scipy.signal.residue

scipy.signal.residue(b, a, tol=0.001, rtype='avg')

Compute partial-fraction 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**(M-1) + ... + b[M]
H(s) = ------ = ------------------------------------------
        a(s)     a[0] s**(N) + a[1] s**(N-1) + ... + a[N]

then the partial-fraction expansion H(s) is defined as:

    r[0]       r[1]             r[-1]
= -------- + -------- + ... + --------- + k(s)
  (s-p[0])   (s-p[1])         (s-p[-1])

If there are any repeated roots (closer together than tol), then H(s) has terms like:

  r[i]      r[i+1]              r[i+n-1]
-------- + ----------- + ... + -----------
(s-p[i])  (s-p[i])**2          (s-p[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 1e-3. 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

invres, residuez, numpy.poly, unique_roots

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.

scipy.signal.unique_roots scipy.signal.residuez