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Add a helper to copy a colormap and set its extreme colors.#14645

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Merged
timhoffm merged 1 commit intomatplotlib:masterfromanntzer:with_extremes
Oct 22, 2020
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13 changes: 13 additions & 0 deletionsdoc/users/next_whats_new/2019-06-28-AL.rst
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@@ -0,0 +1,13 @@
`.Colormap.set_extremes` and `.Colormap.with_extremes`
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I think we've decided not to put links in section titles for aestethic reasons.

But I'm going to merge as is. I'll anyway do a small colormap-related cleanup PR and will update there. While that's a bit of a messy way of working it saves us an extra review roundtrip here.

``````````````````````````````````````````````````````

Because the `.Colormap.set_bad`, `.Colormap.set_under` and `.Colormap.set_over`
methods modify the colormap in place, the user must be careful to first make a
copy of the colormap if setting the extreme colors e.g. for a builtin colormap.

The new ``Colormap.with_extremes(bad=..., under=..., over=...)`` can be used to
first copy the colormap and set the extreme colors on that copy.

The new `.Colormap.set_extremes` method is provided for API symmetry with
`.Colormap.with_extremes`, but note that it suffers from the same issue as the
earlier individual setters.
7 changes: 1 addition & 6 deletionsexamples/images_contours_and_fields/image_masked.py
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Expand Up@@ -8,7 +8,6 @@
The second subplot illustrates the use of BoundaryNorm to
get a filled contour effect.
"""
from copy import copy

import numpy as np
import matplotlib.pyplot as plt
Expand All@@ -25,11 +24,7 @@
Z = (Z1 - Z2) * 2

# Set up a colormap:
# use copy so that we do not mutate the global colormap instance
palette = copy(plt.cm.gray)
palette.set_over('r', 1.0)
palette.set_under('g', 1.0)
palette.set_bad('b', 1.0)
palette = plt.cm.gray.with_extremes(over='r', under='g', bad='b')
# Alternatively, we could use
# palette.set_bad(alpha = 0.0)
# to make the bad region transparent. This is the default.
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8 changes: 2 additions & 6 deletionsexamples/images_contours_and_fields/quadmesh_demo.py
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Expand Up@@ -9,8 +9,6 @@
This demo illustrates a bug in quadmesh with masked data.
"""

import copy

from matplotlib import cm, pyplot as plt
import numpy as np

Expand All@@ -30,10 +28,8 @@
axs[0].pcolormesh(Qx, Qz, Z, shading='gouraud')
axs[0].set_title('Without masked values')

# You can control the color of the masked region. We copy the default colormap
# before modifying it.
cmap = copy.copy(cm.get_cmap(plt.rcParams['image.cmap']))
cmap.set_bad('y', 1.0)
# You can control the color of the masked region.
cmap = cm.get_cmap(plt.rcParams['image.cmap']).with_extremes(bad='y')
axs[1].pcolormesh(Qx, Qz, Zm, shading='gouraud', cmap=cmap)
axs[1].set_title('With masked values')

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5 changes: 2 additions & 3 deletionsexamples/specialty_plots/leftventricle_bulleye.py
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Expand Up@@ -162,9 +162,8 @@ def bullseye_plot(ax, data, seg_bold=None, cmap=None, norm=None):
# The second example illustrates the use of a ListedColormap, a
# BoundaryNorm, and extended ends to show the "over" and "under"
# value colors.
cmap3 = mpl.colors.ListedColormap(['r', 'g', 'b', 'c'])
cmap3.set_over('0.35')
cmap3.set_under('0.75')
cmap3 = (mpl.colors.ListedColormap(['r', 'g', 'b', 'c'])
.with_extremes(over='0.35', under='0.75'))
# If a ListedColormap is used, the length of the bounds array must be
# one greater than the length of the color list. The bounds must be
# monotonically increasing.
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23 changes: 23 additions & 0 deletionslib/matplotlib/colors.py
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Expand Up@@ -67,6 +67,7 @@

import base64
from collections.abc import Sized
import copy
import functools
import inspect
import io
Expand DownExpand Up@@ -687,6 +688,28 @@ def set_over(self, color='k', alpha=None):
if self._isinit:
self._set_extremes()

def set_extremes(self, *, bad=None, under=None, over=None):
"""
Set the colors for masked (*bad*) values and, when ``norm.clip =
False``, low (*under*) and high (*over*) out-of-range values.
"""
if bad is not None:
self.set_bad(bad)
if under is not None:
self.set_under(under)
if over is not None:
self.set_over(over)

def with_extremes(self, *, bad=None, under=None, over=None):
"""
Return a copy of the colormap, for which the colors for masked (*bad*)
values and, when ``norm.clip = False``, low (*under*) and high (*over*)
out-of-range values, have been set accordingly.
"""
new_cm = copy.copy(self)
new_cm.set_extremes(bad=bad, under=under, over=over)
return new_cm

def _set_extremes(self):
if self._rgba_under:
self._lut[self._i_under] = self._rgba_under
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10 changes: 2 additions & 8 deletionslib/matplotlib/tests/test_image.py
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Expand Up@@ -799,10 +799,7 @@ def test_mask_image_over_under():
(2 * np.pi * 0.5 * 1.5))
Z = 10*(Z2 - Z1) # difference of Gaussians

palette = copy(plt.cm.gray)
palette.set_over('r', 1.0)
palette.set_under('g', 1.0)
palette.set_bad('b', 1.0)
palette = plt.cm.gray.with_extremes(over='r', under='g', bad='b')
Zm = np.ma.masked_where(Z > 1.2, Z)
fig, (ax1, ax2) = plt.subplots(1, 2)
im = ax1.imshow(Zm, interpolation='bilinear',
Expand DownExpand Up@@ -868,10 +865,7 @@ def test_imshow_endianess():
remove_text=True, style='mpl20')
def test_imshow_masked_interpolation():

cm = copy(plt.get_cmap('viridis'))
cm.set_over('r')
cm.set_under('b')
cm.set_bad('k')
cm = plt.get_cmap('viridis').with_extremes(over='r', under='b', bad='k')

N = 20
n = colors.Normalize(vmin=0, vmax=N*N-1)
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11 changes: 4 additions & 7 deletionstutorials/colors/colorbar_only.py
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Expand Up@@ -86,9 +86,8 @@
fig, ax = plt.subplots(figsize=(6, 1))
fig.subplots_adjust(bottom=0.5)

cmap = mpl.colors.ListedColormap(['red', 'green', 'blue', 'cyan'])
cmap.set_over('0.25')
cmap.set_under('0.75')
cmap = (mpl.colors.ListedColormap(['red', 'green', 'blue', 'cyan'])
.with_extremes(over='0.25', under='0.75'))

bounds = [1, 2, 4, 7, 8]
norm = mpl.colors.BoundaryNorm(bounds, cmap.N)
Expand All@@ -114,10 +113,8 @@
fig, ax = plt.subplots(figsize=(6, 1))
fig.subplots_adjust(bottom=0.5)

cmap = mpl.colors.ListedColormap(['royalblue', 'cyan',
'yellow', 'orange'])
cmap.set_over('red')
cmap.set_under('blue')
cmap = (mpl.colors.ListedColormap(['royalblue', 'cyan', 'yellow', 'orange'])
.with_extremes(over='red', under='blue'))

bounds = [-1.0, -0.5, 0.0, 0.5, 1.0]
norm = mpl.colors.BoundaryNorm(bounds, cmap.N)
Expand Down
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