgymvBsWPide3GYZVm/RdW//8o5ocJ5WT68BeZ8Ge632AuOuUtb9kjymUHb3HA76u/w3bthW50ZH4Z94wryYPo74VanCex9WvgS1rq3fl/TjK7YUoUZ7HlC2EXghAeg0W6hvWAzjHoY/t0LPvprqOiQTN8OhS/vC/drNgjjajXrlv0ckUSrURv2OgnOeRF+MxWOvDV86Sq0fgWMegQeHRB6Pz77F6xeGM7l58G4Z2D1/HC8en44TtXlNxlI+7GlqryNMOZJ+OQfW++BVbtxWBu332VVk2DK2pPqp5nwyKGhajvAaUNgrxN3/j2leqge+5FVHXdYNClcxU1+sWiz20KWFXpG1q8I206VtMdxcOpToTRY8uhSshJ0xZaqcmrBAZfDdRNhwB/DVjAAG1aGfc/u6Q2jH0/ctOdN68Ii7MKkdsBVSmpSvZlBq33g6NvhN9PgzOfCHopb7R33UelJDcLYdmGJOKnWlNhSXa36cMhNIcH1v66oavrPi+Dt38B9fWHSS1VbLd09rBtaPCUc77Y/HPF/Vff6IomWUzPs6H3ms3DDdDj6DmjVa8fPG/dMwkOTnafEli7qNg1bg1w7IUwmKaxismI2vHpJmPI8/d2qqWIy/pkwcQWgbjM47SkVN5bUVW8X2P9X8KuRUG/Xsh+7al5yYpKdosSWbhq2gmPvDlOf9z6NLV30S76B588Muxf/8FnlX3/hxLCXHITXPvVxaNh6Z6MWqR6ati/7fKO2ZZ+XakGJLV3t0glOeQwu/yzUayw092t46hh45mRYMKFir7l+ZVTceGM4HvA/0PHQKgpYpBrofV7Z5/vs4LxUC0ps6a5lDzj7Bbj4Pdi9f1H7zI/gkUNColr6Xfle6/UrYMUP4X6XI+GgG6o8XJFY9Tp7+zu873FcWPcm1Z4SW6ZodwBc+Dac8wq07FnU/u0b8MD+8MZVsHLu9p+/YWVY2Aphd+OTHlZxY0k/WdlhSv8J9xdNxMqpHY5PGxLOS7WnT6ZMYgZdDofLRoYJH7t0Du1eAOP/E3YrHvZ7WLts20WqhWt+smvC6U+FySoi6Sg7B3qfCw3bhOOGbcKxklrKUEmtTJSVFaoydD8OJj4HI24PCSx/E3z1AIwbEv6Yl5XSRdm8G7TcJ/kxi4iUk67YMll2DvQ5H64ZF2rr1d0ltG9aW3pSg1BQVotURaQaU2KTUFfvwKvCIu9D/xBKC5VFi1RFpBpTYpMitRqEnYq1SFVEUpgSm2yrSbuyz2uRqohUYwlLbGb2hJktMbMpxdpOM7NvzKzAzHIT9d6yk7RIVURSWLlmRZpZNnAM0L74c9z9rjKe9hRwH/B0sbYpwMnAwxWMU5Kp19nw/XuhmnlJWqQqItVceaf7vwlsACYD5SoT7+6fmFn7Em1TAUy71VZvhYtUJ/0X3r4B8jaERarH/DMkNa3nEZFqrLyJra2799zxw6qOmV0GXAbQrt0Oxnyk6hUuUv30rrDZZOEiVRGRaq68Y2zvmtmRCY2kBHd/xN1z3T23efPmyXxrERFJYeW9YvsKeM3MsoDNhL1Q3N0bJiwyERGRSihvYrsLOBCY7F4VO1WKiIgkRnm7IucCUyqS1MzseeBLoJuZzTOzwWZ2kpnNIyTJt83svYqHLCIisn3lvWKbBYwws3eBjYWNZU33d/ftzQl/rfzhiYiIVEx5E9vs6FYzuomIiFRL5Ups7v5/iQ5ERESkKpS38shwYJvxNXc/rMojEhER2Qnl7Yq8sdj92sApQF7VhyMiIrJzytsVObZE0+dmNioB8YiIiOyU8nZFNi12mAXsCzRKSERSvTRut/W/IiLVXHm7IscSxtiM0AU5GxicqKCkGjn/9bgjEBGpkPJ2RXZIdCAiIiJVobxXbJhZP7bdj+3p7T5BREQkBuUdY3sG6ARMAPKjZmfrTURFRERiV94rtlxgTxVAFhGR6q68RZCnAC0TGYiIiEhVKO8VWzPg22jtWvEiyMcnJCoREZFKKm9iuyWRQYiIiFSV8k73H5noQERERKpCecfYtmFmj1RlICIiIlWh0okNeLjKohAREaki5V6gXVIphZFF0sp5j3/NvBXradukDs8M3j/ucESknMq7QLsrcBOwO1tXHtF+bJK25q1Yz+xla+MOQ0QqqLxXbC8BDwGPUlR5REREpNopb2LLc/cHExqJiIhIFSjv5JE3zexKM2tlZk0LbwmNTEREpBLKe8V2QfTvTcXaHOhYteGIiIjsHO3HJiIiaaW8syJrAFcAB0dNI4CH3X1zguISERGplPKOsT0I7As8EN32jdpE0k5efgEvjp7LgpXrAViwcj0vjp5LfoF2bRJJBeUdY+vr7vsUO/7YzCYmIiCROOXlF3D1c+MZ9s2iLW0b8wr47SuT+HjaEu47uzc52TtTsEdEEq28f6H5Ztap8MDMOqL1bJKGXh03f6ukVtywbxbx6vj5SY5IRCqqvIntJmC4mY0ws5HAx8ANiQtLJB4vjJlb5vkXR5d9XkTiV95ZkR+ZWRegW9Q03d03lvUckVS0MBpX254FOzgvIvErM7GZ2WHu/rGZnVziVGczw91fTWBsIknXqnEdFqzasN3zrRvXSWI0IlIZO7piO4TQ7XhcKeccUGKTtNKzTSPG/rhiu+dP77tbEqMRkcooM7G5+5+ju39x99nFz5mZFm1LWvl2wWpeLGOMrXGdGpzcu00SI5JYNW639b+SMso73f8VoE+JtpcJ69lEUt6iVRu4+KnRrN0UJvv277wLY35Ywca8AszAHVau38xH05Zw1F4tY442STL9g/381+OOQCppR2Ns3YG9gEYlxtkaArUTGZhIsqzdmMfFT41m0eowtnb4Hi14+LxcDr9rJLOXraVlw9osjMbd7hg2jYHdW2TGWjZ9sEuK2tFfZzfgWKAxYZyt8NYHuDShkYkkQX6Bc83z4/l24WoA9mrdkH+f2ZvsLNvymNo1shkUXaXNXLqWl8bOiyVWESmfHY2xvQG8YWYHuvuXSYpJJCncnb+8+Q0fT1sCQKtGtXniwr7Uq7Xtn8VNg7rxwdTF5Bc4d3/wHSf2akOdmtnJDllEyqG8/SnjzewqM3vAzJ4ovCU0MpEEe/LzHxjy5Y8A1KuZzeMX9GXXhqX3sHdqXp/Tc8OMyCVrNvLE57NLfZyIxK+8ie0ZoCVwFDASaAusSVRQIon2/jeL+Ovb3wKQnWXcf04f9mzdsMznXH94F+rUCFdpD42YyfK1mxIep4hUXHkTW2d3/xOw1t2HAMcA+ycuLJHEmTxvFdf9dwIeFeu/5fi9OLRbix0+r0XD2gz+RVjlsmZjHvcPn5HIMEWkksqb2Ar3XVtpZj2ARsCOPwlEqpn5K9dz8ZDRrN8cpvVfelAHzjtg93I//7JDOtKkbg0AnvnyR+YuX5eQOEWk8sqb2B4xsybAH4GhwLfAHQmLSiQB1mzYzMVPjmbpmlDmdNBeLfn90XtU6DUa1q7B1Yd1AWBTfgF3f/BdlccpIjunXInN3R9z9xXu/om7d3T3Fu7+UKKDE6kqm/MLuPLZcUxfHIaG92nbiLvP6EVWsWn95XXuAe1o2yTUjHxtwny+XbC6SmMVkZ1TrsRmZn83s8bFjpuY2d8SFpVIFXJ3/veNKXz6/TIA2jSuw2MX9N3hdP22TerQoVm9LUmsUK2cbG48slv02vD/hk1LTOAiUinmvuPt7s1svLv3LtE2zt1LltlKiNzcXB8zZkwy3krS0MMjZ3LbuyH5NKidw6tX9KPLrg126jULCpxj7v2MqdHC7ucu2Z9+nZvtdKwiJVS8S0HKPcaWbWa1Cg/MrA5Qq4zHi1QL70xeuCWp5WQZD56z704nNYCsLOPmo7tvOb592DTK8yVRRBKvvIntWeAjMxtsZoOBD4AhiQtLZOeNm7OC61+YsOX47yftzS+6VN1V1cFdmtG/8y4ATJq3ircnL6yy1xaRyivv5JH/B9wK7BHd/urumhUp1dbc5eu4dMgYNuYVAHDVgE5VvpeamfG7QUVXbf94bzqb8wuq9D1EpOLKXaLc3d919xuj23uJDEpkZ6xat5kLnxzFT1FlkGN7tuKGI7ol5L16tm3MsT1bAfDjT+v476g5CXkfESm/8s6KXGNmq6PbBjPLNzPNcZZqZ1NeAZf/Zywzl64FYN/dm3DnaftUalp/ed14ZDdyotf/90ffs3ZjXsLeS0R2rLxdkQ3cvaG7NwTqAKcADyQ0MpEKcnf+8Npkvpz1EwC771KXR87bl9o1EluFv32zepyzf9iMc9nPm3jsUxVIFolThXdL9OB1QkFkkWrjvo9n8HK0V1qjOjV44sK+7FI/OZN3rxnYhXrRurhHPpnJsp83JuV9RWRb5e2KPLnY7VQzux3YkODYRMrtjQnz+WdU3qpGtvHwefvSqXn9pL1/s/q1uPTgjgCs3ZTPvR99n7T3FpGtlfeKrfju2UcRtqw5IVFBiVTE6B+Wc9NLk7Yc33FqTw7ouEvS47jkoI40q18TgGe/nsOPP61NegwiUv4xtouK3S5191vdfUlZz4k2I11iZlOKtTU1sw/M7Pvo3yY7+wNIZpu9bC2XPj2GTdE0+18f3oWTereNJZb6tXK4bmAokJxX4Nz5vgoki8ShzMRmZvea2T3bu+3gtZ8CBpVouxn4yN27AB9FxyKVsmLtJi56chQr14VdlU7u3WZLYonLmfu1o/0udQF4c+ICJs1bGWs8IploR1dsY4CxQG2gD/B9dOsF1Czrie7+CbC8RPMJFFUsGQKcWKFoRSIb8/K57Jkx/PBT2A9t/w5Nue2UvTGLt7RejewsbjyqaM3c7e+q1JZIspWZ2Nx9SLRjdk/gUHe/193vBQYSkltF7eruhXWHFgG7bu+BZnaZmY0xszFLly6txFtJunJ3fvvyJEb/sAKAjs3q8fB5+1IrJ7HT+svrlz1a0bNtIwC+mPnTll0FRCQ5yjt5pAnQsNhx/ait0jx8jd3uV1l3f8Tdc909t3nz5jvzVpJm7v7gO96YsACApvVq8uRFfWlct8wOhKTKyjJuLlZq6/Z3p1FQoKs2kWQpb2K7HRhnZk+Z2RBgHPD3SrzfYjNrBRD9W+YEFJGSXh47j3s+ngFAzZwsHj1/X3bfpV7MUW2rX+dmHNI1fCH7duFqhk5cEHNEIpmjvIntKeB/CV2SrwCHAFMr8X5DgQui+xcAb1TiNSRDfTFzGb9/tWha/z9P24d9d28aY0Rl+92g7hQO+d35/nQ25uXHG5BIhihvYnsA2B+o4+5DCevY7i/rCWb2PPAl0M3M5kXb3dwOHGFm3wOHR8ciOzRjyRouf2Ysm/NDl95NR3XjuH1axxxV2fZs3ZATe7UBYN6K9Tz7lQokiyRDTjkft7+79zGz8QDuvsLMdjQr8qztnBpYkQBFlv28kYueGs3qDaG48Bm5u3HloZ1ijqp8fnNEV96etJBN+QXc+/H3nJrbloa1a8QdlkhaK+8V22Yzyyaa7GFmzQFtPCUJt2FzPpc+PYa5y9cD0L/zLvztpB6xT+svr92a1uW8A3cHYMW6zTwyclbMEYmkv/ImtnuA14AWZnYr8BmVmzwiUm4FBc5vXpzA+DkrAejSoj4PnLMvNbIrXLs7VlcN6EyDWqFz5LHPZrFktcqsiiRSeUtqPQv8FrgNWAic6O4vJTIwkTvem847kxcBocjwExf2pVGd1OvGa1qvJpdHXacbNhfwLxVIFkmoiuygPc3d73f3+9y9MjMiRcrt+VFzeGjkTABq18jisQty2a1p3ZijqryL+renRYOwhc4Lo+cyc+nPMUckmcjMvog7hmRIrT4dyQiffLeUP74eamebwb/O6E2v3RrHG9ROqlszh+uP6ApAfoHzj2HTY45IMpG794s7hmRQYpNqZfqiNVz57Djyo0od//PLPRjUo2XMUVWN0/ZtS8fmYTH5sG8WMW7OipgjkkxjZj9H/x5qZiPM7GUzm2Zmz1o0I8vM+prZF2Y20cxGmVkDM6ttZk+a2WQzG29mA6LHXmhmr0e7tfxgZleb2W+ix3xlZk2jx3Uys2FmNtbMPjWz7tuPcucpsUm1sWT1Bi56chQ/bwzT+s89oB2Df9Eh5qiqTk52Fr89qliprXdUIFli1Rv4NbAn0BHoHy3jegG4zt33Iaw3Xg9cRaiEuDdwFjDEzGpHr9MDOBnoC9wKrHP33oR1zOdHj3kEuMbd9wVuJKyNThglNqkW1m3KY/CQMSxYFWYMHtK1Obcct1fKTOsvr6P22pU+7RoDMOqH5QyfrqpyEptR7j7P3QuACUB7oBuw0N1HA7j7anfPA34B/Cdqmwb8CHSNXme4u69x96XAKuDNqH0y0N7M6gP9gJfMbALwMNAqkT+YEpvELr/Aufb5CUyevwqA7i0bcN/ZvclJsWn95WFm3Hz0HluO/9+707d0u4ok2cZi9/Mpf8GOsl6noNhxQfSaWcBKd+9V7LZHyRepSun3ySEp59a3p/Lh1MUA7NqwFk9e1JcGaVydY78OTTl8jxYATF+8hlfHzYs5IpEtpgOtzKwvQDS+lgN8CpwTtXUF2kWP3SF3Xw3MNrPTouebme2TiOALKbFJrIZ88QNPfD4bgLo1s3n8gr60alQn5qgS76ajupMV9bLe9cF3bNisAskSP3ffBJwB3GtmE4EPCBtNPwBkmdlkwhjche6+cfuvtI1zgMHRa35D2HQ6YSwVBq9zc3N9zJgxcYchVeyjqYu59OkxFDhkGTx6fi4D99ju3rNp56aXJvLS2HC19odfdueyg1Oj/qUkVXoNMieJrtgkFlPmr+Ka58dTOLz05+P2yqikBnD9EV2plRP+BO8fPpNV6zbHHJFIelBi2468/AJeHD2XUx78gn63fcQpD37Bi6PnaqC/CixctZ7BQ0azblPofruof3su6Nc+3qBi0LpxHS7s3x6AVes388DIGfEGJJImlNhKkZdfwNXPjee3r0xi7I8rWLBqA2N/XMFvX5nEVc+OIy9fGxtU1s8b87j4qTEsXh265w/fY1f+eMyeMUcVnysP6UzD2mEy2pOf/8CCletjjkgk9SmxleLVcfMZ9s2iUs8N+2YRr46fn+SI0kP4wjCOqQtXA9CjTUPuOasX2VmZO4zQqG4NrhrQGYBNeQX868PvYo5IJPUpsZXihTFzyzz/4uiyz8u23J1b3vyGEdOXAtC6UW0ev6AvdWtWdulM+rigX3taNwpFHF4eO4/vFq+JOSKR1KbEVoqFO+gO+n7xGn76uSIzXeXxz2bzn6/mAFC/Vg5PXNSXXRvW3sGzMkPtGtlbCiQXONwxbFrMEYmkNiW2UrRqXPY6qlUb8tj/7x8x+KnRvDlxgdYg7cCwKYu49Z2w01F2lnH/OX3o3rJhzFFVLyf3aUvXXesD8OHUJYyavTzmiESqVlR4eZWZTYhu/1vs3CAzm25mM8zs5mLtI8wsN7rfwcy+N7OjdvRe6gcqxRm5uzH2x7Irr+cVOB9NW8JH05ZQv1YOg3q05OTebdi/4y4ZPWZU0sS5K/n1C+MpXC751xN6cEjX5vEGVQ1lZxm/G9SdwUPCes3b353KK1f0S7tamZJ47W9+O4dQfHgwsBswF3gcGPLD7cdU6bfwqGhyDXdfW86nfOrux5Z4jWzgfuAIYB4w2syGuvu3xR7TFhgG3ODu7+3oTXTFVopT9m3LoL1K3yrl0K7N+f3R3dmzVdEVx88b83h57DzOfuxr+t/+Mbe9O5Vpi1YnK9xqa+7ydQweMoYNm8Ms0l8d3JGz928Xc1TV12HdW7Bfh6YAjJuzkve/XRxzRJJqoqT2AiGR9SMktn7R8YvR+Z1mZnuY2T8JZbW67ujxO7AfMMPdZ0WVT/7L1pVJWgHvA//j7kPL84K6YitFdpZx39m9eXX8fF4cPZcFK9fTunEdTu+7G6f0aUt2lvGrQzoxfdEaXhs/nzcmzGdhVJV+0eoNPDxyFg+PnEX3lg04uU8bjt+nDS0bZdZ40qr1m7n4qdEsi8Yij+7Rkt8NSugWTCkvFEjuzskPhE2O7xg2jYHdW6RlMWhJmPMJW8iU5mTgPODJyrywmdUDTidcCRK9zi3uviY6fzcwoJSn/tfdb4/uHxiV1VoA3Oju3wBtCFeVheYB+xc7HgL80d1fLnesKqm18woKnK9m/8Tr4+fz7uRFrIn2EytkBv07NePE3m0Y1KMl9Wul9/eJzfkFXPTkaD6bsQyAXrs15r+XHUDtGtkxR5YaLn9m7JblJredvDdn7aer3AxWob7o9je//TnhCm17Pv/h9mN+UalAzFYDk4BLoq1rKvr8hkCBu/9sZr8E/u3uXczsVGCQu18SPe48YH93v9rMRgBLgLbA4e6+rjzvpa+CVSAry+jXqRl3nLoPo/94OPed3ZvD92hBTjTW5g6fzVjGjS9NJPdvH3Dt8+MZPm0Jm9Nwobe788fXpmxJam2b1OHR83OV1CrgpkHdtozT3v3Bd6zfpMlJUm677eD8znxLOhWYD7xqZv9rZrsXP2lmdxebGFL8djNs2dvt5+j+O0ANM2sWvWbxuNtGbYXuAEYT9nMr11VBel86xKB2jWyO7dmaY3u25qefN/L25IW8Nn4+4+esBGDD5gKGTlzA0IkL2KVeTY7bpzUn9W5Dz7aN0mKiwIMjZ25ZB9igdg5PXdSX5g1qxRxVaunUvD6n5+7G86PmsGTNRp74fPaWRdwiOzCXspPbnMq+sLu/D7xvZrsA5wJvmNkywhXcD+5+fVnPN7OWwGJ3dzPbj3Bh9ROwEuhiZh0ICe1M4OwST/818BzwuJld6DvoatQVWwLtUr8W5x/Ynteu7M/wGw/luoFd2H2XulvO/7R2E0998QMn3P85A+8ayb0ffc/c5eW60q6W3pq0gDuGhS2acrKMh8/dl84tGsQcVWq6/vAu1Imuch8aMZPlazfFHJGkiMd38vwOuftP7v5vd+8F/IGwSWl5nApMicbY7gHO9CAPuBp4D5gKvBiNvRV/TwcuIEwkuWNHb6QxtiRzd8bNWcnr4+fz5qQFrCylonvf9k04sXcbjt27NY3qpsaGm2N/XM5Zj37NprzQvfqPU3tyWu6OekWkLHe+N537hofCyIN/0YE/HZu5NTUzWEXH2LKBFyl9AsmrwOlVPeW/OlJii9GmvAJGfreU18bP48OpS7YkhUI1s7MY0L05J/Vuw4DuLaiVUz3HqX78aS0nPfDFlquKaw7rzA1Hdos5qtS3esNmDrljOCvWbaZmdhYf3XAIuzWtu+MnSjqp8PhENKX/PMLsxXaE7sfHgaczIamBElu1sWr9ZoZNCeNxX83atupEw9o5HNMzjMfl7t6ErGqyCHzluk2c/OAXzFoa1mcev09r/n1mr7QYL6wOHv9sNn99K6xTPbl3G+46o1e8AUmy6Q+pEpTYqqH5K9fzxoT5vDZuPt8v+Xmb822b1OHEXm04sXcbOreoH0OEwca8fM5/fBRfR+Wfcndvwn8u2V8zIKvQxrx8Bv5zJPNWrMcM3r7mIPZsrXJkGUSJrRKU2Koxd+ebBaujReALtix2Lq5n20ac2KsNx+3TOqmzD92dG16cuGULn/a71OXVK/vTtF7NpMWQKV4fP59fvzABgEO6NmfIxfvFG5AkkxJbJSixpYi8/AK+mPkTr42fz7Api1hfovBydpZxUJdmnNS7DUfu2ZI6NRN71fTvD7/n7mjvsMZ1a/Dalf3p0KxeQt8zUxUUOMfc+9mWfeyeu2R/+nVuFnNUkiRKbJWgxJaC1m7M44NvF/Pq+Pl89v1SCkr8L6xXM5ujerTk5N5tObBT1Rdlfm38PK5/YSIQJrj855L9t9Q4lMQY+d1SLnhiFBCu0t+4qr/GMTOD/idXghJbiluyZgNDJyzg9QnzmTJ/28LLLRrU4oRerTmpd1v2aNVgpz8Mv571E+c+/jWb88Pvzb/P7MUJvdrs1GvKjrk75z7+NZ/P+AmA+8/uwzE9W8UclSRByiQ2M3sKOARYFTVd6O4TLHzo/Bv4JbAuah9nZu2Bt9y9R/T8S4HLCaWzyt5eZUexKLGlj+8Xr9kyHje/lM1Su+3agBN7t+HE3q1p1ajsPecKnff418xbsZ62Tepwy/F7cfIDX7BqfVh795sjunLtwC5V+jPI9k2at5Lj7/scCGOaH/zmEGqoQHK6q3hiu6XRdret4ZZVlZ7ub2ZNyko4UWJ7q2Sx4qgu5DWExLY/oUbk/sUTW1Qf8ibgMHdfVtkYt7ynElv6KShwRv+wnNfGz+ftyQtZs2HboswHdNiFk/q04egeLWlQe/uLwAfcOYLZy9bSrmldzODHn0JllFP6tOXO03qqOyzJrn5uHG9NWgjAX0/Yi/MObB9vQJJoFfsDC0ntBba/QPsMblmVV8q5HQdiNhP4ipAkh5csa1VGYnsYGOHuz0fH04FDgVrAW8BfgD8DA919UWVi2yZWJbb0tmFzPsOnLeHV8fMZMX3Jli7EQrVysjh8z105uXcbDu7afMsVQF5+Aa+Om8+f3pjCxrwCzNiyWegBHZvy9MX7UzNHVwvJ9sOytRx+10jyCpxm9Wsy8qYB1Evz3SLiUry34pnB++/4CYlR0cR2MWWXzbqYW1ZVdtuabOBo4GJgD+AZ4Cl3XxCdfwo4ENgIfATc7O4bzewt4HZ3/yx63EfA74BlwGRgPdDb3edTRfQXkeZq18jm6L1bcfTerVixdhNvTV7I6+Pnb9khfGNeAW9PWsjbkxbStF5Nju3ZiuP3ac2jn8zivWIbXRYmtXo1s7n/7D5KajFp36we5+zfjiFf/siynzfx2Kezue5wdQcnwrwV65m9rLwbQ1cbg8txvlKJzd3zCVdYb5lZc+A2YI6Z9XP3UcDvgUVATeARQvL6yw5edimwnLDP292Vias0+nTKIE3q1eS8A3bnlSv6MfKmQ7n+8K5bTdFfvnYTT3/5I6c+9OVWSa24tZvy+WjakmSFLKW4ZmAX6kXLOR75ZGap6xslYyVy2xrMrJGZ/QoYCnQhXL1NAnD3hVFR442E5Fm44LKsbWnWEcbeLjezc3YmtuKU2DLU7rvU47rDu/DxDYfw2pX9uODA3cu9uPrF0XN3/CBJmGb1a3HpwR2B8EXj3o++jzkiqUZ29MdZ6W1rzOw/wDigA3C+ux/i7k+7+4bofKvoXwNOBKZETx0KnG/BAcAqd19Y+LruvgQYBPzdzI6qbHzFKbFlODOjd7sm/N8JPfj6DwN5/IJcatco+9diQSkzLiW5LjmoI83qhy8iz349hx9/SrkuM0mMRG5b8yLQzd1vdvfSvk09a2aTCeNmzYC/Re3vALOAGcCjwJUln+jus4HjgSeivdp2ihKbbFEjO4uBe+zKXq0blfm41o3Lt1RAEqd+rRyui5Za5BU4d77/XcwRSTUxhDD7sTSvAk9X9oXdfWi0d9r2zh/m7nu7ew93P7fYbtnu7le5e6fo/Jio/YfCNWzR8UR3bxON1+0UJTbZxhk72Eft9L7aZ606OHO/drSPNq59c+ICJs1bGW9AEr+wTu0MwtjX54Suyc+j49N3Zh1bKtGsSNnGKfu25eNpSxj2zbZLSgbt1ZJT+rSNISopqUZ2Fjce1Y2rnxsPwO3vTuPZS/bX2sJMF9apPUklZz+mA12xyTays4z7zu7NHaf2pFY0rb9WThZ3nNqT+8/pU+W1J6XyftmjFT3bhq7jL2b+xKff73TRBpGUp8QmpcrJzuL03N22jKe1blyH03N3U1KrZrKyjJuP7r7l+PZ3p1FQsiq2SIZRYpMytW1Shw7N6tG2iSaMVFf9OjXjkK7NAfh24WrenLQg5ohE4qUxNilTjKWEpAJ+N6g7n3y/FHf4x3vTGdSjJbVytJO5ZCZdsYmkgT1bN+TEaPugeSvW8+xXlV6HK5LylNhE0sRvjuhKzaiI9b0ff8/qDZtjjig15eUX8OLouVsKESxYuZ4XR88lX2OXKUOJTSRN7Na0LucduDsAK9Zt5tFPZsUcUerJyy/g6ufG89tXJrExrwAIhcJ/+8okrnp2HHn5BTFHKOWhxCaSRq4a0JkG0TY2j306myWrN8QcUWp5ddz8UtdvAgz7ZhGvjq+ynVUkgZTYRNJI03o1ufzQTgCs35zPv1QguUL+O7rssUkVAE8NSmwiaeai/u1p0aAWAC+MnsvMpT/HHFH1l1/gDJ24gEnzVpX5OBUATw2xJDYzu87MppjZN2b26zhiEElXdWvmcP0RXYHwgX3ne9Njjqj6yssv4LXx8zji7pFc+/x48nYwQUQFwFND0hObmfUALiVsQrcPcKyZdU52HCLp7LR929KxedhE9t0pixg3Z0XMEVUvefkFvDx2Hkfc/QnXvzCRWUvLt+2PCoCnhjiu2PYAvnb3ddEWCCOBk2OIQyRt5WRn8dujipXaemca7pquvjmayn/YP0dy40sTmb2sKKH9cu+WvHXNLxi0V8tSn6sC4KkjjsojU4BbzWwXYD1hW/AxJR9kZpcBlwG0a7dTu5mLZKSj9tqVPu0aM27OSkb9sJzh05dwWPdd4w4rFpvywhXaAyNmMG9F0TiZGRzbszVXD+hMt5YNALjv7N68On4+f3p9ChvzCqiVk8VfT+zBKX3aqlZqirA4vsWZ2WDCLqprgW+Aje7+6+09Pjc318eM2Sb3icgOjJq9nNMf/hKAbrs24J3rDsqoD+eNefm8OGYeDw6fwYJVRUsfsgyO36c1Vx/Wmc4tGpT63AF3jmD2srV0aFaP4TcemqSIt5E5/7OqUCy1It39caItys3s78C8OOIQSXf7dWjK4Xu04MOpS5i+eA2vjpvHaTvYSDYdbNiczwuj5/LgiJksKraWLzvLOKFXa64a0JlOzevHGKEkUiyJzcxauPsSM2tHGF87II44RDLBTUd15+NpSyhwuOuD7zhun9bUrpGeBZLXb8rnuVFzeHjkTJas2bilPTvLOKVPG648tDPtm9WLMUJJhriq+78SjbFtBq5y95UxxSGS9rq1bMApfdry0th5LFy1gae//IHLDu60w+ed9/jXzFuxnrZN6lT7XR7Wbcrj2a/m8PAns1j2c1FCy8kyTstty5WHdma3pnVjjFCSKa6uyIPieF+RTHX9EV0ZOnEBG/MKuH/4TM7IbUejujXKfM68Feu3mjVYHa3dmMczX/3Io5/M4qe1m7a018g2Ts/djSsO7UTbJkpomUb7sYlkgNaN63Bh//Y8PHIWq9Zv5oGRM/j90XvEHValrdmwmae//JHHPp3FinVFuxjUzM7izP124/JDOmkxdQZTYhPJEFce0pnnv57D6g15PPn5D1xwYPuU+/BfvWEzT33+A49/NptV64sSWq2cLM7arx2XH9KJlo1qxxihVAdKbCIZolHdGlw1oDO3vTuNTXkF/OvD77jj1H3iDqtcVq3bzBOfz+aJz2ezZkPelvbaNbI4d//duezgjrRoqIQmgRKbSAa5oF97hnzxAwtWbeDlsfO45KCOdN219HVc1cGKtZt44vPZPPX5D6zZWJTQ6tTI5vwDd+fSgzvSrH6tGCOU6kiJTSSD1K6RzfVHdOWmlydR4HDHsOk8dkFu3GFtY/naTTz66Sye/uIH1m7K39Jer2Y2F/Rrz+BfdGAXJTTZDiU2kQxzcp+2PPrpLL5b/DMfTl3M6B+W07d907jDAmDZzxt59JNZPPPVj6wrltAa1Mrhwv7tubh/B5rUqxljhJIKlNhEMkx2lvG7Qd0ZPCSUqbvtnam8ckU/zOKr3rRkzQYeGTmL/3z9Ixs2F2xpb1A7h4v7d+Di/h12uDxBpJASm0gGOqx7C/br0JRRs5czbs5K3v92MUdtp6p9Ii1evYEHR8zk+VFz2JhXlNAa1anBJb/owAX929OwthKaVIwSm0gGMjNuPro7Jz/wBQB3DJvGwO4tyMlOzk5WC1et58ERM/nv6LlsKpbQmtStwSUHdeT8A3enQcwJrW2TOlv9K6lDiU0kQ/Vp14RBe7Vk2DeLmLl0LS+NncdZ+yV2i6j5K9fzwPAZvDRmHpvyixLaLvVqcunBHTn3gN2pX6t6fCxV9zJisn3V4zdIRGJx06BufDB1MfkFzt0ffMeJvdpQp2bVF0ieu3wdD4yYwctj57E5v2irrGb1a/GrgztyzgHtqFtTH0dSNfSbJJLBOjWvzxl9d+O5r+ewZM1Gnvh8NlcN6Fxlr//jT2u5f/gMXh03n7yCooTWokEtLj+kE2ft1y4hiVQymxKbSIb79cAuvDZuPus35/PQiJmcvV+7nZ5SP2vpz9w3fAZvTFhAfrGE1rJhba44tBNn9N0tbbfOkfgpsYlkuBYNazP4Fx24b/gM1mzM477hM/jTsXtW6rVmLFnDfR/PYOjEBRTLZ7RuVJsrBnTm9Ny21MpRQpPEUmITES47pCPPfv0jK9Zt5pkvf+TCfu0r9PzvFq/h3o9n8NakBXixhNa2SR2uGtCZU/q0pWZOcmZciiixiQgNa9fg6sO68Ne3vmVTfgF3f/BduZ43deFq7v34e96ZvGir9nZN63L1gM6c1KcNNZK0hECkkBKbiABw7gHtePLz2cxbsZ7XJsynVaPtr9/6ZsEq7vnoe977ZvFW7e13qcvVh3XhhF6tldAkNkpsIgJArZxsbjyyG79+YQLusGjVegAWrFzPi6Pncsq+baOENoMPp26d0Do2r8e1h3Xh2J6tkrbIW2R7zIt3iFdTubm5PmbMmLjDEEl7mzbns++tH26151mh5vVrsfTnjVu1dWlRn2sGduGYvVuRnRVfrck0pv+olaArNhHZ4vUJC0pNasBWSa3brg24dmAXju7RkiwlNKlmlNhEZIsXxswt83ydGtncfcY+HLmnEppUX0psIrLFwpXryzzfuE4Og3q0SlI0IpWjUV4R2aJV47Ir2bdpUjdJkYhUnhKbiGxxRu5uZZ4/vW/Z50WqAyU2EdnilH3bMmg7G44O2qslp/Rpm+SIRCpOiU1EtsjOMu47uzd3nNqTWlEJrFo5Wdxxak/uP6ePpvRLSlBiE5Gt5GRncXrubrSOxttaN67D6bm7KalJylBiExGRtKLEJiIiaUWJTURE0ooSm4iIpBUlNhERSStKbCIiklaU2EREJK0osYmISFpRYhMRkbSixCYiImlFiU1ERNKKEpuIiKQVJTYREUkrSmwiIpJWlNhERCStKLGJiEhaUWITEZG0osQmIiJpRYlNRETSSk7cAYhI9dS2SZ2t/hVJFUpsIlKqZwbvH3cIIpWirkgREUkrSmwiIpJWlNhERCStKLGJiEhaUWITEZG0osQmIiJpJZbEZmbXm9k3ZjbFzJ43s9pxxCEiIukn6YnNzNoA1wK57t4DyAbOTHYcIiKSnuLqiswB6phZDlAXWBBTHCIikmaSntjcfT5wJzAHWAiscvf3Sz7OzC4zszFmNmbp0qXJDlNERFJUHF2RTYATgA5Aa6CemZ1b8nHu/oi757p7bvPmzZMdpoiIpKg4uiIPB2a7+1J33wy8CvSLIQ4REUlDcRRBngMcYGZ1gfXAQGBMWU8YO3bsMjP7MRnBbUczYFmM7x+3TP75M/lnB/38cf/8w9x9UIzvn5KSntjc/WszexkYB+QB44FHdvCcWPsizWyMu+fGGUOcMvnnz+SfHfTzZ/rPn6pi2bbG3f8M/DmO9xYRkfSmyiMiIpJWlNjKp8yu0gyQyT9/Jv/soJ8/03/+lGTuHncMIiIiVUZXbCIiklaU2EREJK0osYmISFpRYhORLcwsy8xUCUhSmhJbKSw418z+NzpuZ2b7xR1XMpnZX0ocZ5vZs3HFkyzRzzkt7jji4u4FwP1xxxEnMzvezO6MbsfFHY9UnBJb6R4ADgTOio7XkHl/7LuZ2e8BzKwWoabn9/GGlHjung9MN7N2cccSo4/M7BQzs7gDSTYzuw24Dvg2ul1rZn+PNyqpKE33L4WZjXP3PmY23t17R20T3X