Repository: DHI/tsod (language: python)

Issue:
Add benchmarking dataset with labelled anomalies for scoring performance of detector algorithms
Do you know about any (open source) datasets at DHI that has labelled anomalies that we can use for testing? @ecomodeller @laurafroelich @akfDHI


Discussion / hints:
@ecomodeller I found some datasets with labelled anomalies here: https://github.com/numenta/NAB
There are very few labels. But I guess that is the case with anomalies. 
@rhaDHI Have you checked out the license for that repo? it seems to be quite strict and copy-left, so if we want to use material from the numenta/NAB repo we need to change our license to the same one (AGPL-3.0 License) as far as I can tell. What do you think? If I am right, making our repo AGPL would then imply that anyone using our repo would also have to make it AGPL... maybe not what we want? 
I don't know any open datasets at DHI that we can use. We have to ask around and see if someone has some annotated dataset they are willing to share. There are lots of data, but not so many with labels and probably even fewer that are public, unfortunately.
I will try to ask around on DHI yammer for labelled data sets with anomalies. @ecomodeller Do you have labels for the DMI data set we have in repo? Otherwise I will try to label the obvious ones with the algorithms, e.g.
![anomaly 1](https://user-images.githubusercontent.com/33832493/106189001-fef78880-61a7-11eb-8b1b-16c6e998af18.png)

@laurafroelich @ecomodeller @akfDHI How do you like this message to be posted on yammer: 

We are trying to establish best practices and automated ways of identifying anomalies/outliers in time series data. 
Please let us know if you:
- have a dataset that needs to be cleaned automatically
- have algorithms for detecting outliers lying around in your head or in actual code
- have a data set, ideally publicly available, with labelled anomalies, i.e. an exact indication about which data points are actually anomalies.

Currently we are working on algorithms based on everything from simple range checks to machine learning models. Check out and potentially contribute to our open source anomaly detection python package on DHI's Github here: https://github.com/DHI/anomalydetection 
Sounds good to me :)
Can we make an interactive application to assist the labelling process?

1. Upload data
2. Automatic labeling of obvious outliers with simple detector
3. Manually add / remove labels by clicking on chart.
4. Save the labelled timeseries in reusable format e.g. csv
Sounds good to me too. Which Yammer channel?
________________________________
From: Laura Froelich <notifications@github.com>
Sent: Friday, 29 January 2021 06.36
To: DHI/anomalydetection <anomalydetection@noreply.github.com>
Cc: Anne Katrine V.Falk <akf@dhigroup.com>; Mention <mention@noreply.github.com>
Subject: Re: [DHI/anomalydetection] Add benchmarking dataset with labelled anomalies for scoring performance of detector algorithms (#12)


Sounds good to me :)

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@ecomodeller There is one open source tool here: https://trainset.geocene.com/
@ecomodeller Is this relevant: http://www.marineinsitu.eu/dashboard ?

Fix patch:
diff --git a/notebooks/cmems.ipynb b/notebooks/cmems.ipynb
new file mode 100644
index 0000000..7d504d6
--- /dev/null
+++ b/notebooks/cmems.ipynb
@@ -0,0 +1,298 @@
+{
+ "metadata": {
+  "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-final"
+  },
+  "orig_nbformat": 2,
+  "kernelspec": {
+   "name": "python3",
+   "display_name": "Python 3",
+   "language": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2,
+ "cells": [
+  {
+   "source": [
+    "# CMEMS In-Situ data\n",
+    "\n",
+    "All CMEMS in-situ data are provided in a standardised netCDF format including QC flags.\n",
+    "\n",
+    "They are also free to use: \n",
+    "\n",
+    "*\"These data were collected and made freely available by the Copernicus project and the programs that contribute to it\"*\n",
+    "\n",
+    "Example downloaded from [CMEMS/EMODNET](https://www.emodnet-physics.eu/Map/platinfo/PIROOSDownload.aspx?PlatformID=13762)"
+   ],
+   "cell_type": "markdown",
+   "metadata": {}
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import xarray as xr\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "output_type": "execute_result",
+     "data": {
+      "text/plain": [
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+       "    references:                     http://marine.copernicus.eu http://www.ma...\n",
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+       "    doi:                            https://doi.org/10.13155/59938 https://do...\n",
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+       "    distribution_statement:         These data follow Copernicus standards; t...\n",
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+       "    comment:                        \n",
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+       "    time_coverage_end:              2020-11-07T07:50:00Z\n",
+       "    id:                             BO_TS_MO_FINO2\n",
+       "    update_interval:                P1M\n",
+       "    last_date_observation:          2020-11-07T07:50:00Z\n",
+       "    time_coverage_start:            2015-10-01T00:00:00Z\n",
+       "    history:                        2019-06-25T13:00:30Z File created by SMHI...\n",
+       "    geospatial_vertical_max:        20.0000\n",
+       "    institution_references:         www.bsh.de\n",
+       "    last_longitude_observation:     13.1542\n",
+       "    pi_name:                        BSH\n",
+       "    geospatial_lat_min:             55.0083\n",
+       "    wmo_platform_code:              \n",
+       "    geospatial_lat_max:             55.0083\n",
+       "    institution_edmo_code:          1850\n",
+       "    data_mode:                      R\n",
+       "    site_code:                      FINO2\n",
+       "    title:                          Global Ocean - In Situ Wave Observations ...\n",
+       "    date_update:                    2020-12-17T13:31:41Z\n",
+       "    platform_name:                  FINO2\n",
+       "    last_latitude_observation:      55.0083\n",
+       "    source_platform_category_code:  48\n",
+       "    institution:                    BSH"
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  timeSeries\n    summary:                        Oceanographic data from the Baltic Sea. M...\n    references:                     http://marine.copernicus.eu http://www.ma...\n    data_assembly_center:           SMHI\n    wmo_inst_type:                  \n    doi:                            https://doi.org/10.13155/59938 https://do...\n    citation:                       These data were collected and made freely...\n    Conventions:                    CF-1.6 Copernicus-InSituTAC-FormatManual-...\n    bottom_depth:                    \n    qc_manual:                      Recommendations for in-situ data Near Rea...\n    distribution_statement:         These data follow Copernicus standards; t...\n    quality_index:                  A\n    comment:                        \n    netcdf_version:                 netCDF-4 classic model\n    source:                         mooring\n    geospatial_lon_min:             13.1542\n    quality_control_indicator:      1\n    history_version:                10\n    geospatial_lon_max:             13.1542\n    data_type:                      OceanSITES time-series data\n    platform_code:                  FINO2\n    geospatial_vertical_min:        2.0000\n    time_coverage_end:              2020-11-07T07:50:00Z\n    id:                             BO_TS_MO_FINO2\n    update_interval:                P1M\n    last_date_observation:          2020-11-07T07:50:00Z\n    time_coverage_start:            2015-10-01T00:00:00Z\n    history:                        2019-06-25T13:00:30Z File created by SMHI...\n    geospatial_vertical_max:        20.0000\n    institution_references:         www.bsh.de\n    last_longitude_observation:     13.1542\n    pi_name:                        BSH\n    geospatial_lat_min:             55.0083\n    wmo_platform_code:              \n    geospatial_lat_max:             55.0083\n    institution_edmo_code:          1850\n    data_mode:                      R\n    site_code:                      FINO2\n    title:                          Global Ocean - In Situ Wave Observations ...\n    date_update:                    2020-12-17T13:31:41Z\n    platform_name:                  FINO2\n    last_latitude_observation:      55.0083\n    source_platform_category_code:  48\n    institution:                    BSH</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-6a298796-3a94-4fd5-9faf-317dd1a6c1ca' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6a298796-3a94-4fd5-9faf-317dd1a6c1ca' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>DEPTH</span>: 10</li><li><span class='xr-has-index'>LATITUDE</span>: 34797</li><li><span class='xr-has-index'>LONGITUDE</span>: 34797</li><li><span>POSITION</span>: 34797</li><li><span class='xr-has-index'>TIME</span>: 34797</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-28b853b5-1243-4edd-abce-d5dea80761d8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-28b853b5-1243-4edd-abce-d5dea80761d8' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>TIME</span></div><div class='xr-var-dims'>(TIME)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2015-10-01 ... 2020-11-07T07:50:...