PR summary

This PR adds the centered-gouraud shading to Axes.pcolormesh. It is a variant of gouraud that adds support for grids that are one larger than the data in each dimension. In this situation, centered-gouraud automatically converts it to match the data by taking the centers of each quadrilateral, averaging its four corners, and then applies Gouraud shading.

• Why is this change necessary / what problem does it solve?

  pcolormesh with shading='gouraud' requires the grid to match the shape of the data. If the user is working with a grid one larger in each dimension and tries to use gouraud, a TypeError is raised. centered-gouraud solves this by allowing such grids without requiring users to reshape them.

• What is the reasoning for this implementation?

  Rather than modifying the existing gouraud shading, a new shading was added following a discussion with @timhoffm on the issue this PR addresses.

Example:

import matplotlib.pyplot as plt
import numpy as np

nrows = 3
ncols = 5
Z = np.arange(nrows * ncols).reshape(nrows, ncols)
x = np.arange(ncols + 1)
y = np.arange(nrows + 1)

fig, ax = plt.subplots()

ax.pcolormesh(x, y, Z, shading='flat')
ax.pcolormesh(x, y, Z, shading='gouraud') # doesn't work
ax.pcolormesh(x, y, Z, shading='centered-gouraud') # works

Closes #8422

AI Disclosure

I used AI tools to help proofread and improve the grammar of this PR description. The code logic and implementation are my own.

PR checklist

• "closes #0000" is in the body of the PR description to link the related issue
• new and changed code is tested
• Plotting related features are demonstrated in an example
• New Features and API Changes are noted with a directive and release note
• Documentation complies with general and docstring guidelines