cupyx.scipy.signal.get_window#

cupyx.scipy.signal.get_window(window, Nx, fftbins=True)[source]#

Return a window of a given length and type.

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 – Returns a window of length Nx and type window

Return type:

ndarray

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)
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

>>> import cupyx.scipy.signal.windows
>>> cupyx.scipy.signal.windows.get_window('triang', 7)
array([ 0.125,  0.375,  0.625,  0.875,  0.875,  0.625,  0.375])
>>> cupyx.scipy.signal.windows.get_window(('kaiser', 4.0), 9)
array([0.08848053, 0.32578323, 0.63343178, 0.89640418, 1.,
       0.89640418, 0.63343178, 0.32578323, 0.08848053])
>>> cupyx.scipy.signal.windows.get_window(4.0, 9)
array([0.08848053, 0.32578323, 0.63343178, 0.89640418, 1.,
       0.89640418, 0.63343178, 0.32578323, 0.08848053])