2fuGNLluhD7VlgMjAAeMfd/xVrUEliZp8AvYFRwNrCdnc/PragksjM1gD1gHxCPVcD3N0bxhpYEpjZJKBXdOWKmWUD4929Z7yRSUXEUlIrBWyOfqEdwMyaAwXxhpQcZtan2OG/gYeBz4FPzKyPu4+LJ7Kk+lPcAcTJ3RvEHUPMGgPLo/uNYoxDKklXbKUws3OAM4A+wBDgVOBP7v5irIElgZkNL+O0u/thSQsmRma2O9DF3T+MdqLIdvc1cceVDNHV+jlAB3f/q5ntBrRy91Exh5ZwZnYWcDswnHClejBws7u/EGtgUiFKbNthZt0JW+oY8JG7T405JEkSM7sUuAxo6u6dzKwL8JC7D4w5tKQwswcJPRSHufse0ebA77t735hDSwozawUU/qyj3H1RnPFIxWnySCnM7Bl3n+bu97v7fe4+1cyeiTuuZDKzv5tZ42LHTczsbzGGlExXAf2B1QDu/j3QItaIkmt/d78K2ADg7iuAmvGGlFSF22TlAP3M7OQ4g5GK0xhb6fYqfhCNt+0bUyxxOdrd/1B44O4rzOyXwB9jjClZNrr7psJJgWaWQzTemiEyeYz5CaAn8A1FP7MTZgVLilBiKyaa3v4HoI6ZrSZ0QwJsIvOqfGebWS133whgZnWAWjHHlCwjzazw9+AI4ErgzZhjSqZ7gNeAFmZ2K2GMORO+0AAc4O57xh2E7ByNsZXCzG5z99/HHUeczOx3wHHAk1HTRcBQd78jvqiSw8yygMHAkYQvN+8Bj3kG/bFk6hizmT0O/NPdv407Fqk8JbZizKy7u08rMeV9iwyZ6r6FmR1N+HAD+MDd34szHkmeqCtyV4r16rj7nPgiSg4zOwQYCiwCNlK0hk/r2FKIElsxZvaIu1+2nSnvGTPVPVOZ2WTKGEvLlA83M7sG+DOwmLBIO2M+3M1sBvAbQmGCLeOK7v5jbEFJhSmxSanM7ADgXmAPwoy4bGBtOlefiNauQZgVCVA4E/Zcwgf7zcmPKvmiD/f93f2nuGNJNjP70t0PjDsO2TlKbNsRVThvz9ZdMU/HFlCSmdkY4EzgJSAXOB/omgljj8VLqRVrG+fupXZRp5uox+IId8+LO5ZkM7MHCJVH3iR0RQLg7poVmUI0K7IU0Zq1TsAEQlcMhC6qjElsAO4+w8yyo8LAT5rZeCDtExuh+EZ/d/88OuhHBqz5NLPfRHdnASPM7G22/nC/K5bAkqsO4Wc+slibpvunGCW20uUCe2bSLLhSrDOzmsAEM7sDWEgGfLhHBgNPmFkjwvjSCuDieENKisIakXOiW02KFmZnxN+Cu18Udwyy89QVWQozewm41t0Xxh1LXKLxpiVADeB6QjHYB9x9RqyBJVGU2HD3VXHHkkxmdpq7v7SjtnRiZr919zvM7F5KSeLufm0MYUklKbEVY2ZvEn6pGwC9CNuWFO+KyYhtSzJdtP/cKWw7xvqX7T0nnZQ2npjuY4xmdpy7v2lmF5R23t2HJDsmqTx1RW7tY8IVyjhgc8yxxEJT3gF4A1gFjKXYF5t0F61b/CXQxszuKXaqIZDWE0ncvbCyzCfuPrv4OTPLiOLP6USJbWttgH6ECRKTCPuQfQF84e7Ly3piGjk27gCqgbbuPijuIGKwABgDnAZ8F7XlEdazXR9XUEn2spkd7+7zYcuC7fuAveMNSypCXZGliCZN5BKS3IHRbWWm1pAzs2bAT5kymcbMHgHudffJcceSTGZWA7gVuAT4IWpuRyir9gd3T/tejOjq7AFCObk+wG3Ase4+N9bApEIyZZZbRdUhdL80im4LgK9jjShJzOwAMxthZq+aWW8zmwJMARabWaZcxfwCGGtm081skplNNrNJcQeVBHcATYDd3b1PNKbWkfA3cGeskSWJu48GrgXeB24BDldSSz26Yism+qa+F7CGkMi+Ar6K9qPKCNHC7D8QPsweIWxf81VUFPf5kguX01GxCiRbSfeySmb2PWERvpdozwamuXuXeCJLvGITxwrtSVjisgI0cSzVaIxta+0IW7N8D8wH5gEr4wwoBjnu/j6Amf3F3b8CiIpDxxtZkhQmMDNrAdSOOZxk8tK6m90938zS/RtwRlyRZgoltmLcfZCFT++9CONrNwA9zGw58KW7/znWAJOj+IaS60ucS/cPNwDM7Hjgn0Brwlq+3YGplNiANg19a2bnlywdZ2bnAtNiiikp3H0kgJnVA9a7e4GZdQW6A+/GGpxUmLoit8PM2gL9CQnuWGAXd28ca1BJYGb5wFpCxY06wLrCU0Btd68RV2zJYmYTgcOAD929t5kNAM5198Exh5ZQZtaGUDpqPWGpA4RJVHWAkwpnCqYzMxsLHEQYa/wcGA1scvdzYg1MKkSJrRgzu5aQyPoR1rF9Uew22d0Lyni6pAkzG+PuuVGC6x19e5/o7vvEHVsymNlhFF2dfuvuH8UZTzIVLkSPtu6pE1UjyZj/9+lCXZFba0+oZn99JpfTElaaWX3gE+BZM1tCuIrNCO7+MaFYQSYyMzsQOIdQMxQ0ezzl6IpNpIRonGUDofv1HMIM0WczcX+yTGNmBwM3Ap+7+/8zs47Ar1UrMrUosYmIlMHMcjJxb7pUpktskYiZrTGz1cX+XV38OO74JHHM7LNi958pcXpUksORnaQxNpGIuzfY8aMkTdUrdr9HiXOZsYAzjeiKTaQEM+sUbV2DmR1qZteaWeOYw5LE8u3cL+1YqjldsYls6xUg18w6E8qKvQE8R9jSRdJTYzM7ifBlv7GZnRy1G2HykKQQTR4RKaHYWqabgA3ufq+Zjc+EOpmZysyeLOu8u1+UrFhk5+mKTWRbm83sLOACwvYlEDaglTSlxJVeNMYmsq2LCHvw3erus82sA1ByppykOTN7K+4YpHLUFSkiUgp1P6cudUWKRMxsMmXMgHP3nkkMR+I3Pu4ApHJ0xSYS2d4Go4XSfaNRkXShxCZSBjM71t011pIhzKw/cAthD74cwnR/d/eOccYlFaPEJlKGwqn/ccchyWFm04DrCfvR5Re2qwB2atEYm0jZVE4ps6xyd+2YneJ0xSZSBjPbz91VBDdDmNntQDZhJ/GNhe3uPi62oKTClNhESjCzqwj7r62MjpsAZ7n7A7EGJglnZsNLaXZ3PyzpwUilKbGJlGBmE9y9V4k2rWkSSREaYxPZVraZmUff+swsG6gZc0ySJGZ2DLAXULuwzd3/El9EUlFKbCLbGga8YGYPR8e/itokzZnZQ0BdYADwGHAq2mg05agrUqQEM8siJLOBUdMHwGPunr/9Z0k6MLNJ7t6z2L/1gXfd/aC4Y5Py0xWbSAnuXgA8GN0ks6yP/l1nZq2Bn4BWMcYjlaDEJlKCmXUBbgP2ZOtxFlWfSH9vRbul/wMYR6gd+lisEUmFqStSpAQz+wz4M3A3YT+2i4Asd//fWAOTpDKzWkBtd18VdyxSMUpsIiWY2Vh339fMJrv73sXb4o5NEsPMDnP3j83s5NLOu/uryY5JKk9dkSLb2hhNIPnezK4G5gP1Y45JEusQ4GOKdkwvzgmVSCRF6IpNpAQz6wtMBRoDfwUaAv9w96/ijEtEykeJTSRiZi2APwCdgcnAbe6+Ot6oJBnM7DdlnXf3u5IVi+y8rLgDEKlGngbWAvcSuh7viTccSaIG0S0XuAJoE90uB7RtUYrRFZtIxMwmuvs+xY61F1uGMbNPgGPcfU103AB4290PjjcyqQhNHhEpJqrkX7gHW3bxY3dfHltgkiy7ApuKHW+K2iSFKLGJFGlE2Dm5+OaihftwOaAF2unvaWCUmb0WHZ8IDIkvHKkMdUWKiBRjZvsCv4gOP3H38XHGIxWnxCZSBjO7xd1viTsOSZ5om6JdKdaj5e5z4otIKkqJTaQMmkCSWczsGkI5tcVAPqFb2t29Z6yBSYVojE2kbLbjh0gauQ7o5u4/xR2IVJ7WsYmUTfUhM8tcQEWPU5yu2ERKMLPmwKVAeyDHLFy0ufvFMYYlyTELGGFmbwMbCxtVeSS1KLGJbOsN4FPgQ8I4i2SOOdGtZnSTFKTJIyIlmNkEd+8VdxwiUjm6YhPZ1ltm9kt3fyfuQCQ5zOxNwiL8Urn78UkMR3aSrthESjCzNUA9whjLZoqmfDeMNTBJGDM7pKzz7j4yWbHIzlNiExEphZn1cfdxO36kVDdKbCKliIofdwFqF7a5+yfxRSTJpsX5qUtjbCIlmNklhIW6bYEJwAHAl8BhMYYlyafF+SlKC7RFtnUd0Bf40d0HAL2BlbFGJAlnZtlm9myxpv+LLRjZKUpsItva4O4bAMyslrtPA7rFHJMkmLvnA7ubWc3o+PV4I5LKUlekyLbmmVlj4HXgAzNbAfwYa0SSLLOAz81sKLC2sFGVR1KLJo+IlCGaBt4IGObum3b0eEltZvbn0trdXd2SKUSJTSRiZg3dfbWZNS3tvLsvT3ZMEg8zq+vu6+KOQypHY2wiRZ6L/h0LjIn+HVvsWNKcmR1oZt8C06LjfczsgZjDkgrSFZuISMTMvgZOBYa6e++obYq794g3MqkIXbGJlGBm/c2sXnT/XDO7y8zaxR2XJIe7zy3RpB0eUowSm8i2HgTWmdk+wA3ATOCZeEOSJJlrZv0AN7MaZnYjMDXuoKRilNhEtpXnoY/+BOA+d78faBBzTJIclwNXAW2A+UCv6FhSiNaxiWxrjZn9HjgPOMjMstDfSkZw92XAOXHHITtHf6wi2zoDOBu4yN0XmdnBhG1sJM2ZWQfgGqA9xT4ftR9balFiEykhSmbDgbPN7D/AbOBf8UYlSfI68DjwJlAQbyhSWUpsIhEz6wqcFd2WAS8QlsQMiDUwSaYN7n5P3EHIztE6NpGImRUAnwKD3X1G1DbL3TvGG5kki5mdTdiH733CDuoAaMPR1KIrNpEiJwNnAsPNbBjwX7QnV6bZmzBp6DCKuiId7cWXUnTFJlJCtDj7BEKX5GHA08Br7v5+rIFJwpnZDGBPFbxObVrHJlKCu6919+fc/TjCLtrjgd/FHJYkxxSgcdxByM7RFZuISMTMRgA9gdEUjbG5u58QW1BSYUpsIiKRaP+9LYfAQcCZ7r5XTCFJJagrUkQk4u4jgdXAscBThDHWh+KMSSpOsyJFJONpDWN6UVekiGQ8rWFML+qKFBEJaxgXEtYwPmpmA9EaxpSlKzYRkYjWMKYHJTYRkVKYWRPgNOAMdx8YdzxSfkpsIiKSVjTGJiIiaUWJTURE0ooSm4iIpBUlNsl4FuhvQSRN6I9ZMpKZtTez6Wb2NKGi++NmNsbMvjGz/yv2uL5m9oWZTTSzUWbWwMyyzewfZjbazCaZ2a/i+0lEpCSV1JJM1gW4wN2/MrOm7r7czLKBj8ysJzCNUFrpDHcfbWYNgfXAYGCVu/c1s1rA52b2vrvPju0nEZEtlNgkk/3o7l9F9083s8sIfxOtgD0JOycvdPfRAO6+GsDMjgR6mtmp0XMbEZKkEptINaDEJplsLYCZdQBuBPq6+wozewqoXcbzDLjG3d9LfIgiUlEaYxOBhoQkt8rMdgWOjtqnA63MrC9ANL6WA7wHXGFmNaL2rlEpJhGpBnTFJhnP3Sea2XjCmNpc4POofZOZnQHca2Z1CONrhwOPAe2BcWZmwFLgxBhCF5FSqKSWiIikFXVFiohIWlFiExGRtKLEJiIiaUWJTURE0ooSm4iIpBUlNhERSStKbCIiklb+P8mOh6qqD0t2AAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 431.75x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.factorplot(x='race',y='education.num',hue='income',data=df)\n",
+    "plt.xticks(rotation=90)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Asian pacific race have comparatively more education than the fellows who earn same as much as they do, belonging to other races. Indians and some other races earn >50k with lowest education level."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:35:59.405433Z",
+     "iopub.status.busy": "2021-07-05T16:35:59.404914Z",
+     "iopub.status.idle": "2021-07-05T16:36:00.894668Z",
+     "shell.execute_reply": "2021-07-05T16:36:00.893676Z",
+     "shell.execute_reply.started": "2021-07-05T16:35:59.40539Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14]),\n",
+       " [Text(0, 0, '?'),\n",
+       "  Text(1, 0, 'Exec-managerial'),\n",
+       "  Text(2, 0, 'Machine-op-inspct'),\n",
+       "  Text(3, 0, 'Prof-specialty'),\n",
+       "  Text(4, 0, 'Other-service'),\n",
+       "  Text(5, 0, 'Adm-clerical'),\n",
+       "  Text(6, 0, 'Craft-repair'),\n",
+       "  Text(7, 0, 'Transport-moving'),\n",
+       "  Text(8, 0, 'Handlers-cleaners'),\n",
+       "  Text(9, 0, 'Sales'),\n",
+       "  Text(10, 0, 'Farming-fishing'),\n",
+       "  Text(11, 0, 'Tech-support'),\n",
+       "  Text(12, 0, 'Protective-serv'),\n",
+       "  Text(13, 0, 'Armed-Forces'),\n",
+       "  Text(14, 0, 'Priv-house-serv')])"
+      ]
+     },
+     "execution_count": 48,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 431.75x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.factorplot(x='occupation',y='education.num',hue='income',data=df)\n",
+    "plt.xticks(rotation=90)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "People with highest education level belong to armed forces, but people with even education level quite low, who belong to handlers cleaners, transport moving  occupation earn as much as they do. Same is the case with prof speciality. occupation of private house service who earn >50k and <50k have the highest education level difference while prof speciality have the minimum difference."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:00.896444Z",
+     "iopub.status.busy": "2021-07-05T16:36:00.896098Z",
+     "iopub.status.idle": "2021-07-05T16:36:02.554348Z",
+     "shell.execute_reply": "2021-07-05T16:36:02.553448Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:00.896407Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:xlabel='age', ylabel='hours.per.week'>"
+      ]
+     },
+     "execution_count": 49,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 576x576 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(8,8))\n",
+    "sns.scatterplot(x='age',y='hours.per.week',hue='income',data=df)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "From the scatterplot between age, hours.per.week and income, we observe that a person needs to be >30 to be earning more than 50K, else needs to work at least 60 hours.per.week to earn >50K."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:02.556715Z",
+     "iopub.status.busy": "2021-07-05T16:36:02.55637Z",
+     "iopub.status.idle": "2021-07-05T16:36:02.930266Z",
+     "shell.execute_reply": "2021-07-05T16:36:02.929319Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:02.556679Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:>"
+      ]
+     },
+     "execution_count": 50,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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ff4zJ33xJyt4UHrrtMQDqNKjFwIf6cehQKi7dMeyh50jZux/YzzsvfsiH498kNTWVhB2JDL5nWGgrmgvS0tJ4/pGXeG3Ui0RGRjDpi6ls2riF2x68hXVr17MgdjETR01l6GuDGL9kFCl7U3hkwOMA7N93gBHvjObT6e+BcyyevZTFs78B4IH/3ZNxa/z7wz9m2yZlVsLNKXXrcl4WjFuX84tA37qcXwT61uX8ItC3Lucngb51OT8J+q3Ly8cE79bl+j2Cfuuyp8yKmb2azeZ9wErnXPjn/UVERCTP8jpmpTBQC/jZv1wClAduMbOXAxKZiIiICN7HrFwCXOH835RkZm8BC4FGwPcBik1ERES8yI+3Y2fiNbNyJlAs0/rpwFn+xstfuR6ViIiIiJ/XzMpzwBozmwcYvgnhnjKz04FZAYpNREREvAjRZG3B4qmx4pz7wMymA33xza8SC+xwzv0OPJjjwSIiIiL/gte7gfoB9+AbVLsGaAB8A7QIWGQiIiLijcasAL6GSj1gq3OuOVAb2BuooEREREQO8zpm5U/n3J9mhpmd5pxbb2bnBTQyERER8SafZ1a8NlZ2mNkZwARgppn9BoT/F1GIiIhInud1gG03/8PHzWwuUBL4OmBRiYiIiGf+adDyLa+ZlQzOufmBCEREREQkOyfdWBEREZE8Jp+PWfF6N5CIiIhISCizIiIiEu7y+Qy2yqyIiIhInqbMioiISLjTmBURERGR0FFjRURERPI0dQOJiIiEOw2wFREREQkdZVZERETCnQbYioiIiISOMisiIiLhTmNWREREREJHmRUREZFwpzErIiIiIqGjzIqIiEi4U2ZFREREJHSUWREREQl3uhtIREREJHSUWREREQl3GrMiIiIiEjrKrIiIiIQ7jVkRERERCR01VkRERCRPUzeQiIhIuNMAWxEREZHQUWZFREQk3GmArYiIiEjoBDyzUiSmcaCfIl84GL8w1CGEjTMrtgx1CGHhjMKnhzqEsJCanhbqEMJGWj7/6z2sacyKiIiISOhozIqIiEi4U2ZFREREJHSUWREREQl3zoU6goBSZkVERETyNGVWREREwp3GrIiIiIh4Y2btzGyDmf1iZv/JZn9FM5trZqvN7Dsza3+icyqzIiIiEu7ySGbFzCKBN4DWwA5ghZlNcs79lKnYIOBL59xbZnYhMA2olNN5lVkRERGR3FIf+MU5t8k59zfwBdDlqDIOKOF/XBKIP9FJlVkREREJd3lnduFywPZM6zuAy44q8zgQa2Z3AacDrU50UmVWRERExDMz629mKzMt/U/yFNcCHzvnygPtgc/MLMf2iDIrIiIi4plz7l3g3ePsjgMqZFov79+W2S1AO/+5vjGzwsDZwM7jPacyKyIiIuEuPT14S85WANXMrLKZFQKuASYdVWYb0BLAzC4ACgPJOZ1UjRURERHJFc65VOBOYAawDt9dPz+a2VAz6+wvdj9wq5mtBUYBNzqX8xS86gYSEREJd3loun3n3DR8tyNn3vZYpsc/AVeczDmVWREREZE8TZkVERGRcJdHJoULFGVWREREJE9TZkVERCTcKbMiIiIiEjrKrIiIiIS7vDPdfkAosyIiIiJ5mjIrIiIiYc6l5515VgJBmRURERHJ05RZERERCXe6G0hEREQkdJRZERERCXe6G0hEREQkdNRYERERkTxN3UAiIiLhTrcui4iIiISOMisiIiLhTrcui4iIiISOMisiIiLhTpkVERERkdBRZkVERCTcOd0NJCIiIhIyyqyIiIiEO41ZEREREQkdZVZERETCnWawDQ8vDR/K+p8W8e2qmdSudVG2ZerUvpjV385i/U+LeGn40IztI0e8xcoVsaxcEcsvG5eyckUsANde2y1j+8oVsfz953Zq1qwRlPqE2qCnhtOkwzV07TMg1KGEzPMvDGHt93NZumw6NWtl/3OvVfsili2fztrv5/L8C0OO2X/X3f048MdmSpU6E4AOHVuzdNl0liydyoJFE7n88roBrUNuadbyCuYvm8yildMYeM8tx+wvVKggb37wAotWTmPyzJGUrxCTsW/gvf1YtHIa85dNpmmLhp7POfTp/7Jh2/KM9T439mTWonHMmP8V46Z9SrXzquRyLYNr2LOP8M23XzNn8QQurnlhtmUuqXkhcxdP5Jtvv2bYs49kbO/UpS3zv5lM/J4fj/vaDGdPPfsoy1fHMm/xJC453rWpVYP5SyaxfHUsTz37aMb2zl3bsXDpFJJ+W0fN2kd+FxQsWJBX33iK+UsmMXfRRBo2qh/wekjuyReNlSvbtaDauZU5/8JG3H77w7zx+tPZlnvj9acZMOAhzr+wEdXOrUy7ts0BuK737dSt14a69dowfvw0JkyYBsCoUeMztt94091s3ryNtWt/DFq9Qqlr+9a8PXxYqMMImTZtm1H13ErUvLg5d935X15+Jftr8fIrw7hz4H+peXFzqp5bidZtmmbsK1cumpYtG7NtW1zGtnlzF9Pgsitp2KADtw94mDfefCbgdfm3IiIiGPbcIPr2vJ3ml3emy1Xtj2koXNOnO/v2ptCobnvee+szHnn8PgCqnVeFLt2vpEXDLvTpMYAnnx9MRETECc95Sa0alDyjRJbnmDB2Kq0adadt06t569UPGTLsocBXPkBatm5ClSrncHmddjxwzxCeffGxbMs9O3wI99/zGJfXaUeVKufQolVjANav+5mb+97F0iUrgxl2ULRq3YQqVStRv3Yb7r9nMM8Nfzzbcs8Pf5z77h5M/dptqFK1Ei1bNQFg3U8bubHPXXyzeEWW8n1v6AFA04ad6dH1JoY++TBmFtC6BJVLD94SAidsrJjZaV62hVKnTm35bMRXACxb/i0lzyhJVFSZLGWiospQvERxli3/FoDPRnxF587tjjnX1Vd34ovRE4/Zfk2vrnw5ZlIAos+b6ta6mJIlioc6jJDp2LE1o0aMA2DFijWULFmCslGls5QpG1WaEsWLsWLFGgBGjRhHp05tMvY/+9xgBg16BpfplsLff/8j4/HpRYtk2ZdX1br0YrZs3sa2rTs4dCiVieOm0+bKFlnKtGnfgjFf+N43UyfG0qjJZb7tV7Zg4rjp/P33IbZvi2PL5m3UuvTiHM8ZERHBoCfu58nHX8zyHAf2/57xuGiYXLvjadu+BV/6r9e3K9dSomQJypTN+voqU7Y0xYoX49uVawH48ouJtOvQEoCfN27i11+2BDXmYGnXoSWjR00AYNXKtb733lHXpmzZ0hQvXoxV/mszetQEruyY+dpsPua8551/LgsXLANg16497Nu3n1q1s8/CS97jJbPyjcdtIVMuJood2+Mz1uN2JFAuJuqYMnE7EnIs07jRZSTtTOaXbF7oPa7uxBejJ+Ru4JJnRceUZUem10t8XAIxR71eYmKiiIvL9JqKSyQ6pizg6+6Jj0/kh+/XHXPuTp3b8O3qWXw17kNuH5D3swPR0WVIiEvMWE+MTyI6+qg/BjKVSUtLIyXlAGeedcZxj83pnDfdeh2xX89lZ9KuY2K54ZZrWLRqOo8+cT+P/Sf7DGo4iI4uS3ym+ifEJx5zTaOjy5AQn5SpTBLR0WWDFmOoHH1t4uMTiYrJWu+omLLExx99/XK+Nj/8sJ527VsQGRlJxXPKU7NmDcqVj87d4EMp3QVvCYHjDrA1syigHFDEzGoDh/NlJYCiQYgt6Hr16srobLIq9evV5o+DB/nxxw0hiErCTZEihXngwTvo0un6bPdPnhTL5EmxXHFFfQY/dh+dOvYNcoR5V9mo0nTo0oYenW7Kdv8nH3zBJx98Qder2nP3/bfxfwMfzbacyNFGfjaW6tWrMmveWLZvj2fF8tWkpaWFOizxKKe7gdoCNwLlgeGZtu8HHsnugMPMrD/QH8AiSxIRcfq/izIbtw+4gVtu6Q3AypVrsgzoK1c+mrhMrW6AuPjELK3oo8tERkbSreuV1G9w5THP1atnl2wbMZK/9L+tLzfedA0Aq1Z9R/lMr5eYctFZ/pID31985cplek2ViyIhPokqVc6h0jnl+WbZtIzti5ZMpmmTrlmyBYsXL6dS5YqUKnUmu3f/Fsiq/SsJCTuJLnckqxQVU5aEhJ1ZyiT6yyTEJxEZGUmJEsX4bc/eHI/NbnuNiy+gUuWKLFrlu3ZFihZm0cppNKrbPsvzTRw3nadeHAwDc726AXNTv+vofcPVAKz59gdiMtU/OibqmGuakLAzI1PnK1OWhIQk8qOb+11H3xt6ArB69fdZrk1MTBSJ8VnrnRiflCXT6bt+OV+btLQ0Bj9yJBs3NXZUvu1Ky4+O2w3knPvEOdccuNE51zzT0tk5Ny6nkzrn3nXO1XXO1Q1EQwXgrbc/yRj8OmnSDPr29n0IXFa/Din7UkhMPOrDNHEn+1P2c1n9OgD07X01kyfPyNjfqmVjNmz4JUtaH8DMuPrqjoz+Uo2V/O7ddz6jYYMONGzQgSmTY7m2d3cA6tWrRUrKfpISk7OUT0pMJmX/AerVqwXAtb27M2XKTH78cQOVK9WjxgWNqXFBY+LiEmnUsBM7k3ZRpco5GcfXrFWD004rlKcbKgBrv/2BylUqUqFiOQoWLECX7lcy8+u5WcrMnD6XHtd0AaBDlzYsXugbGzDz67l06X4lhQoVpELFclSuUpE1q74/7jnnzFxAnQuacXmttlxeqy0H//gzo6FSuUrFjOdr2aYJm3/dFqQrkDs+en8krRp3p1Xj7nw9dTY9/derTt2a7E/Zz86krK+vnUnJHNh/gDp1awLQ85ouzJg2J+hxB8OH74+keeOuNG/clelTZtHr2q4AXFq3pu+9d9S1SUpKZv/+A1zqvza9ru3K11Nn5/gcRYoUpmjRIgA0bd6QtNQ0Nm74NfcrEyIuPT1oSyh4mWflHDO776ht+4BVzrk1uR/SyZs2fTbt2rVgw7rF/HHwIP36HQl35YpY6tbzDXq8865H+OCDlyhSuDBfz5jL9K+PvPF79uyS7cDaJo0bsGNHAps3h9cH47/14JBnWLH6O/buTaFl1z7ccUtfrurUNtRhBc2Mr+fStm1zvvthHgf/OMiATGNLliydSsMGHQD4v3sH8847z1O4SGFmxs4ndsa8HM/bpWs7rruuO4dSUzl48E9u6HtXIKuRK9LS0hj80FOM+OodIiIjGT1iPBvX/8oD/x3I2tU/MvPreXzx+TheeftpFq2cxt7f9nFHvwcB2Lj+VyZPmMGcbyaRlprKoIeeJN3/YZfdOXNy463X0ahpA1IPpbJvbwr/NzDHBG+eNit2Pi1bN2Hp6hkc/ONP7s1Ul1kLx9Gqsa+h/J/7h/LKm09TuMhpzJm5kNkzFwBwZcdWPPnso5Q6+yw+//Jtfvh+PddedWtI6pLbZsbOp1WbpixfM5ODfxzk7kzXZu7CCTRv3BWAh+5/gtfefJrCRQozZ+YCZvmvTfuOrXj6ucGUOvssRn75Dj9+v46e3ftxdulSfDnuA9LT00lISOKO2/L+eDE5wk40ot7MRgJ1gcn+TR2B74BKwBjn3HM5HV+gULnwHbIfRAfjF4Y6hLBxZsWWoQ4hLJxRODBZzfwmNV3jFrxKC9Ftq+Eoed+GoN4X/fuT1wftd+3pj34a9Hu+vWRWygN1nHMHAMxsCDAVaAKsAnJsrIiIiIj8G14aK2WAvzKtHwLKOucOmtlfxzlGREREgiWfZ728NFZGAMvM7PCAjk7ASDM7HfgpYJGJiIiI4KGx4pz7n5lNB67wbxrgnDs8x3PvgEUmIiIi3uTzLzI8YWPFzP4HLADed879fqLyIiIiIrnJSzfQJuBa4FUz2w8sBBY45zTxiIiISF4QovlPguWE3w3knPvIOXcz0Bz4HOjh/19EREQk4Lx0A70PXAgk4cuqXA18G+C4RERExKt8PmbFy7culwIigb3AHmCXcy41kEGJiIiIHOblbqBuAGZ2Ab4vN5xrZpHOufKBDk5EREQ8ONXnWTGzjkBjfDPWngHMwdcdJCIiIhJwXu4GaoevcfKKcy4+wPGIiIjIycrnY1a8dAPdGYxARERERLJz3MaKf06V7JpqBjjnXImARSUiIiLid9zGinOueDADERERkX/G5fNJ4byMWcHMIoGymcs757YFKigRERGRw7zcDXQXMATfpHCHm24OuCSAcYmIiIhXp/oAW+Ae4Dzn3O5AByMiIiJyNC+Nle3AvkAHIiIiIv+QMitsAuaZ2VTgr8MbnXPDAxaViIiIiN9xvxvIzD7zP7wKmAkUAopnWkRERCQvcOnBW0Igp8zKpWYWA2wDXgtSPCIiIiJZ5NRYeRuYDVQGVmbabvjuBqoSwLhERETEq3w+ZuW43UDOuVedcxcAHznnqmRaKjvn1FARERGRoPDy3UC3ByMQERER+WfcqZpZEREREckLPE23LyIiInmYMisiIiIioaPMioiISLjL59+6rMyKiIiI5GnKrIiIiIQ7jVkRERERCR01VkRERCRPUzeQiIhIuFM3kIiIiEjoKLMiIiIS5pxTZkVEREQkZJRZERERCXcasyIiIiISOsqsiIiIhDtlVkRERERCJ+CZlXPPiAn0U+QLZ1ZsGeoQwsZv22aHOoSw0LH2wFCHEBb2pR