8000 Merge pull request #29028 from Kaustbh/issue3 · matplotlib/matplotlib@9cc62f1 · GitHub
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Merge pull request #29028 from Kaustbh/issue3
Update colormap usage documentation to prioritize string colormap names
2 parents 48126ca + 191efce commit 9cc62f1

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‎doc/users/prev_whats_new/whats_new_3.10.0.rst

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@@ -56,9 +56,9 @@ colour maps version 8.0.1 (DOI: https://doi.org/10.5281/zenodo.1243862).
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img = np.sin(x*y)
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_, ax = plt.subplots(1, 3)
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ax[0].imshow(img, cmap=plt.cm.berlin)
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ax[1].imshow(img, cmap=plt.cm.managua)
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ax[2].imshow(img, cmap=plt.cm.vanimo)
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ax[0].imshow(img, cmap="berlin")
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ax[1].imshow(img, cmap="managua")
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ax[2].imshow(img, cmap="vanimo")
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‎galleries/examples/axisartist/demo_curvelinear_grid2.py

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@@ -41,7 +41,7 @@ def inv_tr(x, y):
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# itself (i.e., transData) is not affected by the given transform.
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ax1.imshow(np.arange(25).reshape(5, 5),
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vmax=50, cmap=plt.cm.gray_r, origin="lower")
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vmax=50, cmap="gray_r", origin="lower")
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if __name__ == "__main__":

‎galleries/examples/images_contours_and_fields/contour_demo.py

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@@ -13,8 +13,6 @@
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import matplotlib.pyplot as plt
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import numpy as np
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import matplotlib.cm as cm
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delta = 0.025
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x = np.arange(-3.0, 3.0, delta)
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y = np.arange(-2.0, 2.0, delta)
@@ -79,7 +77,7 @@
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fig, ax = plt.subplots()
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im = ax.imshow(Z, interpolation='bilinear', origin='lower',
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cmap=cm.gray, extent=(-3, 3, -2, 2))
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cmap="gray", extent=(-3, 3, -2, 2))
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levels = np.arange(-1.2, 1.6, 0.2)
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CS = ax.contour(Z, levels, origin='lower', cmap='flag', extend='both',
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linewidths=2, extent=(-3, 3, -2, 2))

‎galleries/examples/images_contours_and_fields/contour_image.py

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@@ -35,7 +35,7 @@
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levels = np.arange(-2.0, 1.601, 0.4)
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norm = cm.colors.Normalize(vmax=abs(Z).max(), vmin=-abs(Z).max())
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cmap = cm.PRGn
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cmap = plt.colormaps["PRGn"]
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fig, _axs = plt.subplots(nrows=2, ncols=2)
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fig.subplots_adjust(hspace=0.3)

‎galleries/examples/images_contours_and_fields/contourf_demo.py

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@@ -39,7 +39,7 @@
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# for purposes of illustration.
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fig1, ax2 = plt.subplots(layout='constrained')
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CS = ax2.contourf(X, Y, Z, 10, cmap=plt.cm.bone)
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CS = ax2.contourf(X, Y, Z, 10, cmap="bone")
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# Note that in the following, we explicitly pass in a subset of the contour
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# levels used for the filled contours. Alternatively, we could pass in

‎galleries/examples/images_contours_and_fields/contourf_log.py

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@@ -10,7 +10,7 @@
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import numpy as np
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from numpy import ma
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from matplotlib import cm, ticker
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from matplotlib import ticker
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N = 100
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x = np.linspace(-3.0, 3.0, N)
@@ -36,7 +36,7 @@
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# Automatic selection of levels works; setting the
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# log locator tells contourf to use a log scale:
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fig, ax = plt.subplots()
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cs = ax.contourf(X, Y, z, locator=ticker.LogLocator(), cmap=cm.PuBu_r)
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cs = ax.contourf(X, Y, z, locator=ticker.LogLocator(), cmap="PuBu_r")
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# Alternatively, you can manually set the levels
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# and the norm:

