From 059e39bf43be4f936954c6c2ac298e3be4d67baa Mon Sep 17 00:00:00 2001 From: akacarlyann Date: Wed, 28 Mar 2018 21:35:24 -0700 Subject: [PATCH] Add choropleth support (#40) * Add basic chloropleth support * Center zoom on click coordinates; rename polygons layer to 'cholorpleth-fill' per PR review comments * Add line_color, line_stroke, and line_width properties to ChloroplethViz; update url transformRequest function in map init to match implementation in master * Add chloropleth label layer; add template block for styling legend keys * Add line styling to example chloropleth notebook * Update internal documentation in ChloroplethViz class; add chloropleth documentation to docs-markdown/viz.md template * Update spelling to mapbox standard: 'choropleth' * Add tests for ChoroplethViz (currently uses polygons.geojson) * Formatting and headers on choropleth notebook * Add vector layer support options; requesting direction for reconciling color assignment with data join and Mapboxgl-jupyter color_stops paradigm * Single ChoroplethViz class defines either vector-based or geojson-based viz templates depending on variables in init * Add support for categorical data-driven styling with vector data-join; include helper function for interpolating (mapping) colors when using vector-join technique; update docs and example notebook for vector data support in ChoroplethViz * Attempt to add test for utils.rgb_tuple_from_str * Additional test coverage for ChoroplethViz and color_map, rgb_tuple_from_str utils * Per @ryanbaumann 's comments: revert color data-join style to the old Mapboxgl property functions (faster) and add layer-filter * Test fix * Minor refactor to color_map to prioritize returning exact match color from color_stops --- docs-markdown/utils.md | 47 +++ docs-markdown/viz.md | 57 +++- examples/choropleth-viz-example.ipynb | 191 ++++++++++++ examples/us-states.geojson | 1 + mapboxgl/colors.py | 18 ++ mapboxgl/templates/choropleth.html | 142 +++++++++ mapboxgl/templates/main.html | 1 + mapboxgl/templates/vector_choropleth.html | 110 +++++++ mapboxgl/utils.py | 106 ++++++- mapboxgl/viz.py | 121 +++++++- setup.py | 2 +- tests/polygons.geojson | 360 ++++++++++++++++++++++ tests/test_html.py | 88 +++++- tests/test_utils.py | 61 +++- 14 files changed, 1284 insertions(+), 21 deletions(-) create mode 100644 examples/choropleth-viz-example.ipynb create mode 100644 examples/us-states.geojson create mode 100644 mapboxgl/templates/choropleth.html create mode 100644 mapboxgl/templates/vector_choropleth.html create mode 100644 tests/polygons.geojson diff --git a/docs-markdown/utils.md b/docs-markdown/utils.md index 8540734..8b73d62 100644 --- a/docs-markdown/utils.md +++ b/docs-markdown/utils.md @@ -134,3 +134,50 @@ df = pd.read_csv(data_url) color_breaks = [0,10,100,1000,10000] color_stops = create_color_stops(color_breaks, colors='YlOrRd') ``` + +## rgb_tuple_from_str +Convert color represented as a string in format 'rgb(RRR,GGG,BBB)', 'rgba(RRR,GGG,BBB,alpha)', '#RRGGBB' or limited English color name (eg 'red') to tuple of integers from 0 to 255, (RRR, GGG, BBB). + +### Params +**rgb_tuple_from_str**(_rgb_string_) + +Parameter | Description +--|-- +rgb_string | color represented as string in form 'rgb(RRR,GGG,BBB)', 'rgba(RRR,GGG,BBB,alpha)', '#RRGGBB', or limited HTML color names (eg 'red') + +### Usage +```python +from mapboxgl.utils import rgb_tuple_from_str + +# convert color string to tuple of integers +rgb_tuple_from_str('rgb(255,143,17') +``` + +## color_map +Convert color represented as a string in format 'rgb(RRR,GGG,BBB)' to tuple of integers from 0 to 255, (RRR, GGG, BBB). + +### Params +**color_map**(_lookup, color_stops, default_color='rgb(122,122,122)'_) + +Parameter | Description +--|-- +lookup | value is numeric for interpolated colors or string for categorical color stops +color_stops | color ramp stops generated from `create_color_stops`, or custom list of numeric or categorical stops with paired colors +default_color | representation of color as hex, RGB, or RGBA strings + +### Usage +```python +from mapboxgl.utils import create_color_stops, color_map + +# interpolate color for numeric color_stops +color_stops = create_color_stops([0, 50, 100, 500, 1500], colors='YlOrRd') +color = color_map(73, color_stops) + +# categorical look up +match_color_stops = [ + ['Massachusetts', 'rgb(46,204,113)'], + ['Utah', 'rgb(231,76,60)'], + ['California', 'rgb(142,68,173)'], +] +color = color_map('California', match_color_stops, default_color='grey)') +``` diff --git a/docs-markdown/viz.md b/docs-markdown/viz.md index d540025..388d9da 100644 --- a/docs-markdown/viz.md +++ b/docs-markdown/viz.md @@ -315,6 +315,61 @@ viz.show() ![HeatmapViz](https://user-images.githubusercontent.com/11286381/36511775-cfc4d794-171c-11e8-86b9-5f1a6060a387.png) +## class ChoroplethViz + +The `ChoroplethViz` object handles the creation of a choropleth map and inherits from the `MapViz` class. It applies a thematic map style to polygon features with color shading in proportion to the intensity of the data being displayed. Choropleth polygons can be initialized with geojson source or vector source styled using the data-join technique. + +### Params +**ChoroplethViz**(_data, vector_url=None, vector_layer_name=None, vector_join_property=None, data_join_property=None, # vector only label_property=None, color_property=None, color_stops=None, color_default='grey', color_function_type='interpolate', line_color='white', line_stroke='solid', line_width=1, *args, **kwargs_) + +Parameter | Description | Example +--|--|-- +data | can be either GeoJSON (containing polygon features) or JSON for data-join technique with vector polygons | +vector_url | optional property to define vector polygon source | "mapbox://mapbox.us_census_states_2015" +vector_layer_name | property to define target layer of vector source if using vector polygon source | "states" +vector_join_property | property to aid in determining color for styling vector polygons | "STATEFP" +data_join_property | property of json data to use as link to vector features | "state_name" +label_property | property to use for marker label | "density" +color_property | property to determine fill color | "density" +color_stops | property to determine fill color | [[0, "red"], [0.5, "blue"], [1, "green"]] +color_default | property to determine default fill color in match lookups | "#F0F0F0" +color_function_type | property to determine type of expression used by Mapbox to assign color | "interpolate" +line_color | property to determine choropleth border line color | "#FFFFFF" +line_stroke | property to determine choropleth border