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Commit d52bdc3

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tacaswelltacaswell
authored
Merge pull request #8677 from QuLogic/pylab-example-cleanups
DOC: Cleanup of merged pylab examples
2 parents e169aff + 869bd95 commit d52bdc3
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‎examples/animation/image_slices_viewer.py

Copy file name to clipboardExpand all lines: examples/animation/image_slices_viewer.py
+5-4Lines changed: 5 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -5,7 +5,8 @@
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"""
77
from __future__ import print_function
8-
import numpy
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9+
import numpy as np
910
import matplotlib.pyplot as plt
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1112

@@ -24,9 +25,9 @@ def __init__(self, ax, X):
2425
def onscroll(self, event):
2526
print("%s %s" % (event.button, event.step))
2627
if event.button == 'up':
27-
self.ind = numpy.clip(self.ind + 1, 0, self.slices - 1)
28+
self.ind = (self.ind + 1) % self.slices
2829
else:
29-
self.ind = numpy.clip(self.ind - 1, 0, self.slices - 1)
30+
self.ind = (self.ind - 1) % self.slices
3031
self.update()
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3233
def update(self):
@@ -37,7 +38,7 @@ def update(self):
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3839
fig, ax = plt.subplots(1, 1)
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40-
X = numpy.random.rand(20, 20, 40)
41+
X = np.random.rand(20, 20, 40)
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4243
tracker = IndexTracker(ax, X)
4344

‎examples/event_handling/pick_event_demo2.py

Copy file name to clipboardExpand all lines: examples/event_handling/pick_event_demo2.py
+4-4Lines changed: 4 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -7,13 +7,13 @@
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mean vs stddev. When you click on one of the mu, sigma points, plot the raw
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data from the dataset that generated the mean and stddev.
99
"""
10-
import numpy
10+
import numpy as np
1111
import matplotlib.pyplot as plt
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1313

14-
X = numpy.random.rand(100, 1000)
15-
xs = numpy.mean(X, axis=1)
16-
ys = numpy.std(X, axis=1)
14+
X = np.random.rand(100, 1000)
15+
xs = np.mean(X, axis=1)
16+
ys = np.std(X, axis=1)
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1818
fig, ax = plt.subplots()
1919
ax.set_title('click on point to plot time series')

‎examples/event_handling/zoom_window.py

Copy file name to clipboardExpand all lines: examples/event_handling/zoom_window.py
+2-2Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -14,7 +14,7 @@
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points**2, so their size is independent of the zoom
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"""
1616
from matplotlib.pyplot import figure, show
17-
import numpy
17+
import numpy as np
1818
figsrc = figure()
1919
figzoom = figure()
2020

@@ -23,7 +23,7 @@
2323
autoscale_on=False)
2424
axsrc.set_title('Click to zoom')
2525
axzoom.set_title('zoom window')
26-
x, y, s, c = numpy.random.rand(4, 200)
26+
x, y, s, c = np.random.rand(4, 200)
2727
s *= 200
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2929

‎examples/frontpage/membrane.py

Copy file name to clipboardExpand all lines: examples/frontpage/membrane.py
+2-2Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -11,8 +11,8 @@
1111
import numpy as np
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1313

14-
datafile = cbook.get_sample_data('membrane.dat', asfileobj=False)
15-
x = np.fromfile(datafile, np.float32)
14+
with cbook.get_sample_data('membrane.dat') as datafile:
15+
x = np.fromfile(datafile, np.float32)
1616
# 0.0005 is the sample interval
1717

1818
fig, ax = plt.subplots()

‎examples/images_contours_and_fields/image_clip_path.py

Copy file name to clipboardExpand all lines: examples/images_contours_and_fields/image_clip_path.py
+2-2Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -10,8 +10,8 @@
1010
import matplotlib.cbook as cbook
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13-
image_file = cbook.get_sample_data('grace_hopper.png')
14-
image = plt.imread(image_file)
13+
with cbook.get_sample_data('grace_hopper.png') as image_file:
14+
image = plt.imread(image_file)
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1616
fig, ax = plt.subplots()
1717
im = ax.imshow(image)

