{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "2c0ee7cb",
   "metadata": {},
   "outputs": [],
   "source": [
    "import gradio as gr\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from joblib import dump, load\n",
    "import os\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from sklearn.preprocessing import OneHotEncoder\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.metrics import accuracy_score, f1_score, confusion_matrix, RocCurveDisplay\n",
    "from sklearn.metrics import roc_curve,ConfusionMatrixDisplay, classification_report\n",
    "from sklearn.metrics import roc_auc_score, precision_score, recall_score\n",
    "from sklearn.metrics import PrecisionRecallDisplay, precision_recall_curve"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e3554bd1",
   "metadata": {},
   "outputs": [],
   "source": [
    "clf = load(\"RandomForestClassifier()20.joblib\")\n",
    "modelname = \"Random Forest\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ea2e94d7",
   "metadata": {},
   "outputs": [],
   "source": [
    "def encode(data, employement):\n",
    "    data['work_type'] = data['work_type'].replace({'Goverment job' : 'Govt_job',\n",
    "                                                   \"Never worked\" : \"Never_worked\",\n",
    "                                                   \"Self-employed\" : \"Self-employed\"})\n",
    "    data_jobs = ['Govt_job', 'Never_worked','Private','Self-employed']\n",
    "    for job in data_jobs:\n",
    "        if data['work_type'][0] == job:\n",
    "            data[job] = 1\n",
    "        else:\n",
    "            data[job] = 0\n",
    "    return data\n",
    "none_argument = lambda y: -999 if type(y) == list else y\n",
    "def replace_with_numeric(data):\n",
    "    data['ever_married'] = data['ever_married'].apply(none_argument)\n",
    "    data['ever_married'] = data['ever_married'].replace({'Yes' : 1 , 'No' : 0 })\n",
    "    \n",
    "    data['residence_type'] = data['residence_type'].replace({'Urban' : 1 , 'Rural' : 0, '' : -999})\n",
    "    \n",
    "    data['smoking_status'] = data['smoking_status'].apply(none_argument)\n",
    "    data['smoking_status'] = data['smoking_status'].replace({'Never smoked' : 0 , 'Formerly smoked' : 1, \n",
    "                                                            'Smokes': 2})\n",
    "    \n",
    "    data['gender'] = data['gender'].replace({'Male' : -1 , 'Female' : 1, 'Other' : 1, '' : -999})\n",
    "    \n",
    "    data['avg_glucose_level'] = data['avg_glucose_level'].apply(none_argument)\n",
    "    data['avg_glucose_level'] = data['avg_glucose_level'].replace({\"Normal (<100 mg/dL)\" : 0,\n",
    "                                                                   \"Prediabetes (<100, 125> mg/dL)\" : 1,\n",
    "                                                                   \"Diabetes (>125 mg/dL)\" : 2})\n",
    "    \n",
    "    data['bmi'] = data['bmi'].apply(none_argument)\n",
    "    data['bmi'] = data['bmi'].replace({\"Underweight (<18.4)\" : 0, \"Normal (<18.5, 24.9>)\" : 1,\n",
    "                                    \"Overweight (<25, 29.9>)\" : 2,\"Obese (>29.9)\" : 3})\n",
    "    return data\n",
    "def change_dtype(data):\n",
    "    data['age'].astype('int32')\n",
    "    data['Govt_job'].astype(pd.SparseDtype('int32', 0))\n",
    "    data['Never_worked'].astype(pd.SparseDtype(\"int32\", 0))\n",
    "    data['Private'].astype(pd.SparseDtype(\"int32\", 0))\n",
    "    data['Self-employed'].astype(pd.SparseDtype(\"int32\", 0))\n",
    "    data.info()\n",
    "    return data\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e0b0c67b",
   "metadata": {},
   "outputs": [],
   "source": [
    "def predict_stroke_from_one_patient(\n",
    "    gender, age, hypertension, heartDisease,\n",
    "    everMarried, residenceType, averageGlucoseLevel,\n",
