8000 Consistently use axs to refer to a set of Axes · matplotlib/matplotlib@791ad1b · GitHub
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Commit 791ad1b

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timhoffmtimhoffm
committed
Consistently use axs to refer to a set of Axes
1 parent a4d82fe commit 791ad1b

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27 files changed

+288
-280
lines changed

27 files changed

+288
-280
lines changed

‎examples/color/colormap_reference.py‎

Lines changed: 4 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -48,18 +48,18 @@ def plot_color_gradients(cmap_category, cmap_list):
4848
# Create figure and adjust figure height to number of colormaps
4949
nrows = len(cmap_list)
5050
figh = 0.35 + 0.15 + (nrows + (nrows-1)*0.1)*0.22
51-
fig, axes = plt.subplots(nrows=nrows, figsize=(6.4, figh))
51+
fig, axs = plt.subplots(nrows=nrows, figsize=(6.4, figh))
5252
fig.subplots_adjust(top=1-.35/figh, bottom=.15/figh, left=0.2, right=0.99)
5353

54-
axes[0].set_title(cmap_category + ' colormaps', fontsize=14)
54+
axs[0].set_title(cmap_category + ' colormaps', fontsize=14)
5555

56-
for ax, name in zip(axes, cmap_list):
56+
for ax, name in zip(axs, cmap_list):
5757
ax.imshow(gradient, aspect='auto', cmap=plt.get_cmap(name))
5858
ax.text(-.01, .5, name, va='center', ha='right', fontsize=10,
5959
transform=ax.transAxes)
6060

6161
# Turn off *all* ticks & spines, not just the ones with colormaps.
62-
for ax in axes:
62+
for ax in axs:
6363
ax.set_axis_off()
6464

6565

‎examples/lines_bars_and_markers/marker_reference.py‎

Lines changed: 4 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -39,14 +39,14 @@ def split_list(a_list):
3939
#
4040
# Plot all un-filled markers
4141

42-
fig, axes = plt.subplots(ncols=2)
42+
fig, axs = plt.subplots(ncols=2)
4343
fig.suptitle('un-filled markers', fontsize=14)
4444

4545
# Filter out filled markers and marker settings that do nothing.
4646
unfilled_markers = [m for m, func in Line2D.markers.items()
4747
if func != 'nothing' and m not in Line2D.filled_markers]
4848

49-
for ax, markers in zip(axes, split_list(unfilled_markers)):
49+
for ax, markers in zip(axs, split_list(unfilled_markers)):
5050
for y, marker in enumerate(markers):
5151
ax.text(-0.5, y, repr(marker), **text_style)
5252
ax.plot(y * points, marker=marker, **marker_style)
@@ -58,8 +58,8 @@ def split_list(a_list):
5858
###############################################################################
5959
# Plot all filled markers.
6060

61-
fig, axes = plt.subplots(ncols=2)
62-
for ax, markers in zip(axes, split_list(Line2D.filled_markers)):
61+
fig, axs = plt.subplots(ncols=2)
62+
for ax, markers in zip(axs, split_list(Line2D.filled_markers)):
6363
for y, marker in enumerate(markers):
6464
ax.text(-0.5, y, repr(marker), **text_style)
6565
ax.plot(y * points, marker=marker, **marker_style)

‎examples/lines_bars_and_markers/spectrum_demo.py‎

Lines changed: 14 additions & 14 deletions
Original file line numberDiff line numberDiff line change
@@ -25,28 +25,28 @@
2525

2626
s = 0.1 * np.sin(4 * np.pi * t) + cnse # the signal
2727

28-
fig, axes = plt.subplots(nrows=3, ncols=2, figsize=(7, 7))
28+
fig, axs = plt.subplots(nrows=3, ncols=2, figsize=(7, 7))
2929

3030
# plot time signal:
31-
axes[0, 0].set_title("Signal")
32-
axes[0, 0].plot(t, s, color='C0')
33-
axes[0, 0].set_xlabel("Time")
34-
axes[0, 0].set_ylabel("Amplitude")
31+
axs[0, 0].set_title("Signal")
32+
axs[0, 0].plot(t, s, color='C0')
33+
axs[0, 0].set_xlabel("Time")
34+
axs[0, 0].set_ylabel("Amplitude")
3535