‎galleries/examples/images_contours_and_fields/image_demo.py

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@@ -12,7 +12,6 @@
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import numpy as np
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import matplotlib.cbook as cbook
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import matplotlib.cm as cm
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from matplotlib.patches import PathPatch
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from matplotlib.path import Path
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@@ -30,7 +29,7 @@
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Z = (Z1 - Z2) * 2
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fig, ax = plt.subplots()
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im = ax.imshow(Z, interpolation='bilinear', cmap=cm.RdYlBu,
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im = ax.imshow(Z, interpolation='bilinear', cmap="RdYlBu",
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origin='lower', extent=[-3, 3, -3, 3],
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vmax=abs(Z).max(), vmin=-abs(Z).max())
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@@ -58,7 +57,7 @@
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ax['hopper'].imshow(image)
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ax['hopper'].axis('off') # clear x-axis and y-axis
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im = ax['mri'].imshow(A, cmap=plt.cm.hot, origin='upper', extent=extent)
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im = ax['mri'].imshow(A, cmap="hot", origin='upper', extent=extent)
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markers = [(15.9, 14.5), (16.8, 15)]
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x, y = zip(*markers)
@@ -163,7 +162,7 @@
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fig, ax = plt.subplots()
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ax.add_patch(patch)
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166-
im = ax.imshow(Z, interpolation='bilinear', cmap=cm.gray,
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im = ax.imshow(Z, interpolation='bilinear', cmap="gray",
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origin='lower', extent=[-3, 3, -3, 3],
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clip_path=patch, clip_on=True)
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im.set_clip_path(patch)

‎galleries/examples/images_contours_and_fields/image_masked.py

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@@ -25,7 +25,7 @@
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Z = (Z1 - Z2) * 2
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# Set up a colormap:
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palette = plt.cm.gray.with_extremes(over='r', under='g', bad='b')
28+
palette = plt.colormaps["gray"].with_extremes(over='r', under='g', bad='b')
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# Alternatively, we could use
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# palette.set_bad(alpha = 0.0)
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# to make the bad region transparent. This is the default.

‎galleries/examples/images_contours_and_fields/image_nonuniform.py

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@@ -11,7 +11,6 @@
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import matplotlib.pyplot as plt
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import numpy as np
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from matplotlib import cm
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from matplotlib.image import NonUniformImage
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interp = 'nearest'
@@ -30,7 +29,7 @@
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fig.suptitle('NonUniformImage class', fontsize='large')
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ax = axs[0, 0]
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im = NonUniformImage(ax, interpolation=interp, extent=(-4, 4, -4, 4),
33-
cmap=cm.Purples)
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cmap="Purples")
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im.set_data(x, y, z)
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ax.add_image(im)
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ax.set_xlim(-4, 4)
@@ -39,7 +38,7 @@
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ax = axs[0, 1]
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im = NonUniformImage(ax, interpolation=interp, extent=(-64, 64, -4, 4),
42-
cmap=cm.Purples)
41+
cmap="Purples")
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im.set_data(x2, y, z)
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ax.add_image(im)
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ax.set_xlim(-64, 64)
@@ -50,7 +49,7 @@
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ax = axs[1, 0]
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im = NonUniformImage(ax, interpolation=interp, extent=(-4, 4, -4, 4),
53-
cmap=cm.Purples)
52+
cmap="Purples")
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im.set_data(x, y, z)
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ax.add_image(im)
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ax.set_xlim(-4, 4)
@@ -59,7 +58,7 @@
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ax = axs[1, 1]
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im = NonUniformImage(ax, interpolation=interp, extent=(-64, 64, -4, 4),
62-
cmap=cm.Purples)
61+
cmap="Purples")
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im.set_data(x2, y, z)
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ax.add_image(im)
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ax.set_xlim(-64, 64)

‎galleries/examples/images_contours_and_fields/layer_images.py

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@@ -31,12 +31,12 @@ def func3(x, y):
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fig = plt.figure(frameon=False)
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Z1 = np.add.outer(range(8), range(8)) % 2 # chessboard
34-
im1 = plt.imshow(Z1, cmap=plt.cm.gray, interpolation='nearest',
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im1 = plt.imshow(Z1, cmap="gray", interpolation='nearest',
3535
extent=extent)
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Z2 = func3(X, Y)
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39-
im2 = plt.imshow(Z2, cmap=plt.cm.viridis, alpha=.9, interpolation='bilinear',
39+
im2 = plt.imshow(Z2, cmap="viridis", alpha=.9, interpolation='bilinear',
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extent=extent)
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plt.show()

‎galleries/examples/images_contours_and_fields/shading_example.py

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@@ -25,10 +25,10 @@ def main():
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dem = cbook.get_sample_data('jacksboro_fault_dem.npz')
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elev = dem['elevation']
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28-
fig = compare(z, plt.cm.copper)
28+
fig = compare(z, plt.colormaps["copper"])
2929
fig.suptitle('HSV Blending Looks Best with Smooth Surfaces', y=0.95)
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31-
fig = compare(elev, plt.cm.gist_earth, ve=0.05)
31+
fig = compare(elev, plt.colormaps["gist_earth"], ve=0.05)
3232
fig.suptitle('Overlay Blending Looks Best with Rough Surfaces', y=0.95)
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plt.show()

