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#!/usr/bin/env python
# Demonstrate arbitrary placement of axes
from matplotlib.matlab import *
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,mode=2)*dt # colored noise
s = s[:len(x)] # remove the decay tail which will skew
# the probability distribution
# I'm just using the if 1 thing to break up the different regions of
# the code visually.
# plot the noise
if 1:
plot(t, s)
axis([0, 1, 1.1*min(s), 2*max(s) ])
xlabel('time (s)')
ylabel('current (nA)')
title('Gaussian colored noise')
# Make a histogram probability density inset
if 1:
a = axes([.65, .6, .2, .2], axisbg='y')
n, bins, patches = hist(s, 400, normed=1)
title('Probability')
set(a, 'xticks', [])
set(a, 'yticks', [])
# Plot the impulse response function
if 1:
a = axes([0.2, 0.6, .2, .2], axisbg='y')
plot(t[:len(r)], r)
title('Impulse response')
set(a, 'xlim', [0,.2])
set(a, 'xticks', [])
set(a, 'yticks', [])
#savefig('axes_demo', dpi=600)
show()
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