8000 Use standard NumPy import in pylab examples. · matplotlib/matplotlib@2b9e2d1 · GitHub
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Commit 2b9e2d1

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QuLogicQuLogic
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Use standard NumPy import in pylab examples.
1 parent 1144e8c commit 2b9e2d1

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12 files changed

+40
-40
lines changed

12 files changed

+40
-40
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‎examples/animation/image_slices_viewer.py

Lines changed: 5 additions & 4 deletions
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@@ -5,7 +5,8 @@
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"""
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from __future__ import print_function
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import numpy
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import numpy as np
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import matplotlib.pyplot as plt
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@@ -24,9 +25,9 @@ def __init__(self, ax, X):
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def onscroll(self, event):
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print("%s %s" % (event.button, event.step))
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if event.button == 'up':
27-
self.ind = numpy.clip(self.ind + 1, 0, self.slices - 1)
28+
self.ind = np.clip(self.ind + 1, 0, self.slices - 1)
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else:
29-
self.ind = numpy.clip(self.ind - 1, 0, self.slices - 1)
30+
self.ind = np.clip(self.ind - 1, 0, self.slices - 1)
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self.update()
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def update(self):
@@ -37,7 +38,7 @@ def update(self):
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fig, ax = plt.subplots(1, 1)
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40-
X = numpy.random.rand(20, 20, 40)
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X = np.random.rand(20, 20, 40)
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tracker = IndexTracker(ax, X)
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‎examples/event_handling/pick_event_demo2.py

Lines changed: 4 additions & 4 deletions
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@@ -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.
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"""
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import numpy
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import numpy as np
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import matplotlib.pyplot as plt
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14-
X = numpy.random.rand(100, 1000)
15-
xs = numpy.mean(X, axis=1)
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ys = numpy.std(X, axis=1)
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X = np.random.rand(100, 1000)
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xs = np.mean(X, axis=1)
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ys = np.std(X, axis=1)
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fig, ax = plt.subplots()
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ax.set_title('click on point to plot time series')

‎examples/event_handling/zoom_window.py

Lines changed: 2 additions & 2 deletions
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@@ -14,7 +14,7 @@
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points**2, so their size is independent of the zoom
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"""
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from matplotlib.pyplot import figure, show
17-
import numpy
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import numpy as np
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figsrc = figure()
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figzoom = figure()
2020

@@ -23,7 +23,7 @@
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autoscale_on=False)
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axsrc.set_title('Click to zoom')
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axzoom.set_title('zoom window')
26-
x, y, s, c = numpy.random.rand(4, 200)
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x, y, s, c = np.random.rand(4, 200)
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s *= 200
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‎examples/pylab_examples/ellipse_demo.py

Lines changed: 6 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -5,20 +5,22 @@
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"""
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import matplotlib.pyplot as plt
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import numpy.random as rnd
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import numpy as np
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from matplotlib.patches import Ellipse
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NUM = 250
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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(),
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angle=np.random.rand()*360)
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for i in range(NUM)]
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fig, ax = plt.subplots(subplot_kw={'aspect': 'equal'})
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for e in ells:
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ax.add_artist(e)
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e.set_clip_box(ax.bbox)
20-
e.set_alpha(rnd.rand())
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e.set_facecolor(rnd.rand(3))
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e.set_alpha(np.random.rand())
23+
e.set_facecolor(np.random.rand(3))
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ax.set_xlim(0, 10)
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ax.set_ylim(0, 10)

‎examples/pylab_examples/pcolor_demo.py

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@@ -10,15 +10,15 @@
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"""
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import matplotlib.pyplot as plt
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import numpy as np
13-
from numpy.random import rand
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from matplotlib.colors import LogNorm
1514
from matplotlib.mlab import bivariate_normal
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16+
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###############################################################################
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# A simple pcolor demo
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# --------------------
2020

21-
Z = rand(6, 10)
21+
Z = np.random.rand(6, 10)
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plt.subplot(2, 1, 1)
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c = plt.pcolor(Z)

‎examples/pylab_examples/spy_demos.py

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -7,15 +7,15 @@
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"""
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from matplotlib.pyplot import figure, show
10-
import numpy
10+
import numpy as np
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1212
fig = figure()
1313
ax1 = fig.add_subplot(221)
1414
ax2 = fig.add_subplot(222)
1515
ax3 = fig.add_subplot(223)
1616
ax4 = fig.add_subplot(224)
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18-
x = numpy.random.randn(20, 20)
18+
x = np.random.randn(20, 20)
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x[5] = 0.
2020
x[:, 12] = 0.
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‎examples/pylab_examples/subplot_toolbar.py

