matplotlib.axes.Axes.xcorr
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Axes.xcorr(self, x, y, normed=True, detrend=<function detrend_none at 0x7f8092177c80>, 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 \(\sum_n x[n+k] \cdot y^*[n]\), where \(y^*\) is the complex conjugate of \(y\).
Parameters: |
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x : array-like of length n -
y : array-like of length n -
detrend : callable, optional, default: 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. -
normed : bool, optional, default: True -
If True , input vectors are normalised to unit length. -
usevlines : bool, optional, default: True -
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 . -
maxlags : int, optional, default: 10 -
Number of lags to show. If None, will return all 2 * len(x) - 1 lags. |
Returns: |
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lags : array (length 2*maxlags+1) -
The lag vector. -
c : array (length 2*maxlags+1) -
The auto correlation vector. -
line : LineCollection or Line2D -
Artist added to the axes of the correlation: -
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 -
The linestyle for plotting the data points. Only used if usevlines is False . -
marker : str, optional, default: 'o' -
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>]:
- All arguments with the following names: 'x', 'y'.
Objects passed as data must support item access (data[<arg>]
) and membership test (<arg> in data
).
Examples using matplotlib.axes.Axes.xcorr