/Matplotlib 3.1


matplotlib.pyplot.acorr(x, *, data=None, **kwargs) [source]

Plot the autocorrelation of x.

x : array-like
detrend : callable, optional, default: mlab.detrend_none

x is 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 acorr value using Axes.vlines. Additionally, a horizontal line is plotted at y=0 using Axes.axhline.

If False, markers are plotted at the acorr values using Axes.plot.

maxlags : int, optional, default: 10

Number of lags to show. If None, will return all 2 * len(x) - 1 lags.

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:
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.


The cross correlation is performed with numpy.correlate() with mode = "full".


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'.

Objects passed as data must support item access (data[<arg>]) and membership test (<arg> in data).

Examples using matplotlib.pyplot.acorr

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