matplotlib · jenshnielsen · Jul 12, 2015 · Jul 11, 2015 · Jul 11, 2015 · Jul 12, 2015
diff --git a/examples/pylab_examples/shared_axis_across_figures.py b/examples/pylab_examples/shared_axis_across_figures.py
@@ -3,18 +3,17 @@
 another.  This is not the right way to do this for two axes in the
 same figure -- use the sharex and sharey property in that case
 """
-# -*- noplot -*-
-import numpy
-from pylab import figure, show
+import numpy as np
+import matplotlib.pyplot as plt

-fig1 = figure()
-fig2 = figure()
+fig1 = plt.figure()
+fig2 = plt.figure()

 ax1 = fig1.add_subplot(111)
 ax2 = fig2.add_subplot(111, sharex=ax1, sharey=ax1)

-ax1.plot(numpy.random.rand(100), 'o')
-ax2.plot(numpy.random.rand(100), 'o')
+ax1.plot(np.random.rand(100), 'o')
+ax2.plot(np.random.rand(100), 'o')

 # In the latest release, it is no longer necessary to do anything
 # special to share axes across figures:
@@ -25,4 +24,4 @@
 # ax1.sharey_foreign(ax2)
 # ax2.sharey_foreign(ax1)

-show()
+plt.show()
diff --git a/examples/pylab_examples/shared_axis_demo.py b/examples/pylab_examples/shared_axis_demo.py
@@ -27,26 +27,27 @@

  setp( ax2.get_xticklabels(), visible=False)

-
 """
-from pylab import *
+import matplotlib.pyplot as plt
+import numpy as np
+
+t = np.arange(0.01, 5.0, 0.01)
+s1 = np.sin(2*np.pi*t)
+s2 = np.exp(-t)
+s3 = np.sin(4*np.pi*t)

-t = arange(0.01, 5.0, 0.01)
-s1 = sin(2*pi*t)
-s2 = exp(-t)
-s3 = sin(4*pi*t)
-ax1 = subplot(311)
-plot(t, s1)
-setp(ax1.get_xticklabels(), fontsize=6)
+ax1 = plt.subplot(311)
+plt.plot(t, s1)
+plt.setp(ax1.get_xticklabels(), fontsize=6)

 # share x only
-ax2 = subplot(312, sharex=ax1)
-plot(t, s2)
+ax2 = plt.subplot(312, sharex=ax1)
+plt.plot(t, s2)
 # make these tick labels invisible
-setp(ax2.get_xticklabels(), visible=False)
+plt.setp(ax2.get_xticklabels(), visible=False)

 # share x and y
-ax3 = subplot(313, sharex=ax1, sharey=ax1)
-plot(t, s3)
-xlim(0.01, 5.0)
-show()
+ax3 = plt.subplot(313, sharex=ax1, sharey=ax1)
+plt.plot(t, s3)
+plt.xlim(0.01, 5.0)
+plt.show()
diff --git a/examples/pylab_examples/simple_plot.py b/examples/pylab_examples/simple_plot.py
@@ -1,12 +1,13 @@
-from pylab import *
+import matplotlib.pyplot as plt
+import numpy as np

-t = arange(0.0, 2.0, 0.01)
-s = sin(2*pi*t)
-plot(t, s)
+t = np.arange(0.0, 2.0, 0.01)
+s = np.sin(2*np.pi*t)
+plt.plot(t, s)

-xlabel('time (s)')
-ylabel('voltage (mV)')
-title('About as simple as it gets, folks')
-grid(True)
-savefig("test.png")
-show()
+plt.xlabel('time (s)')
+plt.ylabel('voltage (mV)')
+plt.title('About as simple as it gets, folks')
+plt.grid(True)
+plt.savefig("test.png")
+plt.show()
diff --git a/examples/pylab_examples/simple_plot_fps.py b/examples/pylab_examples/simple_plot_fps.py
@@ -1,32 +1,30 @@
-#!/usr/bin/env python
-
 """
 Example: simple line plot.
 Show how to make and save a simple line plot with labels, title and grid
 """
-# -*- noplot -*-
-from __future__ import print_function
-from pylab import *
+from __future__ import print_function  # not necessary in Python 3.x
+import matplotlib.pyplot as plt
+import numpy as np
+import time

-ion()

-t = arange(0.0, 1.0 + 0.001, 0.001)
-s = cos(2*2*pi*t)
-plot(t, s, '-', lw=2)
+plt.ion()

-xlabel('time (s)')
-ylabel('voltage (mV)')
-title('About as simple as it gets, folks')
-grid(True)
+t = np.arange(0.0, 1.0 + 0.001, 0.001)
+s = np.cos(2*2*np.pi*t)
+plt.plot(t, s, '-', lw=2)

