Bokeh visualizations

Former-commit-id: 8955e62d6a66da2b2e39a58380be9c0959c08f60
2026-01-09 14:57:56 -05:00 · 2020-02-12 15:09:42 -05:00
parent d5655f753e
commit 4d50963c6f
27 changed files with 433 additions and 0 deletions
--- a/graphs/shapefiles/simple1000_clipped_county.dbf
+++ b/graphs/shapefiles/simple1000_clipped_county.dbf
--- a/graphs/shapefiles/simple1000_clipped_county.prj
+++ b/graphs/shapefiles/simple1000_clipped_county.prj
@@ -0,0 +1 @@
+PROJCS["NAD83_HARN_Texas_Centric_Albers_Equal_Area",GEOGCS["GCS_NAD83(HARN)",DATUM["D_North_American_1983_HARN",SPHEROID["GRS_1980",6378137,298.257222101]],PRIMEM["Greenwich",0],UNIT["Degree",0.017453292519943295]],PROJECTION["Albers"],PARAMETER["standard_parallel_1",27.5],PARAMETER["standard_parallel_2",35],PARAMETER["latitude_of_origin",18],PARAMETER["central_meridian",-100],PARAMETER["false_easting",1500000],PARAMETER["false_northing",6000000],UNIT["Meter",1]]
--- a/graphs/shapefiles/simple1000_clipped_county.qpj
+++ b/graphs/shapefiles/simple1000_clipped_county.qpj
@@ -0,0 +1 @@
+PROJCS["NAD83(HARN) / Texas Centric Albers Equal Area",GEOGCS["NAD83(HARN)",DATUM["NAD83_High_Accuracy_Reference_Network",SPHEROID["GRS 1980",6378137,298.257222101,AUTHORITY["EPSG","7019"]],TOWGS84[0,0,0,0,0,0,0],AUTHORITY["EPSG","6152"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4152"]],PROJECTION["Albers_Conic_Equal_Area"],PARAMETER["standard_parallel_1",27.5],PARAMETER["standard_parallel_2",35],PARAMETER["latitude_of_center",18],PARAMETER["longitude_of_center",-100],PARAMETER["false_easting",1500000],PARAMETER["false_northing",6000000],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["X",EAST],AXIS["Y",NORTH],AUTHORITY["EPSG","3085"]]
--- a/graphs/shapefiles/simple1000_clipped_county.shp.REMOVED.git-id
+++ b/graphs/shapefiles/simple1000_clipped_county.shp.REMOVED.git-id
@@ -0,0 +1 @@
+2a8f074a67f33bda86d85297b7fea83090e64a37
--- a/graphs/shapefiles/simple1000_clipped_county.shx
+++ b/graphs/shapefiles/simple1000_clipped_county.shx
--- a/graphs/shapefiles/simple1000_clipped_huc8.dbf.REMOVED.git-id
+++ b/graphs/shapefiles/simple1000_clipped_huc8.dbf.REMOVED.git-id
@@ -0,0 +1 @@
+66b583ac6076324bafaac49f29679adbfba9764d
--- a/graphs/shapefiles/simple1000_clipped_huc8.prj
+++ b/graphs/shapefiles/simple1000_clipped_huc8.prj
@@ -0,0 +1 @@
+PROJCS["NAD83_HARN_Texas_Centric_Albers_Equal_Area",GEOGCS["GCS_NAD83(HARN)",DATUM["D_North_American_1983_HARN",SPHEROID["GRS_1980",6378137,298.257222101]],PRIMEM["Greenwich",0],UNIT["Degree",0.017453292519943295]],PROJECTION["Albers"],PARAMETER["standard_parallel_1",27.5],PARAMETER["standard_parallel_2",35],PARAMETER["latitude_of_origin",18],PARAMETER["central_meridian",-100],PARAMETER["false_easting",1500000],PARAMETER["false_northing",6000000],UNIT["Meter",1]]
--- a/graphs/shapefiles/simple1000_clipped_huc8.qpj
+++ b/graphs/shapefiles/simple1000_clipped_huc8.qpj
@@ -0,0 +1 @@
+PROJCS["NAD83(HARN) / Texas Centric Albers Equal Area",GEOGCS["NAD83(HARN)",DATUM["NAD83_High_Accuracy_Reference_Network",SPHEROID["GRS 1980",6378137,298.257222101,AUTHORITY["EPSG","7019"]],TOWGS84[0,0,0,0,0,0,0],AUTHORITY["EPSG","6152"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4152"]],PROJECTION["Albers_Conic_Equal_Area"],PARAMETER["standard_parallel_1",27.5],PARAMETER["standard_parallel_2",35],PARAMETER["latitude_of_center",18],PARAMETER["longitude_of_center",-100],PARAMETER["false_easting",1500000],PARAMETER["false_northing",6000000],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["X",EAST],AXIS["Y",NORTH],AUTHORITY["EPSG","3085"]]
