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anntzeranntzer
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Various examples updates.
- don't import out of pyplot or numpy, import as plt/np. - move some examples to use subplots() instead of add_subplot. - set random seed for some examples. - fix some docstrings.
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‎examples/api/font_file.py

+2-1
Original file line numberDiff line numberDiff line change
@@ -15,7 +15,8 @@
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"""
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1717
import os
18-
from matplotlib import font_manager as fm, pyplot as plt, rcParams
18+
from matplotlib import font_manager as fm, rcParams
19+
import matplotlib.pyplot as plt
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2021
fig, ax = plt.subplots()
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‎examples/api/power_norm.py

+1-1
Original file line numberDiff line numberDiff line change
@@ -7,7 +7,7 @@
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"""
99

10-
from matplotlib import pyplot as plt
10+
import matplotlib.pyplot as plt
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import matplotlib.colors as mcolors
1212
import numpy as np
1313
from numpy.random import multivariate_normal

‎examples/axes_grid1/demo_colorbar_with_axes_divider.py

+3-7
Original file line numberDiff line numberDiff line change
@@ -4,27 +4,23 @@
44
===============================
55
66
"""
7+
78
import matplotlib.pyplot as plt
89
from mpl_toolkits.axes_grid1.axes_divider import make_axes_locatable
9-
1010
from mpl_toolkits.axes_grid1.colorbar import colorbar
11-
# from matplotlib.pyplot import colorbar
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13-
fig = plt.figure(1, figsize=(6, 3))
12+
fig, (ax1, ax2) = plt.subplots(1, 2)
1413
fig.subplots_adjust(wspace=0.5)
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16-
ax1 = fig.add_subplot(121)
1715
im1 = ax1.imshow([[1, 2], [3, 4]])
18-
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ax1_divider = make_axes_locatable(ax1)
2017
cax1 = ax1_divider.append_axes("right", size="7%", pad="2%")
2118
cb1 = colorbar(im1, cax=cax1)
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23-
ax2 = fig.add_subplot(122)
2420
im2 = ax2.imshow([[1, 2], [3, 4]])
25-
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ax2_divider = make_axes_locatable(ax2)
2722
cax2 = ax2_divider.append_axes("top", size="7%", pad="2%")
2823
cb2 = colorbar(im2, cax=cax2, orientation="horizontal")
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cax2.xaxis.set_ticks_position("top")
25+
3026
plt.show()

‎examples/event_handling/lasso_demo.py

+8-6
Original file line numberDiff line numberDiff line change
@@ -10,13 +10,12 @@
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This is currently a proof-of-concept implementation (though it is
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usable as is). There will be some refinement of the API.
1212
"""
13-
from matplotlib.widgets import Lasso
14-
from matplotlib.collections import RegularPolyCollection
15-
from matplotlib import colors as mcolors, path
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14+
from matplotlib import colors as mcolors, path
15+
from matplotlib.collections import RegularPolyCollection
1716
import matplotlib.pyplot as plt
18-
from numpy import nonzero
19-
from numpy.random import rand
17+
from matplotlib.widgets import Lasso
18+
import numpy as np
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class Datum(object):
@@ -77,9 +76,12 @@ def onpress(self, event):
7776
# acquire a lock on the widget drawing
7877
self.canvas.widgetlock(self.lasso)
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79+
8080
if __name__ == '__main__':
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82-
data = [Datum(*xy) for xy in rand(100, 2)]
82+
np.random.seed(19680801)
83+
84+
data = [Datum(*xy) for xy in np.random.rand(100, 2)]
8385
ax = plt.axes(xlim=(0, 1), ylim=(0, 1), autoscale_on=False)
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ax.set_title('Lasso points using left mouse button')
8587

