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bundles / scipy latest / scipy / signal / windows / _windows / kaiser_bessel_derived

function

scipy.signal.windows._windows:kaiser_bessel_derived

source: /scipy/signal/windows/_windows.py :1325

Signature

def   kaiser_bessel_derived ( M ,  beta ,  * ,  sym = True ,  xp = None ,  device = None )

Summary

Return a Kaiser-Bessel derived window.

Parameters

M : int

Number of points in the output window. If zero, an empty array is returned. An exception is thrown when it is negative. Note that this window is only defined for an even number of points.

beta : float

Kaiser window shape parameter.

sym : bool, optional

This parameter only exists to comply with the interface offered by the other window functions and to be callable by get_window. When True (default), generates a symmetric window, for use in filter design.

xp : array_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

w : ndarray

The window, normalized to fulfil the Princen-Bradley condition.

Notes

It is designed to be suitable for use with the modified discrete cosine transform (MDCT) and is mainly used in audio signal processing and audio coding.

Array API Standard Support

kaiser_bessel_derived has experimental support for Python Array API Standard compatible backends in addition to NumPy. Please consider testing these features by setting an environment variable SCIPY_ARRAY_API=1 and providing CuPy, PyTorch, JAX, or Dask arrays as array arguments. The following combinations of backend and device (or other capability) are supported.

====================  ====================  ====================
Library               CPU                   GPU
====================  ====================  ====================
NumPy                 ✅                     n/a                 
CuPy                  n/a                   ✅                   
PyTorch               ✅                     ✅                   
JAX                   ✅                     ✅                   
Dask                  ✅                     n/a                 
====================  ====================  ====================

See dev-arrayapi for more information.

Examples

Plot the Kaiser-Bessel derived window based on the wikipedia reference [2]_: 
import numpy as np
from scipy import signal
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
N = 50
✓
for alpha in [0.64, 2.55, 7.64, 31.83]:
    ax.plot(signal.windows.kaiser_bessel_derived(2*N, np.pi*alpha),
            label=f"{alpha=}")
✗
ax.grid(True)
✓
ax.set_title("Kaiser-Bessel derived window")
ax.set_ylabel("Amplitude")
ax.set_xlabel("Sample")
ax.set_xticks([0, N, 2*N-1])
ax.set_yticks([0.0, 0.2, 0.4, 0.6, 0.707, 0.8, 1.0])
fig.legend(loc="center")
✗
fig.tight_layout()
fig.show()
✓

See also

kaiser

Aliases

  • scipy.signal.windows.kaiser_bessel_derived

Referenced by

This package