scipy tutorial - Baustatik-Info-Server

SciPy Reference Guide, Release 0.8.dev
Notes
zf : array (optional)
If zi is None, this is not returned, otherwise, zf holds the final filter delay values.
The filter function is implemented as a direct II transposed structure. This means that the filter implements
a[0]*y[n] = b[0]*x[n] + b[1]*x[n-1] + ... + b[nb]*x[n-nb]
- a[1]*y[n-1] - ... - a[na]*y[n-na]
using the following difference equations:
y[m] = b[0]*x[m] + z[0,m-1]
z[0,m] = b[1]*x[m] + z[1,m-1] - a[1]*y[m]
...
z[n-3,m] = b[n-2]*x[m] + z[n-2,m-1] - a[n-2]*y[m]
z[n-2,m] = b[n-1]*x[m] - a[n-1]*y[m]
where m is the output sample number and n=max(len(a),len(b)) is the model order.
The rational transfer function describing this filter in the z-transform domain is:
-1 -nb
b[0] + b[1]z + ... + b[nb] z
Y(z) = ---------------------------------- X(z)
-1 -na
a[0] + a[1]z + ... + a[na] z
lfiltic(b, a, y, x=None)
Construct initial conditions for lfilter
Given a linear filter (b,a) and initial conditions on the output y and the input x, return the inital conditions on the
state vector zi which is used by lfilter to generate the output given the input.
If M=len(b)-1 and N=len(a)-1. Then, the initial conditions are given in the vectors x and y as:
x = {x[-1],x[-2],...,x[-M]}
y = {y[-1],y[-2],...,y[-N]}
If x is not given, its inital conditions are assumed zero. If either vector is too short, then zeros are added to
achieve the proper length.
The output vector zi contains:
zi = {z_0[-1], z_1[-1], ..., z_K-1[-1]} where K=max(M,N).
deconvolve(signal, divisor)
Deconvolves divisor out of signal.
hilbert(x, N=None, axis=-1)
Compute the analytic signal.
The transformation is done along the last axis by default.
Parameters
x : array-like
Signal data
N : int, optional
332 Chapter 3. Reference