add code to generate member map

This commit is contained in:
Lukas Grossberger 2022-10-09 14:03:18 +02:00
parent 4d92a749f7
commit e2b6c2b3b6
5 changed files with 162 additions and 2 deletions

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.gitignore vendored Normal file
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__pycache__
*.png
*json

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Dockerfile Normal file
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FROM ubuntu:22.04
ARG PLZ_DATA=Postleitzahlengebiete_-_OSM.geojson
ARG PLZ_HIGHLIGHT=wtf_member_plz_prefixes.json
# Set up environment with dependencies
RUN apt-get update && apt-get install libblas-dev python3-pip libgeos-dev wget -y
COPY requirements.txt ./
RUN pip install -r requirements.txt
# Copy all relevant data
COPY $PLZ_DATA ./
COPY $PLZ_HIGHLIGHT ./
# Render map
COPY main.py ./
RUN python3 main.py --plz-data $PLZ_DATA --plz-highlight $PLZ_HIGHLIGHT --out /tmp/map.png
# Output map; use with "docker build -t wtf-map . && docker run wtf-map > map.png"
CMD ["cat", "/tmp/map.png"]

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# member-map
# Map of Germany with highlighted WTF member locations
Generate a map of Germany with highlighted WTF member locations.
## Docker Usage
Download the Germany PLZ dataset in the GeoJSON format from
https://opendata-esri-de.opendata.arcgis.com/datasets/5b203df4357844c8a6715d7d411a8341_0
and place the file in the root of this repository.
Place a JSON file containing a list of PLZ prefixes as `wtf_member_plz_prefixes.json` in
the root of this repository.
The file contents should look like `["121", "635"]` for PLZ data that is anonymized to
the first three digits.
The following will build a Docker image and render the map with the default
configuration for the WTF member PLZ prefix data:
```
docker build -t wtf-map .
docker run wtf-map > map.png
```
Note, the build command already renders the map and thus can take a moment.
The run command just outputs the already rendered image to be piped into any target
file on the host system.
## Script Usage
In case you'd like custom colors or use different data, you are encouraged to use the
script explicity.
To get all relevant requirements, you can `pip install -r requirements.txt`, but note,
you might need to install BLAS and GEOS libraries on your system.
The following will tell you all about what you can adjust for a custom visualization:
```
python main.py --help
```

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main.py Normal file
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import argparse
import json
import cartopy.crs as ccrs
import geopandas as gpd
import geoplot
import geoplot.crs as gcrs
import matplotlib.pyplot as plt
def main(
plz_data_path: str,
plz_prefixes_path: str,
output_file_path: str,
map_background_color: str,
map_accent_color: str,
image_background_color: str,
):
if not output_file_path.endswith(".png"):
raise ValueError(f"Output file needs to be a .png but is {output_file_path}")
with open(plz_prefixes_path, "r") as fh:
plz_prefixes = json.load(fh)
with open(plz_data_path, "r") as fh:
plz_geojson_data = json.load(fh)
data = gpd.GeoDataFrame.from_features(plz_geojson_data["features"])
data["highlighted"] = False
for plz_prefix in plz_prefixes:
data.loc[data["plz"].str.startswith(plz_prefix), "highlighted"] = True
ax = plt.axes(projection=ccrs.TransverseMercator())
geoplot.polyplot(
data,
projection=gcrs.TransverseMercator(),
edgecolor=map_background_color,
facecolor=map_background_color,
linewidth=0.3,
ax=ax,
)
geoplot.polyplot(
data[data["highlighted"]],
projection=gcrs.TransverseMercator(),
edgecolor=map_accent_color,
facecolor=map_accent_color,
linewidth=0.3,
ax=ax,
)
ax.set_facecolor(image_background_color)
plt.tight_layout()
plt.savefig(
output_file_path, dpi=300, facecolor=image_background_color, edgecolor="none"
)
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument(
"--plz-data",
required=True,
help="A GEOJSON file with a 'plz' feature, like the one for Germany that can be"
+ " downloaded from "
+ "https://opendata-esri-de.opendata.arcgis.com/datasets/5b203df4357844c8a6715d7d411a8341_0",
)
parser.add_argument(
"--plz-highlight",
required=True,
help="A JSON file with a list of PLZ (prefixes) that should be highlighted.",
)
parser.add_argument(
"--out",
required=True,
help="A .png file path where the generated image should be stored.",
)
parser.add_argument(
"--img-bg-color",
type=str,
default="#EDEFEB",
help="Color outside of the map, the image file background.",
)
parser.add_argument(
"--map-bg-color",
type=str,
default="#202020",
help="Color code for the background map, non highlighted areas.",
)
parser.add_argument(
"--map-accent-color",
type=str,
default="#EF7C21",
help="Color code for the highlighted areas on the map.",
)
args = parser.parse_args()
main(
plz_data_path=args.plz_data,
plz_prefixes_path=args.plz_highlight,
output_file_path=args.out,
map_background_color=args.map_bg_color,
map_accent_color=args.map_accent_color,
image_background_color=args.img_bg_color,
)

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requirements.txt Normal file
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geopandas==0.11.1
geoplot==0.5.1