Calculate the minimax optimal filter using the Remez exchange algorithm.
Calculate the filtercoefficients for the finite impulse response (FIR) filter whose transfer function minimizes the maximum error between the desired gain and the realized gain in the specified frequency bands using the Remez exchange algorithm.
Parameters :  numtaps : int
bands : array_like
desired : array_like
weight : array_like, optional
Hz : scalar, optional
type : {‘bandpass’, ‘differentiator’, ‘hilbert’}, optional
maxiter : int, optional
grid_density : int, optional


Returns :  out : ndarray

See also
References
[R58]  J. H. McClellan and T. W. Parks, “A unified approach to the design of optimum FIR linear phase digital filters”, IEEE Trans. Circuit Theory, vol. CT20, pp. 697701, 1973. 
[R59]  J. H. McClellan, T. W. Parks and L. R. Rabiner, “A Computer Program for Designing Optimum FIR Linear Phase Digital Filters”, IEEE Trans. Audio Electroacoust., vol. AU21, pp. 506525, 1973. 
Examples
We want to construct a filter with a passband at 0.20.4 Hz, and stop bands at 00.1 Hz and 0.450.5 Hz. Note that this means that the behavior in the frequency ranges between those bands is unspecified and may overshoot.
>>> bpass = sp.signal.remez(72, [0, 0.1, 0.2, 0.4, 0.45, 0.5], [0, 1, 0])
>>> freq, response = sp.signal.freqz(bpass)
>>> ampl = np.abs(response)
>>> import matplotlib.pyplot as plt
>>> fig = plt.figure()
>>> ax1 = fig.add_subplot(111)
>>> ax1.semilogy(freq/(2*np.pi), ampl, 'b') # freq in Hz
[<matplotlib.lines.Line2D object at 0xf486790>]
>>> plt.show()