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# scipy.signal.get_window

`scipy.signal.``get_window`(window, Nx, fftbins=True)

  Return a window.

  Parameters: | window : string, float, or tuple The type of window to create. See below for more details. Nx : int The number of samples in the window. fftbins : bool, optional If True (default), create a “periodic” window, ready to use with ifftshift and be multiplied by the result of an FFT (see also fftpack.fftfreq). If False, create a “symmetric” window, for use in filter design.
  Returns: | get_window : ndarray Returns a window of length Nx and type window

  Notes

  Window types:

  > `boxcar`, `triang`, `blackman`, `hamming`, `hann`, `bartlett`, `flattop`, `parzen`, `bohman`, `blackmanharris`, `nuttall`, `barthann`, `kaiser` (needs beta), `gaussian` (needs standard deviation), `general_gaussian` (needs power, width), `slepian` (needs width), `chebwin` (needs attenuation), `exponential` (needs decay scale), `tukey` (needs taper fraction)

  If the window requires no parameters, then window can be a string.

  If the window requires parameters, then window must be a tuple with the first argument the string name of the window, and the next arguments the needed parameters.

  If window is a floating point number, it is interpreted as the beta parameter of the `kaiser` window.

  Each of the window types listed above is also the name of a function that can be called directly to create a window of that type.

  Examples

      >>> from scipy import signal
      >>> signal.get_window('triang', 7)
      array([ 0.125,  0.375,  0.625,  0.875,  0.875,  0.625,  0.375])
      >>> signal.get_window(('kaiser', 4.0), 9)
      array([ 0.08848053,  0.29425961,  0.56437221,  0.82160913,  0.97885093,
              0.97885093,  0.82160913,  0.56437221,  0.29425961])
      >>> signal.get_window(4.0, 9)
      array([ 0.08848053,  0.29425961,  0.56437221,  0.82160913,  0.97885093,
              0.97885093,  0.82160913,  0.56437221,  0.29425961])