def horner(f, *gens, **args): """ Rewrite a polynomial in Horner form. **Examples** >>> from sympy.polys.polyfuncs import horner >>> from sympy.abc import x, y, a, b, c, d, e >>> horner(9*x**4 + 8*x**3 + 7*x**2 + 6*x + 5) x*(x*(x*(9*x + 8) + 7) + 6) + 5 >>> horner(a*x**4 + b*x**3 + c*x**2 + d*x + e) e + x*(d + x*(c + x*(a*x + b))) >>> f = 4*x**2*y**2 + 2*x**2*y + 2*x*y**2 + x*y >>> horner(f, wrt=x) x*(x*y*(4*y + 2) + y*(2*y + 1)) >>> horner(f, wrt=y) y*(x*y*(4*x + 2) + x*(2*x + 1)) """ allowed_flags(args, []) try: F, opt = poly_from_expr(f, *gens, **args) except PolificationFailed, exc: return exc.expr
def viete(f, roots=None, *gens, **args): """ Generate Viete's formulas for ``f``. Examples ======== >>> from sympy.polys.polyfuncs import viete >>> from sympy import symbols >>> x, a, b, c, r1, r2 = symbols('x,a:c,r1:3') >>> viete(a*x**2 + b*x + c, [r1, r2], x) [(r1 + r2, -b/a), (r1*r2, c/a)] """ allowed_flags(args, []) if isinstance(roots, Basic): gens, roots = (roots,) + gens, None try: f, opt = poly_from_expr(f, *gens, **args) except PolificationFailed, exc: raise ComputationFailed('viete', 1, exc)
def horner(f, *gens, **args): """ Rewrite a polynomial in Horner form. Examples ======== >>> from sympy.polys.polyfuncs import horner >>> from sympy.abc import x, y, a, b, c, d, e >>> horner(9*x**4 + 8*x**3 + 7*x**2 + 6*x + 5) x*(x*(x*(9*x + 8) + 7) + 6) + 5 >>> horner(a*x**4 + b*x**3 + c*x**2 + d*x + e) e + x*(d + x*(c + x*(a*x + b))) >>> f = 4*x**2*y**2 + 2*x**2*y + 2*x*y**2 + x*y >>> horner(f, wrt=x) x*(x*y*(4*y + 2) + y*(2*y + 1)) >>> horner(f, wrt=y) y*(x*y*(4*x + 2) + x*(2*x + 1)) """ allowed_flags(args, []) try: F, opt = poly_from_expr(f, *gens, **args) except PolificationFailed, exc: return exc.expr
def horner(f, *gens, **args): """ Rewrite a polynomial in Horner form. **Examples** >>> from sympy.polys.polyfuncs import horner >>> from sympy.abc import x, y, a, b, c, d, e >>> horner(9*x**4 + 8*x**3 + 7*x**2 + 6*x + 5) 5 + x*(6 + x*(7 + x*(8 + 9*x))) >>> horner(a*x**4 + b*x**3 + c*x**2 + d*x + e) e + x*(d + x*(c + x*(b + a*x))) >>> f = 4*x**2*y**2 + 2*x**2*y + 2*x*y**2 + x*y >>> horner(f, wrt=x) x*(y*(1 + 2*y) + x*y*(2 + 4*y)) >>> horner(f, wrt=y) y*(x*(1 + 2*x) + x*y*(2 + 4*x)) """ allowed_flags(args, []) try: F, opt = poly_from_expr(f, *gens, **args) except PolificationFailed, exc: return exc.expr
def viete(f, roots=None, *gens, **args): """ Generate Viete's formulas for ``f``. Examples ======== >>> from sympy.polys.polyfuncs import viete >>> from sympy import symbols >>> x, a, b, c, r1, r2 = symbols('x,a:c,r1:3') >>> viete(a*x**2 + b*x + c, [r1, r2], x) [(r1 + r2, -b/a), (r1*r2, c/a)] """ allowed_flags(args, []) if isinstance(roots, Basic): gens, roots = (roots,) + gens, None try: f, opt = poly_from_expr(f, *gens, **args) except PolificationFailed, exc: raise ComputationFailed("viete", 1, exc)
def apart(f, x=None, full=False, **options): """ 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 sympy.abc import x, y >>> apart(y/(x + 2)/(x + 1), x) -y/(x + 2) + y/(x + 1) """ allowed_flags(options, []) f = sympify(f) if f.is_Atom: return f else: P, Q = f.as_numer_denom() options = set_defaults(options, extension=True) (P, Q), opt = parallel_poly_from_expr((P, Q), x, **options) 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 Q.degree() <= 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): if term.has(RootSum): terms += term else: terms += factor(term) return common*(poly.as_expr() + terms)
def apart(f, x=None, full=False, **options): """ 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 sympy.abc import x, y >>> apart(y/(x + 2)/(x + 1), x) -y/(x + 2) + y/(x + 1) """ allowed_flags(options, []) f = sympify(f) if f.is_Atom: return f else: P, Q = f.as_numer_denom() options = set_defaults(options, extension=True) (P, Q), opt = parallel_poly_from_expr((P, Q), x, **options) 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 Q.degree() <= 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): if term.has(RootSum): terms += term else: terms += factor(term) return common * (poly.as_expr() + terms)