line stroke (one of solid (-), dashed (--), dotted (:), dash dot (-.)) | "solid" or "-" +line_width | property to determine choropleth border line width | 1 + +[View options](https://github.com/mapbox/mapboxgl-jupyter/blob/master/docs-markdown/viz.md#params) + +### Usage +```python +import os +from mapboxgl.viz import * +from mapboxgl.utils import * + +# Must be a public token, starting with `pk` +token = os.getenv('MAPBOX_ACCESS_TOKEN') + +# Create Choropleth with GeoJSON Source +viz = ChoroplethViz('us-states.geojson', + color_property='density', + color_stops=create_color_stops([0, 50, 100, 500, 1500], colors='YlOrRd'), + color_function_type='interpolate', + line_stroke='--', + line_color='rgb(128,0,38)', + line_width=1, + opacity=0.8, + center=(-96, 37.8), + zoom=3, + below_layer='waterway-label' + ) +viz.show() +``` +![ChoroplethViz](https://user-images.githubusercontent.com/13527707/37823022-73782a0a-2e45-11e8-9fdd-4a8ddd35cb92.png) + + +[Complete example](https://github.com/mapbox/mapboxgl-jupyter/blob/master/examples/choropleth-viz-example.ipynb) + + ## class ImageViz The `ImageViz` object handles the creation of a simple image visualization on map and is built on top of the `MapViz` class. @@ -397,4 +452,4 @@ viz.show() ![RasterTilesViz](https://user-images.githubusercontent.com/10407788/37537676-b055a108-2924-11e8-94cb-ad3203b736af.jpg) -[Complete example](https://github.com/mapbox/mapboxgl-jupyter/blob/master/examples/rastertile-viz-types-example.ipynb) +[Complete example](https://github.com/mapbox/mapboxgl-jupyter/blob/master/examples/rastertile-viz-types-example.ipynb) \ No newline at end of file diff --git a/examples/choropleth-viz-example.ipynb b/examples/choropleth-viz-example.ipynb new file mode 100644 index 0000000..898c8fb --- /dev/null +++ b/examples/choropleth-viz-example.ipynb @@ -0,0 +1,191 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Mapboxgl Python Library\n", + "\n", + "https://github.com/mapbox/mapboxgl-jupyter" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "from mapboxgl.viz import *\n", + "from mapboxgl.utils import *\n", + "\n", + "# Must be a public token, starting with `pk`\n", + "token = os.getenv('MAPBOX_ACCESS_TOKEN')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Choropleths with interpolated color assignment from GeoJSON source" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "# create choropleth from polygon features stored as GeoJSON\n", + "viz = ChoroplethViz('us-states.geojson', \n", + " color_property='density',\n", + " color_stops=create_color_stops([0, 50, 100, 500, 1500], colors='YlOrRd'),\n", + " color_function_type='interpolate',\n", + " line_stroke='--',\n", + " line_color='rgb(128,0,38)',\n", + " line_width=1,\n", + " opacity=0.8,\n", + " center=(-96, 37.8),\n", + " zoom=3,\n", + " below_layer='waterway-label'\n", + " )\n", + "viz.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Choropleths with match-type color scheme from GeoJSON source" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "match_color_stops = [\n", + " ['Massachusetts', 'rgb(46,204,113)'],\n", + " ['Utah', 'rgb(231,76,60)'],\n", + " ['California', 'rgb(142,68,173)'],\n", + "]\n", + "\n", + "viz = ChoroplethViz('us-states.geojson', \n", + " color_property='name', \n", + " color_stops = match_color_stops, \n", + " color_function_type = 'match', \n", + " color_default = 'rgba(52,73,94,0.5)', \n", + " opacity=0.8, \n", + " center = (-96, 37.8), \n", + " zoom = 3, \n", + " below_layer = 'waterway-label'\n", + " )\n", + "viz.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Vector polygon source with data-join technique\n", + "\n", + "In this configuration, properties in JSON data are used to calculate colors to style polygons from the vector source." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# must be JSON object (need to extend to use referenced JSON file)\n", + "data = [{\"id\": \"01\", \"name\": \"Alabama\", \"density\": 94.65}, {\"id\": \"02\", \"name\": \"Alaska\", \"density\": 1.264}, {\"id\": \"04\", \"name\": \"Arizona\", \"density\": 57.05}, {\"id\": \"05\", \"name\": \"Arkansas\", \"density\": 56.43}, {\"id\": \"06\", \"name\": \"California\", \"density\": 241.7}, {\"id\": \"08\", \"name\": \"Colorado\", \"density\": 49.33}, {\"id\": \"09\", \"name\": \"Connecticut\", \"density\": 739.1}, {\"id\": \"10\", \"name\": \"Delaware\", \"density\": 464.3}, {\"id\": \"11\", \"name\": \"District of Columbia\", \"density\": 10065}, {\"id\": \"12\", \"name\": \"Florida\", \"density\": 353.4}, {\"id\": \"13\", \"name\": \"Georgia\", \"density\": 169.5}, {\"id\": \"15\", \"name\": \"Hawaii\", \"density\": 214.1}, {\"id\": \"16\", \"name\": \"Idaho\", \"density\": 19.15}, {\"id\": \"17\", \"name\": \"Illinois\", \"density\": 231.5}, {\"id\": \"18\", \"name\": \"Indiana\", \"density\": 181.7}, {\"id\": \"19\", \"name\": \"Iowa\", \"density\": 54.81}, {\"id\": \"20\", \"name\": \"Kansas\", \"density\": 35.09}, {\"id\": \"21\", \"name\": \"Kentucky\", \"density\": 110}, {\"id\": \"22\", \"name\": \"Louisiana\", \"density\": 105}, {\"id\": \"23\", \"name\": \"Maine\", \"density\": 43.04}, {\"id\": \"24\", \"name\": \"Maryland\", \"density\": 596.3}, {\"id\": \"25\", \"name\": \"Massachusetts\", \"density\": 840.2}, {\"id\": \"26\", \"name\": \"Michigan\", \"density\": 173.9}, {\"id\": \"27\", \"name\": \"Minnesota\", \"density\": 67.14}, {\"id\": \"28\", \"name\": \"Mississippi\", \"density\": 63.5}, {\"id\": \"29\", \"name\": \"Missouri\", \"density\": 87.26}, {\"id\": \"30\", \"name\": \"Montana\", \"density\": 6.858}, {\"id\": \"31\", \"name\": \"Nebraska\", \"density\": 23.97}, {\"id\": \"32\", \"name\": \"Nevada\", \"density\": 24.8}, {\"id\": \"33\", \"name\": \"New Hampshire\", \"density\": 147}, {\"id\": \"34\", \"name\": \"New Jersey\", \"density\": 1189}, {\"id\": \"35\", \"name\": \"New Mexico\", \"density\": 17.16}, {\"id\": \"36\", \"name\": \"New York\", \"density\": 412.3}, {\"id\": \"37\", \"name\": \"North Carolina\", \"density\": 198.2}, {\"id\": \"38\", \"name\": \"North Dakota\", \"density\": 9.916}, {\"id\": \"39\", \"name\": \"Ohio\", \"density\": 281.9}, {\"id\": \"40\", \"name\": \"Oklahoma\", \"density\": 55.22}, {\"id\": \"41\", \"name\": \"Oregon\", \"density\": 40.33}, {\"id\": \"42\", \"name\": \"Pennsylvania\", \"density\": 284.3}, {\"id\": \"44\", \"name\": \"Rhode Island\", \"density\": 1006}, {\"id\": \"45\", \"name\": \"South Carolina\", \"density\": 155.4}, {\"id\": \"46\", \"name\": \"South Dakota\", \"density\": 98.07}, {\"id\": \"47\", \"name\": \"Tennessee\", \"density\": 88.08}, {\"id\": \"48\", \"name\": \"Texas\", \"density\": 