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matplotlib.pyplot.acorr
matplotlib.pyplot.acorr(x, *, data=None, **kwargs)[source]-
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 usingAxes.vlines. Additionally, a horizontal line is plotted at y=0 usingAxes.axhline.If
False, markers are plotted at the acorr values usingAxes.plot. - maxlagsint, default: 10
-
Number of lags to show. If
None, will return all2 * len(x) - 1lags.
Returns: -
lagsarray (length
2*maxlags+1) -
The lag vector.
-
carray (length
2*maxlags+1) -
The auto correlation vector.
-
line
LineCollectionorLine2D -
Artistadded to the Axes of the correlation:LineCollectionif usevlines is True.Line2Dif usevlines is False.
-
b
Line2Dor None -
Horizontal line at 0 if usevlines is True None usevlines is False.
Other Parameters: -
linestyle
Line2Dproperty, 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.vlinesandAxes.axhlineif usevlines isTrue; otherwise they are passed toAxes.plot.
Notes
The cross correlation is performed with
numpy.correlatewithmode = "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 asdata[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.pyplot.acorr
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https://matplotlib.org/3.4.3/api/_as_gen/matplotlib.pyplot.acorr.html