</div><input id='attrs-407ad264-08ec-4b3b-b83b-19a9af7ee921' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-407ad264-08ec-4b3b-b83b-19a9af7ee921' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8672e2be-7f38-4b5b-9987-033e628f6363' class='xr-var-data-in' type='checkbox'><label for='data-8672e2be-7f38-4b5b-9987-033e628f6363' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_max :</span></dt><dd>90000.0</dd><dt><span>uncertainty :</span></dt><dd></dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>valid_min :</span></dt><dd>-90000.0</dd><dt><span>ancillary_variables :</span></dt><dd>TIME_QC</dd><dt><span>comment :</span></dt><dd></dd><dt><span>QC_indicator :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2015-10-01T00:00:00.000000000&#x27;, &#x27;2015-10-01T00:10:00.000000000&#x27;,\n       &#x27;2015-10-01T00:20:00.000000256&#x27;, ..., &#x27;2020-11-07T07:30:00.000000000&#x27;,\n       &#x27;2020-11-07T07:40:00.000000000&#x27;, &#x27;2020-11-07T07:50:00.000000256&#x27;],\n      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>LATITUDE</span></div><div class='xr-var-dims'>(LATITUDE)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>55.01 55.01 55.01 ... 55.01 55.01</div><input id='attrs-70a2192c-4a4a-4720-9340-817be77582fc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-70a2192c-4a4a-4720-9340-817be77582fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-426ace82-e003-4215-8d8b-41de82725b2c' class='xr-var-data-in' type='checkbox'><label for='data-426ace82-e003-4215-8d8b-41de82725b2c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>uncertainty :</span></dt><dd></dd><dt><span>long_name :</span></dt><dd>Latitude of each location</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>ancillary_variables :</span></dt><dd>POSITION_QC</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd><dt><span>comment :</span></dt><dd></dd><dt><span>QC_indicator :</span></dt><dd>1</dd><dt><span>units :</span></dt><dd>degree_north</dd></dl></div><div class='xr-var-data'><pre>array([55.0083, 55.0083, 55.0083, ..., 55.0083, 55.0083, 55.0083],\n      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>LONGITUDE</span></div><div class='xr-var-dims'>(LONGITUDE)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>13.15 13.15 13.15 ... 13.15 13.15</div><input id='attrs-9ec153ec-b783-406c-936d-a8a897baf708' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9ec153ec-b783-406c-936d-a8a897baf708' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-63eb2284-10f0-4a0f-bedd-9ee151d939dd' class='xr-var-data-in' type='checkbox'><label for='data-63eb2284-10f0-4a0f-bedd-9ee151d939dd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>uncertainty :</span></dt><dd></dd><dt><span>long_name :</span></dt><dd>Longitude of each location</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>ancillary_variables :</span></dt><dd>POSITION_QC</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd><dt><span>comment :</span></dt><dd></dd><dt><span>QC_indicator :</span></dt><dd>1</dd><dt><span>units :</span></dt><dd>degree_east</dd></dl></div><div class='xr-var-data'><pre>array([13.1542, 13.1542, 13.1542, ..., 13.1542, 13.1542, 13.1542],\n      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-62afa96d-6cb0-4f77-9396-d494801fc41c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-62afa96d-6cb0-4f77-9396-d494801fc41c' class='xr-section-summary' >Data variables: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>TIME_QC</span></div><div class='xr-var-dims'>(TIME)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e42969d4-05b5-4126-9798-c8fc12d5bf1e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e42969d4-05b5-4126-9798-c8fc12d5bf1e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-16db7f4d-312d-4af2-839c-65cb104decee' class='xr-var-data-in' type='checkbox'><label for='data-16db7f4d-312d-4af2-839c-65cb104decee' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>conventions :</span></dt><dd>Copernicus Marine In Situ reference table 2</dd><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>long_name :</span></dt><dd>Time quality flag</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed not_used nominal_value interpolated_value missing_value</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>flag_values :</span></dt><dd>[0 1 2 3 4 5 6 7 8 9]</dd></dl></div><div class='xr-var-data'><pre>array([1., 1., 1., ..., 1., 1., 1.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>POSITION_QC</span></div><div class='xr-var-dims'>(POSITION)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7f888503-203b-471b-a1a9-22751ff144fb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7f888503-203b-471b-a1a9-22751ff144fb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d4d3877f-9698-4d54-b0c8-e5b33bc2c662' class='xr-var-data-in' type='checkbox'><label for='data-d4d3877f-9698-4d54-b0c8-e5b33bc2c662' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>conventions :</span></dt><dd>Copernicus Marine In Situ reference table 2</dd><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>long_name :</span></dt><dd>Position quality flag</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed not_used nominal_value interpolated_value missing_value</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>flag_values :</span></dt><dd>[0 1 2 3 4 5 6 7 8 9]</dd></dl></div><div class='xr-var-data'><pre>array([7., 7., 7., ..., 1., 1., 1.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PSAL</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b0a127a7-5cd0-4725-a8ea-6fd959082c18' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b0a127a7-5cd0-4725-a8ea-6fd959082c18' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4fdcc723-0b20-4e0a-a589-cf9e8fef63d3' class='xr-var-data-in' type='checkbox'><label for='data-4fdcc723-0b20-4e0a-a589-cf9e8fef63d3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_max :</span></dt><dd>40000</dd><dt><span>long_name :</span></dt><dd>Practical salinity</dd><dt><span>standard_name :</span></dt><dd>sea_water_practical_salinity</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>units :</span></dt><dd>0.001</dd><dt><span>data_mode :</span></dt><dd>R</dd></dl></div><div class='xr-var-data'><pre>[347970 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PSAL_QC</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-769dde3d-5779-4167-95dc-5a02be8aae63' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-769dde3d-5779-4167-95dc-5a02be8aae63' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1cf095cc-bd5f-42b1-86a1-1efc469ab35b' class='xr-var-data-in' type='checkbox'><label for='data-1cf095cc-bd5f-42b1-86a1-1efc469ab35b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>conventions :</span></dt><dd>Copernicus Marine In Situ reference table 2</dd><dt><span>long_name :</span></dt><dd>Practical salinity quality flag</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed not_used nominal_value interpolated_value missing_value</dd><dt><span>flag_values :</span></dt><dd>[0 1 2 3 4 5 6 7 8 9]</dd></dl></div><div class='xr-var-data'><pre>[347970 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TEMP</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3aa9303b-b204-4011-8427-9e5b6ae4de24' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3aa9303b-b204-4011-8427-9e5b6ae4de24' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3877a57-4106-4b46-9d66-24b308a470dc' class='xr-var-data-in' type='checkbox'><label for='data-e3877a57-4106-4b46-9d66-24b308a470dc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_max :</span></dt><dd>32000</dd><dt><span>long_name :</span></dt><dd>Sea temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd><dt><span>valid_min :</span></dt><dd>-2000</dd><dt><span>units :</span></dt><dd>degrees_C</dd><dt><span>data_mode :</span></dt><dd>R</dd></dl></div><div class='xr-var-data'><pre>[347970 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TEMP_QC</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-dd3e56cf-54f9-4e15-8d39-a2366c766b5e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dd3e56cf-54f9-4e15-8d39-a2366c766b5e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7f624074-010b-42a6-89e0-5fd82f167834' class='xr-var-data-in' type='checkbox'><label for='data-7f624074-010b-42a6-89e0-5fd82f167834' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>conventions :</span></dt><dd>Copernicus Marine In Situ reference table 2</dd><dt><span>long_name :</span></dt><dd>Sea temperature quality flag</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed not_used nominal_value interpolated_value missing_value</dd><dt><span>flag_values :</span></dt><dd>[0 1 2 3 4 5 6 7 8 9]</dd></dl></div><div class='xr-var-data'><pre>[347970 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>OSAT</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-290816ee-b98e-46d4-a37b-a259a637c8c4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-290816ee-b98e-46d4-a37b-a259a637c8c4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e6f0dc6-30a7-45b0-90d2-e149c9a694a1' class='xr-var-data-in' type='checkbox'><label for='data-5e6f0dc6-30a7-45b0-90d2-e149c9a694a1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_max :</span></dt><dd>10000</dd><dt><span>long_name :</span></dt><dd>Oxygen saturation</dd><dt><span>standard_name :</span></dt><dd>fractional_saturation_of_oxygen_in_sea_water</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>data_mode :</span></dt><dd>R</dd></dl></div><div class='xr-var-data'><pre>[347970 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>OSAT_QC</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-148403ce-ce2e-471c-a382-4d4c91712231' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-148403ce-ce2e-471c-a382-4d4c91712231' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6af62209-80ba-49c4-bc4c-f7023370a1b3' class='xr-var-data-in' type='checkbox'><label