`scipy.signal.windows._windows:taylor`

source: /scipy/signal/windows/_windows.py :1850

Signature

   def     taylor (    M    ,    nbar    =  4   ,    sll    =  30   ,    norm    =  True   ,    sym    =  True   ,  * ,     xp    =  None   ,    device    =  None     )

Summary

Return a Taylor window.

Extended Summary

The Taylor window taper function approximates the Dolph-Chebyshev window's constant sidelobe level for a parameterized number of near-in sidelobes, but then allows a taper beyond ^[2].

The SAR (synthetic aperture radar) community commonly uses Taylor weighting for image formation processing because it provides strong, selectable sidelobe suppression with minimum broadening of the mainlobe ^[1].

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.
nbar : int, optional: Number of nearly constant level sidelobes adjacent to the mainlobe.
sll : float, optional: Desired suppression of sidelobe level in decibels (dB) relative to the DC gain of the mainlobe. This should be a positive number.
norm : bool, optional: When True (default), divides the window by the largest (middle) value for odd-length windows or the value that would occur between the two repeated middle values for even-length windows such that all values are less than or equal to 1. When False the DC gain will remain at 1 (0 dB) and the sidelobes will be sll dB down.
sym : bool, optional: When True (default), generates a symmetric window, for use in filter design. When False, generates a periodic window, for use in spectral analysis.
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

out : array: The window. When norm is True (default), the maximum value is normalized to 1 (though the value 1 does not appear if M is even and sym is True).

Notes

Array API Standard Support

taylor 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 window and its frequency response:

import numpy as np
from scipy import signal
from scipy.fft import fft, fftshift
import matplotlib.pyplot as plt

✓

window = signal.windows.taylor(51, nbar=20, sll=100, norm=False)

✓

plt.plot(window)
plt.title("Taylor window (100 dB)")
plt.ylabel("Amplitude")
plt.xlabel("Sample")

✗

plt.figure()

✗

A = fft(window, 2048) / (len(window)/2.0)
freq = np.linspace(-0.5, 0.5, len(A))
response = 20 * np.log10(np.abs(fftshift(A / abs(A).max())))

✓

plt.plot(freq, response)
plt.axis([-0.5, 0.5, -120, 0])
plt.title("Frequency response of the Taylor window (100 dB)")
plt.ylabel("Normalized magnitude [dB]")
plt.xlabel("Normalized frequency [cycles per sample]")

✗

Aliases

scipy.signal.windows.taylor

Referenced by

This package

release:1.6.0-notes