0MdQhhI7pA8VCHIMfhlFkRERERCR2NWREREQl3yqyIiIiIhI4yKyIiIuEuPdQBBJYyKyIiIpKnKbMiIiIS5nQ3kIiIiEgIqbEiIiIieZq6gURERMKduoFEREREQkeZFRERkXCnW5dFREREQkeZFRERkTCnW5dFREREQkiZFRERkXCnMSsiIiIioaPGioiISJhz6S5oy4mYWTsz22Bmv5jZf45TpqeZ/WRmP5rZyBOdU91AIiIikivMLBJ4A2gN7ABWmNkk59xPmcpUA/4LXOGc+83MypzovGqsiIiIhLu8M2alPvCLc24TgJl9AXQBfspU5lbgDefcbwDOuZ0nOqm6gURERCS3lAO2Z1rf4d+WWXWgupktNrOlZtbuRCdVZkVERCTMuSBmVsysP9A/06Z3nXPvnsQpCgDVgGZAeWCBmV3snNub0wEiIiIinvgbJsdrnMQBFTKtl/dvy2wHsMw5dwjYbGYb8TVeVhzvOdUNJCIiEu7Sg7jkbAVQzcwqm1kh4Bpg0lFlJuDLqmBmZ+PrFtqU00nVWBEREZFc4ZxLBe4EZgDrgC+dcz+a2VAz6+wvNgPYbWY/AXOBB51zu3M6r7qBREREJNc456YB047a9limxw64z794osaKiIhImAvmANtQUDeQiIiI5GnKrIiIiIQ7ZVZEREREQkeZFRERkTCnMSsiIiIiIaTMioiISJhTZkVEREQkhJRZERERCXPKrIiIiIiEkDIrIiIi4c5ZqCMIKGVWREREJE9TZkVERCTMacyKiIiISAgpsyIiIhLmXLrGrOR5jZpfzvQlXzFj2ThuveuGY/YXLFSQ4e8+xYxl4xg9/SPKVYgG4OLaFzJ+zgjGzxnBhLkjaNW+GQCVq56TsX38nBGs/HUu1/e/NphVCpjnXxjC2u/nsnTZdGrWqpFtmVq1L2LZ8ums/X4uz78w5Jj9d93djwN/bKZUqTMB6NCxNUuXTWfJ0qksWDSRyy+vG9A65CWDnhpOkw7X0LXPgFCHEnJ1m13K+/Pe46OFH9Dzjh7H7L/osot4fdprTNs8hUbtG2Vsr3JhFV6aMJx3Z73NW7Fv0rRTk2CGHRINmtVn9MJPGbN4BH3vvO6Y/QULFWTY248xZvEIPpjyJtHlowCILBDJ4Jf/w+ezP+SL+Z9wfTbH5ie1m9bh9blv8eaCd+h+x9XH7L+wfg1emPoyX22awOXtG2bZ99XmCQyf/grDp7/Cfz8YFKyQJUDCPrMSERHBY88+xM097iQpPokxsZ8wZ8YCft24OaPM1b27kLIvhbaXdad919bcP/gu7uv/CD+v/5WrW19PWloapcuUYsLckcydsZDNv26lW4veGeef/900Zk2bG6oq5po2bZtR9dxK1Ly4OfXq1eLlV4bRvGm3Y8q9/Mow7hz4X1asWMO4CR/Ruk1TZsbOB6BcuWhatmzMtm1xGeXnzV3M1CkzAahx0fl89tnr1KndKjiVCrGu7Vtz3VWdeeR/L4Q6lJCKiIhg4LCB/Pe6R9iVsIvXprzC0pnL2PbztowyyXE7efG+F7n6tquyHPvXwb94/t4XiN8Sz1llz+L1qa+xcv4qfk/5PdjVCIqIiAgeeOoe7r7mAXYmJPPRtLdZOGMxW37emlGm87XtSdl7gB5X9KZVlxYMHNSfQQOG0rJTMwqdVog+LW/mtCKn8cW8T5g5YQ4JOxJDWKPAiIiIoP+wATzeezC7E3bz3OThLJ+5jB0/b88okxyfzGv3v0yX2479HPv7z7+578p7ghmyBFDYZ1YuqVODbZu3s2NrHIcOpTJt/ExatmuapUzLdk2YMHoqADMmz+HyxvUA+PPgX6SlpQFQqPBpONwx57+8ST22b9lBfD74MOjYsTWjRowDYMWKNZQsWYKyUaWzlCkbVZoSxYuxYsUaAEaNGEenTm0y9j/73GAGDXoG545cq99//yPj8elFi2TZl9/VrXUxJUsUD3UYIXdererEb4kncVsiqYdSmTdpPpe3aZClTNKOnWxev4X0o14fcZvjiN8SD8CepD3s272XkmeVDFrswXZh7fPZsSWO+G0JpB5KZebEOTRpe0WWMo3bXsG0MV8DMHfKfOo2uhQA5xxFihYmMjKS0wqfxqG/D/H7gfzZqKtWqxoJWxJI2pZE6qFUFk1eQP02l2Upk7xjJ1vXb8GlnzqfOcfj0oO3hIKnzIqZRQIdgEqZj3HODQ9MWN6VjSpNQlxSxnpiQhI161yUpUyZqDIZZdLS0ti//wBnnFWSvXv2cUmdGjz58mPEVIji4YFDMhovh7Xv2oap42YEviJBEB1Tlh07EjLW4+MSiImJIikxOWNbTEwUcXFHysTFJRIdUxbwdffExyfyw/frjjl3p85teOKJhzi7dCmu7n5zAGsheVGpqLNJjj/yOtqVsIvza5930uc5r1Z1ChQsQMLWhBMXDlOlo0qzM9O12pmQTI06Fx5TJslfJi0tjQMpByh5VknmTJlPk7aNmLJmLIWLnMbLQ94gZe/+oMYfLGdFlWJX/K6M9d0Ju6leq7rn4wudVojnpwwnLTWNcW+OZXns0kCEKUHitRtoMvAn8D2Qr26Q+u7bH+nUpBdVqlXimdceZ8HsJfz9198AFCxYgBZtmzD8yTdCHGXoFSlSmAcevIMuna7Pdv/kSbFMnhTLFVfUZ/Bj99GpY98gRyjh7qwyZ/Lgyw/ywv+9eEpl505GjdoXkJ6WRsfaV1GiZHHenvAqKxauIn5b/m3c/VP9L7+ZPUl7KFuxLENHPcm2DVtI3Br+GfLjcZoUDoDyzrnuzrkhzrknDi/HK2xm/c1spZmt3Hsw+XjFckVSYjLR5cpmrEdFlyUpIetz7kzcmVEmMjKS4sWLsXfPvixlNv28hT9+/4Pq51fN2Na4ZUN++n49u5P3BLAGgdX/tr4sWTqVJUunkpiYTPny0Rn7YspFEx+f9c0bH59IuXJHypQrF0VCfBJVqpxDpXPK882yafy4biHlykWxaMlkypQ9O8vxixcvp1LlihmDb+XUsDtxF6VjjnQpnh19NrsSd3s+vmixogz9eCgfP/cJ61evD0SIeUZyYjJlMl2rMtGlST7qMys5MZmy/jKRkZEUK1GMfXv20aZbS76Zu5y01DR+272X71b8wAU1Tz6DFQ72JO7m7Jgjny+lokuxO8n7a2pPku9zO2lbEj8s/YHKNarkeowSPF4bK9PNrM2Ji/k45951ztV1ztU9o0jpEx/wL3y/+ifOqVKRchVjKFiwAO27tWbOjAVZysyZsZCuvToA0LZTC5YuWgFAuYoxREZGAhBTPooq1SqxY3t8xnEdurVl6rjYgMYfaO++8xkNG3SgYYMOTJkcy7W9uwNQr14tUlL2Z+kCAl/jL2X/AerVqwXAtb27M2XKTH78cQOVK9WjxgWNqXFBY+LiEmnUsBM7k3ZRpco5GcfXrFWD004rxO7dvwWtjhJ6G9ZupFylGMpWKEuBggVo1rkpS2d6S7sXKFiAx94bzOyxs1k0bVGAIw29dWs2UKFyeaIrRFGgYAFad2nBwtglWcosjF1C+x7tAGjesSkrF30LQFLcTuo2qgNA4SKFuajOhWz9ZRv50c9rfya6cgxl/K+pRp2asGLmck/Hnl7ydAoU8nUcFD+zBOfXvYDtmQbm5kcas+KzFBhvZhHAIcAA55wrEbDIPEpLS+N//3mOD0a/SkRkJGNHTuKXDZu46+Hb+GHNOubOWMBXIyby3BtPMGPZOPb9lsJ9tz0KwKWX1eTWu24kNTWV9PR0nnj42YyMS5GihbmiaX2GPPBUKKuXq2Z8PZe2bZvz3Q/zOPjHQQYMeChj35KlU2nYwNeg+797B/POO89TuEhhZsbOJ3bGvBzP26VrO667rjuHUlM5ePBPbuh7VyCrkac8OOQZVqz+jr17U2jZtQ933NKXqzq1DXVYQZeels4bg9/iqc+HEREZSezoWLZu3Mb19/dl43cbWTpzGdVrVuex9wZTvGQxGrS6jOvv60P/VgNo0rExF192ESXOLE7rHr67yF64bzibftoU4loFRlpaGi88+gqvjHyeiMgIpnwxnc0bt3Drgzexfu0GFsYuYfKoaQx59RHGLB5Byt4UBt8+FICvPprAoJceZuTcjzAzpoyezi/r8ud1Sk9L573BbzPksyeIiIxg9uhZbN+4jWvv680v3//MipnLOfeSajz83iMUK1mMeq3qcc19vbmn1UDKn1uB258eSHq6IyLCGPfmV1nuIpLwY176hs1sM9AF+N6dZGfy+WXqqfPZgx0Hdp24kADw27bZoQ4hLHSsPTDUIYSFfWkHQx1C2IguoDvfvBq/bXJQB5Fsr9cyaL9rK6yYHfQBMl67gbYDP5xsQ0VERETk3/LaDbQJmGdm04G/Dm/MC7cui4iInOryeyrBa2Nls38p5F9EREREgsJTYyWn25RFREQktPL7Fxl6ncF2Lhw7F71zrkWuRyQiIiKSidduoAcyPS4MXAWk5n44IiIicrKUWQGcc6uO2rTYzLzNziMiIiLyL3jtBjor02oEcCmQf78WVUREJIzobiCfVfjGrBi+7p/NwC2BCkpERETkMK/dQJUDHYiIiIhIdrxmVjCzhkClzMc45z4NQEwiIiJyEjTAFjCzz4CqwBogzb/ZAWqsiIiISEB5zazUBS7UdwOJiIjkPc7l78yK1y8y/AGICmQgIiIiItnxmlk5G/jJP7dK5i8y7ByQqERERMQzlx7qCALLa2Pl8UAGISIiInI8Xm9dnh/oQEREROSfSdeYleyZ2bu5GYiIiIhIdjzPs5KNd3ItChEREfnHdDfQcWTz5YYiIiIiuc7rpHDVgQeBc8g6g22LAMUlIiIiHmkGW58xwNvAexyZwVZEREQk4Lw2VlKdc28FNBIRERH5R/L7/PJex6xMNrM7zCzazM46vAQ0MhERERG8Z1Zu8P//YKZtDqiSu+GIiIjIydKYFcA5VznQgYiIiIhkx+vdQAWB24Em/k3zgHecc4cCFJeIiIgI4L0b6C2gIPCmf72vf1u/QAQlIiIi3uX36fa9NlbqOedqZlqfY2ZrAxGQiIiISGZeGytpZlbVOfcrgJlVQfOtiIiI5An5fbp9r42VB4G5ZrYJMHwz2d4UsKhERERE/LzeDTTbzKoB5/k3bXDO/RW4sERERMSr/D4pXI6NFTNr4ZybY2bdj9p1rpnhnBsXwNhERERETphZaQrMATpls88BaqyIiIiE2Cl9N5Bzboj/4VDn3ObM+8xME8WJiIhIwHn9bqCx2Wz7KjcDERERkX/GOQvaEgonGrNyPlADKHnUuJUSQOFABiYiIiICJx6zch7QETiDrONW9gO3BigmEREROQmn9N1AzrmJwEQzu9w5902QYhIRERHJ4HVSuNVmNhBfl1BG949z7uaARCUiIiKendJ3A2XyGbAeaAsMBXoD67wcWKJA0X8W2SnmjMKnhzqEsNGx9sBQhxAWpqx+I9QhhIUyldqEOoSwkV6iXKhDkFOU18bKuc65HmbWxTn3iZmNBBYGMjARERHxJr9/N5DXW5cP+f/fa2YXASWBMoEJSUREROQIr5mVd83sTGAQMAkoBjwWsKhERERE/Lx+keH7/ocLgCqBC0dEREROVn4fYOupG8jMnjKzMzKtn2lmwwIWlYiIiIif1zErVzrn9h5ecc79BrQPSEQiIiJyUlwQl1Dw2liJNLPTDq+YWRHgtBzKi4iIiOQKrwNsRwCzzewj//pNwCeBCUlERERORn4fs+J1gO2zZvYd0NK/6X/OuRmBC0tERETEx2tmBefcdGB6AGMRERGRfyC/TwrnqbFiZvs5Mq6mEFAQ+N05VyJQgYmIiIiA926g4ocfm5kBXYAGgQpKREREvEsPdQAB5vVuoAzOZwK+LzUUERERCSiv3UDdM61GAHWBPwMSkYiIiJwUh8asAHTK9DgV2IKvK0hEREQkoLyOWbkp0IGIiIjIP5MeqqllgyTHxoqZvUYOs+s65+7O9YhEREREMjnRANuVwCqgMFAH+Nm/1MJ3C7OIiIiEWDoWtCUUcsysOOc+ATCz24FGzrlU//rbwMLAhyciIiKnOq+3Lp8JZJ4Arph/m4iIiEhAeb0b6BngWzObBxjQBHg8QDGJiIjIScjvty57zax8DDwGXAKMBZoC6wIUk4iIiEgGr5mVN/HN5lvEOTfJzM7E12ipF7DIRERExJP8Pt2+18bKZc65Oma2GsA595uZ6W4gERERCTivjZVDZhaJf84VMytN/m/IiYiIhAWNWfF5FRgPlDGzJ4FFwFMBi0pERETEz+t0+yPMbBXQEt/dQF2dcxpgKyIikgfk964Or5kVnHPrnXNvOOdeV0NFREREsmNm7cxsg5n9Ymb/yaHcVWbmzKzuic7pdcyKiIiI5FF5JbPiH9/6BtAa2AGsMLNJzrmfjipXHLgHWOblvJ4zKyIiIiInUB/4xTm3yTn3N/AF0CWbcv8DngX+9HJSNVZERETCnMOCtpxAOWB7pvUd/m0ZzKwOUME5N9Vr/dRYEREREc/MrL+Zrcy09D+JYyOA4cD9J/OcGrMiIiIS5tKDOM2Kc+5d4N3j7I4DKmRaL+/fdlhx4CJgnpkBRAGTzKyzc27l8Z5TmRURERHJLSuAamZW2T/T/TXApMM7nXP7nHNnO+cqOecqAUuBHBsqoMyKiIhI2EvPIzPYOudSzexOYAYQCXzonPvRzIYCK51zk3I+Q/bUWBEREZFc45ybBkw7attjxynbzMs51Q0kIiIieZoyKyIiImHOhTqAAFNmRURERPI0ZVZERETCXF6Zbj9Q8kVmpUGz+oxZ+BljF4/g+juvO2Z/wUIFefLtIYxdPIIPp7xFdPkoANp2a8XnM9/PWJbumEu1GucC0KZrS0bO/ogRsz7klRHPUfKskkGt07/RrOUVzF82mUUrpzHwnluO2V+oUEHe/OAFFq2cxuSZIylfISZj38B7+7Fo5TTmL5tM0xYNPZ9z6NP/ZcO25RnrfW7syaxF45gx/yvGTfuUaudVyeVaBk/dZpfy/rz3+GjhB/S8o8cx+y+67CJen/Ya0zZPoVH7Rhnbq1xYhZcmDOfdWW/zVuybNO3UJJhh5zmDnhpOkw7X0LXPgFCHEhLPPD+YVWtns2jpFC6pWSPbMjVr1WDxsqmsWjubZ54fnLH9kcH3smjpFBYsmcTYiR8TFVUGgB49O7No6RQWL5vKjFlfctFF5welLoGkz3PJTtg3ViIiInjoqXu5p/dD9Gp2A227tKRytXOylOl8bQf2793PVVf0ZtR7Y7hz0G0AzBg/iz6t+9GndT+G3PUU8dsS+PnHX4iMjOS+oXdxe4976d3qZn5Zt4meN3ULRfVOWkREBMOeG0TfnrfT/PLOdLmq/TENhWv6dGff3hQa1W3Pe299xiOP3wdAtfOq0KX7lbRo2IU+PQbw5PODiYiIOOE5L6lVg5JnlMjyHBPGTqVVo+60bXo1b736IUOGPRT4ygdAREQEA4cNZND1g7m1xW0079KMitUqZimTHLeTF+97kbkT5mbZ/tfBv3j+3hfo32oAj/YdxG1DbuP0EqcHM/w8pWv71rw9fFiowwiJ1m2aUrVqJS6t2ZJ77xrEiy8/kW25F18eyj13PsqlNVtStWolWrX2NXBfe/l9GjXoSJOGnZnx9Rwe+u+dAGzdup0O7a7jiss68Pyzr/PSa+F9ffV5/s+lmwVtCYWwb6zUqH0BO7bEEb8tgdRDqcROnEOTto2ylGna9gqmjpkBwJwp86nXqM4x52nTtSUzJ87xrRiYGUWKFAbg9GJFSU7cHdiK5JJal17Mls3b2LZ1B4cOpTJx3HTaXNkiS5k27Vsw5ouJAEydGEujJpf5tl/ZgonjpvP334fYvi2OLZu3UevSi3M8Z0REBIOeuJ8nH38xy3Mc2P97xuOiRYvgXHgO/zqvVnXit8STuC2R1EOpzJs0n8vbNMhSJmnHTjav30L6UXWM2xxH/JZ4APYk7WHf7r2n9F90dWtdTMkSxUMdRki079iKL0aNB2DlijWULFmCsmVLZylTtmxpipcoxsoVawD4YtR4OnRqDcD+/Qcyyp1etGjG+2n5stXs25sCwIoVa4gpFxXoqgSUPs/leMK+sVI66myS4ndmrO9MSKZ09NnHLZOWlsaBlN+P+aXRunNzZkyY7SuTmsaz/xnOyDkfMW31OCpXr8SkUZ6/bymkoqPLkBCXmLGeGJ9EdHSZLGWiMpVJS0sjJeUAZ551xnGPzemcN916HbFfz2Vn0q5jYrnhlmtYtGo6jz5xP4/95+lcrWewlIo6m+T45Iz1XQm7ODuq1Emf57xa1SlQsAAJWxNyMzwJE9HRZYnbceRnHx+fSHRM2axlYsoSn+l9Fh+XSHT0kTKDhtzHD+sX0qNXZ54a9soxz9H3+h7Mil0QgOiDR5/n/5wL4hIKnhorZlbdzN4zs1gzm3N4CXRwwVKj9gX8efAvNm3YDEBkgUiuur4Lfdv0o33t7vy87lduvKt3iKPMe8pGlaZDlzZ89O7IbPd/8sEXNLr0Sp56fDh3339bkKPLO84qcyYPvvwgL97/UthmmCT0hj0xnIvOb8yY0ZO49ba+WfY1atKAPjf04PHHngtRdHmHPs/zJ6+ZlTHAt8Ag4MFMS7YyfyPjzj8C+5dkcuIuysYcyRyUiS5NcsKu45aJjIykWInT2bdnX8b+Nl1aEOtvhQNUr1ENgLitvhT+7ElzubjuRQGrQ25KSNhJdKZUcFRMWRISdmYpk5ipTGRkJCVKFOO3PXuPe+zxtte4+AIqVa7IolXT+GbNDIoULcyilVkmLQRg4rjptO3Q4pjt4WB34i5KxxxJ158dfTa7TiKFXLRYUYZ+PJSPn/uE9avXByJEyaP69e/DgiWTWLBkEomJyZQrH52xLyYmioT4pCzlE+KTsnTjxJSLIiEhaxmAMaMn0rlL24z1GjXO49XXn6J3rwH8tmdv7lckiPR5/s+lB3EJBa+NlVTn3FvOueXOuVWHl+MVds6965yr65yrW6Zo9PGK5Yqf1qynQuXyxFSIokDBArTp0oKFsYuzlFkQu5gOPXxv7hYdm7Jy0eqMfWZGy07NiZ145MWdnJhM5eqVOMOfWqzfpC5bft4a0HrklrXf/kDlKhWpULEcBQsWoEv3K5n5ddaBnzOnz6XHNV0A6NClDYsXLvNt/3ouXbpfSaFCBalQsRyVq1Rkzarvj3vOOTMXUOeCZlxeqy2X12rLwT/+pFHd9gBUrnJkEGrLNk3Y/Ou2IF2B3LVh7UbKVYqhbIWyFChYgGadm7J05lJPxxYoWIDH3hvM7LGzWTRtUYAjlbzm/Xc/p0nDzjRp2JlpU2ZyzbW+QZ1169UiJWU/SUnJWconJSWzP+UAdevVAuCaa7sxbcosAKpUPTLI9MqOrdi4cRMA5ctH8+nINxlw6/38+suWwFcqwPR5LsfjdZ6VyWZ2BzAe+OvwRufcnoBEdRLS0tJ4/tGXeXXkC0RERjD5i2ls2riF/g/ezLq161kYu4RJo6bxxKuPMnbxCFL27ufR24+MxK/doCZJ8TuJ33YkA7QraTfvD/+Yd8a/RuqhVBLjkhh6b3iMuUhLS2PwQ08x4qt3iIiMZPSI8Wxc/ysP/Hcga1f/yMyv5/HF5+N45e2nWbRyGnt/28cd/XxJso3rf2XyhBnM+WYSaampDHroSdLTfe3o7M6ZkxtvvY5GTRuQeiiVfXtT+L+BjwS87oGQnpbOG4Pf4qnPhxERGUns6Fi2btzG9ff3ZeN3G1k6cxnVa1bnsfcGU7xkMRq0uozr7+tD/1YDaNKxMRdfdhElzixO6x6tAHjhvuFs+mlTiGsVGg8OeYYVq79j794UWnbtwx239OWqTm1PfGA+EDtjHq3bNuPb7+Zw8OBBBg54OGPfgiWTaNKwMwAP/N8Q3nznOQoXLsysmfOZGTsfgCFDH6RatSqkp6ezfVs8993ju635wf/cxVlnncELL/k+01JT02jRJHzvdNHn+T+Xnje+xzBgzEsfupltzmazc86dcPKM+jFN1UnvQfyfGp3uVY3TK4Q6hLAwZfUboQ4hLJSp1CbUIYSNaiXKhTqEsLE8fn5Qmw+jYnoH7XfttfEjgt408pRZcc5VDnQgIiIi8s+kk79TKzk2VsyshXNujpl1z26/c25cYMISERER8TlRZqUpMAfolM0+B6ixIiIiEmL5fbxFjo0V59wQ//83BSccERERkaw8f+uymXUAagCFD29zzg0NRFAiIiIih3lqrJjZ20BRoDnwPnA1sDzHg0RERCQo8vuty14nhWvonLse+M059wRwOVA9cGGJiIiI+HjtBjro//8PM4sBdgOBnZpWREREPAnVNPjB4rWxMsXMzgCex/cdQQ5fd5CIiIhIQHmdFO5//odjzWwKUNg5ty+nY0RERCQ4Tulblw/LblI4M9sHfO+c25nNISIiIiK5wms30C34BtUe/vreZsAqoLKZDXXOfRaA2ERERMSD/H43kNfGSgHgAudcEoCZlQU+BS4DFgBqrIiIiEhAeG2sVDjcUPHb6d+2x8wOBSAuERER8Uh3A/nM8w+sHeNfv8q/7XRgbyACExEREQHvjZWBQHegkX/9U2Csc87hm9VWREREQkSZFcDfKBnrX0RERESCxut0+8cws3dzMxARERH5Z5wFbwmFf9xYAd7JtShEREREjsPrmJVjOOdW5WYgIiIi8s+c0mNWzGwyOczi65zrnOsRiYiIiGRyoszKC0GJQkRERP6xUzqz4pybH6xARERERLLj9YsMqwFPAxcChQ9vd85VCVBcIiIiIoD3u4E+At4CUvFNAvcp8HmgghIRERHvXBCXUPDaWCninJsNmHNuq3PucaBD4MISERER8fF66/JfZhYB/GxmdwJxQLHAhSUiIiJepYdosrZg8ZpZuQcoCtwNXAr0Aa4PVFAiIiIih3nNrFRyzq0ADgA3AZhZD2BZoAITERERb/L7rcteMyv/9bhNREREJFedaAbbK4H2QDkzezXTrhL47gwSERGREMvvmZUTdQPFAyuBzkDm7wLaD/xfoIISEREROexEM9iuBdaa2QjnnDIpIiIieVCo5j8JlhN1A33pnOsJrDazY66Fc+6SgEUmIiIiwom7ge7x/98x0IGIiIjIP3NKz7PinEvw/78V+AuoCVwC/OXfJiIiIhJQnm5dNrN+wHKgO3A1sNTMbg5kYCIiIuJNehCXUPA6KdyDQG3n3G4AMysFLAE+DFRgIiIiIuC9sbIb3+3Kh+33bxMREZEQO6XvBsrkF2CZmU3Ed026AN+Z2X0AzrnhAYpPRERETnFeGyu/+pfDJvr/L5674YiIiIhk5amx4px74p8+wV/ph/7poaeU1PS0UIcQNvalHQx1CGGhTKU2oQ4hLOzcEhvqEMJG3Yv6hDoEOY70fN4R5KmxYmalgYeAGkDhw9udcy0CFJeIiIgI4P1bl0cA64HKwBPAFmBFgGISERGRk5Dfb1322lgp5Zz7ADjknJvvnLsZUFZFREREAs7rANvDA08SzKwDvm9jPiswIYmIiMjJyN8jVrw3VoaZWUngfuA1oARwb6CCEhERETnMazdQD8Cccz8455oDrYFugQtLREREvNKYFZ9LnHN7D6845/YAtQMSkYiIiEgmXruBIszsTOfcbwBmdtZJHCsiIiIBlG6hjiCwvDY4XgS+MbMx/vUewJOBCUlERETkCK8z2H5qZis5crtyd+fcT4ELS0RERLzSDLZ+/saJGigiIiISVBp3IiIiEubyd17F+91AIiIiIiGhzIqIiEiYC9X8J8GizIqIiIjkaWqsiIiISJ6mbiAREZEwl99vXVZmRURERPI0ZVZERETCXP7OqyizIiIiInmcMisiIiJhTrcui4iIiISQMisiIiJhTncDiYiIiISQMisiIiJhLn/nVZRZERERkTxOmRUREZEwp7uBREREREJImRUREZEw5/L5qBVlVkRERCRPU2ZFREQkzGnMioiIiEgIqbEiIiIieZq6gURERMKcptsXERERCSFlVkRERMJc/s6rKLMiIiIieZwaKyIiImEuHRe05UTMrJ2ZbTCzX8zsP9nsv8/MfjKz78xstpmdc6JzqrEiIiIiucLMIoE3gCuBC4FrzezCo4qtBuo65y4BvgKeO9F51VgREREJc+lBXE6gPvCLc26Tc+5v4AugS+YCzrm5zrk//KtLgfInOmm+aKw0bH4ZExeNYvI3X3LznX2P2V+wUEGee2cok7/5ks+nvUdMhSgAYipEsWzzXEbP+pjRsz5m0LMPZhzTrmtrvpr7GWPmfMqbI4dzxlklg1afYBn27CN88+3XzFk8gYtrHt3w9bmk5oXMXTyRb779mmHPPpKxvVOXtsz/ZjLxe36kZq0awQo5JBo0q8/ohZ8yZvEI+t553TH7CxYqyLC3H2PM4hF8MOVNosv7Xl+RBSIZ/PJ/+Hz2h3wx/xOuz+bY/OCZ5wezau1sFi2dwiU1s38t1KxVg8XLprJq7WyeeX5wxvZHBt/LoqVTWLBkEmMnfkxUVBkAevTszKKlU1i8bCozZn3JRRedH5S65AWDnhpOkw7X0LXPgFCHEhKB+Dw/7JVPnmXsvM8DXodTXDlge6b1Hf5tx3MLMP1EJw37xkpERASPPP0Ad1x3P92aXEe7bq2oUr1SljLdrutEyt79dLq8J5+/M5p7B92RsW/H1jh6tbqRXq1uZNjDzwMQGRnJw8Pupd9Vd9KjxfVsXPcL19x8dTCrFXAtWzehSpVzuLxOOx64ZwjPvvhYtuWeHT6E++95jMvrtKNKlXNo0aoxAOvX/czNfe9i6ZKVwQw76CIiInjgqXv4v94Pc22zG2jTpQWVqmXtXu18bXtS9h6gxxW9GfXeVwwc1B+Alp2aUei0QvRpeTM3tOtPt76dMxoy+UXrNk2pWrUSl9Zsyb13DeLFl5/IttyLLw/lnjsf5dKaLalatRKtWjcB4LWX36dRg440adiZGV/P4aH/3gnA1q3b6dDuOq64rAPPP/s6L702LGh1CrWu7Vvz9vBTp76ZBeLz/LCW7Zvyx+8Hg1GNkHBB/Gdm/c1sZaal/z+J2cz6AHWB509UNuwbKxfVvpDtm3cQty2e1EOpfD1hFs3aNs5Spnnbxkz60tdwmzllLvUb1c3xnGaAQZGiRQAoVux0khN3BST+UGnbvgVffjERgG9XrqVEyRKUKVs6S5kyZUtTrHgxvl25FoAvv5hIuw4tAfh54yZ+/WVLUGMOhQtrn8+OLXHEb0sg9VAqMyfOoUnbK7KUadz2CqaN+RqAuVPmU7fRpQA45yhStDCRkZGcVvg0Dv19iN8P/B70OgRS+46t+GLUeABWrlhDyZIlKHvU66hs2dIUL1GMlSvWAPDFqPF06NQagP37D2SUO71oUZzzDd5bvmw1+/amALBixRpiyuWvRl5O6ta6mJIlioc6jJAIxOc5+D7L+952De+9/HEgwj7lOOfedc7VzbS8m2l3HFAh03p5/7YszKwV8CjQ2Tn314me01Njxcx6mFlx/+NBZjbOzOp4OTbQykSXJjE+KWN9Z0IyZaNLH7dMWloaB/b/ntGtU65iNKNnfswH49+g9mU1AUhNTePJh1/gq7mfMWvtJKpUr8z4kZODVKPgiI4uS3xcYsZ6Qnwi0dFljipThoRM1zYhPono6LJBizEvKB1Vmp3xyRnrOxOSKX3U66t0VGmS/GXS0tI4kHKAkmeVZM6U+Rz840+mrBnLxBWjGfH2aFL27g9q/IEWHV2WuB0JGevx8YlEx2R9jUTHZH2txcclZnkdDRpyHz+sX0iPXp15atgrxzxH3+t7MCt2QQCil7wmEJ/nAAMfvpVP3x7Fnwf/DEItQiMPjVlZAVQzs8pmVgi4BpiUuYCZ1QbewddQ2emlfl4zK4Odc/vNrBHQCvgAeMvjsXlWctJu2l7ajV6tb+SFIa/yzJuPc3qxohQoEEnPG7rRq9WNtKrZmZ/X/cItd18f6nAlzNSofQHpaWl0rH0V3S+7lusG9CSmYnSow8pzhj0xnIvOb8yY0ZO49basYxQaNWlAnxt68PhjJ7xZQE5xx/s8P69GNSpUKsec6WrwBoNzLhW4E5gBrAO+dM79aGZDzayzv9jzQDFgjJmtMbNJxzldBq+NlTT//x2Ad51zU4FCxyucuT9r9x9JxyuWK3YmJBOV6S+5MtGlSUpIPm6ZyMhIihU/nb179nHo70Ps+82Xal733Qa2b43jnKoVOe+i6oCv/xNgxqQ51Kx3UUDrEQw39buOWQvHMWvhOJKSkrOk1qNjokhIyNrATUjYmeWv5OiYsiQkBPbnmdckJyZTJubIX3ZlokuTfNTrKzkxmbL+MpGRkRQrUYx9e/bRpltLvpm7nLTUNH7bvZfvVvzABTXPC2r8gdCvfx8WLJnEgiWTSExMplz5Iw2wmJioLNk48GXkMr/WYspFZfs6GjN6Ip27tM1Yr1HjPF59/Sl69xrAb3v25n5FJM8JxOf5JXUv4sKa5zNtxVg+nvg251SpwPvjXg9epYIkmGNWThiLc9Occ9Wdc1Wdc0/6tz3mnJvkf9zKOVfWOVfLv3TO+YzeGytxZvYO0AuYZman5XRs5v6sUkUD223w45p1VKxSnnIVoylQsADturZifuyiLGXmxS6kc88rAWjdsTnLF68C4MxSZxAR4atGuYoxnFO5Aju2xrEzIZkq1StxZqkzALi8ST02/7w1oPUIho/eH0mrxt1p1bg7X0+dTc9rfHeT1albk/0p+9mZdNSHQlIyB/YfoE5dXzq15zVdmDFtTtDjDqV1azZQoXJ5oitEUaBgAVp3acHC2CVZyiyMXUL7Hu0AaN6xKSsXfQtAUtxO6jby9ZYWLlKYi+pcyNZftgW3AgHw/ruf06RhZ5o07My0KTO55tpuANStV4uUlP0kHfU6SkpKZn/KAerWqwXANdd2Y9qUWQBUqXpksPKVHVuxceMmAMqXj+bTkW8y4Nb7T4mxUeITiM/zMZ+Mp3WtLrSvdxU3dhnA1k3b6df9zuBWTP41r98N1BNoB7zgnNtrZtHAsfeFhUBaWhpPPzKct0a9RERkJBNGTeHXDZu546F+/LhmPfNjFzF+5BSefP0xJn/zJSl7U3joNt+dL3Ua1GLgQ/04dCgVl+4Y9tBz/jEF+3nnxQ/5cPybpKamkrAjkcH35K/R+bNi59OydROWrp7BwT/+5N6BR25LnrVwHK0adwfgP/cP5ZU3n6ZwkdOYM3Mhs2f6UqlXdmzFk88+Sqmzz+LzL9/mh+/Xc+1Vt4akLoGUlpbGC4++wisjnyciMoIpX0xn88Yt3PrgTaxfu4GFsUuYPGoaQ159hDGLR5CyN4XBtw8F4KuPJjDopYcZOfcjzIwpo6fzy7pNIa5R7oqdMY/WbZvx7XdzOHjwIAMHPJyxb8GSSTRp6PuD6YH/G8Kb7zxH4cKFmTVzPjNj5wMwZOiDVKtWhfT0dLZvi+e+e3y3NT/4n7s466wzeOEl391FqalptGjSLci1C40HhzzDitXfsXdvCi279uGOW/pyVae2Jz4wHwjM5/mpwcNYkrBmh0ff51jIrCqwwzn3l5k1Ay4BPnXO7T3RsTWjGub371fKFUl//hbqEMJGpQBn6/KLDSk7Qh1CWNi5JTbUIYSNuhf1CXUIYWNt4hIL5vPdUOmqoP2u/WTL2KDWDbx3A40F0szsXOBdfLcljQxYVCIiIiJ+XruB0p1zqWbWHXjNOfeama0OZGAiIiLiTbqHXpJw5jWzcsjMrgWuB6b4txUMTEgiIiIiR3htrNwEXA486ZzbbGaVgc8CF5aIiIh45YK4hIKnxopz7ifgAeB7M7sI32DbZwMamYiIiAgex6z47wD6BNgCGFDBzG5wzmlKQBERkRBLD1nOIzi8DrB9EWjjnNsAYGbVgVHApYEKTERERAS8N1YKHm6oADjnNpqZBtiKiIjkAV6mwQ9nXhsrK83sfeBz/3pvYGVgQhIRERE5wmtj5XZgIHC3f30h8GZAIhIREZGTkt+n2/fUWHHO/QUM9y8iIiIiQZNjY8XMvieH26qdc5fkekQiIiJyUk71u4E6BiUKERERkePIsbHinNsarEBERETkn8nvdwN5nW7/GGb2bm4GIiIiIpIdr3cDZeedXItCRERE/rH8fjfQP86sOOdW5WYgIiIiItk50d1Ak8n5bqDOuR6RiIiISCYn6gZ6IShRiIiIyD/mXP4eYHuiu4HmBysQERERkex4GmBrZtWAp4ELgcKHtzvnqgQoLhEREfEov08K53WA7UfAW0Aq0Bz4lCNfaigiIiISMF4bK0Wcc7MBc85tdc49DnQIXFgiIiLiVXoQl1DwOs/KX2YWAfxsZncCcUCxwIUlIiIi4uO1sXIPUBS4G/gfvq6g6wMVlIiIiHin6fZ9KjnnDjjndjjnbnLOXQVUDGRgIiIiIuC9sfJfj9tEREQkyNJxQVtC4UQz2F4JtAfKmdmrmXaVwHdnkIiIiEhAnWjMSjywEugMZP4uoP3A/wUqKBEREfHuVJ/Bdi2w1sxGOOeUSREREZGgO1E30JfOuZ7AajM7ptnmnLskYJGJiIiIJ6Ga/yRYTtQNdI///46BDkREREQkOyfqBkrw/7/VzKKA+oADVjjnEoMQn4iIiJyA5lkBzKwfsBzoDlwNLDWzmwMZmIiIiAh4n8H2QaC2c243gJmVApYAHwYqMBERERHw3ljZje925cP2+7eJiIhIiIVqsrZg8dpY+QVYZmYT8Y1Z6QJ8Z2b3ATjnhgcoPhERETnFeW2s/OpfDpvo/7947oYjIiIiJ+uUnhTuMOfcE4EORERERCQ7nhorZlYaeAioARQ+vN051yJAcYmIiIhH+X3MitdvXR4BrAcqA08AW4AVAYpJREREJIPXMSulnHMfmNk9zrn5wHwz89RYKWiR/zy6U0iay++TJeee6AIaKuVFeolyoQ4hLNS9qE+oQwgbK3/4PNQhyHHk90nhvDZWDvn/TzCzDvi+jfmswIQkIiIicoTXxsowMysJ3A+8BpQA7g1UUCIiIuJdej6/G8jrmJUegDnnfnDONQdaA90CF5aIiIiIj9fMyiXOub2HV5xze8ysdmBCEhERkZORv/Mq3jMrEWZ25uEVMzsL7w0dERERkX/Ma4PjReAbMxvjX+8BPBmYkERERORk5Pd5VrzOYPupma0EDk8C190591PgwhIRERHx8dyV42+cqIEiIiKSx+T3zIrXMSsiIiIiIaHGioiIiORpuqNHREQkzDlNCiciIiISOsqsiIiIhDkNsBUREREJIWVWREREwpxTZkVEREQkdJRZERERCXO6G0hEREQkhJRZERERCXO6G0hEREQkhJRZERERCXMasyIiIiISQsqsiIiIhDmNWREREREJIWVWREREwpxmsBUREREJITVWREREJE9TN5CIiEiYS9etyyIiIiKho8yKiIhImNMAWxEREZEQUmZFREQkzGnMioiIiEgIKbMiIiIS5jRmRURERCSElFkREREJcxqzIiIiIhJCyqyIiIiEOY1ZEREREQmhfNFYubx5fcYuHMH4JaO44c7ex+wvWKggT739OOOXjOLjqe8QXT4qY9+5F1Tlw8lvMXrep3wx52MKnVYIgNadWzBq9seMnvcpdz06IGh1CbSnnn2U5atjmbd4EpfUvDDbMpfUqsH8JZNYvjqWp559NGN7567tWLh0Ckm/raNm7YsythcsWJBX33iK+UsmMXfRRBo2qh/wegRT7aZ1eH3uW7y54B2633H1MfsvrF+DF6a+zFebJnB5+4ZZ9n21eQLDp7/C8Omv8N8PBgUr5KBp0Kw+YxZ+xtjFI7j+zuuO2V+wUEGefHsIYxeP4MMpb2W899p2a8XnM9/PWJbumEu1GucC0KZrS0bO/ogRsz7klRHPUfKskkGtUyA0bH4ZExeNYvI3X3LznX2P2V+wUEGee2cok7/5ks+nvUdMBd91iqkQxbLNcxk962NGz/qYQc8+eMyxr3zyLGPnfR7wOuQ1g54aTpMO19C1T/75fP430p0L2hIKYd9YiYiI4OGn7uPu3g/Qo2lf2nZtReXqlbKU6XJtB/bv20+3htcy8t0vuWuQ78UdGRnJ/14fzNMPv0CvZtdz21V3k3oolZJnluCex+7g9p730qvZ9ZQqcxb1Gl0agtrlrlatm1ClaiXq127D/fcM5rnhj2db7vnhj3Pf3YOpX7sNVapWomWrJgCs+2kjN/a5i28Wr8hSvu8NPQBo2rAzPbrexNAnH8bMAlqXYImIiKD/sAH874bHubvlQBp1bkL5ahWylEmOT+a1+19mwcT5xxz/959/c9+V93Dflffw9C3DghV2UERERPDQU/dyT++H6NXsBtp2aUnlaudkKdP52g7s37ufq67ozaj3xnDnoNsAmDF+Fn1a96NP634Muesp4rcl8POPvxAZGcl9Q+/i9h730rvVzfyybhM9b+oWiurlmoiICB55+gHuuO5+ujW5jnbdWlHlqM+obtd1ImXvfjpd3pPP3xnNvYPuyNi3Y2scvVrdSK9WNzLs4eezHNeyfVP++P1gMKqR53Rt35q3h+ev95QcX9g3VmrUvoDtW+KI25ZA6qFUYifOpmnbRlnKNG3XmClffg3A7CnzqN/Y1/Bo0LQeP6/7lZ9/+hWAfb+lkJ6eTrmKMWzbtIO9u/cCsHzhKlp0aBq8SgVIuw4tGT1qAgCrVq6lZMkSlC1bOkuZsmVLU7x4MVatXAvA6FETuLJjSwB+3riJX3/ZfMx5zzv/XBYuWAbArl172LdvP7UyZV7CWbVa1UjYkkDStiRSD6WyaPIC6re5LEuZ5B072bp+Cy49f/cZH61G7QvYsSWO+Iz33hyaHP3ea3sFU8fMAGDOlPnUa1TnmPO06dqSmRPn+FYMzIwiRQoDcHqxoiQn7g5sRQLsotoXsn3zDuK2xZN6KJWvJ8yiWdvGWco0b9uYSV9OB2DmlLnUb1T3hOctUrQIfW+7hvde/jgQYed5dWtdTMkSxUMdRp7hgvgvFDw1VszstGy2nZX74Zy8MlGlSYrbmbG+MyGZMlFnH1XmbJLifWXS0tI4kPI7Jc8qScWqFcA5Xhv1Ip/HfsD1d/jS2Nu37OCcqhWILh9FZGQkzdo1omxMmeBVKkCio8sSH5eYsR4fn0hUTNksZaJiyhIff6RMQnwi0dFZyxzthx/W0659CyIjI6l4Tnlq1qxBufLRuRt8iJwVVYpd8bsy1ncn7KZU2VKejy90WiGenzKcZyY8T/02DQIRYsiUzvS+At97r3T02cctk/m9l1nrzs2ZMWG2r0xqGs/+Zzgj53zEtNXjqFy9EpNGTQ1wTQKrTHRpEuOTMtZ3JiRTNrr0ccukpaVxYP/vnOG/TuUqRjN65sd8MP4Nal9WM+OYgQ/fyqdvj+LPg38GoRYioeX1bqBxZtbVOXcIwMyigSlAWPeNREZGUrP+xVx/ZX/+PPgnb335Muu+28CKRat45j8v8vQ7T5Cens53K3+gfKVyoQ43zxr52ViqV6/KrHlj2b49nhXLV5OWlhbqsPKE/pffzJ6kPZStWJaho55k24YtJG5NPPGBp4gatS/gz4N/sWmDL2MXWSCSq67vQt82/YjbGs8DT97DjXf15sNXPgtxpKGRnLSbtpd2Y99vKVxwyXm8/NEzdG/am/LnlKNCpXK8MOTVjPEtIvmZ18bKBOBLM7saqABMAh44XmEz6w/0B6hY4lxKFw3cm2lnYjJlyx3JepSJLs3OxF1HldlF2Zgy7ExIJjIykmIlTmffnn3sTEhm9dK17NuzD4DFc5Zy/sXVWbFoFQtnLmHhzCUAdOvTifS09IDVIZBu7ncdfW/oCcDq1d8TU+7IzyImJirLX3wAifFJxMQcKRMdE0VCQtYyR0tLS2PwI09nrE+NHcWvv2zJhehDb0/ibs6OOZItKBVdit1J3rsl9iTtASBpWxI/LP2ByjWq5JvGSrL/fXVYmejSJCfsyrbM0e+9w9p0aUGsP6sCUL1GNQDitsYDMHvSXK7PZtB8ONmZkJwlg1kmujRJCcnZlsm4TsVPZ6//Ou37+xAA677bwPatcZxTtSI1al3AhTXPZ9qKsRSIjOSss8/k/XGv06/7ncGrmOQpzoXn7yivPHUDOefeA2bha7RMBgY452JzKP+uc66uc65uIBsqAD+tWU+FyuWJqRBNgYIFaNOlJQtmLMpSZsGMRXTs2Q6Alh2bsWLRtwB8M28Z515QldOKnEZkZCR1GtRi08YtAJxZ6gwAipcsxtU3dGPCyCkBrUegfPj+SJo37krzxl2ZPmUWva7tCsCldWuSkrKfpKSsH5pJScns33+AS+v60s29ru3K11NnH33aLIoUKUzRokUAaNq8IWmpaWzc8GvuVyYEfl77M9GVYyhToSwFChagUacmrJi53NOxp5c8nQKFfH8PFD+zBOfXvYDtP28PZLhBdeS9F+V/77VgYeziLGUWxC6mQ4+2ALTo2JSVi1Zn7DMzWnZqTuzEI6+v5MRkKlevlNEFUr9JXbb8vDUItQmcH9eso2KV8pSr6PuMate1FfNjs35GzYtdSOeeVwLQumNzli9eBfg+hyIifB/T5SrGcE7lCuzYGseYT8bTulYX2te7ihu7DGDrpu1qqEi+lmNmxczuy7wKVATWAA3MrIFzbngAY/MkLS2N5x95iddGvUhkZASTvpjKpo1buO3BW1i3dj0LYhczcdRUhr42iPFLRpGyN4VHBjwOwP59Bxjxzmg+nf4eOMfi2UtZPPsbAB743z0Zt1K+P/xjtm0K/18yM2Pn06pNU5avmcnBPw5y98BHMvbNXTiB5o27AvDQ/U/w2ptPU7hIYebMXMCsmQsAaN+xFU8/N5hSZ5/FyC/f4cfv19Gzez/OLl2KL8d9QHp6OgkJSdxx20OhqF5ApKel897gtxny2RNEREYwe/Qstm/cxrX39eaX739mxczlnHtJNR5+7xGKlSxGvVb1uOa+3tzTaiDlz63A7U8PJD3dERFhjHvzK3bko8ZKWloazz/6Mq+OfIGIyAgmfzGNTRu30P/Bm1m3dj0LY5cwadQ0nnj1UcYuHkHK3v08evsTGcfXblCTpPidxG9LyNi2K2k37w//mHfGv0bqoVQS45IYeu/T2T192EhLS+PpR4bz1qiXiIiMZMKoKfy6YTN3PNSPH9esZ37sIsaPnMKTrz/G5G++JGVvCg/d9hgAdRrUYuBD/Th0KBWX7hj20HOk7N0f4hrlDQ8OeYYVq79j794UWnbtwx239OWqTm1DHVbIpOfzSeHM5XDPtJkNyelg59wTOe0HqBvdOH9fwVyy9Y+dJy4kADQqWT3UIYSFuNSUUIcQFv5KPxTqEMLGyh9Ovflc/qmCZ1cJ6vwN55S6JGi/a7fu/i7HuplZO+AVIBJ43zn3zFH7TwM+xTfudTfQyzm3Jadz5phZOboxYmZFnXN/5HSMiIiIBFdOiYdgMrNI4A2gNbADWGFmk5xzP2Uqdgvwm3PuXDO7BngW6JXTeb3euny5mf0ErPev1zSzN/9BPURERCT/qg/84pzb5Jz7G/gC6HJUmS7AJ/7HXwEt7QQziXqdFO5loC2+dA3OubVAE4/HioiISACl44K2nEA5IPPgvB3+bdmWcc6lAvuAHCew8jyDrXPu6JGBmkhDRETkFGNm/c1sZaalf6Cf0+s8K9vNrCHgzKwgcA+wLnBhiYiIiFfBHLPinHsXePc4u+Pwzcd2WHn/tuzK7DCzAkBJ/D03x+M1szIAGIgvdRMH1PKvi4iIiBy2AqhmZpXNrBBwDb6JZDObBNzgf3w1MMedoLXlKbPinNsFhPc0kiIiIvlUeh65G8g5l2pmdwIz8N26/KFz7kczGwqsdM5NAj4APjOzX4A9+Bo0OfLUWDGz6sBbQFnn3EVmdgnQ2Tmn7+cWERGRDM65acC0o7Y9lunxn0CPkzmn126g94D/Aof8T/QdHlpCIiIiEnguiP9CwWtjpahz7ugvREnN7WBEREREjub1bqBdZlYVfE0q/7cvJ+R8iIiIiARDXpnBNlC8NlYG4rtN6XwziwM2owG3IiIiEgRe7wbaBLQys9OBCOecvvZTREQkj8jv37rs9buBfjWzEUBfoGJgQxIRERE5wusA2wuBd/DN3f+8v/EyPnBhiYiIiPh4HbOShu+25TQgHdjpX0RERCTENMDWJwX4HhgOvOecy3EOfxEREZHc4rWxci3QCLgD6GdmS4AFzrnZAYtMREREPMkr0+0Hite7gSYCE83sfOBK4F7gIaBI4EITERER8f7dQGOBmsCvwALgemBZAOMSERERjzRmxedpYLVzLi2QwYiIiIgczWs30Mqjt5lZlHMuMfdDEhERkZOhSeGO74Nci0JERETkOE6YWTGzSGCWc6555u3OuQ4Bi0pEREQ8y+9jVk6YWfGPU0k3s5JBiEdEREQkC68DbA8A35vZTOD3wxudc3cHJCoRERHxTPOs+IzzLyIiIiJB5fVuoE/MrAhQ0Tm3IcAxiYiIyElwuhsIzKwTsAb42r9ey8wmBTAuEREREcB7N9DjQH1gHoBzbo2ZVQlQTCIiInIS8vuYFa/zrBxyzu07alt6bgcjIiIicjSvmZUfzew6INLMqgF3A0sCF5aIiIiIj9fMyl1ADeAvYBSQgu+bl0VERCTEnHNBW0LB691AfwCPmtmzvlW3P7BhiYiIiPh4aqyYWT3gQ6C4f30fcLNzblUAYxMREREP8vuty17HrHwA3OGcWwhgZo2Aj4BLAhWYiIiICHhvrKQdbqgAOOcWmVlqgGISERGRk5Dfv8jQa2Nlvpm9g29wrQN6AfPMrA6Ac+7bAMUnIiIipzivjZWa/v+HHLW9Nr7GS4tci0hEREROijIrgHOueaADEREREcmO13lWjnG4C0hERERCywVxCYV/3FgBbs+1KERERESOw/J7P1d2zKy/c+7dUMcRDnStvNF18k7XyhtdJ290nU4NnjIrZnaFmZ3uf9zHzIab2TmBDS2g+oc6gDCia+WNrpN3ulbe6Dp5o+t0CvDaDfQW8IeZ1QTuB34FPg1YVCIiIiJ+Xhsrqc7XX9QFeN059wb+qfdFREREAsnrPCv7zey/QB+giZlFAAUDF1bAqX/TO10rb3SdvNO18kbXyRtdp1OApwG2ZhYFXAescM4tNLOKQDPnnLqCREREJKBO2Fgxs0hgliaGExERkVA44ZgV51wakG5mJYMQjwSAmd1tZuvMbEQOZQ7kwvPcaGYx//Y8ucEfy+u5fM6uZnZhpvWhZtYqN58jHJlZjJl95X9cy8zaezimmZlNyaXnD5ufQ25eKzOrZGY/BCLOHGIJ+nOGAzN73MweCHUc+ZnXMSsHgO/NbCbw++GNzrm7AxKV5LY7gFbOuR0Bfp4bgR+A+AA/T6h0BaYAPwE45x4LaTR5hHMuHrjav1oLqAtMC+Lzh83PIdTXKi8yswLOudRwfw4JLK93A40DBgMLgFWZljzLzCaY2Soz+9HM+vu33WJmG81suZm9d/gvbzMrbWZjzWyFf7kitNHnHjN7G6gCTDezfWb2oZnNM7NNZnZMY9PM3jCzzv7H483sQ//jm83sSf/jwWa2wcwWmdkoM3vAzK7G98E7wszWmFmRANerj//nuMbM3jGzSDO76fDPF7giU9mP/fEdXj+Q6fHDZva9ma01s2f82271vw7W+l8XRc2sIdAZeN7/nFUzn9fMWprZav+5PjSz0/zbt5jZE2b2rX/f+dnUpZn/Z/KVma03sxFmZpmOP9v/uK6ZzfM/ftzMPjGzhWa21cy6m9lz/uf42sw8D4A3s+vN7Dt/fT8zs05mtsxfn1lmVjbTc35mZt+Y2c9mdqt/eyUz+8HMCgFDgV7+a9TLzOr7y682syVmdt4JYokwszf912GmmU3LdI0f8/9cfjCzdzNdo8w/hxNe738jL12ro+IqbGYf+eu82sya+7fXsCPvk+/MrJqZnW5mU/11+MHMep3kZYg03+fnj2YWa2ZFzJclWup/jvFmdqb/+eeZWV3/47PNbIv/8Y1mNsnM5gCzzSzazBb44/zBzBpnU8d5ZvZKpjL1/dtPN997brm/7l2ye45M56lnZuP8j7uY2UEzK+S/hpv826ua7320ynzvsfP920/4u8J8nx/TLcCfgacc51y+XICz/P8XwffXfjlgC3AWvjuZFuK7DRtgJNDI/7gisC7U8efytdgCnA08DiwBTvOv7wYK+ssc8P9/DfC8//FyYKn/8UdAW6AesAYojO/29Z+BB/xl5gF1g1CfC4DJmWJ/E7gB2AaUBgoBizP9fD8Grs50/OG6Xum/HkWPes2UylR2GHDXcc7zMb6/kgsD24Hq/u2fAvdmuvaHj78DeD+b+jQD9gHl8f0B8U2m1+MW4Gz/47rAPP/jx4FF/tdyTeAP4Er/vvFAV4/XsgawMdNznAWcyZHxbP2AFzM951p876mz/XWOASoBP/jL3Hj4uvvXSwAF/I9bAWMz1XlKNvFcjS/TEAFEAb8dvuaHfz7+x58BnY7+uXi53v/idZfXrlXmc90PfOh/fD6+90Jh4DWgt397IX88VwHvZTpPyZO4BpWAVKCWf/1LfHeJfgc09W8bCrx89GeC/zpsyVT3HRx5z90PPOp/HAkUz+a55x2OG2iSqe5PAX38j8/w/4xOP/o5Mp2nALDJ//gFYAW+P26aAqP822cD1fyPLwPm+B9n+7vC//N+ALgTmAiclluvOy2+xVM3kJltJpvvL3LOVfFyfIjcbWbd/I8rAH2B+c65PQBmNgao7t/fCrjQ/4caQAkzK+ac+9fjOPKgqc65v4C/zGwnUBbfG/qwhcC95hub8RNwpplFA5cDdwO3ABOdc38Cf5rZ5OCGD0BL4FJghf9nVgRoiO8XeTKAmY3myM/3eFoBHznn/gA4/NoALjKzYfg++IoBM05wnvOAzc65jf71T4CBwMv+9XH+/1cB3Y9zjuXO301nZmvw/VJYdILnne6cO2Rm3+P7gP/av/17//FetADGOOd2ge8amNnFwGj/z70QsDlT+YnOuYPAQTObC9TH13g9npLAJ2ZWDd9nyIkyPo388aQDif7nOKy5mT0EFMXXUPgRX6P1aF6u9z+R165VZo3wNUxwzq03s634Xv/fAI+aWXlgnHPuZ//r5UUzexZfI2jhSTwP+F7rh+uxCqgKnOGcm+/f9gkwxsN5ZmZ6z60APjRfRnBCpvMfbRSAc26BmZUwszOANkBnOzJmpDC+hsTRz4H/2FQz+9XMLsD3MxmOr/ETCSw0s2L4Pk/GZPqdcJr//2x/V/gfX4+vUdrVOXfIQ/3lJHjtBqqL7y/qekBj4FXg80AF9W+ZWTN8L6rLnXM1gdXA+hwOiQAaOOdq+Zdy+bShAvBXpsdpHDVuyTkXh++XdDt83X4LgZ74shH7gxTjiRjwSaaf13n4/rI5nlT8r3XzzRFU6ATn/xi40zl3MfAEvg+/f+PwNT/memdT5uhyGbFnE8dfAP5f7Iecc4f/oEjP4Xm8eA3fX/wXA7cd9bxH/9FyorkP/gfMdc5dBHTiH15LMyuML4N2tT+u93I4l5frnVvy3LXK8oTOjcTXfXkQmGZmLfyN6jr4GrXDzOxkx/wc/Vo9I4eyOb1+M49/XICvwRAHfGxm1x/nfNldUwOuyvR5UNE5t+7o5zjKAnyZ1UPALHyNvUb4Pu8igL2ZzlfLOXeB/7icflcc/iOh/HGeU/4FT40V59zuTEucc+5loENgQ/tXSgK/Oef+8Pc1NsCXFmxqZmeaWQF8qdDDYoG7Dq+YWa1gBpsHLQXu5Uhj5QH//+DrXunk798tBnTMdNx+gjOz8WzgajMrA2BmZ+FrkDY1s1L+v856ZCq/BV8mBnwf3If/Yp0J3GRmRTOdB3x1SPCfp3em8xyvfhuASmZ2rn+9LzA/m3L/RObYr8qh3D81B+hhZqUg4xqUxPdLA3zda5l18f/sS+Hrnlhx1P6jr1Hmc93oIZ7FwFXmG7tS1v8ccOQX3S7/6+7q7A4OsLx2rTJbiP+1ambV8WUWNphZFXxdHq/i6564xHx37P3hnPsceB5fw+Xf2Af8lmmcSebX/xaOvH6P+zMz33fNJTnn3gPezyGmXv7yjYB9zrl9+DKfd5lljGGq7SHmhfg+477xZ2NL4cuQ/uCcSwE2m1kP//nMfF81Azn/rliNr8E6yfLIXZH5idcvMqyTaalrZgMI/F8s/8bXQAEzWwc8g++Xbxy+vs3l+D4Qt+B7k4Gve6Ou+QaH/QQMCHrEectCfH3nvwDf4ku5LwRwzq0AJuHro56O76+Jw9fxY+BtC/AAW+fcT8AgINbMvsPX6IjGl135Bt/Pd12mQ97D15BZi68763f/eb7212Wlv+vlcBp5MLDMf57MGbkvgAfNN4ivaqZ4/gRuwpc2/h5fZuPtnOrgfx+976G6TwCvmNlKfH/F5irn3I/Ak8B8//UZju86jjGzVcCuow75DpiL7z31P+e7uyWzufjS5GvMN3DzOeBpM1vNcT4zjroWY/F1S/6EL3v7Lb5fSnvx/Rx/wPfL6ehf/AGXB69VZm8CEf7X32jgRn93b0/gB//r+yJ846kuBpb7tw3BNy7r37oB3+Dz7/Dd5TTUv/0F4HZ/nc7O4fhmwFp/uV7AKwBm9r75B+j6/ekv8za+LmnwZaQKAt+Z2Y/+9WOYb7D24UbEMnxd4Av8698B32fKTvYGbvH/nH/E91UzcILfFc65Rfg+R6aaf2C85A6vM9hm7jdOxfeL/gXn3IYAxRUQ5h+H4s+sjMc3IG18qOMKN5muY1F8b/b+zrlvQx2XBJaZPY6vO/CFAD/P4ddXKXx/XFzhnEsM5HPmtmBdq1OJ+e6Ee8A5tzLUsUjwecqOuPwze+3j5ps8qjC+dN6E0IYTtt413wDcwvjGjqihIrlpin/gZCF8GYmwaqiISO7zmlkpiS9d2MS/aT4w1N9fKCIiIhIwXu8G+hDfYLCe/iUF37wbIiIiIgHlNbOyxjlX60TbRERERHKb18zKQf+tYgCYb4rhg4EJSUREROQIr5mVWvhmJSzp3/QbcINz7rvAhSYiIiLivbFyGr4Jfarim61wH+Ccc0NzOk5ERETk3/I6sdtEYC++CZrici4qIiIiknu8ZlZ+8H9fhYiIiEhQeR1gu8R83y4qIiIiElQ5Zlb83zPh8HUXVQM24fvGTcM3ZuWSYAQpIiIip64TNVbOyelg59zWXI9IREREJBNPY1ZEREREQsXrmBURERGRkFBjRURERPI0NVZEREQkT1NjRURERPI0NVZEREQkT/t/gBNsZHv5HIcAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 720x720 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(10,10))\n",
+    "sns.heatmap(df.corr(),annot=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There are only few features in the above heat map as most of them are of object type. From here we can see that the independent features don not have much correlation with each other i.e. no multicollinearity."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Feature Engineering"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "###### Encoding"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:05.819458Z",
+     "iopub.status.busy": "2021-07-05T16:36:05.818924Z",
+     "iopub.status.idle": "2021-07-05T16:36:05.950297Z",
+     "shell.execute_reply": "2021-07-05T16:36:05.949585Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:05.819423Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "from sklearn.preprocessing import LabelEncoder, OrdinalEncoder\n",
+    "l=LabelEncoder()\n",
+    "o=OrdinalEncoder()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:07.019232Z",
+     "iopub.status.busy": "2021-07-05T16:36:07.018688Z",
+     "iopub.status.idle": "2021-07-05T16:36:07.094492Z",
+     "shell.execute_reply": "2021-07-05T16:36:07.093829Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:07.019197Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "#We use ordinal encoder to Encode Independent features\n",
+    "for i in df.columns:\n",
+    "    if df[i].dtypes=='O' and i!='income':\n",
+    "        df[i]=o.fit_transform(df[i].values.reshape(-1,1))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:07.529008Z",
+     "iopub.status.busy": "2021-07-05T16:36:07.528484Z",
+     "iopub.status.idle": "2021-07-05T16:36:07.539388Z",
+     "shell.execute_reply": "2021-07-05T16:36:07.538415Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:07.528975Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "#We use label encoder to encode label \n",
+    "df['income']=l.fit_transform(df['income'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "##### Removing Outliers"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:10.608324Z",
+     "iopub.status.busy": "2021-07-05T16:36:10.607889Z",
+     "iopub.status.idle": "2021-07-05T16:36:10.611663Z",
+     "shell.execute_reply": "2021-07-05T16:36:10.611024Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:10.608296Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "from scipy.stats import zscore"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:10.970177Z",
+     "iopub.status.busy": "2021-07-05T16:36:10.969781Z",
+     "iopub.status.idle": "2021-07-05T16:36:10.975575Z",
+     "shell.execute_reply": "2021-07-05T16:36:10.974536Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:10.970144Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "#Method to find optimum threshold\n",
+    "def threshold():\n",
+    "    for i in np.arange(3,5,0.2):\n",
+    "        data=df.copy()\n",
+    "        data=data[(z<i).all(axis=1)]\n",
+    "        loss=(df.shape[0]-data.shape[0])/df.shape[0]*100\n",
+    "        print('With threshold {} data loss is {}%'.format(np.round(i,1),np.round(loss,2))) "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:11.15409Z",
+     "iopub.status.busy": "2021-07-05T16:36:11.153708Z",
+     "iopub.status.idle": "2021-07-05T16:36:11.19823Z",
+     "shell.execute_reply": "2021-07-05T16:36:11.197146Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:11.154056Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "With threshold 3.0 data loss is 15.79%\n",
+      "With threshold 3.2 data loss is 12.17%\n",
+      "With threshold 3.4 data loss is 11.1%\n",
+      "With threshold 3.6 data loss is 10.2%\n",
+      "With threshold 3.8 data loss is 9.0%\n",
+      "With threshold 4.0 data loss is 8.44%\n",
+      "With threshold 4.2 data loss is 7.46%\n",
+      "With threshold 4.4 data loss is 6.08%\n",
+      "With threshold 4.6 data loss is 4.37%\n",
+      "With threshold 4.8 data loss is 1.55%\n"
+     ]
+    }
+   ],
+   "source": [
+    "z=np.abs(zscore(df))\n",
+    "threshold()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "From above we choose threhold as 4.2 as data is precious and we cannot afford to lose more than 8% of data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:11.516415Z",
+     "iopub.status.busy": "2021-07-05T16:36:11.515856Z",
+     "iopub.status.idle": "2021-07-05T16:36:11.522605Z",