--- a/graphs/shapefiles/simple1000_clipped_huc8.shp.REMOVED.git-id
+++ b/graphs/shapefiles/simple1000_clipped_huc8.shp.REMOVED.git-id
@@ -0,0 +1 @@
+9fbc0f21af568b1a94c561cd1d9a6e6ec6a41836
--- a/graphs/shapefiles/simple1000_clipped_huc8.shx
+++ b/graphs/shapefiles/simple1000_clipped_huc8.shx
--- a/graphs/shapefiles/simple1000_clipped_latlon.dbf
+++ b/graphs/shapefiles/simple1000_clipped_latlon.dbf
--- a/graphs/shapefiles/simple1000_clipped_latlon.prj
+++ b/graphs/shapefiles/simple1000_clipped_latlon.prj
@@ -0,0 +1 @@
+PROJCS["NAD83_HARN_Texas_Centric_Albers_Equal_Area",GEOGCS["GCS_NAD83(HARN)",DATUM["D_North_American_1983_HARN",SPHEROID["GRS_1980",6378137,298.257222101]],PRIMEM["Greenwich",0],UNIT["Degree",0.017453292519943295]],PROJECTION["Albers"],PARAMETER["standard_parallel_1",27.5],PARAMETER["standard_parallel_2",35],PARAMETER["latitude_of_origin",18],PARAMETER["central_meridian",-100],PARAMETER["false_easting",1500000],PARAMETER["false_northing",6000000],UNIT["Meter",1]]
--- a/graphs/shapefiles/simple1000_clipped_latlon.qpj
+++ b/graphs/shapefiles/simple1000_clipped_latlon.qpj
@@ -0,0 +1 @@
+PROJCS["NAD83(HARN) / Texas Centric Albers Equal Area",GEOGCS["NAD83(HARN)",DATUM["NAD83_High_Accuracy_Reference_Network",SPHEROID["GRS 1980",6378137,298.257222101,AUTHORITY["EPSG","7019"]],TOWGS84[0,0,0,0,0,0,0],AUTHORITY["EPSG","6152"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4152"]],PROJECTION["Albers_Conic_Equal_Area"],PARAMETER["standard_parallel_1",27.5],PARAMETER["standard_parallel_2",35],PARAMETER["latitude_of_center",18],PARAMETER["longitude_of_center",-100],PARAMETER["false_easting",1500000],PARAMETER["false_northing",6000000],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["X",EAST],AXIS["Y",NORTH],AUTHORITY["EPSG","3085"]]
--- a/graphs/shapefiles/simple1000_clipped_latlon.shp
+++ b/graphs/shapefiles/simple1000_clipped_latlon.shp
--- a/graphs/shapefiles/simple1000_clipped_latlon.shx
+++ b/graphs/shapefiles/simple1000_clipped_latlon.shx
--- a/graphs/shapefiles/simple1000_clipped_nerc.dbf
+++ b/graphs/shapefiles/simple1000_clipped_nerc.dbf
--- a/graphs/shapefiles/simple1000_clipped_nerc.prj
+++ b/graphs/shapefiles/simple1000_clipped_nerc.prj
@@ -0,0 +1 @@
+PROJCS["NAD83_HARN_Texas_Centric_Albers_Equal_Area",GEOGCS["GCS_NAD83(HARN)",DATUM["D_North_American_1983_HARN",SPHEROID["GRS_1980",6378137,298.257222101]],PRIMEM["Greenwich",0],UNIT["Degree",0.017453292519943295]],PROJECTION["Albers"],PARAMETER["standard_parallel_1",27.5],PARAMETER["standard_parallel_2",35],PARAMETER["latitude_of_origin",18],PARAMETER["central_meridian",-100],PARAMETER["false_easting",1500000],PARAMETER["false_northing",6000000],UNIT["Meter",1]]
--- a/graphs/shapefiles/simple1000_clipped_nerc.qpj
+++ b/graphs/shapefiles/simple1000_clipped_nerc.qpj
@@ -0,0 +1 @@
+PROJCS["NAD83(HARN) / Texas Centric Albers Equal Area",GEOGCS["NAD83(HARN)",DATUM["NAD83_High_Accuracy_Reference_Network",SPHEROID["GRS 1980",6378137,298.257222101,AUTHORITY["EPSG","7019"]],TOWGS84[0,0,0,0,0,0,0],AUTHORITY["EPSG","6152"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4152"]],PROJECTION["Albers_Conic_Equal_Area"],PARAMETER["standard_parallel_1",27.5],PARAMETER["standard_parallel_2",35],PARAMETER["latitude_of_center",18],PARAMETER["longitude_of_center",-100],PARAMETER["false_easting",1500000],PARAMETER["false_northing",6000000],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["X",EAST],AXIS["Y",NORTH],AUTHORITY["EPSG","3085"]]
--- a/graphs/shapefiles/simple1000_clipped_nerc.shp