3636
# plot different spectrum types:
37-
axes[1, 0].set_title("Magnitude Spectrum")
38-
axes[1, 0].magnitude_spectrum(s, Fs=Fs, color='C1')
37+
axs[1, 0].set_title("Magnitude Spectrum")
38+
axs[1, 0].magnitude_spectrum(s, Fs=Fs, color='C1')
3939

40-
axes[1, 1].set_title("Log. Magnitude Spectrum")
41-
axes[1, 1].magnitude_spectrum(s, Fs=Fs, scale='dB', color='C1')
40+
axs[1, 1].set_title("Log. Magnitude Spectrum")
41+
axs[1, 1].magnitude_spectrum(s, Fs=Fs, scale='dB', color='C1')
4242

43-
axes[2, 0].set_title("Phase Spectrum ")
44-
axes[2, 0].phase_spectrum(s, Fs=Fs, color='C2')
43+
axs[2, 0].set_title("Phase Spectrum ")
44+
axs[2, 0].phase_spectrum(s, Fs=Fs, color='C2')
4545

46-
axes[2, 1].set_title("Angle Spectrum")
47-
axes[2, 1].angle_spectrum(s, Fs=Fs, color='C2')
46+
axs[2, 1].set_title("Angle Spectrum")
47+
axs[2, 1].angle_spectrum(s, Fs=Fs, color='C2')
4848

49-
axes[0, 1].remove() # don't display empty ax
49+
axs[0, 1].remove() # don't display empty ax
5050

5151
fig.tight_layout()
5252
plt.show()

‎examples/scales/power_norm.py‎

Lines changed: 5 additions & 6 deletions
Original file line numberDiff line numberDiff line change
@@ -19,15 +19,14 @@
1919

2020
gammas = [0.8, 0.5, 0.3]
2121

22-
fig, axes = plt.subplots(nrows=2, ncols=2)
22+
fig, axs = plt.subplots(nrows=2, ncols=2)
2323

24-
axes[0, 0].set_title('Linear normalization')
25-
axes[0, 0].hist2d(data[:, 0], data[:, 1], bins=100)
24+
axs[0, 0].set_title('Linear normalization')
25+
axs[0, 0].hist2d(data[:, 0], data[:, 1], bins=100)
2626

27-
for ax, gamma in zip(axes.flat[1:], gammas):
27+
for ax, gamma in zip(axs.flat[1:], gammas):
2828
ax.set_title(r'Power law $(\gamma=%1.1f)$' % gamma)
29-
ax.hist2d(data[:, 0], data[:, 1],
30-
bins=100, norm=mcolors.PowerNorm(gamma))
29+
ax.hist2d(data[:, 0], data[:, 1], bins=100, norm=mcolors.PowerNorm(gamma))
3130

3231
fig.tight_layout()
3332

‎examples/shapes_and_collections/collections.py‎

Lines changed: 1 addition & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -43,10 +43,9 @@
4343
colors = [colors.to_rgba(c)
4444
for c in plt.rcParams['axes.prop_cycle'].by_key()['color']]
4545

46-
fig, axes = plt.subplots(2, 2)
46+
fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2)
4747
fig.subplots_adjust(top=0.92, left=0.07, right=0.97,
4848
hspace=0.3, wspace=0.3)
49-
((ax1, ax2), (ax3, ax4)) = axes # unpack the axes
5049

5150

5251
col = collections.LineCollection([spiral], offsets=xyo,

‎examples/specialty_plots/radar_chart.py‎

Lines changed: 5 additions & 6 deletions
Original file line numberDiff line numberDiff line change
@@ -162,13 +162,13 @@ def example_data():
162162
data = example_data()
163163
spoke_labels = data.pop(0)
164164

165-
fig, axes = plt.subplots(figsize=(9, 9), nrows=2, ncols=2,
166-
subplot_kw=dict(projection='radar'))
165+
fig, axs = plt.subplots(figsize=(9, 9), nrows=2, ncols=2,
166+
subplot_kw=dict(projection='radar'))
167167
fig.subplots_adjust(wspace=0.25, hspace=0.20, top=0.85, bottom=0.05)
168168