+     "shell.execute_reply": "2021-07-05T16:36:11.521832Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:11.516381Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "df=df[(z<4.2).all(axis=1)]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "###### Removing Skewness"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:13.458162Z",
+     "iopub.status.busy": "2021-07-05T16:36:13.457779Z",
+     "iopub.status.idle": "2021-07-05T16:36:13.461994Z",
+     "shell.execute_reply": "2021-07-05T16:36:13.461064Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:13.458128Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "#using Power transformer to remove skewness\n",
+    "from sklearn.preprocessing import PowerTransformer\n",
+    "pt=PowerTransformer()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:14.558068Z",
+     "iopub.status.busy": "2021-07-05T16:36:14.557717Z",
+     "iopub.status.idle": "2021-07-05T16:36:14.742224Z",
+     "shell.execute_reply": "2021-07-05T16:36:14.741301Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:14.558036Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "for i in cont:\n",
+    "    if np.abs(df[i].skew())>0.5:\n",
+    "        df[i]=pt.fit_transform(df[i].values.reshape(-1,1))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:16.259259Z",
+     "iopub.status.busy": "2021-07-05T16:36:16.258779Z",
+     "iopub.status.idle": "2021-07-05T16:36:18.366263Z",
+     "shell.execute_reply": "2021-07-05T16:36:18.365179Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:16.259228Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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v9gkjGdivjIcWb2DW5J6ZKmpmybhn4TsHbPvMWRNSqKTnuMffzstvbeGdLR9wxenJXRumX3kpl540mseWbuKD5n2JtWNm1hEHfzv/UfsuA/uWccmM0Ym286mZ4/igucVz+s2s6Bz8bTTt3stjb9Rx2SljqOhTmmhbNROHMn5YBfe98m6i7ZiZtefgb+PXSzaya28Lf10zLvG2SkrEZ8+ayEtrt7CyzhdiN7PicfDntbYGdz63jpPHDea08UOK0uZVZ4ynX3kJd73wVlHaMzMDB/+HnlixmXWNO/nq+cd2+0pbXTWksg+fPHUsD7+6gfd3NhelTTMzBz+5M3XnPrOWsUMq+NiJ3bugend96bxj2LOvlbnPri1qu2aWXQ5+clfZqn37ff7zXxx72Bdc6arjqwdy+Slj+Pnz66jfvruobZtZNmU++Pe2tHLrYys5tqo/V52ZzkkZ3/jo8exrCX785OpU2jezbMl88N/x3DrWNu7k2x+bRnmRe/v7TRrRn2vOnsg9L7/Dy+u2pFKDmWVHpoN/6YZt/NO8VVwyYxQXThuZai1/f/FUxg2t4MYHXvPZvGaWqMwGf+OOPVx/z2KG9+/LrVecVLSZPAfTv28ZP7ziFN7Z8gF/e+8Sr9xp1gs172tl6wfNvNW4k/rtu2ne15p2Sd2SyUXa3t/ZzDW3L6Ru+27u/spZDKnsk3ZJAJxz3HBu+cQMbn5kGd9+6A1+8J9OLPqHzWaW80HzPhau3cLvX9/Ixm27eW/HHrbvzv01/sPHVwG5q+pNGl7JlJEDmTFmEOdNGcHJ44ZQWpJuR7IzmQv+197dytfvWUz99j3c8YUaTp84LO2S/sznz5lEY9Me/s9Ta9iwdRe3ffoURg7sl3ZZZke9ltZg2cZtPLu6kWdXN7Do7ffZ2xKUlYjRg/txXNUARgzsy8C+ZcyaPIJde1uo27ab1fVNvLm5iceX1/FP899kcEU5syYP5/wpVZw3eQTjh1Wm/U87QCrBL+kS4MdAKXB7RNyadJurNzfx02fW8tDi9YweXMF9Xzub0yYMTbrZbvm7i6Yyblgl33l4KbN/9DRfu+BYPn3meP8CMOtBe1taWVO/g5fXbeGFPzaycN0Wtn6wF4BpowfxpVnHcN6UEaxt2HnAxI8rTj9wWZctO5t5fk0jz7zZwLOrG3n0jdwCjOOHVXDusSM4d/JwzjpmONWD+qY+tKyI4o4lSyoF3gTmAOuBV4CrI2L5wZ5TU1MTtbW1XW7r2dUNzFu2mYXr3uPNzTvoU1bC58+eyPWzJ/f48E4Sa3ava9zJD36/nCdW1FNWImZOGMrMiUOZNLySCcMqqR7cj8o+pVSUl9KvvJS+ZSWp/0BZz+nsvdnZW7ezd/ahjt/5cztr+/Bq70xnz2/e10rTnr3s3NPCjj172b57H5u37Wbjtt2sf/8D3tzcxJt1O2huyY3Rjx1SwTnHDWfW5OGcN7mKqoF/uhZHd97bEcGa+h288Mf3eH5NIy+tfe/DYaKhleWcMGoQU6oHMGZIBaMG9WPkoL4M7FtOZd9SBvQto7JP7j1dVqLDek9LWhQRNe23p9HjPxNYExFrAST9O3A5cNDg766nVzXw4OL1nDZhCFefOYHLTh7zZ/+hvd0xI/pz+7VnsKZ+Bw8tXs9zaxq5/dm17DvIB78SlOZ/SPb/rAjBh7c54LFCfqaSfJN3+v5POGAOJxw7e36R+1RWAAlGDuzL8dUD+eKsSUwbPYjTJw7t8eEYSUypHsiU6oFce+4kWlqD5Ru3U/v2FlbVNbGyromHF2+gaU/nM/h+/sUz+MjUnp11mEaP/0rgkoj4Sv7+54CzIuL6dvtdB1yXvzsVWFXUQnuHEUBj2kX0In49DuTX5EB+Tf5kYkRUtd/Yaz/cjYi5wNy060iTpNqO/kzLKr8eB/JrciC/Jp1LY67gBmB8m/vj8tvMzKwI0gj+V4Apko6R1Ae4CvhNCnWYmWVS0Yd6ImKfpOuBx8lN57wzIpYVu44jRKaHujrg1+NAfk0O5NekE0X/cNfMzNLl9QDMzDLGwW9mljEO/l5I0iWSVklaI+mmtOtJm6Q7JdVLWpp2Lb2FpPGSFkhaLmmZpBvSriltkvpJelnSa/nX5Htp19RbeYy/l+nOkhZHO0kXADuAf4uIE9OupzeQNBoYHRGLJQ0EFgGfzPjPiYD+EbFDUjnwHHBDRLyUcmm9jnv8vc+HS1pERDOwf0mLzIqIZwBfmqyNiNgUEYvzt5uAFcDYdKtKV+TsyN8tz3+5Z9sBB3/vMxZ4t8399WT8DW2HJmkScBqwMOVSUiepVNISoB6YHxGZf0064uA3O4JJGgA8CHwjIranXU/aIqIlIk4ltyLAmZI8NNgBB3/v4yUtrCD5cewHgbsj4qG06+lNImIrsAC4JOVSeiUHf+/jJS2sU/kPMu8AVkTEbWnX0xtIqpI0JH+7gtwEiZWpFtVLOfh7mYjYB+xf0mIF8B9ZX9JC0r3Ai8BUSeslfTntmnqBWcDngNmSluS//irtolI2Glgg6XVyHaj5EfG7lGvqlTyd08wsY9zjNzPLGAe/mVnGOPjNzDLGwW9mljEOfjOzjHHwm7UjaYykB/K3Ty1kmqSkv5TUI1MHJX1f0kd74lhmHSn6pRfNeruI2Ahcmb97KlADPFrE9m8uVluWTe7x21FH0uclvZ5fl/2Xkj4uaaGkVyU9Iak6v98t+cdflLRa0lfz2ydJWpo/c/r7wKfzJ0h9WtKZ+f1flfSCpKmd1FIi6SeSVkqaL+lRSVfmH7tZ0iv5tubmz8ZF0i/a7POWpO9JWizpDUknJPnaWTY4+O2oImkG8B1gdkScAtxAbl32syPiNHLLXN/Y5iknA7OBc4CbJY3Z/0B+Weybgfsi4tSIuI/cEgDn5491M/A/OinpU8AkYDq5M23PafPYv0TEGflrDFQAlx3kGI0RMRP4V+C/ddKeWac81GNHm9nA/RHRCBARWySdBNyXv3hJH2Bdm/0fiYhdwC5JC8hdD2HJIY4/GLhL0hRya72Xd1LPefl6WoG6fBv7fUTSjUAlMAxYBvy2g2PsX4BtEblfJGaHxT1+y4J/Jte7Pgn4GtCvzWPt1yzpbA2TfwAW5HvpH293rIJJ6gf8BLgyX9fPDnGsPfnvLbizZj3AwW9Hm6eAv5Y0HEDSMHK99P1LW1/bbv/L89dqHQ78JbnFvdpqAga2ud/2WF8ooJ7ngSvyY/3V+TbgTyHfmF9T/8qOnmyWBAe/HVXyK5n+AHha0mvAbcAtwP2SFgGN7Z7yOrl1218C/iE/o6etBcD0/R/uAj8E/qekVzlI71tSjaTb83cfJHcVteXAr4DFwLb8evE/A5aSW4m1/S8cs8R4dU7LLEm3ADsi4kcJtzMgfwHw4cDLwKyIqEuyTbND8XihWfJ+l79ASB9yf1U49C1V7vGbmWWMx/jNzDLGwW9mljEOfjOzjHHwm5lljIPfzCxj/j+MJuYGd3zK8wAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 432x288 with 0 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "for i in cont:\n",
+    "    sns.distplot(df[i])\n",
+    "    plt.figure()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "A lot of skewness has been resuced but we cannot remove skewness more than this."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:18.368392Z",
+     "iopub.status.busy": "2021-07-05T16:36:18.368013Z",
+     "iopub.status.idle": "2021-07-05T16:36:18.378452Z",
+     "shell.execute_reply": "2021-07-05T16:36:18.377402Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:18.368352Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "#Separating dependent and independent features.\n",
+    "x=df.copy()\n",
+    "x.drop('income',axis=1,inplace=True)\n",
+    "y=df['income']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "##### Handling Imbalanced Data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:19.318224Z",
+     "iopub.status.busy": "2021-07-05T16:36:19.317905Z",
+     "iopub.status.idle": "2021-07-05T16:36:19.774222Z",
+     "shell.execute_reply": "2021-07-05T16:36:19.773009Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:19.318196Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "#Oversampling using Smote\n",
+    "from imblearn.over_sampling import SMOTE\n",
+    "over=SMOTE()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:19.907976Z",
+     "iopub.status.busy": "2021-07-05T16:36:19.90764Z",
+     "iopub.status.idle": "2021-07-05T16:36:20.216843Z",
+     "shell.execute_reply": "2021-07-05T16:36:20.215965Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:19.907946Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "x,y=over.fit_resample(x,y)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:20.479115Z",
+     "iopub.status.busy": "2021-07-05T16:36:20.478775Z",
+     "iopub.status.idle": "2021-07-05T16:36:20.644175Z",
+     "shell.execute_reply": "2021-07-05T16:36:20.643132Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:20.479079Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1    23424\n",
+       "0    23424\n",
+       "Name: income, dtype: int64"
+      ]
+     },
+     "execution_count": 64,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x360 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(15,5))\n",
+    "plt.subplot(1,2,1)\n",
+    "y.value_counts().plot.pie(autopct='%1.1f%%')\n",
+    "plt.subplot(1,2,2)\n",
+    "sns.countplot(y)\n",
+    "y.value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Data is balanced now, both the category of income have 50% data each."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "##### Scaling the data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:22.2191Z",
+     "iopub.status.busy": "2021-07-05T16:36:22.218755Z",
+     "iopub.status.idle": "2021-07-05T16:36:22.222422Z",
+     "shell.execute_reply": "2021-07-05T16:36:22.221719Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:22.219068Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "#Scaling the data using min max scaler\n",
+    "from sklearn.preprocessing import MinMaxScaler\n",
+    "scaler=MinMaxScaler()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:23.538389Z",
+     "iopub.status.busy": "2021-07-05T16:36:23.538054Z",
+     "iopub.status.idle": "2021-07-05T16:36:23.55238Z",
+     "shell.execute_reply": "2021-07-05T16:36:23.551386Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:23.538359Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "xd=scaler.fit_transform(x)\n",
+    "x=pd.DataFrame(xd,columns=x.columns)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>age</th>\n",
+       "      <th>workclass</th>\n",
+       "      <th>fnlwgt</th>\n",
+       "      <th>education</th>\n",
+       "      <th>education.num</th>\n",
+       "      <th>marital.status</th>\n",
+       "      <th>occupation</th>\n",
+       "      <th>relationship</th>\n",
+       "      <th>race</th>\n",
+       "      <th>sex</th>\n",
+       "      <th>capital.gain</th>\n",
+       "      <th>capital.loss</th>\n",
+       "      <th>hours.per.week</th>\n",
+       "      <th>native.country</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0.186132</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>0.131482</td>\n",
+       "      <td>0.733333</td>\n",
+       "      <td>0.533333</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0.571429</td>\n",
+       "      <td>0.200000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.428571</td>\n",
+       "      <td>0.945946</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0.086358</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.327785</td>\n",
+       "      <td>0.066667</td>\n",
+       "      <td>0.400000</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.600000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.428571</td>\n",
+       "      <td>0.837838</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0.272858</td>\n",
+       "      <td>0.750000</td>\n",
+       "      <td>0.519066</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.600000</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.200000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.428571</td>\n",
+       "      <td>0.945946</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0.722618</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>0.532172</td>\n",
+       "      <td>0.733333</td>\n",
+       "      <td>0.533333</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.857143</td>\n",
+       "      <td>0.800000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.318681</td>\n",
+       "      <td>0.945946</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0.186132</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>0.257392</td>\n",
+       "      <td>0.733333</td>\n",
+       "      <td>0.533333</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0.857143</td>\n",
+       "      <td>0.600000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.340659</td>\n",
+       "      <td>0.945946</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46843</th>\n",
+       "      <td>0.641593</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>0.395278</td>\n",
+       "      <td>0.733333</td>\n",
+       "      <td>0.533333</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>0.214286</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.428571</td>\n",
+       "      <td>0.945946</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46844</th>\n",
+       "      <td>0.559382</td>\n",
+       "      <td>0.380057</td>\n",
+       "      <td>0.751217</td>\n",
+       "      <td>0.695954</td>\n",
+       "      <td>0.800000</td>\n",
+       "      <td>0.826591</td>\n",
+       "      <td>0.714286</td>\n",
+       "      <td>0.695954</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.479772</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.373626</td>\n",
+       "      <td>0.945946</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46845</th>\n",
+       "      <td>0.615802</td>\n",
+       "      <td>0.291082</td>\n",
+       "      <td>0.435371</td>\n",
+       "      <td>0.800000</td>\n",
+       "      <td>0.866667</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>0.285714</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.278557</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.494505</td>\n",
+       "      <td>0.945946</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46846</th>\n",
+       "      <td>0.608934</td>\n",
+       "      <td>0.250000</td>\n",
+       "      <td>0.233602</td>\n",
+       "      <td>0.800000</td>\n",
+       "      <td>0.866667</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>0.714286</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.648352</td>\n",
+       "      <td>0.945946</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46847</th>\n",
+       "      <td>0.505475</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>0.497498</td>\n",
+       "      <td>0.600000</td>\n",
+       "      <td>0.800000</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>0.714286</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.428571</td>\n",
+       "      <td>0.945946</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>46848 rows × 14 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            age  workclass    fnlwgt  education  education.num  \\\n",
+       "0      0.186132   0.500000  0.131482   0.733333       0.533333   \n",
+       "1      0.086358   0.000000  0.327785   0.066667       0.400000   \n",
+       "2      0.272858   0.750000  0.519066   1.000000       0.600000   \n",
+       "3      0.722618   0.500000  0.532172   0.733333       0.533333   \n",
+       "4      0.186132   0.500000  0.257392   0.733333       0.533333   \n",
+       "...         ...        ...       ...        ...            ...   \n",
+       "46843  0.641593   0.500000  0.395278   0.733333       0.533333   \n",
+       "46844  0.559382   0.380057  0.751217   0.695954       0.800000   \n",
+       "46845  0.615802   0.291082  0.435371   0.800000       0.866667   \n",
+       "46846  0.608934   0.250000  0.233602   0.800000       0.866667   \n",
+       "46847  0.505475   0.500000  0.497498   0.600000       0.800000   \n",
+       "\n",
+       "       marital.status  occupation  relationship      race       sex  \\\n",
+       "0            0.666667    0.571429      0.200000  1.000000  0.000000   \n",
+       "1            0.500000    0.000000      0.600000  0.000000  0.000000   \n",
+       "2            0.666667    1.000000      0.200000  1.000000  1.000000   \n",
+       "3            0.000000    0.857143      0.800000  1.000000  0.000000   \n",
+       "4            0.666667    0.857143      0.600000  1.000000  0.000000   \n",
+       "...               ...         ...           ...       ...       ...   \n",
+       "46843        0.333333    0.214286      0.000000  1.000000  1.000000   \n",
+       "46844        0.826591    0.714286      0.695954  1.000000  0.479772   \n",
+       "46845        0.333333    0.285714      0.000000  0.278557  1.000000   \n",
+       "46846        0.333333    0.714286      0.000000  1.000000  1.000000   \n",
+       "46847        0.333333    0.714286      0.000000  1.000000  1.000000   \n",
+       "\n",
+       "       capital.gain  capital.loss  hours.per.week  native.country  \n",
+       "0               0.0           1.0        0.428571        0.945946  \n",
+       "1               0.0           1.0        0.428571        0.837838  \n",
+       "2               0.0           1.0        0.428571        0.945946  \n",
+       "3               0.0           1.0        0.318681        0.945946  \n",