+++ b/graphs/shapefiles/simple1000_clipped_nerc.shp
--- a/graphs/shapefiles/simple1000_clipped_nerc.shx
+++ b/graphs/shapefiles/simple1000_clipped_nerc.shx
--- a/graphs/shapefiles/simple1000_clipped_state.dbf
+++ b/graphs/shapefiles/simple1000_clipped_state.dbf
--- a/graphs/shapefiles/simple1000_clipped_state.prj
+++ b/graphs/shapefiles/simple1000_clipped_state.prj
@@ -0,0 +1 @@
+PROJCS["NAD83_HARN_Texas_Centric_Albers_Equal_Area",GEOGCS["GCS_NAD83(HARN)",DATUM["D_North_American_1983_HARN",SPHEROID["GRS_1980",6378137,298.257222101]],PRIMEM["Greenwich",0],UNIT["Degree",0.017453292519943295]],PROJECTION["Albers"],PARAMETER["standard_parallel_1",27.5],PARAMETER["standard_parallel_2",35],PARAMETER["latitude_of_origin",18],PARAMETER["central_meridian",-100],PARAMETER["false_easting",1500000],PARAMETER["false_northing",6000000],UNIT["Meter",1]]
--- a/graphs/shapefiles/simple1000_clipped_state.qpj
+++ b/graphs/shapefiles/simple1000_clipped_state.qpj
@@ -0,0 +1 @@
+PROJCS["NAD83(HARN) / Texas Centric Albers Equal Area",GEOGCS["NAD83(HARN)",DATUM["NAD83_High_Accuracy_Reference_Network",SPHEROID["GRS 1980",6378137,298.257222101,AUTHORITY["EPSG","7019"]],TOWGS84[0,0,0,0,0,0,0],AUTHORITY["EPSG","6152"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4152"]],PROJECTION["Albers_Conic_Equal_Area"],PARAMETER["standard_parallel_1",27.5],PARAMETER["standard_parallel_2",35],PARAMETER["latitude_of_center",18],PARAMETER["longitude_of_center",-100],PARAMETER["false_easting",1500000],PARAMETER["false_northing",6000000],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["X",EAST],AXIS["Y",NORTH],AUTHORITY["EPSG","3085"]]
--- a/graphs/shapefiles/simple1000_clipped_state.shp
+++ b/graphs/shapefiles/simple1000_clipped_state.shp
--- a/graphs/shapefiles/simple1000_clipped_state.shx
+++ b/graphs/shapefiles/simple1000_clipped_state.shx
--- a/viz/Plot.ipynb
+++ b/viz/Plot.ipynb
@@ -0,0 +1,229 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Plot data on a choropleth map"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "json_file = \"path/to/mongo_doc.json\"  # path to the Mongo document to plot\n",
+    "shapefile_dir = \"path/to/shapefiles/\"  # path to the directory of shapefiles\n",
+    "plot_width = 1200  # pixel width of the plot\n",
+    "plot_height = 800  # pixel height of the plot\n",
+    "projection = 4326  # coordinate reference system to use for plotting"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## import packages"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "from geopandas import read_file\n",
+    "import pandas as pd\n",
+    "import json\n",
+    "\n",
+    "from bokeh.io import show\n",
+    "from bokeh.models import LogColorMapper\n",
+    "from bokeh.palettes import Blues256 as palette\n",
+    "palette.reverse()\n",
+    "from bokeh.plotting import figure, output_file, save"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## geopandas functions for getting coordinates\n",
+    "### references:\n",
+    "\n",
+    "https://automating-gis-processes.github.io/2016/Lesson5-interactive-map-bokeh.html\n",
+    "\n",
+    "https://discourse.bokeh.org/t/mapping-europe-with-bokeh-using-geopandas-and-handling-multipolygons/2571"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def getXYCoords(geometry, coord_type):\n",
+    "    # Returns either x or y coordinates from geometry coordinate sequence. Used with LineString and Polygon geometries.\"\"\"\n",
+    "    if coord_type == 'x':\n",
+    "        return list(geometry.coords.xy[0])\n",
+    "    elif coord_type == 'y':\n",
