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Multivariate plotting in imshow, pcolor and pcolormesh#29221

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1ad6e44
MultiNorm class
trygvradAug 7, 2024
b00cf92
Multivariate plots for imshow, pcolor and pcolormesh
trygvradAug 7, 2024
7755c90
docstrings for multivariate plotting in imshow, pcolor and pcolormesh
trygvradJan 6, 2025
65f41c0
Additional tests for colors.MultiNorm
trygvradJan 6, 2025
5bab105
Incorporating feedback from @story645
trygvradFeb 3, 2025
63d606f
Fix for mouseover image data with a MultiNorm
trygvradFeb 5, 2025
5189e61
More feedback from @story645
trygvradFeb 8, 2025
86c46a4
updated test for im.format_cursor_data
trygvradFeb 20, 2025
e63aa3d
Apply suggestions from tacaswell
trygvradFeb 23, 2025
cbb1979
updated test image multivariate_imshow_alpha.png due to a fix for alp…
trygvradFeb 24, 2025
e1ee7dc
change call signature of colorizer._ensure_multivariate_data()
trygvradFeb 24, 2025
fa40bef
updated reference images in response to fix on main
trygvradApr 6, 2025
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1 change: 1 addition & 0 deletionsdoc/api/colors_api.rst
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Original file line numberDiff line numberDiff line change
Expand Up@@ -53,6 +53,7 @@ Multivariate Colormaps
BivarColormap
SegmentedBivarColormap
BivarColormapFromImage
MultivarColormap

Other classes
-------------
Expand Down
80 changes: 60 additions & 20 deletionslib/matplotlib/axes/_axes.py
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Expand Up@@ -5685,7 +5685,7 @@ def imshow(self, X, cmap=None, norm=None, *, aspect=None,
"""
Display data as an image, i.e., on a 2D regular raster.

The input may either be actual RGB(A) data, or 2Dscalardata, which
The input may either be actual RGB(A) data, or 2D data, which
will be rendered as a pseudocolor image. For displaying a grayscale
image, set up the colormapping using the parameters
``cmap='gray', vmin=0, vmax=255``.
Expand All@@ -5706,24 +5706,25 @@ def imshow(self, X, cmap=None, norm=None, *, aspect=None,
- (M, N): an image with scalar data. The values are mapped to
colors using normalization and a colormap. See parameters *norm*,
*cmap*, *vmin*, *vmax*.
- (K, M, N): multiple images with scalar data. Must be used
with a multivariate or bivariate colormap that supports K channels.
- (M, N, 3): an image with RGB values (0-1 float or 0-255 int).
- (M, N, 4): an image with RGBA values (0-1 float or 0-255 int),
i.e. including transparency.

The first two dimensions (M, N) define the rows and columns of
the image.
The dimensions M and N are the number of rows and columns of the image.

Out-of-range RGB(A) values are clipped.

%(cmap_doc)s
%(multi_cmap_doc)s

This parameter is ignored if *X* is RGB(A).

%(norm_doc)s
%(multi_norm_doc)s

This parameter is ignored if *X* is RGB(A).

%(vmin_vmax_doc)s
%(multi_vmin_vmax_doc)s

This parameter is ignored if *X* is RGB(A).

Expand DownExpand Up@@ -6062,9 +6063,10 @@ def pcolor(self, *args, shading=None, alpha=None, norm=None, cmap=None,

Parameters
----------
C : 2D array-like
C : 2D array-like or list of 2D array-like objects
The color-mapped values. Color-mapping is controlled by *cmap*,
*norm*, *vmin*, and *vmax*.
*norm*, *vmin*, and *vmax*. Multiple arrays are only supported
when a bivariate or mulivariate colormap is used, see *cmap*.

X, Y : array-like, optional
The coordinates of the corners of quadrilaterals of a pcolormesh::
Expand DownExpand Up@@ -6111,11 +6113,11 @@ def pcolor(self, *args, shading=None, alpha=None, norm=None, cmap=None,
See :doc:`/gallery/images_contours_and_fields/pcolormesh_grids`
for more description.

