pandamesh 0.2.3

This package translates geospatial vector data (points, lines, or polygons) to unstructured meshes.

import pandamesh as pm

# Get some sample data in geopandas form.
south_america = pm.data.south_america()

# Explode any multi-polygon, and project it to UTM20.
south_america = south_america.explode(index_parts=True).reset_index().to_crs(epsg=32620)

# Set a maximum cell size of 500 km and generate a mesh.
south_america["cellsize"] = 500_000.0
mesher = pm.TriangleMesher(south_america)
vertices, faces = mesher.generate()

The package converts geospatial data, presented as geopandas GeoDataFrames, to unstructured meshes using the open source high quality mesh generators:

• Christophe Geuzaine and Jean-François Remacle’s Gmsh

• Jonathan Shewchuk’s Triangle

utilizing the respective Python API’s, available at:

• https://pypi.org/project/gmsh/

• https://pypi.org/project/triangle/

For completeness, the source code of both projects can be found at:

• https://gitlab.onelab.info/gmsh/gmsh, under api/gmsh.py

• https://github.com/drufat/triangle

These APIs are wrapped in two lightweight classes: pandamesh.TriangleMesher and pandamesh.GmshMesher. Both are initialized with a GeoDataFrame defining the geometry features of the mesh. During initialization, geometries are checked for overlaps and intersections, as the mesh generators cannot deal with these. Generated meshes are returned as two numpy arrays: the coordinates of the vertices, and the connectivity of the mesh faces to these vertices (as is usual for many unstructured grid representations).

GeoPandas is not suited for geometries that “wrap around” the world. Consequently, this package cannot generate meshes for e.g. a sphere.

pip install pandamesh

Documentation

The documentation can be found here.