+    "        return list(geometry.coords.xy[1])\n",
+    "\n",
+    "def getPolyCoords(geometry, coord_type):\n",
+    "    # Returns Coordinates of Polygon using the Exterior of the Polygon.\"\"\"\n",
+    "    ext = geometry.exterior\n",
+    "    return getXYCoords(ext, coord_type)\n",
+    "\n",
+    "def multiGeomHandler(multi_geometry, coord_type, geom_type):\n",
+    "    \"\"\"\n",
+    "    Function for handling multi-geometries. Can be MultiPoint, MultiLineString or MultiPolygon.\n",
+    "    Returns a list of coordinates where all parts of Multi-geometries are merged into a single list.\n",
+    "    Individual geometries are separated with np.nan which is how Bokeh wants them.\n",
+    "    # Bokeh documentation regarding the Multi-geometry issues can be found here (it is an open issue)\n",
+    "    # https://github.com/bokeh/bokeh/issues/2321\n",
+    "    \"\"\"\n",
+    "\n",
+    "    for i, part in enumerate(multi_geometry):\n",
+    "        # On the first part of the Multi-geometry initialize the coord_array (np.array)\n",
+    "        if i == 0:\n",
+    "            if geom_type == \"MultiPoint\":\n",
+    "                coord_arrays = np.append(getPointCoords(part, coord_type), np.nan)\n",
+    "            elif geom_type == \"MultiLineString\":\n",
+    "                coord_arrays = np.append(getLineCoords(part, coord_type), np.nan)\n",
+    "            elif geom_type == \"MultiPolygon\":\n",
+    "                coord_arrays = np.append(getPolyCoords(part, coord_type), np.nan)\n",
+    "        else:\n",
+    "            if geom_type == \"MultiPoint\":\n",
+    "                coord_arrays = np.concatenate([coord_arrays, np.append(getPointCoords(part, coord_type), np.nan)])\n",
+    "            elif geom_type == \"MultiLineString\":\n",
+    "                coord_arrays = np.concatenate([coord_arrays, np.append(getLineCoords(part, coord_type), np.nan)])\n",
+    "            elif geom_type == \"MultiPolygon\":\n",
+    "                coord_arrays = np.concatenate([coord_arrays, np.append(getPolyCoords(part, coord_type), np.nan)])\n",
+    "\n",
+    "    # Return the coordinates\n",
+    "    return coord_arrays\n",
+    "\n",
+    "def get_coords(row, coord_type):\n",
+    "    \"\"\"Returns the coordinates ('x' or 'y') of edges of a Polygon exterior\"\"\"\n",
+    "    try:\n",
+    "        # plot a single polygon\n",
+    "        return getPolyCoords(row['geometry'], coord_type)\n",
+    "    except Exception as e:\n",
+    "        # plot multiple polygons\n",
+    "        return multiGeomHandler(row['geometry'], coord_type, 'MultiPolygon')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## plot data on the shapefile\n",
+    "### references:\n",
+    "\n",
+    "https://docs.bokeh.org/en/latest/docs/gallery/texas.html"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def plot_mongo_doc(data, projection=4326, save_fig=True, show_fig=True):\n",
+    "    \n",
+    "    df = {}\n",
+    "    geographies = {}\n",
+    "    datasets = data['payload'].keys()\n",
+    "    \n",
+    "    for dataset in datasets:\n",
+    "        \n",
+    "        granularity = data['payload'][dataset]['granularity']\n",
+    "        print(f\"dataset: {dataset}, granularity: {granularity}\")\n",
+    "        instance_col_name = 'ID'\n",
+    "\n",
+    "        df[dataset] = pd.DataFrame.from_dict(data['payload'][dataset]['data'], orient='index', columns=[f\"{dataset}_value\"])\n",
+    "        df[dataset][instance_col_name] = df[dataset].index\n",
+    "\n",
