223 lines
7.5 KiB
Python
223 lines
7.5 KiB
Python
from itertools import combinations_with_replacement
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from sympy.core import symbols, Add, Dummy
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from sympy.core.numbers import Rational
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from sympy.polys import cancel, ComputationFailed, parallel_poly_from_expr, reduced, Poly
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from sympy.polys.monomials import Monomial, monomial_div
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from sympy.polys.polyerrors import DomainError, PolificationFailed
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from sympy.utilities.misc import debug, debugf
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def ratsimp(expr):
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"""
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Put an expression over a common denominator, cancel and reduce.
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Examples
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========
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>>> from sympy import ratsimp
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>>> from sympy.abc import x, y
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>>> ratsimp(1/x + 1/y)
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(x + y)/(x*y)
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"""
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f, g = cancel(expr).as_numer_denom()
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try:
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Q, r = reduced(f, [g], field=True, expand=False)
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except ComputationFailed:
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return f/g
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return Add(*Q) + cancel(r/g)
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def ratsimpmodprime(expr, G, *gens, quick=True, polynomial=False, **args):
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"""
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Simplifies a rational expression ``expr`` modulo the prime ideal
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generated by ``G``. ``G`` should be a Groebner basis of the
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ideal.
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Examples
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========
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>>> from sympy.simplify.ratsimp import ratsimpmodprime
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>>> from sympy.abc import x, y
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>>> eq = (x + y**5 + y)/(x - y)
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>>> ratsimpmodprime(eq, [x*y**5 - x - y], x, y, order='lex')
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(-x**2 - x*y - x - y)/(-x**2 + x*y)
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If ``polynomial`` is ``False``, the algorithm computes a rational
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simplification which minimizes the sum of the total degrees of
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the numerator and the denominator.
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If ``polynomial`` is ``True``, this function just brings numerator and
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denominator into a canonical form. This is much faster, but has
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potentially worse results.
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References
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==========
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.. [1] M. Monagan, R. Pearce, Rational Simplification Modulo a Polynomial
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Ideal, https://dl.acm.org/doi/pdf/10.1145/1145768.1145809
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(specifically, the second algorithm)
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"""
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from sympy.solvers.solvers import solve
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debug('ratsimpmodprime', expr)
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# usual preparation of polynomials:
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num, denom = cancel(expr).as_numer_denom()
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try:
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polys, opt = parallel_poly_from_expr([num, denom] + G, *gens, **args)
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except PolificationFailed:
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return expr
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domain = opt.domain
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if domain.has_assoc_Field:
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opt.domain = domain.get_field()
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else:
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raise DomainError(
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"Cannot compute rational simplification over %s" % domain)
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# compute only once
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leading_monomials = [g.LM(opt.order) for g in polys[2:]]
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tested = set()
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def staircase(n):
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"""
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Compute all monomials with degree less than ``n`` that are
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not divisible by any element of ``leading_monomials``.
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"""
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if n == 0:
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return [1]
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S = []
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for mi in combinations_with_replacement(range(len(opt.gens)), n):
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m = [0]*len(opt.gens)
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for i in mi:
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m[i] += 1
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if all(monomial_div(m, lmg) is None for lmg in
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leading_monomials):
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S.append(m)
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return [Monomial(s).as_expr(*opt.gens) for s in S] + staircase(n - 1)
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def _ratsimpmodprime(a, b, allsol, N=0, D=0):
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r"""
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Computes a rational simplification of ``a/b`` which minimizes
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the sum of the total degrees of the numerator and the denominator.
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Explanation
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===========
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The algorithm proceeds by looking at ``a * d - b * c`` modulo
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the ideal generated by ``G`` for some ``c`` and ``d`` with degree
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less than ``a`` and ``b`` respectively.
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The coefficients of ``c`` and ``d`` are indeterminates and thus
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the coefficients of the normalform of ``a * d - b * c`` are
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linear polynomials in these indeterminates.