-import time
+plt.xlabel('time (s)')
+plt.ylabel('voltage (mV)')
+plt.title('About as simple as it gets, folks')
+plt.grid(True)

 frames = 100.0
 t = time.time()
 c = time.clock()
 for i in range(int(frames)):
    part = i / frames
-    axis([0.0, 1.0 - part, -1.0 + part, 1.0 - part])
+    plt.axis([0.0, 1.0 - part, -1.0 + part, 1.0 - part])
 wallclock = time.time() - t
 user = time.clock() - c
 print("wallclock:", wallclock)

diff --git a/examples/pylab_examples/specgram_demo.py b/examples/pylab_examples/specgram_demo.py
@@ -1,17 +1,17 @@
-#!/usr/bin/env python
-from pylab import *
+import matplotlib.pyplot as plt
+import numpy as np

 dt = 0.0005
-t = arange(0.0, 20.0, dt)
-s1 = sin(2*pi*100*t)
-s2 = 2*sin(2*pi*400*t)
+t = np.arange(0.0, 20.0, dt)
+s1 = np.sin(2*np.pi*100*t)
+s2 = 2*np.sin(2*np.pi*400*t)

 # create a transient "chirp"
-mask = where(logical_and(t > 10, t < 12), 1.0, 0.0)
+mask = np.where(np.logical_and(t > 10, t < 12), 1.0, 0.0)
 s2 = s2 * mask

 # add some noise into the mix
-nse = 0.01*randn(len(t))
+nse = 0.01*np.random.random(size=len(t))

 x = s1 + s2 + nse  # the signal
 NFFT = 1024       # the length of the windowing segments
@@ -22,9 +22,9 @@
 # the power is computed, and im is the matplotlib.image.AxesImage
 # instance

-ax1 = subplot(211)
-plot(t, x)
-subplot(212, sharex=ax1)
-Pxx, freqs, bins, im = specgram(x, NFFT=NFFT, Fs=Fs, noverlap=900,
-                                cmap=cm.gist_heat)
-show()
+ax1 = plt.subplot(211)
+plt.plot(t, x)
+plt.subplot(212, sharex=ax1)
+Pxx, freqs, bins, im = plt.specgram(x, NFFT=NFFT, Fs=Fs, noverlap=900,
+                                cmap=plt.cm.gist_heat)
+plt.show()
diff --git a/examples/pylab_examples/spectrum_demo.py b/examples/pylab_examples/spectrum_demo.py
@@ -1,31 +1,29 @@
-#!/usr/bin/env python
-# python
-
-from pylab import *
+import matplotlib.pyplot as plt
+import numpy as np

 dt = 0.01
 Fs = 1/dt
-t = arange(0, 10, dt)
-nse = randn(len(t))
-r = exp(-t/0.05)
+t = np.arange(0, 10, dt)
+nse = np.random.randn(len(t))
+r = np.exp(-t/0.05)

-cnse = convolve(nse, r)*dt
+cnse = np.convolve(nse, r)*dt
 cnse = cnse[:len(t)]
-s = 0.1*sin(2*pi*t) + cnse
+s = 0.1*np.sin(2*np.pi*t) + cnse

-subplot(3, 2, 1)
-plot(t, s)
+plt.subplot(3, 2, 1)
+plt.plot(t, s)

-subplot(3, 2, 3)
-magnitude_spectrum(s, Fs=Fs)
+plt.subplot(3, 2, 3)
+plt.magnitude_spectrum(s, Fs=Fs)

-subplot(3, 2, 4)
-magnitude_spectrum(s, Fs=Fs, scale='dB')
+plt.subplot(3, 2, 4)
+plt.magnitude_spectrum(s, Fs=Fs, scale='dB')

-subplot(3, 2, 5)
-angle_spectrum(s, Fs=Fs)
+plt.subplot(3, 2, 5)
+plt.angle_spectrum(s, Fs=Fs)

-subplot(3, 2, 6)
-phase_spectrum(s, Fs=Fs)
+plt.subplot(3, 2, 6)
+plt.phase_spectrum(s, Fs=Fs)

-show()
+plt.show()
diff --git a/examples/pylab_examples/subplots_adjust.py b/examples/pylab_examples/subplots_adjust.py
@@ -1,12 +1,12 @@
-from pylab import *
+import matplotlib.pyplot as plt
+import numpy as np

+plt.subplot(211)
+plt.imshow(np.random.random((100, 100)), cmap=plt.cm.BuPu_r)
+plt.subplot(212)
+plt.imshow(np.random.random((100, 100)), cmap=plt.cm.BuPu_r)

-subplot(211)
-imshow(rand(100, 100), cmap=cm.BuPu_r)
-subplot(212)
-imshow(rand(100, 100), cmap=cm.BuPu_r)
-
-subplots_adjust(bottom=0.1, right=0.8, top=0.9)
-cax = axes([0.85, 0.1, 0.075, 0.8])
-colorbar(cax=cax)
-show()
+plt.subplots_adjust(bottom=0.1, right=0.8, top=0.9)
+cax = plt.axes([0.85, 0.1, 0.075, 0.8])
+plt.colorbar(cax=cax)
+plt.show()