for='data-6af62209-80ba-49c4-bc4c-f7023370a1b3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>conventions :</span></dt><dd>Copernicus Marine In Situ reference table 2</dd><dt><span>long_name :</span></dt><dd>Oxygen saturation quality flag</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed not_used nominal_value interpolated_value missing_value</dd><dt><span>flag_values :</span></dt><dd>[0 1 2 3 4 5 6 7 8 9]</dd></dl></div><div class='xr-var-data'><pre>[347970 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>DEPH</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c407cebc-4110-401d-8913-eb395750d3b9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c407cebc-4110-401d-8913-eb395750d3b9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-31b2ca7a-504d-4700-8d8a-d28749cb98d9' class='xr-var-data-in' type='checkbox'><label for='data-31b2ca7a-504d-4700-8d8a-d28749cb98d9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_max :</span></dt><dd>12000.0</dd><dt><span>long_name :</span></dt><dd>Depth</dd><dt><span>standard_name :</span></dt><dd>depth</dd><dt><span>valid_min :</span></dt><dd>-12000.0</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>ancillary_variables :</span></dt><dd>DEPH_QC</dd><dt><span>uncertainty :</span></dt><dd></dd><dt><span>reference :</span></dt><dd>sea_level</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>data_mode :</span></dt><dd>R</dd></dl></div><div class='xr-var-data'><pre>[347970 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>DEPH_QC</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f0f6d4bf-8335-4ba9-85e4-d55807af1f21' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f0f6d4bf-8335-4ba9-85e4-d55807af1f21' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7a38bb60-ba28-4d22-9489-8e6efc1f2f16' class='xr-var-data-in' type='checkbox'><label for='data-7a38bb60-ba28-4d22-9489-8e6efc1f2f16' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>conventions :</span></dt><dd>Copernicus Marine In Situ reference table 2</dd><dt><span>long_name :</span></dt><dd>Depth quality flag</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed not_used nominal_value interpolated_value missing_value</dd><dt><span>flag_values :</span></dt><dd>[0 1 2 3 4 5 6 7 8 9]</dd></dl></div><div class='xr-var-data'><pre>[347970 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-49403484-41f6-4302-b525-d590e55de83b' class='xr-section-summary-in' type='checkbox'  ><label for='section-49403484-41f6-4302-b525-d590e55de83b' class='xr-section-summary' >Attributes: <span>(50)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>naming_authority :</span></dt><dd>Copernicus Marine In Situ</dd><dt><span>ices_platform_code :</span></dt><dd></dd><dt><span>area :</span></dt><dd>Baltic Sea</dd><dt><span>format_version :</span></dt><dd>1.4</dd><dt><span>contact :</span></dt><dd>cmems-service@smhi.se</dd><dt><span>author :</span></dt><dd>cmems-service</dd><dt><span>cdm_data_type :</span></dt><dd>timeSeries</dd><dt><span>summary :</span></dt><dd>Oceanographic data from the Baltic Sea. Measured properties: the hydrographic conditions as currents, temperature and salinity.</dd><dt><span>references :</span></dt><dd>http://marine.copernicus.eu http://www.marineinsitu.eu</dd><dt><span>data_assembly_center :</span></dt><dd>SMHI</dd><dt><span>wmo_inst_type :</span></dt><dd></dd><dt><span>doi :</span></dt><dd>https://doi.org/10.13155/59938 https://doi.org/10.13155/40846 https://doi.org/10.13155/53381 https://doi.org/10.13155/36230 https://doi.org/10.13155/43494</dd><dt><span>citation :</span></dt><dd>These data were collected and made freely available by the Copernicus project and the programs that contribute to it</dd><dt><span>Conventions :</span></dt><dd>CF-1.6 Copernicus-InSituTAC-FormatManual-1.41 Copernicus-InSituTAC-SRD-1.5 Copernicus-InSituTAC-ParametersList-3.2.0</dd><dt><span>bottom_depth :</span></dt><dd> </dd><dt><span>qc_manual :</span></dt><dd>Recommendations for in-situ data Near Real Time Quality Control https://doi.org/10.13155/36230</dd><dt><span>distribution_statement :</span></dt><dd>These data follow Copernicus standards; they are public and free of charge. User assumes all risk for use of data. User must display citation in any publication or product using data. User must contact PI prior to any commercial use of data.</dd><dt><span>quality_index :</span></dt><dd>A</dd><dt><span>comment :</span></dt><dd></dd><dt><span>netcdf_version :</span></dt><dd>netCDF-4 classic model</dd><dt><span>source :</span></dt><dd>mooring</dd><dt><span>geospatial_lon_min :</span></dt><dd>13.1542</dd><dt><span>quality_control_indicator :</span></dt><dd>1</dd><dt><span>history_version :</span></dt><dd>10</dd><dt><span>geospatial_lon_max :</span></dt><dd>13.1542</dd><dt><span>data_type :</span></dt><dd>OceanSITES time-series data</dd><dt><span>platform_code :</span></dt><dd>FINO2</dd><dt><span>geospatial_vertical_min :</span></dt><dd>2.0000</dd><dt><span>time_coverage_end :</span></dt><dd>2020-11-07T07:50:00Z</dd><dt><span>id :</span></dt><dd>BO_TS_MO_FINO2</dd><dt><span>update_interval :</span></dt><dd>P1M</dd><dt><span>last_date_observation :</span></dt><dd>2020-11-07T07:50:00Z</dd><dt><span>time_coverage_start :</span></dt><dd>2015-10-01T00:00:00Z</dd><dt><span>history :</span></dt><dd>2019-06-25T13:00:30Z File created by SMHI Baltic Sea PU.\n2019-06-28T19:43:43Z Data converted by SMHI Baltic Sea PU.\n2019-11-12T08:04:13Z Data converted by SMHI Baltic Sea PU.\n2019-11-18T19:30:44Z Data converted by SMHI Baltic Sea PU.\n2020-01-09T13:30:48Z Data converted by SMHI Baltic Sea PU.\n2020-05-11T13:24:43Z Data converted by SMHI Baltic Sea PU.\n2020-05-29T07:31:37Z Data converted by SMHI Baltic Sea PU.\n2020-05-29T13:32:04Z Data converted by SMHI Baltic Sea PU.\n2020-12-01T13:47:43Z Data converted by SMHI Baltic Sea PU.\n2020-12-17T13:31:41Z Data converted by SMHI Baltic Sea PU.</dd><dt><span>geospatial_vertical_max :</span></dt><dd>20.0000</dd><dt><span>institution_references :</span></dt><dd>www.bsh.de</dd><dt><span>last_longitude_observation :</span></dt><dd>13.1542</dd><dt><span>pi_name :</span></dt><dd>BSH</dd><dt><span>geospatial_lat_min :</span></dt><dd>55.0083</dd><dt><span>wmo_platform_code :</span></dt><dd></dd><dt><span>geospatial_lat_max :</span></dt><dd>55.0083</dd><dt><span>institution_edmo_code :</span></dt><dd>1850</dd><dt><span>data_mode :</span></dt><dd>R</dd><dt><span>site_code :</span></dt><dd>FINO2</dd><dt><span>title :</span></dt><dd>Global Ocean - In Situ Wave Observations Re-Analysis</dd><dt><span>date_update :</span></dt><dd>2020-12-17T13:31:41Z</dd><dt><span>platform_name :</span></dt><dd>FINO2</dd><dt><span>last_latitude_observation :</span></dt><dd>55.0083</dd><dt><span>source_platform_category_code :</span></dt><dd>48</dd><dt><span>institution :</span></dt><dd>BSH</dd></dl></div></li></ul></div></div>"
+     },
+     "metadata": {},
+     "execution_count": 2
+    }
+   ],
+   "source": [
+    "ds = xr.open_dataset(\"../tests/data/BO_TS_MO_FINO2.nc\")\n",
+    "ds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "output_type": "execute_result",
+     "data": {
+      "text/plain": [
+       "'These data were collected and made freely available by the Copernicus project and the programs that contribute to it'"
+      ]
+     },
+     "metadata": {},
+     "execution_count": 3
+    }
+   ],
+   "source": [
+    "ds.attrs['citation']"
+   ]
+  },
+  {
+   "source": [
+    "## Quality flags"
+   ],
+   "cell_type": "markdown",
+   "metadata": {}
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "output_type": "execute_result",
+     "data": {
+      "text/plain": [
+       "   qc_flag                                    meaning\n",
+       "0        0                            no_qc_performed\n",
+       "1        1                                  good_data\n",
+       "2        2                         probably_good_data\n",
+       "3        3  bad_data_that_are_potentially_correctable\n",
+       "4        4                                   bad_data\n",
+       "5        5                              value_changed\n",
+       "6        6                                   not_used\n",
+       "7        7                              nominal_value\n",
+       "8        8                         interpolated_value\n",
+       "9        9                              missing_value"
+      ],
+      "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>qc_flag</th>\n      <th>meaning</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0</td>\n      <td>no_qc_performed</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1</td>\n      <td>good_data</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2</td>\n      <td>probably_good_data</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>3</td>\n      <td>bad_data_that_are_potentially_correctable</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>4</td>\n      <td>bad_data</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>5</td>\n      <td>value_changed</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>6</td>\n      <td>not_used</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>7</td>\n      <td>nominal_value</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>8</td>\n      <td>interpolated_value</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>9</td>\n      <td>missing_value</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
+     },
+     "metadata": {},
+     "execution_count": 4
+    }
+   ],
+   "source": [
+    "pd.DataFrame({'qc_flag' : ds.PSAL_QC.flag_values,\n",
+    "    'meaning' : ds.PSAL_QC.flag_meanings.split()})"
+   ]
+  },
+  {
+   "source": [
+    "# Salinity\n",
+    "\n",
+    "Lets's see if we have some outliers..."
