scipy.signal.

get_window#

scipy.signal.get_window(window, Nx, fftbins=True, *, xp=None, device=None)[source] #

Return a window of a given length and type.

Parameters:

windowstring, float, or tuple: The type of window to create. See below for more details.
Nxint: The number of samples in the window.
fftbinsbool, optional: If True (default), create a "periodic" window, ready to use with ifftshift and be multiplied by the result of an FFT (see also fftfreq). If False, create a "symmetric" window, for use in filter design.
xparray_namespace, optional: Optional array namespace. Should be compatible with the array API standard, or supported by array-api-compat. Default: numpy
device: any: optional device specification for output. Should match one of the supported device specification in xp.

Returns:

get_windowndarray: Returns a window of length Nx and type window

Notes

Window types:

boxcar
triang
blackman
hamming
hann
bartlett
flattop
parzen
bohman
blackmanharris
nuttall
barthann
cosine
exponential
tukey
taylor
lanczos
kaiser (needs beta)
kaiser_bessel_derived (needs beta)
gaussian (needs standard deviation)
general_cosine (needs weighting coefficients)
general_gaussian (needs power, width)
general_hamming (needs window coefficient)
dpss (needs normalized half-bandwidth)
chebwin (needs attenuation)

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

>>> fromscipyimport 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(('exponential', None, 1.), 9)
array([ 0.011109 , 0.03019738, 0.082085 , 0.22313016, 0.60653066,
 0.60653066, 0.22313016, 0.082085 , 0.03019738])
>>> 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])