Sep 23, 2021 · Sep 23, 2021
diff --git a/doc/sphinxext/gallery_order.py b/doc/sphinxext/gallery_order.py
    # Basic
    "plot", "scatter_plot", "bar", "stem", "step", "pie", "fill_between",
    # Arrays
    "imshow", "pcolormesh", "contourf", "quiver", "streamplot",
    "imshow", "pcolormesh", "contour", "contourf", "quiver", "streamplot",
    # Stats
    "hist_plot", "boxplot_plot", "errorbar_plot", "violin",
    "barbs", "eventplot", "hist2d", "hexbin",
    # Unstructured
    "tricontour", "tripcolor", "triplot",
    "tricontour", "tricontourf", "tripcolor", "triplot",
    ]
 explicit_subsection_order = [item + ".py" for item in list_all]

diff --git a/lib/matplotlib/mpl-data/stylelib/_mpl-gallery-nogrid.mplstyle b/lib/matplotlib/mpl-data/stylelib/_mpl-gallery-nogrid.mplstyle
 # This style is used for the plot_types gallery. It is considered private.

 axes.grid: False
 axes.axisbelow: True

 figure.figsize: 2, 2
 # make it so the axes labels don't show up.  Obviously
 # not good style for any quantitative analysis:
 figure.subplot.left: 0.01
 figure.subplot.right: 0.99
 figure.subplot.bottom: 0.01
 figure.subplot.top: 0.99

 xtick.major.size: 0.0
 ytick.major.size: 0.0

 # colors:
 image.cmap    : Blues
 # axes.prop_cycle: cycler('color', ['FF7F0E', '1F77B4', '2CA02C'])
diff --git a/...l-data/stylelib/mpl_plot_gallery.mplstyle → ...b/mpl-data/stylelib/_mpl-gallery.mplstyle b/...l-data/stylelib/mpl_plot_gallery.mplstyle → ...b/mpl-data/stylelib/_mpl-gallery.mplstyle
 #fromtheMatplotlib cheatsheet as used in our gallery:
 #This style is used fortheplot_types gallery. It is considered part of the private API.

 axes.grid: True
 axes.axisbelow: True
diff --git a/plot_types/arrays/contour.py b/plot_types/arrays/contour.py
 importmatplotlib.pyplotasplt
 importnumpyasnp

 plt.style.use('mpl_plot_gallery')
 plt.style.use('_mpl-gallery-nogrid')

 # make data
 X,Y=np.meshgrid(np.linspace(-3,3,256),np.linspace(-3,3,256))

 # plot
 fig,ax=plt.subplots()
 ax.grid(False)

 ax.contour(X,Y,Z,levels=levels)

diff --git a/plot_types/arrays/contourf.py b/plot_types/arrays/contourf.py
 importmatplotlib.pyplotasplt
 importnumpyasnp

 plt.style.use('mpl_plot_gallery')
 plt.style.use('_mpl-gallery-nogrid')

 # make data
 X,Y=np.meshgrid(np.linspace(-3,3,256),np.linspace(-3,3,256))
diff --git a/plot_types/arrays/imshow.py b/plot_types/arrays/imshow.py
 import matplotlib.pyplot as plt
 import numpy as np

 plt.style.use('mpl_plot_gallery')
 plt.style.use('_mpl-gallery-nogrid')

 # make data
 X, Y = np.meshgrid(np.linspace(-3, 3, 256), np.linspace(-3, 3, 256))
 Z = (1 - X/2. + X**5 + Y**3) * np.exp(-X**2 - Y**2)
 Z = (1 - X/2 + X**5 + Y**3) * np.exp(-X**2 - Y**2)
 Z = Z[::16, ::16]

 # plot
 fig, ax = plt.subplots()
 ax.grid(False)

 ax.imshow(Z)

diff --git a/plot_types/arrays/pcolormesh.py b/plot_types/arrays/pcolormesh.py
 import matplotlib.pyplot as plt
 import numpy as np

 plt.style.use('mpl_plot_gallery')
 plt.style.use('_mpl-gallery-nogrid')

 # make full-res data
 X, Y = np.meshgrid(np.linspace(-3, 3, 256), np.linspace(-3, 3, 256))
 Z = (1 - X/2. + X**5 + Y**3) * np.exp(-X**2 - Y**2)
 Z = (1 - X/2 + X**5 + Y**3) * np.exp(-X**2 - Y**2)

