libb.numpy_smooth

numpy_smooth(x, window_len=11, window='hanning')[source]

Smooth the data using a window with requested size.

https://scipy-cookbook.readthedocs.io/items/SignalSmooth.html

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 begining and end part of the output signal.

Parameters:

  • x – the input signal

  • window_len – the dimension of the smoothing window; should be an odd integer

  • window – the type of window from ‘flat’, ‘hanning’, ‘hamming’, ‘bartlett’, ‘blackman’. Flat window will produce a moving average smoothing.

Returns:

the smoothed signal

Example:

t=linspace(-2,2,0.1)
x=sin(t)+randn(len(t))*0.1
y=smooth(x)

See also

numpy.hanning, numpy.hamming, numpy.bartlett, numpy.blackman, numpy.convolve, scipy.signal.lfilter

Note

The window parameter could be the window itself if an array instead of a string. length(output) != length(input), to correct this: return y[(window_len/2-1):-(window_len/2)] instead of just y.