‎examples/event_handling/pick_event_demo2.py

+3-4
Original file line numberDiff line numberDiff line change
@@ -29,11 +29,10 @@ def onpick(event):
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if not N:
3030
return True
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32-
figi = plt.figure()
33-
for subplotnum, dataind in enumerate(event.ind):
34-
ax = figi.add_subplot(N, 1, subplotnum + 1)
32+
figi, axs = plt.subplots(N, squeeze=False)
33+
for ax, dataind in zip(axs.flat, event.ind):
3534
ax.plot(X[dataind])
36-
ax.text(0.05, 0.9, 'mu=%1.3f\nsigma=%1.3f' % (xs[dataind], ys[dataind]),
35+
ax.text(.05, .9, 'mu=%1.3f\nsigma=%1.3f' % (xs[dataind], ys[dataind]),
3736
transform=ax.transAxes, va='top')
3837
ax.set_ylim(-0.5, 1.5)
3938
figi.show()

‎examples/event_handling/zoom_window.py

+16-16
Original file line numberDiff line numberDiff line change
@@ -6,27 +6,27 @@
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This example shows how to connect events in one window, for example, a mouse
77
press, to another figure window.
88
9-
If you click on a point in the first window, the z and y limits of the
10-
second will be adjusted so that the center of the zoom in the second
11-
window will be the x,y coordinates of the clicked point.
9+
If you click on a point in the first window, the z and y limits of the second
10+
will be adjusted so that the center of the zoom in the second window will be
11+
the x,y coordinates of the clicked point.
1212
13-
Note the diameter of the circles in the scatter are defined in
14-
points**2, so their size is independent of the zoom
13+
Note the diameter of the circles in the scatter are defined in points**2, so
14+
their size is independent of the zoom.
1515
"""
16-
from matplotlib.pyplot import figure, show
16+
17+
import matplotlib.pyplot as plt
1718
import numpy as np
18-
figsrc = figure()
19-
figzoom = figure()
20-
21-
axsrc = figsrc.add_subplot(111, xlim=(0, 1), ylim=(0, 1), autoscale_on=False)
22-
axzoom = figzoom.add_subplot(111, xlim=(0.45, 0.55), ylim=(0.4, .6),
23-
autoscale_on=False)
24-
axsrc.set_title('Click to zoom')
25-
axzoom.set_title('zoom window')
19+
20+
figsrc, axsrc = plt.subplots()
21+
figzoom, axzoom = plt.subplots()
22+
axsrc.set(xlim=(0, 1), ylim=(0, 1), autoscale_on=False,
23+
title='Click to zoom')
24+
axzoom.set(xlim=(0.45, 0.55), ylim=(0.4, 0.6), autoscale_on=False,
25+
title='Zoom window')
26+
2627
x, y, s, c = np.random.rand(4, 200)
2728
s *= 200
2829

29-
3030
axsrc.scatter(x, y, s, c)
3131
axzoom.scatter(x, y, s, c)
3232

@@ -40,4 +40,4 @@ def onpress(event):
4040
figzoom.canvas.draw()
4141

4242
figsrc.canvas.mpl_connect('button_press_event', onpress)
43-
show()
43+
plt.show()

‎examples/images_contours_and_fields/multi_image.py

+2-1
Original file line numberDiff line numberDiff line change
@@ -6,7 +6,8 @@
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Make a set of images with a single colormap, norm, and colorbar.
77
"""
88

9-
from matplotlib import colors, pyplot as plt
9+
from matplotlib import colors
10+
import matplotlib.pyplot as plt
1011
import numpy as np
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1213
np.random.seed(19680801)

‎examples/lines_bars_and_markers/eventplot_demo.py

+9-14
Original file line numberDiff line numberDiff line change
@@ -32,18 +32,15 @@
3232
lineoffsets1 = np.array([-15, -3, 1, 1.5, 6, 10])
3333
linelengths1 = [5, 2, 1, 1, 3, 1.5]
3434

35-
fig = plt.figure()
35+
fig, axs = plt.subplots(2, 2)
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3737
# create a horizontal plot
38-
ax1 = fig.add_subplot(221)
39-
ax1.eventplot(data1, colors=colors1, lineoffsets=lineoffsets1,
40-
linelengths=linelengths1)
41-
38+
axs[0, 0].eventplot(data1, colors=colors1, lineoffsets=lineoffsets1,
39+
linelengths=linelengths1)
4240