+       "4               0.0           1.0        0.340659        0.945946  \n",
+       "...             ...           ...             ...             ...  \n",
+       "46843           0.0           0.0        0.428571        0.945946  \n",
+       "46844           0.0           0.0        0.373626        0.945946  \n",
+       "46845           0.0           0.0        0.494505        0.945946  \n",
+       "46846           0.0           0.0        0.648352        0.945946  \n",
+       "46847           0.0           0.0        0.428571        0.945946  \n",
+       "\n",
+       "[46848 rows x 14 columns]"
+      ]
+     },
+     "execution_count": 67,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Modelling Phase"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:25.047128Z",
+     "iopub.status.busy": "2021-07-05T16:36:25.046784Z",
+     "iopub.status.idle": "2021-07-05T16:36:25.127027Z",
+     "shell.execute_reply": "2021-07-05T16:36:25.126071Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:25.047099Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "#We import Classification Models\n",
+    "from sklearn.naive_bayes import  GaussianNB\n",
+    "from sklearn.neighbors import KNeighborsClassifier\n",
+    "from sklearn.linear_model import LogisticRegression\n",
+    "from sklearn.tree import DecisionTreeClassifier\n",
+    "from sklearn.ensemble import RandomForestClassifier\n",
+    "from sklearn.ensemble import AdaBoostClassifier\n",
+    "from sklearn.ensemble import GradientBoostingClassifier\n",
+    "from xgboost import XGBClassifier"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:26.248114Z",
+     "iopub.status.busy": "2021-07-05T16:36:26.247757Z",
+     "iopub.status.idle": "2021-07-05T16:36:26.252576Z",
+     "shell.execute_reply": "2021-07-05T16:36:26.251854Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:26.248074Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "from sklearn.model_selection import train_test_split, cross_val_score"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:26.639631Z",
+     "iopub.status.busy": "2021-07-05T16:36:26.639156Z",
+     "iopub.status.idle": "2021-07-05T16:36:26.643649Z",
+     "shell.execute_reply": "2021-07-05T16:36:26.642623Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:26.6396Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "from sklearn.metrics import accuracy_score,confusion_matrix,classification_report,roc_auc_score,roc_curve"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:27.319144Z",
+     "iopub.status.busy": "2021-07-05T16:36:27.318791Z",
+     "iopub.status.idle": "2021-07-05T16:36:27.324076Z",
+     "shell.execute_reply": "2021-07-05T16:36:27.323386Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:27.319114Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "#Function to find the best random state\n",
+    "def randomstate(x,y):\n",
+    "    maxx=0\n",
+    "    model=LogisticRegression()\n",
+    "    for i in range(1,201):\n",
+    "        xtrain,xtest,ytrain,ytest=train_test_split(x,y,test_size=0.25,random_state=i)\n",
+    "        model.fit(xtrain,ytrain)\n",
+    "        p=model.predict(xtest)\n",
+    "        accu=accuracy_score(p,ytest)\n",
+    "        if accu>maxx:\n",
+    "            maxx=accu\n",
+    "            j=i\n",
+    "    return j"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:27.859665Z",
+     "iopub.status.busy": "2021-07-05T16:36:27.859095Z",
+     "iopub.status.idle": "2021-07-05T16:36:27.865052Z",
+     "shell.execute_reply": "2021-07-05T16:36:27.864185Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:27.859631Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "#To evakuate performances of all the models\n",
+    "def performance(p,ytest,m,xtest,s):\n",
+    "    print('------------------------------------',m,'------------------------------------')\n",
+    "    print('Accuracy',np.round(accuracy_score(p,ytest),4))\n",
+    "    print('----------------------------------------------------------')\n",
+    "    print('Mean of Cross Validation Score',np.round(s.mean(),4))\n",
+    "    print('----------------------------------------------------------')\n",
+    "    print('AUC_ROC Score',np.round(roc_auc_score(ytest,m.predict_proba(xtest)[:,1]),4))\n",
+    "    print('----------------------------------------------------------')\n",
+    "    print('Confusion Matrix')\n",
+    "    print(confusion_matrix(p,ytest))\n",
+    "    print('----------------------------------------------------------')\n",
+    "    print('Classification Report')\n",
+    "    print(classification_report(p,ytest))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:30.408181Z",
+     "iopub.status.busy": "2021-07-05T16:36:30.407693Z",
+     "iopub.status.idle": "2021-07-05T16:36:30.412054Z",
+     "shell.execute_reply": "2021-07-05T16:36:30.411332Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:30.408148Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "#Creating a list of models which will be created one by one\n",
+    "models=[GaussianNB(),KNeighborsClassifier(),LogisticRegression(),DecisionTreeClassifier(),\n",
+    "        RandomForestClassifier(),AdaBoostClassifier(),GradientBoostingClassifier(),XGBClassifier(verbosity=0)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:30.858989Z",
+     "iopub.status.busy": "2021-07-05T16:36:30.858664Z",
+     "iopub.status.idle": "2021-07-05T16:36:30.864602Z",
+     "shell.execute_reply": "2021-07-05T16:36:30.863414Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:30.858961Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "#Creates and trains model from the models list\n",
+    "def createmodel(x,y):\n",
+    "    xtrain,xtest,ytrain,ytest=train_test_split(x,y,test_size=0.25,random_state=randomstate(x,y))\n",
+    "    for i in models:\n",
+    "        model=i\n",
+    "        model.fit(xtrain,ytrain)\n",
+    "        p=model.predict(xtest)\n",
+    "        score=cross_val_score(model,x,y,cv=10)\n",
+    "        performance(p,ytest,model,xtest,score) "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:36:32.968371Z",
+     "iopub.status.busy": "2021-07-05T16:36:32.968055Z",
+     "iopub.status.idle": "2021-07-05T16:40:42.188105Z",
+     "shell.execute_reply": "2021-07-05T16:40:42.187002Z",
+     "shell.execute_reply.started": "2021-07-05T16:36:32.968344Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "createmodel(x,y)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Random Forest, Gradient Boost, Xtreme Gradient Boost give us the best performance, so we further try hyperparameter tuning on them"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Hyperparameter Tuning"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:40:59.299177Z",
+     "iopub.status.busy": "2021-07-05T16:40:59.298762Z",
+     "iopub.status.idle": "2021-07-05T16:40:59.303254Z",
+     "shell.execute_reply": "2021-07-05T16:40:59.301801Z",
+     "shell.execute_reply.started": "2021-07-05T16:40:59.299142Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "from sklearn.model_selection import GridSearchCV"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:41:00.699099Z",
+     "iopub.status.busy": "2021-07-05T16:41:00.69875Z",
+     "iopub.status.idle": "2021-07-05T16:41:54.416094Z",
+     "shell.execute_reply": "2021-07-05T16:41:54.415022Z",
+     "shell.execute_reply.started": "2021-07-05T16:41:00.699069Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "xtrain,xtest,ytrain,ytest=train_test_split(x,y,test_size=0.25,random_state=randomstate(x,y))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "##### Random Forest"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:41:54.418493Z",
+     "iopub.status.busy": "2021-07-05T16:41:54.41775Z",
+     "iopub.status.idle": "2021-07-05T16:41:54.424355Z",
+     "shell.execute_reply": "2021-07-05T16:41:54.423418Z",
+     "shell.execute_reply.started": "2021-07-05T16:41:54.418443Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "params={'n_estimators':[100,300,500],\n",
+    "            'criterion':['gini','entropty'],\n",
+    "            'max_depth':[None,1,2,3,4,5,6,7,8,9,10],\n",
+    "           'max_features':['int','float','auto','log2']}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:41:54.427242Z",
+     "iopub.status.busy": "2021-07-05T16:41:54.426517Z",
+     "iopub.status.idle": "2021-07-05T16:41:54.437322Z",
+     "shell.execute_reply": "2021-07-05T16:41:54.435883Z",
+     "shell.execute_reply.started": "2021-07-05T16:41:54.42719Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "g=GridSearchCV(RandomForestClassifier(),params,cv=10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T16:41:54.439968Z",
+     "iopub.status.busy": "2021-07-05T16:41:54.439512Z",
+     "iopub.status.idle": "2021-07-05T17:42:07.320823Z",
+     "shell.execute_reply": "2021-07-05T17:42:07.32016Z",
+     "shell.execute_reply.started": "2021-07-05T16:41:54.439918Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "g.fit(xtrain,ytrain)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T17:42:07.322587Z",
+     "iopub.status.busy": "2021-07-05T17:42:07.322161Z",
+     "iopub.status.idle": "2021-07-05T17:42:07.328675Z",
+     "shell.execute_reply": "2021-07-05T17:42:07.327673Z",
+     "shell.execute_reply.started": "2021-07-05T17:42:07.322557Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "print(g.best_params_)\n",
+    "print(g.best_estimator_)\n",
+    "print(g.best_score_)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T17:52:25.11716Z",
+     "iopub.status.busy": "2021-07-05T17:52:25.116788Z",
+     "iopub.status.idle": "2021-07-05T17:57:17.067821Z",
+     "shell.execute_reply": "2021-07-05T17:57:17.066617Z",
+     "shell.execute_reply.started": "2021-07-05T17:52:25.117125Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "m=RandomForestClassifier(max_features='log2', n_estimators=500)\n",
+    "m.fit(xtrain,ytrain)\n",
+    "p=m.predict(xtest)\n",
+    "score=cross_val_score(m,x,y,cv=10)\n",
+    "performance(p,ytest,m,xtest,score)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "##### Gradient Boost"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T17:58:51.117177Z",
+     "iopub.status.busy": "2021-07-05T17:58:51.116818Z",
+     "iopub.status.idle": "2021-07-05T17:58:51.120447Z",
+     "shell.execute_reply": "2021-07-05T17:58:51.119819Z",
+     "shell.execute_reply.started": "2021-07-05T17:58:51.117142Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "from sklearn.model_selection import RandomizedSearchCV"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T17:58:52.395874Z",
+     "iopub.status.busy": "2021-07-05T17:58:52.395308Z",
+     "iopub.status.idle": "2021-07-05T17:58:52.40048Z",
+     "shell.execute_reply": "2021-07-05T17:58:52.39993Z",
+     "shell.execute_reply.started": "2021-07-05T17:58:52.395815Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "params={'n_estimators':[100,300,500],\n",
+    "      'learning_rate':[0.001,0.01,0.10,],\n",
+    "      'subsample':[0.5,1],\n",
+    "      'max_depth':[1,2,3,4,5,6,7,8,9,10,None]}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T17:58:53.916639Z",
+     "iopub.status.busy": "2021-07-05T17:58:53.916103Z",
+     "iopub.status.idle": "2021-07-05T17:58:53.921326Z",
+     "shell.execute_reply": "2021-07-05T17:58:53.920478Z",
+     "shell.execute_reply.started": "2021-07-05T17:58:53.916594Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "g=RandomizedSearchCV(GradientBoostingClassifier(),params,cv=10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T17:58:54.635604Z",
+     "iopub.status.busy": "2021-07-05T17:58:54.635275Z",
+     "iopub.status.idle": "2021-07-05T18:53:06.235616Z",
+     "shell.execute_reply": "2021-07-05T18:53:06.234679Z",
+     "shell.execute_reply.started": "2021-07-05T17:58:54.635573Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "g.fit(xtrain,ytrain)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T18:53:06.237909Z",
+     "iopub.status.busy": "2021-07-05T18:53:06.23746Z",
+     "iopub.status.idle": "2021-07-05T18:53:06.245608Z",
+     "shell.execute_reply": "2021-07-05T18:53:06.244355Z",
+     "shell.execute_reply.started": "2021-07-05T18:53:06.237847Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "print(g.best_params_)\n",
+    "print(g.best_estimator_)\n",
+    "print(g.best_score_)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T18:55:39.112709Z",
+     "iopub.status.busy": "2021-07-05T18:55:39.112375Z",
+     "iopub.status.idle": "2021-07-05T18:57:15.885788Z",
+     "shell.execute_reply": "2021-07-05T18:57:15.884695Z",
+     "shell.execute_reply.started": "2021-07-05T18:55:39.112672Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "m=GradientBoostingClassifier(max_depth=8, subsample=0.5)\n",
+    "m.fit(xtrain,ytrain)\n",
+    "p=m.predict(xtest)\n",
+    "score=cross_val_score(m,x,y,cv=10)\n",
+    "performance(p,ytest,m,xtest,score)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "##### Xtreme Gradient Boost"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T19:02:31.373415Z",
+     "iopub.status.busy": "2021-07-05T19:02:31.373068Z",
+     "iopub.status.idle": "2021-07-05T19:02:31.378382Z",
+     "shell.execute_reply": "2021-07-05T19:02:31.3774Z",
+     "shell.execute_reply.started": "2021-07-05T19:02:31.373382Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "params={\n",
+    " \"learning_rate\"    : [0.01,0.05, 0.10, 0.15, ] ,\n",
+    " \"max_depth\"        : [ 3, 4, 5, 6, 8, 10, 12, 15],\n",
+    " \"min_child_weight\" : [ 1, 3, 5, 7 ],\n",
+    " \"gamma\"            : [ 0.0, 0.1, 0.2 , 0.3, 0.4 ],\n",
+    " \"colsample_bytree\" : [ 0.3, 0.4, 0.5 , 0.7 ]\n",
+    "    }"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T19:02:31.89253Z",
+     "iopub.status.busy": "2021-07-05T19:02:31.892195Z",
+     "iopub.status.idle": "2021-07-05T19:02:31.897111Z",
+     "shell.execute_reply": "2021-07-05T19:02:31.895923Z",
+     "shell.execute_reply.started": "2021-07-05T19:02:31.892497Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "g=RandomizedSearchCV(XGBClassifier(),params,cv=10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T19:02:34.952368Z",
+     "iopub.status.busy": "2021-07-05T19:02:34.952049Z",
+     "iopub.status.idle": "2021-07-05T19:05:27.525806Z",
+     "shell.execute_reply": "2021-07-05T19:05:27.524878Z",
+     "shell.execute_reply.started": "2021-07-05T19:02:34.952334Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "g.fit(xtrain,ytrain)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T19:05:27.52811Z",
+     "iopub.status.busy": "2021-07-05T19:05:27.527419Z",
+     "iopub.status.idle": "2021-07-05T19:05:27.537509Z",
+     "shell.execute_reply": "2021-07-05T19:05:27.536404Z",
+     "shell.execute_reply.started": "2021-07-05T19:05:27.528065Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "print(g.best_params_)\n",
+    "print(g.best_estimator_)\n",
+    "print(g.best_score_)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T19:08:13.572829Z",
+     "iopub.status.busy": "2021-07-05T19:08:13.572484Z",
+     "iopub.status.idle": "2021-07-05T19:08:36.785989Z",
+     "shell.execute_reply": "2021-07-05T19:08:36.78487Z",
+     "shell.execute_reply.started": "2021-07-05T19:08:13.572798Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "m=XGBClassifier(colsample_bytree=0.3, gamma= 0.1, learning_rate= 0.15, max_depth= 10, min_child_weight= 5)\n",
+    "m.fit(xtrain,ytrain)\n",
+    "p=m.predict(xtest)\n",
+    "score=cross_val_score(m,x,y,cv=10)\n",
+    "performance(p,ytest,m,xtest,score)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We choose random forest as our final model because it gives the highest cross validation score as well as difference between its accuracy score and cross validation score is minimum."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Finalizing the model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T19:08:48.388688Z",
