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[pyplot] Eliminate QuadMesh seams in pcolormesh/hist2d output

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@Alek99 is already working on this.

Since Jul 31, 2026.

  • #413 by @Alek99 — open

Assessment

Difficulty
4/5
Estimated time
3-5 days
Newbie friendliness
25/100
Issue type
Bug
Clarity
Clearly specified
Activity status
Stale
Tech stack
python
Domain
data-visualization

Research direction

Start with the implementation and regression gates in PR #413, then review the QuadMesh rendering path described in this issue. Check the 11 affected pcolormesh and hist2d gallery examples and their filled-vector visual gate. Done means no unintended shared-edge strokes, intentional edges still work, and all listed Matplotlib structure and gallery acceptance checks pass.

Written by the indexing model from the issue text.

Description

pyplot

Problem

The XY rasterizer used to stroke the shared edges of adjacent mesh cells. That produced visible grid seams in filled pcolormesh and hist2d output even when Matplotlib renders a continuous field.

This root cause directly affects 11 gallery examples using pcolormesh or hist2d, and can affect any downstream QuadMesh rendering.

Comparison

Matplotlib Corrected xy.pyplot
Matplotlib reference XY corrected
Before Difference
XY before Difference before the fix

The implementation and regression gates are in PR #413.

Complete upstream Matplotlib example

Source: scales/power_norm.py from the supplied Matplotlib 3.11.1 gallery archive.

"""
========================
Exploring normalizations
========================

Various normalization on a multivariate normal distribution.

"""

import matplotlib.pyplot as plt
import numpy as np
from numpy.random import multivariate_normal

import matplotlib.colors as mcolors

# Fixing random state for reproducibility.
np.random.seed(19680801)

data = np.vstack([
    multivariate_normal([10, 10], [[3, 2], [2, 3]], size=100000),
    multivariate_normal([30, 20], [[3, 1], [1, 3]], size=1000)
])

gammas = [0.8, 0.5, 0.3]

fig, axs = plt.subplots(nrows=2, ncols=2)

axs[0, 0].set_title('Linear normalization')
axs[0, 0].hist2d(data[:, 0], data[:, 1], bins=100)

for ax, gamma in zip(axs.flat[1:], gammas):
    ax.set_title(r'Power law $(\gamma=%1.1f)$' % gamma)
    ax.hist2d(data[:, 0], data[:, 1], bins=100, norm=mcolors.PowerNorm(gamma))

fig.tight_layout()

plt.show()

# %%
#
# .. admonition:: References
#
#    The use of the following functions, methods, classes and modules is shown
#    in this example:
#
#    - `matplotlib.colors`
#    - `matplotlib.colors.PowerNorm`
#    - `matplotlib.axes.Axes.hist2d`
#    - `matplotlib.pyplot.hist2d`

Acceptance

  • Adjacent mesh cells are filled without unintended boundary strokes.
  • Intentional user-specified edges remain supported.
  • Mesh geometry, normalization, colorbar, labels, and limits match the Matplotlib structure.
  • The filled-vector visual gate passes without a waiver or Matplotlib-renderer fallback.
  • All 11 directly affected gallery examples remain ratcheted green.
Dominant language
Python
Stars
1.9k
Forks
76
Avg merge
1h 25m
Merged PRs (30d)
5

Getting set up

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

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