nuttall(M, sym=True)
This variation is called "Nuttall4c" by Heinzel.
Number of points in the output window. If zero or less, an empty array is returned.
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 minimum 4-term Blackman-Harris window according to Nuttall.
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.nuttall(51)
... plt.plot(window)
... plt.title("Nuttall window")
... 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("Frequency response of the Nuttall window")
... 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.windows._windows.nuttall
scipy.signal.nuttall
Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.
Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)
SVG is more flexible but power hungry; and does not scale well to 50 + nodes.
All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them