diff --git a/examples/data/equity_analysis/analyses.ini b/examples/data/equity_analysis/analyses.ini
new file mode 100644
index 000000000..05b45ae21
--- /dev/null
+++ b/examples/data/equity_analysis/analyses.ini
@@ -0,0 +1,12 @@
+[project]
+name = pontianak
+
+[analysis1]
+name = optimal route origin destination
+analysis = optimal_route_origin_destination
+weighing = length
+save_traffic = True #True if you want to record the traffic in each edge
+equity_weight = region_weight.csv #equity-weighted factors for each region, should be stored in static/network. Note that 'region' and 'region_var' should present in network.ini
+save_gpkg = True
+save_csv = True
+
diff --git a/examples/data/equity_analysis/network.ini b/examples/data/equity_analysis/network.ini
new file mode 100644
index 000000000..b8b80a3ae
--- /dev/null
+++ b/examples/data/equity_analysis/network.ini
@@ -0,0 +1,43 @@
+[project]
+name = pontianak_newra2ce
+
+[network]
+directed = False
+source = OSM download
+primary_file = None
+diversion_file = Pontianak_4326_buffer_0_025deg.geojson
+file_id = None
+polygon = Pontianak_4326.geojson
+network_type = drive
+road_types = motorway,motorway_link,trunk,trunk_link,primary,primary_link,secondary,secondary_link,tertiary,tertiary_link
+save_gpkg = True
+
+[origins_destinations]
+origins = origins_points.shp # Must be in the static/network folder, belongs to this analysis
+destinations = osm_health_point.shp # gis_osm_pois_pontianak.shp # Must be in the static/network folder, belongs to this analysis
+origins_names = A
+destinations_names = B
+id_name_origin_destination = OBJECTID #default if origins is a tif file = OBJECTID
+origin_count = values #necessary if traffic on each edge would be recorded in optimal_route_origin_destination
+origin_out_fraction = 1
+category = category
+region = region.shp #necessary for distributional / equity analysis
+region_var = DESA #necessary for distributional / equity analysis
+
+[hazard]
+hazard_map = None
+hazard_id = 1
+hazard_field_name = waterdepth
+aggregate_wl = max
+hazard_crs = None #EPSG:4326
+
+[cleanup]
+snapping_threshold = None
+pruning_threshold = None
+segmentation_length = None
+merge_lines = None
+ignore_intersections = None
+
+
+[isolation]
+locations = None
\ No newline at end of file
diff --git a/examples/data/equity_analysis/static/network/Pontianak_4326.geojson b/examples/data/equity_analysis/static/network/Pontianak_4326.geojson
new file mode 100644
index 000000000..fd865ff2b
--- /dev/null
+++ b/examples/data/equity_analysis/static/network/Pontianak_4326.geojson
@@ -0,0 +1,8 @@
+{
+"type": "FeatureCollection",
+"name": "Pontianak_4326",
+"crs": { "type": "name", "properties": { "name": "urn:ogc:def:crs:OGC:1.3:CRS84" } },
+"features": [
+{ "type": "Feature", "properties": { "PROVNO": "61", "KABKOTNO": "71", "KECNO": "31", "DESANO": "5", "PROVINSI": "KALIMANTAN BARAT", "KABKOT": "PONTIANAK", "KECAMATAN": "PONTIANAK KOTA", "DESA": "SUNGAI JAWI", "IDDESA": "6171031005", "SUMBER": "BPS", "MALE": 17859.0, "FEM": 17841.0, "HSHOLDS": 7212.0, "HHSIZE": 4.95008, "POP2016": "35700", "WFLOW": "Kalimantan", "2010_BestE": "38025", "2016_BestE": "42053", "2017_BestE": "42666", "urban/rura": "1", "V2_Water": 355.0509, "V2_Terr": 135.40344, "V2_Terr_ha": 0.18363, "IDDESA_nw": null, "Pop2017_UD": "43712", "area_ha": 738.723, "Village": "Sungai Jawi", "FGT0_NPL": 4.43, "SE_FGT0_NP": 3.03, "FGT1_NPL": 1.08, "SE_FGT1_NP": 1.08, "FGT2_NPL": 0.41, "SE_FGT2_NP": 0.41, "FGT0_USD3.": 14.35, "SE_FGT0_US": 12.42, "FGT1_USD3.": 4.07, "SE_FGT1_US": 3.94, "FGT2_USD3.": 1.7, "SE_FGT2_US": 1.69, "Gini": 0.39, "SE_Gini": 0.01, "NA_02": "No", "FA_02": 2, "FA_03": 1, "PA_01": 6, "PA_02": 5, "PA_03": 6, "PA_04": 0, "PA_05": 11, "PA_06": 1, "PA_07": 1, "PA_08": "Yes", "NA_03": "No", "PA_09": "Yes", "PA_10": "Yes", "PA_11": "Yes", "PA_12": "No", "PA_13": "Yes", "PA_14": "Yes", "HA_01": "No", "HA_02": 89, "HA_03": "Others", "SA_01": "No", "NA_04": "No", "SA_02": "No", "NA_05": "No", "NA_06": "No", "NA_07": "No", "NA_08": "No", "NA_09": "No", "FA_01": 3, "NA_01": "No", "baseT001": 2449315.0, "measT001": 73401.0234375, "baseT010": 10281386.000000002, "measT010": 574973.9375, "baseT025": 13701082.0, "measT025": 993459.5, "baseT100": 18641800.0, "measT100": 2082467.5, "baseEAD": 5841443.4177276064, "measEAD": 320417.95456254785, "benefit": 5521025.4631650588, "Barea_ha": 702, "BBPS_HH19": "12934", "BBPS_pop19": 44072, "Bpopdens19": 6278, "BBPS_f": 21927, "Btoddler": 4297, "Belderly": 2931, "BBPS_healt": 5, "Bmalnutrit": 3, "Bhealthpro": "2811", "Bfloodeven": 0, "healthprob": 2811, "popgrowth": 1.235, "%benefit": 0.945, "SMP_1m": 113.451, "SMA_1m": 136.141, "health_1m": 63781.993, "bank_1m": 68.07, "worldpop_s": 16867.33182144165, 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diff --git a/examples/data/equity_analysis/static/network/Pontianak_4326_buffer_0_025deg.geojson b/examples/data/equity_analysis/static/network/Pontianak_4326_buffer_0_025deg.geojson
new file mode 100644
index 000000000..7ea4aa1d9
--- /dev/null
+++ b/examples/data/equity_analysis/static/network/Pontianak_4326_buffer_0_025deg.geojson
@@ -0,0 +1,8 @@
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+]
+}
diff --git a/examples/data/equity_analysis/static/network/origins_points.cpg b/examples/data/equity_analysis/static/network/origins_points.cpg
new file mode 100644
index 000000000..cd89cb975
--- /dev/null
+++ b/examples/data/equity_analysis/static/network/origins_points.cpg
@@ -0,0 +1 @@
+ISO-8859-1
\ No newline at end of file
diff --git a/examples/data/equity_analysis/static/network/origins_points.dbf b/examples/data/equity_analysis/static/network/origins_points.dbf
new file mode 100644
index 000000000..7e2e444e0
Binary files /dev/null and b/examples/data/equity_analysis/static/network/origins_points.dbf differ
diff --git a/examples/data/equity_analysis/static/network/origins_points.prj b/examples/data/equity_analysis/static/network/origins_points.prj
new file mode 100644
index 000000000..f45cbadf0
--- /dev/null
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+]
+}
diff --git a/examples/data/equity_analysis/static/network/region.prj b/examples/data/equity_analysis/static/network/region.prj
new file mode 100644
index 000000000..f45cbadf0
--- /dev/null
+++ b/examples/data/equity_analysis/static/network/region.prj
@@ -0,0 +1 @@
+GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]]
\ No newline at end of file
diff --git a/examples/data/equity_analysis/static/network/region.qmd b/examples/data/equity_analysis/static/network/region.qmd
new file mode 100644
index 000000000..b500990b0
--- /dev/null
+++ b/examples/data/equity_analysis/static/network/region.qmd
@@ -0,0 +1,26 @@
+<!DOCTYPE qgis PUBLIC 'http://mrcc.com/qgis.dtd' 'SYSTEM'>
+<qgis version="3.22.10-Bia?owie?a">
+  <identifier></identifier>
+  <parentidentifier></parentidentifier>
+  <language></language>
+  <type>dataset</type>
+  <title></title>
+  <abstract></abstract>
+  <links/>
+  <fees></fees>
+  <encoding></encoding>
+  <crs>
+    <spatialrefsys>
+      <wkt></wkt>
+      <proj4></proj4>
+      <srsid>0</srsid>
+      <srid>0</srid>
+      <authid></authid>
+      <description></description>
+      <projectionacronym></projectionacronym>
+      <ellipsoidacronym></ellipsoidacronym>
+      <geographicflag>false</geographicflag>
+    </spatialrefsys>
+  </crs>
+  <extent/>
+</qgis>
diff --git a/examples/data/equity_analysis/static/network/region.shp b/examples/data/equity_analysis/static/network/region.shp
new file mode 100644
index 000000000..6aeccf807
Binary files /dev/null and b/examples/data/equity_analysis/static/network/region.shp differ
diff --git a/examples/data/equity_analysis/static/network/region.shx b/examples/data/equity_analysis/static/network/region.shx
new file mode 100644
index 000000000..e0c7f37f2
Binary files /dev/null and b/examples/data/equity_analysis/static/network/region.shx differ
diff --git a/examples/data/equity_analysis/static/network/region_weight.csv b/examples/data/equity_analysis/static/network/region_weight.csv
new file mode 100644
index 000000000..187cb3955
--- /dev/null
+++ b/examples/data/equity_analysis/static/network/region_weight.csv
@@ -0,0 +1,30 @@
+region;weight
+SUNGAI JAWI;0.441758257
+PARIT TOKAYA;0.153340981
+BATU LAYANG;1.160449143
+SUNGAI BANGKONG;0.423991044
+BENUA MELAYU DARAT;0.992460846
+SIANTAN HULU;1.469602714
+BANSIR LAUT;0.032957022
+SIANTAN TENGAH;3.483517402
+SUNGAI JAWI DALAM;1.272954571
+AKCAYA;0.380242685
+KOTA BARU;0.536064278
+SIANTAN HILIR;3.123689118
+PAL LIMA;0.79156505
+SUNGAI BELIUNG;0.94229261
+BENUA MELAYU LAUT;2.444064492
+BANSIR DARAT;0.012661925
+TANJUNG HILIR;3.602120813
+BANJAR SERASAN;2.444064492
+DARAT SEKIP;2.505429248
+DALAM BUGIS;1.32424381
+TANJUNG HULU;0.127506152
+SAIGON;0.254129908
+BANGKA BELITUNG DARAT;0.069727254
+SUNGAI JAWI LUAR;2.748538215
+TENGAH;0.449771849
+BANGKA BELITUNG LAUT;0.345899041
+MARIANA;0.463968963
+PARIT MAYOR;0.385813932
+TAMBELAN SAMPIT;6.964804054
diff --git a/examples/data/equity_analysis/static/readme.txt b/examples/data/equity_analysis/static/readme.txt
new file mode 100644
index 000000000..e69de29bb
diff --git a/examples/example_equity_analysis.ipynb b/examples/example_equity_analysis.ipynb
new file mode 100644
index 000000000..bf5d637fd
--- /dev/null
+++ b/examples/example_equity_analysis.ipynb
@@ -0,0 +1,2047 @@
+{
+ "cells": [
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "id": "e0bf8629",
+   "metadata": {},
+   "source": [
+    "# RA2CE feature: Equity analysis"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fb251586",
+   "metadata": {},
+   "source": [
+    "This notebook is a rather technical notebook. The recommended user is a user with background knowledge of network criticality. \n",
+    "\n",
+    "In this notebook, we will perform criticality analysis with three different distributive principles: utilitarian, egalitarian and prioritarian principles. For more background knowledge on these principles and the application on transport network criticality analysis, please read: https://www.sciencedirect.com/science/article/pii/S0965856420308077 \n",
+    "\n",
+    "The purpose of the equity analysis performd in this notebook is providing insight into how different distributive principles can result in different prioritizations of the network. While we usually prioritize network interventions based on the number of people that use the road, equity principles allow us to also take into account the function of the network for for example underpriviliged communities. \n",
+    "Depending on the equity principle applied, your network prioritization might change, which can change decision-aking.\n",
+    "\n",
+    "The RA2CE analysis is set up generically. The user can determine the equity weights themselves. This can for example be GINI-coefficients or social vulnerability scores. The user-defined equity weights will feed into the prioritarian principle.\n",
+    "\n",
+    "The three applied principles are explained below:"
+   ]
+  },
+  {
+   "attachments": {
+    "image.png": {
+     "image/png": 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+    }
+   },
+   "cell_type": "markdown",
+   "id": "fe73ccb4",
+   "metadata": {},
+   "source": [
+    "![image.png](attachment:image.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bb771623",
+   "metadata": {},
+   "source": [
+    "### For new users\n",
+    "\n",
+    "If you have not checked out the previous RA2CE examples and you want to run your own RA2CE analysis, we advise you to first familiarize yourself with those notebooks. In this current notebook we will not provide extensive explanations as to how to run RA2CE and create the correct setups. We will assume the user has this knowledge already. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7256f804",
+   "metadata": {},
+   "source": [
+    "# Imports"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ea3f682f",
+   "metadata": {},
+   "source": [
+    "Packages import"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "e67d001f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import ast\n",
+    "import random\n",
+    "import sys\n",
+    "import webbrowser\n",
+    "import geopandas as gpd\n",
+    "import pandas as pd\n",
+    "from IPython.display import display\n",
+    "import matplotlib.pyplot as plt\n",
+    "from matplotlib.pyplot import get_cmap\n",
+    "from matplotlib.colors import to_hex\n",
+    "from pathlib import Path\n",
+    "import rasterio\n",
+    "import folium"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "67d38a12",
+   "metadata": {},
+   "source": [
+    "Set the path to your equity analysis data folder"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "99350e41",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "root_dir = Path(\"data\", \"equity_analysis\")\n",
+    "assert root_dir.exists()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cb60c4e8",
+   "metadata": {},
+   "source": [
+    "# Inspect data and get familiar with the use-case"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "32ad1f48",
+   "metadata": {},
+   "source": [
+    "We will first show you the data that will be used in this use case on Pontianak Indonesia"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "675c06b8",
+   "metadata": {},
+   "source": [
+    "### 1. Using equity weights to delineate more vulnerable areas"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "184a1fc2",
+   "metadata": {},
+   "source": [
+    "For the equity analysis, the user can assign equity weights which can be used in the criticality analysis. In this analysis we use a region weights file (region_weight.csv) which holds weights for specific areas in Pontianak Indonesia. You then also need a shapefile delineating the regions in question. We will inspect both files in this example and see which areas of Pontianak are more vulnerable according to this user-specified equity-weight file"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "50e0e257",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# load the files\n",
+    "path_network = root_dir / \"static\" / \"network\"\n",
+    "path_region_weights = path_network / \"region_weight.csv\"\n",
+    "path_regions = path_network / \"region.shp\"\n",
+    "\n",
+    "region_weigths = pd.read_csv(path_region_weights, sep=';')\n",
+    "regions = gpd.read_file(path_regions, driver = \"SHP\")\n",
+    "\n",
+    "#Merge the shapefile and the weights csv file:\n",
+    "region_weights_plot = pd.merge(regions, region_weigths, left_on='DESA', right_on='region')\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3625082a",
+   "metadata": {},
+   "source": [
+    "Which regions are more vulnerable?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "900749e0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "    &lt;script src=&quot;https://cdnjs.cloudflare.com/ajax/libs/d3/3.5.5/d3.min.js&quot;&gt;&lt;/script&gt;\n",
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+       "            &lt;div class=&quot;folium-map&quot; id=&quot;map_462d83635a66945f72d8bdb40f3efa52&quot; &gt;&lt;/div&gt;\n",
+       "        \n",
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+       "    \n",
+       "    \n",
+       "            var map_462d83635a66945f72d8bdb40f3efa52 = L.map(\n",
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+       "            L.control.scale().addTo(map_462d83635a66945f72d8bdb40f3efa52);\n",
+       "\n",
+       "            \n",
+       "\n",
+       "        \n",
+       "    \n",
+       "            var tile_layer_f85abcee3d053f562f104a6dada94849 = L.tileLayer(\n",
+       "                &quot;https://cartodb-basemaps-{s}.global.ssl.fastly.net/light_all/{z}/{x}/{y}.png&quot;,\n",
+       "                {&quot;attribution&quot;: &quot;\\u0026copy; \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://www.openstreetmap.org/copyright\\&quot;\\u003eOpenStreetMap\\u003c/a\\u003e contributors \\u0026copy; \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://cartodb.com/attributions\\&quot;\\u003eCartoDB\\u003c/a\\u003e, CartoDB \\u003ca target=\\&quot;_blank\\&quot; href =\\&quot;http://cartodb.com/attributions\\&quot;\\u003eattributions\\u003c/a\\u003e&quot;, &quot;detectRetina&quot;: false, &quot;maxNativeZoom&quot;: 18, &quot;maxZoom&quot;: 18, &quot;minZoom&quot;: 0, &quot;noWrap&quot;: false, &quot;opacity&quot;: 1, &quot;subdomains&quot;: &quot;abc&quot;, &quot;tms&quot;: false}\n",
+       "            );\n",
+       "        \n",
+       "    \n",
+       "                tile_layer_f85abcee3d053f562f104a6dada94849.addTo(map_462d83635a66945f72d8bdb40f3efa52);\n",
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+       "            map_462d83635a66945f72d8bdb40f3efa52.fitBounds(\n",
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+       "                {}\n",
+       "            );\n",
+       "        \n",
+       "    \n",
+       "        function geo_json_bf7208d105ff72056f38887081b418f5_styler(feature) {\n",
+       "            switch(feature.id) {\n",