+     "iopub.status.busy": "2021-07-05T19:08:48.388368Z",
+     "iopub.status.idle": "2021-07-05T19:13:36.449561Z",
+     "shell.execute_reply": "2021-07-05T19:13:36.448834Z",
+     "shell.execute_reply.started": "2021-07-05T19:08:48.388661Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "model=RandomForestClassifier(max_features='log2', n_estimators=500)\n",
+    "model.fit(xtrain,ytrain)\n",
+    "p=model.predict(xtest)\n",
+    "score=cross_val_score(model,x,y,cv=10)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Evaluation Metrics"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T19:13:36.451684Z",
+     "iopub.status.busy": "2021-07-05T19:13:36.451289Z",
+     "iopub.status.idle": "2021-07-05T19:13:37.897673Z",
+     "shell.execute_reply": "2021-07-05T19:13:37.896873Z",
+     "shell.execute_reply.started": "2021-07-05T19:13:36.451642Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "performance(p,ytest,model,xtest,score)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T19:13:37.899851Z",
+     "iopub.status.busy": "2021-07-05T19:13:37.899473Z",
+     "iopub.status.idle": "2021-07-05T19:13:39.319284Z",
+     "shell.execute_reply": "2021-07-05T19:13:39.318358Z",
+     "shell.execute_reply.started": "2021-07-05T19:13:37.899802Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "fpred=pd.Series(model.predict_proba(xtest)[:,1])\n",
+    "fpr,tpr,threshold=roc_curve(ytest,fpred)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T19:13:39.321032Z",
+     "iopub.status.busy": "2021-07-05T19:13:39.32072Z",
+     "iopub.status.idle": "2021-07-05T19:13:39.469322Z",
+     "shell.execute_reply": "2021-07-05T19:13:39.468314Z",
+     "shell.execute_reply.started": "2021-07-05T19:13:39.320978Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "plt.plot(fpr,tpr,color='k',label='ROC')\n",
+    "plt.plot([0,1],[0,1],color='b',linestyle='--')\n",
+    "plt.xlabel('False Positive Rate')\n",
+    "plt.ylabel('True Positive Rate')\n",
+    "plt.title('ROC-AUC curve')\n",
+    "plt.legend()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Saving the model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-07-05T19:15:36.273422Z",
+     "iopub.status.busy": "2021-07-05T19:15:36.273091Z",
+     "iopub.status.idle": "2021-07-05T19:15:36.790047Z",
+     "shell.execute_reply": "2021-07-05T19:15:36.789222Z",
+     "shell.execute_reply.started": "2021-07-05T19:15:36.273393Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "import joblib\n",
+    "joblib.dump(model,'census_income.obj')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Fairness "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>age</th>\n",
+       "      <th>workclass</th>\n",
+       "      <th>fnlwgt</th>\n",
+       "      <th>education</th>\n",
+       "      <th>education.num</th>\n",
+       "      <th>marital.status</th>\n",
+       "      <th>occupation</th>\n",
+       "      <th>relationship</th>\n",
+       "      <th>race</th>\n",
+       "      <th>sex</th>\n",
+       "      <th>capital.gain</th>\n",
+       "      <th>capital.loss</th>\n",
+       "      <th>hours.per.week</th>\n",
+       "      <th>native.country</th>\n",
+       "      <th>income</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>-1.111495</td>\n",
+       "      <td>4.0000</td>\n",
+       "      <td>-1.814520</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>8.000000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.296771</td>\n",
+       "      <td>7.690495</td>\n",
+       "      <td>40</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>-1.576984</td>\n",
+       "      <td>0.0000</td>\n",
+       "      <td>-0.680310</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>7</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.296771</td>\n",
+       "      <td>7.690495</td>\n",
+       "      <td>40</td>\n",
+       "      <td>35.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>-0.706882</td>\n",
+       "      <td>6.0000</td>\n",
+       "      <td>0.424877</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>10</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>14.000000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-0.296771</td>\n",
+       "      <td>7.690495</td>\n",
+       "      <td>40</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1.391427</td>\n",
+       "      <td>4.0000</td>\n",
+       "      <td>0.500601</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>12.000000</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.296771</td>\n",
+       "      <td>7.690495</td>\n",
+       "      <td>30</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>-1.111495</td>\n",
+       "      <td>4.0000</td>\n",
+       "      <td>-1.087030</td>\n",
+       "      <td>11.0</td>\n",
+       "      <td>9</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>12.000000</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.296771</td>\n",
+       "      <td>7.690495</td>\n",
+       "      <td>32</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46843</th>\n",
+       "      <td>0.792777</td>\n",
+       "      <td>5.0000</td>\n",
+       "      <td>-1.213544</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>10</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>4.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>3.369626</td>\n",
+       "      <td>-0.130031</td>\n",
+       "      <td>50</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46844</th>\n",
+       "      <td>0.351664</td>\n",
+       "      <td>4.0000</td>\n",
+       "      <td>0.527037</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>13</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>10.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-0.296771</td>\n",
+       "      <td>-0.130031</td>\n",
+       "      <td>60</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46845</th>\n",
+       "      <td>0.952576</td>\n",
+       "      <td>4.0000</td>\n",
+       "      <td>0.530354</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>12</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>3.966126</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>-0.296771</td>\n",
+       "      <td>-0.130031</td>\n",
+       "      <td>44</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46846</th>\n",
+       "      <td>0.962675</td>\n",
+       "      <td>4.6962</td>\n",
+       "      <td>-0.712134</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>10</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>10.000000</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>-0.296771</td>\n",
+       "      <td>-0.130031</td>\n",
+       "      <td>40</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46847</th>\n",
+       "      <td>1.660793</td>\n",
+       "      <td>0.0000</td>\n",
+       "      <td>0.260739</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>13</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>3.369631</td>\n",
+       "      <td>-0.130031</td>\n",
+       "      <td>12</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>46848 rows × 15 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            age  workclass    fnlwgt  education  education.num  \\\n",
+       "0     -1.111495     4.0000 -1.814520       11.0              9   \n",
+       "1     -1.576984     0.0000 -0.680310        1.0              7   \n",
+       "2     -0.706882     6.0000  0.424877       15.0             10   \n",
+       "3      1.391427     4.0000  0.500601       11.0              9   \n",
+       "4     -1.111495     4.0000 -1.087030       11.0              9   \n",
+       "...         ...        ...       ...        ...            ...   \n",
+       "46843  0.792777     5.0000 -1.213544       15.0             10   \n",
+       "46844  0.351664     4.0000  0.527037        9.0             13   \n",
+       "46845  0.952576     4.0000  0.530354        7.0             12   \n",
+       "46846  0.962675     4.6962 -0.712134       15.0             10   \n",
+       "46847  1.660793     0.0000  0.260739        9.0             13   \n",
+       "\n",
+       "       marital.status  occupation  relationship  race  sex  capital.gain  \\\n",
+       "0                 4.0    8.000000           1.0   4.0  0.0     -0.296771   \n",
+       "1                 3.0    0.000000           3.0   1.0  0.0     -0.296771   \n",
+       "2                 4.0   14.000000           1.0   4.0  1.0     -0.296771   \n",
+       "3                 0.0   12.000000           4.0   4.0  0.0     -0.296771   \n",
+       "4                 4.0   12.000000           3.0   4.0  0.0     -0.296771   \n",
+       "...               ...         ...           ...   ...  ...           ...   \n",
+       "46843             2.0    4.000000           0.0   4.0  1.0      3.369626   \n",
+       "46844             2.0   10.000000           0.0   4.0  1.0     -0.296771   \n",
+       "46845             2.0    3.966126           0.0   4.0  1.0     -0.296771   \n",
+       "46846             2.0   10.000000           5.0   4.0  0.0     -0.296771   \n",
+       "46847             2.0    0.000000           0.0   4.0  1.0      3.369631   \n",
+       "\n",
+       "       capital.loss  hours.per.week  native.country  income  \n",
+       "0          7.690495              40            39.0       0  \n",
+       "1          7.690495              40            35.0       0  \n",
+       "2          7.690495              40            39.0       0  \n",
+       "3          7.690495              30            39.0       0  \n",
+       "4          7.690495              32            39.0       0  \n",
+       "...             ...             ...             ...     ...  \n",
+       "46843     -0.130031              50            39.0       1  \n",
+       "46844     -0.130031              60            39.0       1  \n",
+       "46845     -0.130031              44            39.0       1  \n",
+       "46846     -0.130031              40            39.0       1  \n",
+       "46847     -0.130031              12            39.0       1  \n",
+       "\n",
+       "[46848 rows x 15 columns]"
+      ]
+     },
+     "execution_count": 66,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x['income'] = y\n",
+    "x"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# This DataFrame is created to stock differents models and fair metrics that we produce in this notebook\n",
+    "algo_metrics = pd.DataFrame(columns=['model', 'fair_metrics', 'prediction', 'probs'])\n",
+    "\n",
+    "def add_to_df_algo_metrics(algo_metrics, model, fair_metrics, preds, probs, name):\n",
+    "    return algo_metrics.append(pd.DataFrame(data=[[model, fair_metrics, preds, probs]], columns=['model', 'fair_metrics', 'prediction', 'probs'], index=[name]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def fair_metrics(dataset, pred, pred_is_dataset=False):\n",
+    "    if pred_is_dataset:\n",
+    "        dataset_pred = pred\n",
+    "    else:\n",
+    "        dataset_pred = dataset.copy()\n",
+    "        dataset_pred.labels = pred\n",
+    "    \n",
+    "    cols = ['statistical_parity_difference', 'equal_opportunity_difference', 'average_abs_odds_difference',  'disparate_impact', 'theil_index']\n",
+    "    obj_fairness = [[0,0,0,1,0]]\n",
+    "    \n",
+    "    fair_metrics = pd.DataFrame(data=obj_fairness, index=['objective'], columns=cols)\n",
+    "    \n",
+    "    for attr in dataset_pred.protected_attribute_names:\n",
+    "        idx = dataset_pred.protected_attribute_names.index(attr)\n",
+    "        privileged_groups =  [{attr:dataset_pred.privileged_protected_attributes[idx][0]}] \n",
+    "        unprivileged_groups = [{attr:dataset_pred.unprivileged_protected_attributes[idx][0]}] \n",
+    "        \n",
+    "        classified_metric = ClassificationMetric(dataset, \n",
+    "                                                     dataset_pred,\n",
+    "                                                     unprivileged_groups=unprivileged_groups,\n",
+    "                                                     privileged_groups=privileged_groups)\n",
+    "\n",
+    "        metric_pred = BinaryLabelDatasetMetric(dataset_pred,\n",
+    "                                                     unprivileged_groups=unprivileged_groups,\n",
+    "                                                     privileged_groups=privileged_groups)\n",
+    "\n",
+    "        acc = classified_metric.accuracy()\n",
+    "\n",
+    "        row = pd.DataFrame([[metric_pred.mean_difference(),\n",
+    "                                classified_metric.equal_opportunity_difference(),\n",
+    "                                classified_metric.average_abs_odds_difference(),\n",
+    "                                metric_pred.disparate_impact(),\n",
+    "                                classified_metric.theil_index()]],\n",
+    "                           columns  = cols,\n",
+    "                           index = [attr]\n",
+    "                          )\n",
+    "        fair_metrics = fair_metrics.append(row)    \n",
+    "    \n",
+    "    fair_metrics = fair_metrics.replace([-np.inf, np.inf], 2)\n",
+    "        \n",
+    "    return fair_metrics\n",
+    "\n",
+    "def plot_fair_metrics(fair_metrics):\n",
+    "    fig, ax = plt.subplots(figsize=(20,4), ncols=5, nrows=1)\n",
+    "\n",
+    "    plt.subplots_adjust(\n",
+    "        left    =  0.125, \n",
+    "        bottom  =  0.1, \n",
+    "        right   =  0.9, \n",
+    "        top     =  0.9, \n",
+    "        wspace  =  .5, \n",
+    "        hspace  =  1.1\n",
+    "    )\n",
+    "\n",
+    "    y_title_margin = 1.2\n",
+    "\n",
+    "    plt.suptitle(\"Fairness metrics\", y = 1.09, fontsize=20)\n",
+    "    sns.set(style=\"dark\")\n",
+    "\n",
+    "    cols = fair_metrics.columns.values\n",
+    "    obj = fair_metrics.loc['objective']\n",
+    "    size_rect = [0.2,0.2,0.2,0.4,0.25]\n",
+    "    rect = [-0.1,-0.1,-0.1,0.8,0]\n",
+    "    bottom = [-1,-1,-1,0,0]\n",
+    "    top = [1,1,1,2,1]\n",
+    "    bound = [[-0.1,0.1],[-0.1,0.1],[-0.1,0.1],[0.8,1.2],[0,0.25]]\n",
+    "\n",
+    "    display(Markdown(\"### Check bias metrics :\"))\n",
+    "    display(Markdown(\"A model can be considered bias if just one of these five metrics show that this model is biased.\"))\n",
+    "    for attr in fair_metrics.index[1:len(fair_metrics)].values:\n",
+    "        display(Markdown(\"#### For the %s attribute :\"%attr))\n",
+    "        check = [bound[i][0] < fair_metrics.loc[attr][i] < bound[i][1] for i in range(0,5)]\n",
+    "        display(Markdown(\"With default thresholds, bias against unprivileged group detected in **%d** out of 5 metrics\"%(5 - sum(check))))\n",
+    "\n",
+    "    for i in range(0,5):\n",
+    "        plt.subplot(1, 5, i+1)\n",
+    "        ax = sns.barplot(x=fair_metrics.index[1:len(fair_metrics)], y=fair_metrics.iloc[1:len(fair_metrics)][cols[i]])\n",
+    "        \n",
+    "        for j in range(0,len(fair_metrics)-1):\n",
+    "            a, val = ax.patches[j], fair_metrics.iloc[j+1][cols[i]]\n",
+    "            marg = -0.2 if val < 0 else 0.1\n",
+    "            ax.text(a.get_x()+a.get_width()/5, a.get_y()+a.get_height()+marg, round(val, 3), fontsize=15,color='black')\n",
+    "\n",
+    "        plt.ylim(bottom[i], top[i])\n",
+    "        plt.setp(ax.patches, linewidth=0)\n",
+    "        ax.add_patch(patches.Rectangle((-5,rect[i]), 10, size_rect[i], alpha=0.3, facecolor=\"green\", linewidth=1, linestyle='solid'))\n",
+    "        plt.axhline(obj[i], color='black', alpha=0.3)\n",
+    "        plt.title(cols[i])\n",
+    "        ax.set_ylabel('')    \n",