    "    bmi, smokingStatus, employementType):\n",
    "    if type(bmi) == list:\n",
    "        d = {'gender': [gender], 'age': [age], 'hypertension': [hypertension], \n",
    "             'heart_disease': [heartDisease], 'ever_married': [everMarried],\n",
    "             'residence_type': [residenceType],'avg_glucose_level': [averageGlucoseLevel], \n",
    "             'bmi': [bmi], 'smoking_status': [smokingStatus], 'bmi_was_missing' : True, 'work_type': [employementType]}\n",
    "    else:\n",
    "        d = {'gender': [gender], 'age': [age], 'hypertension': [hypertension], \n",
    "             'heart_disease': [heartDisease], 'ever_married': [everMarried],\n",
    "             'residence_type': [residenceType],'avg_glucose_level': [averageGlucoseLevel], \n",
    "             'bmi': [bmi], 'smoking_status': [smokingStatus], 'bmi_was_missing' : False, 'work_type': [employementType]}  \n",
    "    data = pd.DataFrame(data=d)\n",
    "    data = pd.DataFrame(data=d)\n",
    "    encode(data, employementType)\n",
    "    data = data.drop(\"work_type\", axis = 1)\n",
    "    data = replace_with_numeric(data)\n",
    "    #data = change_dtype(data)\n",
    "    y_predicted = clf.predict(data)\n",
    "    if y_predicted == 1:\n",
    "        prediction = 'stroke'\n",
    "    else:\n",
    "        prediction = 'no stroke'\n",
    "    return prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "bfae7bf2",
   "metadata": {},
   "outputs": [],
   "source": [
    "demo2 = gr.Interface(predict_stroke_from_one_patient,\n",
    "                   [\n",
    "                       gr.Radio([\"Male\", \"Female\", \"Other\"]),\n",
    "                       gr.Slider(40, 90, value=40, step=1),\n",
    "                       gr.Checkbox(label=\"Hypertension\"),\n",
    "                       gr.Checkbox(label=\"Heart Disease\"),\n",
    "                       gr.Checkbox(label=\"Is/Was Married?\"),\n",
    "                       gr.Radio([\"Urban\", \"Rural\"]),\n",
    "                       gr.Dropdown([\"Normal (<100 mg/dL)\", \"Prediabetes (<100, 125> mg/dL)\",\n",
    "                                    \"Diabetes (>125 mg/dL)\"]),\n",
    "                       gr.Dropdown([\"Underweight (<18.4)\", \"Normal (<18.5, 24.9>)\",\n",
    "                                    \"Overweight (<25, 29.9>)\",\"Obese (>29.9)\"]),\n",
    "                       gr.Dropdown([\"Never smoked\", \"Formerly smoked\",\"Smokes\"]),\n",
    "                       gr.Dropdown([\"Goverment job\", \"Never worked\", \"Private\",\n",
    "                                    \"Self-employed\"])],\n",
    "                   outputs=\"label\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "58c61542",
   "metadata": {},
   "outputs": [],
   "source": [
    "def bmi(col):\n",
    "    if col <= 18.4: #Underweight\n",
    "        return 0\n",
    "    elif col >= 18.5 and col <= 24.9: #normal\n",
    "        return 1\n",
    "    elif col >= 25.0 and col <= 29.9: #Overweight (Pre-obese)\n",
    "        return 2\n",
    "    else: #obese\n",
    "        return 3\n",
    "def glucose(col):\n",
    "    if col >= 100 and col <= 125: #prediabetes\n",
    "        return 1\n",
    "    elif col < 100: #normal\n",
    "        return 0\n",
    "    else: # diabetes\n",
    "        return 2\n",
    "def smoking_status(col):\n",
    "    if col == 'never smoked':\n",
    "        return 0\n",
    "    elif col == 'formerly smoked':\n",
    "        return 1\n",
    "    elif col == 'smokes':\n",
    "        return 2\n",
    "    else:\n",
    "        return -999"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "112c59b1",
   "metadata": {},
   "outputs": [],
   "source": [
    "def fill_with_median(data):\n",
    "    bmi_num = data[[\"bmi\"]]\n",
    "    #MEDIAN OF BMI VALUES\n",