+       "                case &quot;0&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#fee8de&quot;, &quot;fillColor&quot;: &quot;#fee8de&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;1&quot;: case &quot;14&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ffece4&quot;, &quot;fillColor&quot;: &quot;#ffece4&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;2&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#fff4ee&quot;, &quot;fillColor&quot;: &quot;#fff4ee&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;3&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ffede5&quot;, &quot;fillColor&quot;: &quot;#ffede5&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;4&quot;: case &quot;13&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#fc9b7c&quot;, &quot;fillColor&quot;: &quot;#fc9b7c&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;5&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#fff2eb&quot;, &quot;fillColor&quot;: &quot;#fff2eb&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;6&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#fedbcc&quot;, &quot;fillColor&quot;: &quot;#fedbcc&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;7&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#fff2ec&quot;, &quot;fillColor&quot;: &quot;#fff2ec&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;8&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#fff0e8&quot;, &quot;fillColor&quot;: &quot;#fff0e8&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;10&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#f96346&quot;, &quot;fillColor&quot;: &quot;#f96346&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;11&quot;: case &quot;12&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#fff5f0&quot;, &quot;fillColor&quot;: &quot;#fff5f0&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
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+       "                case &quot;17&quot;: case &quot;26&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#feeae1&quot;, &quot;fillColor&quot;: &quot;#feeae1&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;18&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#fc9879&quot;, &quot;fillColor&quot;: &quot;#fc9879&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
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+       "                    return {&quot;color&quot;: &quot;#fdd0bc&quot;, &quot;fillColor&quot;: &quot;#fdd0bc&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
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+       "                    return {&quot;color&quot;: &quot;#fb6b4b&quot;, &quot;fillColor&quot;: &quot;#fb6b4b&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;27&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#fb7b5b&quot;, &quot;fillColor&quot;: &quot;#fb7b5b&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;28&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#fdd4c2&quot;, &quot;fillColor&quot;: &quot;#fdd4c2&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                default:\n",
+       "                    return {&quot;color&quot;: &quot;#fdcdb9&quot;, &quot;fillColor&quot;: &quot;#fdcdb9&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "            }\n",
+       "        }\n",
+       "        function geo_json_bf7208d105ff72056f38887081b418f5_highlighter(feature) {\n",
+       "            switch(feature.id) {\n",
+       "                default:\n",
+       "                    return {&quot;fillOpacity&quot;: 0.75};\n",
+       "            }\n",
+       "        }\n",
+       "        function geo_json_bf7208d105ff72056f38887081b418f5_pointToLayer(feature, latlng) {\n",
+       "            var opts = {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;#3388ff&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: true, &quot;fillColor&quot;: &quot;#3388ff&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 2, &quot;stroke&quot;: true, &quot;weight&quot;: 3};\n",
+       "            \n",
+       "            let style = geo_json_bf7208d105ff72056f38887081b418f5_styler(feature)\n",
+       "            Object.assign(opts, style)\n",
+       "            \n",
+       "            return new L.CircleMarker(latlng, opts)\n",
+       "        }\n",
+       "\n",
+       "        function geo_json_bf7208d105ff72056f38887081b418f5_onEachFeature(feature, layer) {\n",
+       "            layer.on({\n",
+       "                mouseout: function(e) {\n",
+       "                    if(typeof e.target.setStyle === &quot;function&quot;){\n",
+       "                        geo_json_bf7208d105ff72056f38887081b418f5.resetStyle(e.target);\n",
+       "                    }\n",
+       "                },\n",
+       "                mouseover: function(e) {\n",
+       "                    if(typeof e.target.setStyle === &quot;function&quot;){\n",
+       "                        const highlightStyle = geo_json_bf7208d105ff72056f38887081b418f5_highlighter(e.target.feature)\n",
+       "                        e.target.setStyle(highlightStyle);\n",
+       "                    }\n",
+       "                },\n",
+       "            });\n",
+       "        };\n",
+       "        var geo_json_bf7208d105ff72056f38887081b418f5 = L.geoJson(null, {\n",
+       "                onEachFeature: geo_json_bf7208d105ff72056f38887081b418f5_onEachFeature,\n",
+       "            \n",
+       "                style: geo_json_bf7208d105ff72056f38887081b418f5_styler,\n",
+       "                pointToLayer: geo_json_bf7208d105ff72056f38887081b418f5_pointToLayer,\n",
+       "        });\n",
+       "\n",
+       "        function geo_json_bf7208d105ff72056f38887081b418f5_add (data) {\n",
+       "            geo_json_bf7208d105ff72056f38887081b418f5\n",
+       "                .addData(data);\n",
+       "        }\n",
+       "            geo_json_bf7208d105ff72056f38887081b418f5_add({&quot;bbox&quot;: [109.27209867200008, -0.097412109999944, 109.38412129200009, 0.038096201000034], &quot;features&quot;: [{&quot;bbox&quot;: [109.30385344200005, -0.07981471499994, 109.32397781900005, -0.050868752999969], &quot;geometry&quot;: {&quot;coordinates&quot;: [[[109.32397781900005, -0.058267891999942], [109.32387856700007, -0.058367208999925], [109.32354943400009, -0.058706853999973], [109.32320381700004, -0.059119392999945], [109.32297669700007, -0.059392762999954], [109.32270514000004, -0.059750628999958], [109.32253233000006, -0.059984236999984], [109.32234470700007, -0.060287429999967], [109.32220151900009, -0.060570742999971], [109.32195464400007, -0.06104293099998], [109.32173739600006, -0.061400797999968], [109.32124512600006, -0.06211109199995], [109.32116959100006, -0.062240790999971], [109.32102640500005, -0.062449545999925], [109.32065146700006, -0.063019663999959], [109.32010804100008, 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[109.32528441100004, 0.001867594000028], [109.32523767900005, 0.001820547000015], [109.32517395300005, 0.001752115000037], [109.32511872500004, 0.001735007000033], [109.3250677440001, 0.001696514000063], [109.32503375800007, 0.001649467000058], [109.32499127400007, 0.00159814300002], [109.32497003200007, 0.00152971100005], [109.32497428100004, 0.001461279000066], [109.32500401900006, 0.001427063000054], [109.32499552300004, 0.001392847000035], [109.32493604600006, 0.001320138000036], [109.32492754900005, 0.001251706000056], [109.32486382400003, 0.001183275000079], [109.32485532700008, 0.001080627000028], [109.32481709200005, 0.000965148000035], [109.32473637300006, 0.000862500000037], [109.32463016400004, 0.000734190000066], [109.32448996800008, 0.000640096000042], [109.32435402100005, 0.000464740000037], [109.32361905500005, -0.00044625899994], [109.32284128100008, -0.001485642999973], [109.32184461800007, -0.000894201999919], [109.32184461800007, -0.000586019999962], [109.32136052400006, -0.000220501999928], [109.32060590600008, -3.4158999936e-05], [109.31995095400003, 0.000281189000023], [109.31988688300004, 0.000166517000024], [109.31939567000008, 0.000367193000053], [109.31896140900005, 0.000524867000028], [109.31797898300005, 0.000954887000038], [109.31767998300006, 0.001091060000024], [109.31730979400005, 0.00122006600003], [109.31625617800006, 0.001614250000038], [109.31587887000006, 0.001728922000042], [109.31592870300007, 0.001793425000076], [109.31543749100007, 0.001900930000026], [109.31478254100006, 0.002144607000041], [109.31397809200007, 0.00250295500007], [109.31386418800008, 0.002467120000067], [109.31365061800005, 0.002524456000056], [109.31222681600008, 0.002875636000054], [109.31172136600009, 0.003112146000043], [109.31166828700009, 0.003046167000043], [109.31135829700008, 0.003140813000078], [109.31035451700006, 0.003527828000072], [109.30958566500004, 0.003800172000061], [109.30892359800004, 0.003936343000028], [109.30833272100006, 0.004000845000056], [109.30780591600008, 0.004108348000043], [109.30712249300008, 0.004301855000053], [109.30626821400006, 0.004567030000024], [109.30539257900006, 0.004774870000061], [109.30346333500006, 0.004968373000052], [109.30260905900009, 0.004961204000042], [109.30151273800006, 0.00490386600007], [109.30095745800008, 0.004903864000025], [109.30042353600004, 0.004982699000038], [109.30048760600005, 0.005212041000055], [109.29905669200008, 0.006193908000062], [109.29832343900006, 0.006580920000035], [109.29800308500006, 0.006781593000034], [109.29713457100007, 0.007233106000062], [109.29629453300004, 0.007734787000053], [109.29519109600005, 0.007999959000079], [109.29516262000004, 0.007956957000034], [109.29425851400003, 0.008114626000071], [109.29420156200007, 0.008179128000058], [109.29359645200009, 0.008308130000045], [109.29245127900003, 0.008305618000059], [109.29189502700007, 0.008336790000039], [109.29085566400005, 0.008308118000062], [109.28998918400004, 0.008419383000038], [109.29000931600007, 0.008467579000074], [109.29116948500007, 0.011245046000062], [109.29136784900005, 0.011701511000076], [109.29157565800006, 0.012157977000069], [109.29180235900009, 0.012757088000057], [109.29180235800004, 0.012928262000061], [109.29214240700009, 0.013888741000066], [109.29237105800007, 0.014610442000048], [109.29337035800006, 0.017835269000045], [109.29393839100004, 0.019589474000045], [109.29525005800008, 0.023369927000038], [109.29585804200008, 0.025205933000053], [109.29646335500007, 0.02688932400002], [109.29671546600008, 0.027631266000079], [109.29685035600005, 0.028028235000023], [109.29747160200009, 0.029819905000076], [109.29975088000005, 0.029070227000032], [109.30206311800004, 0.028834107000025], [109.30253983900008, 0.028788558000025], [109.30569144800006, 0.028827776000069], [109.30571087300007, 0.030734099000028], [109.30569790000004, 0.030936482000075], [109.30571085900006, 0.031641560000034], [109.30576270900008, 0.03331938600008], [109.30700779200004, 0.033234537000063], [109.31033118700009, 0.034069227000038], [109.30969692700006, 0.03614532500006], [109.30925581500009, 0.038096201000034], [109.31165960800007, 0.037560426000032], [109.31274126600005, 0.037279978000068], [109.31456033200004, 0.036942169000041], [109.31631267700006, 0.036562420000058], [109.31728272500004, 0.036352202000047], [109.31860611200005, 0.036066734000031], [109.31921109000007, 0.035933515000065], [109.31987278400004, 0.035762231000029], [109.32082313500007, 0.03557257400007], [109.32138200400004, 0.035461141000044]]], &quot;type&quot;: &quot;Polygon&quot;}, &quot;id&quot;: &quot;28&quot;, &quot;properties&quot;: {&quot;2010_BestE&quot;: &quot;19057&quot;, &quot;2016_BestE&quot;: &quot;21076&quot;, &quot;2017_BestE&quot;: &quot;21383&quot;, &quot;DESA&quot;: &quot;BATU LAYANG&quot;, &quot;DESANO&quot;: &quot;1&quot;, &quot;FA_01&quot;: 0, &quot;FA_02&quot;: 2, &quot;FA_03&quot;: 0, &quot;FEM&quot;: 10251.0, &quot;FGT0_NPL&quot;: 7.18, &quot;FGT0_USD3.&quot;: 20.39, &quot;FGT1_NPL&quot;: 1.85, &quot;FGT1_USD3.&quot;: 6.24, &quot;FGT2_NPL&quot;: 0.73, &quot;FGT2_USD3.&quot;: 2.75, &quot;Gini&quot;: 0.42, &quot;HA_01&quot;: &quot;No&quot;, &quot;HA_02&quot;: 2, &quot;HA_03&quot;: &quot;Others&quot;, &quot;HHSIZE&quot;: 4.68796, &quot;HSHOLDS&quot;: 4509.0, &quot;ID&quot;: 29, &quot;IDDESA&quot;: &quot;6171040001&quot;, &quot;IDDESA_nw&quot;: null, &quot;KABKOT&quot;: &quot;PONTIANAK&quot;, &quot;KABKOTNO&quot;: &quot;71&quot;, &quot;KECAMATAN&quot;: &quot;PONTIANAK UTARA&quot;, &quot;KECNO&quot;: &quot;40&quot;, &quot;MALE&quot;: 10887.0, &quot;NA_01&quot;: &quot;No&quot;, &quot;NA_02&quot;: &quot;No&quot;, &quot;NA_03&quot;: &quot;No&quot;, &quot;NA_04&quot;: &quot;No&quot;, &quot;NA_05&quot;: &quot;No&quot;, &quot;NA_06&quot;: &quot;No&quot;, &quot;NA_07&quot;: &quot;No&quot;, &quot;NA_08&quot;: &quot;No&quot;, &quot;NA_09&quot;: &quot;No&quot;, &quot;PA_01&quot;: 6, &quot;PA_02&quot;: 3, &quot;PA_03&quot;: 2, &quot;PA_04&quot;: 0, &quot;PA_05&quot;: 13, &quot;PA_06&quot;: 2, &quot;PA_07&quot;: 0, &quot;PA_08&quot;: &quot;Yes&quot;, &quot;PA_09&quot;: &quot;Yes&quot;, &quot;PA_10&quot;: &quot;Yes&quot;, &quot;PA_11&quot;: &quot;No&quot;, &quot;PA_12&quot;: &quot;No&quot;, &quot;PA_13&quot;: &quot;Yes&quot;, &quot;PA_14&quot;: &quot;Yes&quot;, &quot;POP2016&quot;: &quot;21138&quot;, &quot;PROVINSI&quot;: &quot;KALIMANTAN BARAT&quot;, &quot;PROVNO&quot;: &quot;61&quot;, &quot;Pop2017_UD&quot;: &quot;21907&quot;, &quot;SA_01&quot;: &quot;No&quot;, &quot;SA_02&quot;: &quot;No&quot;, &quot;SE_FGT0_NP&quot;: 3.93, &quot;SE_FGT0_US&quot;: 16.39, &quot;SE_FGT1_NP&quot;: 1.84, &quot;SE_FGT1_US&quot;: 5.91, &quot;SE_FGT2_NP&quot;: 0.73, &quot;SE_FGT2_US&quot;: 2.7, &quot;SE_Gini&quot;: 0.02, &quot;SUMBER&quot;: &quot;BPS&quot;, &quot;V2_Terr&quot;: 67.8597, &quot;V2_Terr_ha&quot;: 0.05955, &quot;V2_Water&quot;: 177.9397, &quot;Village&quot;: &quot;Batu Layang&quot;, &quot;WFLOW&quot;: &quot;Kalimantan&quot;, &quot;__folium_color&quot;: &quot;#fdd4c2&quot;, &quot;area_ha&quot;: 1141.606, &quot;baseEAD&quot;: 4849877.0169887915, &quot;baseT001&quot;: 2239166.0, &quot;baseT010&quot;: 8233516.5, &quot;baseT025&quot;: 10919452.0, &quot;baseT100&quot;: 15163832.0, &quot;benefit&quot;: 4839195.817593007, &quot;measEAD&quot;: 10681.199395784393, &quot;measT001&quot;: 0.0, &quot;measT010&quot;: 0.0, &quot;measT025&quot;: 88180.9375, &quot;measT100&quot;: 314931.9375, &quot;region&quot;: &quot;BATU LAYANG&quot;, &quot;urban/rura&quot;: &quot;1&quot;, &quot;weight&quot;: 1.160449143}, &quot;type&quot;: &quot;Feature&quot;}], &quot;type&quot;: &quot;FeatureCollection&quot;});\n",
+       "\n",
+       "        \n",
+       "    \n",
+       "    geo_json_bf7208d105ff72056f38887081b418f5.bindTooltip(\n",
+       "    function(layer){\n",
+       "    let div = L.DomUtil.create(&#x27;div&#x27;);\n",
+       "    \n",
+       "    let handleObject = feature=&gt;typeof(feature)==&#x27;object&#x27; ? JSON.stringify(feature) : feature;\n",
+       "    let fields = [&quot;PROVNO&quot;, &quot;KABKOTNO&quot;, &quot;KECNO&quot;, &quot;DESANO&quot;, &quot;PROVINSI&quot;, &quot;KABKOT&quot;, &quot;KECAMATAN&quot;, &quot;DESA&quot;, &quot;IDDESA&quot;, &quot;SUMBER&quot;, &quot;MALE&quot;, &quot;FEM&quot;, &quot;HSHOLDS&quot;, &quot;HHSIZE&quot;, &quot;POP2016&quot;, &quot;WFLOW&quot;, &quot;2010_BestE&quot;, &quot;2016_BestE&quot;, &quot;2017_BestE&quot;, &quot;urban/rura&quot;, &quot;V2_Water&quot;, &quot;V2_Terr&quot;, &quot;V2_Terr_ha&quot;, &quot;IDDESA_nw&quot;, &quot;Pop2017_UD&quot;, &quot;area_ha&quot;, &quot;Village&quot;, &quot;FGT0_NPL&quot;, &quot;SE_FGT0_NP&quot;, &quot;FGT1_NPL&quot;, &quot;SE_FGT1_NP&quot;, &quot;FGT2_NPL&quot;, &quot;SE_FGT2_NP&quot;, &quot;FGT0_USD3.&quot;, &quot;SE_FGT0_US&quot;, &quot;FGT1_USD3.&quot;, &quot;SE_FGT1_US&quot;, &quot;FGT2_USD3.&quot;, &quot;SE_FGT2_US&quot;, &quot;Gini&quot;, &quot;SE_Gini&quot;, &quot;NA_02&quot;, &quot;FA_02&quot;, &quot;FA_03&quot;, &quot;PA_01&quot;, &quot;PA_02&quot;, &quot;PA_03&quot;, &quot;PA_04&quot;, &quot;PA_05&quot;, &quot;PA_06&quot;, &quot;PA_07&quot;, &quot;PA_08&quot;, &quot;NA_03&quot;, &quot;PA_09&quot;, &quot;PA_10&quot;, &quot;PA_11&quot;, &quot;PA_12&quot;, &quot;PA_13&quot;, &quot;PA_14&quot;, &quot;HA_01&quot;, &quot;HA_02&quot;, &quot;HA_03&quot;, &quot;SA_01&quot;, &quot;NA_04&quot;, &quot;SA_02&quot;, &quot;NA_05&quot;, &quot;NA_06&quot;, &quot;NA_07&quot;, &quot;NA_08&quot;, &quot;NA_09&quot;, &quot;FA_01&quot;, &quot;NA_01&quot;, &quot;baseT001&quot;, &quot;measT001&quot;, &quot;baseT010&quot;, &quot;measT010&quot;, &quot;baseT025&quot;, &quot;measT025&quot;, &quot;baseT100&quot;, &quot;measT100&quot;, &quot;baseEAD&quot;, &quot;measEAD&quot;, &quot;benefit&quot;, &quot;ID&quot;, &quot;region&quot;, &quot;weight&quot;];\n",
+       "    let aliases = [&quot;PROVNO&quot;, &quot;KABKOTNO&quot;, &quot;KECNO&quot;, &quot;DESANO&quot;, &quot;PROVINSI&quot;, &quot;KABKOT&quot;, &quot;KECAMATAN&quot;, &quot;DESA&quot;, &quot;IDDESA&quot;, &quot;SUMBER&quot;, &quot;MALE&quot;, &quot;FEM&quot;, &quot;HSHOLDS&quot;, &quot;HHSIZE&quot;, &quot;POP2016&quot;, &quot;WFLOW&quot;, &quot;2010_BestE&quot;, &quot;2016_BestE&quot;, &quot;2017_BestE&quot;, &quot;urban/rura&quot;, &quot;V2_Water&quot;, &quot;V2_Terr&quot;, &quot;V2_Terr_ha&quot;, &quot;IDDESA_nw&quot;, &quot;Pop2017_UD&quot;, &quot;area_ha&quot;, &quot;Village&quot;, &quot;FGT0_NPL&quot;, &quot;SE_FGT0_NP&quot;, &quot;FGT1_NPL&quot;, &quot;SE_FGT1_NP&quot;, &quot;FGT2_NPL&quot;, &quot;SE_FGT2_NP&quot;, &quot;FGT0_USD3.&quot;, &quot;SE_FGT0_US&quot;, &quot;FGT1_USD3.&quot;, &quot;SE_FGT1_US&quot;, &quot;FGT2_USD3.&quot;, &quot;SE_FGT2_US&quot;, &quot;Gini&quot;, &quot;SE_Gini&quot;, &quot;NA_02&quot;, &quot;FA_02&quot;, &quot;FA_03&quot;, &quot;PA_01&quot;, &quot;PA_02&quot;, &quot;PA_03&quot;, &quot;PA_04&quot;, &quot;PA_05&quot;, &quot;PA_06&quot;, &quot;PA_07&quot;, &quot;PA_08&quot;, &quot;NA_03&quot;, &quot;PA_09&quot;, &quot;PA_10&quot;, &quot;PA_11&quot;, &quot;PA_12&quot;, &quot;PA_13&quot;, &quot;PA_14&quot;, &quot;HA_01&quot;, &quot;HA_02&quot;, &quot;HA_03&quot;, &quot;SA_01&quot;, &quot;NA_04&quot;, &quot;SA_02&quot;, &quot;NA_05&quot;, &quot;NA_06&quot;, &quot;NA_07&quot;, &quot;NA_08&quot;, &quot;NA_09&quot;, &quot;FA_01&quot;, &quot;NA_01&quot;, &quot;baseT001&quot;, &quot;measT001&quot;, &quot;baseT010&quot;, &quot;measT010&quot;, &quot;baseT025&quot;, &quot;measT025&quot;, &quot;baseT100&quot;, &quot;measT100&quot;, &quot;baseEAD&quot;, &quot;measEAD&quot;, &quot;benefit&quot;, &quot;ID&quot;, &quot;region&quot;, &quot;weight&quot;];\n",
+       "    let table = &#x27;&lt;table&gt;&#x27; +\n",
+       "        String(\n",
+       "        fields.map(\n",
+       "        (v,i)=&gt;\n",