‎galleries/examples/lines_bars_and_markers/gradient_bar.py

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@@ -56,15 +56,15 @@ def gradient_bar(ax, x, y, width=0.5, bottom=0):
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for left, top in zip(x, y):
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right = left + width
5858
gradient_image(ax, extent=(left, right, bottom, top),
59-
cmap=plt.cm.Blues_r, cmap_range=(0, 0.8))
59+
cmap="Blues_r", cmap_range=(0, 0.8))
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fig, ax = plt.subplots()
6363
ax.set(xlim=(0, 10), ylim=(0, 1))
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# background image
6666
gradient_image(ax, direction=1, extent=(0, 1, 0, 1), transform=ax.transAxes,
67-
cmap=plt.cm.RdYlGn, cmap_range=(0.2, 0.8), alpha=0.5)
67+
cmap="RdYlGn", cmap_range=(0.2, 0.8), alpha=0.5)
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N = 10
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x = np.arange(N) + 0.15

‎galleries/examples/lines_bars_and_markers/multivariate_marker_plot.py

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@@ -39,7 +39,7 @@
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t = Affine2D().scale(skill).rotate_deg(takeoff)
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m = MarkerStyle(SUCCESS_SYMBOLS[mood], transform=t)
4141
ax.plot(pos[0], pos[1], marker=m, color=cmap(thrust))
42-
fig.colorbar(plt.cm.ScalarMappable(norm=Normalize(0, 1), cmap=cmap),
42+
fig.colorbar(plt.cm.ScalarMappable(norm=Normalize(0, 1), cmap="plasma"),
4343
ax=ax, label="Normalized Thrust [a.u.]")
4444
ax.set_xlabel("X position [m]")
4545
ax.set_ylabel("Y position [m]")

‎galleries/examples/misc/contour_manual.py

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import matplotlib.pyplot as plt
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import matplotlib.cm as cm
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from matplotlib.contour import ContourSet
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from matplotlib.path import Path
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@@ -30,12 +29,12 @@
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fig, ax = plt.subplots()
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# Filled contours using filled=True.
33-
cs = ContourSet(ax, [0, 1, 2], [filled01, filled1 97AE 2], filled=True, cmap=cm.bone)
32+
cs = ContourSet(ax, [0, 1, 2], [filled01, filled12], filled=True, cmap="bone")
3433
cbar = fig.colorbar(cs)
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3635
# Contour lines (non-filled).
3736
lines = ContourSet(
38-
ax, [0, 1, 2], [lines0, lines1, lines2], cmap=cm.cool, linewidths=3)
37+
ax, [0, 1, 2], [lines0, lines1, lines2], cmap="cool", linewidths=3)
3938
cbar.add_lines(lines)
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ax.set(xlim=(-0.5, 3.5), ylim=(-0.5, 4.5),

‎galleries/examples/misc/demo_agg_filter.py

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import numpy as np
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from matplotlib.artist import Artist
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import matplotlib.cm as cm
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from matplotlib.colors import LightSource
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import matplotlib.transforms as mtransforms
2019

@@ -179,7 +178,7 @@ def filtered_text(ax):
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180179
# draw
181180
ax.imshow(Z, interpolation='bilinear', origin='lower',
182-
cmap=cm.gray, extent=(-3, 3, -2, 2), aspect='auto')
181+
cmap="gray", extent=(-3, 3, -2, 2), aspect='auto')
183182
levels = np.arange(-1.2, 1.6, 0.2)
184183
CS = ax.contour(Z, levels,
185184
origin='lower',

‎galleries/examples/misc/hyperlinks_sgskip.py

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import matplotlib.pyplot as plt
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import numpy as np
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import matplotlib.cm as cm
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# %%
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2018
fig = plt.figure()
@@ -32,7 +30,7 @@
3230
Z2 = np.exp(-(X - 1)**2 - (Y - 1)**2)
3331
Z = (Z1 - Z2) * 2
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35-
im = plt.imshow(Z, interpolation='bilinear', cmap=cm.gray,
33+
im = plt.imshow(Z, interpolation='bilinear', cmap="gray",
3634
origin='lower', extent=(-3, 3, -3, 3))
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3836
im.set_url('https://www.google.com/')

‎galleries/examples/misc/table_demo.py

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value_increment = 1000
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# Get some pastel shades for the colors
24-
colors = plt.cm.BuPu(np.linspace(0, 0.5, len(rows)))
24+
colors = plt.colormaps["BuPu"](np.linspace(0, 0.5, len(rows)))
2525
n_rows = len(data)
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2727
index = np.arange(len(columns)) + 0.3