169169
colors = ['b', 'r', 'g', 'm', 'y']
170170
# Plot the four cases from the example data on separate axes
171-
for ax, (title, case_data) in zip(axes.flat, data):
171+
for ax, (title, case_data) in zip(axs.flat, data):
172172
ax.set_rgrids([0.2, 0.4, 0.6, 0.8])
173173
ax.set_title(title, weight='bold', size='medium', position=(0.5, 1.1),
174174
horizontalalignment='center', verticalalignment='center')
@@ -178,10 +178,9 @@ def example_data():
178178
ax.set_varlabels(spoke_labels)
179179

180180
# add legend relative to top-left plot
181-
ax = axes[0, 0]
182181
labels = ('Factor 1', 'Factor 2', 'Factor 3', 'Factor 4', 'Factor 5')
183-
legend = ax.legend(labels, loc=(0.9, .95),
184-
labelspacing=0.1, fontsize='small')
182+
legend = axs[0, 0].legend(labels, loc=(0.9, .95),
183+
labelspacing=0.1, fontsize='small')
185184

186185
fig.text(0.5, 0.965, '5-Factor Solution Profiles Across Four Scenarios',
187186
horizontalalignment='center', color='black', weight='bold',

‎examples/specialty_plots/topographic_hillshading.py‎

Lines changed: 11 additions & 11 deletions
Original file line numberDiff line numberDiff line change
@@ -44,11 +44,11 @@
4444
ls = LightSource(azdeg=315, altdeg=45)
4545
cmap = plt.cm.gist_earth
4646

47-
fig, axes = plt.subplots(nrows=4, ncols=3, figsize=(8, 9))
48-
plt.setp(axes.flat, xticks=[], yticks=[])
47+
fig, axs = plt.subplots(nrows=4, ncols=3, figsize=(8, 9))
48+
plt.setp(axs.flat, xticks=[], yticks=[])
4949

5050
# Vary vertical exaggeration and blend mode and plot all combinations
51-
for col, ve in zip(axes.T, [0.1, 1, 10]):
51+
for col, ve in zip(axs.T, [0.1, 1, 10]):
5252
# Show the hillshade intensity image in the first row
5353
col[0].imshow(ls.hillshade(z, vert_exag=ve, dx=dx, dy=dy), cmap='gray')
5454

@@ -59,18 +59,18 @@
5959
ax.imshow(rgb)
6060

6161
# Label rows and columns
62-
for ax, ve in zip(axes[0], [0.1, 1, 10]):
62+
for ax, ve in zip(axs[0], [0.1, 1, 10]):
6363
ax.set_title('{0}'.format(ve), size=18)
64-
for ax, mode in zip(axes[:, 0], ['Hillshade', 'hsv', 'overlay', 'soft']):
64+
for ax, mode in zip(axs[:, 0], ['Hillshade', 'hsv', 'overlay', 'soft']):
6565
ax.set_ylabel(mode, size=18)
6666

6767
# Group labels...
68-
axes[0, 1].annotate('Vertical Exaggeration', (0.5, 1), xytext=(0, 30),
69-
textcoords='offset points', xycoords='axes fraction',
70-
ha='center', va='bottom', size=20)
71-
axes[2, 0].annotate('Blend Mode', (0, 0.5), xytext=(-30, 0),
72-
textcoords='offset points', xycoords='axes fraction',
73-
ha='right', va='center', size=20, rotation=90)
68+
axs[0, 1].annotate('Vertical Exaggeration', (0.5, 1), xytext=(0, 30),
69+
textcoords='offset points', xycoords='axes fraction',
70+
ha='center', va='bottom', size=20)
71+
axs[2, 0].annotate('Blend Mode', (0, 0.5), xytext=(-30, 0),
72+
textcoords='offset points', xycoords='axes fraction',
73+
ha='right', va='center', size=20, rotation=90)
7474
fig.subplots_adjust(bottom=0.05, right=0.95)
7575

7676
plt.show()

‎examples/statistics/boxplot.py‎

Lines changed: 30 additions & 30 deletions
Original file line numberDiff line numberDiff line change
@@ -28,27 +28,27 @@
2828
###############################################################################
2929
# Demonstrate how to toggle the display of different elements:
3030

31-
fig, axes = plt.subplots(nrows=2, ncols=3, figsize=(6, 6), sharey=True)
32-
axes[0, 0].boxplot(data, labels=labels)
33-
axes[0, 0].set_title('Default', fontsize=fs)
31+
fig, axs = plt.subplots(nrows=2, ncols=3, figsize=(6, 6), sharey=True)
32+
axs[0, 0].boxplot(data, labels=labels)
33+
axs[0, 0].set_title('Default', fontsize=fs)
3434