+       "        `&lt;tr&gt;\n",
+       "            &lt;th&gt;${aliases[i]}&lt;/th&gt;\n",
+       "            \n",
+       "            &lt;td&gt;${handleObject(layer.feature.properties[v])}&lt;/td&gt;\n",
+       "        &lt;/tr&gt;`).join(&#x27;&#x27;))\n",
+       "    +&#x27;&lt;/table&gt;&#x27;;\n",
+       "    div.innerHTML=table;\n",
+       "    \n",
+       "    return div\n",
+       "    }\n",
+       "    ,{&quot;className&quot;: &quot;foliumtooltip&quot;, &quot;sticky&quot;: true});\n",
+       "                     \n",
+       "    \n",
+       "                geo_json_bf7208d105ff72056f38887081b418f5.addTo(map_462d83635a66945f72d8bdb40f3efa52);\n",
+       "    \n",
+       "    var color_map_21242c215072b5e579ccebcc92c60057 = {};\n",
+       "\n",
+       "    \n",
+       "    color_map_21242c215072b5e579ccebcc92c60057.color = d3.scale.threshold()\n",
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+       "    \n",
+       "\n",
+       "    color_map_21242c215072b5e579ccebcc92c60057.x = d3.scale.linear()\n",
+       "              .domain([0.012661925, 6.964804054])\n",
+       "              .range([0, 450 - 50]);\n",
+       "\n",
+       "    color_map_21242c215072b5e579ccebcc92c60057.legend = L.control({position: &#x27;topright&#x27;});\n",
+       "    color_map_21242c215072b5e579ccebcc92c60057.legend.onAdd = function (map) {var div = L.DomUtil.create(&#x27;div&#x27;, &#x27;legend&#x27;); return div};\n",
+       "    color_map_21242c215072b5e579ccebcc92c60057.legend.addTo(map_462d83635a66945f72d8bdb40f3efa52);\n",
+       "\n",
+       "    color_map_21242c215072b5e579ccebcc92c60057.xAxis = d3.svg.axis()\n",
+       "        .scale(color_map_21242c215072b5e579ccebcc92c60057.x)\n",
+       "        .orient(&quot;top&quot;)\n",
+       "        .tickSize(1)\n",
+       "        .tickValues([0.012661925, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, 0.7215077891333334, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, 1.4303536532666667, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, 2.1391995174000002, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, 2.8480453815333338, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, 3.556891245666667, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, 4.2657371098, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, 4.974582973933334, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, 5.683428838066667, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, 6.3922747022, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;]);\n",
+       "\n",
+       "    color_map_21242c215072b5e579ccebcc92c60057.svg = d3.select(&quot;.legend.leaflet-control&quot;).append(&quot;svg&quot;)\n",
+       "        .attr(&quot;id&quot;, &#x27;legend&#x27;)\n",
+       "        .attr(&quot;width&quot;, 450)\n",
+       "        .attr(&quot;height&quot;, 40);\n",
+       "\n",
+       "    color_map_21242c215072b5e579ccebcc92c60057.g = color_map_21242c215072b5e579ccebcc92c60057.svg.append(&quot;g&quot;)\n",
+       "        .attr(&quot;class&quot;, &quot;key&quot;)\n",
+       "        .attr(&quot;transform&quot;, &quot;translate(25,16)&quot;);\n",
+       "\n",
+       "    color_map_21242c215072b5e579ccebcc92c60057.g.selectAll(&quot;rect&quot;)\n",
+       "        .data(color_map_21242c215072b5e579ccebcc92c60057.color.range().map(function(d, i) {\n",
+       "          return {\n",
+       "            x0: i ? color_map_21242c215072b5e579ccebcc92c60057.x(color_map_21242c215072b5e579ccebcc92c60057.color.domain()[i - 1]) : color_map_21242c215072b5e579ccebcc92c60057.x.range()[0],\n",
+       "            x1: i &lt; color_map_21242c215072b5e579ccebcc92c60057.color.domain().length ? color_map_21242c215072b5e579ccebcc92c60057.x(color_map_21242c215072b5e579ccebcc92c60057.color.domain()[i]) : color_map_21242c215072b5e579ccebcc92c60057.x.range()[1],\n",
+       "            z: d\n",
+       "          };\n",
+       "        }))\n",
+       "      .enter().append(&quot;rect&quot;)\n",
+       "        .attr(&quot;height&quot;, 40 - 30)\n",
+       "        .attr(&quot;x&quot;, function(d) { return d.x0; })\n",
+       "        .attr(&quot;width&quot;, function(d) { return d.x1 - d.x0; })\n",
+       "        .style(&quot;fill&quot;, function(d) { return d.z; });\n",
+       "\n",
+       "    color_map_21242c215072b5e579ccebcc92c60057.g.call(color_map_21242c215072b5e579ccebcc92c60057.xAxis).append(&quot;text&quot;)\n",
+       "        .attr(&quot;class&quot;, &quot;caption&quot;)\n",
+       "        .attr(&quot;y&quot;, 21)\n",
+       "        .text(&quot;weight&quot;);\n",
+       "&lt;/script&gt;\n",
+       "&lt;/html&gt;\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
+      ],
+      "text/plain": [
+       "<folium.folium.Map at 0x1a354c3e350>"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Inspect the regions\n",
+    "region_weights_plot.explore(column='weight', cmap='Reds', tiles=\"CartoDB positron\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b21e3726",
+   "metadata": {},
+   "source": [
+    "### 2. Inspect origins, destinations and the road network"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a484934e",
+   "metadata": {},
+   "source": [
+    "Load the origins and destinations data and the road network of our analysis"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "ae73f50c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "path_network = root_dir / \"static\" / \"network\"\n",
+    "path_origins = path_network / \"origins_points.shp\"\n",
+    "path_destinations = path_network / \"osm_health_point.shp\"\n",
+    "origins = gpd.read_file(path_origins, driver = \"SHP\")\n",
+    "destinations = gpd.read_file(path_destinations, driver = \"SHP\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5bbbc39b",
+   "metadata": {},
+   "source": [
+    "Inspect origins (blue) and health destinations (red)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "37051457",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "&lt;head&gt;\n",
+       "    \n",
+       "    &lt;meta http-equiv=&quot;content-type&quot; content=&quot;text/html; charset=UTF-8&quot; /&gt;\n",
+       "    \n",
+       "        &lt;script&gt;\n",
+       "            L_NO_TOUCH = false;\n",
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+       "    &lt;style&gt;#map {position:absolute;top:0;bottom:0;right:0;left:0;}&lt;/style&gt;\n",
+       "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.js&quot;&gt;&lt;/script&gt;\n",
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+       "    \n",
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+       "                initial-scale=1.0, maximum-scale=1.0, user-scalable=no&quot; /&gt;\n",
+       "            &lt;style&gt;\n",
+       "                #map_e3b5c42e586ebd5e61b9489d48846b26 {\n",
+       "                    position: relative;\n",
+       "                    width: 100.0%;\n",
+       "                    height: 100.0%;\n",
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+       "                .leaflet-container { font-size: 1rem; }\n",
+       "            &lt;/style&gt;\n",
+       "        \n",
+       "    \n",
+       "                    &lt;style&gt;\n",
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+       "                        }\n",
+       "                       .foliumtooltip table{\n",
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+       "                        .foliumtooltip tr{\n",
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+       "                        .foliumtooltip th{\n",
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+       "                        }\n",
+       "                    &lt;/style&gt;\n",
+       "            \n",
+       "    \n",
+       "                    &lt;style&gt;\n",
+       "                        .foliumtooltip {\n",
+       "                            \n",
+       "                        }\n",
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+       "                            margin: auto;\n",
+       "                        }\n",
+       "                        .foliumtooltip tr{\n",
+       "                            text-align: left;\n",
+       "                        }\n",
+       "                        .foliumtooltip th{\n",
+       "                            padding: 2px; padding-right: 8px;\n",
+       "                        }\n",
+       "                    &lt;/style&gt;\n",
+       "            \n",
+       "&lt;/head&gt;\n",
+       "&lt;body&gt;\n",
+       "    \n",
+       "    \n",
+       "            &lt;div class=&quot;folium-map&quot; id=&quot;map_e3b5c42e586ebd5e61b9489d48846b26&quot; &gt;&lt;/div&gt;\n",
+       "        \n",
+       "&lt;/body&gt;\n",
+       "&lt;script&gt;\n",
+       "    \n",
+       "    \n",
+       "            var map_e3b5c42e586ebd5e61b9489d48846b26 = L.map(\n",
+       "                &quot;map_e3b5c42e586ebd5e61b9489d48846b26&quot;,\n",
+       "                {\n",
+       "                    center: [-0.03227964663674228, 109.32661280506221],\n",
+       "                    crs: L.CRS.EPSG3857,\n",
+       "                    zoom: 10,\n",
+       "                    zoomControl: true,\n",
+       "                    preferCanvas: false,\n",
+       "                }\n",
+       "            );\n",
+       "            L.control.scale().addTo(map_e3b5c42e586ebd5e61b9489d48846b26);\n",
+       "\n",
+       "            \n",
+       "\n",
+       "        \n",
+       "    \n",
+       "            var tile_layer_6485aefc516e1e6b5ec81738856f39c4 = L.tileLayer(\n",
+       "                &quot;https://cartodb-basemaps-{s}.global.ssl.fastly.net/light_all/{z}/{x}/{y}.png&quot;,\n",
+       "                {&quot;attribution&quot;: &quot;\\u0026copy; \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://www.openstreetmap.org/copyright\\&quot;\\u003eOpenStreetMap\\u003c/a\\u003e contributors \\u0026copy; \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://cartodb.com/attributions\\&quot;\\u003eCartoDB\\u003c/a\\u003e, CartoDB \\u003ca target=\\&quot;_blank\\&quot; href =\\&quot;http://cartodb.com/attributions\\&quot;\\u003eattributions\\u003c/a\\u003e&quot;, &quot;detectRetina&quot;: false, &quot;maxNativeZoom&quot;: 18, &quot;maxZoom&quot;: 18, &quot;minZoom&quot;: 0, &quot;noWrap&quot;: false, &quot;opacity&quot;: 1, &quot;subdomains&quot;: &quot;abc&quot;, &quot;tms&quot;: false}\n",
+       "            );\n",
+       "        \n",
+       "    \n",
+       "                tile_layer_6485aefc516e1e6b5ec81738856f39c4.addTo(map_e3b5c42e586ebd5e61b9489d48846b26);\n",
+       "    \n",
+       "            map_e3b5c42e586ebd5e61b9489d48846b26.fitBounds(\n",
+       "                [[-0.09083820519530084, 109.27706325551266], [0.026278911921816285, 109.37616235461175]],\n",
+       "                {}\n",
+       "            );\n",
+       "        \n",
+       "    \n",
+       "        function geo_json_7cc1d548cae9cfe8e90222d12d184851_styler(feature) {\n",
+       "            switch(feature.id) {\n",
+       "                default:\n",
+       "                    return {&quot;color&quot;: &quot;blue&quot;, &quot;fillColor&quot;: &quot;blue&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "            }\n",
+       "        }\n",
+       "        function geo_json_7cc1d548cae9cfe8e90222d12d184851_highlighter(feature) {\n",
+       "            switch(feature.id) {\n",
+       "                default:\n",
+       "                    return {&quot;fillOpacity&quot;: 0.75};\n",
+       "            }\n",
+       "        }\n",
+       "        function geo_json_7cc1d548cae9cfe8e90222d12d184851_pointToLayer(feature, latlng) {\n",
+       "            var opts = {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;#3388ff&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: true, &quot;fillColor&quot;: &quot;#3388ff&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 2, &quot;stroke&quot;: true, &quot;weight&quot;: 3};\n",
+       "            \n",
+       "            let style = geo_json_7cc1d548cae9cfe8e90222d12d184851_styler(feature)\n",
+       "            Object.assign(opts, style)\n",
+       "            \n",
+       "            return new L.CircleMarker(latlng, opts)\n",
+       "        }\n",
+       "\n",
+       "        function geo_json_7cc1d548cae9cfe8e90222d12d184851_onEachFeature(feature, layer) {\n",
+       "            layer.on({\n",
+       "                mouseout: function(e) {\n",
+       "                    if(typeof e.target.setStyle === &quot;function&quot;){\n",
+       "                        geo_json_7cc1d548cae9cfe8e90222d12d184851.resetStyle(e.target);\n",
+       "                    }\n",
+       "                },\n",
+       "                mouseover: function(e) {\n",
+       "                    if(typeof e.target.setStyle === &quot;function&quot;){\n",
+       "                        const highlightStyle = geo_json_7cc1d548cae9cfe8e90222d12d184851_highlighter(e.target.feature)\n",
+       "                        e.target.setStyle(highlightStyle);\n",
+       "                    }\n",
+       "                },\n",
+       "            });\n",
+       "        };\n",
+       "        var geo_json_7cc1d548cae9cfe8e90222d12d184851 = L.geoJson(null, {\n",
+       "                onEachFeature: geo_json_7cc1d548cae9cfe8e90222d12d184851_onEachFeature,\n",
+       "            \n",
+       "                style: geo_json_7cc1d548cae9cfe8e90222d12d184851_styler,\n",
+       "                pointToLayer: geo_json_7cc1d548cae9cfe8e90222d12d184851_pointToLayer,\n",
+       "        });\n",
+       "\n",
+       "        function geo_json_7cc1d548cae9cfe8e90222d12d184851_add (data) {\n",
+       "            geo_json_7cc1d548cae9cfe8e90222d12d184851\n",
+       "                .addData(data);\n",
+       "        }\n",
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&quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;85&quot;, &quot;properties&quot;: {&quot;OBJECTID&quot;: 148, &quot;__folium_color&quot;: &quot;blue&quot;, &quot;category&quot;: &quot;origin&quot;, &quot;values&quot;: 4228.13134765625}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [109.35814433659374, -0.00975712411421975, 109.35814433659374, -0.00975712411421975], &quot;geometry&quot;: {&quot;coordinates&quot;: [109.35814433659374, -0.00975712411421975], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;86&quot;, &quot;properties&quot;: {&quot;OBJECTID&quot;: 149, &quot;__folium_color&quot;: &quot;blue&quot;, &quot;category&quot;: &quot;origin&quot;, &quot;values&quot;: 5094.998046875}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [109.35814433659374, -0.018766133123228758, 109.35814433659374, -0.018766133123228758], &quot;geometry&quot;: {&quot;coordinates&quot;: [109.35814433659374, -0.018766133123228758], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;87&quot;, &quot;properties&quot;: {&quot;OBJECTID&quot;: 150, &quot;__folium_color&quot;: &quot;blue&quot;, &quot;category&quot;: &quot;origin&quot;, &quot;values&quot;: 4870.58056640625}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [109.35814433659374, -0.027775142132237772, 109.35814433659374, -0.027775142132237772], &quot;geometry&quot;: {&quot;coordinates&quot;: [109.35814433659374, -0.027775142132237772], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;88&quot;, &quot;properties&quot;: {&quot;OBJECTID&quot;: 151, &quot;__folium_color&quot;: &quot;blue&quot;, &quot;category&quot;: &quot;origin&quot;, &quot;values&quot;: 6146.875}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [109.35814433659374, -0.03678415114124677, 109.35814433659374, -0.03678415114124677], &quot;geometry&quot;: {&quot;coordinates&quot;: [109.35814433659374, -0.03678415114124677], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;89&quot;, &quot;properties&quot;: {&quot;OBJECTID&quot;: 152, &quot;__folium_color&quot;: &quot;blue&quot;, &quot;category&quot;: &quot;origin&quot;, &quot;values&quot;: 6454.96240234375}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [109.35814433659374, -0.045793160150255786, 109.35814433659374, -0.045793160150255786], &quot;geometry&quot;: {&quot;coordinates&quot;: [109.35814433659374, -0.045793160150255786], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;90&quot;, &quot;properties&quot;: {&quot;OBJECTID&quot;: 153, &quot;__folium_color&quot;: &quot;blue&quot;, &quot;category&quot;: &quot;origin&quot;, &quot;values&quot;: 4999.47705078125}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [109.35814433659374, -0.0548021691592648, 109.35814433659374, -0.0548021691592648], &quot;geometry&quot;: {&quot;coordinates&quot;: [109.35814433659374, -0.0548021691592648], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;91&quot;, &quot;properties&quot;: {&quot;OBJECTID&quot;: 154, &quot;__folium_color&quot;: &quot;blue&quot;, &quot;category&quot;: &quot;origin&quot;, &quot;values&quot;: 7310.28076171875}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [109.35814433659374, -0.06381117816827381, 109.35814433659374, -0.06381117816827381], &quot;geometry&quot;: {&quot;coordinates&quot;: [109.35814433659374, -0.06381117816827381], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;92&quot;, &quot;properties&quot;: {&quot;OBJECTID&quot;: 155, &quot;__folium_color&quot;: &quot;blue&quot;, &quot;category&quot;: &quot;origin&quot;, &quot;values&quot;: 6344.6611328125}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [109.35814433659374, -0.07282018717728281, 109.35814433659374, -0.07282018717728281], &quot;geometry&quot;: {&quot;coordinates&quot;: [109.35814433659374, -0.07282018717728281], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;93&quot;, &quot;properties&quot;: {&quot;OBJECTID&quot;: 