├── .gitignore
├── README.md
├── animation.gif
├── data
├── city.json
├── districts.json
├── graph.graphml
└── hospitals.json
├── environment.yml
└── main.ipynb
/.gitignore:
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1 | # Byte-compiled / optimized / DLL files
2 | __pycache__/
3 | *.py[cod]
4 |
5 | # C extensions
6 | *.so
7 |
8 | # Distribution / packaging
9 | .Python
10 | env/
11 | build/
12 | develop-eggs/
13 | dist/
14 | downloads/
15 | eggs/
16 | .eggs/
17 | lib/
18 | lib64/
19 | parts/
20 | sdist/
21 | var/
22 | *.egg-info/
23 | .installed.cfg
24 | *.egg
25 |
26 | # PyInstaller
27 | # Usually these files are written by a python script from a template
28 | # before PyInstaller builds the exe, so as to inject date/other infos into it.
29 | *.manifest
30 | *.spec
31 |
32 | # Installer logs
33 | pip-log.txt
34 | pip-delete-this-directory.txt
35 |
36 | # Unit test / coverage reports
37 | htmlcov/
38 | .tox/
39 | .coverage
40 | .coverage.*
41 | .cache
42 | nosetests.xml
43 | coverage.xml
44 | *.cover
45 |
46 | # Translations
47 | *.mo
48 | *.pot
49 |
50 | # Django stuff:
51 | *.log
52 |
53 | # Sphinx documentation
54 | docs/_build/
55 |
56 | # PyBuilder
57 | target/
58 |
59 | # DotEnv configuration
60 | .env
61 |
62 | # Database
63 | *.db
64 | *.rdb
65 |
66 | # Pycharm
67 | .idea
68 |
69 | # VS Code
70 | .vscode/
71 |
72 | # Spyder
73 | .spyproject/
74 |
75 | # Jupyter NB Checkpoints
76 | .ipynb_checkpoints/
77 |
78 | # exclude data from source control by default
79 | # /data/
80 |
81 | # Mac OS-specific storage files
82 | .DS_Store
83 |
84 | # vim
85 | *.swp
86 | *.swo
87 |
88 | # Mypy cache
89 | .mypy_cache/
90 |
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/README.md:
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1 | [](https://mybinder.org/v2/gh/mikhailsirenko/osmnx-matplotlib-animation/master?filepath=main.ipynb)
2 |
3 | # osmnx-matplotlib-animation
4 | A simple example of how to animate objects moving on OSMnx graph
5 |
6 | ## Motivation
7 | Create a simple minimalistic animation of an object (e.g. car, citizen) moving on OSMnx or NetworkX graph object (street network) using matplotlib syntax.
8 |
9 | An alternative that is worth mentioning is [streamlit](https://github.com/streamlit/streamlit). It is much more powerful, allows you to use controls and looks fancier :-) The drawback is its syntax and the way how it works with matplotlib (GeoPandas) objects (my application was too slow). If you know better ways to animate this task, please, ping [me](https://twitter.com/mikhailsirenko) on Twitter.
10 |
11 | ## Example
12 | The example in `main.ipynb` describes a ride of 5 ambulance cars from 5 hospitals in The Hague to a district called Centrum. To get from the origins to destinations cars use the shortest paths. They start the ride at the same time, but since the route lengths are different, some of them arrive earlier.
13 |
14 | In OSXMnx and matplotlib "language", we first define origin (O) and destination (D) points: hospital coordinates and a Centrum district centroid; second, we calculate the shortest paths from O to D; thereafter, extract coordinates of the nodes of derived shortest paths; finally, sequentially plotting each of the coordinate pairs using matplotlib FuncAnimation.
15 |
16 |
17 |
18 |
19 |
20 | ## Data used
21 | The data sets used in this example:
22 | 1. city.json: The Hague city shapefile;
23 | 2. districts.json: The Hague districts shapefile;
24 | 3. hospitals.json: Hospital locations;
25 | 4. graph.graphml: The Hague street network derived with OSMnx graph_from_point function.