35-
axes[0, 1].boxplot(data, labels=labels, showmeans=True)
36-
axes[0, 1].set_title('showmeans=True', fontsize=fs)
35+
axs[0, 1].boxplot(data, labels=labels, showmeans=True)
36+
axs[0, 1].set_title('showmeans=True', fontsize=fs)
3737

38-
axes[0, 2].boxplot(data, labels=labels, showmeans=True, meanline=True)
39-
axes[0, 2].set_title('showmeans=True,\nmeanline=True', fontsize=fs)
38+
axs[0, 2].boxplot(data, labels=labels, showmeans=True, meanline=True)
39+
axs[0, 2].set_title('showmeans=True,\nmeanline=True', fontsize=fs)
4040

41-
axes[1, 0].boxplot(data, labels=labels, showbox=False, showcaps=False)
41+
axs[1, 0].boxplot(data, labels=labels, showbox=False, showcaps=False)
4242
tufte_title = 'Tufte Style \n(showbox=False,\nshowcaps=False)'
43-
axes[1, 0].set_title(tufte_title, fontsize=fs)
43+
axs[1, 0].set_title(tufte_title, fontsize=fs)
4444

45-
axes[1, 1].boxplot(data, labels=labels, notch=True, bootstrap=10000)
46-
axes[1, 1].set_title('notch=True,\nbootstrap=10000', fontsize=fs)
45+
axs[1, 1].boxplot(data, labels=labels, notch=True, bootstrap=10000)
46+
axs[1, 1].set_title('notch=True,\nbootstrap=10000', fontsize=fs)
4747

48-
axes[1, 2].boxplot(data, labels=labels, showfliers=False)
49-
axes[1, 2].set_title('showfliers=False', fontsize=fs)
48+
axs[1, 2].boxplot(data, labels=labels, showfliers=False)
49+
axs[1, 2].set_title('showfliers=False', fontsize=fs)
5050

51-
for ax in axes.flat:
51+
for ax in axs.flat:
5252
ax.set_yscale('log')
5353
ax.set_yticklabels([])
5454

@@ -67,28 +67,28 @@
6767
markerfacecolor='firebrick')
6868
meanlineprops = dict(linestyle='--', linewidth=2.5, color='purple')
6969

70-
fig, axes = plt.subplots(nrows=2, ncols=3, figsize=(6, 6), sharey=True)
71-
axes[0, 0].boxplot(data, boxprops=boxprops)
72-
axes[0, 0].set_title('Custom boxprops', fontsize=fs)
70+
fig, axs = plt.subplots(nrows=2, ncols=3, figsize=(6, 6), sharey=True)
71+
axs[0, 0].boxplot(data, boxprops=boxprops)
72+
axs[0, 0].set_title('Custom boxprops', fontsize=fs)
7373

74-
axes[0, 1].boxplot(data, flierprops=flierprops, medianprops=medianprops)
75-
axes[0, 1].set_title('Custom medianprops\nand flierprops', fontsize=fs)
74+
axs[0, 1].boxplot(data, flierprops=flierprops, medianprops=medianprops)
75+
axs[0, 1].set_title('Custom medianprops\nand flierprops', fontsize=fs)
7676

77-
axes[0, 2].boxplot(data, whis='range')
78-
axes[0, 2].set_title('whis="range"', fontsize=fs)
77+
axs[0, 2].boxplot(data, whis='range')
78+
axs[0, 2].set_title('whis="range"', fontsize=fs)
7979

80-
axes[1, 0].boxplot(data, meanprops=meanpointprops, meanline=False,
81-
showmeans=True)
82-
axes[1, 0].set_title('Custom mean\nas point', fontsize=fs)
80+
axs[1, 0].boxplot(data, meanprops=meanpointprops, meanline=False,
81+
showmeans=True)
82+
axs[1, 0].set_title('Custom mean\nas point', fontsize=fs)
8383

84-
axes[1, 1].boxplot(data, meanprops=meanlineprops, meanline=True,
85-
showmeans=True)
86-
axes[1, 1].set_title('Custom mean\nas line', fontsize=fs)
84+
axs[1, 1].boxplot(data, meanprops=meanlineprops, meanline=True,
85+
showmeans=True)
86+
axs[1, 1].set_title('Custom mean\nas line', fontsize=fs)
8787