98.07}, {\"id\": \"49\", \"name\": \"Utah\", \"density\": 34.3}, {\"id\": \"50\", \"name\": \"Vermont\", \"density\": 67.73}, {\"id\": \"51\", \"name\": \"Virginia\", \"density\": 204.5}, {\"id\": \"53\", \"name\": \"Washington\", \"density\": 102.6}, {\"id\": \"54\", \"name\": \"West Virginia\", \"density\": 77.06}, {\"id\": \"55\", \"name\": \"Wisconsin\", \"density\": 105.2}, {\"id\": \"56\", \"name\": \"Wyoming\", \"density\": 5.851}, {\"id\": \"72\", \"name\": \"Puerto Rico\", \"density\": 1082}]\n", + "\n", + "# create choropleth map with vector source styling use data in JSON object\n", + "viz = ChoroplethViz(data, \n", + " vector_url='mapbox://mapbox.us_census_states_2015',\n", + " vector_layer_name='states',\n", + " vector_join_property='STATEFP',\n", + " data_join_property='id',\n", + " color_property='density',\n", + " color_stops=create_color_stops([0, 50, 100, 500, 1500], colors='YlOrRd'),\n", + " line_stroke='dashed',\n", + " line_color='rgb(128,0,38)',\n", + " opacity=0.8,\n", + " center=(-96, 37.8),\n", + " zoom=3,\n", + " below_layer='waterway-label'\n", + " )\n", + "viz.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Vector polygon source with data-join technique, categorical color scheme" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# must be JSON object (need to extend to use referenced JSON file)\n", + "data = [{\"id\": \"01\", \"name\": \"Alabama\", \"density\": 94.65}, {\"id\": \"02\", \"name\": \"Alaska\", \"density\": 1.264}, {\"id\": \"04\", \"name\": \"Arizona\", \"density\": 57.05}, {\"id\": \"05\", \"name\": \"Arkansas\", \"density\": 56.43}, {\"id\": \"06\", \"name\": \"California\", \"density\": 241.7}, {\"id\": \"08\", \"name\": \"Colorado\", \"density\": 49.33}, {\"id\": \"09\", \"name\": \"Connecticut\", \"density\": 739.1}, {\"id\": \"10\", \"name\": \"Delaware\", \"density\": 464.3}, {\"id\": \"11\", \"name\": \"District of Columbia\", \"density\": 10065}, {\"id\": \"12\", \"name\": \"Florida\", \"density\": 353.4}, {\"id\": \"13\", \"name\": \"Georgia\", \"density\": 169.5}, {\"id\": \"15\", \"name\": \"Hawaii\", \"density\": 214.1}, {\"id\": \"16\", \"name\": \"Idaho\", \"density\": 19.15}, {\"id\": \"17\", \"name\": \"Illinois\", \"density\": 231.5}, {\"id\": \"18\", \"name\": \"Indiana\", \"density\": 181.7}, {\"id\": \"19\", \"name\": \"Iowa\", \"density\": 54.81}, {\"id\": \"20\", \"name\": \"Kansas\", \"density\": 35.09}, {\"id\": \"21\", \"name\": \"Kentucky\", \"density\": 110}, {\"id\": \"22\", \"name\": \"Louisiana\", \"density\": 105}, {\"id\": \"23\", \"name\": \"Maine\", \"density\": 43.04}, {\"id\": \"24\", \"name\": \"Maryland\", \"density\": 596.3}, {\"id\": \"25\", \"name\": \"Massachusetts\", \"density\": 840.2}, {\"id\": \"26\", \"name\": \"Michigan\", \"density\": 173.9}, {\"id\": \"27\", \"name\": \"Minnesota\", \"density\": 67.14}, {\"id\": \"28\", \"name\": \"Mississippi\", \"density\": 63.5}, {\"id\": \"29\", \"name\": \"Missouri\", \"density\": 87.26}, {\"id\": \"30\", \"name\": \"Montana\", \"density\": 6.858}, {\"id\": \"31\", \"name\": \"Nebraska\", \"density\": 23.97}, {\"id\": \"32\", \"name\": \"Nevada\", \"density\": 24.8}, {\"id\": \"33\", \"name\": \"New Hampshire\", \"density\": 147}, {\"id\": \"34\", \"name\": \"New Jersey\", \"density\": 1189}, {\"id\": \"35\", \"name\": \"New Mexico\", \"density\": 17.16}, {\"id\": \"36\", \"name\": \"New York\", \"density\": 412.3}, {\"id\": \"37\", \"name\": \"North Carolina\", \"density\": 198.2}, {\"id\": \"38\", \"name\": \"North Dakota\", \"density\": 9.916}, {\"id\": \"39\", \"name\": \"Ohio\", \"density\": 281.9}, {\"id\": \"40\", \"name\": \"Oklahoma\", \"density\": 55.22}, {\"id\": \"41\", \"name\": \"Oregon\", \"density\": 40.33}, {\"id\": \"42\", \"name\": \"Pennsylvania\", \"density\": 284.3}, {\"id\": \"44\", \"name\": \"Rhode Island\", \"density\": 1006}, {\"id\": \"45\", \"name\": \"South Carolina\", \"density\": 155.4}, {\"id\": \"46\", \"name\": \"South Dakota\", \"density\": 98.07}, {\"id\": \"47\", \"name\": \"Tennessee\", \"density\": 88.08}, {\"id\": \"48\", \"name\": \"Texas\", \"density\": 98.07}, {\"id\": \"49\", \"name\": \"Utah\", \"density\": 34.3}, {\"id\": \"50\", \"name\": \"Vermont\", \"density\": 67.73}, {\"id\": \"51\", \"name\": \"Virginia\", \"density\": 204.5}, {\"id\": \"53\", \"name\": \"Washington\", \"density\": 102.6}, {\"id\": \"54\", \"name\": \"West Virginia\", \"density\": 77.06}, {\"id\": \"55\", \"name\": \"Wisconsin\", \"density\": 105.2}, {\"id\": \"56\", \"name\": \"Wyoming\", \"density\": 5.851}, {\"id\": \"72\", \"name\": \"Puerto Rico\", \"density\": 1082}]\n", + "\n", + "match_color_stops = [\n", + " ['Massachusetts', 'rgb(46,204,113)'],\n", + " ['Utah', 'rgb(231,76,60)'],\n", + " ['California', 'rgb(142,68,173)'],\n", + "]\n", + "\n", + "# create choropleth map with vector source styling use data in JSON object\n", + "viz = ChoroplethViz(data, \n", + " vector_url='mapbox://mapbox.us_census_states_2015',\n", + " vector_layer_name='states',\n", + " vector_join_property='STATEFP',\n", + " data_join_property='id',\n", + " color_property='name',\n", + " color_stops=match_color_stops,\n", + " color_default = 'rgba(52,73,94,0.5)', \n", + " opacity=0.8,\n", + " center=(-96, 37.8),\n", + " zoom=3,\n", + " below_layer='waterway-label'\n", + " )\n", + "viz.show()" + ] + } + ], + "metadata": { + "anaconda-cloud": { + "attach-environment": true, + "environment": "Root", + "summary": "Mapboxgl Python Data Visualization example" + }, + "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": "3.6.1" + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} diff --git a/examples/us-states.geojson b/examples/us-states.geojson new file mode 100644 index 0000000..cfac5c9 --- /dev/null +++ b/examples/us-states.geojson @@ -0,0 +1 @@ +{"type": "FeatureCollection", "features": [{"type": "Feature", "id": "01", "properties": {"name": "Alabama", "density": 94.65}, "geometry": {"type": "Polygon", "coordinates": [[[-87.359296, 35.00118], [-85.606675, 34.984749], [-85.431413, 34.124869], [-85.184951, 32.859696], [-85.069935, 32.580372], [-84.960397, 32.421541], [-85.004212, 32.322956], [-84.889196, 32.262709], [-85.058981, 32.13674], [-85.053504, 32.01077], [-85.141136, 31.840985], [-85.042551, 31.539753], [-85.113751, 31.27686], [-85.004212, 31.003013], [-85.497137, 30.997536], [-87.600282, 30.997536], [-87.633143, 30.86609], [-87.408589, 30.674397], [-87.446927, 30.510088], [-87.37025, 30.427934], [-87.518128, 30.280057], [-87.655051, 30.247195], [-87.90699, 30.411504], [-87.934375, 30.657966], [-88.011052, 30.685351], [-88.10416, 30.499135], [-88.137022, 30.318396], [-88.394438, 30.367688], [-88.471115, 