26 |
27 | ## Use cases
28 | You can easily fine-tune this notebook for your case study: just think in terms of origins and destinations. For example, instead of ambulance cars, you want to animate citizens walking from their homes to supermarkets. No problem! Define where the citizens live (replace hospitals.json), where the supermarkets are located (replace districts.json), get new graph.graphml file with OSMnx, finally, configure the variable names in the notebook to avoid confusion. Now you can rerun the notebook and voila your animation is created!
29 |
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/animation.gif:
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https://raw.githubusercontent.com/mikhailsirenko/osmnx-matplotlib-animation/761dce889551eab2bd6eb48cebed8405ab9b485a/animation.gif
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/data/hospitals.json:
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1 | {
2 | "type": "FeatureCollection",
3 | "features": [
4 | { "type": "Feature", "properties": { "name": "HagaZiekenhuis locatie Juliana Kinderziekenhuis", "addr:city": null, "addr:postcode": null, "healthcare:speciality": null, "emergency": null }, "geometry": { "type": "Point", "coordinates": [ 4.2639767, 52.0550701 ] } },
5 | { "type": "Feature", "properties": { "name": "HMC Bronovo", "addr:city": "'s-Gravenhage", "addr:postcode": "2597AX", "healthcare:speciality": null, "emergency": "yes" }, "geometry": { "type": "Point", "coordinates": [ 4.317859246480068, 52.101371071194201 ] } },
6 | { "type": "Feature", "properties": { "name": "HMC Westeinde", "addr:city": "'s-Gravenhage", "addr:postcode": "2512VA", "healthcare:speciality": null, "emergency": "yes" }, "geometry": { "type": "Point", "coordinates": [ 4.299907823461282, 52.07416759435074 ] } },
7 | { "type": "Feature", "properties": { "name": "HagaZiekenhuis locatie Leyweg", "addr:city": "'s-Gravenhage", "addr:postcode": "2545AA", "healthcare:speciality": null, "emergency": "yes" }, "geometry": { "type": "Point", "coordinates": [ 4.263328143864035, 52.055550964665287 ] } },
8 | { "type": "Feature", "properties": { "name": "Haga Ziekenhuis, locatie Sportlaan", "addr:city": null, "addr:postcode": null, "healthcare:speciality": null, "emergency": null }, "geometry": { "type": "Point", "coordinates": [ 4.264572128869638, 52.081313493144407 ] } }
9 | ]
10 | }
11 |
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/environment.yml:
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1 | name: osmnx-matplotlib-animation
2 | channels:
3 | - conda-forge
4 | dependencies:
5 | - pandas
6 | - geopandas
7 | - descartes
8 | - numpy
9 | - matplotlib
10 | - networkx
11 | - osmnx
12 | - partd
13 | - bokeh
14 | - dask
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/main.ipynb:
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1 | {
2 | "cells": [
3 | {
4 | "cell_type": "markdown",
5 | "metadata": {},
6 | "source": [
7 | "# osmnx-matplotlib-animation"
8 | ]
9 | },
10 | {
11 | "cell_type": "code",
12 | "execution_count": 8,
13 | "metadata": {},
14 | "outputs": [],
15 | "source": [
16 | "import osmnx as ox\n",
17 | "import networkx as nx\n",
18 | "import pandas as pd\n",
19 | "import numpy as np\n",
20 | "import geopandas as gpd\n",
21 | "import matplotlib.pyplot as plt\n",
22 | "from shapely.geometry import Point\n",
23 | "from matplotlib.animation import FuncAnimation\n",
24 | "from IPython.display import HTML"