+    "        ax.set_xlabel('')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def get_fair_metrics_and_plot(data, model, plot=False, model_aif=False):\n",
+    "    pred = model.predict(data).labels if model_aif else model.predict(data.features)\n",
+    "    # fair_metrics function available in the metrics.py file\n",
+    "    fair = fair_metrics(data, pred)\n",
+    "\n",
+    "    if plot:\n",
+    "        # plot_fair_metrics function available in the visualisations.py file\n",
+    "        # The visualisation of this function is inspired by the dashboard on the demo of IBM aif360 \n",
+    "        plot_fair_metrics(fair)\n",
+    "        display(fair)\n",
+    "    \n",
+    "    return fair"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#print(X)\n",
+    "\n",
+    "\n",
+    "#combine_final = [train_df, test_df]\n",
+    "#result = pd.concat(combine_final)\n",
+    "#print(result.ifany())\n",
+    "#print(result)\n",
+    "privileged_groups = [{'sex': 1}]\n",
+    "unprivileged_groups = [{'sex': 0}]\n",
+    "dataset_orig = StandardDataset(x,\n",
+    "                                  label_name='income',\n",
+    "                                  protected_attribute_names=['sex'],\n",
+    "                                  favorable_classes=[1],\n",
+    "                                  privileged_classes=[[1]])\n",
+    "\n",
+    "#metric_orig_train = BinaryLabelDatasetMetric(dataset_orig, \n",
+    "#                                             unprivileged_groups=unprivileged_groups,\n",
+    "#                                             privileged_groups=privileged_groups)\n",
+    "#display(Markdown(\"#### Original training dataset\"))\n",
+    "#print(\"Difference in mean outcomes between unprivileged and privileged groups = %f\" % metric_orig_train.mean_difference())\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/markdown": [
+       "#### Original training dataset"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Difference in mean outcomes between unprivileged and privileged groups = -0.343167\n"
+     ]
+    }
+   ],
+   "source": [
+    "metric_orig_train = BinaryLabelDatasetMetric(dataset_orig, \n",
+    "                                             unprivileged_groups=unprivileged_groups,\n",
+    "                                             privileged_groups=privileged_groups)\n",
+    "display(Markdown(\"#### Original training dataset\"))\n",
+    "print(\"Difference in mean outcomes between unprivileged and privileged groups = %f\" % metric_orig_train.mean_difference())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import ipynbname\n",
+    "nb_fname = ipynbname.name()\n",
+    "nb_path = ipynbname.path()\n",
+    "\n",
+    "from sklearn.ensemble import GradientBoostingClassifier\n",
+    "import pickle\n",
+    "\n",
+    "data_orig_train, data_orig_test = dataset_orig.split([0.7], shuffle=True)\n",
+    "X_train = data_orig_train.features\n",
+    "y_train = data_orig_train.labels.ravel()\n",
+    "\n",
+    "X_test = data_orig_test.features\n",
+    "y_test = data_orig_test.labels.ravel()\n",
+    "num_estimators = 100\n",
+    "\n",
+    "model = GradientBoostingClassifier(n_estimators= 1, max_depth=8, subsample=0.5)\n",
+    "\n",
+    "mdl = model.fit(X_train, y_train)\n",
+    "with open('../../Results/GBC/' + nb_fname + '.pkl', 'wb') as f:\n",
+    "        pickle.dump(mdl, f)\n",
+    "\n",
+    "with open('../../Results/GBC/' + nb_fname + '_Train' + '.pkl', 'wb') as f:\n",
+    "    pickle.dump(data_orig_train, f) \n",
+    "    \n",
+    "with open('../../Results/GBC/' + nb_fname + '_Test' + '.pkl', 'wb') as f:\n",
+    "    pickle.dump(data_orig_test, f) "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from csv import writer\n",
+    "from sklearn.metrics import accuracy_score, f1_score\n",
+    "\n",
+    "final_metrics = []\n",
+    "accuracy = []\n",
+    "f1= []\n",
+    "\n",
+    "for i in range(1,num_estimators+1):\n",
+    "    \n",
+    "    model = GradientBoostingClassifier(n_estimators= i, max_depth=8, subsample=0.5)\n",
+    "    mdl = model.fit(X_train, y_train)\n",
+    "    yy = mdl.predict(X_test)\n",
+    "    accuracy.append(accuracy_score(y_test, yy))\n",
+    "    f1.append(f1_score(y_test, yy))\n",
+    "    fair = get_fair_metrics_and_plot(data_orig_test, mdl)                           \n",
+    "    fair_list = fair.iloc[1].tolist()\n",
+    "    #fair_list.insert(0, i)\n",
+    "    final_metrics.append(fair_list)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>classifier</th>\n",
+       "      <th>T0</th>\n",
+       "      <th>T1</th>\n",
+       "      <th>T2</th>\n",
+       "      <th>T3</th>\n",
+       "      <th>T4</th>\n",
+       "      <th>T5</th>\n",
+       "      <th>T6</th>\n",
+       "      <th>T7</th>\n",
+       "      <th>T8</th>\n",
+       "      <th>...</th>\n",
+       "      <th>T90</th>\n",
+       "      <th>T91</th>\n",
+       "      <th>T92</th>\n",
+       "      <th>T93</th>\n",
+       "      <th>T94</th>\n",
+       "      <th>T95</th>\n",
+       "      <th>T96</th>\n",
+       "      <th>T97</th>\n",
+       "      <th>T98</th>\n",
+       "      <th>T99</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>accuracy</th>\n",
+       "      <td>0.904731</td>\n",
+       "      <td>0.845678</td>\n",
+       "      <td>0.851014</td>\n",
+       "      <td>0.856421</td>\n",
+       "      <td>0.854287</td>\n",
+       "      <td>0.860334</td>\n",
+       "      <td>0.858769</td>\n",
+       "      <td>0.862113</td>\n",
+       "      <td>0.864105</td>\n",
+       "      <td>0.863180</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.901743</td>\n",
+       "      <td>0.903664</td>\n",
+       "      <td>0.902170</td>\n",
+       "      <td>0.902668</td>\n",
+       "      <td>0.900178</td>\n",
+       "      <td>0.902028</td>\n",
+       "      <td>0.901459</td>\n",
+       "      <td>0.901032</td>\n",
+       "      <td>0.901885</td>\n",
+       "      <td>0.904731</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>f1</th>\n",
+       "      <td>0.905737</td>\n",
+       "      <td>0.852218</td>\n",
+       "      <td>0.857995</td>\n",
+       "      <td>0.862083</td>\n",
+       "      <td>0.861284</td>\n",
+       "      <td>0.865576</td>\n",
+       "      <td>0.865360</td>\n",
+       "      <td>0.867984</td>\n",
+       "      <td>0.870315</td>\n",
+       "      <td>0.869477</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.902958</td>\n",
+       "      <td>0.904836</td>\n",
+       "      <td>0.903543</td>\n",
+       "      <td>0.904108</td>\n",
+       "      <td>0.901620</td>\n",
+       "      <td>0.903646</td>\n",
+       "      <td>0.902936</td>\n",
+       "      <td>0.902311</td>\n",
+       "      <td>0.903058</td>\n",
+       "      <td>0.905737</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>statistical_parity_difference</th>\n",
+       "      <td>-0.377308</td>\n",
+       "      <td>-0.403577</td>\n",
+       "      <td>-0.415459</td>\n",
+       "      <td>-0.408686</td>\n",
+       "      <td>-0.427396</td>\n",
+       "      <td>-0.402541</td>\n",
+       "      <td>-0.419832</td>\n",
+       "      <td>-0.414258</td>\n",
+       "      <td>-0.410635</td>\n",
+       "      <td>-0.420139</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.377972</td>\n",
+       "      <td>-0.379855</td>\n",
+       "      <td>-0.378719</td>\n",
+       "      <td>-0.379142</td>\n",
+       "      <td>-0.375711</td>\n",
+       "      <td>-0.378287</td>\n",
+       "      <td>-0.379437</td>\n",
+       "      <td>-0.376004</td>\n",
+       "      <td>-0.376804</td>\n",
+       "      <td>-0.377308</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>equal_opportunity_difference</th>\n",
+       "      <td>-0.089967</td>\n",
+       "      <td>-0.086682</td>\n",
+       "      <td>-0.104883</td>\n",
+       "      <td>-0.097388</td>\n",
+       "      <td>-0.121729</td>\n",
+       "      <td>-0.093021</td>\n",
+       "      <td>-0.109395</td>\n",
+       "      <td>-0.111907</td>\n",
+       "      <td>-0.099431</td>\n",
+       "      <td>-0.120273</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.085884</td>\n",
+       "      <td>-0.085057</td>\n",
+       "      <td>-0.086927</td>\n",
+       "      <td>-0.087284</td>\n",
+       "      <td>-0.077248</td>\n",
+       "      <td>-0.083401</td>\n",
+       "      <td>-0.083372</td>\n",
+       "      <td>-0.086898</td>\n",
+       "      <td>-0.079774</td>\n",
+       "      <td>-0.089967</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>average_abs_odds_difference</th>\n",
+       "      <td>0.108318</td>\n",
+       "      <td>0.158102</td>\n",
+       "      <td>0.171056</td>\n",
+       "      <td>0.160802</td>\n",
+       "      <td>0.183259</td>\n",
+       "      <td>0.152251</td>\n",
+       "      <td>0.171325</td>\n",
+       "      <td>0.166208</td>\n",
+       "      <td>0.158728</td>\n",
+       "      <td>0.172592</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.109316</td>\n",
+       "      <td>0.109565</td>\n",
+       "      <td>0.109980</td>\n",
+       "      <td>0.110090</td>\n",
+       "      <td>0.105910</td>\n",
+       "      <td>0.108618</td>\n",
+       "      <td>0.109893</td>\n",
+       "      <td>0.108465</td>\n",
+       "      <td>0.106698</td>\n",
+       "      <td>0.108318</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>disparate_impact</th>\n",
+       "      <td>-1.001039</td>\n",
+       "      <td>-0.992257</td>\n",
+       "      <td>-1.028232</td>\n",
+       "      <td>-1.027109</td>\n",
+       "      <td>-1.067466</td>\n",
+       "      <td>-1.008828</td>\n",
+       "      <td>-1.043666</td>\n",
+       "      <td>-1.038214</td>\n",
+       "      <td>-1.015336</td>\n",
+       "      <td>-1.048952</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.998111</td>\n",
+       "      <td>-1.006112</td>\n",
+       "      <td>-0.996150</td>\n",
+       "      <td>-0.995257</td>\n",
+       "      <td>-0.983227</td>\n",
+       "      <td>-0.986724</td>\n",
+       "      <td>-0.995748</td>\n",
+       "      <td>-0.989233</td>\n",
+       "      <td>-0.995355</td>\n",
+       "      <td>-1.001039</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>theil_index</th>\n",
+       "      <td>0.061961</td>\n",
+       "      <td>0.088417</td>\n",
+       "      <td>0.082828</td>\n",
+       "      <td>0.082610</td>\n",
+       "      <td>0.080135</td>\n",
+       "      <td>0.080851</td>\n",
+       "      <td>0.077794</td>\n",
+       "      <td>0.077422</td>\n",
+       "      <td>0.074705</td>\n",
+       "      <td>0.075171</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.063311</td>\n",
+       "      <td>0.062077</td>\n",
+       "      <td>0.062374</td>\n",
+       "      <td>0.061738</td>\n",
+       "      <td>0.063573</td>\n",
+       "      <td>0.061502</td>\n",
+       "      <td>0.062483</td>\n",
+       "      <td>0.063583</td>\n",
+       "      <td>0.063375</td>\n",
+       "      <td>0.061961</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>7 rows × 101 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                               classifier        T0        T1        T2  \\\n",
+       "accuracy                         0.904731  0.845678  0.851014  0.856421   \n",
+       "f1                               0.905737  0.852218  0.857995  0.862083   \n",
+       "statistical_parity_difference   -0.377308 -0.403577 -0.415459 -0.408686   \n",
+       "equal_opportunity_difference    -0.089967 -0.086682 -0.104883 -0.097388   \n",
+       "average_abs_odds_difference      0.108318  0.158102  0.171056  0.160802   \n",
+       "disparate_impact                -1.001039 -0.992257 -1.028232 -1.027109   \n",
+       "theil_index                      0.061961  0.088417  0.082828  0.082610   \n",
+       "\n",
+       "                                     T3        T4        T5        T6  \\\n",
+       "accuracy                       0.854287  0.860334  0.858769  0.862113   \n",
+       "f1                             0.861284  0.865576  0.865360  0.867984   \n",
+       "statistical_parity_difference -0.427396 -0.402541 -0.419832 -0.414258   \n",
+       "equal_opportunity_difference  -0.121729 -0.093021 -0.109395 -0.111907   \n",
+       "average_abs_odds_difference    0.183259  0.152251  0.171325  0.166208   \n",
+       "disparate_impact              -1.067466 -1.008828 -1.043666 -1.038214   \n",
+       "theil_index                    0.080135  0.080851  0.077794  0.077422   \n",
+       "\n",
+       "                                     T7        T8  ...       T90       T91  \\\n",
+       "accuracy                       0.864105  0.863180  ...  0.901743  0.903664   \n",
+       "f1                             0.870315  0.869477  ...  0.902958  0.904836   \n",
+       "statistical_parity_difference -0.410635 -0.420139  ... -0.377972 -0.379855   \n",
+       "equal_opportunity_difference  -0.099431 -0.120273  ... -0.085884 -0.085057   \n",
+       "average_abs_odds_difference    0.158728  0.172592  ...  0.109316  0.109565   \n",
+       "disparate_impact              -1.015336 -1.048952  ... -0.998111 -1.006112   \n",
+       "theil_index                    0.074705  0.075171  ...  0.063311  0.062077   \n",
+       "\n",
+       "                                    T92       T93       T94       T95  \\\n",
+       "accuracy                       0.902170  0.902668  0.900178  0.902028   \n",
+       "f1                             0.903543  0.904108  0.901620  0.903646   \n",
+       "statistical_parity_difference -0.378719 -0.379142 -0.375711 -0.378287   \n",
+       "equal_opportunity_difference  -0.086927 -0.087284 -0.077248 -0.083401   \n",
+       "average_abs_odds_difference    0.109980  0.110090  0.105910  0.108618   \n",
+       "disparate_impact              -0.996150 -0.995257 -0.983227 -0.986724   \n",
+       "theil_index                    0.062374  0.061738  0.063573  0.061502   \n",
+       "\n",
+       "                                    T96       T97       T98       T99  \n",
+       "accuracy                       0.901459  0.901032  0.901885  0.904731  \n",
+       "f1                             0.902936  0.902311  0.903058  0.905737  \n",
+       "statistical_parity_difference -0.379437 -0.376004 -0.376804 -0.377308  \n",
+       "equal_opportunity_difference  -0.083372 -0.086898 -0.079774 -0.089967  \n",
+       "average_abs_odds_difference    0.109893  0.108465  0.106698  0.108318  \n",
+       "disparate_impact              -0.995748 -0.989233 -0.995355 -1.001039  \n",
+       "theil_index                    0.062483  0.063583  0.063375  0.061961  \n",
+       "\n",
+       "[7 rows x 101 columns]"
+      ]
+     },
+     "execution_count": 74,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "final_result = pd.DataFrame(final_metrics)\n",
+    "#print(final_result)\n",
+    "final_result[3] = np.log(final_result[3])\n",
+    "final_result = final_result.transpose()\n",
+    "acc_f1 = pd.DataFrame(accuracy)\n",
+    "acc_f1['f1'] = f1\n",
+    "acc_f1 = pd.DataFrame(acc_f1).transpose()\n",
+    "acc = acc_f1.rename(index={0: 'accuracy', 1: 'f1'})\n",
+    "final_result = final_result.rename(index={0: 'statistical_parity_difference', 1: 'equal_opportunity_difference', 2: 'average_abs_odds_difference', 3: 'disparate_impact', 4: 'theil_index'})\n",
+    "final_result = pd.concat([acc,final_result])\n",
+    "final_result.columns = ['T' + str(col) for col in final_result.columns]\n",
+    "final_result.insert(0, \"classifier\", final_result['T' + str(num_estimators - 1)])   ##Add final metrics add the beginning of the df\n",
+    "final_result.to_csv('../../Results/GBC/' + nb_fname + '.csv')\n",
+    "final_result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}