4341
# create a vertical plot
44-
ax2 = fig.add_subplot(223)
45-
ax2.eventplot(data1, colors=colors1, lineoffsets=lineoffsets1,
46-
linelengths=linelengths1, orientation='vertical')
42+
axs[1, 0].eventplot(data1, colors=colors1, lineoffsets=lineoffsets1,
43+
linelengths=linelengths1, orientation='vertical')
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4845
# create another set of random data.
4946
# the gamma distribution is only used fo aesthetic purposes
@@ -57,14 +54,12 @@
5754
linelengths2 = 1
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5956
# create a horizontal plot
60-
ax1 = fig.add_subplot(222)
61-
ax1.eventplot(data2, colors=colors2, lineoffsets=lineoffsets2,
62-
linelengths=linelengths2)
57+
axs[0, 1].eventplot(data2, colors=colors2, lineoffsets=lineoffsets2,
58+
linelengths=linelengths2)
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6460

6561
# create a vertical plot
66-
ax2 = fig.add_subplot(224)
67-
ax2.eventplot(data2, colors=colors2, lineoffsets=lineoffsets2,
68-
linelengths=linelengths2, orientation='vertical')
62+
axs[1, 1].eventplot(data2, colors=colors2, lineoffsets=lineoffsets2,
63+
linelengths=linelengths2, orientation='vertical')
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7065
plt.show()

‎examples/lines_bars_and_markers/gradient_bar.py

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@@ -5,8 +5,9 @@
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"""
77
import matplotlib.pyplot as plt
8-
from numpy import arange
9-
from numpy.random import rand
8+
import numpy as np
9+
10+
np.random.seed(19680801)
1011

1112

1213
def gbar(ax, x, y, width=0.5, bottom=0):
@@ -17,20 +18,19 @@ def gbar(ax, x, y, width=0.5, bottom=0):
1718
extent=(left, right, bottom, top), alpha=1)
1819

1920

20-
fig = plt.figure()
21-
2221
xmin, xmax = xlim = 0, 10
2322
ymin, ymax = ylim = 0, 1
24-
ax = fig.add_subplot(111, xlim=xlim, ylim=ylim,
25-
autoscale_on=False)
26-
X = [[.6, .6], [.7, .7]]
2723

24+
fig, ax = plt.subplots()
25+
ax.set(xlim=xlim, ylim=ylim, autoscale_on=False)
26+
27+
X = [[.6, .6], [.7, .7]]
2828
ax.imshow(X, interpolation='bicubic', cmap=plt.cm.copper,
2929
extent=(xmin, xmax, ymin, ymax), alpha=1)
3030

3131
N = 10
32-
x = arange(N) + 0.25
33-
y = rand(N)
32+
x = np.arange(N) + 0.25
33+
y = np.random.rand(N)
3434
gbar(ax, x, y, width=0.7)
3535
ax.set_aspect('auto')
3636
plt.show()

‎examples/lines_bars_and_markers/interp_demo.py

+4-4
Original file line numberDiff line numberDiff line change
@@ -5,13 +5,13 @@
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66
"""
77
import matplotlib.pyplot as plt
8-
from numpy import pi, sin, linspace
8+
import numpy as np
99
from matplotlib.mlab import stineman_interp
1010

11-
x = linspace(0, 2*pi, 20)
12-
y = sin(x)
11+
x = np.linspace(0, 2*np.pi, 20)
12+
y = np.sin(x)
1313
yp = None
14-
xi = linspace(x[0], x[-1], 100)
14+
xi = np.linspace(x[0], x[-1], 100)
1515
yi = stineman_interp(xi, x, y, yp)
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1717
fig, ax = plt.subplots()

‎examples/lines_bars_and_markers/scatter_symbol.py

+1-1
Original file line numberDiff line numberDiff line change
@@ -4,7 +4,7 @@
44
==============
55
66
"""
7-
from matplotlib import pyplot as plt
7+
import matplotlib.pyplot as plt
88
import numpy as np
99
import matplotlib
1010

‎examples/lines_bars_and_markers/simple_plot.py

+2-1
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@@ -5,6 +5,7 @@
55
66
Create a simple plot.
77
"""
8+
89
import matplotlib.pyplot as plt
910
import numpy as np
1011