+    "        geographies[dataset] = read_file(f\"{shapefile_dir}/simple1000_clipped_{granularity}.shp\").to_crs(epsg=projection)\n",
+    "        geographies[dataset] = geographies[dataset].merge(df[dataset], on=instance_col_name)\n",
+    "\n",
+    "        # reset the color palette\n",
+    "        color_mapper = LogColorMapper(palette=palette)\n",
+    "\n",
+    "        geographies[dataset]['x'] = geographies[dataset].apply(get_coords, coord_type='x', axis=1)\n",
+    "        geographies[dataset]['y'] = geographies[dataset].apply(get_coords, coord_type='y', axis=1)\n",
+    "\n",
+    "        plot_data=dict(\n",
+    "            x=geographies[dataset]['x'].tolist(),\n",
+    "            y=geographies[dataset]['y'].tolist(),\n",
+    "            name=geographies[dataset]['ID'].tolist(),\n",
+    "            value=geographies[dataset][f\"{dataset}_value\"].tolist()\n",
+    "        )\n",
+    "\n",
+    "        TOOLS = \"pan,wheel_zoom,reset,hover,save,box_zoom\"\n",
+    "\n",
+    "        coords_tuple = (\"(Lat, Lon)\", \"($y, $x)\") if projection == 4326 else (\"(x, y)\", \"($x, $y)\")\n",
+    "        fig = figure(\n",
+    "            title=f\"USA {dataset}\", tools=TOOLS,\n",
+    "            plot_width=plot_width, plot_height=plot_height,\n",
+    "            x_axis_location=None, y_axis_location=None,\n",
+    "            tooltips=[\n",
+    "                (\"Name\", \"@name\"), (\"Value\", \"@value\"), coords_tuple\n",
+    "            ])\n",
+    "        fig.grid.grid_line_color = None\n",
+    "        fig.hover.point_policy = \"follow_mouse\"\n",
+    "\n",
+    "        fig.patches('x', 'y', source=plot_data,\n",
+    "                  fill_color={'field': 'value', 'transform': color_mapper},\n",
+    "                  fill_alpha=0.7, line_color=\"white\", line_width=0.5)\n",
+    "\n",
+    "        if save_fig:\n",
+    "            output_file(f\"{dataset}.html\")\n",
+    "            save(fig)\n",
+    "        if show_fig:\n",
+    "            show(fig)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## load and plot the data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "with open(json_file) as f:\n",
+    "    data = json.load(f)\n",
+    "\n",
+    "plot_mongo_doc(data, projection=projection, show_fig=False)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
--- a/viz/plot.py
+++ b/viz/plot.py
@@ -0,0 +1,191 @@
+#!/usr/bin/env python
+# coding: utf-8
+
+# Plot data on a choropleth map
+
+# import packages
+import sys
+import numpy as np
+from geopandas import read_file
+import pandas as pd
+import json
+from bokeh.io import show
+from bokeh.models import LogColorMapper
+from bokeh.palettes import Blues256 as palette
+palette.reverse()
+from bokeh.plotting import figure, output_file, save
+
+# parameters
+json_file = sys.argv[1]  # path to the Mongo document to plot
+shapefile_dir = "../graphs/shapefiles/"  # path to the directory of shapefiles
+plot_width = 1200  # pixel width of the plot
+plot_height = 800  # pixel height of the plot
+projection = 4326  # coordinate reference system to use for plotting
+
+# geopandas functions for getting coordinates
+# references:
+# https://automating-gis-processes.github.io/2016/Lesson5-interactive-map-bokeh.html
+# https://discourse.bokeh.org/t/mapping-europe-with-bokeh-using-geopandas-and-handling-multipolygons/2571
+
+def getXYCoords(geometry, coord_type):
+    # Returns either x or y coordinates from geometry coordinate sequence. Used with LineString and Polygon geometries."""