%(cmap_doc)s
%(multi_cmap_doc)s

%(norm_doc)s
%(multi_norm_doc)s

%(vmin_vmax_doc)s
%(multi_vmin_vmax_doc)s

%(colorizer_doc)s

Expand DownExpand Up@@ -6190,6 +6192,26 @@ def pcolor(self, *args, shading=None, alpha=None, norm=None, cmap=None,
if shading is None:
shading = mpl.rcParams['pcolor.shading']
shading = shading.lower()

mcolorizer.ColorizingArtist._check_exclusionary_keywords(colorizer,
vmin=vmin,
vmax=vmax)

# we need to get the colorizer object to know the number of
# n_variates that should exist in the array, we therefore get the
# colorizer here.
colorizer_obj = mcolorizer.ColorizingArtist._get_colorizer(norm=norm,
cmap=cmap,
colorizer=colorizer)
if colorizer_obj.norm.n_input > 1:
# Valid call signatures for pcolor are with args = (C) or args = (X, Y, C)
# If provided, _pcolorargs will check that X, Y and C have the same shape.
# Before this check, we need to convert C from shape (K, N, M), where K is
# the number of variates, to (N, M) with a data type with K fields.
data = mcolorizer._ensure_multivariate_data(args[-1],
colorizer_obj.norm.n_input)
args = (*args[:-1], data)

X, Y, C, shading = self._pcolorargs('pcolor', *args, shading=shading,
kwargs=kwargs)
linewidths = (0.25,)
Expand DownExpand Up@@ -6226,9 +6248,8 @@ def pcolor(self, *args, shading=None, alpha=None, norm=None, cmap=None,
coords = stack([X, Y], axis=-1)

collection = mcoll.PolyQuadMesh(
coords, array=C,cmap=cmap, norm=norm,colorizer=colorizer,
coords, array=C, colorizer=colorizer_obj,
alpha=alpha, **kwargs)
collection._check_exclusionary_keywords(colorizer, vmin=vmin, vmax=vmax)
collection._scale_norm(norm, vmin, vmax)

coords = coords.reshape(-1, 2) # flatten the grid structure; keep x, y
Expand DownExpand Up@@ -6266,12 +6287,13 @@ def pcolormesh(self, *args, alpha=None, norm=None, cmap=None, vmin=None,
- (M, N) or M*N: a mesh with scalar data. The values are mapped to
colors using normalization and a colormap. See parameters *norm*,
*cmap*, *vmin*, *vmax*.
- (K, M, N): multiple layers with scalar data. Must be used with
a multivariate or bivariate colormap. See *cmap*.
- (M, N, 3): an image with RGB values (0-1 float or 0-255 int).
- (M, N, 4): an image with RGBA values (0-1 float or 0-255 int),
i.e. including transparency.

The first two dimensions (M, N) define the rows and columns of
the mesh data.
Here M and N define the rows and columns of the mesh.

X, Y : array-like, optional
The coordinates of the corners of quadrilaterals of a pcolormesh::
Expand DownExpand Up@@ -6302,11 +6324,11 @@ def pcolormesh(self, *args, alpha=None, norm=None, cmap=None, vmin=None,
expanded as needed into the appropriate 2D arrays, making a
rectangular grid.

%(cmap_doc)s
%(multi_cmap_doc)s

%(norm_doc)s
%(multi_norm_doc)s

%(vmin_vmax_doc)s
%(multi_vmin_vmax_doc)s

%(colorizer_doc)s

Expand DownExpand Up@@ -6429,6 +6451,24 @@ def pcolormesh(self, *args, alpha=None, norm=None, cmap=None, vmin=None,
shading = mpl._val_or_rc(shading, 'pcolor.shading').lower()
kwargs.setdefault('edgecolors', 'none')

