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Rewrite subplots_demo
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‎examples/subplots_axes_and_figures/subplots_demo.py

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"""
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=============
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Subplots Demo
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=============
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Examples illustrating the use of plt.subplots().
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This function creates a figure and a grid of subplots with a single call, while
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providing reasonable control over how the individual plots are created. For
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very refined tuning of subplot creation, you can still use add_subplot()
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directly on a new figure.
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================================================
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Creating multiple subplots using ``plt.subplot``
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================================================
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`.pyplot.subplots` creates a figure and a grid of subplots with a single call,
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while providing reasonable control over how the individual plots are created.
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For more advanced use cases you can use `.GridSpec` for a more general subplot
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layout or `.Figure.add_subplot` for adding subplots at arbitrary locations
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within the figure.
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"""
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# sphinx_gallery_thumbnail_number = 11
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import matplotlib.pyplot as plt
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import numpy as np
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# Simple data to display in various forms
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# Some example data to display
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x = np.linspace(0, 2 * np.pi, 400)
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y = np.sin(x ** 2)
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plt.close('all')
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###############################################################################
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# Just a figure and one subplot
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f, ax = plt.subplots()
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# A figure with just one subplot
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# """"""""""""""""""""""""""""""
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#
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# ``subplots()`` without arguments returns a `.Figure` and a single
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# `~.axes.Axes`.
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#
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# This is actually the simplest and recommended way of creating a single
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# Figure and Axes.
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fig, ax = plt.subplots()
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ax.plot(x, y)
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ax.set_title('Simple plot')
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ax.set_title('A single plot')
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###############################################################################
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# Two subplots, the axes array is 1-d
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# Stacking subplots in one direction
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# """"""""""""""""""""""""""""""""""
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#
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# The first two optional arguments of `.pyplot.subplots` define the number of
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# rows and columns of the subplot grid.
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#
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# When stacking in one direction only, the returned `axs` is a 1D numpy array
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# containing the list of created Axes.
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fig, axs = plt.subplots(2)
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fig.suptitle('Vertically stacked subplots')
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axs[0].plot(x, y)
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axs[1].plot(x, -y)
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f, axarr = plt.subplots(2, sharex=True)
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f.suptitle('Sharing X axis')
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axarr[0].plot(x, y)
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axarr[1].scatter(x, y)
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###############################################################################
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# If you are creating just a few Axes, it's handy to unpack them immediately to
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# dedicated variables for each Axes. That way, we can use ``ax1`` instead of
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# the more verbose ``axs[0]``.
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fig, (ax1, ax2) = plt.subplots(2)
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fig.suptitle('Vertically stacked subplots')
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ax1.plot(x, y)
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ax2.plot(x, -y)
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###############################################################################
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# Two subplots, unpack the axes array immediately
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# To obtain side-by-side subplots, pass parameters ``1, 2`` for one row and two
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# columns.
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f, (ax1, ax2) = plt.subplots(1, 2, sharey=True)
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f.suptitle('Sharing Y axis')
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fig, (ax1, ax2) = plt.subplots(1, 2)
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fig.suptitle('Horizontally stacked subplots')
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ax1.plot(x, y)
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ax2.scatter(x, y)
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ax2.plot(x, -y)
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###############################################################################
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# Three subplots sharing both x/y axes
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f, axarr = plt.subplots(3, sharex=True, sharey=True)
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f.suptitle('Sharing both axes')
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axarr[0].plot(x, y)
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axarr[1].scatter(x, y)
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axarr[2].scatter(x, 2 * y ** 2 - 1, color='r')
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# Bring subplots close to each other.
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f.subplots_adjust(hspace=0)
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# Hide x labels and tick labels for all but bottom plot.
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for ax in axarr:
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# Stacking subplots in two directions
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# """""""""""""""""""""""""""""""""""
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#
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# When stacking in two directions, the returned `axs` is a 2D numpy array.
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#
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# If you have to set parameters for each subplot it's handy to iterate over
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# all subplots in a 2D grid using ``for ax in axs.flat:``.
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fig, axs = plt.subplots(2, 2)
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axs[0, 0].plot(x, y)
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axs[0, 0].set_title('Axis [0,0]')
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axs[0, 1].plot(x, y, 'tab:orange')
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axs[0, 1].set_title('Axis [0,1]')
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axs[1, 0].plot(x, -y, 'tab:green')
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axs[1, 0].set_title('Axis [1,0]')
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axs[1, 1].plot(x, -y, 'tab:red')
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axs[1, 1].set_title('Axis [1,1]')
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for ax in axs.flat:
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ax.set(xlabel='x-label', ylabel='y-label')
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# Hide x labels and tick labels for top plots and y ticks for right plots.