@@ -13,7 +14,7 @@
1314
s = 1 + np.sin(2 * np.pi * t)
1415

1516
# Note that using plt.subplots below is equivalent to using
16-
# fig = plt.figure and then ax = fig.add_subplot(111)
17+
# fig = plt.figure() and then ax = fig.add_subplot(111)
1718
fig, ax = plt.subplots()
1819
ax.plot(t, s)
1920

‎examples/misc/pythonic_matplotlib.py

+7-12
Original file line numberDiff line numberDiff line change
@@ -14,7 +14,6 @@
1414
instances, managing the bounding boxes of the figure elements,
1515
creating and realizing GUI windows and embedding figures in them.
1616
17-
1817
If you are an application developer and want to embed matplotlib in
1918
your application, follow the lead of examples/embedding_in_wx.py,
2019
examples/embedding_in_gtk.py or examples/embedding_in_tk.py. In this
@@ -55,30 +54,26 @@
5554
a.set_yticks([])
5655
"""
5756

57+
import matplotlib.pyplot as plt
58+
import numpy as np
5859

59-
from matplotlib.pyplot import figure, show
60-
from numpy import arange, sin, pi
61-
62-
t = arange(0.0, 1.0, 0.01)
60+
t = np.arange(0.0, 1.0, 0.01)
6361

64-
fig = figure(1)
62+
fig, (ax1, ax2) = plt.subplots(2)
6563

66-
ax1 = fig.add_subplot(211)
67-
ax1.plot(t, sin(2*pi * t))
64+
ax1.plot(t, np.sin(2*np.pi * t))
6865
ax1.grid(True)
6966
ax1.set_ylim((-2, 2))
7067
ax1.set_ylabel('1 Hz')
7168
ax1.set_title('A sine wave or two')
7269

7370
ax1.xaxis.set_tick_params(labelcolor='r')
7471

75-
76-
ax2 = fig.add_subplot(212)
77-
ax2.plot(t, sin(2 * 2*pi * t))
72+
ax2.plot(t, np.sin(2 * 2*np.pi * t))
7873
ax2.grid(True)
7974
ax2.set_ylim((-2, 2))
8075
l = ax2.set_xlabel('Hi mom')
8176
l.set_color('g')
8277
l.set_fontsize('large')
8378

84-
show()
79+
plt.show()

‎examples/mplot3d/surface3d_radial.py

+1-1
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@@ -11,7 +11,7 @@
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'''
1212

1313
from mpl_toolkits.mplot3d import Axes3D
14-
from matplotlib import pyplot as plt
14+
import matplotlib.pyplot as plt
1515
import numpy as np
1616

1717

‎examples/pie_and_polar_charts/nested_pie.py

+1-1
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@@ -8,7 +8,7 @@
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99
"""
1010

11-
from matplotlib import pyplot as plt
11+
import matplotlib.pyplot as plt
1212
import numpy as np
1313

1414
###############################################################################

‎examples/pie_and_polar_charts/polar_legend.py

+7-6
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@@ -5,16 +5,17 @@
55
66
Demo of a legend on a polar-axis plot.
77
"""
8+
9+
import matplotlib.pyplot as plt
810
import numpy as np
9-
from matplotlib.pyplot import figure, show, rc
1011

1112
# radar green, solid grid lines
12-
rc('grid', color='#316931', linewidth=1, linestyle='-')
13-
rc('xtick', labelsize=15)
14-
rc('ytick', labelsize=15)
13+
plt.rc('grid', color='#316931', linewidth=1, linestyle='-')
14+
plt.rc('xtick', labelsize=15)
15+
plt.rc('ytick', labelsize=15)
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1617
# force square figure and square axes looks better for polar, IMO
17-
fig = figure(figsize=(8, 8))
18+
fig = plt.figure(figsize=(8, 8))
1819
ax = fig.add_axes([0.1, 0.1, 0.8, 0.8],
1920
projection='polar', facecolor='#d5de9c')
2021

@@ -24,4 +25,4 @@
2425
ax.plot(0.5 * theta, r, color='blue', ls='--', lw=3, label='another line')
2526
ax.legend()
2627

27-
show()
28+
plt.show()

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