mcolorizer.ColorizingArtist._check_exclusionary_keywords(colorizer,
vmin=vmin,
vmax=vmax)
# we need to get the colorizer object to know the number of
# n_variates that should exist in the array, we therefore get the
# colorizer here.
colorizer_obj = mcolorizer.ColorizingArtist._get_colorizer(norm=norm,
cmap=cmap,
colorizer=colorizer)
if colorizer_obj.norm.n_input > 1:
# Valid call signatures for pcolor are with args = (C) or args = (X, Y, C)
# If provided, _pcolorargs will check that X, Y and C have the same shape.
# Before this check, we need to convert C from shape (K, N, M), where K is
# the number of variates, to (N, M) with a data type with K fields.
data = mcolorizer._ensure_multivariate_data(args[-1],
colorizer_obj.norm.n_input)
args = (*args[:-1], data)

X, Y, C, shading = self._pcolorargs('pcolormesh', *args,
shading=shading, kwargs=kwargs)
coords = np.stack([X, Y], axis=-1)
Expand All@@ -6437,8 +6477,8 @@ def pcolormesh(self, *args, alpha=None, norm=None, cmap=None, vmin=None,

collection = mcoll.QuadMesh(
coords, antialiased=antialiased, shading=shading,
array=C,cmap=cmap, norm=norm,colorizer=colorizer, alpha=alpha, **kwargs)
collection._check_exclusionary_keywords(colorizer, vmin=vmin, vmax=vmax)
array=C, colorizer=colorizer_obj,
alpha=alpha, **kwargs)
collection._scale_norm(norm, vmin, vmax)

coords = coords.reshape(-1, 2) # flatten the grid structure; keep x, y
Expand Down
12 changes: 11 additions & 1 deletionlib/matplotlib/cbook.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -690,7 +690,17 @@ def safe_masked_invalid(x, copy=False):
try:
xm = np.ma.masked_where(~(np.isfinite(x)), x, copy=False)
except TypeError:
return x
if len(x.dtype.descr) == 1:
return x
else:
# in case of a dtype with multiple fields:
try:
mask = np.empty(x.shape, dtype=np.dtype('bool, '*len(x.dtype.descr)))
for dd, dm in zip(x.dtype.descr, mask.dtype.descr):
mask[dm[0]] = ~(np.isfinite(x[dd[0]]))
xm = np.ma.array(x, mask=mask, copy=False)
except TypeError:
return x
return xm


Expand Down
29 changes: 0 additions & 29 deletionslib/matplotlib/cm.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -278,32 +278,3 @@ def get_cmap(name=None, lut=None):
return _colormaps[name]
else:
return _colormaps[name].resampled(lut)


def _ensure_cmap(cmap):
"""
Ensure that we have a `.Colormap` object.

For internal use to preserve type stability of errors.

Parameters
----------
cmap : None, str, Colormap

- if a `Colormap`, return it
- if a string, look it up in mpl.colormaps
- if None, look up the default color map in mpl.colormaps

Returns
-------
Colormap

"""
if isinstance(cmap, colors.Colormap):
return cmap
cmap_name = mpl._val_or_rc(cmap, "image.cmap")
# use check_in_list to ensure type stability of the exception raised by
# the internal usage of this (ValueError vs KeyError)
if cmap_name not in _colormaps:
_api.check_in_list(sorted(_colormaps), cmap=cmap_name)
return mpl.colormaps[cmap_name]
8 changes: 7 additions & 1 deletionlib/matplotlib/collections.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -2611,10 +2611,16 @@ def _get_unmasked_polys(self):
arr = self.get_array()
if arr is not None:
arr = np.ma.getmaskarray(arr)
if arr.ndim == 3:
if self.norm.n_input > 1:
# multivar case
for a in mcolors.MultiNorm._iterable_variates_in_data(
arr, self.norm.n_input):
mask |= np.any(a, axis=0)
elif arr.ndim == 3:
# RGB(A) case
mask |= np.any(arr, axis=-1)
elif arr.ndim == 2:
# scalar case
mask |= arr
else:
mask |= arr.reshape(self._coordinates[:-1, :-1, :].shape[:2])
Expand Down
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