Iris’ Mesh Partner Packages#

Python is an easy to use language and has formed a very strong collaborative scientific community, which is why Iris is written in Python. Performant Python relies on calls down to low level languages like C, which is ideal for structured grid work since they can be directly represented as NumPy arrays. This is more difficult when working with unstructured meshes where extra steps are needed to determine data position (see the data model detail), and we need to find ways of again passing the operations down to more optimised languages.

The Iris team are therefore developing ‘wrapper’ packages, which make it quick and easy to analyse Iris mesh data via some popular Python packages that use powerful tools under the hood, working in C and other languages.

These solutions have been placed in their own ‘partner packages’ for several reasons:

  • Can be useful to others who are not using Iris.

    • Everyone working with multi-dimensional geographic datasets shares common problems that need solving.

    • Wider user base = stronger community = better solutions.

  • Only some Iris users will need them - they are optional Iris dependencies.

    • They introduce a lot of new API.

    • They introduce new large dependencies that take time to install and need disk space.

Below you can learn more about the partner packages and how they are useful. Specifics of what operations would require their installation can be found in: Working with Mesh Data.



As with Iris’ mesh support, these packages are still in the experimental stages. They would love your feedback, but as immature packages their API, documentation, test coverage and CI are still ‘under construction’.



“Cartographic rendering and mesh analytics powered by PyVista

PyVista is described as “VTK for humans” - VTK is a very powerful toolkit for working with meshes, and PyVista brings that power into the Python ecosystem. GeoVista in turn makes it easy to use PyVista specifically for cartographic work, designed from the start with the Iris Mesh in mind.


  • Interactively plot mesh data:

    • On a 3D globe.

    • On your favourite projection.

  • Extract a specific region from a mesh.

  • Combine multiple meshes into one.



“A collection of structured and unstructured ESMF regridding schemes for Iris”

ESMF provide a sophisticated, performant regridding utility that supports a variety of regridding types with both structured grids and unstructured meshes, and this also has a flexible Python interface - ESMPy. iris-esmf-regrid takes advantage of having a specific use-case - regridding Iris Cubes - to provide ESMPy-Iris wrappers that make the process as easy as possible, with highly optimised performance.


  • Regrid structured to unstructured.

  • Regrid unstructured to structured.

  • Regrid with dask integration, computing in parallel and maintaining data laziness.

  • Save a prepared regridder for reuse in subsequent runs.
    Regridders can even be re-used on sources with different masks - a significant efficiency gain.