+   ],
+   "cell_type": "markdown",
+   "metadata": {}
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "output_type": "display_data",
+     "data": {
+      "text/plain": "<Figure size 432x288 with 1 Axes>",
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144.141142 73.922979 \r\nL 144.276925 72.742339 \r\nL 144.344816 73.248328 \r\nL 144.304082 72.067688 \r\nL 144.385551 72.911002 \r\nL 144.521334 68.863096 \r\nL 144.582436 68.863096 \r\nL 144.602803 68.694434 \r\nL 144.616382 69.031759 \r\nL 144.691062 68.863096 \r\nL 144.813267 69.200422 \r\nL 144.840423 69.200422 \r\nL 144.989784 68.188446 \r\nL 144.996573 68.188446 \r\nL 145.139145 66.501818 \r\nL 145.159512 66.839144 \r\nL 145.17988 66.839144 \r\nL 145.186669 67.007806 \r\nM 147.175885 66.839144 \r\nL 147.318457 65.99583 \r\nL 147.461029 67.007806 \r\nL 147.630757 65.489842 \r\nL 147.651124 65.489842 \r\nL 147.786907 66.164493 \r\nL 147.800485 66.164493 \r\nL 147.92269 66.501818 \r\nL 147.929479 66.501818 \r\nL 147.936268 66.670481 \r\nL 147.983792 66.333155 \r\nL 148.038105 66.501818 \r\nL 148.160309 66.164493 \r\nL 148.187466 66.333155 \r\nL 148.248568 65.99583 \r\nL 148.268935 66.164493 \r\nL 148.289303 66.164493 \r\nL 148.350405 65.658504 \r\nL 148.404718 65.827167 \r\nL 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291.085144 75.609606 \r\nL 291.200559 75.440943 \r\nL 291.533227 75.440943 \r\nL 291.621486 75.103618 \r\nL 291.641853 75.440943 \r\nL 291.675799 75.440943 \r\nL 291.764057 75.609606 \r\nL 291.784425 75.440943 \r\nL 291.831949 75.440943 \r\nL 291.947364 75.609606 \r\nL 291.967731 75.609606 \r\nL 291.974521 75.440943 \r\nL 292.076358 75.609606 \r\nL 292.571964 75.609606 \r\nL 292.660223 75.27228 \r\nL 292.68738 75.440943 \r\nL 292.707747 75.440943 \r\nL 292.823162 75.27228 \r\nL 292.850319 75.27228 \r\nL 292.986101 74.59763 \r\nL 293.094728 74.59763 \r\nL 293.23051 75.440943 \r\nL 293.244089 75.103618 \r\nL 293.257667 75.27228 \r\nL 293.522443 75.27228 \r\nL 293.529232 75.103618 \r\nL 293.631069 75.27228 \r\nL 293.78043 75.27228 \r\nL 293.827954 75.440943 \r\nL 293.889056 75.27228 \r\nL 294.466133 75.27228 \r\nL 294.581548 75.103618 \r\nL 294.819167 75.103618 \r\nL 294.887059 74.934955 \r\nL 294.927794 75.27228 \r\nL 294.948161 75.103618 \r\nL 295.016052 75.778269 \r\nL 295.022841 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48.286243 \r\nL 113.359212 48.11758 \r\nL 113.420314 48.960894 \r\nL 113.440681 48.960894 \r\nL 113.556097 49.129556 \r\nL 113.562886 49.129556 \r\nL 113.678301 48.960894 \r\nL 113.68509 48.960894 \r\nL 113.807295 48.623568 \r\nL 113.827662 48.623568 \r\nL 113.943077 48.454905 \r\nL 114.004179 48.454905 \r\nL 114.126384 48.11758 \r\nL 114.146751 48.11758 \r\nL 114.275745 47.611592 \r\nL 114.364004 47.611592 \r\nL 114.425106 47.442929 \r\nL 114.445473 47.780254 \r\nL 114.465841 47.780254 \r\nL 114.649147 51.490835 \r\nL 114.655936 51.490835 \r\nL 114.873189 48.454905 \r\nL 114.879978 48.623568 \r\nL 114.913923 48.11758 \r\nL 115.002182 48.960894 \r\nL 115.192278 42.214384 \r\nL 115.294115 40.021769 \r\nL 115.307693 40.190431 \r\nL 115.355217 37.154502 \r\nL 115.32806 41.033745 \r\nL 115.368795 38.503804 \r\nL 115.56568 27.709389 \r\nL 115.572469 28.38404 \r\nL 139.972614 67.513795 \r\nL 140.020138 67.682457 \r\nL 140.101608 67.007806 \r\nL 140.203445 67.345132 \r\nL 140.217023 67.176469 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71.5617 \r\nL 142.959833 71.899026 \r\nL 142.973411 71.899026 \r\nL 143.109194 72.573677 \r\nL 143.149929 72.573677 \r\nL 143.204242 72.405014 \r\nL 143.258555 72.742339 \r\nL 143.380759 72.236351 \r\nL 143.516542 73.079665 \r\nL 143.523331 72.911002 \r\nL 143.591223 73.754316 \r\nL 143.598012 73.754316 \r\nL 143.604801 73.754316 \r\nL 143.733794 74.260304 \r\nL 143.76774 74.260304 \r\nL 143.883155 74.428967 \r\nL 143.984992 74.428967 \r\nL 144.100408 74.260304 \r\nL 144.134353 74.260304 \r\nL 144.276925 73.079665 \r\nL 144.283714 73.41699 \r\nL 144.358395 72.236351 \r\nL 144.419497 72.573677 \r\nL 144.528123 69.200422 \r\nL 144.562069 69.200422 \r\nL 144.602803 69.031759 \r\nL 144.616382 69.369085 \r\nL 144.670695 69.200422 \r\nL 144.792899 69.537747 \r\nL 144.826845 69.537747 \r\nL 144.976206 68.525771 \r\nL 144.989784 68.525771 \r\nL 145.139145 66.839144 \r\nL 145.152723 67.007806 \r\nL 145.186669 67.176469 \r\nM 147.175885 67.176469 \r\nL 147.318457 66.333155 \r\nL 147.461029 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77.802222 \r\nL 256.521666 77.464896 \r\nL 256.535245 77.464896 \r\nL 256.664238 76.958908 \r\nL 256.840756 76.958908 \r\nL 256.96296 76.621582 \r\nL 257.085164 76.621582 \r\nL 257.390675 76.958908 \r\nL 257.506091 76.790245 \r\nL 257.526458 76.790245 \r\nL 257.641873 76.621582 \r\nL 257.675819 76.621582 \r\nL 257.723343 76.115594 \r\nL 257.845547 78.139547 \r\nL 257.872704 78.139547 \r\nL 257.933806 78.476872 \r\nL 257.967752 77.970884 \r\nL 258.0628 76.958908 \r\nL 258.21895 76.790245 \r\nL 258.334365 77.802222 \r\nL 258.354732 77.633559 \r\nL 258.422624 76.958908 \r\nL 258.470148 77.464896 \r\nL 258.571985 78.139547 \r\nL 258.483726 77.296233 \r\nL 258.592352 77.802222 \r\nL 258.599141 77.802222 \r\nL 258.707767 78.139547 \r\nL 258.714556 77.970884 \r\nL 258.721346 77.970884 \r\nL 258.734924 78.139547 \r\nL 258.76208 77.802222 \r\nL 258.823183 77.802222 \r\nL 258.836761 77.802222 \r\nL 258.931809 77.127571 \r\nL 258.965754 77.296233 \r\nL 258.972543 77.296233 \r\nL 258.979333 77.127571 \r\nL 258.986122 77.464896 \r\nL 258.9997 77.296233 \r\nL 259.169428 76.958908 \r\nL 259.203374 77.127571 \r\nL 259.325578 77.127571 \r\nL 259.386681 76.958908 \r\nL 259.434205 77.127571 \r\nL 259.495307 77.127571 \r\nL 259.617511 76.790245 \r\nL 259.671824 76.790245 \r\nL 259.787239 75.103618 \r\nL 259.807607 75.440943 \r\nL 259.923022 77.127571 \r\nL 259.94339 76.958908 \r\nL 259.977335 76.958908 \r\nL 260.601935 75.609606 \r\nL 260.72414 74.766292 \r\nL 260.730929 75.103618 \r\nL 260.873501 75.946931 \r\nL 260.982127 75.946931 \r\nL 260.988916 75.778269 \r\nL 260.995705 75.946931 \r\nL 261.199379 75.609606 \r\nL 261.341951 74.766292 \r\nL 261.362318 74.766292 \r\nL 261.464155 74.59763 \r\nL 261.470945 74.766292 \r\nL 261.518468 74.766292 \r\nL 261.640673 75.103618 \r\nL 261.647462 75.103618 \r\nM 268.579167 71.055712 \r\nL 268.592745 71.055712 \r\nL 268.613113 71.5617 \r\nL 268.640269 70.718387 \r\nL 268.653848 70.718387 \r\nL 290.467333 76.284257 \r\nL 290.596327 75.778269 \r\nL 290.64385 75.778269 \r\nL 290.677796 75.440943 \r\nL 290.691374 76.115594 \r\nL 290.738898 76.115594 \r\nL 290.745687 76.115594 \r\nL 290.80679 75.440943 \r\nL 290.867892 75.609606 \r\nL 290.901838 75.778269 \r\nL 290.949361 75.27228 \r\nL 290.96294 75.27228 \r\nL 290.983307 75.27228 \r\nL 291.078355 75.440943 \r\nL 291.091933 75.27228 \r\nL 291.19377 75.27228 \r\nL 291.200559 75.103618 \r\nL 291.220927 75.27228 \r\nL 291.50607 75.27228 \r\nL 291.621486 75.103618 \r\nL 291.641853 75.103618 \r\nL 291.74369 75.440943 \r\nL 291.757268 75.27228 \r\nL 291.89984 75.27228 \r\nL 292.015255 75.440943 \r\nL 292.028834 75.440943 \r\nL 292.05599 75.27228 \r\nL 292.13746 