def viete(f, roots=None, *gens, **args): """ Generate Viete's formulas for ``f``. Examples ======== >>> from sympy.polys.polyfuncs import viete >>> from sympy import symbols >>> x, a, b, c, r1, r2 = symbols('x,a:c,r1:3') >>> viete(a*x**2 + b*x + c, [r1, r2], x) [(r1 + r2, -b/a), (r1*r2, c/a)] """ allowed_flags(args, []) if isinstance(roots, Basic): gens, roots = (roots, ) + gens, None try: f, opt = poly_from_expr(f, *gens, **args) except PolificationFailed as exc: raise ComputationFailed('viete', 1, exc) if f.is_multivariate: raise MultivariatePolynomialError( "multivariate polynomials are not allowed") n = f.degree() if n < 1: raise ValueError( "can't derive Viete's formulas for a constant polynomial") if roots is None: roots = numbered_symbols('r', start=1) roots = take(roots, n) if n != len(roots): raise ValueError("required %s roots, got %s" % (n, len(roots))) lc, coeffs = f.LC(), f.all_coeffs() result, sign = [], -1 for i, coeff in enumerate(coeffs[1:]): poly = symmetric_poly(i + 1, roots) coeff = sign * (coeff / lc) result.append((poly, coeff)) sign = -sign return result
def viete(f, roots=None, *gens, **args): """ Generate Viete's formulas for ``f``. Examples ======== >>> from sympy.polys.polyfuncs import viete >>> from sympy import symbols >>> x, a, b, c, r1, r2 = symbols('x,a:c,r1:3') >>> viete(a*x**2 + b*x + c, [r1, r2], x) [(r1 + r2, -b/a), (r1*r2, c/a)] """ allowed_flags(args, []) if isinstance(roots, Basic): gens, roots = (roots,) + gens, None try: f, opt = poly_from_expr(f, *gens, **args) except PolificationFailed as exc: raise ComputationFailed('viete', 1, exc) if f.is_multivariate: raise MultivariatePolynomialError( "multivariate polynomials are not allowed") n = f.degree() if n < 1: raise ValueError( "can't derive Viete's formulas for a constant polynomial") if roots is None: roots = numbered_symbols('r', start=1) roots = take(roots, n) if n != len(roots): raise ValueError("required %s roots, got %s" % (n, len(roots))) lc, coeffs = f.LC(), f.all_coeffs() result, sign = [], -1 for i, coeff in enumerate(coeffs[1:]): poly = symmetric_poly(i + 1, roots) coeff = sign*(coeff/lc) result.append((poly, coeff)) sign = -sign return result
def symmetrize(F, *gens, **args): """ Rewrite a polynomial in terms of elementary symmetric polynomials. Examples ======== >>> from sympy.polys.polyfuncs import symmetrize >>> from sympy.abc import x, y >>> symmetrize(x**2 + y**2) (-2*x*y + (x + y)**2, 0) >>> symmetrize(x**2 + y**2, formal=True) (s1**2 - 2*s2, 0, [(s1, x + y), (s2, x*y)]) >>> symmetrize(x**2 - y**2) (-2*x*y + (x + y)**2, -2*y**2) >>> symmetrize(x**2 - y**2, formal=True) (s1**2 - 2*s2, -2*y**2, [(s1, x + y), (s2, x*y)]) """ allowed_flags(args, ["formal", "symbols"]) iterable = True if not hasattr(F, "__iter__"): iterable = False F = [F] try: F, opt = parallel_poly_from_expr(F, *gens, **args) except PolificationFailed, exc: result = [] for expr in exc.exprs: if expr.is_Number: result.append((expr, S.Zero)) else: raise ComputationFailed("symmetrize", len(F), exc) else: if not iterable: result, = result if not exc.opt.formal: return result else: if iterable: return result, [] else: return result + ([],)
def symmetrize(F, *gens, **args): """ Rewrite a polynomial in terms of elementary symmetric polynomials. Examples ======== >>> from sympy.polys.polyfuncs import symmetrize >>> from sympy.abc import x, y >>> symmetrize(x**2 + y**2) (-2*x*y + (x + y)**2, 0) >>> symmetrize(x**2 + y**2, formal=True) (s1**2 - 2*s2, 0, [(s1, x + y), (s2, x*y)]) >>> symmetrize(x**2 - y**2) (-2*x*y + (x + y)**2, -2*y**2) >>> symmetrize(x**2 - y**2, formal=True) (s1**2 - 2*s2, -2*y**2, [(s1, x + y), (s2, x*y)]) """ allowed_flags(args, ['formal', 'symbols']) iterable = True if not hasattr(F, '__iter__'): iterable = False F = [F] try: F, opt = parallel_poly_from_expr(F, *gens, **args) except PolificationFailed, exc: result = [] for expr in exc.exprs: if expr.is_Number: result.append((expr, S.Zero)) else: raise ComputationFailed('symmetrize', len(F), exc) else: if not iterable: result, = result if not exc.opt.formal: return result else: if iterable: return result, [] else: return result + ([],)
