matplotlib.axes.Axes.xcorr
-
Axes.xcorr(x, y, normed=True, detrend=<function detrend_none>, usevlines=True, maxlags=10, *, data=None, **kwargs)
[source]
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Plot the cross correlation between x and y.
The correlation with lag k is defined as , where is the complex conjugate of .
Parameters: |
-
x : sequence of scalars of length n -
y : sequence of scalars of length n -
detrend : callable, optional, default: mlab.detrend_none -
x is detrended by the detrend callable. Default is no normalization. -
normed : bool, optional, default: True -
If True , input vectors are normalised to unit length. -
usevlines : bool, optional, default: True -
If True , Axes.vlines is used to plot the vertical lines from the origin to the acorr. Otherwise, Axes.plot is used. -
maxlags : int, optional -
Number of lags to show. If None, will return all 2 * len(x) - 1 lags. Default is 10. |
Returns: |
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lags : array (length 2*maxlags+1) -
lag vector. -
c : array (length 2*maxlags+1) -
auto correlation vector. -
line : LineCollection or Line2D -
Artist added to the axes of the correlation LineCollection if usevlines is True Line2D if usevlines is False -
b : Line2D or None -
Horizontal line at 0 if usevlines is True None usevlines is False |
Other Parameters: |
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linestyle : Line2D property, optional -
Only used if usevlines is False . -
marker : string, optional -
Default is 'o'. |
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>]:
- All arguments with the following names: 'x', 'y'.
Objects passed as data must support item access (data[<arg>]
) and membership test (<arg> in data
).