88-
axes[1, 2].boxplot(data, whis=[15, 85])
89-
axes[1, 2].set_title('whis=[15, 85]\n#percentiles', fontsize=fs)
88+
axs[1, 2].boxplot(data, whis=[15, 85])
89+
axs[1, 2].set_title('whis=[15, 85]\n#percentiles', fontsize=fs)
9090

91-
for ax in axes.flat:
91+
for ax in axs.flat:
9292
ax.set_yscale('log')
9393
ax.set_yticklabels([])
9494

‎examples/statistics/boxplot_color.py‎

Lines changed: 13 additions & 13 deletions
Original file line numberDiff line numberDiff line change
@@ -21,22 +21,22 @@
2121
all_data = [np.random.normal(0, std, size=100) for std in range(1, 4)]
2222
labels = ['x1', 'x2', 'x3']
2323

24-
fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(9, 4))
24+
fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2, figsize=(9, 4))
2525

2626
# rectangular box plot
27-
bplot1 = axes[0].boxplot(all_data,
28-
vert=True, # vertical box alignment
29-
patch_artist=True, # fill with color
30-
labels=labels) # will be used to label x-ticks
31-
axes[0].set_title('Rectangular box plot')
27+
bplot1 = ax1.boxplot(all_data,
28+
vert=True, # vertical box alignment
29+
patch_artist=True, # fill with color
30+
labels=labels) # will be used to label x-ticks
31+
ax1.set_title('Rectangular box plot')
3232

3333
# notch shape box plot
34-
bplot2 = axes[1].boxplot(all_data,
35-
notch=True, # notch shape
36-
vert=True, # vertical box alignment
37-
patch_artist=True, # fill with color
38-
labels=labels) # will be used to label x-ticks
39-
axes[1].set_title('Notched box plot')
34+
bplot2 = ax2.boxplot(all_data,
35+
notch=True, # notch shape
36+
vert=True, # vertical box alignment
37+
patch_artist=True, # fill with color
38+
labels=labels) # will be used to label x-ticks
39+
ax2.set_title('Notched box plot')
4040

4141
# fill with colors
4242
colors = ['pink', 'lightblue', 'lightgreen']
@@ -45,7 +45,7 @@
4545
patch.set_facecolor(color)
4646

4747
# adding horizontal grid lines
48-
for ax in axes:
48+
for ax in [ax1, ax2]:
4949
ax.yaxis.grid(True)
5050
ax.set_xlabel('Three separate samples')
5151
ax.set_ylabel('Observed values')

‎examples/statistics/boxplot_vs_violin.py‎

Lines changed: 9 additions & 9 deletions
Original file line numberDiff line numberDiff line change
@@ -23,7 +23,7 @@
2323
import matplotlib.pyplot as plt
2424
import numpy as np
2525

26-
fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(9, 4))
26+
fig, axs = plt.subplots(nrows=1, ncols=2, figsize=(9, 4))
2727

2828
# Fixing random state for reproducibility
2929
np.random.seed(19680801)
@@ -33,23 +33,23 @@
3333
all_data = [np.random.normal(0, std, 100) for std in range(6, 10)]
3434

3535
# plot violin plot
36-
axes[0].violinplot(all_data,
37-
showmeans=False,
38-
showmedians=True)
39-
axes[0].set_title('Violin plot')
36+
axs[0].violinplot(all_data,
37+
showmeans=False,
38+
showmedians=True)
39+
axs[0].set_title('Violin plot')
4040

4141
# plot box plot
42-
axes[1].boxplot(all_data)
43-
axes[1].set_title('Box plot')
42+
axs[1].boxplot(all_data)
43+
axs[1].set_title('Box plot')
4444

4545
# adding horizontal grid lines
46-
for ax in axes:
46+
for ax in axs:
4747
ax.yaxis.grid(True)
4848
ax.set_xticks([y + 1 for y in range(len(all_data))])
4949
ax.set_xlabel('Four separate samples')
5050
ax.set_ylabel('Observed values')
5151

5252
# add x-tick labels
53-
plt.setp(axes, xticks=[y + 1 for y in range(len(all_data))],
53+
plt.setp(axs, xticks=[y + 1 for y in range(len(all_data))],
5454
xticklabels=['x1', 'x2', 'x3', 'x4'])
5555
plt.show()

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