Jan 27, 2018 · Jan 26, 2018 · Jan 26, 2018 · Jan 26, 2018
diff --git a/examples/api/font_file.py b/examples/api/font_file.py
 """

 import os
 from matplotlib import font_manager as fm, pyplot as plt, rcParams
 from matplotlib import font_manager as fm, rcParams
 import matplotlib.pyplot as plt

 fig, ax = plt.subplots()

diff --git a/examples/api/power_norm.py b/examples/api/power_norm.py

 """

 from matplotlibimport pyplot as plt
 importmatplotlib.pyplot as plt
 import matplotlib.colors as mcolors
 import numpy as np
 from numpy.random import multivariate_normal
diff --git a/examples/axes_grid1/demo_colorbar_with_axes_divider.py b/examples/axes_grid1/demo_colorbar_with_axes_divider.py
 ===============================

 """

 importmatplotlib.pyplotasplt
 frommpl_toolkits.axes_grid1.axes_dividerimportmake_axes_locatable

 frommpl_toolkits.axes_grid1.colorbarimportcolorbar
 # from matplotlib.pyplot import colorbar

 fig=plt.figure(1,figsize=(6,3))
 fig, (ax1,ax2)=plt.subplots(1,2)
 fig.subplots_adjust(wspace=0.5)

 ax1=fig.add_subplot(121)
 im1=ax1.imshow([[1,2], [3,4]])

 ax1_divider=make_axes_locatable(ax1)
 cax1=ax1_divider.append_axes("right",size="7%",pad="2%")
 cb1=colorbar(im1,cax=cax1)

 ax2=fig.add_subplot(122)
 im2=ax2.imshow([[1,2], [3,4]])

 ax2_divider=make_axes_locatable(ax2)
 cax2=ax2_divider.append_axes("top",size="7%",pad="2%")
 cb2=colorbar(im2,cax=cax2,orientation="horizontal")
 cax2.xaxis.set_ticks_position("top")

 plt.show()
diff --git a/examples/event_handling/lasso_demo.py b/examples/event_handling/lasso_demo.py
 This is currently a proof-of-concept implementation (though it is
 usable as is).  There will be some refinement of the API.
 """
 from matplotlib.widgets import Lasso
 from matplotlib.collections import RegularPolyCollection
 from matplotlib import colors as mcolors, path

 from matplotlib import colors as mcolors, path
 from matplotlib.collections import RegularPolyCollection
 import matplotlib.pyplot as plt
 fromnumpy importnonzero
 from numpy.random import rand
 frommatplotlib.widgets importLasso
 import numpy as np


 class Datum(object):
        # acquire a lock on the widget drawing
        self.canvas.widgetlock(self.lasso)


 if __name__ == '__main__':

    data = [Datum(*xy) for xy in rand(100, 2)]
    np.random.seed(19680801)

    data = [Datum(*xy) for xy in np.random.rand(100, 2)]
    ax = plt.axes(xlim=(0, 1), ylim=(0, 1), autoscale_on=False)
    ax.set_title('Lasso points using left mouse button')

diff --git a/examples/event_handling/pick_event_demo2.py b/examples/event_handling/pick_event_demo2.py
    if not N:
        return True

    figi = plt.figure()
    for subplotnum, dataind in enumerate(event.ind):
        ax = figi.add_subplot(N, 1, subplotnum + 1)
    figi, axs = plt.subplots(N, squeeze=False)
    for ax, dataind in zip(axs.flat, event.ind):
        ax.plot(X[dataind])
        ax.text(0.05,0.9, 'mu=%1.3f\nsigma=%1.3f' % (xs[dataind], ys[dataind]),
        ax.text(.05, .9, 'mu=%1.3f\nsigma=%1.3f' % (xs[dataind], ys[dataind]),
                transform=ax.transAxes, va='top')
        ax.set_ylim(-0.5, 1.5)
    figi.show()
diff --git a/examples/event_handling/zoom_window.py b/examples/event_handling/zoom_window.py
 This example shows how to connect events in one window, for example, a mouse
 press, to another figure window.