+    if coord_type == 'x':
+        return list(geometry.coords.xy[0])
+    elif coord_type == 'y':
+        return list(geometry.coords.xy[1])
+
+
+def getPolyCoords(geometry, coord_type):
+    # Returns Coordinates of Polygon using the Exterior of the Polygon."""
+    ext = geometry.exterior
+    return getXYCoords(ext, coord_type)
+
+
+def multiGeomHandler(multi_geometry, coord_type, geom_type):
+    """
+    Function for handling multi-geometries. Can be MultiPoint, MultiLineString or MultiPolygon.
+    Returns a list of coordinates where all parts of Multi-geometries are merged into a single list.
+    Individual geometries are separated with np.nan which is how Bokeh wants them.
+    # Bokeh documentation regarding the Multi-geometry issues can be found here (it is an open issue)
+    # https://github.com/bokeh/bokeh/issues/2321
+    """
+
+    for i, part in enumerate(multi_geometry):
+        # On the first part of the Multi-geometry initialize the coord_array (np.array)
+        if i == 0:
+            if geom_type == "MultiPoint":
+                coord_arrays = np.append(
+                    getPointCoords(part, coord_type), np.nan
+                )
+            elif geom_type == "MultiLineString":
+                coord_arrays = np.append(
+                    getLineCoords(part, coord_type), np.nan
+                )
+            elif geom_type == "MultiPolygon":
+                coord_arrays = np.append(
+                    getPolyCoords(part, coord_type), np.nan
+                )
+        else:
+            if geom_type == "MultiPoint":
+                coord_arrays = np.concatenate(
+                    [
+                        coord_arrays,
+                        np.append(getPointCoords(part, coord_type), np.nan),
+                    ]
+                )
+            elif geom_type == "MultiLineString":
+                coord_arrays = np.concatenate(
+                    [
+                        coord_arrays,
+                        np.append(getLineCoords(part, coord_type), np.nan),
+                    ]
+                )
+            elif geom_type == "MultiPolygon":
+                coord_arrays = np.concatenate(
+                    [
+                        coord_arrays,
+                        np.append(getPolyCoords(part, coord_type), np.nan),
+                    ]
+                )
+
+    # Return the coordinates
+    return coord_arrays
+
+
+def get_coords(row, coord_type):
+    """Returns the coordinates ('x' or 'y') of edges of a Polygon exterior"""
+    try:
+        # plot a single polygon
+        return getPolyCoords(row['geometry'], coord_type)
+    except Exception as e:
+        # plot multiple polygons
+        return multiGeomHandler(row['geometry'], coord_type, 'MultiPolygon')
+
+
+# plot data on the shapefile
+# references:
+# https://docs.bokeh.org/en/latest/docs/gallery/texas.html
+def plot_mongo_doc(data, projection=4326, save_fig=True, show_fig=True):
+
+    df = {}
+    geographies = {}
+    datasets = data['payload'].keys()
+
+    for dataset in datasets:
+
+        granularity = data['payload'][dataset]['granularity']
+        print(f"dataset: {dataset}, granularity: {granularity}")
+        instance_col_name = 'ID'
+
+        df[dataset] = pd.DataFrame.from_dict(
+            data['payload'][dataset]['data'],
+            orient='index',