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for ax in axs.flat:
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ax.label_outer()
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###############################################################################
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# Row and column sharing
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# You can use tuple-unpacking also in 2D to assign all subplots to dedicated
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# variables:
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f, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, sharex='col', sharey='row')
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f.suptitle('Sharing x per column, y per row')
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fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2)
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fig.suptitle('Sharing x per column, y per row')
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ax1.plot(x, y)
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ax2.scatter(x, y)
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ax3.scatter(x, 2 * y ** 2 - 1, color='r')
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ax4.plot(x, 2 * y ** 2 - 1, color='r')
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ax2.plot(x, y**2, 'tab:orange')
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ax3.plot(x, -y, 'tab:green')
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ax4.plot(x, -y**2, 'tab:red')
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for ax in axs.flat:
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ax.label_outer()
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###############################################################################
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# Four axes, returned as a 2-d array
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f, axarr = plt.subplots(2, 2)
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axarr[0, 0].plot(x, y)
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axarr[0, 0].set_title('Axis [0,0]')
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axarr[0, 1].scatter(x, y)
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axarr[0, 1].set_title('Axis [0,1]')
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axarr[1, 0].plot(x, y ** 2)
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axarr[1, 0].set_title('Axis [1,0]')
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axarr[1, 1].scatter(x, y ** 2)
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axarr[1, 1].set_title('Axis [1,1]')
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for ax in axarr.flat:
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ax.set(xlabel='x-label', ylabel='y-label')
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# Hide x labels and tick labels for top plots and y ticks for right plots.
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for ax in axarr.flat:
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# Sharing axes
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# """"""""""""
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#
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# By default, each Axes is scaled individually. Thus, if the ranges are
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# different the tick values of the subplots do not align.
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fig, (ax1, ax2) = plt.subplots(2)
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fig.suptitle('Axes values are scaled individually by default')
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ax1.plot(x, y)
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ax2.plot(x + 1, -y)
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###############################################################################
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#
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# You can use *sharex* or *sharey* to align the horizontal or vertical axis.
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fig, (ax1, ax2) = plt.subplots(2, sharex=True)
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fig.suptitle('Aligning x-axis using sharex')
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ax1.plot(x, y)
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ax2.plot(x + 1, -y)
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###############################################################################
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# Setting *sharex* or *sharey* to ``True`` enables global sharing across the
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# whole grid, i.e. also the y-axes of vertically stacked subplots have the
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# same scale when using ``sharey=True``.
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fig, axs = plt.subplots(3, sharex=True, sharey=True)
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fig.suptitle('Sharing both axes')
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axs[0].plot(x, y ** 2)
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axs[1].plot(x, 0.3 * y, 'o')
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axs[2].plot(x, y, '+')
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###############################################################################
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# For subplots that are sharing axes one set of tick labels is enough. Tick
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# labels of inner Axes are automatically removed by *sharex* and *sharey*.
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# Still there remains an unused empty space between the subplots.
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#
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# The parameter *gridspec_kw* of `.pyplot.subplots` controls the grid
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# properties (see also `.GridSpec`). For example, we can reduce the height
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# between vertical subplots using ``gridspec_kw={'hspace': 0}``.
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#
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# `.label_outer` is a handy method to remove labels and ticks from subplots
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# that are not at the edge of the grid.
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fig, axs = plt.subplots(3, sharex=True, sharey=True, gridspec_kw={'hspace': 0})
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fig.suptitle('Sharing both axes')
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axs[0].plot(x, y ** 2)
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axs[1].plot(x, 0.3 * y, 'o')
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axs[2].plot(x, y, '+')
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# Hide x labels and tick labels for all but bottom plot.
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for ax in axs:
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ax.label_outer()
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###############################################################################
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# Apart from ``True`` and ``False``, both *sharex* and *sharey* accept the
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# values 'row' and 'col' to share the values only per row or column.
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fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2,
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sharex='col', sharey='row',
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gridspec_kw={'hspace': 0,
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'wspace': 0})
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fig.suptitle('Sharing x per column, y per row')
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ax1.plot(x, y)
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ax2.plot(x, y**2, 'tab:orange')
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ax3.plot(x + 1, -y, 'tab:green')
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ax4.plot(x + 2, -y**2, 'tab:red')
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for ax in axs:
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ax.label_outer()
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###############################################################################
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# Four polar axes
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f, axarr = plt.subplots(2, 2, subplot_kw=dict(projection='polar'))
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axarr[0, 0].plot(x, y)
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axarr[0, 0].set_title('Axis [0,0]')
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axarr[0, 1].scatter(x, y)
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axarr[0, 1].set_title('Axis [0,1]')
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axarr[1, 0].plot(x, y ** 2)
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axarr[1, 0].set_title('Axis [1,0]')
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axarr[1, 1].scatter(x, y ** 2)
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axarr[1, 1].set_title('Axis [1,1]')
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# Fine-tune figure; make subplots farther from each other.
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f.subplots_adjust(hspace=0.3)
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plt.show()
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# Polar axes
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# """"""""""
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#
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# The parameter *subplot_kw* of `.pyplot.subplots` controls the subplot
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# properties (see also `.Figure.add_subplot`). In particular, this can be used
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# to create a grid of polar Axes.
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fig, (ax1, ax2) = plt.subplots(1, 2, subplot_kw=dict(projection='polar'))
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ax1.plot(x, y)
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ax2.plot(x, y ** 2)
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