 If you click on a point in the first window, the z and y limits of the
 secondwill be adjusted so that the center of the zoom in the second
 window will bethe x,y coordinates of the clicked point.
 If you click on a point in the first window, the z and y limits of the second
 will be adjusted so that the center of the zoom in the second window will be
 the x,y coordinates of the clicked point.

 Note the diameter of the circles in the scatter are defined in
 points**2, sotheir size is independent of the zoom
 Note the diameter of the circles in the scatter are defined in points**2, so
 their size is independent of the zoom.
 """
 from matplotlib.pyplot import figure, show

 import matplotlib.pyplot as plt
 import numpy as np
 figsrc = figure()
 figzoom = figure()

 axsrc = figsrc.add_subplot(111,xlim=(0, 1), ylim=(0, 1), autoscale_on=False)
 axzoom = figzoom.add_subplot(111, xlim=(0.45, 0.55), ylim=(0.4, .6),
 autoscale_on=False)
 axsrc.set_title('Click to zoom')
 axzoom.set_title('zoom window')

 figsrc, axsrc = plt.subplots()
 figzoom, axzoom = plt.subplots()
 axsrc.set(xlim=(0, 1), ylim=(0, 1), autoscale_on=False,
          title='Click to zoom')
 axzoom.set(xlim=(0.45, 0.55), ylim=(0.4, 0.6),autoscale_on=False,
           title='Zoom window')

 x, y, s, c = np.random.rand(4, 200)
 s *= 200


 axsrc.scatter(x, y, s, c)
 axzoom.scatter(x, y, s, c)

    figzoom.canvas.draw()

 figsrc.canvas.mpl_connect('button_press_event', onpress)
 show()
 plt.show()
diff --git a/examples/images_contours_and_fields/multi_image.py b/examples/images_contours_and_fields/multi_image.py
 Make a set of images with a single colormap, norm, and colorbar.
 """

 from matplotlib import colors, pyplot as plt
 from matplotlib import colors
 import matplotlib.pyplot as plt
 import numpy as np

 np.random.seed(19680801)
diff --git a/examples/lines_bars_and_markers/eventplot_demo.py b/examples/lines_bars_and_markers/eventplot_demo.py
 lineoffsets1 = np.array([-15, -3, 1, 1.5, 6, 10])
 linelengths1 = [5, 2, 1, 1, 3, 1.5]

 fig= plt.figure()
 fig, axs= plt.subplots(2, 2)

 # create a horizontal plot
 ax1 = fig.add_subplot(221)
 ax1.eventplot(data1, colors=colors1, lineoffsets=lineoffsets1,
              linelengths=linelengths1)

 axs[0, 0].eventplot(data1, colors=colors1, lineoffsets=lineoffsets1,
                    linelengths=linelengths1)

 # create a vertical plot
 ax2 = fig.add_subplot(223)
 ax2.eventplot(data1, colors=colors1, lineoffsets=lineoffsets1,
              linelengths=linelengths1, orientation='vertical')
 axs[1, 0].eventplot(data1, colors=colors1, lineoffsets=lineoffsets1,
                    linelengths=linelengths1, orientation='vertical')

 # create another set of random data.
 # the gamma distribution is only used fo aesthetic purposes
 linelengths2 = 1

 # create a horizontal plot
 ax1 = fig.add_subplot(222)
 ax1.eventplot(data2, colors=colors2, lineoffsets=lineoffsets2,
              linelengths=linelengths2)
 axs[0, 1].eventplot(data2, colors=colors2, lineoffsets=lineoffsets2,
                    linelengths=linelengths2)


 # create a vertical plot
 ax2 = fig.add_subplot(224)
 ax2.eventplot(data2, colors=colors2, lineoffsets=lineoffsets2,
              linelengths=linelengths2, orientation='vertical')
 axs[1, 1].eventplot(data2, colors=colors2, lineoffsets=lineoffsets2,
                    linelengths=linelengths2, orientation='vertical')

 plt.show()
diff --git a/examples/lines_bars_and_markers/gradient_bar.py b/examples/lines_bars_and_markers/gradient_bar.py