def horner(f, *gens, **args): """ Rewrite a polynomial in Horner form. Among other applications, evaluation of a polynomial at a point is optimal when it is applied using the Horner scheme ([1]). Examples ======== >>> from sympy.polys.polyfuncs import horner >>> from sympy.abc import x, y, a, b, c, d, e >>> horner(9*x**4 + 8*x**3 + 7*x**2 + 6*x + 5) x*(x*(x*(9*x + 8) + 7) + 6) + 5 >>> horner(a*x**4 + b*x**3 + c*x**2 + d*x + e) e + x*(d + x*(c + x*(a*x + b))) >>> f = 4*x**2*y**2 + 2*x**2*y + 2*x*y**2 + x*y >>> horner(f, wrt=x) x*(x*y*(4*y + 2) + y*(2*y + 1)) >>> horner(f, wrt=y) y*(x*y*(4*x + 2) + x*(2*x + 1)) References ========== [1] - http://en.wikipedia.org/wiki/Horner_scheme """ allowed_flags(args, []) try: F, opt = poly_from_expr(f, *gens, **args) except PolificationFailed as exc: return exc.expr form, gen = S.Zero, F.gen if F.is_univariate: for coeff in F.all_coeffs(): form = form*gen + coeff else: F, gens = Poly(F, gen), gens[1:] for coeff in F.all_coeffs(): form = form*gen + horner(coeff, *gens, **args) return form
def horner(f, *gens, **args): """ Rewrite a polynomial in Horner form. Among other applications, evaluation of a polynomial at a point is optimal when it is applied using the Horner scheme ([1]). Examples ======== >>> from sympy.polys.polyfuncs import horner >>> from sympy.abc import x, y, a, b, c, d, e >>> horner(9*x**4 + 8*x**3 + 7*x**2 + 6*x + 5) x*(x*(x*(9*x + 8) + 7) + 6) + 5 >>> horner(a*x**4 + b*x**3 + c*x**2 + d*x + e) e + x*(d + x*(c + x*(a*x + b))) >>> f = 4*x**2*y**2 + 2*x**2*y + 2*x*y**2 + x*y >>> horner(f, wrt=x) x*(x*y*(4*y + 2) + y*(2*y + 1)) >>> horner(f, wrt=y) y*(x*y*(4*x + 2) + x*(2*x + 1)) References ========== [1] - http://en.wikipedia.org/wiki/Horner_scheme """ allowed_flags(args, []) try: F, opt = poly_from_expr(f, *gens, **args) except PolificationFailed as exc: return exc.expr form, gen = S.Zero, F.gen if F.is_univariate: for coeff in F.all_coeffs(): form = form * gen + coeff else: F, gens = Poly(F, gen), gens[1:] for coeff in F.all_coeffs(): form = form * gen + horner(coeff, *gens, **args) return form
def __new__(cls, iterative, F, n, *gens, **args): """Compute a reduced Groebner basis for a system of polynomials. """ options.allowed_flags(args, ['polys', 'method']) try: polys, opt = parallel_poly_from_expr(F, *gens, **args) except PolificationFailed as exc: raise ComputationFailed('groebner', len(F), exc) from sympy.polys.rings import PolyRing ring = PolyRing(opt.gens, opt.domain, opt.order) polys = [ring.from_dict(poly.rep.to_dict()) for poly in polys if poly] if iterative: G = iter_groebner(polys, n, ring, method=opt.method ) #Assumes last element is the "new" polynomial else: G = _groebner(polys, ring, method=opt.method) G = [Poly._from_dict(g, opt) for g in G] return cls._new(G, opt)
def symmetrize(F, *gens, **args): """ Rewrite a polynomial in terms of elementary symmetric polynomials. A symmetric polynomial is a multivariate polynomial that remains invariant under any variable permutation, i.e., if ``f = f(x_1, x_2, ..., x_n)``, then ``f = f(x_{i_1}, x_{i_2}, ..., x_{i_n})``, where ``(i_1, i_2, ..., i_n)`` is a permutation of ``(1, 2, ..., n)`` (an element of the group ``S_n``). Returns a tuple of symmetric polynomials ``(f1, f2, ..., fn)`` such that ``f = f1 + f2 + ... + fn``. Examples ======== >>> from sympy.polys.polyfuncs import symmetrize >>> from sympy.abc import x, y >>> symmetrize(x**2 + y**2) (-2*x*y + (x + y)**2, 0) >>> symmetrize(x**2 + y**2, formal=True) (s1**2 - 2*s2, 0, [(s1, x + y), (s2, x*y)]) >>> symmetrize(x**2 - y**2) (-2*x*y + (x + y)**2, -2*y**2) >>> symmetrize(x**2 - y**2, formal=True) (s1**2 - 2*s2, -2*y**2, [(s1, x + y), (s2, x*y)]) """ allowed_flags(args, ['formal', 'symbols']) iterable = True if not hasattr(F, '__iter__'): iterable = False F = [F] try: F, opt = parallel_poly_from_expr(F, *gens, **args) except PolificationFailed as exc: result = [] for expr in exc.exprs: if expr.is_Number: result.append((expr, S.Zero)) else: raise ComputationFailed('symmetrize', len(F), exc) else: if not iterable: result, = result if not exc.opt.formal: return result else: if iterable: return result, [] else: return result + ([], ) polys, symbols = [], opt.symbols gens, dom = opt.gens, opt.domain for i in xrange(0, len(gens)): poly = symmetric_poly(i + 1, gens, polys=True) polys.append((symbols.next(), poly.set_domain(dom))) indices = range(0, len(gens) - 1) weights = range(len(gens), 0, -1) result = [] for f in F: symmetric = [] if not f.is_homogeneous: symmetric.append(f.TC()) f -= f.TC() while f: _height, _monom, _coeff = -1, None, None for i, (monom, coeff) in enumerate(f.terms()): if all(monom[i] >= monom[i + 1] for i in indices): height = max([n * m for n, m in zip(weights, monom)]) if height > _height: _height, _monom, _coeff = height, monom, coeff if _height != -1: monom, coeff = _monom, _coeff else: break exponents = [] for m1, m2 in zip(monom, monom[1:] + (0, )): exponents.append(m1 - m2) term = [s**n for (s, _), n in zip(polys, exponents)] poly = [p**n for (_, p), n in zip(polys, exponents)] symmetric.append(Mul(coeff, *term)) product = poly[0].mul(coeff) for p in poly[1:]: product = product.mul(p) f -= product result.append((Add(*symmetric), f.as_expr())) polys = [(s, p.as_expr()) for s, p in polys] if not opt.formal: for i, (sym, non_sym) in enumerate(result): result[i] = (sym.subs(polys), non_sym) if not iterable: result, = result if not opt.formal: return result else: if iterable: return result, polys else: return result + (polys, )
def symmetrize(F, *gens, **args): """ Rewrite a polynomial in terms of elementary symmetric polynomials. A symmetric polynomial is a multivariate polynomial that remains invariant under any variable permutation, i.e., if ``f = f(x_1, x_2, ..., x_n)``, then ``f = f(x_{i_1}, x_{i_2}, ..., x_{i_n})``, where ``(i_1, i_2, ..., i_n)`` is a permutation of ``(1, 2, ..., n)`` (an element of the group ``S_n``). Returns a tuple of symmetric polynomials ``(f1, f2, ..., fn)`` such that ``f = f1 + f2 + ... + fn``. Examples ======== >>> from sympy.polys.polyfuncs import symmetrize >>> from sympy.abc import x, y >>> symmetrize(x**2 + y**2) (-2*x*y + (x + y)**2, 0) >>> symmetrize(x**2 + y**2, formal=True) (s1**2 - 2*s2, 0, [(s1, x + y), (s2, x*y)]) >>> symmetrize(x**2 - y**2) (-2*x*y + (x + y)**2, -2*y**2) >>> symmetrize(x**2 - y**2, formal=True) (s1**2 - 2*s2, -2*y**2, [(s1, x + y), (s2, x*y)]) """ allowed_flags(args, ["formal", "symbols"]) iterable = True if not hasattr(F, "__iter__"): iterable = False F = [F] try: F, opt = parallel_poly_from_expr(F, *gens, **args) except PolificationFailed, exc: result = [] for expr in exc.exprs: if expr.is_Number: result.append((expr, S.Zero)) else: raise ComputationFailed("symmetrize", len(F), exc) else: if not iterable: result, = result if not exc.opt.formal: return result else: if iterable: return result, [] else: return result + ([],)
def apart_list(f, x=None, dummies=None, **options): """ Compute partial fraction decomposition of a rational function and return the result in structured form. Given a rational function ``f`` compute the partial fraction decomposition of ``f``. Only Bronstein's full partial fraction decomposition algorithm is supported by this method. The return value is highly structured and perfectly suited for further algorithmic treatment rather than being human-readable. The function returns a tuple holding three elements: * The first item is the common coefficient, free of the variable `x` used for decomposition. (It is an element of the base field `K`.) * The second item is the polynomial part of the decomposition. This can be the zero polynomial. (It is an element of `K[x]`.) * The third part itself is a list of quadruples. Each quadruple has the following elements in this order: - The (not necessarily irreducible) polynomial `D` whose roots `w_i` appear in the linear denominator of a bunch of related fraction terms. (This item can also be a list of explicit roots. However, at the moment ``apart_list`` never returns a result this way, but the related ``assemble_partfrac_list`` function accepts this format as input.) - The numerator of the fraction, written as a function of the root `w` - The linear denominator of the fraction *excluding its power exponent*, written as a function of the root `w`. - The power to which the denominator has to be raised. On can always rebuild a plain expression by using the function ``assemble_partfrac_list``. Examples ======== A first example: >>> from sympy.polys.partfrac import apart_list, assemble_partfrac_list >>> from sympy.abc import x, t >>> f = (2*x**3 - 2*x) / (x**2 - 2*x + 1) >>> pfd = apart_list(f) >>> pfd (1, Poly(2*x + 4, x, domain='ZZ'), [(Poly(_w - 1, _w, domain='ZZ'), Lambda(_a, 4), Lambda(_a, -_a + x), 1)]) >>> assemble_partfrac_list(pfd) 2*x + 4 + 4/(x - 1) Second example: >>> f = (-2*x - 2*x**2) / (3*x**2 - 6*x) >>> pfd = apart_list(f) >>> pfd (-1, Poly(2/3, x, domain='QQ'), [(Poly(_w - 2, _w, domain='ZZ'), Lambda(_a, 2), Lambda(_a, -_a + x), 1)]) >>> assemble_partfrac_list(pfd) -2/3 - 2/(x - 2) Another example, showing symbolic