The scripts used for cluster selection in the 2017-19 MLL Prevalance Study.
raster2points.py turns a raster of population counts into points at all locations > 0 and tags them with a district name from a complementary dataset.
Dependencies:
- rasterio
- fiona
- shapely
Random points were extracted from that dataset using QGIS (no point reinventing the wheel...)
html-output.py turns the results into a HTML list including links to startic Google Satellite images allowing pre-visit site assessment.
Usage:
python html-output.py > clusters.md && pandoc -s -c skeleton.css -o clusters.html clusters.md
Dependencies:
- geopandas
- shapely
- pyproj
This repository includes unmdified css from Skeleton