 """
 import matplotlib.pyplot as plt
 from numpy import arange
 from numpy.random import rand
 import numpy as np

 np.random.seed(19680801)


 def gbar(ax, x, y, width=0.5, bottom=0):
                  extent=(left, right, bottom, top), alpha=1)


 fig = plt.figure()

 xmin, xmax = xlim = 0, 10
 ymin, ymax = ylim = 0, 1
 ax = fig.add_subplot(111, xlim=xlim, ylim=ylim,
                     autoscale_on=False)
 X = [[.6, .6], [.7, .7]]

 fig, ax = plt.subplots()
 ax.set(xlim=xlim, ylim=ylim, autoscale_on=False)

 X = [[.6, .6], [.7, .7]]
 ax.imshow(X, interpolation='bicubic', cmap=plt.cm.copper,
          extent=(xmin, xmax, ymin, ymax), alpha=1)

 N = 10
 x = arange(N) + 0.25
 y = rand(N)
 x =np.arange(N) + 0.25
 y =np.random.rand(N)
 gbar(ax, x, y, width=0.7)
 ax.set_aspect('auto')
 plt.show()
diff --git a/examples/lines_bars_and_markers/interp_demo.py b/examples/lines_bars_and_markers/interp_demo.py

 """
 import matplotlib.pyplot as plt
 from numpyimport pi, sin, linspace
 import numpyas np
 from matplotlib.mlab import stineman_interp

 x = linspace(0, 2*pi, 20)
 y = sin(x)
 x =np.linspace(0, 2*np.pi, 20)
 y =np.sin(x)
 yp = None
 xi = linspace(x[0], x[-1], 100)
 xi =np.linspace(x[0], x[-1], 100)
 yi = stineman_interp(xi, x, y, yp)

 fig, ax = plt.subplots()
diff --git a/examples/lines_bars_and_markers/scatter_symbol.py b/examples/lines_bars_and_markers/scatter_symbol.py
 ==============

 """
 from matplotlibimport pyplot as plt
 importmatplotlib.pyplot as plt
 import numpy as np
 import matplotlib

diff --git a/examples/lines_bars_and_markers/simple_plot.py b/examples/lines_bars_and_markers/simple_plot.py

 Create a simple plot.
 """

 import matplotlib.pyplot as plt
 import numpy as np

 s = 1 + np.sin(2 * np.pi * t)

 # Note that using plt.subplots below is equivalent to using
 # fig = plt.figure and then ax = fig.add_subplot(111)
 # fig = plt.figure() and then ax = fig.add_subplot(111)
 fig, ax = plt.subplots()
 ax.plot(t, s)

diff --git a/examples/misc/pythonic_matplotlib.py b/examples/misc/pythonic_matplotlib.py
 instances, managing the bounding boxes of the figure elements,
 creating and realizing GUI windows and embedding figures in them.


 If you are an application developer and want to embed matplotlib in
 your application, follow the lead of examples/embedding_in_wx.py,
 examples/embedding_in_gtk.py or examples/embedding_in_tk.py.  In this
    a.set_yticks([])
 """

 import matplotlib.pyplot as plt
 import numpy as np

 from matplotlib.pyplot import figure, show
 from numpy import arange, sin, pi

 t = arange(0.0, 1.0, 0.01)
 t = np.arange(0.0, 1.0, 0.01)

 fig = figure(1)
 fig, (ax1, ax2) = plt.subplots(2)

 ax1 = fig.add_subplot(211)
 ax1.plot(t, sin(2*pi * t))
 ax1.plot(t, np.sin(2*np.pi * t))
 ax1.grid(True)
 ax1.set_ylim((-2, 2))
 ax1.set_ylabel('1 Hz')
 ax1.set_title('A sine wave or two')

 ax1.xaxis.set_tick_params(labelcolor='r')


