#### Previous topic

scipy.signal.boxcar

#### Next topic

scipy.signal.cosine

# scipy.signal.chebwin

`scipy.signal.``chebwin`(M, at, sym=True)

  Return a Dolph-Chebyshev window.

  Parameters: | M : int Number of points in the output window. If zero or less, an empty array is returned. at : float Attenuation (in dB). 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.
  Returns: | w : ndarray The window, with the maximum value always normalized to 1

  Notes

  This window optimizes for the narrowest main lobe width for a given order M and sidelobe equiripple attenuation at, using Chebyshev polynomials. It was originally developed by Dolph to optimize the directionality of radio antenna arrays.

  Unlike most windows, the Dolph-Chebyshev is defined in terms of its frequency response:

  \[W(k) = \frac {\cos\{M \cos^{-1}[\beta \cos(\frac{\pi k}{M})]\}} {\cosh[M \cosh^{-1}(\beta)]}\]

  where

  \[\beta = \cosh \left [\frac{1}{M} \cosh^{-1}(10^\frac{A}{20}) \right ]\]

  and 0 <= abs(k) <= M-1. A is the attenuation in decibels (at).

  The time domain window is then generated using the IFFT, so power-of-two M are the fastest to generate, and prime number M are the slowest.

  The equiripple condition in the frequency domain creates impulses in the time domain, which appear at the ends of the window.

  References

  [R163] | C. Dolph, “A current distribution for broadside arrays which optimizes the relationship between beam width and side-lobe level”, Proceedings of the IEEE, Vol. 34, Issue 6

  [R164] | Peter Lynch, “The Dolph-Chebyshev Window: A Simple Optimal Filter”, American Meteorological Society (April 1997) http://mathsci.ucd.ie/~plynch/Publications/Dolph.pdf

  [R165] | F. J. Harris, “On the use of windows for harmonic analysis with the discrete Fourier transforms”, Proceedings of the IEEE, Vol. 66, No. 1, January 1978

  Examples

  Plot the window and its frequency response:

      >>> from scipy import signal
      >>> from scipy.fftpack import fft, fftshift
      >>> import matplotlib.pyplot as plt

      >>> window = signal.chebwin(51, at=100)
      >>> plt.plot(window)
      >>> plt.title("Dolph-Chebyshev 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 Dolph-Chebyshev window (100 dB)")
      >>> plt.ylabel("Normalized magnitude [dB]")
      >>> plt.xlabel("Normalized frequency [cycles per sample]")

  (Source code)