31.895754], [-88.241084, 33.796253], [-88.098683, 34.891641], [-88.202745, 34.995703], [-87.359296, 35.00118]]]}}, {"type": "Feature", "id": "02", "properties": {"name": "Alaska", "density": 1.264}, "geometry": 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18.006234], [-66.924832, 17.929556], [-66.985078, 17.973372], [-67.209633, 17.956941], [-67.154863, 18.19245], [-67.269879, 18.362235], [-67.094617, 18.515589], [-66.957694, 18.488204], [-66.409999, 18.488204], [-65.840398, 18.433435], [-65.632274, 18.367712], [-65.626797, 18.203403], [-65.730859, 18.186973], [-65.834921, 18.017187], [-66.234737, 17.929556], [-66.448338, 17.984326]]]}}]} \ No newline at end of file diff --git a/mapboxgl/colors.py b/mapboxgl/colors.py index ac64e39..3f2ab61 100644 --- a/mapboxgl/colors.py +++ b/mapboxgl/colors.py @@ -337,3 +337,21 @@ 12: ['rgb(141,211,199)', 'rgb(255,255,179)', 'rgb(190,186,218)', 'rgb(251,128,114)', 'rgb(128,177,211)', 'rgb(253,180,98)', 'rgb(179,222,105)', 'rgb(252,205,229)', 'rgb(217,217,217)', 'rgb(188,128,189)', 'rgb(204,235,197)', 'rgb(255,237,111)'] } ) + +# a few HTML / X11 color names +common_html_colors = { + 'red': 'rgb(255,0,0)', + 'orange': 'rgb(255,165,0)', + 'yellow': 'rgb(255,255,0)', + 'green': 'rgb(0,128,0)', + 'blue': 'rgb(0,0,255)', + 'purple': 'rgb(128,0,128)', + 'pink': 'rgb(255,192,203)', + 'white': 'rgb(255,255,255)', + 'grey': 'rgb(128,128,128)', + 'gray': 'rgb(128,128,128)', + 'black': 'rgb(0,0,0)', + 'brown': 'rgb(139,69,19)', + 'magenta': 'rgb(255,0,255)', + 'cyan': 'rgb(0,255,255)', +} diff --git a/mapboxgl/templates/choropleth.html b/mapboxgl/templates/choropleth.html new file mode 100644 index 0000000..eca17ae --- /dev/null +++ b/mapboxgl/templates/choropleth.html @@ -0,0 +1,142 @@ +{% extends "main.html" %} + + +{% block extra_css %} + +{% endblock extra_css %} + +{% block javascript %} +var legend = document.getElementById('legend'); + +mapboxgl.accessToken = '{{ accessToken }}'; + +var map = new mapboxgl.Map({ + container: 'map', + style: {{ style }}, + center: {{ center }}, + zoom: {{ zoom }}, + transformRequest: (url, resourceType)=> { + if ( url.slice(0,22) == 'https://api.mapbox.com' ) { + //Add Python Plugin identifier for Mapbox API traffic + return { + url: [url.slice(0, url.indexOf("?")+1), "pluginName=PythonMapboxgl&", url.slice(url.indexOf("?")+1)].join('') + } + } + else { + //Do not transform URL for non Mapbox GET requests + return {url: url} + } + } +}); + +map.addControl(new mapboxgl.NavigationControl()); + +calcCircleColorLegend({{ colorStops }}, "{{ colorProperty }}"); + +map.on('style.load', function() { + + {% block choropleth %} + + // Add geojson data source + map.addSource("data", { + "type": "geojson", + "data": {{ geojson_data }}, + "buffer": 1, + "maxzoom": 14 + }); + + // Add data layer + map.addLayer({ + "id": "choropleth-fill", + "source": "data", + "type": "fill", + "paint": { + "fill-color": generatePropertyExpression("{{ colorType }}", "{{ colorProperty }}", {{ colorStops }}, "{{ defaultColor }}"), + "fill-opacity": {{ opacity }} + } + }, "{{ belowLayer }}" ); + + // Add border layer + map.addLayer({ + "id": "choropleth-line", + "source": "data", + "type": "line", + "layout": { + "line-join": "round", + "line-cap": "round" + }, + "paint": { + {% if lineDashArray %} + "line-dasharray": {{ lineDashArray }}, + {% endif %} + "line-color": "{{ lineColor }}", + "line-width": {{ lineWidth }}, + "line-opacity": {{ opacity }} + } + }, "{{ belowLayer }}" ); + + // Add label layer + map.addLayer({ + "id": "choropleth-label", + "source": "data", + "type": "symbol", + "layout": { + {% if labelProperty %} + "text-field": "{{ labelProperty }}", + {% endif %} + "text-size" : generateInterpolateExpression('zoom', [[0,8],[22,16]] ), + "text-offset": [0,-1] + }, + "paint": { + "text-halo-color": "white", + "text-halo-width": 1 + } + }, "{{belowLayer}}" ); + + {% endblock choropleth %} + + // Create a popup + var popup = new mapboxgl.Popup({ + closeButton: false, + closeOnClick: false + }); + + {% block choropleth_popup %} + + // Show the popup on mouseover + map.on('mousemove', 'choropleth-fill', function(e) { + map.getCanvas().style.cursor = 'pointer'; + + let f = e.features[0]; + let popup_html = '
'; + + for (key in f.properties) { + popup_html += '
  • ' + key + ': ' + f.properties[key] + '
    • ' + } + + popup_html += '
    ' + popup.setLngLat(e.lngLat) + .setHTML(popup_html) + .addTo(map); + }); + + {% endblock choropleth_popup %} + + map.on('mouseleave', 'choropleth-fill', function() { + map.getCanvas().style.cursor = ''; + popup.remove(); + }); + + // Fly to on click + map.on('click', 'choropleth-fill', function(e) { + map.flyTo({ + center: e.lngLat, + zoom: map.getZoom() + 1 + }); + }); + +}); + +{% endblock %} diff --git a/mapboxgl/templates/main.html b/mapboxgl/templates/main.html index 72e6d34..29e1c4c 100644 --- a/mapboxgl/templates/main.html +++ b/mapboxgl/templates/main.html @@ -41,6 +41,7 @@ width: 10px; } +{% block extra_css %}{% endblock extra_css %} diff --git a/mapboxgl/templates/vector_choropleth.html b/mapboxgl/templates/vector_choropleth.html new file mode 100644 index 0000000..3bb0ee4 --- /dev/null +++ b/mapboxgl/templates/vector_choropleth.html @@ -0,0 +1,110 @@ +{% extends "choropleth.html" %} + +{% block choropleth %} + + // extract JSON property used for data-driven styling to add to popup + {% if joinData %} + + let joinData = {{ joinData }}; + var popUpKeys = {}; + + // Create filter for layers from join data + let layerFilter = ['in', "{{ vectorJoinColorProperty }}"] + + joinData.forEach(function(row, index) { + popUpKeys[row["{{ dataJoinProperty }}"]] = row["{{ colorProperty }}"]; + layerFilter.push(row["{{ dataJoinProperty }}"]); + }); + + {% endif %} + + // Add vector data source + map.addSource("vector-data", { + type: "vector", + url: "{{ vectorUrl }}", + }); + + // Add layer from the vector tile source with data-driven style + map.addLayer({ + "id": "choropleth-fill", + "type": "fill", + "source": "vector-data", + "source-layer": "{{ vectorLayer }}", + "paint": { + "fill-color": { + "type": "categorical", + "property": "{{ vectorJoinColorProperty }}", + "stops": {{ vectorColorStops }}, + "default": "{{ defaultColor }}" + }, + "fill-opacity": {{ opacity }} + }, + filter: layerFilter + }, "{{ belowLayer }}"); + + // Add border layer + map.addLayer({ + "id": "choropleth-line", + "source": "vector-data", + "source-layer": "{{ vectorLayer }}", + "type": "line", + "layout": { + "line-join": "round", + "line-cap": "round" + }, + "paint": { + {% if lineDashArray %} + "line-dasharray": {{ lineDashArray }}, + {% endif %} + "line-color": "{{ lineColor }}", + "line-width": {{ lineWidth }}, + "line-opacity": {{ opacity }} + }, + filter: layerFilter + }, "{{ belowLayer }}" ); + + // Add label layer + map.addLayer({ + "id": "choropleth-label", + "source": "vector-data", + "source-layer": "{{ vectorLayer }}", + "type": "symbol", + "layout": { + {% if labelProperty %} + "text-field": "{{ labelProperty }}", + {% endif %} + "text-size" : generateInterpolateExpression('zoom', [[0,8],[22,16]] ), + "text-offset": [0,-1] + }, + "paint": { + "text-halo-color": "white", + "text-halo-width": 1 + }, + filter: layerFilter + }, "{{belowLayer}}" ); + +{% endblock choropleth %} + +{% block choropleth_popup %} + + // Show the popup on mouseover + map.on('mousemove', 'choropleth-fill', function(e) { + map.getCanvas().style.cursor = 'pointer'; + + let f = e.features[0]; + let popup_html = '
