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Cmap cleanup #18792

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Oct 23, 2020
Merged

Cmap cleanup #18792

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d9a1e54
Don't use links in titles
timhoffm Oct 22, 2020
55bba4b
Use 'cmap' as a canonical variable name for a colormap, not 'cm'
timhoffm Oct 22, 2020
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4 changes: 2 additions & 2 deletions doc/users/next_whats_new/2019-06-28-AL.rst
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Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
`.Colormap.set_extremes` and `.Colormap.with_extremes`
``````````````````````````````````````````````````````
``Colormap.set_extremes`` and ``Colormap.with_extremes``
````````````````````````````````````````````````````````

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
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4 changes: 2 additions & 2 deletions examples/color/custom_cmap.py
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Expand Up @@ -90,9 +90,9 @@
fig.subplots_adjust(left=0.02, bottom=0.06, right=0.95, top=0.94, wspace=0.05)
for n_bin, ax in zip(n_bins, axs.ravel()):
# Create the colormap
cm = LinearSegmentedColormap.from_list(cmap_name, colors, N=n_bin)
cmap = LinearSegmentedColormap.from_list(cmap_name, colors, N=n_bin)
# Fewer bins will result in "coarser" colomap interpolation
im = ax.imshow(Z, origin='lower', cmap=cm)
im = ax.imshow(Z, origin='lower', cmap=cmap)
ax.set_title("N bins: %s" % n_bin)
fig.colorbar(im, ax=ax)

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8 changes: 4 additions & 4 deletions examples/subplots_axes_and_figures/colorbar_placement.py
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Expand Up @@ -16,12 +16,12 @@
np.random.seed(19680801)

fig, axs = plt.subplots(2, 2)
cm = ['RdBu_r', 'viridis']
cmaps = ['RdBu_r', 'viridis']
for col in range(2):
for row in range(2):
ax = axs[row, col]
pcm = ax.pcolormesh(np.random.random((20, 20)) * (col + 1),
cmap=cm[col])
cmap=cmaps[col])
fig.colorbar(pcm, ax=ax)
plt.show()

Expand All @@ -31,12 +31,12 @@
# `.Figure.colorbar` with a list of axes instead of a single axes.

fig, axs = plt.subplots(2, 2)
cm = ['RdBu_r', 'viridis']
cmaps = ['RdBu_r', 'viridis']
for col in range(2):
for row in range(2):
ax = axs[row, col]
pcm = ax.pcolormesh(np.random.random((20, 20)) * (col + 1),
cmap=cm[col])
cmap=cmaps[col])
fig.colorbar(pcm, ax=axs[:, col], shrink=0.6)
plt.show()

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16 changes: 8 additions & 8 deletions lib/matplotlib/tests/test_colors.py
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Expand Up @@ -132,22 +132,22 @@ def test_colormap_dict_deprecate():
# Make sure we warn on get and set access into cmap_d
with pytest.warns(cbook.MatplotlibDeprecationWarning,
match="The global colormaps dictionary is no longer"):
cm = plt.cm.cmap_d['viridis']
cmap = plt.cm.cmap_d['viridis']

with pytest.warns(cbook.MatplotlibDeprecationWarning,
match="The global colormaps dictionary is no longer"):
plt.cm.cmap_d['test'] = cm
plt.cm.cmap_d['test'] = cmap


def test_colormap_copy():
cm = plt.cm.Reds
cm_copy = copy.copy(cm)
cmap = plt.cm.Reds
copied_cmap = copy.copy(cmap)
with np.errstate(invalid='ignore'):
ret1 = cm_copy([-1, 0, .5, 1, np.nan, np.inf])
cm2 = copy.copy(cm_copy)
cm2.set_bad('g')
ret1 = copied_cmap([-1, 0, .5, 1, np.nan, np.inf])
cmap2 = copy.copy(copied_cmap)
cmap2.set_bad('g')
with np.errstate(invalid='ignore'):
ret2 = cm_copy([-1, 0, .5, 1, np.nan, np.inf])
ret2 = copied_cmap([-1, 0, .5, 1, np.nan, np.inf])
assert_array_equal(ret1, ret2)


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10 changes: 5 additions & 5 deletions lib/matplotlib/tests/test_image.py
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Expand Up @@ -865,7 +865,7 @@ def test_imshow_endianess():
remove_text=True, style='mpl20')
def test_imshow_masked_interpolation():

cm = plt.get_cmap('viridis').with_extremes(over='r', under='b', bad='k')
cmap = plt.get_cmap('viridis').with_extremes(over='r', under='b', bad='k')

N = 20
n = colors.Normalize(vmin=0, vmax=N*N-1)
Expand All @@ -892,7 +892,7 @@ def test_imshow_masked_interpolation():

for interp, ax in zip(interps, ax_grid.ravel()):
ax.set_title(interp)
ax.imshow(data, norm=n, cmap=cm, interpolation=interp)
ax.imshow(data, norm=n, cmap=cmap, interpolation=interp)
ax.axis('off')


Expand Down Expand Up @@ -1213,8 +1213,8 @@ def test_huge_range_log(fig_test, fig_ref):
data = np.full((5, 5), -1, dtype=np.float64)
data[0:2, :] = 1000

cm = copy(plt.get_cmap('viridis'))
cm.set_under('w')
cmap = copy(plt.get_cmap('viridis'))
cmap.set_under('w')
ax = fig_ref.subplots()
im = ax.imshow(data, norm=colors.Normalize(vmin=100, vmax=data.max()),
interpolation='nearest', cmap=cm)
interpolation='nearest', cmap=cmap)