parameters: >>> pfd = apart_list(t/(x**2 + x + t), x) >>> pfd (1, Poly(0, x, domain='ZZ[t]'), [(Poly(_w**2 + _w + t, _w, domain='ZZ[t]'), Lambda(_a, -2*_a*t/(4*t - 1) - t/(4*t - 1)), Lambda(_a, -_a + x), 1)]) >>> assemble_partfrac_list(pfd) RootSum(_w**2 + _w + t, Lambda(_a, (-2*_a*t/(4*t - 1) - t/(4*t - 1))/(-_a + x))) This example is taken from Bronstein's original paper: >>> f = 36 / (x**5 - 2*x**4 - 2*x**3 + 4*x**2 + x - 2) >>> pfd = apart_list(f) >>> pfd (1, Poly(0, x, domain='ZZ'), [(Poly(_w - 2, _w, domain='ZZ'), Lambda(_a, 4), Lambda(_a, -_a + x), 1), (Poly(_w**2 - 1, _w, domain='ZZ'), Lambda(_a, -3*_a - 6), Lambda(_a, -_a + x), 2), (Poly(_w + 1, _w, domain='ZZ'), Lambda(_a, -4), Lambda(_a, -_a + x), 1)]) >>> assemble_partfrac_list(pfd) -4/(x + 1) - 3/(x + 1)**2 - 9/(x - 1)**2 + 4/(x - 2) See also ======== apart, assemble_partfrac_list References ========== 1. [Bronstein93]_ """ allowed_flags(options, []) f = sympify(f) if f.is_Atom: return f else: P, Q = f.as_numer_denom() options = set_defaults(options, extension=True) (P, Q), opt = parallel_poly_from_expr((P, Q), x, **options) 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) polypart = poly if dummies is None: def dummies(name): d = Dummy(name) while True: yield d dummies = dummies("w") rationalpart = apart_list_full_decomposition(P, Q, dummies) return (common, polypart, rationalpart)
def apart(f, x=None, full=False, **options): """ 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 sympy.abc import x, y By default, using the undetermined coefficients method: >>> apart(y/(x + 2)/(x + 1), x) -y/(x + 2) + y/(x + 1) You can choose Bronstein's algorithm by setting ``full=True``: >>> apart(y/(x**2 + x + 1), x) y/(x**2 + x + 1) >>> apart(y/(x**2 + x + 1), x, full=True) RootSum(_w**2 + _w + 1, Lambda(_a, (-2*_a*y/3 - y/3)/(-_a + x))) See Also ======== apart_list, assemble_partfrac_list """ allowed_flags(options, []) f = sympify(f) if f.is_Atom: return f else: P, Q = f.as_numer_denom() _options = options.copy() options = set_defaults(options, extension=True) try: (P, Q), opt = parallel_poly_from_expr((P, Q), x, **options) except PolynomialError as msg: if f.is_commutative: raise PolynomialError(msg) # non-commutative if f.is_Mul: c, nc = f.args_cnc(split_1=False) nc = Mul(*[apart(i, x=x, full=full, **_options) for i in nc]) if c: c = apart(Mul._from_args(c), x=x, full=full, **_options) return c*nc else: return nc elif f.is_Add: c = [] nc = [] for i in f.args: if i.is_commutative: c.append(i) else: try: nc.append(apart(i, x=x, full=full, **_options)) except NotImplementedError: nc.append(i) return apart(Add(*c), x=x, full=full, **_options) + Add(*nc) else: reps = [] pot = preorder_traversal(f) pot.next() for e in pot: try: reps.append((e, apart(e, x=x, full=full, **_options))) pot.skip() # this was handled successfully except NotImplementedError: pass return f.xreplace(dict(reps)) if P.is_multivariate: fc = f.cancel() if fc != f: return apart(fc, x=x, full=full, **_options) 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 Q.degree() <= 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): if term.has(RootSum): terms += term else: terms += factor(term) return common*(poly.as_expr() + terms)
def apart(f, x=None, full=False, **options): """ Compute partial fraction decomposition of a rational function. Given a rational function ``f``, computes the partial fraction decomposition of ``f``. Two algorithms are available: One is based on the undertermined coefficients method, the other is Bronstein's full partial fraction decomposition algorithm. The undetermined coefficients method (selected by ``full=False``) uses polynomial factorization (and therefore accepts the same options as factor) for the denominator. Per default it works over the rational numbers, therefore decomposition of denominators with non-rational roots (e.g. irrational, complex roots) is not supported by default (see options of factor). Bronstein's algorithm can be selected by using ``full=True`` and allows a decomposition of denominators with non-rational roots. A human-readable result can be obtained via ``doit()`` (see examples below). Examples ======== >>> from sympy.polys.partfrac import apart >>> from sympy.abc import x, y By default, using the undetermined coefficients method: >>> apart(y/(x + 2)/(x + 1), x) -y/(x + 