    '; + + for (key in f.properties) { + popup_html += '
  • ' + key + ': ' + f.properties[key] + '
    • ' + } + + // Add property from joined data to vector's feature popup + popup_html += '
  • ' + "{{ colorProperty }}".toUpperCase() + ': ' + popUpKeys[f.properties["{{ vectorJoinColorProperty }}"]] + '
    • ' + + popup_html += '
    ' + popup.setLngLat(e.lngLat) + .setHTML(popup_html) + .addTo(map); + }); + +{% endblock choropleth_popup %} diff --git a/mapboxgl/utils.py b/mapboxgl/utils.py index 05627dd..0951b25 100644 --- a/mapboxgl/utils.py +++ b/mapboxgl/utils.py @@ -1,14 +1,12 @@ +from .colors import color_ramps, common_html_colors +from chroma import Color, Scale +import geojson import json import base64 from io import BytesIO - -from matplotlib.image import imsave - -from .colors import color_ramps -import geojson -import json import re -from colour import Color +from matplotlib.image import imsave +from colour import Color as Colour def row_to_geojson(row, lon, lat): @@ -130,7 +128,7 @@ def create_color_stops(breaks, colors='RdYlGn', color_ramps=color_ramps): for color in colors: # Check if color is valid string try: - Color(color) + Colour(color) except: raise ValueError( 'The color code {color} is in the wrong format'.format(color=color)) @@ -155,9 +153,99 @@ def create_color_stops(breaks, colors='RdYlGn', color_ramps=color_ramps): return stops +def rgb_tuple_from_str(color_string): + """Convert color in format 'rgb(RRR,GGG,BBB)', 'rgba(RRR,GGG,BBB,alpha)', + '#RRGGBB', or limited English color name (eg 'red') to tuple (RRR, GGG, BBB) + """ + try: + # English color names (limited) + rgb_string = common_html_colors[color_string] + return tuple([float(x) for x in re.findall(r'\d{1,3}', rgb_string)]) + + except KeyError: + try: + # HEX color code + hex_string = color_string.lstrip('#') + return tuple(int(hex_string[i:i+2], 16) for i in (0, 2 ,4)) + + except ValueError: + # RGB or RGBA formatted strings + return tuple([int(x) if float(x) > 1 else float(x) + for x in re.findall(r"[-+]?\d*\.*\d+", color_string)]) + + +def color_map(lookup, color_stops, default_color='rgb(122,122,122)'): + """Return an rgb color value interpolated from given color_stops; + assumes colors in color_stops provided as strings of form 'rgb(RRR,GGG,BBB)' + or in hex: '#RRGGBB' + """ + # if no color_stops, use default color + if len(color_stops) == 0: + return default_color + + # dictionary to lookup color from match-type color_stops + match_map = dict((x, y) for (x, y) in color_stops) + + # if lookup matches stop exactly, return corresponding color (first priority) + # (includes non-numeric color_stop "keys" for finding color by match) + if lookup in match_map.keys(): + return match_map.get(lookup) + + # if lookup value numeric, map color by interpolating from color scale + if isinstance(lookup, (int, float, complex)): + + # try ordering stops + try: + stops, colors = zip(*sorted(color_stops)) + + # if not all stops are numeric, attempt looking up as if categorical stops + except TypeError: + return match_map.get(lookup, default_color) + + # for interpolation, all stops must be numeric + if not all(isinstance(x, (int, float, complex)) for x in stops): + return default_color + + # check if lookup value in stops bounds + if float(lookup) <= stops[0]: + return colors[0] + + elif float(lookup) >= stops[-1]: + return colors[-1] + + # check if lookup value matches any stop value + elif float(lookup) in stops: + return colors[stops.index(lookup)] + + # interpolation required + else: + + rgb_tuples = [Color(rgb_tuple_from_str(x)) for x in colors] + + # identify bounding color stop values + lower = max([stops[0]] + [x for x in stops if x < lookup]) + upper = min([stops[-1]] + [x for x in stops if x > lookup]) + + # colors from bounding stops + lower_color = rgb_tuples[stops.index(lower)] + upper_color = rgb_tuples[stops.index(upper)] + + # generate color scale for mapping lookup value to interpolated color + scale = Scale(Color(lower_color), Color(upper_color)) + + # compute linear "relative distance" from lower bound color to upper bound color + distance = (lookup - lower) / (upper - lower) + + # return string representing rgb color value + return scale(distance).to_string().replace(', ', ',') + + # default color value catch-all + return default_color + + def img_encode(arr, **kwargs): """Encode ndarray to base64 string image data - + Parameters ---------- arr: ndarray (rows, cols, depth) diff --git a/mapboxgl/viz.py b/mapboxgl/viz.py index f898dce..6056052 100644 --- a/mapboxgl/viz.py +++ b/mapboxgl/viz.py @@ -6,6 +6,7 @@ import numpy from mapboxgl.errors import TokenError +from mapboxgl.utils import color_map from mapboxgl import templates from mapboxgl.utils import img_encode @@ -367,6 +368,124 @@ def add_unique_template_variables(self, options): )) +class ChoroplethViz(MapViz): + """Create a choropleth viz""" + + def __init__(self, + data, + vector_url=None, + vector_layer_name=None, + vector_join_property=None, + data_join_property=None, # vector only + label_property=None, + color_property=None, + color_stops=None, + color_default='grey', + color_function_type='interpolate', + line_color='white', + line_stroke='solid', + line_width=1, + *args, + **kwargs): + """Construct a Mapviz object + + :param data: can be either GeoJSON (containing polygon features) or JSON for data-join technique with vector polygons + :param vector_url: optional property to define vector polygon source + :param vector_layer_name: property to define target layer of vector source + :param vector_join_property: property to aid in determining color for styling vector polygons + :param data_join_property: property to join json data to vector features + :param label_property: property to use for marker label + :param color_property: property to determine circle color + :param color_stops: property to determine circle color + :param color_default: property to determine default circle color if match lookup fails + :param color_function_type: property to determine `type` used by Mapbox to assign color + :param line_color: property to determine choropleth line color + :param line_stroke: property to determine choropleth line stroke (solid, dashed, dotted, dash dot) + :param line_width: property to determine choropleth line width + + """ + super(ChoroplethViz, self).