 # sample unevenly in x:
 dx = np.sqrt((np.arange(16) - 8)**2) + 6

 # plot
 fig, ax = plt.subplots()
 ax.grid(False)

 ax.pcolormesh(X, Y, Z, vmin=-0.5, vmax=1.0)

diff --git a/plot_types/arrays/quiver.py b/plot_types/arrays/quiver.py
 importmatplotlib.pyplotasplt
 importnumpyasnp

 plt.style.use('mpl_plot_gallery')
 plt.style.use('_mpl-gallery')

 # make data
 phi=np.linspace(0,2*np.pi,8)
diff --git a/plot_types/arrays/streamplot.py b/plot_types/arrays/streamplot.py
 import matplotlib.pyplot as plt
 import numpy as np

 plt.style.use('mpl_plot_gallery')
 plt.style.use('_mpl-gallery-nogrid')

 # make a stream function:
 X, Y = np.meshgrid(np.linspace(-3, 3, 256), np.linspace(-3, 3, 256))
 Z = (1 - X/2. + X**5 + Y**3) * np.exp(-X**2 - Y**2)
 Z = (1 - X/2 + X**5 + Y**3) * np.exp(-X**2 - Y**2)
 # make U and V out of the streamfunction:
 V = np.diff(Z[1:, :], axis=1)
 U = -np.diff(Z[:, 1:], axis=0)

 # plot:
 fig, ax = plt.subplots()
 ax.grid(False)

 # plot stream plot
 ax.streamplot(X[1:, 1:], Y[1:, 1:], U, V)

 plt.show()
diff --git a/plot_types/basic/bar.py b/plot_types/basic/bar.py
 """
 import matplotlib.pyplot as plt
 import numpy as np
 plt.style.use('mpl_plot_gallery')
 plt.style.use('_mpl-gallery')

 # make data:
 np.random.seed(3)
diff --git a/plot_types/basic/pie.py b/plot_types/basic/pie.py
 importmatplotlib.pyplotasplt
 importnumpyasnp

 plt.style.use('mpl_plot_gallery')
 plt.style.use('_mpl-gallery-nogrid')


 # make data
diff --git a/plot_types/basic/plot.py b/plot_types/basic/plot.py
 importmatplotlib.pyplotasplt
 importnumpyasnp

 plt.style.use('mpl_plot_gallery')
 plt.style.use('_mpl-gallery')

 # make data
 x=np.linspace(0,10,100)
diff --git a/plot_types/basic/scatter_plot.py b/plot_types/basic/scatter_plot.py
 import matplotlib.pyplot as plt
 import numpy as np

 plt.style.use('mpl_plot_gallery')
 plt.style.use('_mpl-gallery')

 # make the data
 np.random.seed(3)
diff --git a/plot_types/basic/stem.py b/plot_types/basic/stem.py
 import matplotlib.pyplot as plt
 import numpy as np

 plt.style.use('mpl_plot_gallery')
 plt.style.use('_mpl-gallery')

 # make data
 np.random.seed(3)
diff --git a/plot_types/basic/step.py b/plot_types/basic/step.py
 importmatplotlib.pyplotasplt
 importnumpyasnp

 plt.style.use('mpl_plot_gallery')
 plt.style.use('_mpl-gallery')

 # make data
 np.random.seed(3)
diff --git a/plot_types/stats/barbs.py b/plot_types/stats/barbs.py
 importmatplotlib.pyplotasplt
 importnumpyasnp

 plt.style.use('mpl_plot_gallery')
 plt.style.use('_mpl-gallery')

 # make data:
 np.random.seed(1)
diff --git a/plot_types/stats/boxplot_plot.py b/plot_types/stats/boxplot_plot.py
 importmatplotlib.pyplotasplt
 importnumpyasnp

 plt.style.use('mpl_plot_gallery')
 plt.style.use('_mpl-gallery')

 # make data:
 np.random.seed(10)
diff --git a/plot_types/stats/errorbar_plot.py b/plot_types/stats/errorbar_plot.py
 import matplotlib.pyplot as plt
 import numpy as np

 plt.style.use('mpl_plot_gallery')
 plt.style.use('_mpl-gallery')