75.440943 \r\nL 292.578753 75.440943 \r\nL 292.700958 75.103618 \r\nL 292.707747 75.27228 \r\nL 292.809584 75.103618 \r\nL 292.823162 75.103618 \r\nL 292.958945 74.428967 \r\nL 293.094728 74.428967 \r\nL 293.237299 75.27228 \r\nL 293.244089 75.103618 \r\nL 293.257667 75.440943 \r\nL 293.569967 74.934955 \r\nL 293.597123 74.934955 \r\nL 293.712539 75.103618 \r\nL 293.827954 75.103618 \r\nL 293.848321 75.27228 \r\nL 293.93658 75.103618 \r\nL 293.970526 75.103618 \r\nL 294.031628 74.934955 \r\nL 294.079152 75.103618 \r\nL 294.425398 75.103618 \r\nL 294.540813 74.934955 \r\nL 294.825957 74.934955 \r\nL 294.927794 75.103618 \r\nL 294.934583 74.934955 \r\nL 294.948161 74.934955 \r\nL 295.016052 75.27228 \r\nL 295.063576 75.103618 \r\nL 295.090733 75.103618 \r\nL 295.104311 75.440943 \r\nL 295.199359 75.103618 \r\nL 295.362298 75.103618 \r\nL 295.477713 75.27228 \r\nL 295.491292 75.27228 \r\nL 295.613496 74.934955 \r\nL 296.007266 74.934955 \r\nL 296.109103 75.27228 \r\nL 296.319566 74.934955 \r\nL 296.448559 75.946931 \r\nL 296.475716 75.946931 \r\nL 296.591131 76.284257 \r\nL 296.726914 75.609606 \r\nL 296.733703 75.609606 \r\nL 296.740492 75.778269 \r\nL 296.75407 75.440943 \r\nL 296.828751 75.440943 \r\nL 296.957744 74.934955 \r\nL 296.971323 74.934955 \r\nL 297.086738 74.766292 \r\nL 297.30399 74.59763 \r\nL 297.310779 74.428967 \r\nL 297.392249 74.934955 \r\nL 297.399038 74.934955 \r\nL 297.466929 75.440943 \r\nL 297.521243 75.27228 \r\nL 297.643447 74.260304 \r\nL 297.663814 74.428967 \r\nL 297.677393 74.428967 \r\nL 297.765651 74.59763 \r\nL 297.786019 74.428967 \r\nL 297.792808 74.428967 \r\nL 297.921801 73.922979 \r\nL 298.037217 73.922979 \r\nL 298.105108 73.754316 \r\nL 298.390252 73.922979 \r\nL 298.512456 73.585653 \r\nL 298.519245 73.585653 \r\nL 298.587136 73.248328 \r\nL 298.627871 73.585653 \r\nL 298.750076 73.922979 \r\nL 298.770443 73.922979 \r\nL 298.892647 74.260304 \r\nL 298.906226 74.260304 \r\nL 299.021641 74.428967 \r\nL 299.123478 74.428967 \r\nL 299.49688 73.922979 \r\nL 299.517248 74.091641 \r\nL 299.557983 74.091641 \r\nL 299.564772 73.922979 \r\nL 299.666609 74.091641 \r\nL 299.693765 74.091641 \r\nL 299.822759 74.59763 \r\nL 300.012854 72.573677 \r\nL 300.019644 72.573677 \r\nL 300.060378 72.742339 \r\nL 300.230107 73.248328 \r\nL 300.250474 73.079665 \r\nL 300.365889 71.899026 \r\nL 300.393046 72.236351 \r\nL 300.399835 72.236351 \r\nL 300.535618 72.911002 \r\nL 300.555985 72.911002 \r\nL 300.698557 73.754316 \r\nL 300.732503 73.754316 \r\nL 300.786816 73.922979 \r\nL 300.83434 73.585653 \r\nL 300.881864 73.585653 \r\nL 300.915809 73.41699 \r\nL 301.289212 74.428967 \r\nL 301.370681 74.59763 \r\nL 301.391049 74.428967 \r\nL 301.526831 71.730363 \r\nL 301.587933 72.236351 \r\nL 301.608301 72.236351 \r\nL 301.61509 72.405014 \r\nL 301.662614 71.5617 \r\nL 301.764451 68.694434 \r\nL 301.798397 68.863096 \r\nL 301.839131 68.863096 \r\nL 301.92739 68.525771 \r\nL 301.934179 68.694434 \r\nL 302.015649 71.730363 \r\nL 302.198955 72.911002 \r\nL 302.253268 72.742339 \r\nL 302.32116 72.573677 \r\nL 302.361895 72.742339 \r\nL 302.368684 72.911002 \r\nL 302.470521 72.742339 \r\nL 302.518045 72.742339 \r\nL 302.667406 71.730363 \r\nL 302.728508 71.730363 \r\nL 302.898236 69.031759 \r\nL 302.938971 69.200422 \r\nL 303.169801 69.200422 \r\nL 303.292006 68.863096 \r\nL 303.305584 68.863096 \r\nL 303.346319 68.694434 \r\nL 303.387054 69.200422 \r\nL 303.400632 69.200422 \r\nL 303.448156 69.537747 \r\nL 303.502469 69.031759 \r\nL 303.516047 69.031759 \r\nL 303.549993 68.863096 \r\nL 303.604306 69.369085 \r\nL 352.472488 74.091641 \r\nL 352.492855 73.754316 \r\nL 352.526801 74.59763 \r\nL 352.560746 74.59763 \r\nL 352.581114 74.59763 \r\nL 352.710107 75.27228 \r\nL 352.832312 74.934955 \r\nL 352.84589 74.934955 \r\nL 352.893414 75.103618 \r\nL 353.076721 75.440943 \r\nL 353.15819 75.27228 \r\nL 353.171768 75.27228 \r\nL 353.287184 75.103618 \r\nL 353.341497 75.103618 \r\nL 353.355075 74.428967 \r\nL 353.456912 74.59763 \r\nL 353.511225 74.59763 \r\nL 353.518014 74.766292 \r\nL 353.579116 73.754316 \r\nL 353.585906 73.754316 \r\nL 353.680953 73.754316 \r\nL 353.809947 73.248328 \r\nL 353.816736 73.248328 \r\nL 353.823525 73.41699 \r\nL 353.871049 73.248328 \r\nL 354.013621 72.742339 \r\nL 354.115458 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143.469018 71.730363 \r\nL 143.489386 70.549724 \r\nL 143.591223 70.212398 \r\nL 143.61159 72.573677 \r\nL 143.618379 72.236351 \r\nL 143.659114 73.41699 \r\nL 143.706638 73.248328 \r\nL 143.713427 73.248328 \r\nL 143.862788 74.260304 \r\nL 143.903523 74.428967 \r\nL 143.978203 73.922979 \r\nL 143.991781 74.260304 \r\nL 144.052884 73.41699 \r\nL 144.066462 73.41699 \r\nL 144.100408 73.41699 \r\nL 144.147931 73.585653 \r\nL 144.120775 73.248328 \r\nL 144.16151 73.41699 \r\nL 144.168299 70.887049 \r\nL 144.195455 73.922979 \r\nL 144.270136 72.911002 \r\nL 144.534912 69.031759 \r\nL 144.609593 68.863096 \r\nL 144.643538 69.200422 \r\nL 144.684273 68.863096 \r\nL 144.731797 69.369085 \r\nL 144.745375 69.369085 \r\nL 144.752164 69.369085 \r\nL 144.772532 69.537747 \r\nL 144.86758 69.200422 \r\nL 144.894736 69.200422 \r\nL 145.078043 67.176469 \r\nL 145.132356 67.345132 \r\nL 145.111988 66.839144 \r\nL 145.186669 67.176469 \r\nM 147.175885 67.345132 \r\nL 147.298089 66.501818 \r\nL 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106.067683 54.695427 \r\nL 106.149152 53.68345 \r\nL 106.183098 54.358101 \r\nL 106.223833 54.695427 \r\nL 106.264567 54.020776 \r\nL 106.271357 54.020776 \r\nL 106.407139 52.671474 \r\nL 106.427507 52.840137 \r\nL 106.522555 53.346125 \r\nL 106.542922 53.177462 \r\nL 106.624392 53.008799 \r\nL 106.644759 53.177462 \r\nL 106.807698 54.526764 \r\nL 106.821276 54.526764 \r\nL 106.929903 54.864089 \r\nL 106.936692 54.695427 \r\nL 106.95027 54.695427 \r\nL 107.10642 53.514787 \r\nL 107.113209 53.68345 \r\nL 107.1811 52.840137 \r\nL 107.18789 52.840137 \r\nL 107.221835 52.840137 \r\nL 107.350829 54.020776 \r\nL 107.364407 54.020776 \r\nL 107.391564 54.189438 \r\nL 107.432298 53.177462 \r\nL 107.520557 52.165486 \r\nL 107.547714 52.502811 \r\nL 107.710653 53.852113 \r\nL 107.724231 53.852113 \r\nL 107.826068 54.864089 \r\nL 107.839646 54.358101 \r\nL 107.866803 53.852113 \r\nL 107.927905 54.526764 \r\nL 107.948273 54.189438 \r\nL 107.961851 54.189438 \r\nL 107.975429 53.852113 \r\nL 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111.641561 35.973863 \r\nL 111.655139 36.311188 \r\nL 111.668718 32.431945 \r\nL 111.831657 28.38404 \r\nL 111.838446 28.38404 \r\nL 111.967439 31.251306 \r\nL 112.048909 30.576655 \r\nL 112.055698 31.588632 \r\nL 112.062487 31.588632 \r\nL 112.069276 31.588632 \r\nL 112.211848 35.299212 \r\nL 112.286529 34.287235 \r\nL 112.293318 34.287235 \r\nL 112.35442 34.455898 \r\nL 112.415522 33.94991 \r\nL 112.422311 34.118573 \r\nL 112.483414 33.106596 \r\nL 112.605618 32.263283 \r\nL 112.625985 32.263283 \r\nL 112.632775 32.09462 \r\nL 112.659931 33.94991 \r\nL 112.673509 33.106596 \r\nL 112.782135 42.214384 \r\nL 112.802503 39.51578 \r\nL 112.809292 38.166478 \r\nL 112.843238 41.539733 \r\nL 112.90434 