__init__(data, *args, **kwargs) + + self.vector_url = vector_url + self.vector_layer_name = vector_layer_name + self.vector_join_property = vector_join_property + self.data_join_property = data_join_property + + if self.vector_url is not None and self.vector_layer_name is not None: + self.template = 'vector_choropleth' + self.vector_source = True + else: + self.vector_source = False + self.template = 'choropleth' + + self.label_property = label_property + self.color_property = color_property + self.color_stops = color_stops + self.color_default = color_default + self.color_function_type = color_function_type + self.line_color = line_color + self.line_stroke = line_stroke + self.line_width = line_width + + def generate_vector_color_map(self): + """Generate color stops array for use with match expression in mapbox template""" + vector_stops = [] + for row in self.data: + + # map color to JSON feature using color_property + color = color_map(row[self.color_property], self.color_stops, self.color_default) + + # link to vector feature using data_join_property (from JSON object) + vector_stops.append([row[self.data_join_property], color]) + + return vector_stops + + def add_unique_template_variables(self, options): + """Update map template variables specific to heatmap visual""" + + # set line stroke dash interval based on line_stroke property + if self.line_stroke in ["dashed", "--"]: + self.line_dash_array = [6, 4] + elif self.line_stroke in ["dotted", ":"]: + self.line_dash_array = [0.5, 4] + elif self.line_stroke in ["dash dot", "-."]: + self.line_dash_array = [6, 4, 0.5, 4] + elif self.line_stroke in ["solid", "-"]: + self.line_dash_array = [1, 0] + else: + # default to solid line + self.line_dash_array = [1, 0] + + # common variables for vector and geojson-based choropleths + options.update(dict( + colorStops=self.color_stops, + colorProperty=self.color_property, + colorType=self.color_function_type, + defaultColor=self.color_default, + lineColor=self.line_color, + lineDashArray=self.line_dash_array, + lineStroke=self.line_stroke, + lineWidth=self.line_width, + )) + + # vector-based choropleth map variables + if self.vector_source: + options.update(dict( + vectorUrl=self.vector_url, + vectorLayer=self.vector_layer_name, + vectorColorStops=self.generate_vector_color_map(), + vectorJoinColorProperty=self.vector_join_property, + joinData=json.dumps(self.data, ensure_ascii=False), + dataJoinProperty=self.data_join_property, + )) + + # geojson-based choropleth map variables + else: + options.update(dict( + geojson_data=json.dumps(self.data, ensure_ascii=False), + )) + + class ImageViz(MapViz): """Create a image viz""" @@ -380,7 +499,7 @@ def __init__(self, :param coordinates: property to determine image coordinates (UL, UR, LR, LL). EX. [[-80.425, 46.437], [-71.516, 46.437], [-71.516, 37.936], [-80.425, 37.936]] :param image: url, local path or a numpy ndarray - + """ super(ImageViz, self).__init__(None, *args, **kwargs) diff --git a/setup.py b/setup.py index 75cbd68..aefea8e 100644 --- a/setup.py +++ b/setup.py @@ -31,6 +31,6 @@ 'mapboxgl': ['templates/*']}, include_package_data=True, zip_safe=False, - install_requires=['jinja2', 'geojson', 'colour', 'matplotlib'], + install_requires=['jinja2', 'geojson', 'chroma-py', 'colour', 'matplotlib'], extras_require={ 'test': ['pytest', 'pytest-cov', 'codecov', 'mock', 'jupyter', 'Sphinx', 'pandas']}) diff --git a/tests/polygons.geojson b/tests/polygons.geojson new file mode 100644 index 0000000..96d5dca --- /dev/null +++ b/tests/polygons.geojson @@ -0,0 +1,360 @@ +{ + "type": "FeatureCollection", + "features": [ + { + "type": "Feature", + "id": "06", + "properties": { + "name": "California", + "density": 241.7 + }, + "geometry": { + "type": "Polygon", + "coordinates": [ + [ + [-123.233256, 42.006186], + [-122.378853, 42.011663], + [-121.037003, 41.995232], + [-120.001861, 41.995232], + [-119.996384, 40.264519], + [-120.001861, 38.999346], + [-118.71478, 38.101128], + [-117.498899, 37.21934], + [-116.540435, 36.501861], + [-115.85034, 35.970598], + [-114.634459, 35.00118], + [-114.634459, 34.87521], + [-114.470151, 34.710902], + [-114.333228, 34.448009], + [-114.136058, 34.305608], + [-114.256551, 34.174162], + [-114.415382, 34.108438], + [-114.535874, 33.933176], + [-114.497536, 33.697668], + [-114.524921, 33.54979], + [-114.727567, 33.40739], + [-114.661844, 33.034958], + [-114.524921, 33.029481], + [-114.470151, 32.843265], + [-114.524921, 32.755634], + [-114.72209, 32.717295], + [-116.04751, 32.624187], + [-117.126467, 32.536556], + [-117.24696, 32.668003], + [-117.252437, 32.876127], + [-117.329114, 33.122589], + [-117.471515, 33.297851], + [-117.7837, 33.538836], + [-118.183517, 33.763391], + [-118.260194, 33.703145], + [-118.413548, 33.741483], + [-118.391641, 33.840068], + [-118.566903, 34.042715], + [-118.802411, 33.998899], + [-119.218659, 34.146777], + [-119.278905, 34.26727], + [-119.558229, 34.415147], + [-119.875891, 34.40967], + [-120.138784, 34.475393], + [-120.472878, 34.448009], + [-120.64814, 34.579455], + [-120.609801, 34.858779], + [-120.670048, 34.902595], + [-120.631709, 35.099764], + [-120.894602, 35.247642], + [-120.905556, 35.450289], + [-121.004141, 35.461243], + [-121.168449, 35.636505], + [-121.283465, 35.674843], + [-121.332757, 35.784382], + [-121.716143, 36.195153], + [-121.896882, 36.315645], + [-121.935221, 36.638785], + [-121.858544, 36.6114], + [-121.787344, 36.803093], + [-121.929744, 36.978355], + [-122.105006, 36.956447], + [-122.335038, 37.115279], + [-122.417192, 37.241248], + [-122.400761, 37.361741], + [-122.515777, 37.520572], + [-122.515777, 37.783465], + [-122.329561, 37.783465], + [-122.406238, 38.15042], + [-122.488392, 38.112082], + [-122.504823, 37.931343], + [-122.701993, 37.893004], + [-122.937501, 38.029928], + [-122.97584, 38.265436], + [-123.129194, 38.451652], + [-123.331841, 38.566668], + [-123.44138, 38.698114], + [-123.737134, 38.95553], + [-123.687842, 39.032208], + [-123.824765, 39.366301], + [-123.764519, 39.552517], + [-123.85215, 39.831841], + [-124.109566, 40.105688], + [-124.361506, 40.259042], + [-124.410798, 40.439781], + [-124.158859, 