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Original file line numberDiff line numberDiff line change
@@ -5,17 +5,17 @@
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"""
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import matplotlib.pyplot as plt
8-
import numpy.random as rnd
8+
import numpy as np
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1010
fig = plt.figure()
1111
plt.subplot(221)
12-
plt.imshow(rnd.random((100, 100)))
12+
plt.imshow(np.random.random((100, 100)))
1313
plt.subplot(222)
14-
plt.imshow(rnd.random((100, 100)))
14+
plt.imshow(np.random.random((100, 100)))
1515
plt.subplot(223)
16-
plt.imshow(rnd.random((100, 100)))
16+
plt.imshow(np.random.random((100, 100)))
1717
plt.subplot(224)
18-
plt.imshow(rnd.random((100, 100)))
18+
plt.imshow(np.random.random((100, 100)))
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2020
plt.subplot_tool()
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plt.show()

‎examples/pylab_examples/tricontour_vs_griddata.py

Lines changed: 3 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -9,16 +9,15 @@
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import matplotlib.pyplot as plt
1010
import matplotlib.tri as tri
1111
import numpy as np
12-
import numpy.random as rnd
1312
import matplotlib.mlab as mlab
1413
import time
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16-
rnd.seed(0)
15+
np.random.seed(0)
1716
npts = 200
1817
ngridx = 100
1918
ngridy = 200
20-
x = rnd.uniform(-2, 2, npts)
21-
y = rnd.uniform(-2, 2, npts)
19+
x = np.random.uniform(-2, 2, npts)
20+
y = np.random.uniform(-2, 2, npts)
2221
z = x*np.exp(-x**2 - y**2)
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2423
# griddata and contour.

‎examples/pylab_examples/vline_hline_demo.py

Lines changed: 1 addition & 2 deletions
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@@ -9,7 +9,6 @@
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import matplotlib.pyplot as plt
1010
from matplotlib.transforms import blended_transform_factory as btf
1111
import numpy as np
12-
import numpy.random as rnd
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1413

1514
def f(t):
@@ -19,7 +18,7 @@ def f(t):
1918

2019
t = np.arange(0.0, 5.0, 0.1)
2120
s = f(t)
22-
nse = rnd.normal(0.0, 0.3, t.shape) * s
21+
nse = np.random.normal(0.0, 0.3, t.shape) * s
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2423
fig = plt.figure(figsize=(12, 6))
2524
vax = fig.add_subplot(121)

‎examples/units/units_sample.py

Lines changed: 2 additions & 2 deletions
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@@ -15,9 +15,9 @@
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"""
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from basic_units import cm, inch
1717
import matplotlib.pyplot as plt
18-
import numpy
18+
import numpy as np
1919

20-
cms = cm * numpy.arange(0, 10, 2)
20+
cms = cm * np.arange(0, 10, 2)
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2222
fig = plt.figure()
2323

‎examples/user_interfaces/histogram_demo_canvasagg_sgskip.py

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@@ -15,16 +15,15 @@
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from matplotlib.backends.backend_agg import FigureCanvasAgg
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from matplotlib.figure import Figure
1717
from matplotlib.mlab import normpdf
18-
from numpy.random import randn
19-
import numpy
18+
import numpy as np
2019

2120
fig = Figure(figsize=(5, 4), dpi=100)
2221
ax = fig.add_subplot(111)
2322

2423
canvas = FigureCanvasAgg(fig)
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2625
mu, sigma = 100, 15
27-
x = mu + sigma*randn(10000)
26+
x = mu + sigma * np.random.randn(10000)
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2928
# the histogram of the data
3029
n, bins, patches = ax.hist(x, 50, normed=1)
@@ -52,7 +51,7 @@
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5352
if 0:
5453
# convert to a numpy array
55-
X = numpy.fromstring(s, numpy.uint8).reshape((h, w, 3))
54+
X = np.fromstring(s, np.uint8).reshape((h, w, 3))
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5756
if 0:
5857
# pass off to PIL

‎examples/userdemo/annotate_text_arrow.py

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@@ -5,16 +5,16 @@
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"""
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8-
import numpy.random
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import numpy as np
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import matplotlib.pyplot as plt
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1111
fig, ax = plt.subplots(figsize=(5, 5))
1212
ax.set_aspect(1)
1313

14-
x1 = -1 + numpy.random.randn(100)
15-
y1 = -1 + numpy.random.randn(100)
16-
x2 = 1. + numpy.random.randn(100)
17-
y2 = 1. + numpy.random.randn(100)
14+
x1 = -1 + np.random.randn(100)
15+
y1 = -1 + np.random.randn(100)
16+
x2 = 1. + np.random.randn(100)
17+
y2 = 1. + np.random.randn(100)
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1919
ax.scatter(x1, y1, color="r")
2020
ax.scatter(x2, y2, color="g")

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