156, &quot;__folium_color&quot;: &quot;blue&quot;, &quot;category&quot;: &quot;origin&quot;, &quot;values&quot;: 8229.517578125}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [109.36715334560274, 0.017269902912807278, 109.36715334560274, 0.017269902912807278], &quot;geometry&quot;: {&quot;coordinates&quot;: [109.36715334560274, 0.017269902912807278], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;94&quot;, &quot;properties&quot;: {&quot;OBJECTID&quot;: 162, &quot;__folium_color&quot;: &quot;blue&quot;, &quot;category&quot;: &quot;origin&quot;, &quot;values&quot;: 253.24107360839844}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [109.36715334560274, 0.00826089390379827, 109.36715334560274, 0.00826089390379827], &quot;geometry&quot;: {&quot;coordinates&quot;: [109.36715334560274, 0.00826089390379827], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;95&quot;, &quot;properties&quot;: {&quot;OBJECTID&quot;: 163, &quot;__folium_color&quot;: &quot;blue&quot;, &quot;category&quot;: &quot;origin&quot;, &quot;values&quot;: 773.019775390625}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [109.36715334560274, -0.0007481151052107435, 109.36715334560274, -0.0007481151052107435], &quot;geometry&quot;: {&quot;coordinates&quot;: [109.36715334560274, -0.0007481151052107435], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;96&quot;, &quot;properties&quot;: {&quot;OBJECTID&quot;: 164, &quot;__folium_color&quot;: &quot;blue&quot;, &quot;category&quot;: &quot;origin&quot;, &quot;values&quot;: 2695.613525390625}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [109.36715334560274, -0.00975712411421975, 109.36715334560274, -0.00975712411421975], &quot;geometry&quot;: {&quot;coordinates&quot;: [109.36715334560274, -0.00975712411421975], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;97&quot;, &quot;properties&quot;: {&quot;OBJECTID&quot;: 165, &quot;__folium_color&quot;: &quot;blue&quot;, &quot;category&quot;: &quot;origin&quot;, &quot;values&quot;: 3561.189208984375}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [109.36715334560274, -0.018766133123228758, 109.36715334560274, -0.018766133123228758], &quot;geometry&quot;: {&quot;coordinates&quot;: [109.36715334560274, -0.018766133123228758], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;98&quot;, &quot;properties&quot;: {&quot;OBJECTID&quot;: 166, &quot;__folium_color&quot;: &quot;blue&quot;, &quot;category&quot;: &quot;origin&quot;, &quot;values&quot;: 2656.97705078125}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [109.36715334560274, -0.027775142132237772, 109.36715334560274, -0.027775142132237772], &quot;geometry&quot;: {&quot;coordinates&quot;: [109.36715334560274, -0.027775142132237772], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;99&quot;, &quot;properties&quot;: {&quot;OBJECTID&quot;: 167, &quot;__folium_color&quot;: &quot;blue&quot;, &quot;category&quot;: &quot;origin&quot;, &quot;values&quot;: 7481.85791015625}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [109.36715334560274, -0.03678415114124677, 109.36715334560274, -0.03678415114124677], &quot;geometry&quot;: {&quot;coordinates&quot;: [109.36715334560274, -0.03678415114124677], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;100&quot;, &quot;properties&quot;: {&quot;OBJECTID&quot;: 168, &quot;__folium_color&quot;: &quot;blue&quot;, &quot;category&quot;: &quot;origin&quot;, &quot;values&quot;: 4338.23974609375}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [109.36715334560274, -0.045793160150255786, 109.36715334560274, -0.045793160150255786], &quot;geometry&quot;: {&quot;coordinates&quot;: [109.36715334560274, -0.045793160150255786], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;101&quot;, &quot;properties&quot;: {&quot;OBJECTID&quot;: 169, &quot;__folium_color&quot;: &quot;blue&quot;, &quot;category&quot;: &quot;origin&quot;, &quot;values&quot;: 5250.23974609375}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [109.36715334560274, -0.0548021691592648, 109.36715334560274, -0.0548021691592648], &quot;geometry&quot;: {&quot;coordinates&quot;: [109.36715334560274, -0.0548021691592648], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;102&quot;, &quot;properties&quot;: {&quot;OBJECTID&quot;: 170, &quot;__folium_color&quot;: &quot;blue&quot;, &quot;category&quot;: &quot;origin&quot;, &quot;values&quot;: 4252.70556640625}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [109.37616235461175, -0.00975712411421975, 109.37616235461175, -0.00975712411421975], &quot;geometry&quot;: {&quot;coordinates&quot;: [109.37616235461175, -0.00975712411421975], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;103&quot;, &quot;properties&quot;: {&quot;OBJECTID&quot;: 181, &quot;__folium_color&quot;: &quot;blue&quot;, &quot;category&quot;: &quot;origin&quot;, &quot;values&quot;: 326.29742431640625}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [109.37616235461175, -0.018766133123228758, 109.37616235461175, -0.018766133123228758], &quot;geometry&quot;: {&quot;coordinates&quot;: [109.37616235461175, -0.018766133123228758], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;104&quot;, &quot;properties&quot;: {&quot;OBJECTID&quot;: 182, &quot;__folium_color&quot;: &quot;blue&quot;, &quot;category&quot;: &quot;origin&quot;, &quot;values&quot;: 680.6234130859375}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [109.37616235461175, -0.027775142132237772, 109.37616235461175, -0.027775142132237772], &quot;geometry&quot;: {&quot;coordinates&quot;: [109.37616235461175, -0.027775142132237772], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;105&quot;, &quot;properties&quot;: {&quot;OBJECTID&quot;: 183, &quot;__folium_color&quot;: &quot;blue&quot;, &quot;category&quot;: &quot;origin&quot;, &quot;values&quot;: 6358.58056640625}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [109.37616235461175, -0.045793160150255786, 109.37616235461175, -0.045793160150255786], &quot;geometry&quot;: {&quot;coordinates&quot;: [109.37616235461175, -0.045793160150255786], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;106&quot;, &quot;properties&quot;: {&quot;OBJECTID&quot;: 185, &quot;__folium_color&quot;: &quot;blue&quot;, &quot;category&quot;: &quot;origin&quot;, &quot;values&quot;: 1697.9564208984375}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [109.37616235461175, -0.0548021691592648, 109.37616235461175, -0.0548021691592648], &quot;geometry&quot;: {&quot;coordinates&quot;: [109.37616235461175, -0.0548021691592648], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;107&quot;, &quot;properties&quot;: {&quot;OBJECTID&quot;: 186, &quot;__folium_color&quot;: &quot;blue&quot;, &quot;category&quot;: &quot;origin&quot;, &quot;values&quot;: 3222.84130859375}, &quot;type&quot;: &quot;Feature&quot;}], &quot;type&quot;: &quot;FeatureCollection&quot;});\n",
+       "\n",
+       "        \n",
+       "    \n",
+       "    geo_json_7cc1d548cae9cfe8e90222d12d184851.bindTooltip(\n",
+       "    function(layer){\n",
+       "    let div = L.DomUtil.create(&#x27;div&#x27;);\n",
+       "    \n",
+       "    let handleObject = feature=&gt;typeof(feature)==&#x27;object&#x27; ? JSON.stringify(feature) : feature;\n",
+       "    let fields = [&quot;OBJECTID&quot;, &quot;values&quot;, &quot;category&quot;];\n",
+       "    let aliases = [&quot;OBJECTID&quot;, &quot;values&quot;, &quot;category&quot;];\n",
+       "    let table = &#x27;&lt;table&gt;&#x27; +\n",
+       "        String(\n",
+       "        fields.map(\n",
+       "        (v,i)=&gt;\n",
+       "        `&lt;tr&gt;\n",
+       "            &lt;th&gt;${aliases[i]}&lt;/th&gt;\n",
+       "            \n",
+       "            &lt;td&gt;${handleObject(layer.feature.properties[v])}&lt;/td&gt;\n",
+       "        &lt;/tr&gt;`).join(&#x27;&#x27;))\n",
+       "    +&#x27;&lt;/table&gt;&#x27;;\n",
+       "    div.innerHTML=table;\n",
+       "    \n",
+       "    return div\n",
+       "    }\n",
+       "    ,{&quot;className&quot;: &quot;foliumtooltip&quot;, &quot;sticky&quot;: true});\n",
+       "                     \n",
+       "    \n",
+       "                geo_json_7cc1d548cae9cfe8e90222d12d184851.addTo(map_e3b5c42e586ebd5e61b9489d48846b26);\n",
+       "    \n",
+       "        function geo_json_4561ddde7c302d18bb0406e1cb08c0bc_styler(feature) {\n",
+       "            switch(feature.id) {\n",
+       "                default:\n",
+       "                    return {&quot;color&quot;: &quot;red&quot;, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "            }\n",
+       "        }\n",
+       "        function geo_json_4561ddde7c302d18bb0406e1cb08c0bc_highlighter(feature) {\n",
+       "            switch(feature.id) {\n",
+       "                default:\n",
+       "                    return {&quot;fillOpacity&quot;: 0.75};\n",
+       "            }\n",
+       "        }\n",
+       "        function geo_json_4561ddde7c302d18bb0406e1cb08c0bc_pointToLayer(feature, latlng) {\n",
+       "            var opts = {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;#3388ff&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: true, &quot;fillColor&quot;: &quot;#3388ff&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 2, &quot;stroke&quot;: true, &quot;weight&quot;: 3};\n",
+       "            \n",
+       "            let style = geo_json_4561ddde7c302d18bb0406e1cb08c0bc_styler(feature)\n",
+       "            Object.assign(opts, style)\n",
+       "            \n",
+       "            return new L.CircleMarker(latlng, opts)\n",
+       "        }\n",
+       "\n",
+       "        function geo_json_4561ddde7c302d18bb0406e1cb08c0bc_onEachFeature(feature, layer) {\n",
+       "            layer.on({\n",
+       "                mouseout: function(e) {\n",
+       "                    if(typeof e.target.setStyle === &quot;function&quot;){\n",
+       "                        geo_json_4561ddde7c302d18bb0406e1cb08c0bc.resetStyle(e.target);\n",
+       "                    }\n",
+       "                },\n",
+       "                mouseover: function(e) {\n",
+       "                    if(typeof e.target.setStyle === &quot;function&quot;){\n",
+       "                        const highlightStyle = geo_json_4561ddde7c302d18bb0406e1cb08c0bc_highlighter(e.target.feature)\n",
+       "                        e.target.setStyle(highlightStyle);\n",
+       "                    }\n",
+       "                },\n",
+       "            });\n",
+       "        };\n",
+       "        var geo_json_4561ddde7c302d18bb0406e1cb08c0bc = L.geoJson(null, {\n",
+       "                onEachFeature: geo_json_4561ddde7c302d18bb0406e1cb08c0bc_onEachFeature,\n",
+       "            \n",
+       "                style: geo_json_4561ddde7c302d18bb0406e1cb08c0bc_styler,\n",
+       "                pointToLayer: geo_json_4561ddde7c302d18bb0406e1cb08c0bc_pointToLayer,\n",
+       "        });\n",
+       "\n",
+       "        function geo_json_4561ddde7c302d18bb0406e1cb08c0bc_add (data) {\n",
+       "            geo_json_4561ddde7c302d18bb0406e1cb08c0bc\n",
+       "                .addData(data);\n",
+       "        }\n",
+       "            geo_json_4561ddde7c302d18bb0406e1cb08c0bc_add({&quot;bbox&quot;: [109.31815864302261, -0.03787203702364643, 109.34184636372416, -0.019298162339136424], &quot;features&quot;: [{&quot;bbox&quot;: [109.32385141500384, -0.019298162339136424, 109.32385141500384, -0.019298162339136424], &quot;geometry&quot;: {&quot;coordinates&quot;: [109.32385141500384, -0.019298162339136424], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;0&quot;, &quot;properties&quot;: {&quot;__folium_color&quot;: &quot;red&quot;, &quot;category&quot;: &quot;health&quot;, &quot;id&quot;: 1}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [109.31815864302261, -0.03599052764002074, 109.31815864302261, -0.03599052764002074], &quot;geometry&quot;: {&quot;coordinates&quot;: [109.31815864302261, -0.03599052764002074], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;1&quot;, &quot;properties&quot;: {&quot;__folium_color&quot;: &quot;red&quot;, &quot;category&quot;: &quot;health&quot;, &quot;id&quot;: 2}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [109.32959243081542, -0.03787203702364643, 109.32959243081542, -0.03787203702364643], &quot;geometry&quot;: {&quot;coordinates&quot;: [109.32959243081542, -0.03787203702364643], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;2&quot;, &quot;properties&quot;: {&quot;__folium_color&quot;: &quot;red&quot;, &quot;category&quot;: &quot;health&quot;, &quot;id&quot;: 3}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [109.34112270626892, -0.03348184846185316, 109.34112270626892, -0.03348184846185316], &quot;geometry&quot;: {&quot;coordinates&quot;: [109.34112270626892, -0.03348184846185316], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;3&quot;, &quot;properties&quot;: {&quot;__folium_color&quot;: &quot;red&quot;, &quot;category&quot;: &quot;health&quot;, &quot;id&quot;: 4}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [109.34184636372416, -0.0348326757116357, 109.34184636372416, -0.0348326757116357], &quot;geometry&quot;: {&quot;coordinates&quot;: [109.34184636372416, -0.0348326757116357], &quot;type&quot;: &quot;Point&quot;}, &quot;id&quot;: &quot;4&quot;, &quot;properties&quot;: {&quot;__folium_color&quot;: &quot;red&quot;, &quot;category&quot;: &quot;health&quot;, &quot;id&quot;: 5}, &quot;type&quot;: &quot;Feature&quot;}], &quot;type&quot;: &quot;FeatureCollection&quot;});\n",
+       "\n",
+       "        \n",
+       "    \n",
+       "    geo_json_4561ddde7c302d18bb0406e1cb08c0bc.bindTooltip(\n",
+       "    function(layer){\n",
+       "    let div = L.DomUtil.create(&#x27;div&#x27;);\n",
+       "    \n",
+       "    let handleObject = feature=&gt;typeof(feature)==&#x27;object&#x27; ? JSON.stringify(feature) : feature;\n",
+       "    let fields = [&quot;id&quot;, &quot;category&quot;];\n",
+       "    let aliases = [&quot;id&quot;, &quot;category&quot;];\n",
+       "    let table = &#x27;&lt;table&gt;&#x27; +\n",
+       "        String(\n",
+       "        fields.map(\n",
+       "        (v,i)=&gt;\n",
+       "        `&lt;tr&gt;\n",
+       "            &lt;th&gt;${aliases[i]}&lt;/th&gt;\n",
+       "            \n",
+       "            &lt;td&gt;${handleObject(layer.feature.properties[v])}&lt;/td&gt;\n",
+       "        &lt;/tr&gt;`).join(&#x27;&#x27;))\n",
+       "    +&#x27;&lt;/table&gt;&#x27;;\n",
+       "    div.innerHTML=table;\n",
+       "    \n",
+       "    return div\n",
+       "    }\n",
+       "    ,{&quot;className&quot;: &quot;foliumtooltip&quot;, &quot;sticky&quot;: true});\n",
+       "                     \n",
+       "    \n",
+       "                geo_json_4561ddde7c302d18bb0406e1cb08c0bc.addTo(map_e3b5c42e586ebd5e61b9489d48846b26);\n",
+       "    \n",
+       "            var layer_control_8997c8a32a28ca836f604ba50c0a11cc_layers = {\n",
+       "                base_layers : {\n",
+       "                    &quot;cartodbpositron&quot; : tile_layer_6485aefc516e1e6b5ec81738856f39c4,\n",
+       "                },\n",
+       "                overlays :  {\n",
+       "                    &quot;WorldPop origins&quot; : geo_json_7cc1d548cae9cfe8e90222d12d184851,\n",
+       "                    &quot;Health destinations&quot; : geo_json_4561ddde7c302d18bb0406e1cb08c0bc,\n",
+       "                },\n",
+       "            };\n",
+       "            let layer_control_8997c8a32a28ca836f604ba50c0a11cc = L.control.layers(\n",
+       "                layer_control_8997c8a32a28ca836f604ba50c0a11cc_layers.base_layers,\n",
+       "                layer_control_8997c8a32a28ca836f604ba50c0a11cc_layers.overlays,\n",
+       "                {&quot;autoZIndex&quot;: true, &quot;collapsed&quot;: true, &quot;position&quot;: &quot;topright&quot;}\n",
+       "            ).addTo(map_e3b5c42e586ebd5e61b9489d48846b26);\n",
+       "\n",
+       "        \n",
+       "&lt;/script&gt;\n",
+       "&lt;/html&gt;\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
+      ],
+      "text/plain": [
+       "<folium.folium.Map at 0x1a354d629b0>"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "m = origins.explore(color='blue', tiles=\"CartoDB positron\", name='WorldPop origins')\n",
+    "m = destinations.explore(m=m, color=\"red\", name=\"Health destinations\")\n",
+    "# this is completely optional\n",
+    "folium.LayerControl().add_to(m)\n",
+    "m\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6163a416",
+   "metadata": {},
+   "source": [
+    "# Running the RA2CE analysis"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6071f5fd",
+   "metadata": {},
+   "source": [
+    "### 1. Make sure your data is created and stored correctly"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "08ec6ce7",
+   "metadata": {},
+   "source": [
+    "See the origins/destinations example to familiarize yourself with how to set up origins and destinations files. Inspect the regions file and the region_weight file and make sure they are saved in the correct folder"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "195ad33f",
+   "metadata": {},
+   "source": [
+    "### 2. Set up your network and analysis ini"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bf330d14",
+   "metadata": {},
+   "source": [
+    "Before you start running, you need to make sure that your .ini files contain the right parameters. Check out the analysis and network.ini files in the data folder to check the additional parameters that need to be set to run this example! Below we paste a snippet of these files as example"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5909031d",
+   "metadata": {},
+   "source": [
+    "**Network Ini update section origins_destinations**<br>\n",
+    "[origins_destinations]<br>\n",