 ax2 = fig.add_subplot(212)
 ax2.plot(t, sin(2 * 2*pi * t))
 ax2.plot(t, np.sin(2 * 2*np.pi * t))
 ax2.grid(True)
 ax2.set_ylim((-2, 2))
 l = ax2.set_xlabel('Hi mom')
 l.set_color('g')
 l.set_fontsize('large')

 show()
 plt.show()
diff --git a/examples/mplot3d/surface3d_radial.py b/examples/mplot3d/surface3d_radial.py
 '''

 from mpl_toolkits.mplot3d import Axes3D
 from matplotlibimport pyplot as plt
 importmatplotlib.pyplot as plt
 import numpy as np


diff --git a/examples/pie_and_polar_charts/nested_pie.py b/examples/pie_and_polar_charts/nested_pie.py

 """

 from matplotlibimport pyplot as plt
 importmatplotlib.pyplot as plt
 import numpy as np

 ###############################################################################
diff --git a/examples/pie_and_polar_charts/polar_legend.py b/examples/pie_and_polar_charts/polar_legend.py

 Demo of a legend on a polar-axis plot.
 """

 import matplotlib.pyplot as plt
 import numpy as np
 from matplotlib.pyplot import figure, show, rc

 # radar green, solid grid lines
 rc('grid', color='#316931', linewidth=1, linestyle='-')
 rc('xtick', labelsize=15)
 rc('ytick', labelsize=15)
 plt.rc('grid', color='#316931', linewidth=1, linestyle='-')
 plt.rc('xtick', labelsize=15)
 plt.rc('ytick', labelsize=15)

 # force square figure and square axes looks better for polar, IMO
 fig = figure(figsize=(8, 8))
 fig =plt.figure(figsize=(8, 8))
 ax = fig.add_axes([0.1, 0.1, 0.8, 0.8],
                  projection='polar', facecolor='#d5de9c')

 ax.plot(0.5 * theta, r, color='blue', ls='--', lw=3, label='another line')
 ax.legend()

 show()
 plt.show()
Original file line number	Diff line number	Diff line change
Expand Up		@@ -15,7 +15,8 @@
		"""

		import os
		from matplotlib import font_manager as fm, pyplot as plt, rcParams
		from matplotlib import font_manager as fm, rcParams
		import matplotlib.pyplot as plt

		fig, ax = plt.subplots()

Expand Down
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Expand Up		@@ -7,7 +7,7 @@

		"""

		from matplotlibimport pyplot as plt
		importmatplotlib.pyplot as plt
		import matplotlib.colors as mcolors
		import numpy as np
		from numpy.random import multivariate_normal
Expand Down
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Expand Up		@@ -4,27 +4,23 @@
		===============================

		"""

		importmatplotlib.pyplotasplt
		frommpl_toolkits.axes_grid1.axes_dividerimportmake_axes_locatable

		frommpl_toolkits.axes_grid1.colorbarimportcolorbar
		# from matplotlib.pyplot import colorbar

		fig=plt.figure(1,figsize=(6,3))
		fig, (ax1,ax2)=plt.subplots(1,2)
		fig.subplots_adjust(wspace=0.5)
Copy link Member timhoffmJan 26, 2018 Choose a reason for hiding this comment The reason will be displayed to describe this comment to others.Learn more. Could be added to`subplots` via`gridspec_kw`. Copy link ContributorAuthor anntzerJan 26, 2018 Choose a reason for hiding this comment The reason will be displayed to describe this comment to others.Learn more. Not convinced it's an improvement in legibility...

		ax1=fig.add_subplot(121)
		im1=ax1.imshow([[1,2], [3,4]])

		ax1_divider=make_axes_locatable(ax1)
		cax1=ax1_divider.append_axes("right",size="7%",pad="2%")
		cb1=colorbar(im1,cax=cax1)

		ax2=fig.add_subplot(122)
		im2=ax2.imshow([[1,2], [3,4]])

		ax2_divider=make_axes_locatable(ax2)
		cax2=ax2_divider.append_axes("top",size="7%",pad="2%")
		cb2=colorbar(im2,cax=cax2,orientation="horizontal")
		cax2.xaxis.set_ticks_position("top")

