scipy.signal.gaussian(M, std, sym=True)[source]

Return a Gaussian window.

Parameters :

M : int

Number of points in the output window. If zero or less, an empty array is returned.

std : float

The standard deviation, sigma.

sym : bool, optional

When True, generates a symmetric window, for use in filter design. When False, generates a periodic window, for use in spectral analysis.

Returns :

w : ndarray

The window, with the maximum value normalized to 1 (though the value 1 does not appear if the number of samples is even and sym is True).


The Gaussian window is defined as

w(n) = e^{ -\frac{1}{2}\left(\frac{n}{\sigma}\right)^2 }


Plot the window and its frequency response:

>>> from scipy import signal
>>> from scipy.fftpack import fft, fftshift
>>> import matplotlib.pyplot as plt
>>> window = signal.gaussian(51, std=7)
>>> plt.plot(window)
>>> plt.title(r"Gaussian window ($\sigma$=7)")
>>> 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(r"Frequency response of the Gaussian window ($\sigma$=7)")
>>> plt.ylabel("Normalized magnitude [dB]")
>>> plt.xlabel("Normalized frequency [cycles per sample]")

(Source code)


Previous topic


Next topic