40.527757 \r\nL 113.006177 47.274266 \r\nL 113.019755 46.093627 \r\nL 113.101225 48.960894 \r\nL 113.14196 48.286243 \r\nL 113.250586 45.924964 \r\nL 113.257375 46.936941 \r\nL 113.345634 48.11758 \r\nL 113.29132 42.55171 \r\nL 113.352423 47.611592 \r\nL 113.413525 48.623568 \r\nL 113.481416 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142.084035 60.092634 \r\nL 142.179083 72.911002 \r\nL 142.314865 74.428967 \r\nL 142.3556 74.428967 \r\nL 142.504961 72.742339 \r\nL 142.532118 73.585653 \r\nL 142.586431 70.043736 \r\nL 142.620376 71.730363 \r\nL 142.600009 69.537747 \r\nL 142.6679 69.70641 \r\nL 142.681479 68.019783 \r\nL 142.742581 71.055712 \r\nL 142.762948 71.055712 \r\nL 142.776527 71.055712 \r\nL 142.837629 71.393038 \r\nL 142.885153 71.224375 \r\nL 142.898731 70.887049 \r\nL 142.973411 71.899026 \r\nL 143.102405 72.405014 \r\nL 143.211031 70.043736 \r\nL 143.129561 72.573677 \r\nL 143.258555 70.212398 \r\nL 143.278922 71.393038 \r\nL 143.346814 67.007806 \r\nL 143.353603 70.381061 \r\nL 143.448651 63.634552 \r\nL 143.475807 65.827167 \r\nL 143.489386 64.309203 \r\nL 143.496175 68.019783 \r\nL 143.584433 66.164493 \r\nL 143.788107 73.248328 \r\nL 143.794897 73.248328 \r\nL 143.903523 74.260304 \r\nL 143.937468 74.091641 \r\nL 144.066462 72.742339 \r\nL 144.073251 72.911002 \r\nL 144.100408 71.5617 \r\nL 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113.121592 42.889035 \r\nL 113.230218 37.829153 \r\nL 113.189483 47.948917 \r\nL 113.237007 38.166478 \r\nL 113.366001 44.575662 \r\nL 113.29132 36.479851 \r\nL 113.399947 42.383047 \r\nL 113.474627 39.009792 \r\nL 113.522151 39.347118 \r\nL 113.535729 39.347118 \r\nL 113.542518 39.178455 \r\nL 113.603621 39.853106 \r\nL 113.644355 39.347118 \r\nL 113.691879 39.853106 \r\nL 113.76656 39.684443 \r\nL 113.827662 38.503804 \r\nL 113.84124 39.853106 \r\nL 113.895553 38.672467 \r\nL 113.902342 38.672467 \r\nL 113.983812 37.829153 \r\nL 114.017758 37.997816 \r\nL 114.099227 38.841129 \r\nL 114.119595 37.997816 \r\nL 114.187486 36.648514 \r\nL 114.173908 38.166478 \r\nL 114.194275 36.817177 \r\nL 114.31648 45.756302 \r\nL 114.323269 45.756302 \r\nL 114.459051 47.611592 \r\nL 114.621991 49.804207 \r\nL 114.635569 49.298219 \r\nL 114.812086 45.418976 \r\nL 114.873189 45.756302 \r\nL 114.927502 46.26229 \r\nL 114.961447 44.744325 \r\nL 114.968236 44.744325 \r\nL 115.165121 35.973863 \r\nL 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144.514545 65.827167 \r\nL 144.643538 68.357108 \r\nL 144.663906 68.188446 \r\nL 144.738586 67.85112 \r\nL 144.758953 68.357108 \r\nL 144.765743 68.357108 \r\nL 144.772532 68.357108 \r\nL 144.813267 69.031759 \r\nL 144.887947 68.694434 \r\nL 145.030519 67.345132 \r\nL 145.044097 67.513795 \r\nL 145.050886 67.513795 \r\nL 145.125567 66.839144 \r\nL 145.173091 67.176469 \r\nL 145.17988 67.176469 \r\nL 145.186669 67.345132 \r\nM 147.175885 67.345132 \r\nL 147.230198 65.827167 \r\nL 147.2913 66.501818 \r\nL 147.37277 65.658504 \r\nL 147.379559 66.501818 \r\nL 147.461029 67.345132 \r\nL 147.406715 65.99583 \r\nL 147.494974 67.176469 \r\nL 147.664703 65.658504 \r\nL 147.786907 65.99583 \r\nL 147.9159 65.99583 \r\nL 147.929479 66.333155 \r\nL 148.038105 65.658504 \r\nL 148.044894 65.658504 \r\nL 148.167098 65.152516 \r\nL 148.207833 65.321179 \r\nL 148.275725 65.152516 \r\nL 148.282514 65.152516 \r\nL 148.377562 65.489842 \r\nL 148.397929 65.321179 \r\nL 148.404718 65.321179 \r\nL 148.452242 65.489842 \r\nL 148.513344 65.321179 \r\nL 148.540501 65.321179 \r\nL 148.662705 65.658504 \r\nL 148.683073 65.658504 \r\nL 148.696651 65.827167 \r\nL 148.791699 65.489842 \r\nL 148.907114 65.658504 \r\nL 149.008951 65.489842 \r\nL 149.01574 65.658504 \r\nL 149.022529 65.658504 \r\nL 149.124366 65.827167 \r\nL 149.131155 65.658504 \r\nL 149.137944 65.658504 \r\nL 149.17189 65.99583 \r\nL 149.25336 65.827167 \r\nL 149.341618 65.658504 \r\nM 188.26372 73.079665 \r\nL 188.277298 72.573677 \r\nL 188.284087 72.911002 \r\nL 256.250101 74.59763 \r\nL 256.392673 76.621582 \r\nL 256.514877 72.911002 \r\nL 256.555612 74.59763 \r\nL 256.671027 76.958908 \r\nL 256.677816 76.958908 \r\nL 256.718551 76.790245 \r\nL 256.72534 77.127571 \r\nL 256.786443 76.958908 \r\nL 256.901858 77.127571 \r\nL 256.922225 77.127571 \r\nL 256.929014 77.296233 \r\nL 256.96296 76.958908 \r\nL 257.024062 77.127571 \r\nL 257.085164 76.958908 \r\nL 257.214158 76.958908 \r\nL 257.315995 76.790245 \r\nL 257.282049 77.127571 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258.9997 76.284257 \r\nL 259.169428 76.284257 \r\nL 259.257687 76.621582 \r\nL 259.284844 76.45292 \r\nL 259.298422 76.45292 \r\nL 259.318789 76.621582 \r\nL 259.427415 75.778269 \r\nL 259.434205 75.946931 \r\nL 259.481728 74.428967 \r\nL 259.488518 74.091641 \r\nL 259.495307 75.609606 \r\nL 259.569987 75.440943 \r\nL 259.590355 75.778269 \r\nL 259.651457 74.428967 \r\nL 259.800818 71.055712 \r\nL 259.807607 72.405014 \r\nL 259.895866 69.70641 \r\nL 259.902655 70.043736 \r\nL 259.909444 70.212398 \r\nL 259.956968 68.694434 \r\nL 259.977335 68.019783 \r\nL 260.153853 67.176469 \r\nL 260.276057 63.971877 \r\nL 260.425418 62.453913 \r\nL 260.432207 62.791238 \r\nL 260.56799 67.176469 \r\nL 260.452575 62.622575 \r\nL 260.601935 65.152516 \r\nL 260.690194 61.610599 \r\nL 260.72414 62.116587 \r\nL 260.785242 62.622575 \r\nL 260.825977 60.935948 \r\nL 260.900657 67.85112 \r\nL 260.948181 66.839144 \r\nL 260.982127 65.321179 \r\nL 260.995705 65.658504 \r\nL 261.151855 72.067688 \r\nL 261.179012 70.043736 \r\nL 261.260481 66.164493 \r\nL 261.301216 66.670481 \r\nL 261.389475 70.212398 \r\nL 261.423421 70.043736 \r\nL 261.443788 68.694434 \r\nL 261.491312 74.260304 \r\nL 261.498101 71.899026 \r\nL 261.606727 75.103618 \r\nL 261.613516 74.934955 \r\nL 261.633884 74.428967 \r\nL 261.647462 75.103618 \r\nL 268.565589 214.756364 \r\nL 268.613113 67.85112 \r\nL 268.653848 68.694434 \r\nL 290.467333 70.718387 \r\nL 290.474122 71.393038 \r\nL 290.562381 70.043736 \r\nL 290.575959 70.549724 \r\nL 290.732109 66.839144 \r\nL 290.745687 67.513795 \r\nL 290.895048 70.718387 \r\nL 290.935783 69.875073 \r\nL 291.11909 62.28525 \r\nL 291.139457 62.791238 \r\nL 291.173403 62.453913 \r\nL 291.220927 63.465889 \r\nL 291.438179 68.188446 \r\nL 291.458546 67.176469 \r\nL 291.526438 64.815191 \r\nL 291.546805 67.682457 \r\nL 291.567173 66.839144 \r\nL 291.573962 66.670481 \r\nL 291.675799 70.381061 \r\nL 291.689377 70.043736 \r\nL 291.818371 74.091641 \r\nL 291.845527 73.41699 \r\nL 292.035623 68.357108 \r\nL 292.144249 72.573677 \r\nL 292.164616 71.899026 \r\nL 292.198562 70.718387 \r\nL 292.409025 70.718387 \r\nL 292.558386 71.899026 \r\nL 292.646645 70.718387 \r\nL 292.68059 71.055712 \r\nL 292.694169 71.055712 \r\nL 292.789217 72.742339 \r\nL 292.816373 72.067688 \r\nL 292.84353 71.730363 \r\nL 292.924999 72.067688 \r\nL 293.053993 71.5617 \r\nL 293.121884 71.5617 \r\nL 293.176197 70.549724 \r\nL 293.203354 71.899026 \r\nL 293.216932 71.899026 \r\nL 293.223721 71.899026 \r\nL 293.257667 72.405014 \r\nL 293.38666 72.742339 \r\nL 293.474919 74.59763 \r\nL 293.515654 74.091641 \r\nL 293.529232 73.922979 \r\nL 293.583545 