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DOC: update axes_demo to directly manipulate fig, ax #14934

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Aug 1, 2019
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DOC: update axes_demo to directly manipulate fig, ax #14934

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DOC: update axes_demo to directly manipulate fig, ax
Jul 30, 2019
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Jul 31, 2019
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45 changes: 26 additions & 19 deletions examples/subplots_axes_and_figures/axes_demo.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,14 @@
Axes Demo
=========

Example use of ``plt.axes`` to create inset axes within the main plot axes.
Example use of ``fig.add_axes`` to create inset axes within the main plot axes.

Please see also the :ref:`axes_grid_examples` section, and the following three
examples:

- :doc:`/gallery/subplots_axes_and_figures/zoom_inset_axes`
- :doc:`/gallery/axes_grid1/inset_locator_demo`
- :doc:`/gallery/axes_grid1/inset_locator_demo2`
"""
import matplotlib.pyplot as plt
import numpy as np
Expand All @@ -19,27 +26,27 @@
x = np.random.randn(len(t))
s = np.convolve(x, r)[:len(x)] * dt # colored noise

# the main axes is subplot(111) by default
plt.plot(t, s)
plt.xlim(0, 1)
plt.ylim(1.1 * np.min(s), 2 * np.max(s))
plt.xlabel('time (s)')
plt.ylabel('current (nA)')
plt.title('Gaussian colored noise')
fig, main_ax = plt.subplots()
main_ax.plot(t, s)
main_ax.set_xlim(0, 1)
main_ax.set_ylim(1.1 * np.min(s), 2 * np.max(s))
main_ax.set_xlabel('time (s)')
main_ax.set_ylabel('current (nA)')
main_ax.set_title('Gaussian colored noise')

# this is an inset axes over the main axes
a = plt.axes([.65, .6, .2, .2], facecolor='k')
n, bins, patches = plt.hist(s, 400, density=True)
plt.title('Probability')
plt.xticks([])
plt.yticks([])
right_inset_ax = fig.add_axes([.65, .6, .2, .2], facecolor='k')
right_inset_ax.hist(s, 400, density=True)
right_inset_ax.set_title('Probability')
right_inset_ax.set_xticks([])
right_inset_ax.set_yticks([])

# this is another inset axes over the main axes
a = plt.axes([0.2, 0.6, .2, .2], facecolor='k')
plt.plot(t[:len(r)], r)
plt.title('Impulse response')
plt.xlim(0, 0.2)
plt.xticks([])
plt.yticks([])
left_inset_ax = fig.add_axes([.2, .6, .2, .2], facecolor='k')
left_inset_ax.plot(t[:len(r)], r)
left_inset_ax.set_title('Impulse response')
left_inset_ax.set_xlim(0, 0.2)
left_inset_ax.set_xticks([])
left_inset_ax.set_yticks([])

plt.show()