Falko
2014-10-10 00:02:23
You want to compare two signals, e.g. A and B in the following example:
import numpy as np
A = np.random.rand(5)
B = np.random.rand(5)
print "A:", A
print "B:", B
Output:
A: [ 0.66926369 0.63547359 0.5294013 0.65333154 0.63912645]
B: [ 0.17207719 0.26638423 0.55176735 0.05251388 0.90012135]
Analyzing individual signals
The standard deviation of each single signal is not what you need:
print "standard deviation of A:", np.std(A)
print "standard deviation of B:", np.std(B)
Output:
standard deviation of A: 0.0494162021651
standard deviation of B: 0.304319034639
Analyzing the difference
Instead you might compute the difference and apply some common measure like the sum of absolute differences (SAD), the sum of squared differences (SSD) or the correlation coefficient:
print "difference:", A - B
print "SAD:", np.sum(np.abs(A - B))
print "SSD:", np.sum(np.square(A - B))
print "correlation:", np.corrcoef(np.array((A, B)))[0, 1]
Output:
difference: [ 0.4971865 0.36908937 -0.02236605 0.60081766 -0.2609949 ]
SAD: 1.75045448355
SSD: 0.813021824351
correlation: -0.38247081