scipy.signal.residue¶

scipy.signal.
residue
(b, a, tol=0.001, rtype='avg')[source]¶ Compute partialfraction expansion of b(s) / a(s).
If M is the degree of numerator b and N the degree of denominator a:
b(s) b[0] s**(M) + b[1] s**(M1) + ... + b[M] H(s) =  =  a(s) a[0] s**(N) + a[1] s**(N1) + ... + a[N]
then the partialfraction expansion H(s) is defined as:
r[0] r[1] r[1] =  +  + ... +  + k(s) (sp[0]) (sp[1]) (sp[1])
If there are any repeated roots (closer together than tol), then H(s) has terms like:
r[i] r[i+1] r[i+n1]  +  + ... +  (sp[i]) (sp[i])**2 (sp[i])**n
This function is used for polynomials in positive powers of s or z, such as analog filters or digital filters in controls engineering. For negative powers of z (typical for digital filters in DSP), use
residuez
.See Notes for details about the algorithm.
 Parameters
 barray_like
Numerator polynomial coefficients.
 aarray_like
Denominator polynomial coefficients.
 tolfloat, optional
The tolerance for two roots to be considered equal in terms of the distance between them. Default is 1e3. See
unique_roots
for further details. rtype{‘avg’, ‘min’, ‘max’}, optional
Method for computing a root to represent a group of identical roots. Default is ‘avg’. See
unique_roots
for further details.
 Returns
 rndarray
Residues corresponding to the poles. For repeated poles, the residues are ordered to correspond to ascending by power fractions.
 pndarray
Poles ordered by magnitude in ascending order.
 kndarray
Coefficients of the direct polynomial term.
See also
Notes
The “deflation through subtraction” algorithm is used for computations — method 6 in [1].
The form of partial fraction expansion depends on poles multiplicity in the exact mathematical sense. However there is no way to exactly determine multiplicity of roots of a polynomial in numerical computing. Thus you should think of the result of
residue
with given tol as partial fraction expansion computed for the denominator composed of the computed poles with empirically determined multiplicity. The choice of tol can drastically change the result if there are close poles.References
 1
J. F. Mahoney, B. D. Sivazlian, “Partial fractions expansion: a review of computational methodology and efficiency”, Journal of Computational and Applied Mathematics, Vol. 9, 1983.