25 | ]
26 | },
27 | {
28 | "cell_type": "markdown",
29 | "metadata": {},
30 | "source": [
31 | "## 1. Load the data"
32 | ]
33 | },
34 | {
35 | "cell_type": "code",
36 | "execution_count": 9,
37 | "metadata": {},
38 | "outputs": [],
39 | "source": [
40 | "city = gpd.read_file('data/city.json')\n",
41 | "city.crs = \"EPSG:4326\"\n",
42 | "graph = ox.load_graphml(\"data/graph.graphml\") # street network\n",
43 | "districts = gpd.read_file('data/districts.json') # district shapefiles\n",
44 | "districts.crs = \"EPSG:4326\"\n",
45 | "hospitals = gpd.read_file('data/hospitals.json') # hospital locations\n",
46 | "hospitals.crs = \"EPSG:4326\""
47 | ]
48 | },
49 | {
50 | "cell_type": "markdown",
51 | "metadata": {},
52 | "source": [
53 | "## 2. Find routes"
54 | ]
55 | },
56 | {
57 | "cell_type": "code",
58 | "execution_count": 10,
59 | "metadata": {},
60 | "outputs": [
61 | {
62 | "name": "stdout",
63 | "output_type": "stream",
64 | "text": [
65 | "Number of origin points : 5\n"
66 | ]
67 | }
68 | ],
69 | "source": [
70 | "# Specify origin points as hospital locations\n",
71 | "orig_points = []\n",
72 | "for geometry in hospitals[\"geometry\"]:\n",
73 | " x, y = geometry.xy\n",
74 | " x = x[0]\n",
75 | " y = y[0]\n",
76 | " orig_points.append((y, x))\n",
77 | "print(f'Number of origin points : {len(orig_points)}')"
78 | ]
79 | },
80 | {
81 | "cell_type": "code",
82 | "execution_count": 11,
83 | "metadata": {},
84 | "outputs": [
85 | {
86 | "name": "stdout",
87 | "output_type": "stream",
88 | "text": [
89 | "Destination point : Wijk 28 Centrum\n"
90 | ]
91 | }
92 | ],
93 | "source": [
94 | "# Select a random district a destination point\n",
95 | "n = 27\n",
96 | "centroid = districts.iloc[n, :]['geometry'].centroid\n",
97 | "district_name = districts.iloc[n, :]['WK_NAAM']\n",
98 | "district = districts[districts['WK_NAAM'] == district_name]\n",
99 | "print(f'Destination point : {district_name}')"
100 | ]
101 | },
102 | {
103 | "cell_type": "code",
104 | "execution_count": 12,
105 | "metadata": {},
106 | "outputs": [],
107 | "source": [
108 | "# Specify destination points\n",
109 | "x, y = centroid.xy\n",
110 | "x = x[0]\n",
111 | "y = y[0]\n",
112 | "dest_points = [(y, x)] * len(orig_points)"
113 | ]
114 | },
115 | {
116 | "cell_type": "code",
117 | "execution_count": 13,
118 | "metadata": {},
119 | "outputs": [],
120 | "source": [
121 | "# Find nearest nodes to of specified origin desination points\n",
122 | "# Based on them make the routes\n",
123 | "orig_nodes = []\n",
124 | "for orig_point in orig_points:\n",
125 | " orig_nodes.append(ox.get_nearest_node(graph, orig_point))\n",
126 | " \n",
127 | "dest_nodes = []\n",
128 | "for dest_point in dest_points:\n",
129 | " dest_nodes.append(ox.get_nearest_node(graph, dest_point))"
130 | ]
131 | },
132 | {
133 | "cell_type": "code",
134 | "execution_count": 14,
135 | "metadata": {},
136 | "outputs": [
137 | {
138 | "name": "stdout",
139 | "output_type": "stream",
140 | "text": [
141 | "Wall time: 182 ms\n"
142 | ]
143 | }
144 | ],
145 | "source": [
146 | "%%time\n",
147 | "egs = []\n",
148 | "for orig_node in orig_nodes:\n",
149 | " egs.append(nx.ego_graph(graph, orig_node, radius=2000, distance='length'))"
150 | ]
151 | },
152 | {
153 | "cell_type": "code",
154 | "execution_count": 15,
155 | "metadata": {},
156 | "outputs": [
157 | {
158 | "name": "stdout",
159 | "output_type": "stream",
160 | "text": [
