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Smooth data using a window with requested size. This method is based on the convolution of a scaled window with the signal.
The signal is prepared by introducing reflected copies of the signal
(with the window size) in both ends so that transient parts are minimized
in the beginning and end part of the output signal.
au.smooth(x, window_len=10, window='hanning')
- x: the input signal
- window_len: the dimension of the smoothing window
- window: the type of window from 'flat', 'hanning', 'hamming', 'bartlett', 'blackman'
- 'flat' window will produce a moving average smoothing.