+    "origins = origins_points.shp # Must be in the static/network folder, belongs to this analysis <br>\n",
+    "destinations = osm_health_point.shp # gis_osm_pois_pontianak.shp # Must be in the static/network folder, belongs to this analysis<br>\n",
+    "origins_names = A<br>\n",
+    "destinations_names = B<br>\n",
+    "id_name_origin_destination = OBJECTID #default if origins is a tif file = OBJECTID<br>\n",
+    "origin_count = values #necessary if traffic on each edge would be recorded in optimal_route_origin_destination<br>\n",
+    "origin_out_fraction = 1<br>\n",
+    "category = category<br>\n",
+    "region = region.shp #necessary for distributional / equity analysis<br>\n",
+    "region_var = DESA #necessary for distributional / equity analysis<br>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d97f55bb",
+   "metadata": {},
+   "source": [
+    "**analysis_ini update optimal_route_origin_destination analysis**<br>\n",
+    "[analysis1]<br>\n",
+    "name = optimal route origin destination<br>\n",
+    "analysis = optimal_route_origin_destination<br>\n",
+    "weighing = length<br>\n",
+    "save_traffic = True #True if you want to record the traffic in each edge<br>\n",
+    "equity_weight = region_weight.csv #equity-weighted factors for each region, should be stored in static/network. Note that 'region' and 'region_var' should present in network.ini<br>\n",
+    "save_gpkg = True<br>\n",
+    "save_csv = True<br>\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4de8e703",
+   "metadata": {},
+   "source": [
+    "### 3. Find your folder and initalization files"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d65d045f",
+   "metadata": {},
+   "source": [
+    "Now we can start our RA2CE analysis. Let's initialize RA2CE first"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "0d6562dd",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "c:\\Users\\meije_le\\Anaconda3\\envs\\ra2ce_env\\lib\\site-packages\\tqdm\\auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+      "  from .autonotebook import tqdm as notebook_tqdm\n"
+     ]
+    }
+   ],
+   "source": [
+    "from ra2ce.ra2ce_handler import Ra2ceHandler #import the ra2cehandler to run ra2ce analyses\n",
+    "\n",
+    "_network_ini_name = \"network.ini\" #set the name for the network.ini\n",
+    "_analysis_ini_name = \"analyses.ini\" #set the name for the analysis.ini"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "52f92d24",
+   "metadata": {},
+   "source": [
+    "Check if the network.ini and analysis.ini indeed exist"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "5a017a29",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "network_ini = root_dir / _network_ini_name\n",
+    "assert network_ini.is_file()\n",
+    "\n",
+    "analysis_ini = root_dir / _analysis_ini_name\n",
+    "assert analysis_ini.is_file()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "18e187eb",
+   "metadata": {},
+   "source": [
+    "### 4. Run RA2CE"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "fdd2b259",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-03-13 11:14:23 AM - [ra2ce_logging.py:41] - root - INFO - RA2CE logger initialized.\n",
+      "2024-03-13 11:14:23 AM - [networks.py:186] - root - INFO - Apparently, you already did create a network with ra2ce earlier. Ra2ce will use this: data\\equity_analysis\\static\\output_graph\\base_graph.p\n",
+      "2024-03-13 11:14:23 AM - [analyses_indirect.py:1090] - root - INFO - ----------------------------- Started analyzing 'optimal route origin destination'  -----------------------------\n",
+      "Finding optimal routes.: 100%|██████████| 540/540 [00:03<00:00, 136.62it/s]\n",
+      "2024-03-13 11:14:36 AM - [analyses_indirect.py:1386] - root - INFO - Results saved to: data\\equity_analysis\\output\\optimal_route_origin_destination\\optimal_route_origin_destination.gpkg\n",
+      "2024-03-13 11:14:37 AM - [analyses_indirect.py:1362] - root - INFO - ----------------------------- Analysis 'optimal route origin destination' finished. Time: 13.44s  -----------------------------\n"
+     ]
+    }
+   ],
+   "source": [
+    "handler = Ra2ceHandler(network=network_ini, analysis=analysis_ini)\n",
+    "handler.configure()\n",
+    "handler.run_analysis()"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "id": "a29bba14",
+   "metadata": {},
+   "source": [
+    "# Post-processing results"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1f08ac47",
+   "metadata": {},
+   "source": [
+    "The result of the equity analysis will be saved into the 'output' folder, under the specified analysis 'optimal_route_origin_destination'. This is a .csv file without geometry. To plot the results below, we will first add geometry to this data prior to showing the results"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "19a35997",
+   "metadata": {},
+   "source": [
+    "####  1. Load the traffic analysis output data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "e484c96b",
+   "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>u</th>\n",
+       "      <th>v</th>\n",
+       "      <th>traffic</th>\n",
+       "      <th>traffic_egalitarian</th>\n",
+       "      <th>traffic_prioritarian</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>10736480824</td>\n",
+       "      <td>1906180830</td>\n",
+       "      <td>4549.779297</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>14212.096079</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1906180830</td>\n",
+       "      <td>10736480825</td>\n",
+       "      <td>31950.635376</td>\n",
+       "      <td>50.0</td>\n",
+       "      <td>45468.956352</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>10736480825</td>\n",
+       "      <td>10736480837</td>\n",
+       "      <td>35600.869019</td>\n",
+       "      <td>55.0</td>\n",
+       "      <td>49119.189995</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>10736480837</td>\n",
+       "      <td>10736480838</td>\n",
+       "      <td>42651.551636</td>\n",
+       "      <td>60.0</td>\n",
+       "      <td>71143.330561</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>10736480838</td>\n",
+       "      <td>10736480852</td>\n",
+       "      <td>48254.479858</td>\n",
+       "      <td>65.0</td>\n",
+       "      <td>76746.258783</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             u            v       traffic  traffic_egalitarian  \\\n",
+       "0  10736480824   1906180830   4549.779297                  5.0   \n",
+       "1   1906180830  10736480825  31950.635376                 50.0   \n",
+       "2  10736480825  10736480837  35600.869019                 55.0   \n",
+       "3  10736480837  10736480838  42651.551636                 60.0   \n",
+       "4  10736480838  10736480852  48254.479858                 65.0   \n",
+       "\n",
+       "   traffic_prioritarian  \n",
+       "0          14212.096079  \n",
+       "1          45468.956352  \n",
+       "2          49119.189995  \n",
+       "3          71143.330561  \n",
+       "4          76746.258783  "
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "optimal_route = root_dir/'output'/'optimal_route_origin_destination'\n",
+    "optimal_route_graph = optimal_route / \"optimal_route_origin_destination_link_traffic.csv\"\n",
+    "traffic = pd.read_csv(optimal_route_graph)\n",
+    "df = traffic.copy()\n",
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a0104a74",
+   "metadata": {},
+   "source": [
+    "#### 2. Load the origin_destination graph edges that hold geometry"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "6df0d73f",
+   "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>u</th>\n",
+       "      <th>v</th>\n",
+       "      <th>key</th>\n",
+       "      <th>oneway</th>\n",
+       "      <th>name</th>\n",
+       "      <th>highway</th>\n",
+       "      <th>reversed</th>\n",
+       "      <th>length</th>\n",
+       "      <th>rfid_c</th>\n",
+       "      <th>rfid</th>\n",
+       "      <th>bridge</th>\n",
+       "      <th>junction</th>\n",
+       "      <th>lanes</th>\n",
+       "      <th>width</th>\n",
+       "      <th>access</th>\n",
+       "      <th>osmid_original</th>\n",
+       "      <th>geometry</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>559431729</td>\n",
+       "      <td>1848302290</td>\n",
+       "      <td>0</td>\n",
+       "      <td>True</td>\n",
+       "      <td>Jalan Agus Salim</td>\n",
+       "      <td>tertiary</td>\n",
+       "      <td>False</td>\n",
+       "      <td>9.0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1</td>\n",
+       "      <td>nan</td>\n",
+       "      <td>nan</td>\n",
+       "      <td>nan</td>\n",
+       "      <td>nan</td>\n",
+       "      <td>nan</td>\n",
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+       "      <td>LINESTRING (109.33922 -0.02962, 109.33915 -0.0...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>559431729</td>\n",
+       "      <td>559431731</td>\n",
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+       "      <td>True</td>\n",
+       "      <td>Jalan Gajah Mada</td>\n",
+       "      <td>tertiary</td>\n",
+       "      <td>False</td>\n",
+       "      <td>127.0</td>\n",
+       "      <td>[1425, 3, 2765, 6534]</td>\n",
+       "      <td>2</td>\n",
+       "      <td>nan</td>\n",
+       "      <td>nan</td>\n",
+       "      <td>nan</td>\n",
+       "      <td>nan</td>\n",
+       "      <td>nan</td>\n",
+       "      <td>43996468</td>\n",
+       "      <td>LINESTRING (109.33922 -0.02962, 109.33930 -0.0...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>559431729</td>\n",
+       "      <td>1977410506</td>\n",
+       "      <td>0</td>\n",
+       "      <td>True</td>\n",
+       "      <td>nan</td>\n",
+       "      <td>tertiary</td>\n",
+       "      <td>False</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>883</td>\n",
+       "      <td>97</td>\n",
+       "      <td>nan</td>\n",
+       "      <td>nan</td>\n",
+       "      <td>nan</td>\n",
+       "      <td>nan</td>\n",
+       "      <td>nan</td>\n",
+       "      <td>575398528</td>\n",
+       "      <td>LINESTRING (109.33922 -0.02962, 109.33916 -0.0...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>559431729</td>\n",
+       "      <td>1977410544</td>\n",
+       "      <td>0</td>\n",
+       "      <td>True</td>\n",
+       "      <td>Jalan Agus Salim</td>\n",
+       "      <td>tertiary</td>\n",
+       "      <td>False</td>\n",
+       "      <td>74.0</td>\n",
+       "      <td>[6530, 909]</td>\n",
+       "      <td>106</td>\n",
+       "      <td>nan</td>\n",
+       "      <td>nan</td>\n",
+       "      <td>nan</td>\n",
+       "      <td>nan</td>\n",
+       "      <td>nan</td>\n",
+       "      <td>43996479</td>\n",
+       "      <td>LINESTRING (109.33976 -0.02924, 109.33934 -0.0...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>559431731</td>\n",
+       "      <td>5891888009</td>\n",
+       "      <td>0</td>\n",
+       "      <td>True</td>\n",
+       "      <td>Jalan Gajah Mada</td>\n",
+       "      <td>tertiary</td>\n",
+       "      <td>False</td>\n",
+       "      <td>187.0</td>\n",
+       "      <td>[992, 993, 2144, 3939, 5, 3886, 6043, 2143]</td>\n",
+       "      <td>3</td>\n",
+       "      <td>nan</td>\n",
+       "      <td>nan</td>\n",
+       "      <td>nan</td>\n",
+       "      <td>nan</td>\n",
+       "      <td>nan</td>\n",
+       "      <td>43996468</td>\n",
+       "      <td>LINESTRING (109.33975 -0.03064, 109.33989 -0.0...</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           u           v  key  oneway              name   highway reversed  \\\n",
+       "0  559431729  1848302290    0    True  Jalan Agus Salim  tertiary    False   \n",
+       "1  559431729   559431731    0    True  Jalan Gajah Mada  tertiary    False   \n",
+       "2  559431729  1977410506    0    True               nan  tertiary    False   \n",
+       "3  559431729  1977410544    0    True  Jalan Agus Salim  tertiary    False   \n",
+       "4  559431731  5891888009    0    True  Jalan Gajah Mada  tertiary    False   \n",
+       "\n",
+       "   length                                       rfid_c  rfid bridge junction  \\\n",
+       "0     9.0                                            4     1    nan      nan   \n",
+       "1   127.0                        [1425, 3, 2765, 6534]     2    nan      nan   \n",
+       "2    14.0                                          883    97    nan      nan   \n",
+       "3    74.0                                  [6530, 909]   106    nan      nan   \n",
+       "4   187.0  [992, 993, 2144, 3939, 5, 3886, 6043, 2143]     3    nan      nan   \n",
+       "\n",
+       "  lanes width access osmid_original  \\\n",
+       "0   nan   nan    nan      782412294   \n",
+       "1   nan   nan    nan       43996468   \n",
+       "2   nan   nan    nan      575398528   \n",
+       "3   nan   nan    nan       43996479   \n",
+       "4   nan   nan    nan       43996468   \n",
+       "\n",
+       "                                            geometry  \n",
+       "0  LINESTRING (109.33922 -0.02962, 109.33915 -0.0...  \n",
+       "1  LINESTRING (109.33922 -0.02962, 109.33930 -0.0...  \n",
+       "2  LINESTRING (109.33922 -0.02962, 109.33916 -0.0...  \n",
+       "3  LINESTRING (109.33976 -0.02924, 109.33934 -0.0...  \n",
+       "4  LINESTRING (109.33975 -0.03064, 109.33989 -0.0...  "
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "path_output_graph = root_dir / \"static\" / \"output_graph\"\n",
+    "base_graph_edges = path_output_graph / \"origins_destinations_graph_edges.gpkg\"\n",
+    "edges_gdf = gpd.read_file(base_graph_edges, driver = \"GPKG\")\n",
+    "gdf = edges_gdf.copy()\n",
+    "edges_gdf.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "eebcab54",
+   "metadata": {},
+   "source": [
+    "#### 3. Merge analysis data with geometry "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "76685748",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for var in ['traffic', 'traffic_egalitarian', 'traffic_prioritarian']:\n",
+    "    gdf[var] = 0\n",
+    "    \n",
+    "    # Create a dictionary to store the values for faster lookup\n",
+    "    var_values = dict(zip(zip(df['u'], df['v']), df[var]))\n",
+    "\n",
+    "    for u, v in zip(df['u'], df['v']):\n",
+    "        if u != v:\n",
+    "            # Check if the edge (u, v) exists in the DataFrame\n",
+    "            if (u, v) in var_values:\n",
+    "                gdf.loc[(gdf['u'] == u) & (gdf['v'] == v), var] = var_values[(u, v)]\n",
+    "                \n",
+    "                # Check if the reverse edge (v, u) exists and hasn't been assigned a value yet\n",
+    "                if (v, u) not in var_values:\n",
+    "                    gdf.loc[(gdf['u'] == v) & (gdf['v'] == u), var] = var_values[(u, v)]\n",
+    "            else:\n",
+    "                # If the edge doesn't exist in the DataFrame, check if the reverse edge does\n",
+    "                if (v, u) in var_values:\n",
+    "                    gdf.loc[(gdf['u'] == v) & (gdf['v'] == u), var] = var_values[(v, u)]\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d4512585",
+   "metadata": {},
+   "source": [
+    "#### 4. Rank the edges based on the different traffic analysis results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "d8d7ff80",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "gdf['traffic_ranked'] = gdf['traffic'].rank(method='min', ascending=False)\n",
+    "gdf['traffic_egalitarian_ranked'] = gdf['traffic_egalitarian'].rank(method='min', ascending=False)\n",
+    "gdf['traffic_prioritarian_ranked'] = gdf['traffic_prioritarian'].rank(method='min', ascending=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7a291bb1",
+   "metadata": {},
+   "source": [
+    "# Visualize results"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fd661ba6",
+   "metadata": {},
+   "source": [
+    "The darker the edge, the higher its ranking, the more critical the network part \n",
+    "\n",
+    "Ranking 1 is the highest ranking, higher values represent lower rankings"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "37f909c8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1500x500 with 6 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, axs = plt.subplots(1, 3, figsize=(15, 5))\n",
+    "gdf.plot(column='traffic_ranked',cmap='gist_heat',ax=axs[0],legend=True)\n",
+    "axs[0].set_title('Utilitarian principle ranking')\n",
+    "gdf.plot(column='traffic_egalitarian_ranked', cmap='gist_heat', ax=axs[1], legend=True)\n",
+    "axs[1].set_title('Egalitarian principle ranking')\n",
+    "gdf.plot(column='traffic_prioritarian_ranked', cmap='gist_heat',ax=axs[2], legend=True)\n",
+    "axs[2].set_title('Prioritarian principle ranking')\n",
+    "\n",
+    "# Adjust layout\n",
+    "plt.tight_layout()\n",
+    "\n",
+    "# Show plot\n",
+    "plt.show()\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8f302147",
+   "metadata": {},
+   "source": [
+    "What does this tell us?\n",
+    "\n",
+    "The higher the ranking of an edge (values closer to 1), the more critical that part of the network, given the equity principle applied. In the utilitarian principle, this means the most people using that edge. In the egalitarian principle it means having each origin-destination pair having equal opportunity to acces, regardless of how many people live in one origin. In the last principle we correct for the provided equity weight and base the travel calculations on that. This prioritizes more vulnerable areas. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0318f0f8",
+   "metadata": {},
+   "source": [
