Stairs.
cov
(other, lower=inf, upper=inf, lag=0, clip='pre')¶Calculates either covariance, autocovariance or crosscovariance.
The calculation is between two step functions described by self and other. If lag is None or 0 then covariance is calculated, otherwise crosscovariance is calculated. Autocovariance is a special case of crosscovariance when other is equal to self.
Parameters: 


Returns:  The covariance (or crosscovariance) between self and other 
Return type:  float 
See also
Examples
>>> fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(12,5), sharey=True, sharex=True)
>>> for ax, title, stair_instance in zip(axes, ("s1", "s2"), (s1, s2)):
... stair_instance.plot(ax, label=title)
... ax.set_title(title)
>>> s1.cov(s2)
0.1404958677685951
>>> s2.cov(s1)
0.1404958677685951
>>> s1.cov(s2, lower=0, upper=6)
0.125
>>> # autocovariance with lag 1
>>> s1.cov(s1, lower=1, upper=5, lag=1)
0.3333333333333333
>>> # crosscovariance with lag 1
>>> s1.cov(s2, lower=1, upper=4.5, lag=1)
0.15999999999999998
>>> # crosscovariance with lag 1
>>> s1.cov(s2, lower=1, upper=4.5, lag=1, clip='post')
0.163265306122449