40.877937], + [-124.109566, 41.025814], + [-124.158859, 41.14083], + [-124.065751, 41.442061], + [-124.147905, 41.715908], + [-124.257444, 41.781632], + [-124.213628, 42.000709], + [-123.233256, 42.006186] + ] + ] + } + }, + { + "type": "Feature", + "id": "11", + "properties": { + "name": "District of Columbia", + "density": 10065 + }, + "geometry": { + "type": "Polygon", + "coordinates": [ + [ + [-77.035264, 38.993869], + [-76.909294, 38.895284], + [-77.040741, 38.791222], + [-77.117418, 38.933623], + [-77.035264, 38.993869] + ] + ] + } + }, + { + "type": "Feature", + "id": "25", + "properties": { + "name": "Massachusetts", + "density": 840.2 + }, + "geometry": { + "type": "Polygon", + "coordinates": [ + [ + [-70.917521, 42.887974], + [-70.818936, 42.871543], + [-70.780598, 42.696281], + [-70.824413, 42.55388], + [-70.983245, 42.422434], + [-70.988722, 42.269079], + [-70.769644, 42.247172], + [-70.638197, 42.08834], + [-70.660105, 41.962371], + [-70.550566, 41.929509], + [-70.539613, 41.814493], + [-70.260289, 41.715908], + [-69.937149, 41.809016], + [-70.008349, 41.672093], + [-70.484843, 41.5516], + [-70.660105, 41.546123], + [-70.764167, 41.639231], + [-70.928475, 41.611847], + [-70.933952, 41.540646], + [-71.120168, 41.496831], + [-71.196845, 41.67757], + [-71.22423, 41.710431], + [-71.328292, 41.781632], + [-71.383061, 42.01714], + [-71.530939, 42.01714], + [-71.799309, 42.006186], + [-71.799309, 42.022617], + [-73.053528, 42.039048], + [-73.486206, 42.050002], + [-73.508114, 42.08834], + [-73.267129, 42.745573], + [-72.456542, 42.729142], + [-71.29543, 42.696281], + [-71.185891, 42.789389], + [-70.917521, 42.887974] + ] + ] + } + }, + { + "type": "Feature", + "id": "30", + "properties": { + "name": "Montana", + "density": 6.858 + }, + "geometry": { + "type": "Polygon", + "coordinates": [ + [ + [-104.047534, 49.000239], + [-104.042057, 47.861036], + [-104.047534, 45.944106], + [-104.042057, 44.996596], + [-104.058488, 44.996596], + [-105.91517, 45.002073], + [-109.080842, 45.002073], + [-111.05254, 45.002073], + [-111.047063, 44.476286], + [-111.227803, 44.580348], + [-111.386634, 44.75561], + [-111.616665, 44.547487], + [-111.819312, 44.509148], + [-111.868605, 44.563917], + [-112.104113, 44.520102], + [-112.241036, 44.569394], + [-112.471068, 44.481763], + [-112.783254, 44.48724], + [-112.887315, 44.394132], + [-113.002331, 44.448902], + [-113.133778, 44.772041], + [-113.341901, 44.782995], + [-113.456917, 44.865149], + [-113.45144, 45.056842], + [-113.571933, 45.128042], + [-113.736241, 45.330689], + [-113.834826, 45.522382], + [-113.807441, 45.604536], + [-113.98818, 45.703121], + [-114.086765, 45.593582], + [-114.333228, 45.456659], + [-114.546828, 45.560721], + [-114.497536, 45.670259], + [-114.568736, 45.774321], + [-114.387997, 45.88386], + [-114.492059, 46.037214], + [-114.464674, 46.272723], + [-114.322274, 46.645155], + [-114.612552, 46.639678], + [-114.623506, 46.705401], + [-114.886399, 46.809463], + [-114.930214, 46.919002], + [-115.302646, 47.187372], + [-115.324554, 47.258572], + [-115.527201, 47.302388], + [-115.718894, 47.42288], + [-115.724371, 47.696727], + [-116.04751, 47.976051], + [-116.04751, 49.000239], + [-111.50165, 48.994762], + [-109.453274, 49.000239], + [-104.047534, 49.000239] + ] + ] + } + }, + { + "type": "Feature", + "id": "36", + "properties": { + "name": "New York", + "density": 412.3 + }, + "geometry": { + "type": "Polygon", + "coordinates": [ + [ + [-73.343806, 45.013027], + [-73.332852, 44.804903], + [-73.387622, 44.618687], + [-73.294514, 44.437948], + [-73.321898, 44.246255], + [-73.436914, 44.043608], + [-73.349283, 43.769761], + [-73.404052, 43.687607], + [-73.245221, 43.523299], + [-73.278083, 42.833204], + [-73.267129, 42.745573], + [-73.508114, 42.08834], + [-73.486206, 42.050002], + [-73.55193, 41.294184], + [-73.48073, 41.21203], + [-73.727192, 41.102491], + [-73.655992, 40.987475], + [-73.22879, 40.905321], + [-73.141159, 40.965568], + [-72.774204, 40.965568], + [-72.587988, 40.998429], + [-72.28128, 41.157261], + [-72.259372, 41.042245], + [-72.100541, 40.992952], + [-72.467496, 40.845075], + [-73.239744, 40.625997], + [-73.562884, 40.582182], + [-73.776484, 40.593136], + [-73.935316, 40.543843], + [-74.022947, 40.708151], + [-73.902454, 40.998429], + [-74.236547, 41.14083], + [-74.69661, 41.359907], + [-74.740426, 41.431108], + [-74.89378, 41.436584], + [-75.074519, 41.60637], + [-75.052611, 41.754247], + [-75.173104, 41.869263], + [-75.249781, 41.863786], + [-75.35932, 42.000709], + [-79.76278, 42.000709], + [-79.76278, 42.252649], + [-79.76278, 42.269079], + [-79.149363, 42.55388], + [-79.050778, 42.690804], + [-78.853608, 42.783912], + [-78.930285, 42.953697], + [-79.012439, 42.986559], + [-79.072686, 43.260406], + [-78.486653, 43.375421], + [-77.966344, 43.369944], + [-77.75822, 43.34256], + [-77.533665, 43.233021], + [-77.391265, 43.276836], + [-76.958587, 43.271359], + [-76.695693, 43.34256], + [-76.41637, 43.523299], + [-76.235631, 43.528776], + [-76.230154, 43.802623], + [-76.137046, 43.961454], + [-76.3616, 44.070993], + [-76.312308, 44.196962], + [-75.912491, 44.366748], + [-75.764614, 44.514625], + [-75.282643, 44.848718], + [-74.828057, 45.018503], + [-74.148916, 44.991119], + [-73.343806, 45.013027] + ] + ] + } + }, + { + "type": "Feature", + "id": "49", + "properties": { + "name": "Utah", + "density": 34.3 + }, + "geometry": { + "type": "Polygon", + "coordinates": [ + [ + [-112.164359, 41.995232], + [-111.047063, 42.000709], + [-111.047063, 40.998429], + [-109.04798, 40.998429], + [-109.053457, 39.125316], + [-109.058934, 38.27639], + [-109.042503, 38.166851], + [-109.042503, 37.000263], + [-110.499369, 37.00574], + [-114.048427, 37.000263], + [-114.04295, 41.995232], + [-112.164359, 41.995232] + ] + ] + } + } + ] +} \ No newline at end of file diff --git a/tests/test_html.py b/tests/test_html.py index d530a42..5887474 100644 --- a/tests/test_html.py +++ b/tests/test_html.py @@ -8,6 +8,7 @@ from mapboxgl.viz import * from mapboxgl.errors import TokenError +from mapboxgl.utils import create_color_stops from matplotlib.pyplot import imread @@ -17,6 +18,12 @@ def data(): return json.loads(fh.read()) +@pytest.fixture() +def polygon_data(): + with open('tests/polygons.geojson') as fh: + return json.loads(fh.read()) + + TOKEN = 'pk.abc123' @@ -36,6 +43,14 @@ def test_secret_key_GraduatedCircleViz(data): GraduatedCircleViz(data, access_token=secret) +def test_secret_key_ChoroplethViz(polygon_data): + """Secret key raises a token error + """ + secret = 'sk.abc123' + with pytest.raises(TokenError): + ChoroplethViz(polygon_data, access_token=secret) + + def