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MEP12 on axes_demo.py #4661

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d0ff103
pylab to plt and np
Jul 11, 2015
da7841c
pep8
Jul 17, 2015
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40 changes: 21 additions & 19 deletions examples/pylab_examples/axes_demo.py
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@@ -1,32 +1,34 @@
#!/usr/bin/env python

from pylab import *
import matplotlib.pyplot as plt
import numpy as np
import scipy as sp
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We shouldn't use Scipy. As is it not installed on our Travis machine and we try avoiding to depend on it.

You can get randn from numpy.random

import numpy as np
np.random.randn


# create some data to use for the plot
dt = 0.001
t = arange(0.0, 10.0, dt)
r = exp(-t[:1000]/0.05) # impulse response
x = randn(len(t))
s = convolve(x, r)[:len(x)]*dt # colored noise
t = np.arange(0.0, 10.0, dt)
r = np.exp(-t[:1000]/0.05) # impulse response
x = sp.randn(len(t))
s = np.convolve(x, r)[:len(x)]*dt # colored noise

# the main axes is subplot(111) by default
plot(t, s)
axis([0, 1, 1.1*amin(s), 2*amax(s)])
xlabel('time (s)')
ylabel('current (nA)')
title('Gaussian colored noise')
plt.plot(t, s)
plt.axis([0, 1, 1.1*np.amin(s), 2*np.amax(s)])
plt.xlabel('time (s)')
plt.ylabel('current (nA)')
plt.title('Gaussian colored noise')

# this is an inset axes over the main axes
a = axes([.65, .6, .2, .2], axisbg='y')
n, bins, patches = hist(s, 400, normed=1)
title('Probability')
setp(a, xticks=[], yticks=[])
a = plt.axes([.65, .6, .2, .2], axisbg='y')
n, bins, patches = plt.hist(s, 400, normed=1)
plt.title('Probability')
plt.setp(a, xticks=[], yticks=[])

# this is another inset axes over the main axes
a = axes([0.2, 0.6, .2, .2], axisbg='y')
plot(t[:len(r)], r)
title('Impulse response')
setp(a, xlim=(0, .2), xticks=[], yticks=[])
a = plt.axes([0.2, 0.6, .2, .2], axisbg='y')
plt.plot(t[:len(r)], r)
plt.title('Impulse response')
plt.setp(a, xlim=(0, .2), xticks=[], yticks=[])


show()
plt.show()