gaussian(M, std, sym=True)
The Gaussian window is defined as
$$w(n) = e^{ -\frac{1}{2}\left(\frac{n}{\sigma}\right)^2 }$$Number of points in the output window. If zero or less, an empty array is returned.
The standard deviation, sigma.
When True (default), generates a symmetric window, for use in filter design. When False, generates a periodic window, for use in spectral analysis.
The window, with the maximum value normalized to 1 (though the value 1 does not appear if M is even and :None:None:`sym` is True).
Return a Gaussian window.
Plot the window and its frequency response:
>>> from scipy import signal
... from scipy.fft import fft, fftshift
... import matplotlib.pyplot as plt
>>> window = signal.windows.gaussian(51, std=7)
... plt.plot(window)
... plt.title(r"Gaussian window ($\sigma$=7)")
... plt.ylabel("Amplitude")
... plt.xlabel("Sample")
>>> plt.figure()See :
... 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(r"Frequency response of the Gaussian window ($\sigma$=7)")
... plt.ylabel("Normalized magnitude [dB]")
... plt.xlabel("Normalized frequency [cycles per sample]")
The following pages refer to to this document either explicitly or contain code examples using this.
scipy.signal.windows._windows.get_window
scipy.signal._signaltools.fftconvolve
scipy.signal.gaussian
scipy.signal.windows._windows.gaussian
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