matplotlib.pyplot.
xcorr
(x, y, normed=True, detrend=<function detrend_none at 0x7fb11b56c2f0>, 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:mlab.detrend_none
x and y are detrended by the detrend callable. This must be a function x = detrend(x)
accepting and returning an numpy.array
. Default is no normalization.
If True
, input vectors are normalised to unit length.
Determines the plot style.
If True
, vertical lines are plotted from 0 to the xcorr value using Axes.vlines
. Additionally, a horizontal line is plotted at y=0 using Axes.axhline
.
If False
, markers are plotted at the xcorr values using Axes.plot
.
Number of lags to show. If None, will return all 2 * len(x) - 1
lags.
2*maxlags+1
)
The lag vector.
2*maxlags+1
)
The auto correlation vector.
LineCollection
or Line2D
Artist
added to the axes of the correlation:
LineCollection
if usevlines is True.Line2D
if usevlines is False.Line2D
or None
Horizontal line at 0 if usevlines is True None usevlines is False.
Line2D
property, optional
The linestyle for plotting the data points. Only used if usevlines is False
.
The marker for plotting the data points. Only used if usevlines is False
.
Notes
The cross correlation is performed with numpy.correlate()
with mode = "full"
.
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
).
matplotlib.pyplot.xcorr
¶
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