‎examples/images_contours_and_fields/image_demo.py

Copy file name to clipboardExpand all lines: examples/images_contours_and_fields/image_demo.py
+22-24Lines changed: 22 additions & 24 deletions
Original file line numberDiff line numberDiff line change
@@ -41,8 +41,8 @@
4141
# It is also possible to show images of pictures.
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# A sample image
44-
image_file = cbook.get_sample_data('ada.png')
45-
image = plt.imread(image_file)
44+
with cbook.get_sample_data('ada.png') as image_file:
45+
image = plt.imread(image_file)
4646

4747
fig, ax = plt.subplots()
4848
ax.imshow(image)
@@ -53,19 +53,20 @@
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5454
w, h = 512, 512
5555

56-
datafile = cbook.get_sample_data('ct.raw.gz', asfileobj=True)
57-
s = datafile.read()
56+
with cbook.get_sample_data('ct.raw.gz', asfileobj=True) as datafile:
57+
s = datafile.read()
5858
A = np.fromstring(s, np.uint16).astype(float).reshape((w, h))
5959
A /= A.max()
6060

61+
fig, ax = plt.subplots()
6162
extent = (0, 25, 0, 25)
62-
im = plt.imshow(A, cmap=plt.cm.hot, origin='upper', extent=extent)
63+
im = ax.imshow(A, cmap=plt.cm.hot, origin='upper', extent=extent)
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6465
markers = [(15.9, 14.5), (16.8, 15)]
6566
x, y = zip(*markers)
66-
plt.plot(x, y, 'o')
67+
ax.plot(x, y, 'o')
6768

68-
plt.title('CT density')
69+
ax.set_title('CT density')
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7071
plt.show()
7172

@@ -121,26 +122,21 @@
121122
# suggested.
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123124
A = np.random.rand(5, 5)
124-
plt.figure(1)
125-
plt.imshow(A, interpolation='nearest')
126-
plt.grid(True)
127-
128-
plt.figure(2)
129-
plt.imshow(A, interpolation='bilinear')
130-
plt.grid(True)
131125

132-
plt.figure(3)
133-
plt.imshow(A, interpolation='bicubic')
134-
plt.grid(True)
126+
fig, axs = plt.subplots(1, 3, figsize=(10, 3))
127+
for ax, interp in zip(axs, ['nearest', 'bilinear', 'bicubic']):
128+
ax.imshow(A, interpolation=interp)
129+
ax.set_title(interp.capitalize())
130+
ax.grid(True)
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136132
plt.show()
137133

138134

139135
###############################################################################
140136
# You can specify whether images should be plotted with the array origin
141-
# x[0,0] in the upper left or upper right by using the origin parameter.
142-
# You can also control the default be setting image.origin in your
143-
# matplotlibrc file; see http://matplotlib.org/matplotlibrc
137+
# x[0,0] in the upper left or lower right by using the origin parameter.
138+
# You can also control the default setting image.origin in your
139+
# :ref:`matplotlibrc file <customizing-with-matplotlibrc-files>`
144140

145141
x = np.arange(120).reshape((10, 12))
146142

@@ -166,11 +162,13 @@
166162

167163
path = Path([[0, 1], [1, 0], [0, -1], [-1, 0], [0, 1]])
168164
patch = PathPatch(path, facecolor='none')
169-
plt.gca().add_patch(patch)
170165

171-
im = plt.imshow(Z, interpolation='bilinear', cmap=cm.gray,
172-
origin='lower', extent=[-3, 3, -3, 3],
173-
clip_path=patch, clip_on=True)
166+
fig, ax = plt.subplots()
167+
ax.add_patch(patch)
168+
169+
im = ax.imshow(Z, interpolation='bilinear', cmap=cm.gray,
170+
origin='lower', extent=[-3, 3, -3, 3],
171+
clip_path=patch, clip_on=True)
174172
im.set_clip_path(patch)
175173