+    "These insights can be used to for example prioritize network investments. Depending on the service of the network, the prioritization of investments can shift. If investments were to be done based on serving underpiviliged communities, the prioritarian ranking principle can be used, utilizing weights that represent priviliged and underpriviliged areas/communities/regions. As the user is free to specify their own 'equity weights', they can determine their own criteria for prioritization of areas. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "dd6495a5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "            );\n",
+       "        \n",
+       "    \n",
+       "        function geo_json_7c563e41ad1646b88f2baf29842aa32d_styler(feature) {\n",
+       "            switch(feature.id) {\n",
+       "                case &quot;0&quot;: case &quot;3&quot;: case &quot;5&quot;: case &quot;6&quot;: case &quot;13&quot;: case &quot;16&quot;: case &quot;21&quot;: case &quot;22&quot;: case &quot;23&quot;: case &quot;24&quot;: case &quot;27&quot;: case &quot;41&quot;: case &quot;45&quot;: case &quot;47&quot;: case &quot;49&quot;: case &quot;50&quot;: case &quot;51&quot;: case &quot;56&quot;: case &quot;57&quot;: case &quot;58&quot;: case &quot;59&quot;: case &quot;60&quot;: case &quot;61&quot;: case &quot;62&quot;: case &quot;63&quot;: case &quot;68&quot;: case &quot;71&quot;: case &quot;91&quot;: case &quot;97&quot;: case &quot;100&quot;: case &quot;101&quot;: case &quot;105&quot;: case &quot;107&quot;: case &quot;110&quot;: case &quot;111&quot;: case &quot;112&quot;: case &quot;113&quot;: case &quot;118&quot;: case &quot;119&quot;: case &quot;122&quot;: case &quot;125&quot;: case &quot;126&quot;: case &quot;131&quot;: case &quot;133&quot;: case &quot;136&quot;: case &quot;137&quot;: case &quot;140&quot;: case &quot;141&quot;: case &quot;142&quot;: case &quot;143&quot;: case &quot;146&quot;: case &quot;152&quot;: case &quot;155&quot;: case &quot;156&quot;: case &quot;160&quot;: case &quot;165&quot;: case &quot;172&quot;: case &quot;174&quot;: case &quot;180&quot;: case &quot;185&quot;: case &quot;186&quot;: case &quot;187&quot;: case &quot;188&quot;: case &quot;189&quot;: case &quot;190&quot;: case &quot;191&quot;: case &quot;192&quot;: case &quot;193&quot;: case &quot;198&quot;: case &quot;201&quot;: case &quot;209&quot;: case &quot;210&quot;: case &quot;211&quot;: case &quot;212&quot;: case &quot;213&quot;: case &quot;214&quot;: case &quot;215&quot;: case &quot;221&quot;: case &quot;222&quot;: case &quot;223&quot;: case &quot;224&quot;: case &quot;225&quot;: case &quot;226&quot;: case &quot;227&quot;: case &quot;228&quot;: case &quot;229&quot;: case &quot;230&quot;: case &quot;231&quot;: case &quot;232&quot;: case &quot;233&quot;: case &quot;234&quot;: case &quot;237&quot;: case &quot;238&quot;: case &quot;245&quot;: case &quot;246&quot;: case &quot;247&quot;: case &quot;248&quot;: case &quot;249&quot;: case &quot;250&quot;: case &quot;254&quot;: case &quot;255&quot;: case &quot;256&quot;: case &quot;258&quot;: case &quot;262&quot;: case &quot;264&quot;: case &quot;265&quot;: case &quot;266&quot;: case &quot;267&quot;: case &quot;268&quot;: case &quot;272&quot;: case &quot;278&quot;: case &quot;279&quot;: case &quot;280&quot;: case &quot;291&quot;: case &quot;296&quot;: case &quot;297&quot;: case &quot;301&quot;: case &quot;302&quot;: case &quot;305&quot;: case &quot;307&quot;: case &quot;308&quot;: case &quot;309&quot;: case &quot;313&quot;: case &quot;318&quot;: case &quot;326&quot;: case &quot;329&quot;: case &quot;331&quot;: case &quot;335&quot;: case &quot;337&quot;: case &quot;341&quot;: case &quot;344&quot;: case &quot;346&quot;: case &quot;348&quot;: case &quot;350&quot;: case &quot;351&quot;: case &quot;352&quot;: case &quot;353&quot;: case &quot;354&quot;: case &quot;359&quot;: case &quot;362&quot;: case &quot;370&quot;: case &quot;372&quot;: case &quot;376&quot;: case &quot;380&quot;: case &quot;382&quot;: case &quot;387&quot;: case &quot;391&quot;: case &quot;393&quot;: case &quot;394&quot;: case &quot;396&quot;: case &quot;397&quot;: case &quot;398&quot;: case &quot;399&quot;: case &quot;400&quot;: case &quot;401&quot;: case &quot;402&quot;: case &quot;403&quot;: case &quot;434&quot;: case &quot;453&quot;: case &quot;461&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ffffff&quot;, &quot;fillColor&quot;: &quot;#ffffff&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;1&quot;: case &quot;2&quot;: case &quot;4&quot;: case &quot;114&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#8b0000&quot;, &quot;fillColor&quot;: &quot;#8b0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;7&quot;: case &quot;8&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#de2900&quot;, &quot;fillColor&quot;: &quot;#de2900&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;9&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#fff5eb&quot;, &quot;fillColor&quot;: &quot;#fff5eb&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;10&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ffb367&quot;, &quot;fillColor&quot;: &quot;#ffb367&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;11&quot;: case &quot;12&quot;: case &quot;14&quot;: case &quot;244&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ffa74f&quot;, &quot;fillColor&quot;: &quot;#ffa74f&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;15&quot;: case &quot;17&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#f94d00&quot;, &quot;fillColor&quot;: &quot;#f94d00&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;18&quot;: case &quot;129&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#c90d00&quot;, &quot;fillColor&quot;: &quot;#c90d00&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;19&quot;: case &quot;39&quot;: case &quot;176&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#e12d00&quot;, &quot;fillColor&quot;: &quot;#e12d00&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;20&quot;: case &quot;271&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#210000&quot;, &quot;fillColor&quot;: &quot;#210000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;25&quot;: case &quot;26&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ac0000&quot;, &quot;fillColor&quot;: &quot;#ac0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;28&quot;: case &quot;33&quot;: case &quot;277&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#650000&quot;, &quot;fillColor&quot;: &quot;#650000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;29&quot;: case &quot;34&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#a50000&quot;, &quot;fillColor&quot;: &quot;#a50000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;30&quot;: case &quot;117&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#6c0000&quot;, &quot;fillColor&quot;: &quot;#6c0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;31&quot;: case &quot;32&quot;: case &quot;154&quot;: case &quot;157&quot;: case &quot;158&quot;: case &quot;316&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ffebd7&quot;, &quot;fillColor&quot;: &quot;#ffebd7&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;35&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#b50000&quot;, &quot;fillColor&quot;: &quot;#b50000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;36&quot;: case &quot;451&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#2d0000&quot;, &quot;fillColor&quot;: &quot;#2d0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;37&quot;: case &quot;138&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ff972f&quot;, &quot;fillColor&quot;: &quot;#ff972f&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;38&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ffe3c7&quot;, &quot;fillColor&quot;: &quot;#ffe3c7&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;40&quot;: case &quot;177&quot;: case &quot;181&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#1b0000&quot;, &quot;fillColor&quot;: &quot;#1b0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;42&quot;: case &quot;259&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#6f0000&quot;, &quot;fillColor&quot;: &quot;#6f0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;43&quot;: case &quot;44&quot;: case &quot;257&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#be0000&quot;, &quot;fillColor&quot;: &quot;#be0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;46&quot;: case &quot;48&quot;: case &quot;147&quot;: case &quot;148&quot;: case &quot;149&quot;: case &quot;194&quot;: case &quot;298&quot;: case &quot;299&quot;: case &quot;300&quot;: case &quot;306&quot;: case &quot;383&quot;: case &quot;392&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#4e0000&quot;, &quot;fillColor&quot;: &quot;#4e0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;52&quot;: case &quot;81&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ed3d00&quot;, &quot;fillColor&quot;: &quot;#ed3d00&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;53&quot;: case &quot;109&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#2e0000&quot;, &quot;fillColor&quot;: &quot;#2e0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;54&quot;: case &quot;55&quot;: case &quot;67&quot;: case &quot;69&quot;: case &quot;70&quot;: case &quot;102&quot;: case &quot;103&quot;: case &quot;385&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#3d0000&quot;, &quot;fillColor&quot;: &quot;#3d0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;64&quot;: case &quot;374&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#8a0000&quot;, &quot;fillColor&quot;: &quot;#8a0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;65&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#630000&quot;, &quot;fillColor&quot;: &quot;#630000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;66&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#270000&quot;, &quot;fillColor&quot;: &quot;#270000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;72&quot;: case &quot;73&quot;: case &quot;166&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ff5b00&quot;, &quot;fillColor&quot;: &quot;#ff5b00&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;74&quot;: case &quot;75&quot;: case &quot;77&quot;: case &quot;167&quot;: case &quot;168&quot;: case &quot;171&quot;: case &quot;368&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ff6100&quot;, &quot;fillColor&quot;: &quot;#ff6100&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;76&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#fe5300&quot;, &quot;fillColor&quot;: &quot;#fe5300&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;78&quot;: case &quot;440&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#d41b00&quot;, &quot;fillColor&quot;: &quot;#d41b00&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;79&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#5d0000&quot;, &quot;fillColor&quot;: &quot;#5d0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;80&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#4a0000&quot;, &quot;fillColor&quot;: &quot;#4a0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;82&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#e43100&quot;, &quot;fillColor&quot;: &quot;#e43100&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;83&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ffb76f&quot;, &quot;fillColor&quot;: &quot;#ffb76f&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;84&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#f84b00&quot;, &quot;fillColor&quot;: &quot;#f84b00&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;85&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#750000&quot;, &quot;fillColor&quot;: &quot;#750000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;86&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#960000&quot;, &quot;fillColor&quot;: &quot;#960000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;87&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#5e0000&quot;, &quot;fillColor&quot;: &quot;#5e0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;88&quot;: case &quot;317&quot;: case &quot;465&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#690000&quot;, &quot;fillColor&quot;: &quot;#690000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;89&quot;: case &quot;456&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#b20000&quot;, &quot;fillColor&quot;: &quot;#b20000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;90&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#aa0000&quot;, &quot;fillColor&quot;: &quot;#aa0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;92&quot;: case &quot;93&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#fff9f3&quot;, &quot;fillColor&quot;: &quot;#fff9f3&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;94&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#f64900&quot;, &quot;fillColor&quot;: &quot;#f64900&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;95&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#fc5100&quot;, &quot;fillColor&quot;: &quot;#fc5100&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;96&quot;: case &quot;431&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ffe5cb&quot;, &quot;fillColor&quot;: &quot;#ffe5cb&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;104&quot;: case &quot;106&quot;: case &quot;108&quot;: case &quot;405&quot;: case &quot;406&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#990000&quot;, &quot;fillColor&quot;: &quot;#990000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;115&quot;: case &quot;139&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#7e0000&quot;, &quot;fillColor&quot;: &quot;#7e0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;116&quot;: case &quot;457&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#980000&quot;, &quot;fillColor&quot;: &quot;#980000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;120&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#d21900&quot;, &quot;fillColor&quot;: &quot;#d21900&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;121&quot;: case &quot;282&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#620000&quot;, &quot;fillColor&quot;: &quot;#620000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;123&quot;: case &quot;124&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#000000&quot;, &quot;fillColor&quot;: &quot;#000000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;127&quot;: case &quot;128&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#bd0000&quot;, &quot;fillColor&quot;: &quot;#bd0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;130&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#b10000&quot;, &quot;fillColor&quot;: &quot;#b10000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;132&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#940000&quot;, &quot;fillColor&quot;: &quot;#940000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;134&quot;: case &quot;135&quot;: case &quot;295&quot;: case &quot;379&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ff9f3f&quot;, &quot;fillColor&quot;: &quot;#ff9f3f&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;144&quot;: case &quot;145&quot;: case &quot;336&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ff7300&quot;, &quot;fillColor&quot;: &quot;#ff7300&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;150&quot;: case &quot;459&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#1a0000&quot;, &quot;fillColor&quot;: &quot;#1a0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;151&quot;: case &quot;197&quot;: case &quot;199&quot;: case &quot;340&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#0c0000&quot;, &quot;fillColor&quot;: &quot;#0c0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;153&quot;: case &quot;159&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#160000&quot;, &quot;fillColor&quot;: &quot;#160000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;161&quot;: case &quot;162&quot;: case &quot;371&quot;: case &quot;373&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#f04100&quot;, &quot;fillColor&quot;: &quot;#f04100&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;163&quot;: case &quot;164&quot;: case &quot;332&quot;: case &quot;378&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#d61f00&quot;, &quot;fillColor&quot;: &quot;#d61f00&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;169&quot;: case &quot;170&quot;: case &quot;173&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ff9933&quot;, &quot;fillColor&quot;: &quot;#ff9933&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;175&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#dc2700&quot;, &quot;fillColor&quot;: &quot;#dc2700&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;178&quot;: case &quot;182&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#e53300&quot;, &quot;fillColor&quot;: &quot;#e53300&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;179&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#c30500&quot;, &quot;fillColor&quot;: &quot;#c30500&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;183&quot;: case &quot;184&quot;: case &quot;388&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#c40700&quot;, &quot;fillColor&quot;: &quot;#c40700&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;195&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ff6b00&quot;, &quot;fillColor&quot;: &quot;#ff6b00&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;196&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ce1300&quot;, &quot;fillColor&quot;: &quot;#ce1300&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;200&quot;: case &quot;202&quot;: case &quot;235&quot;: case &quot;236&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ff8307&quot;, &quot;fillColor&quot;: &quot;#ff8307&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;203&quot;: case &quot;381&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#cc1100&quot;, &quot;fillColor&quot;: &quot;#cc1100&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;204&quot;: case &quot;220&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ffbf7f&quot;, &quot;fillColor&quot;: &quot;#ffbf7f&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;205&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#d01700&quot;, &quot;fillColor&quot;: &quot;#d01700&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;206&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#bb0000&quot;, &quot;fillColor&quot;: &quot;#bb0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;207&quot;: case &quot;327&quot;: case &quot;328&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ff9123&quot;, &quot;fillColor&quot;: &quot;#ff9123&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;208&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#cf1500&quot;, &quot;fillColor&quot;: &quot;#cf1500&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;216&quot;: case &quot;219&quot;: case &quot;349&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ff6f00&quot;, &quot;fillColor&quot;: &quot;#ff6f00&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;217&quot;: case &quot;321&quot;: case &quot;322&quot;: case &quot;433&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ffb973&quot;, &quot;fillColor&quot;: &quot;#ffb973&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;218&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ee3f00&quot;, &quot;fillColor&quot;: &quot;#ee3f00&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;239&quot;: case &quot;320&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#040000&quot;, &quot;fillColor&quot;: &quot;#040000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;240&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#060000&quot;, &quot;fillColor&quot;: &quot;#060000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;241&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#100000&quot;, &quot;fillColor&quot;: &quot;#100000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;242&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#120000&quot;, &quot;fillColor&quot;: &quot;#120000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;243&quot;: case &quot;288&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#480000&quot;, &quot;fillColor&quot;: &quot;#480000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;251&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#2c0000&quot;, &quot;fillColor&quot;: &quot;#2c0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;252&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#7a0000&quot;, &quot;fillColor&quot;: &quot;#7a0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;253&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#310000&quot;, &quot;fillColor&quot;: &quot;#310000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;260&quot;: case &quot;263&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#a00000&quot;, &quot;fillColor&quot;: &quot;#a00000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;261&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ff8f1f&quot;, &quot;fillColor&quot;: &quot;#ff8f1f&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;269&quot;: case &quot;338&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#080000&quot;, &quot;fillColor&quot;: &quot;#080000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;270&quot;: case &quot;290&quot;: case &quot;460&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#140000&quot;, &quot;fillColor&quot;: &quot;#140000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;273&quot;: case &quot;274&quot;: case &quot;275&quot;: case &quot;404&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ffc993&quot;, &quot;fillColor&quot;: &quot;#ffc993&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;276&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#200000&quot;, &quot;fillColor&quot;: &quot;#200000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;281&quot;: case &quot;294&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ff8d1b&quot;, &quot;fillColor&quot;: &quot;#ff8d1b&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;283&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ff8103&quot;, &quot;fillColor&quot;: &quot;#ff8103&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;284&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#3c0000&quot;, &quot;fillColor&quot;: &quot;#3c0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;285&quot;: case &quot;287&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#3b0000&quot;, &quot;fillColor&quot;: &quot;#3b0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;286&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#360000&quot;, &quot;fillColor&quot;: &quot;#360000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;289&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#a60000&quot;, &quot;fillColor&quot;: &quot;#a60000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;292&quot;: case &quot;293&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ff5900&quot;, &quot;fillColor&quot;: &quot;#ff5900&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;303&quot;: case &quot;304&quot;: case &quot;384&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#330000&quot;, &quot;fillColor&quot;: &quot;#330000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;310&quot;: case &quot;324&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ffc387&quot;, &quot;fillColor&quot;: &quot;#ffc387&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;311&quot;: case &quot;314&quot;: case &quot;342&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ffd7af&quot;, &quot;fillColor&quot;: &quot;#ffd7af&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;312&quot;: case &quot;315&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ffd1a3&quot;, &quot;fillColor&quot;: &quot;#ffd1a3&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;319&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#030000&quot;, &quot;fillColor&quot;: &quot;#030000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;323&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ff7900&quot;, &quot;fillColor&quot;: &quot;#ff7900&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;325&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#280000&quot;, &quot;fillColor&quot;: &quot;#280000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;330&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#020000&quot;, &quot;fillColor&quot;: &quot;#020000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;333&quot;: case &quot;377&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#260000&quot;, &quot;fillColor&quot;: &quot;#260000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;334&quot;: case &quot;463&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#7d0000&quot;, &quot;fillColor&quot;: &quot;#7d0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;339&quot;: case &quot;364&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#840000&quot;, &quot;fillColor&quot;: &quot;#840000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;343&quot;: case &quot;345&quot;: case &quot;347&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ffddbb&quot;, &quot;fillColor&quot;: &quot;#ffddbb&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;355&quot;: case &quot;356&quot;: case &quot;366&quot;: case &quot;367&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ffad5b&quot;, &quot;fillColor&quot;: &quot;#ffad5b&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;357&quot;: case &quot;358&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#b80000&quot;, &quot;fillColor&quot;: &quot;#b80000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;360&quot;: case &quot;361&quot;: case &quot;363&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#e73500&quot;, &quot;fillColor&quot;: &quot;#e73500&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;365&quot;: case &quot;464&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#760000&quot;, &quot;fillColor&quot;: &quot;#760000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;369&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#d51d00&quot;, &quot;fillColor&quot;: &quot;#d51d00&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;375&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#240000&quot;, &quot;fillColor&quot;: &quot;#240000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;386&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#390000&quot;, &quot;fillColor&quot;: &quot;#390000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;389&quot;: case &quot;390&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ab0000&quot;, &quot;fillColor&quot;: &quot;#ab0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;395&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ffa54b&quot;, &quot;fillColor&quot;: &quot;#ffa54b&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;407&quot;: case &quot;408&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ff5500&quot;, &quot;fillColor&quot;: &quot;#ff5500&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;409&quot;: case &quot;454&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#fff7ef&quot;, &quot;fillColor&quot;: &quot;#fff7ef&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;410&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ffe1c3&quot;, &quot;fillColor&quot;: &quot;#ffe1c3&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;411&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ff7f00&quot;, &quot;fillColor&quot;: &quot;#ff7f00&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;412&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#a30000&quot;, &quot;fillColor&quot;: &quot;#a30000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;413&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#f44700&quot;, &quot;fillColor&quot;: &quot;#f44700&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;414&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#b70000&quot;, &quot;fillColor&quot;: &quot;#b70000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;415&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ffc78f&quot;, &quot;fillColor&quot;: &quot;#ffc78f&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;416&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#9f0000&quot;, &quot;fillColor&quot;: &quot;#9f0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;417&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#930000&quot;, &quot;fillColor&quot;: &quot;#930000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;418&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#a80000&quot;, &quot;fillColor&quot;: &quot;#a80000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;419&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#880000&quot;, &quot;fillColor&quot;: &quot;#880000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;420&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ec3b00&quot;, &quot;fillColor&quot;: &quot;#ec3b00&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;421&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#b00000&quot;, &quot;fillColor&quot;: &quot;#b00000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;422&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#c80b00&quot;, &quot;fillColor&quot;: &quot;#c80b00&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;423&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#fb4f00&quot;, &quot;fillColor&quot;: &quot;#fb4f00&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;424&quot;: case &quot;429&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#920000&quot;, &quot;fillColor&quot;: &quot;#920000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;425&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#850000&quot;, &quot;fillColor&quot;: &quot;#850000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;426&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#7b0000&quot;, &quot;fillColor&quot;: &quot;#7b0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;427&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#5b0000&quot;, &quot;fillColor&quot;: &quot;#5b0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;428&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#700000&quot;, &quot;fillColor&quot;: &quot;#700000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;430&quot;: case &quot;448&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ff7b00&quot;, &quot;fillColor&quot;: &quot;#ff7b00&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;432&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ffe7cf&quot;, &quot;fillColor&quot;: &quot;#ffe7cf&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;435&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#780000&quot;, &quot;fillColor&quot;: &quot;#780000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;436&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#370000&quot;, &quot;fillColor&quot;: &quot;#370000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;437&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#220000&quot;, &quot;fillColor&quot;: &quot;#220000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;438&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#870000&quot;, &quot;fillColor&quot;: &quot;#870000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;439&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ff6d00&quot;, &quot;fillColor&quot;: &quot;#ff6d00&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;441&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ff8b17&quot;, &quot;fillColor&quot;: &quot;#ff8b17&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;442&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#4d0000&quot;, &quot;fillColor&quot;: &quot;#4d0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;443&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#0a0000&quot;, &quot;fillColor&quot;: &quot;#0a0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;444&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ffcf9f&quot;, &quot;fillColor&quot;: &quot;#ffcf9f&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;445&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ffe9d3&quot;, &quot;fillColor&quot;: &quot;#ffe9d3&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;446&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#fffdfb&quot;, &quot;fillColor&quot;: &quot;#fffdfb&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;447&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ff7d00&quot;, &quot;fillColor&quot;: &quot;#ff7d00&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;449&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#db2500&quot;, &quot;fillColor&quot;: &quot;#db2500&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;450&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ba0000&quot;, &quot;fillColor&quot;: &quot;#ba0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;452&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#2a0000&quot;, &quot;fillColor&quot;: &quot;#2a0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;455&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#b40000&quot;, &quot;fillColor&quot;: &quot;#b40000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;458&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#820000&quot;, &quot;fillColor&quot;: &quot;#820000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;462&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#810000&quot;, &quot;fillColor&quot;: &quot;#810000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;466&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#600000&quot;, &quot;fillColor&quot;: &quot;#600000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;467&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#730000&quot;, &quot;fillColor&quot;: &quot;#730000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;468&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#720000&quot;, &quot;fillColor&quot;: &quot;#720000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;469&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#4b0000&quot;, &quot;fillColor&quot;: &quot;#4b0000&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;470&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ff8913&quot;, &quot;fillColor&quot;: &quot;#ff8913&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;471&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ffc58b&quot;, &quot;fillColor&quot;: &quot;#ffc58b&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                case &quot;472&quot;: \n",
+       "                    return {&quot;color&quot;: &quot;#ffb56b&quot;, &quot;fillColor&quot;: &quot;#ffb56b&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "                default:\n",
+       "                    return {&quot;color&quot;: &quot;#ffd3a7&quot;, &quot;fillColor&quot;: &quot;#ffd3a7&quot;, &quot;fillOpacity&quot;: 0.5, &quot;weight&quot;: 2};\n",
+       "            }\n",
+       "        }\n",
+       "        function geo_json_7c563e41ad1646b88f2baf29842aa32d_highlighter(feature) {\n",
+       "            switch(feature.id) {\n",
+       "                default:\n",
+       "                    return {&quot;fillOpacity&quot;: 0.75};\n",
+       "            }\n",
+       "        }\n",
+       "        function geo_json_7c563e41ad1646b88f2baf29842aa32d_pointToLayer(feature, latlng) {\n",
+       "            var opts = {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;#3388ff&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: true, &quot;fillColor&quot;: &quot;#3388ff&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;opacity&quot;: 1.0, &quot;radius&quot;: 2, &quot;stroke&quot;: true, &quot;weight&quot;: 3};\n",
