This library provides transformations for 2d triangle meshes built on top of scipy.spatial.Delaunay and Triangle:
- Insert points (nodes) in an existing mesh, splitting any triangles
that points fall into.
- Meshes created this way might not be Delaunay, but any new connected set of triangles added will be Delaunay if viewed in isolation (without the pre-existing mesh).
- Extend a mesh outwards to include new points.
- The extension to the mesh will be a constrained delaunay.
- Calculate the boundary polygon of a mesh.
This library uses a similar data structure to the Triangles library above, but replaces numpy arrays with pandas dataframes, preserving any extra columns across operations. It also contains a plotting function similar to the one in the Triangle library, that supports color attributes for vertices as well as triangle faces.
In addition, EmeraldTriangles provides import and export functionality for
- LandXML (import and export, no extra columns)
- SQL (import and export, same supported databases as pandas)
- PyVista (Only export)
- VTK (only export)
as well as some data transforms
- Reprojection of coordinates using pyproj
- Spatial interpolation (Kriging) of data using scikit-gstat
- Sampling of data from a raster to triangulation vertices using RasterIO
- Sampling of data from a triangulation to new point locations (linear interpolation between vertices of the surrounding triangle)
Documentation is provided in the form of a jupyter notebook with example usages as well as in docstrings accesible with the python help() function.
Users have experience issues with using the setup.py develop option due to some strange behaviour from cython. Using pip instead seems to do this trick.