161 | "Route length : 4.8 km\n",
162 | "Route length : 4.0 km\n",
163 | "Route length : 1.1 km\n",
164 | "Route length : 4.8 km\n",
165 | "Route length : 4.0 km\n",
166 | "\n",
167 | "The shortest route is 1.1 km\n"
168 | ]
169 | }
170 | ],
171 | "source": [
172 | "routes = []\n",
173 | "lengths = []\n",
174 | "for orig_node, dest_node in zip(orig_nodes, dest_nodes):\n",
175 | " try:\n",
176 | " routes.append(nx.shortest_path(graph, source=orig_node, target=dest_node, weight='length'))\n",
177 | " length = nx.shortest_path_length(G=graph, source=orig_node, target=dest_node, weight='length')\n",
178 | " lengths.append(length)\n",
179 | " print(f'Route length : {round(length / 1000, 1)} km')\n",
180 | " except:\n",
181 | " print('Error. No route from {} to {}.'.format(orig_node, dest_node))\n",
182 | " pass\n",
183 | "\n",
184 | "print()\n",
185 | "print(f'The shortest route is {round(min(lengths) / 1000, 1)} km')"
186 | ]
187 | },
188 | {
189 | "cell_type": "markdown",
190 | "metadata": {},
191 | "source": [
192 | "## 3. Define route coordinates"
193 | ]
194 | },
195 | {
196 | "cell_type": "code",
197 | "execution_count": 16,
198 | "metadata": {},
199 | "outputs": [],
200 | "source": [
201 | "# Project graph to 3395 to make CRS coherent with the rest of the objects\n",
202 | "projected_graph = ox.project_graph(graph, to_crs=\"EPSG:3395\")"
203 | ]
204 | },
205 | {
206 | "cell_type": "code",
207 | "execution_count": 17,
208 | "metadata": {},
209 | "outputs": [],
210 | "source": [
211 | "# Extrat coordinates of route nodes \n",
212 | "route_coorindates = []\n",
213 | "\n",
214 | "for route in routes:\n",
215 | " points = []\n",
216 | " for node_id in route:\n",
217 | " x = projected_graph.nodes[node_id]['x']\n",
218 | " y = projected_graph.nodes[node_id]['y']\n",
219 | " points.append([x, y])\n",
220 | " route_coorindates.append(points)\n",
221 | " \n",
222 | "n_routes = len(route_coorindates)\n",
223 | "max_route_len = max([len(x) for x in route_coorindates])"
224 | ]
225 | },
226 | {
227 | "cell_type": "code",
228 | "execution_count": 18,
229 | "metadata": {},
230 | "outputs": [
231 | {
232 | "name": "stdout",
233 | "output_type": "stream",
234 | "text": [
235 | "Number of routes : 5\n",
236 | "Number of nodes in the first route : 62\n",
237 | "Coordinates of the first node in the first route : [474767.45363185334, 6776344.155987251]\n",
238 | "Max number of nodes in a route : 62\n"
239 | ]
240 | }
241 | ],
242 | "source": [
243 | "print(f'Number of routes : {n_routes}')\n",
244 | "print(f'Number of nodes in the first route : {len(route_coorindates[0])}')\n",
245 | "print(f'Coordinates of the first node in the first route : {route_coorindates[0][0]}')\n",
246 | "print(f'Max number of nodes in a route : {max_route_len}')"
247 | ]
248 | },
249 | {
250 | "cell_type": "markdown",
251 | "metadata": {},
252 | "source": [
253 | "## 4. Animate ambulance cars"
254 | ]
255 | },
256 | {
257 | "cell_type": "code",
258 | "execution_count": 19,
259 | "metadata": {},
260 | "outputs": [
261 | {
262 | "name": "stdout",
263 | "output_type": "stream",
264 | "text": [
265 | "Wall time: 257 ms\n"
266 | ]
267 | }
268 | ],
269 | "source": [
270 | "%%time\n",
271 | "# Transform everything to the same coordiante system \n",
272 | "# Figures plotted with 3395 looks better than 4326 :-)\n",
273 | "city.to_crs('EPSG:3395', inplace=True)\n",
274 | "district = district.to_crs('EPSG:3395')\n",