    "    bmi_median = bmi_num.median()\n",
    "    bmi_plus = bmi_num.copy()\n",
    "    bmi_plus['bmi'] = bmi_plus.isnull()\n",
    "    bmi_plus.columns = ['bmi_was_missing']\n",
    "    data = data.fillna(bmi_median)\n",
    "    data = data.join(bmi_plus)\n",
    "    return data\n",
    "def encode_1H(data):\n",
    "    cat_encoder = OneHotEncoder()\n",
    "    work_cat = data[[\"work_type\"]]\n",
    "    work_cat_1hot =pd.DataFrame.sparse.from_spmatrix(cat_encoder.fit_transform(work_cat))\n",
    "    work_cat_1hot.columns = ['Govt_job', 'Never_worked', 'Private', 'Self-employed', 'children']\n",
    "    work_cat_1hot = work_cat_1hot.astype(int)\n",
    "    data = data.join(work_cat_1hot)\n",
    "    data = data.drop(\"work_type\", axis = 1)\n",
    "    return data\n",
    "def replace_with_numeric(data):\n",
    "    data['age'] = data['age'].astype(int)\n",
    "    data['ever_married'] = data['ever_married'].replace({'Yes' : 1 , 'No' : 0 })\n",
    "    data['residence_type'] = data['residence_type'].replace({'Urban' : 1 , 'Rural' : 0 })\n",
    "    data.smoking_status = data.smoking_status.apply(smoking_status)\n",
    "    data['gender'] = data['gender'].replace({'Male' : -1 , 'Female' : 1 , 'Other': 1})\n",
    "    data.avg_glucose_level = data.avg_glucose_level.apply(glucose)\n",
    "    data.bmi = data.bmi.apply(bmi)\n",
    "    return data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "8c11a032",
   "metadata": {},
   "outputs": [],
   "source": [
    "def rf_feat_importance(df):\n",
    "    return pd.DataFrame({'Feature':df.columns,\n",
    "                         'Importance':clf.feature_importances_}).sort_values('Importance', ascending=False)\n",
    "def plot_importance(df):\n",
    "    fi = rf_feat_importance(model_data)\n",
    "\n",
    "    fig, ax = plt.subplots(1,1, figsize=(10, 8))\n",
    "\n",
    "    sns.barplot(data=fi,x='Importance',y='Feature',ax=ax)\n",
    "    for s in ['top', 'left', 'right']:\n",
    "        ax.spines[s].set_visible(False)\n",
    "    \n",
    "    fig.text(0.12,0.92,\"Feature Importance: \"+ modelname +\" Stroke Prediction\", fontsize=18, fontweight='bold', fontfamily='serif')\n",
    "    \n",
    "    plt.xlabel(\" \", fontsize=12, fontweight='light', fontfamily='serif',loc='left',y=-1.5)\n",
    "    plt.ylabel(\" \", fontsize=12, fontweight='light', fontfamily='serif')\n",
    "\n",
    "    import matplotlib.lines as lines\n",
    "    l1 = lines.Line2D([0.98, 0.98], [0, 1], transform=fig.transFigure, figure=fig,color='black',lw=0.2)\n",
    "    fig.lines.extend([l1])\n",
    "    return fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "bed16f25",
   "metadata": {},
   "outputs": [],
   "source": [
    "def predict_stroke_from_csv(file):\n",
    "   # print(file.name)\n",
    "    data = pd.read_csv(file)\n",
    "    data.columns = data.columns.str.lower()\n",
    "    if data.isna().any().any() == True:\n",
    "        print('Missing values detected. Filling with median of feature values')\n",
    "        data = fill_with_median(data)\n",
    "    data = encode_1H(data)\n",
    "    if data['age'].where(data['age'] < 40).any():\n",
    "        print(\"Patients younger than 40 years old detected. \" +\n",
    "              \"Diagnose of younger than 40 years old can be false\")\n",
    "              #\"Dropping the data about too young for model to predict stroke\")\n",
    "        #data = data.drop(data[data.age < 40].index)\n",
    "    data = data.drop(['children'],axis=1)\n",
    "    data = replace_with_numeric(data)\n",
    "    data = data.drop(['stroke'],axis=1)\n",
    "    model_data = data.drop(['id'],axis=1)\n",
    "    y_predicted = clf.predict(model_data)\n",
    "    y_predicted_proba = clf.predict_proba(model_data)\n",
    "    predictions = []\n",