176174
plt.show()

‎examples/pylab_examples/ellipse_demo.py

Copy file name to clipboardExpand all lines: examples/pylab_examples/ellipse_demo.py
+6-4Lines changed: 6 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -5,20 +5,22 @@
55
66
"""
77
import matplotlib.pyplot as plt
8-
import numpy.random as rnd
8+
import numpy as np
99
from matplotlib.patches import Ellipse
1010

1111
NUM = 250
1212

13-
ells = [Ellipse(xy=rnd.rand(2)*10, width=rnd.rand(), height=rnd.rand(), angle=rnd.rand()*360)
13+
ells = [Ellipse(xy=np.random.rand(2)*10,
14+
width=np.random.rand(), height=np.random.rand(),
15+
angle=np.random.rand()*360)
1416
for i in range(NUM)]
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1618
fig, ax = plt.subplots(subplot_kw={'aspect': 'equal'})
1719
for e in ells:
1820
ax.add_artist(e)
1921
e.set_clip_box(ax.bbox)
20-
e.set_alpha(rnd.rand())
21-
e.set_facecolor(rnd.rand(3))
22+
e.set_alpha(np.random.rand())
23+
e.set_facecolor(np.random.rand(3))
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2325
ax.set_xlim(0, 10)
2426
ax.set_ylim(0, 10)

‎examples/pylab_examples/fancybox_demo.py

Copy file name to clipboardExpand all lines: examples/pylab_examples/fancybox_demo.py
+3-3Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -93,7 +93,7 @@ def test2(ax):
9393
#p_fancy.set_boxstyle("round", pad=0.1, rounding_size=0.2)
9494

9595
ax.text(0.1, 0.8,
96-
' boxstyle="round,pad=0.1\n rounding\\_size=0.2"',
96+
' boxstyle="round,pad=0.1\n rounding_size=0.2"',
9797
size=10, transform=ax.transAxes)
9898

9999
# draws control points for the fancy box.
@@ -118,7 +118,7 @@ def test3(ax):
118118
ax.add_patch(p_fancy)
119119

120120
ax.text(0.1, 0.8,
121-
' boxstyle="round,pad=0.1"\n mutation\\_scale=2',
121+
' boxstyle="round,pad=0.1"\n mutation_scale=2',
122122
size=10, transform=ax.transAxes)
123123

124124
# draws control points for the fancy box.
@@ -152,7 +152,7 @@ def test4(ax):
152152
ax.add_patch(p_fancy)
153153

154154
ax.text(0.1, 0.8,
155-
' boxstyle="round,pad=0.3"\n mutation\\_aspect=.5',
155+
' boxstyle="round,pad=0.3"\n mutation_aspect=.5',
156156
size=10, transform=ax.transAxes)
157157

158158
draw_bbox(ax, bb)

‎examples/pylab_examples/line_collection.py

Copy file name to clipboardExpand all lines: examples/pylab_examples/line_collection.py
+2-3Lines changed: 2 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -30,7 +30,7 @@
3030
segs = np.ma.masked_where((segs > 50) & (segs < 60), segs)
3131

3232
# We need to set the plot limits.
33-
ax = plt.axes()
33+
fig, ax = plt.subplots()
3434
ax.set_xlim(x.min(), x.max())
3535
ax.set_ylim(ys.min(), ys.max())
3636

@@ -60,7 +60,7 @@
6060
ys = [x + i for i in x]
6161

6262
# We need to set the plot limits, they will not autoscale
63-
ax = plt.axes()
63+
fig, ax = plt.subplots()
6464
ax.set_xlim(np.min(x), np.max(x))
6565
ax.set_ylim(np.min(ys), np.max(ys))
6666