 # make data:
 np.random.seed(1)
diff --git a/plot_types/stats/eventplot.py b/plot_types/stats/eventplot.py
 import matplotlib.pyplot as plt
 import numpy as np

 plt.style.use('mpl_plot_gallery')
 plt.style.use('_mpl-gallery')

 # make data:
 np.random.seed(1)
diff --git a/plot_types/stats/hexbin.py b/plot_types/stats/hexbin.py
 import matplotlib.pyplot as plt
 import numpy as np

 plt.style.use('mpl_plot_gallery')
 plt.style.use('_mpl-gallery-nogrid')

 # make data: correlated + noise
 np.random.seed(1)
diff --git a/plot_types/stats/hist2d.py b/plot_types/stats/hist2d.py
 import matplotlib.pyplot as plt
 import numpy as np

 plt.style.use('mpl_plot_gallery')
 plt.style.use('_mpl-gallery-nogrid')

 # make data: correlated + noise
 np.random.seed(1)
diff --git a/plot_types/stats/hist_plot.py b/plot_types/stats/hist_plot.py
 import matplotlib.pyplot as plt
 import numpy as np

 plt.style.use('mpl_plot_gallery')
 plt.style.use('_mpl-gallery')

 # make data
 np.random.seed(1)
diff --git a/plot_types/stats/violin.py b/plot_types/stats/violin.py
 import matplotlib.pyplot as plt
 import numpy as np

 plt.style.use('mpl_plot_gallery')
 plt.style.use('_mpl-gallery')

 # make data:
 np.random.seed(10)
diff --git a/plot_types/unstructured/tricontour.py b/plot_types/unstructured/tricontour.py
 import matplotlib.pyplot as plt
 import numpy as np

 plt.style.use('mpl_plot_gallery')
 plt.style.use('_mpl-gallery-nogrid')

 # make structured data
 X, Y = np.meshgrid(np.linspace(-3, 3, 256), np.linspace(-3, 3, 256))
 Z = (1 - X/2 + X**5 + Y**3) * np.exp(-X**2 - Y**2)
 levels = np.linspace(Z.min(), Z.max(), 7)

 # sample it to make unstructured x, y, z
 # make data:
 np.random.seed(1)
 ysamp = np.random.randint(0, 256, size=250)
 xsamp = np.random.randint(0, 256, size=250)
 y = Y[:, 0][ysamp]
 x = X[0, :][xsamp]
 z = Z[ysamp, xsamp]
 x = np.random.uniform(-3, 3, 256)
 y = np.random.uniform(-3, 3, 256)
 z = (1 - x/2 + x**5 + y**3) * np.exp(-x**2 - y**2)
 levels = np.linspace(z.min(), z.max(), 7)

 # plot:
 fig, ax = plt.subplots()
 ax.grid(False)

 ax.plot(x, y, 'o', markersize=2, color='lightgrey')
 ax.tricontour(x, y, z, levels=levels)
diff --git a/plot_types/unstructured/tricontourf.py b/plot_types/unstructured/tricontourf.py
 import matplotlib.pyplot as plt
 import numpy as np

 plt.style.use('mpl_plot_gallery')
 plt.style.use('_mpl-gallery-nogrid')

 # make structured data
 X, Y = np.meshgrid(np.linspace(-3, 3, 256), np.linspace(-3, 3, 256))
 Z = (1 - X/2 + X**5 + Y**3) * np.exp(-X**2 - Y**2)
 levels = np.linspace(np.min(Z), np.max(Z), 7)

 # sample it to make unstructured x, y, z
 # make data:
 np.random.seed(1)
 ysamp = np.random.randint(0, 256, size=250)
 xsamp = np.random.randint(0, 256, size=250)
 y = Y[:, 0][ysamp]
 x = X[0, :][xsamp]
 z = Z[ysamp, xsamp]
 x = np.random.uniform(-3, 3, 256)
 y = np.random.uniform(-3, 3, 256)
 z = (1 - x/2 + x**5 + y**3) * np.exp(-x**2 - y**2)
 levels = np.linspace(z.min(), z.max(), 7)