+            columns=[f"{dataset}_value"],
+        )
+        df[dataset][instance_col_name] = df[dataset].index
+
+        geographies[dataset] = read_file(
+            f"{shapefile_dir}/simple1000_clipped_{granularity}.shp"
+        ).to_crs(epsg=projection)
+        geographies[dataset] = geographies[dataset].merge(
+            df[dataset], on=instance_col_name
+        )
+
+        # reset the color palette
+        color_mapper = LogColorMapper(palette=palette)
+
+        geographies[dataset]['x'] = geographies[dataset].apply(
+            get_coords, coord_type='x', axis=1
+        )
+        geographies[dataset]['y'] = geographies[dataset].apply(
+            get_coords, coord_type='y', axis=1
+        )
+
+        plot_data = dict(
+            x=geographies[dataset]['x'].tolist(),
+            y=geographies[dataset]['y'].tolist(),
+            name=geographies[dataset]['ID'].tolist(),
+            value=geographies[dataset][f"{dataset}_value"].tolist(),
+        )
+
+        TOOLS = "pan,wheel_zoom,reset,hover,save,box_zoom"
+
+        coords_tuple = (
+            ("(Lat, Lon)", "($y, $x)")
+            if projection == 4326
+            else ("(x, y)", "($x, $y)")
+        )
+        fig = figure(
+            title=f"USA {dataset}",
+            tools=TOOLS,
+            plot_width=plot_width,
+            plot_height=plot_height,
+            x_axis_location=None,
+            y_axis_location=None,
+            tooltips=[("Name", "@name"), ("Value", "@value"), coords_tuple],
+        )
+        fig.grid.grid_line_color = None
+        fig.hover.point_policy = "follow_mouse"
+
+        fig.patches(
+            'x',
+            'y',
+            source=plot_data,
+            fill_color={'field': 'value', 'transform': color_mapper},
+            fill_alpha=0.7,
+            line_color="white",
+            line_width=0.5,
+        )
+
+        if save_fig:
+            output_file(f"{dataset}.html")
+            save(fig)
+        if show_fig:
+            show(fig)
+
+
+# load and plot the data
+with open(json_file) as f:
+    data = json.load(f)
+
+plot_mongo_doc(data, projection=projection, show_fig=False)
				`@@ -0,0 +1 @@`
				`PROJCS["NAD83_HARN_Texas_Centric_Albers_Equal_Area",GEOGCS["GCS_NAD83(HARN)",DATUM["D_North_American_1983_HARN",SPHEROID["GRS_1980",6378137,298.257222101]],PRIMEM["Greenwich",0],UNIT["Degree",0.017453292519943295]],PROJECTION["Albers"],PARAMETER["standard_parallel_1",27.5],PARAMETER["standard_parallel_2",35],PARAMETER["latitude_of_origin",18],PARAMETER["central_meridian",-100],PARAMETER["false_easting",1500000],PARAMETER["false_northing",6000000],UNIT["Meter",1]]`
				`@@ -0,0 +1 @@`
				PROJCS["NAD83(HARN) / Texas Centric Albers Equal Area",GEOGCS["NAD83(HARN)",DATUM["NAD83_High_Accuracy_Reference_Network",SPHEROID["GRS 1980",6378137,298.257222101,AUTHORITY["EPSG","7019"]],TOWGS84[0,0,0,0,0,0,0],AUTHORITY["EPSG","6152"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4152"]],PROJECTION["Albers_Conic_Equal_Area"],PARAMETER["standard_parallel_1",27.5],PARAMETER["standard_parallel_2",35],PARAMETER["latitude_of_center",18],PARAMETER["longitude_of_center",-100],PARAMETER["false_easting",1500000],PARAMETER["false_northing",6000000],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["X",EAST],AXIS["Y",NORTH],AUTHORITY["EPSG","3085"]]