‎galleries/examples/mplot3d/contour3d.py

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import matplotlib.pyplot as plt
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from matplotlib import cm
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from mpl_toolkits.mplot3d import axes3d
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1514
ax = plt.figure().add_subplot(projection='3d')
1615
X, Y, Z = axes3d.get_test_data(0.05)
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18-
ax.contour(X, Y, Z, cmap=cm.coolwarm) # Plot contour curves
17+
ax.contour(X, Y, Z, cmap="coolwarm") # Plot contour curves
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plt.show()
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‎galleries/examples/mplot3d/contour3d_2.py

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import matplotlib.pyplot as plt
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from matplotlib import cm
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from mpl_toolkits.mplot3d import axes3d
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1514
ax = plt.figure().add_subplot(projection='3d')
1615
X, Y, Z = axes3d.get_test_data(0.05)
17-
ax.contour(X, Y, Z, extend3d=True, cmap=cm.coolwarm)
16+
ax.contour(X, Y, Z, extend3d=True, cmap="coolwarm")
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plt.show()
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‎galleries/examples/mplot3d/contourf3d.py

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import matplotlib.pyplot as plt
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from matplotlib import cm
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from mpl_toolkits.mplot3d import axes3d
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1817
ax = plt.figure().add_subplot(projection='3d')
1918
X, Y, Z = axes3d.get_test_data(0.05)
20-
ax.contourf(X, Y, Z, cmap=cm.coolwarm)
19+
ax.contourf(X, Y, Z, cmap="coolwarm")
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plt.show()
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‎galleries/examples/mplot3d/custom_shaded_3d_surface.py

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import matplotlib.pyplot as plt
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import numpy as np
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from matplotlib import cbook, cm
12+
from matplotlib import cbook
1313
from matplotlib.colors import LightSource
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1515
# Load and format data
@@ -29,7 +29,7 @@
2929
ls = LightSource(270, 45)
3030
# To use a custom hillshading mode, override the built-in shading and pass
3131
# in the rgb colors of the shaded surface calculated from "shade".
32-
rgb = ls.shade(z, cmap=cm.gist_earth, vert_exag=0.1, blend_mode='soft')
32+
rgb = ls.shade(z, cmap=plt.colormaps["gist_earth"], vert_exag=0.1, blend_mode='soft')
3333
surf = ax.plot_surface(x, y, z, rstride=1, cstride=1, facecolors=rgb,
3434
linewidth=0, antialiased=False, shade=False)
3535

‎galleries/examples/mplot3d/subplot3d.py

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import matplotlib.pyplot as plt
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import numpy as np
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from matplotlib import cm
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from mpl_toolkits.mplot3d.axes3d import get_test_data
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1514
# set up a figure twice as wide as it is tall
@@ -27,7 +26,7 @@
2726
X, Y = np.meshgrid(X, Y)
2827
R = np.sqrt(X**2 + Y**2)
2928
Z = np.sin(R)
30-
surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.coolwarm,
29+
surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap="coolwarm",
3130
linewidth=0, antialiased=False)
3231
ax.set_zlim(-1.01, 1.01)
3332
fig.colorbar(surf, shrink=0.5, aspect=10)

‎galleries/examples/mplot3d/surface3d.py

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import matplotlib.pyplot as plt
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import numpy as np
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from matplotlib import cm
1716
from matplotlib.ticker import LinearLocator
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1918
fig, ax = plt.subplots(subplot_kw={"projection": "3d"})
@@ -26,7 +25,7 @@
2625
Z = np.sin(R)
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2827
# Plot the surface.
29-
surf = ax.plot_surface(X, Y, Z, cmap=cm.coolwarm,
28+
surf = ax.plot_surface(X, Y, Z, cmap="coolwarm",
3029
linewidth=0, antialiased=False)
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3231
# Customize the z axis.

‎galleries/examples/mplot3d/surface3d_radial.py

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X, Y = R*np.cos(P), R*np.sin(P)
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2828
# Plot the surface.
29-
ax.plot_surface(X, Y, Z, cmap=plt.cm.YlGnBu_r)
29+
ax.plot_surface(X, Y, Z, cmap="YlGnBu_r")
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# Tweak the limits and add latex math labels.
3232
ax.set_zlim(0, 1)

‎galleries/examples/mplot3d/tricontour3d.py

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< min_radius)
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3939
ax = plt.figure().add_subplot(projection='3d')
40-
ax.tricontour(triang, z, cmap=plt.cm.CMRmap)
40+
ax.tricontour(triang, z, cmap="CMRmap")
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4242
# Customize the view angle so it's easier to understand the plot.
4343
ax.view_init(elev=45.)

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