    "    proba_predictions = []\n",
    "    i = 0\n",
    "    for y in y_predicted:\n",
    "        if y == 1:\n",
    "            predictions.append(data._get_value(i, 'id'))\n",
    "            proba_predictions.append(y_predicted_proba[i, 1].round(2))\n",
    "        i = i + 1\n",
    "    prob = pd.DataFrame({'ID': predictions, 'Probability of stroke': proba_predictions})\n",
    "    plot = plot_importance(df = model_data)\n",
    "    return prob, plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "2c773510",
   "metadata": {},
   "outputs": [],
   "source": [
    "with gr.Blocks() as demo3:\n",
    "    gr.Markdown(\n",
    "    \"\"\"\n",
    "    # Predict stroke fo multiple patients\n",
    "    Upload a CSV file with data about your patients to get IDs of patients at risk of stroke with probability > 50%\n",
    "    \"\"\")\n",
    "    filename = gr.File(file_types=[\".csv\"])\n",
    "    button = gr.Button(\"Zatwierdź\")\n",
    "    plot = gr.Plot(label=\"Plot\")\n",
    "    outputs = gr.Dataframe(row_count = (1, \"dynamic\"),\n",
    "                           col_count=(1, \"dynamic\"), label=\"Predictions\",\n",
    "                           headers=[\"ID\"])\n",
    "    button.click(fn=predict_stroke_from_csv, inputs=filename, outputs=[outputs, plot])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f069207c",
   "metadata": {},
   "outputs": [],
   "source": [
    "recallScore = load(\"recall.joblib\")\n",
    "recallDT = recallScore.loc[:, modelname]\n",
    "precisionScore = load(\"precision.joblib\")\n",
    "precisionDT = precisionScore.loc[:, modelname]\n",
    "accuracy = load(\"accuracy.joblib\")\n",
    "accuracyDT = accuracy.loc[:, modelname]\n",
    "score = {'Recall' : recallDT, 'Precision' : precisionDT, 'Accuracy' : accuracyDT}\n",
    "df = pd.DataFrame(score)\n",
    "df.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "50605954",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "learning = load(\"learning.joblib\")\n",
    "importance = load(\"importance.joblib\")\n",
    "matrixes = load(\"matrixes.joblib\")\n",
    "recCurve = load(\"recCurve.joblib\")\n",
    "roc = load(\"roc.joblib\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "9fc72d77",
   "metadata": {},
   "outputs": [],
   "source": [
    "with gr.Blocks() as demo4:\n",
    "    gr.Markdown(\n",
    "    \"\"\"\n",
    "    # Random Forest\n",
    "    \"\"\"),\n",
    "    with gr.Row():\n",
    "        with gr.Column():\n",
    "            plot4 = gr.Plot(recCurve, show_label = False)\n",
    "        with gr.Column():\n",
    "            plot1 = gr.Plot(importance, show_label = False)\n",
    "    with gr.Row():\n",
    "            plot2 = gr.Plot(learning, show_label = False)\n",
    "            plot4 = gr.Plot(roc, show_label = False)\n",
    "    with gr.Row():\n",
    "            plot3 = gr.Plot(matrixes, show_label = False)\n",
    "            scores = gr.Dataframe(df, label=\"Metrics scores\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a973c37d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running on local URL:  http://127.0.0.1:7896\n",
      "\n",
      "To create a public link, set `share=True` in `launch()`.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div><iframe src=\"http://127.0.0.1:7896/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "with gr.Blocks() as demo:\n",
    "    with gr.Tab(\"Model Overwiew\"):\n",
    "        demo4.render()\n",
    "    with gr.Tab(\"Predict Stroke\"):\n",
    "        demo2.render()\n",
    "    with gr.Tab(\"Predict Stroke CSV\"):\n",
    "        demo3.render()\n",
    "demo.launch()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d0a545dc",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "my_env",
   "language": "python",
   "name": "my_env"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}