 # plot:
 fig, ax = plt.subplots()
 ax.grid(False)

 ax.plot(x, y, 'o', markersize=2, color='grey')
 ax.tricontourf(x, y, z, levels=levels)
diff --git a/plot_types/unstructured/tripcolor.py b/plot_types/unstructured/tripcolor.py
 import matplotlib.pyplot as plt
 import numpy as np

 plt.style.use('mpl_plot_gallery')
 plt.style.use('_mpl-gallery-nogrid')

 # make structured data
 X, Y = np.meshgrid(np.linspace(-3, 3, 256), np.linspace(-3, 3, 256))
 Z = (1 - X/2 + X**5 + Y**3) * np.exp(-X**2 - Y**2)

 # sample it to make unstructured x, y, z
 # make data:
 np.random.seed(1)
 ysamp = np.random.randint(0, 256, size=250)
 xsamp = np.random.randint(0, 256, size=250)
 y = Y[:, 0][ysamp]
 x = X[0, :][xsamp]
 z = Z[ysamp, xsamp]
 x = np.random.uniform(-3, 3, 256)
 y = np.random.uniform(-3, 3, 256)
 z = (1 - x/2 + x**5 + y**3) * np.exp(-x**2 - y**2)

 # plot:
 fig, ax = plt.subplots()
diff --git a/plot_types/unstructured/triplot.py b/plot_types/unstructured/triplot.py
 import matplotlib.pyplot as plt
 import numpy as np

 plt.style.use('mpl_plot_gallery')
 plt.style.use('_mpl-gallery-nogrid')

 # make structured data
 X, Y = np.meshgrid(np.linspace(-3, 3, 256), np.linspace(-3, 3, 256))

 # sample it to make x, y, z
 # make data:
 np.random.seed(1)
 ysamp = np.random.randint(0, 256, size=250)
 xsamp = np.random.randint(0, 256, size=250)
 y = Y[:, 0][ysamp]
 x = X[0, :][xsamp]
 x = np.random.uniform(-3, 3, 256)
 y = np.random.uniform(-3, 3, 256)
 z = (1 - x/2 + x**5 + y**3) * np.exp(-x**2 - y**2)

 # plot:
 fig, ax = plt.subplots()
 ax.grid(False)

 ax.triplot(x, y)
Original file line number	Diff line number	Diff line change
Expand Up		@@ -70,12 +70,12 @@ def __call__(self, item):
		# Basic
		"plot", "scatter_plot", "bar", "stem", "step", "pie", "fill_between",
		# Arrays
		"imshow", "pcolormesh", "contourf", "quiver", "streamplot",
		"imshow", "pcolormesh", "contour", "contourf", "quiver", "streamplot",
		# Stats
		"hist_plot", "boxplot_plot", "errorbar_plot", "violin",
		"barbs", "eventplot", "hist2d", "hexbin",
		# Unstructured
		"tricontour", "tripcolor", "triplot",
		"tricontour", "tricontourf", "tripcolor", "triplot",
		]
		explicit_subsection_order = [item + ".py" for item in list_all]

Expand Down
Original file line number	Diff line number	Diff line change
		@@ -0,0 +1,19 @@
		# This style is used for the plot_types gallery. It is considered private.

		axes.grid: False
		axes.axisbelow: True

		figure.figsize: 2, 2
		# make it so the axes labels don't show up. Obviously
		# not good style for any quantitative analysis:
		figure.subplot.left: 0.01
		figure.subplot.right: 0.99
		figure.subplot.bottom: 0.01
		figure.subplot.top: 0.99

		xtick.major.size: 0.0
		ytick.major.size: 0.0

		# colors:
		image.cmap : Blues
		# axes.prop_cycle: cycler('color', ['FF7F0E', '1F77B4', '2CA02C'])
Original file line number	Diff line number	Diff line change
		@@ -1,4 +1,4 @@
		#fromtheMatplotlib cheatsheet as used in our gallery:
		#This style is used fortheplot_types gallery. It is considered part of the private API.

		axes.grid: True
		axes.axisbelow: True
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -8,7 +8,7 @@
		importmatplotlib.pyplotasplt
		importnumpyasnp

		plt.style.use('mpl_plot_gallery')
		plt.style.use('_mpl-gallery-nogrid')

		# make data
		X,Y=np.meshgrid(np.linspace(-3,3,256),np.linspace(-3,3,256))
Expand All		@@ -17,7 +17,6 @@

		# plot
		fig,ax=plt.subplots()
		ax.grid(False)

		ax.contour(X,Y,Z,levels=levels)

Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -9,16 +9,15 @@
		import matplotlib.pyplot as plt
		import numpy as np

		plt.style.use('mpl_plot_gallery')
		plt.style.use('_mpl-gallery-nogrid')

		# make data
		X, Y = np.meshgrid(np.linspace(-3, 3, 256), np.linspace(-3, 3, 256))
		Z = (1 - X/2. + X5 + Y3) * np.exp(-X2 - Y2)
		Z = (1 - X/2 + X5 + Y3) * np.exp(-X2 - Y2)
		Z = Z[::16, ::16]

		# plot
		fig, ax = plt.subplots()
		ax.grid(False)

		ax.imshow(Z)

Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -10,11 +10,11 @@
		import matplotlib.pyplot as plt
		import numpy as np

		plt.style.use('mpl_plot_gallery')
		plt.style.use('_mpl-gallery-nogrid')

		# make full-res data
		X, Y = np.meshgrid(np.linspace(-3, 3, 256), np.linspace(-3, 3, 256))
		Z = (1 - X/2. + X5 + Y3) * np.exp(-X2 - Y2)
		Z = (1 - X/2 + X5 + Y3) * np.exp(-X2 - Y2)

		# sample unevenly in x:
		dx = np.sqrt((np.arange(16) - 8)**2) + 6
Expand All		@@ -26,7 +26,6 @@

		# plot
		fig, ax = plt.subplots()
		ax.grid(False)

		ax.pcolormesh(X, Y, Z, vmin=-0.5, vmax=1.0)

Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -8,20 +8,18 @@
		import matplotlib.pyplot as plt
		import numpy as np

		plt.style.use('mpl_plot_gallery')
		plt.style.use('_mpl-gallery-nogrid')

		# make a stream function:
		X, Y = np.meshgrid(np.linspace(-3, 3, 256), np.linspace(-3, 3, 256))
		Z = (1 - X/2. + X5 + Y3) * np.exp(-X2 - Y2)
		Z = (1 - X/2 + X5 + Y3) * np.exp(-X2 - Y2)
		# make U and V out of the streamfunction:
		V = np.diff(Z[1:, :], axis=1)
		U = -np.diff(Z[:, 1:], axis=0)

		# plot:
		fig, ax = plt.subplots()
		ax.grid(False)

		# plot stream plot
		ax.streamplot(X[1:, 1:], Y[1:, 1:], U, V)

		plt.show()
Original file line number	Diff line number	Diff line change
Expand Up		@@ -7,7 +7,7 @@
		"""
		import matplotlib.pyplot as plt
		import numpy as np
		plt.style.use('mpl_plot_gallery')
		plt.style.use('_mpl-gallery')

		# make data:
		np.random.seed(3)
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -9,7 +9,7 @@
		importmatplotlib.pyplotasplt
		importnumpyasnp

		plt.style.use('mpl_plot_gallery')
		plt.style.use('_mpl-gallery')

		# make data
		x=np.linspace(0,10,100)
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -8,24 +8,17 @@
		import matplotlib.pyplot as plt
		import numpy as np

		plt.style.use('mpl_plot_gallery')
		plt.style.use('_mpl-gallery-nogrid')

		# make structured data
		X, Y = np.meshgrid(np.linspace(-3, 3, 256), np.linspace(-3, 3, 256))
		Z = (1 - X/2 + X5 + Y3) * np.exp(-X2 - Y2)
		levels = np.linspace(Z.min(), Z.max(), 7)

		# sample it to make unstructured x, y, z
		# make data:
		np.random.seed(1)
		ysamp = np.random.randint(0, 256, size=250)
		xsamp = np.random.randint(0, 256, size=250)
		y = Y[:, 0][ysamp]
		x = X[0, :][xsamp]
		z = Z[ysamp, xsamp]
		x = np.random.uniform(-3, 3, 256)
		y = np.random.uniform(-3, 3, 256)
		z = (1 - x/2 + x5 + y3) * np.exp(-x2 - y2)
		levels = np.linspace(z.min(), z.max(), 7)

		# plot:
		fig, ax = plt.subplots()
		ax.grid(False)

		ax.plot(x, y, 'o', markersize=2, color='lightgrey')
		ax.tricontour(x, y, z, levels=levels)
Expand Down