		plt.show()
Original file line number	Diff line number	Diff line change
Expand Up		@@ -10,13 +10,12 @@
		This is currently a proof-of-concept implementation (though it is
		usable as is). There will be some refinement of the API.
		"""
		from matplotlib.widgets import Lasso
		from matplotlib.collections import RegularPolyCollection
		from matplotlib import colors as mcolors, path

		from matplotlib import colors as mcolors, path
		from matplotlib.collections import RegularPolyCollection
		import matplotlib.pyplot as plt
		fromnumpy importnonzero
		from numpy.random import rand
		frommatplotlib.widgets importLasso
		import numpy as np


		class Datum(object):
Expand DownExpand Up		@@ -77,9 +76,12 @@ def onpress(self, event):
		# acquire a lock on the widget drawing
		self.canvas.widgetlock(self.lasso)


		if __name__ == '__main__':

		data = [Datum(*xy) for xy in rand(100, 2)]
		np.random.seed(19680801)

		data = [Datum(*xy) for xy in np.random.rand(100, 2)]
		ax = plt.axes(xlim=(0, 1), ylim=(0, 1), autoscale_on=False)
		ax.set_title('Lasso points using left mouse button')

Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -29,11 +29,10 @@ def onpick(event):
		if not N:
		return True

		figi = plt.figure()
		for subplotnum, dataind in enumerate(event.ind):
		ax = figi.add_subplot(N, 1, subplotnum + 1)
		figi, axs = plt.subplots(N, squeeze=False)
		for ax, dataind in zip(axs.flat, event.ind):
		ax.plot(X[dataind])
		ax.text(0.05,0.9, 'mu=%1.3f\nsigma=%1.3f' % (xs[dataind], ys[dataind]),
		ax.text(.05, .9, 'mu=%1.3f\nsigma=%1.3f' % (xs[dataind], ys[dataind]),
		transform=ax.transAxes, va='top')
		ax.set_ylim(-0.5, 1.5)
		figi.show()
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -6,27 +6,27 @@
		This example shows how to connect events in one window, for example, a mouse
		press, to another figure window.

		If you click on a point in the first window, the z and y limits of the
		secondwill be adjusted so that the center of the zoom in the second
		window will bethe x,y coordinates of the clicked point.
		If you click on a point in the first window, the z and y limits of the second
		will be adjusted so that the center of the zoom in the second window will be
		the x,y coordinates of the clicked point.

		Note the diameter of the circles in the scatter are defined in
		points**2, sotheir size is independent of the zoom
		Note the diameter of the circles in the scatter are defined in points**2, so
		their size is independent of the zoom.
		"""
		from matplotlib.pyplot import figure, show

		import matplotlib.pyplot as plt
		import numpy as np
		figsrc = figure()
		figzoom = figure()

		axsrc = figsrc.add_subplot(111,xlim=(0, 1), ylim=(0, 1), autoscale_on=False)
		axzoom = figzoom.add_subplot(111, xlim=(0.45, 0.55), ylim=(0.4, .6),
		autoscale_on=False)
		axsrc.set_title('Click to zoom')
		axzoom.set_title('zoom window')

		figsrc, axsrc = plt.subplots()
		figzoom, axzoom = plt.subplots()
		axsrc.set(xlim=(0, 1), ylim=(0, 1), autoscale_on=False,
		title='Click to zoom')
		axzoom.set(xlim=(0.45, 0.55), ylim=(0.4, 0.6),autoscale_on=False,
		title='Zoom window')

		x, y, s, c = np.random.rand(4, 200)
		s *= 200


		axsrc.scatter(x, y, s, c)
		axzoom.scatter(x, y, s, c)