test_token_env_CircleViz(monkeypatch, data): """Viz can get token from environment if not specified """ @@ -44,6 +59,24 @@ def test_token_env_CircleViz(monkeypatch, data): assert TOKEN in viz.create_html() +def test_token_env_GraduatedCircleViz(monkeypatch, data): + """Viz can get token from environment if not specified + """ + monkeypatch.setenv('MAPBOX_ACCESS_TOKEN', TOKEN) + viz = GraduatedCircleViz(data, + color_property="Avg Medicare Payments", + radius_property="Avg Covered Charges") + assert TOKEN in viz.create_html() + + +def test_token_env_ChoroplethViz(monkeypatch, polygon_data): + """Viz can get token from environment if not specified + """ + monkeypatch.setenv('MAPBOX_ACCESS_TOKEN', TOKEN) + viz = ChoroplethViz(polygon_data, color_property="density") + assert TOKEN in viz.create_html() + + def test_html_color(data): viz = CircleViz(data, color_property="Avg Medicare Payments", @@ -59,14 +92,12 @@ def test_html_GraduatedCricleViz(data): assert "" in viz.create_html() -def test_token_env_GraduatedCircleViz(monkeypatch, data): - """Viz can get token from environment if not specified - """ - monkeypatch.setenv('MAPBOX_ACCESS_TOKEN', TOKEN) - viz = GraduatedCircleViz(data, - color_property="Avg Medicare Payments", - radius_property="Avg Covered Charges") - assert TOKEN in viz.create_html() +def test_html_ChoroplethViz(polygon_data): + viz = ChoroplethViz(polygon_data, + color_property="density", + color_stops=[[0.0, "red"], [50.0, "gold"], [1000.0, "blue"]], + access_token=TOKEN) + assert "" in viz.create_html() @patch('mapboxgl.viz.display') @@ -111,6 +142,7 @@ def test_display_HeatmapViz(display, data): viz.show() display.assert_called_once() + @patch('mapboxgl.viz.display') def test_display_ClusteredCircleViz(display, data): """Assert that show calls the mocked display function @@ -122,6 +154,45 @@ def test_display_ClusteredCircleViz(display, data): viz.show() display.assert_called_once() + +@patch('mapboxgl.viz.display') +def test_display_ChoroplethViz(display, polygon_data): + """Assert that show calls the mocked display function + """ + viz = ChoroplethViz(polygon_data, + color_property="density", + color_stops=[[0.0, "red"], [50.0, "gold"], [1000.0, "blue"]], + access_token=TOKEN) + viz.show() + display.assert_called_once() + + +@patch('mapboxgl.viz.display') +def test_display_vector_ChoroplethViz(display): + """Assert that show calls the mocked display function when using data-join technique + for ChoroplethViz. + """ + data = [{"id": "06", "name": "California", "density": 241.7}, + {"id": "11", "name": "District of Columbia", "density": 10065}, + {"id": "25", "name": "Massachusetts", "density": 840.2}, + {"id": "30", "name": "Montana", "density": 6.858}, + {"id": "36", "name": "New York", "density": 412.3}, + {"id": "49", "name": "Utah", "density": 34.3}, + {"id": "72", "name": "Puerto Rico", "density": 1082}] + + viz = ChoroplethViz(data, + vector_url='mapbox://mapbox.us_census_states_2015', + vector_layer_name='states', + vector_join_property='STATEFP', + data_join_property='id', + color_property='density', + color_stops=create_color_stops([0, 50, 100, 500, 1500], colors='YlOrRd'), + access_token=TOKEN + ) + viz.show() + display.assert_called_once() + + @patch('mapboxgl.viz.display') def test_min_zoom(display, data): viz = GraduatedCircleViz(data, @@ -133,6 +204,7 @@ def test_min_zoom(display, data): viz.show() display.assert_called_once() + @patch('mapboxgl.viz.display') def test_max_zoom(display, data): viz = HeatmapViz(data, diff --git a/tests/test_utils.py b/tests/test_utils.py index bc7a42e..9065707 100644 --- a/tests/test_utils.py +++ b/tests/test_utils.py @@ -7,7 +7,8 @@ from matplotlib.pyplot import imread from mapboxgl.utils import (df_to_geojson, scale_between, create_radius_stops, - create_weight_stops, create_color_stops, img_encode) + create_weight_stops, create_color_stops, img_encode, + rgb_tuple_from_str, color_map) @pytest.fixture() @@ -94,3 +95,61 @@ def test_img_encode(): image_path = os.path.join(os.path.dirname(__file__), 'mosaic.png') image = imread(image_path) assert img_encode(image).startswith('data:image/png;base64') + + +def test_rgb_tuple_from_str(): + """Extract RGB values as tuple from string RGB color representation""" + assert rgb_tuple_from_str('rgb(122,43,17)') == (122, 43, 17) + + +def test_rgb_tuple_from_str_rgba(): + """Extract RGBA values as tuple from string RGBA color representation""" + assert rgb_tuple_from_str('rgba(122,43,17,0.5)') == (122, 43, 17, 0.5) + + +def test_rgb_tuple_from_str_hex(): + """Extract RGB(A) values as tuple from string HEX color representation""" + assert rgb_tuple_from_str('#bada55') == (186, 218, 85) + + +def test_rgb_tuple_from_str_english(): + """Extract RGB(A) values as tuple from limited English color name strings""" + assert rgb_tuple_from_str('red') == (255, 0, 0) + + +def test_color_map(): + """Compute color for lookup value in gradient based on color_stops argument using categorical match""" + match_stops = [[0.0, 'rgb(255,0,255)'],['CA', 'rgb(255,0,0)'], ['NY', 'rgb(255,255,0)'], ['MA', 'rgb(0,0,255)']] + assert color_map('CA', match_stops, default_color='gray') == 'rgb(255,0,0)' + + +def test_color_map_numeric_default_color(): + """Default color when look up value does not match any stop in categorical color stops""" + match_stops = [[0.0, 'rgb(255,0,255)'],['CA', 'rgb(255,0,0)'], ['NY', 'rgb(255,255,0)'], ['MA', 'rgb(0,0,255)']] + assert color_map(17, match_stops, 'blue') == 'blue' + + +def test_color_map_default_color(): + """Default color when look up value does not match any stop in categorical color stops""" + match_stops = [[0.0, 'rgb(255,0,255)'],['CA', 'rgb(255,0,0)'], ['NY', 'rgb(255,255,0)'], ['MA', 'rgb(0,0,255)']] + assert color_map('MI', match_stops, 'gray') == 'gray' + + +def test_color_map_numeric_match(): + """Get color for numeric lookup value in categorical color stops if number exists in stops""" + match_stops = [[0.0, 'rgb(255,0,255)'],['CA', 'rgb(255,0,0)'], ['NY', 'rgb(255,255,0)'], ['MA', 'rgb(0,0,255)']] + assert color_map(0.0, match_stops, 'green') == 'rgb(255,0,255)' + + +def test_color_map_interp(): + """Compute color for lookup value by interpolation of color stops""" + interp_stops = [[0.0, 'rgb(255,0,0)'], [50.0, 'rgb(255,255,0)'], [1000.0, 'rgb(0,0,255)']] + assert color_map(17, interp_stops, 'orange') == 'rgb(255,87,0)' + + +def test_color_map_interp_exact(): + """Compute color for lookup value exactly matching numeric stop in color stops""" + interp_stops = [[0.0, 'rgb(255,0,0)'], [50.0, 'rgb(255,255,0)'], [1000.0, 'rgb(0,0,255)']] + assert color_map(0.0, interp_stops, 'rgb(32,32,32)') == 'rgb(255,0,0)' + +