scipy tutorial - Baustatik-Info-Server

SciPy Reference Guide, Release 0.8.dev
If window is an array of the same length as x.shape[axis] it is assumed to be the window to be applied directly
in the Fourier domain (with dc and low-frequency first).
If window is a string then use the named window. If window is a float, then it represents a value of beta for a
kaiser window. If window is a tuple, then the first component is a string representing the window, and the next
arguments are parameters for that window.
Possible windows are:
‘flattop’ – ‘flat’, ‘flt’ ‘boxcar’ – ‘ones’, ‘box’ ‘triang’ – ‘traing’, ‘tri’ ‘parzen’ – ‘parz’, ‘par’ ‘bohman’ –
‘bman’, ‘bmn’ ‘blackmanharris’ – ‘blackharr’, ‘bkh’ ‘nuttall’, – ‘nutl’, ‘nut’ ‘barthann’ – ‘brthan’, ‘bth’
‘blackman’ – ‘black’, ‘blk’ ‘hamming’ – ‘hamm’, ‘ham’ ‘bartlett’ – ‘bart’, ‘brt’ ‘hanning’ – ‘hann’, ‘han’
(‘kaiser’, beta) – ‘ksr’ (‘gaussian’, std) – ‘gauss’, ‘gss’ (‘general gauss’, power, width) – ‘general’, ‘ggs’
(‘slepian’, width) – ‘slep’, ‘optimal’, ‘dss’
The first sample of the returned vector is the same as the first sample of the input vector, the spacing between
samples is changed from dx to
dx * len(x) / num
If t is not None, then it represents the old sample positions, and the new sample positions will be returned as
well as the new samples.
3.13.4 Filter design
remez(numtaps, bands, desired[, weight, Hz, Calculate the minimax optimal filter using Remez exchange
...])
algorithm.
firwin(N, cutoff[, width, window]) FIR Filter Design using windowed ideal filter method.
iirdesign(wp, ws, gpass, gstop[, analog,
...])
Complete IIR digital and analog filter design.
iirfilter(N, Wn[, rp, rs, btype, analog,
...])
IIR digital and analog filter design given order and critical points.
freqs(b, a[, worN, plot]) Compute frequency response of analog filter.
freqz(b[, a, worN, whole, plot]) Compute frequency response of a digital filter.
unique_roots(p[, tol, rtype]) Determine the unique roots and their multiplicities in two lists
residue(b, a[, tol, rtype]) Compute partial-fraction expansion of b(s) / a(s).
residuez(b, a[, tol, rtype]) Compute partial-fraction expansion of b(z) / a(z).
invres(r, p, k[, tol, rtype]) Compute b(s) and a(s) from partial fraction expansion: r,p,k
remez(numtaps, bands, desired, weight=None, Hz=1, type=’bandpass’, maxiter=25, grid_density=16)
Calculate the minimax optimal filter using Remez exchange algorithm.
Description:
Inputs:
Calculate the filter-coefficients 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 bands
using the remez exchange algorithm.
numtaps – The desired number of taps in the filter. bands – A montonic sequence containing the
band edges. All elements
must be non-negative and less than 1/2 the sampling frequency as given by Hz.
desired – A sequency half the size of bands containing the desired gain
in each of the specified bands
weight – A relative weighting to give to each band region. type — The type of filter:
334 Chapter 3. Reference