`scipy.signal.windows._windows:taylor`

source: build-install/usr/lib/python3.14/site-packages/scipy/signal/windows/_windows.py:2018

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).

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")

✗

Text(0.5, 0, 'Sample')

plt.figure()

✗

<Figure size 640x480 with 0 Axes>

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]")

✗

Text(0.5, 0, 'Normalized frequency [cycles per sample]')

`scipy.signal.windows._windows:taylor`

Signature

Summary

Extended Summary

Parameters

Returns

Examples

See also

Aliases

Referenced by

This package