2) + y/(x + 1) The undetermined coefficients method does not provide a result when the denominators roots are not rational: >>> apart(y/(x**2 + x + 1), x) y/(x**2 + x + 1) You can choose Bronstein's algorithm by setting ``full=True``: >>> apart(y/(x**2 + x + 1), x, full=True) RootSum(_w**2 + _w + 1, Lambda(_a, (-2*_a*y/3 - y/3)/(-_a + x))) Calling ``doit()`` yields a human-readable result: >>> apart(y/(x**2 + x + 1), x, full=True).doit() (-y/3 - 2*y*(-1/2 - sqrt(3)*I/2)/3)/(x + 1/2 + sqrt(3)*I/2) + (-y/3 - 2*y*(-1/2 + sqrt(3)*I/2)/3)/(x + 1/2 - sqrt(3)*I/2) See Also ======== apart_list, assemble_partfrac_list """ allowed_flags(options, []) f = sympify(f) if f.is_Atom: return f else: P, Q = f.as_numer_denom() _options = options.copy() options = set_defaults(options, extension=True) try: (P, Q), opt = parallel_poly_from_expr((P, Q), x, **options) except PolynomialError as msg: if f.is_commutative: raise PolynomialError(msg) # non-commutative if f.is_Mul: c, nc = f.args_cnc(split_1=False) nc = f.func(*nc) if c: c = apart(f.func._from_args(c), x=x, full=full, **_options) return c*nc else: return nc elif f.is_Add: c = [] nc = [] for i in f.args: if i.is_commutative: c.append(i) else: try: nc.append(apart(i, x=x, full=full, **_options)) except NotImplementedError: nc.append(i) return apart(f.func(*c), x=x, full=full, **_options) + f.func(*nc) else: reps = [] pot = preorder_traversal(f) next(pot) for e in pot: try: reps.append((e, apart(e, x=x, full=full, **_options))) pot.skip() # this was handled successfully except NotImplementedError: pass return f.xreplace(dict(reps)) if P.is_multivariate: fc = f.cancel() if fc != f: return apart(fc, x=x, full=full, **_options) 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 Q.degree() <= 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): if term.has(RootSum): terms += term else: terms += factor(term) return common*(poly.as_expr() + terms)
def symmetrize(F, *gens, **args): """ Rewrite a polynomial in terms of elementary symmetric polynomials. A symmetric polynomial is a multivariate polynomial that remains invariant under any variable permutation, i.e., if ``f = f(x_1, x_2, ..., x_n)``, then ``f = f(x_{i_1}, x_{i_2}, ..., x_{i_n})``, where ``(i_1, i_2, ..., i_n)`` is a permutation of ``(1, 2, ..., n)`` (an element of the group ``S_n``). Returns a tuple of symmetric polynomials ``(f1, f2, ..., fn)`` such that ``f = f1 + f2 + ... + fn``. Examples ======== >>> from sympy.polys.polyfuncs import symmetrize >>> from sympy.abc import x, y >>> symmetrize(x**2 + y**2) (-2*x*y + (x + y)**2, 0) >>> symmetrize(x**2 + y**2, formal=True) (s1**2 - 2*s2, 0, [(s1, x + y), (s2, x*y)]) >>> symmetrize(x**2 - y**2) (-2*x*y + (x + y)**2, -2*y**2) >>> symmetrize(x**2 - y**2, formal=True) (s1**2 - 2*s2, -2*y**2, [(s1, x + y), (s2, x*y)]) """ allowed_flags(args, ['formal', 'symbols']) iterable = True if not hasattr(F, '__iter__'): iterable = False F = [F] try: F, opt = parallel_poly_from_expr(F, *gens, **args) except PolificationFailed as exc: result = [] for expr in exc.exprs: if expr.is_Number: result.append((expr, S.Zero)) else: raise ComputationFailed('symmetrize', len(F), exc) else: if not iterable: result, = result if not exc.opt.formal: return result else: if iterable: return result, [] else: return result + ([],) polys, symbols = [], opt.symbols gens, dom = opt.gens, opt.domain for i in xrange(0, len(gens)): poly = symmetric_poly(i + 1, gens, polys=True) polys.append((next(symbols), poly.set_domain(dom))) indices = list(range(0, len(gens) - 1)) weights = list(range(len(gens), 0, -1)) result = [] for f in F: symmetric = [] if not f.is_homogeneous: symmetric.append(f.TC()) f -= f.TC() while f: _height, _monom, _coeff = -1, None, None for i, (monom, coeff) in enumerate(f.terms()): if all(monom[i] >= monom[i + 1] for i in indices): height = max([ n*m for n, m in zip(weights, monom) ]) if height > _height: _height, _monom, _coeff = height, monom, coeff if _height != -1: monom, coeff = _monom, _coeff else: break exponents = [] for m1, m2 in zip(monom, monom[1:] + (0,)): exponents.append(m1 - m2) term = [ s**n for (s, _), n in zip(polys, exponents) ] poly = [ p**n for (_, p), n in zip(polys, exponents) ] symmetric.append(Mul(coeff, *term)) product = poly[0].mul(coeff) for p in poly[1:]: product = product.mul(p) f -= product result.append((Add(*symmetric), f.as_expr())) polys = [ (s, p.as_expr()) for s, p in polys ] if not opt.formal: for i, (sym, non_sym) in enumerate(result): result[i] = (sym.subs(polys), non_sym) if not iterable: result, = result if not opt.formal: return result else: if iterable: return result, polys else: return result + (polys,)
