Stripy 2.0 released

Stripy 2.0 released

Published on

We've been busy creating the next major release of Stripy. To refresh your memory, Stripy is a Python tool for triangulating scattered points either in Cartesian coordinates or on the sphere. It wraps a bunch of Fortran codes in a neat, object-oriented Python interface that can be used for many geographical applications.

What's new?

Spline tension - a lot of data transformations in Stripy are underpinned by cubic splines (e.g. interpolation, derivatives, smoothing). In v2.0 you can now add spline tension which avoids overshoot / undershoot artefacts. The most visible improvements are in accuracy of derivatives at points along the boundary and extrapolation of data beyond the boundary of a mesh.

Difference between derivatives evaluated at the poles with spline tension vs. without. Looks like a beautiful flower. (Graphic generated with LavaVu).

Voronoi diagram - the Voronoi diagram is the dual of a Delaunay triangulation. For every triangle in the mesh, there is a voronoi point which lies at an equal radius from each node. The diagram is constructed by connecting up the voronoi points from each neighbouring triangle.

Voronoi diagram on the sphere. Graphic generated with Matplotlib and Cartopy.

Other notable new features include:

  • a new equispaced elliptical mesh in Cartesian coordinates
  • central area node weights for any mesh
  • efficient evaluation of second derivatives in Cartesian coordinates
  • better documentation, LGPLv3 license, and other small bug fixes

You can install the latest release of Stripy with pip

pip install stripy

or Conda:

conda install -c underworldcode stripy

Make Stripy better!

We welcome contributions to the code. If you want to add something you think is missing in Stripy, submit a pull request and if it looks good we'll merge your changes. Check out our contribution guidelines for more details.

Written by

Postdoc in the EarthByte Group at Sydney Uni
More posts by Ben Mather.


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