8000 convert some sample plots to use plt.subplots() instead of other methods by asafmaman101 · Pull Request #17340 · matplotlib/matplotlib · GitHub
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convert some sample plots to use plt.subplots() instead of other methods #17340

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Merged
merged 9 commits into from
May 25, 2020
Merged

convert some sample plots to use plt.subplots() instead of other methods #17340

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a2765d5
convert some sample plots to use plt.subplots() instead of other methods
asafmaman101 May 6, 2020
3c4faca
fixing line length
asafmaman101 May 6, 2020
cd25cea
changing the use of gridspec() to avoid repeatation, removing unpacki…
asafmaman101 May 7, 2020
2ae3dd9
fix exeeded line while linting test
asafmaman101 May 7, 2020
1e58203
revert plot_streamplot.py to original version
asafmaman101 May 11, 2020
a664c8a
adding both methods how to generate multiple plots
asafmaman101 May 17, 2020
a9d580e
fix linting
asafmaman101 May 17, 2020
bc444fa
revert xkcd.py
asafmaman101 May 19, 2020
820bbdf
modify heading in subplot.py
asafmaman101 May 25, 2020
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2 changes: 1 addition & 1 deletion examples/pie_and_polar_charts/polar_demo.py
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Original file line number Diff line number Diff line change
Expand Up @@ -12,7 +12,7 @@
r = np.arange(0, 2, 0.01)
theta = 2 * np.pi * r

ax = plt.subplot(111, projection='polar')
fig, ax = plt.subplots(subplot_kw={'projection': 'polar'})
ax.plot(theta, r)
ax.set_rmax(2)
ax.set_rticks([0.5, 1, 1.5, 2]) # Less radial ticks
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8 changes: 4 additions & 4 deletions examples/showcase/xkcd.py
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Expand Up @@ -14,8 +14,8 @@
# Based on "Stove Ownership" from XKCD by Randall Munroe
# https://xkcd.com/418/

fig = plt.figure()
ax = fig.add_axes((0.1, 0.2, 0.8, 0.7))
fig, ax = plt.subplots()
ax.set_position((0.1, 0.2, 0.8, 0.7))
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add_axes() is specifically designed for adding axes at arbitrary locations. IMHO it's the right method to use here. Creating a figure and then creating an axes at a specific position is conceptually simpler than creating a figure and an axes in the default layout and then moving the existing axes raound.

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subplots sets up a gridspec for the underlying axes, whereas if you are just going to move it that gridspec is not needed. So there is some advantage to add_axes here.

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Hi, no problem I can revert it to the original version, but I want to make sure I understand - you suggest to keep it the same way it was in the beginning? or some other method using both subplots and add_axes (if it's feasible, didn't already thought about it to details).

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Hi, no problem I can revert it to the original version, but I want to make sure I understand - you suggest to keep it the same way it was in the beginning? or some other method using both subplots and add_axes (if it's feasible, didn't already thought about it to details).

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That example was already correct as it was originally. Please revert your change.

ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
ax.set_xticks([])
Expand Down Expand Up @@ -44,8 +44,8 @@
# Based on "The Data So Far" from XKCD by Randall Munroe
# https://xkcd.com/373/

fig = plt.figure()
ax = fig.add_axes((0.1, 0.2, 0.8, 0.7))
fig, ax = plt.subplots()
ax.set_position((0.1, 0.2, 0.8, 0.7))
ax.bar([0, 1], [0, 100], 0.25)
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
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29 changes: 29 additions & 0 deletions examples/subplots_axes_and_figures/subplot.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,6 +8,35 @@
import numpy as np
import matplotlib.pyplot as plt

###############################################################################

x1 = np.linspace(0.0, 5.0)
x2 = np.linspace(0.0, 2.0)

y1 = np.cos(2 * np.pi * x1) * np.exp(-x1)
y2 = np.cos(2 * np.pi * x2)

fig, (ax1, ax2) = plt.subplots(2, 1)
fig.suptitle('A tale of 2 subplots')

ax1.plot(x1, y1, 'o-')
ax1.set_ylabel('Damped oscillation')

ax2.plot(x2, y2, '.-')
ax2.set_xlabel('time (s)')
ax2.set_ylabel('Undamped')

plt.show()

#############################################################################
#
#
# Alternative Method For Creating Multiple Plots
# """"""""""
#
# Subplots can also be generated using `subplot()` as in the following example:
#


x1 = np.linspace(0.0, 5.0)
x2 = np.linspace(0.0, 2.0)
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