def apart(f, x=None, full=False, **options): """ 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 sympy.abc import x, y By default, using the undetermined coefficients method: >>> apart(y/(x + 2)/(x + 1), x) -y/(x + 2) + y/(x + 1) You can choose Bronstein's algorithm by setting ``full=True``: >>> apart(y/(x**2 + x + 1), x) y/(x**2 + x + 1) >>> apart(y/(x**2 + x + 1), x, full=True) RootSum(_w**2 + _w + 1, Lambda(_a, (-2*_a*y/3 - y/3)/(-_a + x))) See Also ======== apart_list, assemble_partfrac_list """ allowed_flags(options, []) f = sympify(f) if f.is_Atom: return f else: P, Q = f.as_numer_denom() _options = options.copy() options = set_defaults(options, extension=True) try: (P, Q), opt = parallel_poly_from_expr((P, Q), x, **options) except PolynomialError as msg: if f.is_commutative: raise PolynomialError(msg) # non-commutative if f.is_Mul: c, nc = f.args_cnc(split_1=False) nc = f.func(*[apart(i, x=x, full=full, **_options) for i in nc]) if c: c = apart(f.func._from_args(c), x=x, full=full, **_options) return c*nc else: return nc elif f.is_Add: c = [] nc = [] for i in f.args: if i.is_commutative: c.append(i) else: try: nc.append(apart(i, x=x, full=full, **_options)) except NotImplementedError: nc.append(i) return apart(f.func(*c), x=x, full=full, **_options) + f.func(*nc) else: reps = [] pot = preorder_traversal(f) next(pot) for e in pot: try: reps.append((e, apart(e, x=x, full=full, **_options))) pot.skip() # this was handled successfully except NotImplementedError: pass return f.xreplace(dict(reps)) if P.is_multivariate: fc = f.cancel() if fc != f: return apart(fc, x=x, full=full, **_options) 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 Q.degree() <= 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): if term.has(RootSum): terms += term else: terms += factor(term) return common*(poly.as_expr() + terms)
def apart(f, x=None, full=False, **options): """ 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 sympy.abc import x, y By default, using the undetermined coefficients method: >>> apart(y/(x + 2)/(x + 1), x) -y/(x + 2) + y/(x + 1) You can choose Bronstein's algorithm by setting ``full=True``: >>> apart(y/(x**2 + x + 1), x) y/(x**2 + x + 1) >>> apart(y/(x**2 + x + 1), x, full=True) RootSum(_w**2 + _w + 1, Lambda(_a, (-2*_a*y/3 - y/3)/(-_a + x))) See Also ======== apart_list, assemble_partfrac_list """ allowed_flags(options, []) f = sympify(f) if f.is_Atom: return f else: P, Q = f.as_numer_denom() _options = options.copy() options = set_defaults(options, extension=True) try: (P, Q), opt = parallel_poly_from_expr((P, Q), x, **options) except PolynomialError, msg: if f.is_commutative: raise PolynomialError(msg) # non-commutative if f.is_Mul: c, nc = f.args_cnc(split_1=False) nc = Mul(*[apart(i, x=x, full=full, **_options) for i in nc]) if c: c = apart(Mul._from_args(c), x=x, full=full, **_options) return c*nc else: return nc elif f.is_Add: c = [] nc = [] for i in f.args: if i.is_commutative: c.append(i) else: try: nc.append(apart(i, x=x, full=full, **_options)) except NotImplementedError: nc.append(i) return apart(Add(*c), x=x, full=full, **_options) + Add(*nc) else: reps = [] pot = preorder_traversal(f) pot.next() for e in pot: try: reps.append((e, apart(e, x=x, full=full, **_options))) pot.skip() # this was handled successfully except NotImplementedError: pass return f.xreplace(dict(reps))
