Source code for sympy.polys.partfrac

"""Algorithms for partial fraction decomposition of rational functions. """

from sympy.polys import Poly, RootSum, cancel, factor
from sympy.polys.polytools import parallel_poly_from_expr

from sympy.core import S, Add, sympify, Symbol, Function, Lambda, Dummy
from sympy.utilities import numbered_symbols, take, threaded

[docs]def apart(f, x=None, full=False): """ Compute partial fraction decomposition of a rational function. Given a rational function ``f`` compute partial fraction decomposition of ``f``. Two algorithms are available: one is based on undetermined coefficients method and the other is Bronstein's full partial fraction decomposition algorithm. **Examples** >>> from sympy.polys.partfrac import apart >>> from import x, y >>> apart(y/(x + 2)/(x + 1), x) -y/(x + 2) + y/(x + 1) """ f = sympify(f) if f.is_Atom: return f else: P, Q = f.as_numer_denom() (P, Q), opt = parallel_poly_from_expr((P, Q), x) if P.is_multivariate: raise NotImplementedError("multivariate partial fraction decomposition") common, P, Q = P.cancel(Q) poly, P = P.div(Q, auto=True) P, Q = P.rat_clear_denoms(Q) if <= 1: partial = P/Q else: if not full: partial = apart_undetermined_coeffs(P, Q) else: partial = apart_full_decomposition(P, Q) terms = S.Zero for term in Add.make_args(partial): terms += factor(term) return common*(poly.as_expr() + terms)
def apart_undetermined_coeffs(P, Q): """Partial fractions via method of undetermined coefficients. """ X = numbered_symbols(cls=Dummy) partial, symbols = [], [] _, factors = Q.factor_list() for f, k in factors: n, q =, Q for i in xrange(1, k+1): coeffs, q = take(X, n), q.quo(f) partial.append((coeffs, q, f, i)) symbols.extend(coeffs) dom = Q.get_domain().inject(*symbols) F = Poly(0, Q.gen, domain=dom) for i, (coeffs, q, f, k) in enumerate(partial): h = Poly(coeffs, Q.gen, domain=dom) partial[i] = (h, f, k) q = q.set_domain(dom) F += h*q system, result = [], S(0) for (k,), coeff in F.terms(): system.append(coeff - P.nth(k)) from sympy.solvers import solve solution = solve(system, symbols) for h, f, k in partial: h = h.as_expr().subs(solution) result += h/f.as_expr()**k return result def apart_full_decomposition(P, Q): """ Bronstein's full partial fraction decomposition algorithm. Given a univariate rational function ``f``, performing only GCD operations over the algebraic closure of the initial ground domain of definition, compute full partial fraction decomposition with fractions having linear denominators. Note that no factorization of the initial denominator of ``f`` is performed. The final decomposition is formed in terms of a sum of :class:`RootSum` instances. **References** 1. [Bronstein93]_ """ f, x, U = P/Q, P.gen, [] u = Function('u')(x) a = Dummy('a') partial = S(0) for d, n in Q.sqf_list_include(all=True): b = d.as_expr() U += [ u.diff(x, n-1) ] h = cancel(f*b**n) / u**n H, subs = [h], [] for j in range(1, n): H += [ H[-1].diff(x) / j ] for j in range(1, n+1): subs += [ (U[j-1], b.diff(x, j) / j) ] for j in range(0, n): P, Q = cancel(H[j]).as_numer_denom() for i in range(0, j+1): P = P.subs(*subs[j-i]) Q = Q.subs(*subs[0]) P = Poly(P, x) Q = Poly(Q, x) G = P.gcd(d) D = d.quo(G) B, g = Q.half_gcdex(D) b = (P * B.quo(g)).rem(D) numer = b.as_expr() denom = (x-a)**(n-j) expr = numer.subs(x, a) / denom partial += RootSum(D, Lambda(a, expr)) return partial