+       "            \n",
+       "            let style = geo_json_7c563e41ad1646b88f2baf29842aa32d_styler(feature)\n",
+       "            Object.assign(opts, style)\n",
+       "            \n",
+       "            return new L.CircleMarker(latlng, opts)\n",
+       "        }\n",
+       "\n",
+       "        function geo_json_7c563e41ad1646b88f2baf29842aa32d_onEachFeature(feature, layer) {\n",
+       "            layer.on({\n",
+       "                mouseout: function(e) {\n",
+       "                    if(typeof e.target.setStyle === &quot;function&quot;){\n",
+       "                        geo_json_7c563e41ad1646b88f2baf29842aa32d.resetStyle(e.target);\n",
+       "                    }\n",
+       "                },\n",
+       "                mouseover: function(e) {\n",
+       "                    if(typeof e.target.setStyle === &quot;function&quot;){\n",
+       "                        const highlightStyle = geo_json_7c563e41ad1646b88f2baf29842aa32d_highlighter(e.target.feature)\n",
+       "                        e.target.setStyle(highlightStyle);\n",
+       "                    }\n",
+       "                },\n",
+       "            });\n",
+       "        };\n",
+       "        var geo_json_7c563e41ad1646b88f2baf29842aa32d = L.geoJson(null, {\n",
+       "                onEachFeature: geo_json_7c563e41ad1646b88f2baf29842aa32d_onEachFeature,\n",
+       "            \n",
+       "                style: geo_json_7c563e41ad1646b88f2baf29842aa32d_styler,\n",
+       "                pointToLayer: geo_json_7c563e41ad1646b88f2baf29842aa32d_pointToLayer,\n",
+       "        });\n",
+       "\n",
+       "        function geo_json_7c563e41ad1646b88f2baf29842aa32d_add (data) {\n",
+       "            geo_json_7c563e41ad1646b88f2baf29842aa32d\n",
+       "                .addData(data);\n",
+       "        }\n",
+       "            geo_json_7c563e41ad1646b88f2baf29842aa32d_add({&quot;bbox&quot;: [109.2819734, -0.0931726, 109.3826227, 0.0116772], &quot;features&quot;: [{&quot;bbox&quot;: [109.3391503, -0.02967, 109.3392187, -0.0296238], &quot;geometry&quot;: {&quot;coordinates&quot;: [[109.3392187, -0.0296238], [109.3391503, -0.02967]], &quot;type&quot;: &quot;LineString&quot;}, &quot;id&quot;: &quot;0&quot;, &quot;properties&quot;: {&quot;__folium_color&quot;: &quot;#ffffff&quot;, &quot;access&quot;: &quot;nan&quot;, &quot;bridge&quot;: &quot;nan&quot;, &quot;highway&quot;: &quot;tertiary&quot;, &quot;junction&quot;: &quot;nan&quot;, &quot;key&quot;: 0, &quot;lanes&quot;: &quot;nan&quot;, &quot;length&quot;: 9.0, &quot;name&quot;: &quot;Jalan Agus Salim&quot;, &quot;oneway&quot;: true, &quot;osmid_original&quot;: &quot;782412294&quot;, &quot;reversed&quot;: &quot;False&quot;, &quot;rfid&quot;: 1, &quot;rfid_c&quot;: &quot;4&quot;, &quot;traffic&quot;: 0.0, &quot;traffic_egalitarian&quot;: 0, &quot;traffic_egalitarian_ranked&quot;: 315.0, &quot;traffic_prioritarian&quot;: 0.0, &quot;traffic_prioritarian_ranked&quot;: 315.0, &quot;traffic_ranked&quot;: 315.0, &quot;u&quot;: 559431729, &quot;v&quot;: 1848302290, &quot;width&quot;: &quot;nan&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [109.3392187, -0.0306358, 109.3397495, -0.0296238], &quot;geometry&quot;: {&quot;coordinates&quot;: [[109.3392187, -0.0296238], [109.3393024, -0.0297757], [109.3395318, -0.030192], [109.3396737, -0.0304909], [109.3397495, -0.0306358]], &quot;type&quot;: &quot;LineString&quot;}, &quot;id&quot;: &quot;1&quot;, &quot;properties&quot;: {&quot;__folium_color&quot;: &quot;#8b0000&quot;, &quot;access&quot;: &quot;nan&quot;, &quot;bridge&quot;: &quot;nan&quot;, &quot;highway&quot;: &quot;tertiary&quot;, &quot;junction&quot;: &quot;nan&quot;, &quot;key&quot;: 0, &quot;lanes&quot;: &quot;nan&quot;, &quot;length&quot;: 127.0, &quot;name&quot;: &quot;Jalan Gajah Mada&quot;, &quot;oneway&quot;: true, &quot;osmid_original&quot;: &quot;43996468&quot;, &quot;reversed&quot;: &quot;False&quot;, &quot;rfid&quot;: 2, &quot;rfid_c&quot;: &quot;[1425, 3, 2765, 6534]&quot;, &quot;traffic&quot;: 10796.36012573242, &quot;traffic_egalitarian&quot;: 9, &quot;traffic_egalitarian_ranked&quot;: 236.0, &quot;traffic_prioritarian&quot;: 18151.007761509904, &quot;traffic_prioritarian_ranked&quot;: 116.0, &quot;traffic_ranked&quot;: 185.0, &quot;u&quot;: 559431729, &quot;v&quot;: 559431731, &quot;width&quot;: &quot;nan&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [109.339159, -0.0296238, 109.3392187, -0.0295164], &quot;geometry&quot;: {&quot;coordinates&quot;: [[109.3392187, -0.0296238], [109.339159, -0.0295164]], &quot;type&quot;: &quot;LineString&quot;}, &quot;id&quot;: &quot;2&quot;, &quot;properties&quot;: {&quot;__folium_color&quot;: &quot;#8b0000&quot;, &quot;access&quot;: &quot;nan&quot;, &quot;bridge&quot;: &quot;nan&quot;, &quot;highway&quot;: &quot;tertiary&quot;, &quot;junction&quot;: &quot;nan&quot;, &quot;key&quot;: 0, &quot;lanes&quot;: &quot;nan&quot;, &quot;length&quot;: 14.0, &quot;name&quot;: &quot;nan&quot;, &quot;oneway&quot;: true, &quot;osmid_original&quot;: &quot;575398528&quot;, &quot;reversed&quot;: &quot;False&quot;, &quot;rfid&quot;: 97, &quot;rfid_c&quot;: &quot;883&quot;, &quot;traffic&quot;: 10796.36012573242, &quot;traffic_egalitarian&quot;: 9, &quot;traffic_egalitarian_ranked&quot;: 236.0, &quot;traffic_prioritarian&quot;: 18151.007761509904, &quot;traffic_prioritarian_ranked&quot;: 116.0, &quot;traffic_ranked&quot;: 185.0, &quot;u&quot;: 559431729, &quot;v&quot;: 1977410506, &quot;width&quot;: &quot;nan&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [109.3392187, -0.0296238, 109.339759, -0.0292392], &quot;geometry&quot;: {&quot;coordinates&quot;: [[109.339759, -0.0292392], [109.3393438, -0.0295347], [109.3392187, -0.0296238]], &quot;type&quot;: &quot;LineString&quot;}, &quot;id&quot;: &quot;3&quot;, &quot;properties&quot;: {&quot;__folium_color&quot;: &quot;#ffffff&quot;, &quot;access&quot;: &quot;nan&quot;, &quot;bridge&quot;: &quot;nan&quot;, &quot;highway&quot;: &quot;tertiary&quot;, &quot;junction&quot;: &quot;nan&quot;, &quot;key&quot;: 0, &quot;lanes&quot;: &quot;nan&quot;, &quot;length&quot;: 74.0, &quot;name&quot;: &quot;Jalan Agus Salim&quot;, &quot;oneway&quot;: true, &quot;osmid_original&quot;: &quot;43996479&quot;, &quot;reversed&quot;: &quot;False&quot;, &quot;rfid&quot;: 106, &quot;rfid_c&quot;: &quot;[6530, 909]&quot;, &quot;traffic&quot;: 0.0, &quot;traffic_egalitarian&quot;: 0, &quot;traffic_egalitarian_ranked&quot;: 315.0, &quot;traffic_prioritarian&quot;: 0.0, &quot;traffic_prioritarian_ranked&quot;: 315.0, &quot;traffic_ranked&quot;: 315.0, &quot;u&quot;: 559431729, &quot;v&quot;: 1977410544, &quot;width&quot;: &quot;nan&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [109.3397495, -0.032194, 109.340385, -0.0306358], &quot;geometry&quot;: {&quot;coordinates&quot;: [[109.3397495, -0.0306358], [109.3398941, -0.030971], [109.3399297, -0.0310487], [109.3401653, -0.0315138], [109.3402461, -0.0316762], [109.3402646, -0.0317325], [109.3402925, -0.0318482], [109.3403367, -0.0320109], [109.340385, -0.032194]], &quot;type&quot;: &quot;LineString&quot;}, &quot;id&quot;: &quot;4&quot;, &quot;properties&quot;: {&quot;__folium_color&quot;: &quot;#8b0000&quot;, &quot;access&quot;: &quot;nan&quot;, &quot;bridge&quot;: &quot;nan&quot;, &quot;highway&quot;: &quot;tertiary&quot;, &quot;junction&quot;: &quot;nan&quot;, &quot;key&quot;: 0, &quot;lanes&quot;: &quot;nan&quot;, &quot;length&quot;: 187.0, &quot;name&quot;: &quot;Jalan Gajah Mada&quot;, &quot;oneway&quot;: true, &quot;osmid_original&quot;: &quot;43996468&quot;, &quot;reversed&quot;: &quot;False&quot;, &quot;rfid&quot;: 3, &quot;rfid_c&quot;: &quot;[992, 993, 2144, 3939, 5, 3886, 6043, 2143]&quot;, &quot;traffic&quot;: 10796.36012573242, &quot;traffic_egalitarian&quot;: 9, &quot;traffic_egalitarian_ranked&quot;: 236.0, &quot;traffic_prioritarian&quot;: 18151.007761509904, &quot;traffic_prioritarian_ranked&quot;: 116.0, &quot;traffic_ranked&quot;: 185.0, &quot;u&quot;: 559431731, &quot;v&quot;: 5891888009, &quot;width&quot;: &quot;nan&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [109.3396832, -0.030659, 109.3397495, -0.0306358], &quot;geometry&quot;: {&quot;coordinates&quot;: [[109.3397495, -0.0306358], [109.3396832, -0.030659]], &quot;type&quot;: &quot;LineString&quot;}, &quot;id&quot;: &quot;5&quot;, &quot;properties&quot;: {&quot;__folium_color&quot;: &quot;#ffffff&quot;, &quot;access&quot;: &quot;nan&quot;, &quot;bridge&quot;: &quot;nan&quot;, &quot;highway&quot;: &quot;tertiary_link&quot;, &quot;junction&quot;: &quot;nan&quot;, &quot;key&quot;: 0, &quot;lanes&quot;: &quot;nan&quot;, &quot;length&quot;: 8.0, &quot;name&quot;: &quot;nan&quot;, &quot;oneway&quot;: true, &quot;osmid_original&quot;: &quot;187052115&quot;, &quot;reversed&quot;: &quot;False&quot;, &quot;rfid&quot;: 83, &quot;rfid_c&quot;: &quot;806&quot;, &quot;traffic&quot;: 0.0, &quot;traffic_egalitarian&quot;: 0, &quot;traffic_egalitarian_ranked&quot;: 315.0, &quot;traffic_prioritarian&quot;: 0.0, &quot;traffic_prioritarian_ranked&quot;: 315.0, &quot;traffic_ranked&quot;: 315.0, &quot;u&quot;: 559431731, &quot;v&quot;: 1957952262, &quot;width&quot;: &quot;nan&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [109.3605443, -0.0531907, 109.3610346, -0.0529281], &quot;geometry&quot;: {&quot;coordinates&quot;: [[109.3610346, -0.0529281], [109.3605443, -0.0531907]], &quot;type&quot;: &quot;LineString&quot;}, &quot;id&quot;: &quot;6&quot;, &quot;properties&quot;: {&quot;__folium_color&quot;: &quot;#ffffff&quot;, &quot;access&quot;: &quot;nan&quot;, &quot;bridge&quot;: &quot;nan&quot;, &quot;highway&quot;: &quot;tertiary&quot;, &quot;junction&quot;: &quot;nan&quot;, &quot;key&quot;: 0, &quot;lanes&quot;: &quot;nan&quot;, &quot;length&quot;: 62.0, &quot;name&quot;: &quot;Jalan Abdurahman Saleh&quot;, &quot;oneway&quot;: true, &quot;osmid_original&quot;: &quot;245935890&quot;, &quot;reversed&quot;: &quot;False&quot;, &quot;rfid&quot;: 4, &quot;rfid_c&quot;: &quot;25&quot;, &quot;traffic&quot;: 0.0, &quot;traffic_egalitarian&quot;: 0, &quot;traffic_egalitarian_ranked&quot;: 315.0, &quot;traffic_prioritarian&quot;: 0.0, &quot;traffic_prioritarian_ranked&quot;: 315.0, &quot;traffic_ranked&quot;: 315.0, &quot;u&quot;: 586717899, &quot;v&quot;: 2530351161, &quot;width&quot;: &quot;nan&quot;}, &quot;type&quot;: &quot;Feature&quot;}, {&quot;bbox&quot;: [109.3609793, -0.0529281, 109.3610346, -0.0528555], &quot;geometry&quot;: {&quot;coordinates&quot;: [[109.3610346, -0.0529281], [109.3609793, -0.0528555]], &quot;type&quot;: &quot;LineString&quot;}, &quot;id&quot;: &quot;7&quot;, &quot;properties&quot;: {&quot;__folium_color&quot;: &quot;#de2900&quot;, 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180189183]&quot;, &quot;reversed&quot;: &quot;True&quot;, &quot;rfid&quot;: 209, &quot;rfid_c&quot;: &quot;[2570, 2572, 2574, 2576, 2578, 2580, 2582, 2584, 2586, 2588, 2590, 2592, 2594, 2596, 2598, 626, 630, 634, 636, 637, 642, 648, 3721, 650, 652, 662, 668, 4775, 688, 5307, 5357, 5359, 5361, 6392, 3351, 3361, 3363, 3377, 4420, 4422, 4424, 4426, 4428, 3413, 3415, 3417, 3419, 2908, 3421, 3423, 3427, 4459, 2417, 2419, 2421, 2423, 2425, 2427, 2429, 4989, 2431, 4991, 2433, 2435, 4997, 2437, 2439, 2441, 2443, 2445, 2447, 2449, 2451, 2453, 2455, 2457, 2458, 5022, 4529, 4531, 4533, 3531, 3533, 3535, 3537, 3539, 3541, 3543, 3547, 3549, 3551, 3553, 3044, 3046, 3048, 3050, 3052]&quot;, &quot;traffic&quot;: 3222.84130859375, &quot;traffic_egalitarian&quot;: 5, &quot;traffic_egalitarian_ranked&quot;: 250.0, &quot;traffic_prioritarian&quot;: 1243.4170774805802, &quot;traffic_prioritarian_ranked&quot;: 269.0, &quot;traffic_ranked&quot;: 278.0, &quot;u&quot;: 10736480882, &quot;v&quot;: 10736480883, &quot;width&quot;: &quot;nan&quot;}, &quot;type&quot;: &quot;Feature&quot;}], &quot;type&quot;: &quot;FeatureCollection&quot;});\n",
+       "\n",
+       "        \n",
+       "    \n",
+       "    geo_json_7c563e41ad1646b88f2baf29842aa32d.bindTooltip(\n",
+       "    function(layer){\n",
+       "    let div = L.DomUtil.create(&#x27;div&#x27;);\n",
+       "    \n",
+       "    let handleObject = feature=&gt;typeof(feature)==&#x27;object&#x27; ? JSON.stringify(feature) : feature;\n",
+       "    let fields = [&quot;u&quot;, &quot;v&quot;, &quot;key&quot;, &quot;oneway&quot;, &quot;name&quot;, &quot;highway&quot;, &quot;reversed&quot;, &quot;length&quot;, &quot;rfid_c&quot;, &quot;rfid&quot;, &quot;bridge&quot;, &quot;junction&quot;, &quot;lanes&quot;, &quot;width&quot;, &quot;access&quot;, &quot;osmid_original&quot;, &quot;traffic&quot;, &quot;traffic_egalitarian&quot;, &quot;traffic_prioritarian&quot;, &quot;traffic_ranked&quot;, &quot;traffic_egalitarian_ranked&quot;, &quot;traffic_prioritarian_ranked&quot;];\n",
+       "    let aliases = [&quot;u&quot;, &quot;v&quot;, &quot;key&quot;, &quot;oneway&quot;, &quot;name&quot;, &quot;highway&quot;, &quot;reversed&quot;, &quot;length&quot;, &quot;rfid_c&quot;, &quot;rfid&quot;, &quot;bridge&quot;, &quot;junction&quot;, &quot;lanes&quot;, &quot;width&quot;, &quot;access&quot;, &quot;osmid_original&quot;, &quot;traffic&quot;, &quot;traffic_egalitarian&quot;, &quot;traffic_prioritarian&quot;, &quot;traffic_ranked&quot;, &quot;traffic_egalitarian_ranked&quot;, &quot;traffic_prioritarian_ranked&quot;];\n",
+       "    let table = &#x27;&lt;table&gt;&#x27; +\n",
+       "        String(\n",
+       "        fields.map(\n",
+       "        (v,i)=&gt;\n",
+       "        `&lt;tr&gt;\n",
+       "            &lt;th&gt;${aliases[i]}&lt;/th&gt;\n",
+       "            \n",
+       "            &lt;td&gt;${handleObject(layer.feature.properties[v])}&lt;/td&gt;\n",
+       "        &lt;/tr&gt;`).join(&#x27;&#x27;))\n",
+       "    +&#x27;&lt;/table&gt;&#x27;;\n",
+       "    div.innerHTML=table;\n",
+       "    \n",
+       "    return div\n",
+       "    }\n",
+       "    ,{&quot;className&quot;: &quot;foliumtooltip&quot;, &quot;sticky&quot;: true});\n",
+       "                     \n",
+       "    \n",
+       "                geo_json_7c563e41ad1646b88f2baf29842aa32d.addTo(map_21916fa20e58c80cc80d08abb8d1e7a6);\n",
+       "    \n",
+       "    var color_map_aa547979798ba73255e770639825a1d1 = {};\n",
+       "\n",
+       "    \n",
+       "    color_map_aa547979798ba73255e770639825a1d1.color = d3.scale.threshold()\n",
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+       "    \n",
+       "\n",
+       "    color_map_aa547979798ba73255e770639825a1d1.x = d3.scale.linear()\n",
+       "              .domain([1.0, 315.0])\n",
+       "              .range([0, 450 - 50]);\n",
+       "\n",
+       "    color_map_aa547979798ba73255e770639825a1d1.legend = L.control({position: &#x27;topright&#x27;});\n",
+       "    color_map_aa547979798ba73255e770639825a1d1.legend.onAdd = function (map) {var div = L.DomUtil.create(&#x27;div&#x27;, &#x27;legend&#x27;); return div};\n",
+       "    color_map_aa547979798ba73255e770639825a1d1.legend.addTo(map_21916fa20e58c80cc80d08abb8d1e7a6);\n",
+       "\n",
+       "    color_map_aa547979798ba73255e770639825a1d1.xAxis = d3.svg.axis()\n",
+       "        .scale(color_map_aa547979798ba73255e770639825a1d1.x)\n",
+       "        .orient(&quot;top&quot;)\n",
+       "        .tickSize(1)\n",
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+       "\n",
+       "    color_map_aa547979798ba73255e770639825a1d1.svg = d3.select(&quot;.legend.leaflet-control&quot;).append(&quot;svg&quot;)\n",
+       "        .attr(&quot;id&quot;, &#x27;legend&#x27;)\n",
+       "        .attr(&quot;width&quot;, 450)\n",
+       "        .attr(&quot;height&quot;, 40);\n",
+       "\n",
+       "    color_map_aa547979798ba73255e770639825a1d1.g = color_map_aa547979798ba73255e770639825a1d1.svg.append(&quot;g&quot;)\n",
+       "        .attr(&quot;class&quot;, &quot;key&quot;)\n",
+       "        .attr(&quot;transform&quot;, &quot;translate(25,16)&quot;);\n",
+       "\n",
+       "    color_map_aa547979798ba73255e770639825a1d1.g.selectAll(&quot;rect&quot;)\n",
+       "        .data(color_map_aa547979798ba73255e770639825a1d1.color.range().map(function(d, i) {\n",
+       "          return {\n",
+       "            x0: i ? color_map_aa547979798ba73255e770639825a1d1.x(color_map_aa547979798ba73255e770639825a1d1.color.domain()[i - 1]) : color_map_aa547979798ba73255e770639825a1d1.x.range()[0],\n",
+       "            x1: i &lt; color_map_aa547979798ba73255e770639825a1d1.color.domain().length ? color_map_aa547979798ba73255e770639825a1d1.x(color_map_aa547979798ba73255e770639825a1d1.color.domain()[i]) : color_map_aa547979798ba73255e770639825a1d1.x.range()[1],\n",
+       "            z: d\n",
+       "          };\n",
+       "        }))\n",
+       "      .enter().append(&quot;rect&quot;)\n",
+       "        .attr(&quot;height&quot;, 40 - 30)\n",
+       "        .attr(&quot;x&quot;, function(d) { return d.x0; })\n",
+       "        .attr(&quot;width&quot;, function(d) { return d.x1 - d.x0; })\n",
+       "        .style(&quot;fill&quot;, function(d) { return d.z; });\n",
+       "\n",
+       "    color_map_aa547979798ba73255e770639825a1d1.g.call(color_map_aa547979798ba73255e770639825a1d1.xAxis).append(&quot;text&quot;)\n",
+       "        .attr(&quot;class&quot;, &quot;caption&quot;)\n",
+       "        .attr(&quot;y&quot;, 21)\n",
+       "        .text(&quot;traffic_prioritarian_ranked&quot;);\n",
+       "&lt;/script&gt;\n",
+       "&lt;/html&gt;\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
+      ],
+      "text/plain": [
+       "<folium.folium.Map at 0x1a356ecbe20>"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "gdf.explore(column='traffic_prioritarian_ranked', tiles=\"CartoDB positron\", cmap='gist_heat')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}