DOC: update axes_demo to directly manipulate fig, ax

Matthias Bussonnier · Matthias Bussonnier · commit 7f320b148ec9 · 2019-07-30T16:40:43.000-07:00
Directly call method on each individual axis; instead of the global
``plt.`` one, same to create inset; directly refer to the figure on
which wee create an inset.

I also use some more explicit renaming for each axis,
and remove assignments on the LHS when those were unused as it seem like
a distraction on the subject at hand.
diff --git a/examples/subplots_axes_and_figures/axes_demo.py b/examples/subplots_axes_and_figures/axes_demo.py
@@ -3,7 +3,7 @@
 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.
 """
 import matplotlib.pyplot as plt
 import numpy as np
@@ -19,27 +19,27 @@
 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()
