matplotlib.axes.Axes.acorr

Axes.acorr(x, *, data=None, **kwargs)

Plot the autocorrelation of x.

Parameters:

xarray-like

detrendcallable, default: mlab.detrend_none (no detrending)

A detrending function applied to x. It must have the signature

detrend(x: np.ndarray) -> np.ndarray

normedbool, default: True

If True, input vectors are normalised to unit length.

usevlinesbool, 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.

maxlagsint, default: 10

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

Returns:

lagsarray (length 2*maxlags+1)

The lag vector.

carray (length 2*maxlags+1)

The auto correlation vector.

lineLineCollection or Line2D

Artist added to the axes of the correlation:

• LineCollection if usevlines is True.
• Line2D if usevlines is False.

bLine2D or None

Horizontal line at 0 if usevlines is True None usevlines is False.

Other Parameters:

linestyleLine2D property, optional

The linestyle for plotting the data points. Only used if usevlines is False.

markerstr, default: 'o'

The marker for plotting the data points. Only used if usevlines is False.

**kwargs

Additional parameters are passed to Axes.vlines and Axes.axhline if usevlines is True; otherwise they are passed to Axes.plot.

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 can also be string s, which is interpreted as data[s] (unless this raises an exception): x.

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

Examples using matplotlib.axes.Axes.acorr

Cross- and Auto-Correlation Demo