matplotlib.pyplot.acorr#

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

Plot the autocorrelation ofx.

Parameters:
xarray-like

Not run through Matplotlib's unit conversion, so this shouldbe a unit-less array.

detrendcallable, default:mlab.detrend_none (no detrending)

A detrending function applied tox. It must have thesignature

detrend(x:np.ndarray)->np.ndarray
normedbool, default: True

IfTrue, input vectors are normalised to unit length.

usevlinesbool, default: True

Determines the plot style.

IfTrue, vertical lines are plotted from 0 to the acorr valueusingAxes.vlines. Additionally, a horizontal line is plottedat y=0 usingAxes.axhline.

IfFalse, markers are plotted at the acorr values usingAxes.plot.

maxlagsint, default: 10

Number of lags to show. IfNone, will return all2*len(x)-1 lags.

Returns:
lagsarray (length2*maxlags+1)

The lag vector.

carray (length2*maxlags+1)

The auto correlation vector.

lineLineCollection orLine2D

Artist added to the Axes of the correlation:

bLine2D or None

Horizontal line at 0 ifusevlines is TrueNoneusevlines is False.

Other Parameters:
linestyleLine2D property, optional

The linestyle for plotting the data points.Only used ifusevlines isFalse.

markerstr, default: 'o'

The marker for plotting the data points.Only used ifusevlines isFalse.

dataindexable object, optional

If given, the following parameters also accept a strings, which isinterpreted asdata[s] ifs is a key indata:

x

**kwargs

Additional parameters are passed toAxes.vlines andAxes.axhline ifusevlines isTrue; otherwise they arepassed toAxes.plot.

Notes

Note

This is thepyplot wrapper foraxes.Axes.acorr.

The cross correlation is performed withnumpy.correlate withmode="full".

Examples usingmatplotlib.pyplot.acorr#

Cross- and auto-correlation

Cross- and auto-correlation