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FIX: Raise for single row/column grids with nearest shading #32405

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Merged
QuLogic merged 1 commit into from
Oct 15, 2026
Merged

FIX: Raise for single row/column grids with nearest shading #32405

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44 changes: 24 additions & 20 deletions lib/matplotlib/axes/_axes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6535,6 +6535,15 @@ def _pcolorargs(self, funcname, *args, shading='auto', **kwargs):
' X (%d) and/or Y (%d); see help(%s)' % (
C.shape, Nx, Ny, funcname))
if shading == 'nearest':
if Nx == 1 or Ny == 1:

@jklymak jklymak Oct 10, 2026

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I think the error message could be confusing between number of dimensions and the length of the appropriate dimension. I think you need to refer to the size of the data array not X and Y.

@lucaznch lucaznch Oct 10, 2026

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I understand that it may be confusing. I pushed a new commit to make the message clearer and refer to the data array.

# If a coordinate array has a single cell center,
# its corresponding cell size cannot be determined
# from neighboring centers.
raise TypeError(f"C has shape ({nrows}, {ncols}) but "
"shading='nearest' requires at least two rows "
"and two columns. Please supply explicit cell "
"edges for X and Y and use shading='flat' "
f"with {funcname}.")
# grid is specified at the center, so define corners
# at the midpoints between the grid centers and then use the
# flat algorithm.
Expand All @@ -6543,26 +6552,21 @@ def _interp_grid(X, require_monotonicity=False):
# correctly, when expanding columns, the monotonicity of
# X coords needs to be checked. When expanding rows, the
# monotonicity of Y coords needs to be checked.
if np.shape(X)[1] > 1:
dX = np.diff(X, axis=1) * 0.5
if (require_monotonicity and
not (np.all(dX >= 0) or np.all(dX <= 0))):
_api.warn_external(
f"The input coordinates to {funcname} are "
"interpreted as cell centers, but are not "
"monotonically increasing or decreasing. "
"This may lead to incorrectly calculated cell "
"edges, in which case, please supply "
f"explicit cell edges to {funcname}.")

hstack = np.ma.hstack if np.ma.isMA(X) else np.hstack
X = hstack((X[:, [0]] - dX[:, [0]],
X[:, :-1] + dX,
X[:, [-1]] + dX[:, [-1]]))
else:
# This is just degenerate, but we can't reliably guess
# a dX if there is just one value.
X = np.hstack((X, X))
dX = np.diff(X, axis=1) * 0.5
if (require_monotonicity and
not (np.all(dX >= 0) or np.all(dX <= 0))):
_api.warn_external(

@jklymak jklymak Oct 10, 2026

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I'm not following why this had to change

@lucaznch lucaznch Oct 10, 2026

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With the new check for single row or single column grids with nearest shading, interp_grid() is guaranteed to handle coordinate arrays with at least two columns (therefore np.shape(X)[1] is always greater than one).

So it made sense to me to remove the else branch entirely (which handles arrays with one column) and remove the first conditional which will always be true.

f"The input coordinates to {funcname} are "
"interpreted as cell centers, but are not "
"monotonically increasing or decreasing. "
"This may lead to incorrectly calculated cell "
"edges, in which case, please supply "
f"explicit cell edges to {funcname}.")

hstack = np.ma.hstack if np.ma.isMA(X) else np.hstack
X = hstack((X[:, [0]] - dX[:, [0]],
X[:, :-1] + dX,
X[:, [-1]] + dX[:, [-1]]))
return X

if ncols == Nx:
Expand Down
12 changes: 12 additions & 0 deletions lib/matplotlib/tests/test_axes.py
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Expand Up @@ -1678,6 +1678,18 @@ def test_pcolorargs():
# bad grid warnings.
ax.pcolormesh(X+10*noise_X, Y+10*noise_Y, Z, shading='auto')
assert len(record) == 2
# Grid cannot contain a single row or single column for nearest shading.
x = [1, 2, 3]
y = [4]
Z = np.arange(3).reshape(1, 3)
with pytest.raises(TypeError):
ax.pcolormesh(Z, shading='nearest')
with pytest.raises(TypeError):
ax.pcolormesh(x, y, Z)
with pytest.raises(TypeError):
ax.pcolormesh(y, x, Z.T)
with pytest.raises(TypeError):
ax.pcolormesh(y, y, Z[:, [0]])


def test_pcolormesh_underflow_error():
Expand Down
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