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If these linear polynomials, considered as system of
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equations, have a nontrivial solution, then `\frac{a}{b}
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\equiv \frac{c}{d}` modulo the ideal generated by ``G``. So,
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by construction, the degree of ``c`` and ``d`` is less than
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the degree of ``a`` and ``b``, so a simpler representation
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has been found.
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After a simpler representation has been found, the algorithm
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tries to reduce the degree of the numerator and denominator
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and returns the result afterwards.
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As an extension, if quick=False, we look at all possible degrees such
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that the total degree is less than *or equal to* the best current
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solution. We retain a list of all solutions of minimal degree, and try
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to find the best one at the end.
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"""
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c, d = a, b
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steps = 0
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maxdeg = a.total_degree() + b.total_degree()
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if quick:
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bound = maxdeg - 1
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else:
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bound = maxdeg
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while N + D <= bound:
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if (N, D) in tested:
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break
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tested.add((N, D))
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M1 = staircase(N)
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M2 = staircase(D)
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debugf('%s / %s: %s, %s', (N, D, M1, M2))
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Cs = symbols("c:%d" % len(M1), cls=Dummy)
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Ds = symbols("d:%d" % len(M2), cls=Dummy)
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ng = Cs + Ds
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c_hat = Poly(
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sum([Cs[i] * M1[i] for i in range(len(M1))]), opt.gens + ng)
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d_hat = Poly(
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sum([Ds[i] * M2[i] for i in range(len(M2))]), opt.gens + ng)
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r = reduced(a * d_hat - b * c_hat, G, opt.gens + ng,
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order=opt.order, polys=True)[1]
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S = Poly(r, gens=opt.gens).coeffs()
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sol = solve(S, Cs + Ds, particular=True, quick=True)
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if sol and not all(s == 0 for s in sol.values()):
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c = c_hat.subs(sol)
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d = d_hat.subs(sol)
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# The "free" variables occurring before as parameters
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# might still be in the substituted c, d, so set them
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# to the value chosen before:
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c = c.subs(dict(list(zip(Cs + Ds, [1] * (len(Cs) + len(Ds))))))
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d = d.subs(dict(list(zip(Cs + Ds, [1] * (len(Cs) + len(Ds))))))
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c = Poly(c, opt.gens)
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d = Poly(d, opt.gens)
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if d == 0:
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raise ValueError('Ideal not prime?')
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allsol.append((c_hat, d_hat, S, Cs + Ds))
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if N + D != maxdeg:
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allsol = [allsol[-1]]
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break
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steps += 1
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N += 1
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D += 1
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if steps > 0:
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c, d, allsol = _ratsimpmodprime(c, d, allsol, N, D - steps)
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c, d, allsol = _ratsimpmodprime(c, d, allsol, N - steps, D)
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return c, d, allsol
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# preprocessing. this improves performance a bit when deg(num)
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# and deg(denom) are large:
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num = reduced(num, G, opt.gens, order=opt.order)[1]
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denom = reduced(denom, G, opt.gens, order=opt.order)[1]
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if polynomial:
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return (num/denom).cancel()
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c, d, allsol = _ratsimpmodprime(
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Poly(num, opt.gens, domain=opt.domain), Poly(denom, opt.gens, domain=opt.domain), [])
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if not quick and allsol:
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debugf('Looking for best minimal solution. Got: %s', len(allsol))
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newsol = []
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for c_hat, d_hat, S, ng in allsol:
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sol = solve(S, ng, particular=True, quick=False)
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# all values of sol should be numbers; if not, solve is broken
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newsol.append((c_hat.subs(sol), d_hat.subs(sol)))
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c, d = min(newsol, key=lambda x: len(x[0].terms()) + len(x[1].terms()))
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if not domain.is_Field:
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cn, c = c.clear_denoms(convert=True)
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dn, d = d.clear_denoms(convert=True)
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r = Rational(cn, dn)
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else:
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r = Rational(1)
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return (c*r.q)/(d*r.p)
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