275 | "hospitals.to_crs('EPSG:3395', inplace=True)"
276 | ]
277 | },
278 | {
279 | "cell_type": "code",
280 | "execution_count": 20,
281 | "metadata": {},
282 | "outputs": [],
283 | "source": [
284 | "# Fix bounds for axis\n",
285 | "x_min, y_min, x_max, y_max = city.total_bounds"
286 | ]
287 | },
288 | {
289 | "cell_type": "code",
290 | "execution_count": 21,
291 | "metadata": {},
292 | "outputs": [
293 | {
294 | "data": {
295 | "image/png": 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\n",
296 | "text/plain": [
297 | ""
298 | ]
299 | },
300 | "metadata": {},
301 | "output_type": "display_data"
302 | }
303 | ],
304 | "source": [
305 | "# Prepare the layout\n",
306 | "fig, ax = ox.plot_graph(projected_graph, node_size=0, edge_linewidth=0.5, show=False, close=False) # network\n",
307 | "city.plot(ax=ax, edgecolor='black', linewidth=1, alpha=0.1) # city shapefile\n",
308 | "district.plot(ax=ax, edgecolor='black', linewidth=1, alpha=0.5, color='orange') # destination district\n",
309 | "hospitals.plot(ax=ax, color='red', label='hospital') # hospitals\n",
310 | "ax.set(xlim=(x_min, x_max), ylim=(y_min, y_max)) # set the map limits\n",
311 | "\n",
312 | "# Each list is a route\n",
313 | "# Length of this list = n_routes\n",
314 | "scatter_list = []\n",
315 | "\n",
316 | "# Plot the first scatter plot (starting nodes = initial car locations = hospital locations)\n",
317 | "for j in range(n_routes):\n",
318 | " scatter_list.append(ax.scatter(route_coorindates[j][0][0], # x coordiante of the first node of the j route\n",
319 | " route_coorindates[j][0][1], # y coordiante of the first node of the j route\n",
320 | " label=f'ambulance car {j}', \n",
321 | " alpha=.75))\n",
322 | " \n",
323 | "plt.legend(frameon=False)\n",
324 | "\n",
325 | "def animate(i):\n",
326 | " \"\"\"Animate scatter plot (car movement)\n",
327 | " \n",
328 | " Args:\n",
329 | " i (int) : Iterable argument. \n",
330 | " \n",
331 | " Returns:\n",
332 | " None\n",
333 | " \n",
334 | " \"\"\"\n",
335 | " # Iterate over all routes = number of ambulance cars riding\n",
336 | " for j in range(n_routes):\n",
337 | " # Some routes are shorter than others\n",
338 | " # Therefore we need to use try except with continue construction\n",
339 | " try:\n",
340 | " # Try to plot a scatter plot\n",
341 | " x_j = route_coorindates[j][i][0]\n",
342 | " y_j = route_coorindates[j][i][1]\n",
343 | " scatter_list[j].set_offsets(np.c_[x_j, y_j])\n",
344 | " except:\n",
345 | " # If i became > len(current_route) then continue to the next route\n",
346 | " continue\n",
347 | "\n",
348 | "# Make the animation\n",
349 | "animation = FuncAnimation(fig, animate, frames=max_route_len)\n",
350 | "\n",
351 | "# HTML(animation.to_jshtml()) # to display animation in Jupyter Notebook\n",
352 | "animation.save('animation.mp4', dpi=300) # to save animation"
353 | ]
354 | }
355 | ],
356 | "metadata": {
357 | "kernelspec": {
358 | "display_name": "Python 3",
359 | "language": "python",
360 | "name": "python3"
361 | },
362 | "language_info": {
363 | "codemirror_mode": {
364 | "name": "ipython",
365 | "version": 3
366 | },
367 | "file_extension": ".py",
368 | "mimetype": "text/x-python",
369 | "name": "python",
370 | "nbconvert_exporter": "python",
371 | "pygments_lexer": "ipython3",
372 | "version": "3.7.6"
373 | }
374 | },
375 | "nbformat": 4,
376 | "nbformat_minor": 4
377 | }
378 |
--------------------------------------------------------------------------------