74.428967 \r\nL 293.617491 74.091641 \r\nL 293.658226 73.41699 \r\nL 293.712539 74.428967 \r\nL 293.800797 71.224375 \r\nL 293.848321 71.730363 \r\nL 293.997682 74.091641 \r\nL 293.8619 71.5617 \r\nL 294.011261 73.079665 \r\nL 294.01805 73.079665 \r\nL 294.140254 75.27228 \r\nL 294.153832 75.103618 \r\nL 294.377874 75.103618 \r\nL 294.384663 74.260304 \r\nL 294.4865 74.59763 \r\nL 294.506867 74.766292 \r\nL 294.534024 73.248328 \r\nL 294.778433 69.031759 \r\nL 294.56797 73.922979 \r\nL 294.805589 69.200422 \r\nL 294.819167 69.200422 \r\nL 294.893848 69.369085 \r\nL 294.859902 68.863096 \r\nL 294.900637 69.031759 \r\nL 294.941372 69.369085 \r\nL 295.043209 66.670481 \r\nL 295.077155 67.176469 \r\nL 295.070365 65.827167 \r\nL 295.151835 67.007806 \r\nL 295.212937 62.28525 \r\nL 295.355509 62.28525 \r\nL 295.50487 69.537747 \r\nL 295.559183 67.682457 \r\nL 295.572761 68.188446 \r\nL 295.681387 65.99583 \r\nL 295.688177 66.333155 \r\nL 295.708544 63.465889 \r\nL 295.74249 63.803214 \r\nL 295.762857 63.128563 \r\nL 295.830748 64.309203 \r\nL 295.925796 70.043736 \r\nL 295.97332 69.70641 \r\nL 296.034422 66.839144 \r\nL 295.993688 70.718387 \r\nL 296.081946 69.200422 \r\nL 296.088735 70.887049 \r\nL 296.102314 66.670481 \r\nL 296.109103 69.200422 \r\nL 296.319566 68.525771 \r\nL 296.326355 63.465889 \r\nL 296.360301 70.549724 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298.397041 73.248328 \r\nL 298.40383 73.248328 \r\nL 298.451354 74.091641 \r\nL 298.485299 72.911002 \r\nL 298.519245 73.585653 \r\nL 298.587136 73.079665 \r\nL 298.63466 73.41699 \r\nL 298.763654 73.922979 \r\nL 298.804389 73.922979 \r\nL 298.87228 71.730363 \r\nL 298.824756 74.091641 \r\nL 298.926593 73.248328 \r\nL 299.014852 74.428967 \r\nL 299.048798 74.091641 \r\nL 299.069165 74.091641 \r\nL 299.123478 74.428967 \r\nL 299.551193 73.922979 \r\nL 299.57835 74.091641 \r\nL 299.605506 72.911002 \r\nL 299.632663 73.248328 \r\nL 299.639452 73.248328 \r\nL 299.741289 73.754316 \r\nL 299.768446 71.5617 \r\nL 299.843126 73.922979 \r\nL 299.849915 73.922979 \r\nL 299.877072 74.260304 \r\nL 299.911017 73.41699 \r\nL 299.938174 73.41699 \r\nL 300.060378 72.405014 \r\nL 300.230107 71.730363 \r\nL 300.270842 72.742339 \r\nL 300.338733 72.067688 \r\nL 300.365889 71.899026 \r\nL 300.426992 72.405014 \r\nL 300.44057 72.236351 \r\nL 300.583142 73.079665 \r\nL 300.6714 73.248328 \r\nL 300.705346 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114.778141 37.323165 \r\nL 114.85961 35.130549 \r\nL 114.873189 34.961886 \r\nL 114.988604 41.37107 \r\nL 115.002182 24.336134 \r\nL 115.09723 36.648514 \r\nL 115.463843 17.252299 \r\nL 115.470632 17.252299 \r\nL 115.491 17.083636 \r\nL 115.545313 17.92695 \r\nL 115.558891 17.758287 \r\nL 115.572469 17.92695 \r\nL 139.918301 59.923971 \r\nL 139.945458 60.598622 \r\nL 140.013349 59.249321 \r\nL 140.020138 59.249321 \r\nL 140.128765 60.935948 \r\nL 140.142343 60.42996 \r\nL 140.24418 60.598622 \r\nL 140.264547 58.911995 \r\nL 140.386752 60.935948 \r\nL 140.40033 60.935948 \r\nL 140.434276 60.261297 \r\nL 140.502167 61.273273 \r\nL 140.508956 61.104611 \r\nL 140.549691 59.923971 \r\nL 140.63116 60.42996 \r\nL 140.63795 60.42996 \r\nL 140.651528 60.261297 \r\nL 140.699052 61.273273 \r\nL 140.71263 61.104611 \r\nL 140.78731 61.947924 \r\nL 140.828045 61.610599 \r\nL 140.834834 61.610599 \r\nL 140.970617 60.767285 \r\nL 140.977406 61.273273 \r\nL 141.058876 60.261297 \r\nL 141.072454 60.261297 \r\nL 141.140345 60.261297 \r\nL 141.276128 59.586646 \r\nL 141.344019 59.586646 \r\nL 141.439067 59.080658 \r\nL 141.466224 59.249321 \r\nL 141.486591 59.249321 \r\nL 141.588428 60.092634 \r\nL 141.534115 59.080658 \r\nL 141.595217 59.923971 \r\nL 141.635952 59.249321 \r\nL 141.710633 59.586646 \r\nL 141.819259 60.935948 \r\nL 141.832837 60.092634 \r\nL 141.880361 59.417983 \r\nL 141.927885 60.935948 \r\nL 141.934674 60.935948 \r\nL 141.941463 61.104611 \r\nL 141.961831 59.249321 \r\nL 141.975409 59.249321 \r\nL 142.104402 59.249321 \r\nL 142.138348 60.092634 \r\nL 142.219818 59.417983 \r\nL 142.274131 59.417983 \r\nL 142.3556 72.742339 \r\nL 142.484594 72.236351 \r\nL 142.613587 64.14054 \r\nL 142.633955 64.477865 \r\nL 142.647533 64.646528 \r\nL 142.67469 63.803214 \r\nL 142.796894 60.767285 \r\nL 142.810472 61.610599 \r\nL 142.83084 60.42996 \r\nL 142.90552 60.598622 \r\nL 142.919098 60.598622 \r\nL 143.075248 61.779262 \r\nL 143.082038 61.779262 \r\nL 143.197453 65.152516 \r\nL 143.183875 61.610599 \r\nL 143.244977 63.297226 \r\nL 143.333235 61.610599 \r\nL 143.401127 62.116587 \r\nL 143.407916 62.116587 \r\nL 143.523331 61.779262 \r\nL 143.652325 62.28525 \r\nL 143.69306 62.28525 \r\nL 143.808475 62.453913 \r\nL 143.815264 62.453913 \r\nL 143.930679 67.513795 \r\nL 144.052884 65.658504 \r\nL 144.059673 65.658504 \r\nL 144.134353 65.321179 \r\nL 144.16151 65.827167 \r\nL 144.168299 65.827167 \r\nL 144.249768 67.007806 \r\nL 144.276925 65.99583 \r\nL 144.412708 64.983854 \r\nL 144.426286 65.99583 \r\nL 144.494177 64.646528 \r\nL 144.521334 65.321179 \r\nL 144.541701 64.983854 \r\nL 144.575647 65.99583 \r\nL 144.609593 65.658504 \r\nL 144.731797 67.682457 \r\nL 144.792899 67.176469 \r\nL 144.779321 68.863096 \r\nL 144.813267 68.188446 \r\nL 144.854001 68.863096 \r\nL 144.915104 67.682457 \r\nL 144.996573 67.85112 \r\nL 145.030519 67.345132 \r\nL 145.071254 67.513795 \r\nL 145.105199 67.007806 \r\nL 145.125567 67.007806 \r\nL 145.152723 67.007806 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149.294095 65.827167 \r\nL 149.341618 65.658504 \r\nM 188.26372 72.573677 \r\nL 188.270509 70.718387 \r\nL 188.284087 71.730363 \r\nL 256.250101 73.922979 \r\nL 256.25689 74.59763 \r\nL 256.317992 71.5617 \r\nL 256.33836 71.899026 \r\nL 256.351938 72.067688 \r\nL 256.426618 71.393038 \r\nL 256.460564 71.055712 \r\nL 256.508088 71.5617 \r\nL 256.521666 71.5617 \r\nL 256.664238 75.609606 \r\nL 256.671027 73.922979 \r\nL 256.766075 72.742339 \r\nL 256.772864 74.260304 \r\nL 256.779653 74.260304 \r\nL 256.861123 75.609606 \r\nL 256.80681 72.405014 \r\nL 256.901858 75.440943 \r\nL 256.96296 73.754316 \r\nL 256.983327 76.958908 \r\nL 256.996906 76.958908 \r\nL 257.03764 76.284257 \r\nL 257.085164 77.296233 \r\nL 257.227736 75.609606 \r\nL 257.241314 76.115594 \r\nL 257.248104 76.958908 \r\nL 257.315995 74.091641 \r\nL 257.343151 75.440943 \r\nL 257.451778 71.5617 \r\nL 257.465356 72.911002 \r\nL 257.478934 72.911002 \r\nL 257.499302 72.236351 \r\nL 257.560404 74.428967 \r\nL 257.573982 74.260304 \r\nL 257.594349 76.115594 \r\nL 257.662241 73.585653 \r\nL 257.66903 74.091641 \r\nL 257.798023 70.549724 \r\nL 257.804813 70.887049 \r\nL 257.859126 70.043736 \r\nL 257.893071 70.381061 \r\nL 258.022065 67.513795 \r\nL 258.028854 68.525771 \r\nL 258.042432 69.031759 \r\nL 258.0628 67.513795 \r\nL 258.205371 61.610599 \r\nL 258.286841 64.14054 \r\nL 258.313998 66.839144 \r\nL 258.341154 63.803214 \r\nL 258.368311 63.971877 \r\nL 258.476937 61.273273 \r\nL 258.381889 64.14054 \r\nL 258.483726 61.947924 \r\nL 258.504093 62.453913 \r\nL 258.571985 60.598622 \r\nL 258.578774 61.104611 \r\nL 258.599141 60.598622 \r\nL 258.653454 63.465889 \r\nL 258.660243 62.959901 \r\nL 258.6874 66.839144 \r\nL 258.694189 66.670481 \r\nL 258.816393 75.778269 \r\nL 258.911441 70.381061 \r\nL 258.850339 76.115594 \r\nL 258.938598 73.922979 \r\nL 258.945387 76.284257 \r\nL 258.979333 71.5617 \r\nL 258.9997 74.59763 \r\nL 259.169428 74.091641 \r\nL 259.176217 75.440943 \r\nL 259.278054 74.59763 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261.233325 65.321179 \r\nL 261.240114 64.477865 \r\nL 261.253692 66.501818 \r\nL 261.355529 65.827167 \r\nL 261.43021 64.14054 \r\nL 261.396264 67.176469 \r\nL 261.457366 66.333155 \r\nL 261.572782 68.863096 \r\nL 261.477734 65.152516 \r\nL 261.613516 67.682457 \r\nL 261.640673 66.839144 \r\nL 261.647462 69.200422 \r\nL 268.565589 71.730363 \r\nL 268.653848 67.345132 \r\nL 290.467333 69.70641 \r\nL 290.528435 69.875073 \r\nL 290.542013 69.031759 \r\nL 290.732109 62.453913 \r\nL 290.752477 66.164493 \r\nL 290.854314 71.224375 \r\nL 290.793211 65.321179 \r\nL 290.874681 69.031759 \r\nL 290.96294 66.501818 \r\nL 290.990096 66.670481 \r\nL 291.153035 63.634552 \r\nL 291.207349 64.477865 \r\nL 291.220927 64.309203 \r\nL 291.438179 61.779262 \r\nL 291.492492 62.116587 \r\nL 291.621486 64.815191 \r\nL 291.648642 64.477865 \r\nL 291.675799 65.99583 \r\nL 291.696166 65.827167 \r\nL 291.838738 70.043736 \r\nL 291.988099 67.176469 \r\nL 291.994888 67.345132 \r\nL 292.001677 68.357108 \r\nL 292.062779 65.152516 \r\nL 292.096725 65.99583 \r\nL 292.103514 65.827167 \r\nL 292.144249 67.176469 \r\nL 292.151038 67.007806 \r\nL 292.198562 68.357108 \r\nL 292.422603 67.682457 \r\nL 292.517651 70.549724 \r\nL 292.558386 70.043736 \r\nL 292.60591 67.176469 \r\nL 292.673801 68.863096 \r\nL 292.68738 68.525771 \r\nL 292.870686 71.224375 \r\nL 292.972523 69.537747 \r\nL 292.931788 71.730363 \r\nL 292.992891 70.212398 \r\nL 293.006469 70.549724 \r\nL 293.053993 69.70641 \r\nL 293.101517 70.212398 \r\nL 293.142252 68.357108 \r\nL 293.196565 70.381061 \r\nL 293.210143 70.043736 \r\nL 293.257667 71.5617 \r\nL 293.38666 69.70641 \r\nL 293.407028 70.212398 \r\nL 293.427395 72.236351 \r\nL 293.488497 68.188446 \r\nL 293.515654 70.381061 \r\nL 293.569967 69.200422 \r\nL 293.62428 70.212398 \r\nL 293.665015 72.742339 \r\nL 293.746484 71.730363 \r\nL 293.875478 68.525771 \r\nL 293.923002 70.212398 \r\nL 293.895845 67.682457 \r\nL 293.984104 69.200422 \r\nL 293.990893 69.200422 \r\nL 294.072363 70.043736 \r\nL 294.01805 69.031759 \r\nL 294.106308 69.875073 \r\nL 294.113098 69.875073 \r\nL 294.119887 70.043736 \r\nL 294.147043 68.525771 \r\nL 294.153832 68.525771 \r\nL 294.418609 70.043736 \r\nL 294.4865 71.5617 \r\nL 294.513656 69.369085 \r\nL 294.527235 70.043736 \r\nL 294.547602 71.055712 \r\nL 294.696963 68.019783 \r\nL 294.72412 68.863096 \r\nL 294.792011 67.85112 \r\nL 294.805589 68.694434 \r\nL 294.846324 67.176469 \r\nL 294.921004 67.85112 \r\nL 294.927794 67.85112 \r\nL 295.090733 62.453913 \r\nL 294.948161 68.188446 \r\nL 295.097522 63.465889 \r\nL 295.172202 63.128563 \r\nL 295.117889 63.971877 \r\nL 295.19257 63.971877 \r\nL 295.199359 64.14054 \r\nL 295.212937 63.465889 \r\nL 295.34872 62.959901 \r\nL 295.457346 64.309203 \r\nL 295.464135 63.971877 \r\nL 295.477713 63.634552 \r\nL 295.50487 65.152516 \r\nL 295.545605 64.477865 \r\nL 295.647442 67.345132 \r\nL 295.66102 65.321179 \r\nL 295.694966 65.489842 \r\nL 295.790014 63.297226 \r\nL 295.986898 67.345132 \r\nL 296.007266 66.164493 \r\nL 296.068368 63.634552 \r\nL 296.109103 64.14054 \r\nL 296.319566 64.646528 \r\nL 296.333144 63.803214 \r\nL 296.414614 66.164493 \r\nL 296.543607 64.983854 \r\nL 296.428192 66.333155 \r\nL 296.550396 65.489842 \r\nL 296.713336 69.031759 \r\nL 296.720125 68.694434 \r\nL 296.726914 68.525771 \r\nL 296.740492 70.212398 \r\nL 296.801594 73.079665 \r\nL 296.869486 72.911002 \r\nL 296.896642 73.41699 \r\nL 296.978112 67.682457 \r\nL 297.012058 68.188446 \r\nL 297.018847 68.188446 \r\nL 297.066371 68.357108 \r\nL 297.086738 67.682457 \r\nL 297.297201 71.5617 \r\nL 297.30399 71.224375 \r\nL 297.432984 66.333155 \r\nL 297.473719 65.99583 \r\nL 297.582345 67.345132 \r\nL 297.643447 65.152516 \r\nL 297.684182 67.513795 \r\nL 297.69776 67.176469 \r\nL 297.704549 67.176469 \r\nL 297.792808 71.899026 \r\nL 297.718127 65.489842 \r\nL 297.806386 71.5617 \r\nL 297.921801 73.585653 \r\nL 297.928591 73.585653 \r\nL 297.962536 73.248328 \r\nL 298.037217 73.754316 \r\nL 298.308782 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\n"
+     },
+     "metadata": {
+      "needs_background": "light"
+     }
+    }
+   ],
+   "source": [
+    "ds.PSAL.sel(TIME=slice(\"2020\",\"2021\")).plot.line(x='TIME');\n"
+   ]
+  },
+  {
+   "source": [
+    "Qualtity flags indicates not all values are good ()"
+   ],
+   "cell_type": "markdown",
+   "metadata": {}
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "output_type": "display_data",
+     "data": {
+      "text/plain": "<Figure size 432x288 with 1 Axes>",
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+     },
+     "metadata": {
+      "needs_background": "light"
+     }
+    }
+   ],
+   "source": [
+    "ds.PSAL_QC.sel(TIME=slice(\"2020\",\"2021\")).plot.line(x='TIME');"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "output_type": "execute_result",
+     "data": {
+      "text/plain": [
+       "<AxesSubplot:>"
+      ]
+     },
+     "metadata": {},
+     "execution_count": 7
+    },
+    {
+     "output_type": "display_data",
+     "data": {
+      "text/plain": "<Figure size 432x288 with 1 Axes>",
+      "image/svg+xml": "<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\r\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\r\n  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\r\n<!-- Created with matplotlib (https://matplotlib.org/) -->\r\n<svg height=\"245.2025pt\" version=\"1.1\" viewBox=\"0 0 388.0125 245.2025\" width=\"388.0125pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\r\n <metadata>\r\n  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\r\n   <cc:Work>\r\n    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\r\n    <dc:date>2021-02-02T13:59:37.094433</dc:date>\r\n    <dc:format>image/svg+xml</dc:format>\r\n    <dc:creator>\r\n     <cc:Agent>\r\n      <dc:title>Matplotlib v3.3.2, https://matplotlib.org/</dc:title>\r\n     </cc:Agent>\r\n    </dc:creator>\r\n   </cc:Work>\r\n  </rdf:RDF>\r\n 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+     },
+     "metadata": {
+      "needs_background": "light"
+     }
+    }
+   ],
+   "source": [
+    "pd.Series(ds.PSAL_QC.sel(TIME=slice(\"2020\",\"2021\")).values.astype(np.int32).flatten()).value_counts().plot.bar() # simple on-liner to get distriution of values"
+   ]
+  },
+  {
+   "source": [
+    "Most values have a qc-flag ==1 (good data). But some have 2,3,4, which are varying degrees of confidence that the data is bad."
+   ],
+   "cell_type": "markdown",
+   "metadata": {}
+  }
+ ]
+}
\ No newline at end of file


Test patch:
diff --git a/tests/data/BO_TS_MO_FINO2.nc b/tests/data/BO_TS_MO_FINO2.nc
new file mode 100644
index 0000000..8853a94
Binary files /dev/null and b/tests/data/BO_TS_MO_FINO2.nc differ