@@ -77,7 +77,6 @@
7777
linestyles='solid')
7878
line_segments.set_array(x)
7979
ax.add_collection(line_segments)
80-
fig = plt.gcf()
8180
axcb = fig.colorbar(line_segments)
8281
axcb.set_label('Line Number')
8382
ax.set_title('Line Collection with mapped colors')

‎examples/pylab_examples/major_minor_demo.py

Copy file name to clipboardExpand all lines: examples/pylab_examples/major_minor_demo.py
+5-5Lines changed: 5 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -47,7 +47,7 @@
4747
s = np.sin(0.1*np.pi*t)*np.exp(-t*0.01)
4848

4949
fig, ax = plt.subplots()
50-
plt.plot(t, s)
50+
ax.plot(t, s)
5151

5252
ax.xaxis.set_major_locator(majorLocator)
5353
ax.xaxis.set_major_formatter(majorFormatter)
@@ -76,12 +76,12 @@
7676
s = np.sin(2*np.pi*t)*np.exp(-t*0.01)
7777

7878
fig, ax = plt.subplots()
79-
plt.plot(t, s)
79+
ax.plot(t, s)
8080

8181
ax.xaxis.set_minor_locator(minorLocator)
8282

83-
plt.tick_params(which='both', width=2)
84-
plt.tick_params(which='major', length=7)
85-
plt.tick_params(which='minor', length=4, color='r')
83+
ax.tick_params(which='both', width=2)
84+
ax.tick_params(which='major', length=7)
85+
ax.tick_params(which='minor', length=4, color='r')
8686

8787
plt.show()

‎examples/pylab_examples/mri_demo.py

Copy file name to clipboardExpand all lines: examples/pylab_examples/mri_demo.py
+3-4Lines changed: 3 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -12,13 +12,12 @@
1212
import matplotlib.cm as cm
1313
import numpy as np
1414

15-
fig, ax = plt.subplots(num="MRI_demo")
1615

1716
# Data are 256x256 16 bit integers
18-
dfile = cbook.get_sample_data('s1045.ima.gz')
19-
im = np.fromstring(dfile.read(), np.uint16).reshape((256, 256))
20-
dfile.close()
17+
with cbook.get_sample_data('s1045.ima.gz') as dfile:
18+
im = np.fromstring(dfile.read(), np.uint16).reshape((256, 256))
2119

20+
fig, ax = plt.subplots(num="MRI_demo")
2221
ax.imshow(im, cmap=cm.gray)
2322
ax.axis('off')
2423

‎examples/pylab_examples/mri_with_eeg.py

Copy file name to clipboardExpand all lines: examples/pylab_examples/mri_with_eeg.py
+4-6Lines changed: 4 additions & 6 deletions
Original file line numberDiff line numberDiff line change
@@ -20,9 +20,8 @@
2020
fig = plt.figure("MRI_with_EEG")
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2222
# Load the MRI data (256x256 16 bit integers)
23-
dfile = cbook.get_sample_data('s1045.ima.gz')
24-
im = np.fromstring(dfile.read(), np.uint16).reshape((256, 256))
25-
dfile.close()
23+
with cbook.get_sample_data('s1045.ima.gz') as dfile:
24+
im = np.fromstring(dfile.read(), np.uint16).reshape((256, 256))
2625

2726
# Plot the MRI image
2827
ax0 = fig.add_subplot(2, 2, 1)
@@ -43,9 +42,8 @@
4342

4443
# Load the EEG data
4544
numSamples, numRows = 800, 4
46-
eegfile = cbook.get_sample_data('eeg.dat', asfileobj=False)
47-
print('Loading EEG %s' % eegfile)
48-
data = np.fromfile(eegfile, dtype=float)
45+
with cbook.get_sample_data('eeg.dat') as eegfile:
46+
data = np.fromfile(eegfile, dtype=float)
4947
data.shape = (numSamples, numRows)
5048
t = 10.0 * np.arange(numSamples) / numSamples
5149

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