Expand All		@@ -40,4 +40,4 @@ def onpress(event):
		figzoom.canvas.draw()

		figsrc.canvas.mpl_connect('button_press_event', onpress)
		show()
		plt.show()
Original file line number	Diff line number	Diff line change
Expand Up		@@ -6,7 +6,8 @@
		Make a set of images with a single colormap, norm, and colorbar.
		"""

		from matplotlib import colors, pyplot as plt
		from matplotlib import colors
		import matplotlib.pyplot as plt
		import numpy as np

		np.random.seed(19680801)
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -32,18 +32,15 @@
		lineoffsets1 = np.array([-15, -3, 1, 1.5, 6, 10])
		linelengths1 = [5, 2, 1, 1, 3, 1.5]

		fig= plt.figure()
		fig, axs= plt.subplots(2, 2)

		# create a horizontal plot
		ax1 = fig.add_subplot(221)
		ax1.eventplot(data1, colors=colors1, lineoffsets=lineoffsets1,
		linelengths=linelengths1)

		axs[0, 0].eventplot(data1, colors=colors1, lineoffsets=lineoffsets1,
		linelengths=linelengths1)

		# create a vertical plot
		ax2 = fig.add_subplot(223)
		ax2.eventplot(data1, colors=colors1, lineoffsets=lineoffsets1,
		linelengths=linelengths1, orientation='vertical')
		axs[1, 0].eventplot(data1, colors=colors1, lineoffsets=lineoffsets1,
		linelengths=linelengths1, orientation='vertical')

		# create another set of random data.
		# the gamma distribution is only used fo aesthetic purposes
Expand All		@@ -57,14 +54,12 @@
		linelengths2 = 1

		# create a horizontal plot
		ax1 = fig.add_subplot(222)
		ax1.eventplot(data2, colors=colors2, lineoffsets=lineoffsets2,
		linelengths=linelengths2)
		axs[0, 1].eventplot(data2, colors=colors2, lineoffsets=lineoffsets2,
		linelengths=linelengths2)


		# create a vertical plot
		ax2 = fig.add_subplot(224)
		ax2.eventplot(data2, colors=colors2, lineoffsets=lineoffsets2,
		linelengths=linelengths2, orientation='vertical')
		axs[1, 1].eventplot(data2, colors=colors2, lineoffsets=lineoffsets2,
		linelengths=linelengths2, orientation='vertical')

		plt.show()
Original file line number	Diff line number	Diff line change
Expand Up		@@ -5,8 +5,9 @@

		"""
		import matplotlib.pyplot as plt
		from numpy import arange
		from numpy.random import rand
		import numpy as np

		np.random.seed(19680801)


		def gbar(ax, x, y, width=0.5, bottom=0):
Expand All		@@ -17,20 +18,19 @@ def gbar(ax, x, y, width=0.5, bottom=0):
		extent=(left, right, bottom, top), alpha=1)


		fig = plt.figure()

		xmin, xmax = xlim = 0, 10
		ymin, ymax = ylim = 0, 1
		ax = fig.add_subplot(111, xlim=xlim, ylim=ylim,
		autoscale_on=False)
		X = [[.6, .6], [.7, .7]]

		fig, ax = plt.subplots()
		ax.set(xlim=xlim, ylim=ylim, autoscale_on=False)

		X = [[.6, .6], [.7, .7]]
		ax.imshow(X, interpolation='bicubic', cmap=plt.cm.copper,
		extent=(xmin, xmax, ymin, ymax), alpha=1)

		N = 10
		x = arange(N) + 0.25
		y = rand(N)
		x =np.arange(N) + 0.25
		y =np.random.rand(N)
		gbar(ax, x, y, width=0.7)
		ax.set_aspect('auto')
		plt.show()
Original file line number	Diff line number	Diff line change
Expand Up		@@ -5,13 +5,13 @@

		"""
		import matplotlib.pyplot as plt
		from numpyimport pi, sin, linspace
		import numpyas np
		from matplotlib.mlab import stineman_interp

		x = linspace(0, 2*pi, 20)
		y = sin(x)
		x =np.linspace(0, 2*np.pi, 20)
		y =np.sin(x)
		yp = None
		xi = linspace(x[0], x[-1], 100)
		xi =np.linspace(x[0], x[-1], 100)
		yi = stineman_interp(xi, x, y, yp)

		fig, ax = plt.subplots()
Expand Down