def apart_list(f, x=None, dummies=None, **options): """ Compute partial fraction decomposition of a rational function and return the result in structured form. Given a rational function ``f`` compute the partial fraction decomposition of ``f``. Only Bronstein's full partial fraction decomposition algorithm is supported by this method. The return value is highly structured and perfectly suited for further algorithmic treatment rather than being human-readable. The function returns a tuple holding three elements: * The first item is the common coefficient, free of the variable `x` used for decomposition. (It is an element of the base field `K`.) * The second item is the polynomial part of the decomposition. This can be the zero polynomial. (It is an element of `K[x]`.) * The third part itself is a list of quadruples. Each quadruple has the following elements in this order: - The (not necessarily irreducible) polynomial `D` whose roots `w_i` appear in the linear denominator of a bunch of related fraction terms. (This item can also be a list of explicit roots. However, at the moment ``apart_list`` never returns a result this way, but the related ``assemble_partfrac_list`` function accepts this format as input.) - The numerator of the fraction, written as a function of the root `w` - The linear denominator of the fraction *excluding its power exponent*, written as a function of the root `w`. - The power to which the denominator has to be raised. On can always rebuild a plain expression by using the function ``assemble_partfrac_list``. Examples ======== A first example: >>> from sympy.polys.partfrac import apart_list, assemble_partfrac_list >>> from sympy.abc import x, t >>> f = (2*x**3 - 2*x) / (x**2 - 2*x + 1) >>> pfd = apart_list(f) >>> pfd (1, Poly(2*x + 4, x, domain='ZZ'), [(Poly(_w - 1, _w, domain='ZZ'), Lambda(_a, 4), Lambda(_a, -_a + x), 1)]) >>> assemble_partfrac_list(pfd) 2*x + 4 + 4/(x - 1) Second example: >>> f = (-2*x - 2*x**2) / (3*x**2 - 6*x) >>> pfd = apart_list(f) >>> pfd (-1, Poly(2/3, x, domain='QQ'), [(Poly(_w - 2, _w, domain='ZZ'), Lambda(_a, 2), Lambda(_a, -_a + x), 1)]) >>> assemble_partfrac_list(pfd) -2/3 - 2/(x - 2) Another example, showing symbolic parameters: >>> pfd = apart_list(t/(x**2 + x + t), x) >>> pfd (1, Poly(0, x, domain='ZZ[t]'), [(Poly(_w**2 + _w + t, _w, domain='ZZ[t]'), Lambda(_a, -2*_a*t/(4*t - 1) - t/(4*t - 1)), Lambda(_a, -_a + x), 1)]) >>> assemble_partfrac_list(pfd) RootSum(_w**2 + _w + t, Lambda(_a, (-2*_a*t/(4*t - 1) - t/(4*t - 1))/(-_a + x))) This example is taken from Bronstein's original paper: >>> f = 36 / (x**5 - 2*x**4 - 2*x**3 + 4*x**2 + x - 2) >>> pfd = apart_list(f) >>> pfd (1, Poly(0, x, domain='ZZ'), [(Poly(_w - 2, _w, domain='ZZ'), Lambda(_a, 4), Lambda(_a, -_a + x), 1), (Poly(_w**2 - 1, _w, domain='ZZ'), Lambda(_a, -3*_a - 6), Lambda(_a, -_a + x), 2), (Poly(_w + 1, _w, domain='ZZ'), Lambda(_a, -4), Lambda(_a, -_a + x), 1)]) >>> assemble_partfrac_list(pfd) -4/(x + 1) - 3/(x + 1)**2 - 9/(x - 1)**2 + 4/(x - 2) See also ======== apart, assemble_partfrac_list References ========== .. [1] [Bronstein93]_ """ allowed_flags(options, []) f = sympify(f) if f.is_Atom: return f else: P, Q = f.as_numer_denom() options = set_defaults(options, extension=True) (P, Q), opt = parallel_poly_from_expr((P, Q), x, **options) 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) polypart = poly if dummies is None: def dummies(name): d = Dummy(name) while True: yield d dummies = dummies("w") rationalpart = apart_list_full_decomposition(P, Q, dummies) return (common, polypart, rationalpart)
def symmetrize(F, *gens, **args): """ Rewrite a polynomial in terms of elementary symmetric polynomials. A symmetric polynomial is a multivariate polynomial that remains invariant under any variable permutation, i.e., if ``f = f(x_1, x_2, ..., x_n)``, then ``f = f(x_{i_1}, x_{i_2}, ..., x_{i_n})``, where ``(i_1, i_2, ..., i_n)`` is a permutation of ``(1, 2, ..., n)`` (an element of the group ``S_n``). Returns a tuple of symmetric polynomials ``(f1, f2, ..., fn)`` such that ``f = f1 + f2 + ... + fn``. Examples ======== >>> from sympy.polys.polyfuncs import symmetrize >>> from sympy.abc import x, y >>> symmetrize(x**2 + y**2) (-2*x*y + (x + y)**2, 0) >>> symmetrize(x**2 + y**2, formal=True) (s1**2 - 2*s2, 0, [(s1, x + y), (s2, x*y)]) >>> symmetrize(x**2 - y**2) (-2*x*y + (x + y)**2, -2*y**2) >>> symmetrize(x**2 - y**2, formal=True) (s1**2 - 2*s2, -2*y**2, [(s1, x + y), (s2, x*y)]) """ allowed_flags(args, ['formal', 'symbols']) iterable = True if not hasattr(F, '__iter__'): iterable = False F = [F] try: F, opt = parallel_poly_from_expr(F, *gens, **args) except PolificationFailed, exc: result = [] for expr in exc.exprs: if expr.is_Number: result.append((expr, S.Zero)) else: raise ComputationFailed('symmetrize', len(F), exc) else: if not iterable: result, = result if not exc.opt.formal: return result else: if iterable: return result, [] else: return result + ([], )