matplotlib.axes.Axes.acorr
-
Axes.acorr(self, x, *, data=None, **kwargs)
[source] -
Plot the autocorrelation of x.
Parameters: -
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 annumpy.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 usingAxes.vlines
. Additionally, a horizontal line is plotted at y=0 usingAxes.axhline
.If
False
, markers are plotted at the acorr values usingAxes.plot
. -
maxlags : int, optional, default: 10
-
Number of lags to show. If
None
, will return all2 * len(x) - 1
lags.
Returns: -
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:-
LineCollection
if usevlines is True. -
Line2D
if usevlines is False.
-
-
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
.
Notes
The cross correlation is performed with
numpy.correlate()
withmode = "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'.
Objects passed as data must support item access (
data[<arg>]
) and membership test (<arg> in data
). -
Examples using matplotlib.axes.Axes.acorr
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Licensed under the Matplotlib License Agreement.
https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.axes.Axes.acorr.html