matplotlib.pyplot.
xcorr
(x, y, normed=True, detrend=<function detrend_none>, usevlines=True, maxlags=10, *, data=None, **kwargs)[source]¶Plot the cross correlation between x and y.
The correlation with lag k is defined as \(\sum_n x[n+k] \cdot y^*[n]\), where \(y^*\) is the complex conjugate of \(y\).
Parameters: | x : sequence of scalars of length n y : sequence of scalars of length n detrend : callable, optional, default:
normed : bool, optional, default: True
usevlines : bool, optional, default: True
maxlags : int, optional
|
---|---|
Returns: | lags : array (length
c : array (length
line :
b :
|
Other Parameters: | linestyle :
marker : string, optional
|
Notes
The cross correlation is performed with numpy.correlate()
with
mode = 2
.
Note
In addition to the above described arguments, this function can take a data keyword argument. If such a data argument is given, the following arguments are replaced by data[<arg>]:
Objects passed as data must support item access (data[<arg>]
) and
membership test (<arg> in data
).