"""Functions for generating interesting polynomials, e.g. for benchmarking. """ from sympy.core import Add, Mul, Symbol, sympify, Dummy, symbols from sympy.core.containers import Tuple from sympy.core.singleton import S from sympy.ntheory import nextprime from sympy.polys.densearith import ( dmp_add_term, dmp_neg, dmp_mul, dmp_sqr ) from sympy.polys.densebasic import ( dmp_zero, dmp_one, dmp_ground, dup_from_raw_dict, dmp_raise, dup_random ) from sympy.polys.domains import ZZ from sympy.polys.factortools import dup_zz_cyclotomic_poly from sympy.polys.polyclasses import DMP from sympy.polys.polytools import Poly, PurePoly from sympy.polys.polyutils import _analyze_gens from sympy.utilities import subsets, public, filldedent @public def swinnerton_dyer_poly(n, x=None, polys=False): """Generates n-th Swinnerton-Dyer polynomial in `x`. Parameters ---------- n : int `n` decides the order of polynomial x : optional polys : bool, optional ``polys=True`` returns an expression, otherwise (default) returns an expression. """ if n <= 0: raise ValueError( "Cannot generate Swinnerton-Dyer polynomial of order %s" % n) if x is not None: sympify(x) else: x = Dummy('x') if n > 3: from sympy.functions.elementary.miscellaneous import sqrt from .numberfields import minimal_polynomial p = 2 a = [sqrt(2)] for i in range(2, n + 1): p = nextprime(p) a.append(sqrt(p)) return minimal_polynomial(Add(*a), x, polys=polys) if n == 1: ex = x**2 - 2 elif n == 2: ex = x**4 - 10*x**2 + 1 elif n == 3: ex = x**8 - 40*x**6 + 352*x**4 - 960*x**2 + 576 return PurePoly(ex, x) if polys else ex @public def cyclotomic_poly(n, x=None, polys=False): """Generates cyclotomic polynomial of order `n` in `x`. Parameters ---------- n : int `n` decides the order of polynomial x : optional polys : bool, optional ``polys=True`` returns an expression, otherwise (default) returns an expression. """ if n <= 0: raise ValueError( "Cannot generate cyclotomic polynomial of order %s" % n) poly = DMP(dup_zz_cyclotomic_poly(int(n), ZZ), ZZ) if x is not None: poly = Poly.new(poly, x) else: poly = PurePoly.new(poly, Dummy('x')) return poly if polys else poly.as_expr() @public def symmetric_poly(n, *gens, polys=False): """ Generates symmetric polynomial of order `n`. Parameters ========== polys: bool, optional (default: False) Returns a Poly object when ``polys=True``, otherwise (default) returns an expression. """ gens = _analyze_gens(gens) if n < 0 or n > len(gens) or not gens: raise ValueError("Cannot generate symmetric polynomial of order %s for %s" % (n, gens)) elif not n: poly = S.One else: poly = Add(*[Mul(*s) for s in subsets(gens, int(n))]) return Poly(poly, *gens) if polys else poly @public def random_poly(x, n, inf, sup, domain=ZZ, polys=False): """Generates a polynomial of degree ``n`` with coefficients in ``[inf, sup]``. Parameters ---------- x `x` is the independent term of polynomial n : int `n` decides the order of polynomial inf Lower limit of range in which coefficients lie sup Upper limit of range in which coefficients lie domain : optional Decides what ring the coefficients are supposed to belong. Default is set to Integers. polys : bool, optional ``polys=True`` returns an expression, otherwise (default) returns an expression. """ poly = Poly(dup_random(n, inf, sup, domain), x, domain=domain) return poly if polys else poly.as_expr() @public def interpolating_poly(n, x, X='x', Y='y'): """Construct Lagrange interpolating polynomial for ``n`` data points. If a sequence of values are given for ``X`` and ``Y`` then the first ``n`` values will be used. """ ok = getattr(x, 'free_symbols', None) if isinstance(X, str): X = symbols("%s:%s" % (X, n)) elif ok and ok & Tuple(*X).free_symbols: ok = False if isinstance(Y, str): Y = symbols("%s:%s" % (Y, n)) elif ok and ok & Tuple(*Y).free_symbols: ok = False if not ok: raise ValueError(filldedent(''' Expecting symbol for x that does not appear in X or Y. Use `interpolate(list(zip(X, Y)), x)` instead.''')) coeffs = [] numert = Mul(*[x - X[i] for i in range(n)]) for i in range(n): numer = numert/(x - X[i]) denom = Mul(*[(X[i] - X[j]) for j in range(n) if i != j]) coeffs.append(numer/denom) return Add(*[coeff*y for coeff, y in zip(coeffs, Y)]) def fateman_poly_F_1(n): """Fateman's GCD benchmark: trivial GCD """ Y = [Symbol('y_' + str(i)) for i in range(n + 1)] y_0, y_1 = Y[0], Y[1] u = y_0 + Add(*Y[1:]) v = y_0**2 + Add(*[y**2 for y in Y[1:]]) F = ((u + 1)*(u + 2)).as_poly(*Y) G = ((v + 1)*(-3*y_1*y_0**2 + y_1**2 - 1)).as_poly(*Y) H = Poly(1, *Y) return F, G, H def dmp_fateman_poly_F_1(n, K): """Fateman's GCD benchmark: trivial GCD """ u = [K(1), K(0)] for i in range(n): u = [dmp_one(i, K), u] v = [K(1), K(0), K(0)] for i in range(0, n): v = [dmp_one(i, K), dmp_zero(i), v] m = n - 1 U = dmp_add_term(u, dmp_ground(K(1), m), 0, n, K) V = dmp_add_term(u, dmp_ground(K(2), m), 0, n, K) f = [[-K(3), K(0)], [], [K(1), K(0), -K(1)]] W = dmp_add_term(v, dmp_ground(K(1), m), 0, n, K) Y = dmp_raise(f, m, 1, K) F = dmp_mul(U, V, n, K) G = dmp_mul(W, Y, n, K) H = dmp_one(n, K) return F, G, H def fateman_poly_F_2(n): """Fateman's GCD benchmark: linearly dense quartic inputs """ Y = [Symbol('y_' + str(i)) for i in range(n + 1)] y_0 = Y[0] u = Add(*Y[1:]) H = Poly((y_0 + u + 1)**2, *Y) F = Poly((y_0 - u - 2)**2, *Y) G = Poly((y_0 + u + 2)**2, *Y) return H*F, H*G, H def dmp_fateman_poly_F_2(n, K): """Fateman's GCD benchmark: linearly dense quartic inputs """ u = [K(1), K(0)] for i in range(n - 1): u = [dmp_one(i, K), u] m = n - 1 v = dmp_add_term(u, dmp_ground(K(2), m - 1), 0, n, K) f = dmp_sqr([dmp_one(m, K), dmp_neg(v, m, K)], n, K) g = dmp_sqr([dmp_one(m, K), v], n, K) v = dmp_add_term(u, dmp_one(m - 1, K), 0, n, K) h = dmp_sqr([dmp_one(m, K), v], n, K) return dmp_mul(f, h, n, K), dmp_mul(g, h, n, K), h def fateman_poly_F_3(n): """Fateman's GCD benchmark: sparse inputs (deg f ~ vars f) """ Y = [Symbol('y_' + str(i)) for i in range(n + 1)] y_0 = Y[0] u = Add(*[y**(n + 1) for y in Y[1:]]) H = Poly((y_0**(n + 1) + u + 1)**2, *Y) F = Poly((y_0**(n + 1) - u - 2)**2, *Y) G = Poly((y_0**(n + 1) + u + 2)**2, *Y) return H*F, H*G, H def dmp_fateman_poly_F_3(n, K): """Fateman's GCD benchmark: sparse inputs (deg f ~ vars f) """ u = dup_from_raw_dict({n + 1: K.one}, K) for i in range(0, n - 1): u = dmp_add_term([u], dmp_one(i, K), n + 1, i + 1, K) v = dmp_add_term(u, dmp_ground(K(2), n - 2), 0, n, K) f = dmp_sqr( dmp_add_term([dmp_neg(v, n - 1, K)], dmp_one(n - 1, K), n + 1, n, K), n, K) g = dmp_sqr(dmp_add_term([v], dmp_one(n - 1, K), n + 1, n, K), n, K) v = dmp_add_term(u, dmp_one(n - 2, K), 0, n - 1, K) h = dmp_sqr(dmp_add_term([v], dmp_one(n - 1, K), n + 1, n, K), n, K) return dmp_mul(f, h, n, K), dmp_mul(g, h, n, K), h # A few useful polynomials from Wang's paper ('78). from sympy.polys.rings import ring def _f_0(): R, x, y, z = ring("x,y,z", ZZ) return x**2*y*z**2 + 2*x**2*y*z + 3*x**2*y + 2*x**2 + 3*x + 4*y**2*z**2 + 5*y**2*z + 6*y**2 + y*z**2 + 2*y*z + y + 1 def _f_1(): R, x, y, z = ring("x,y,z", ZZ) return x**3*y*z + x**2*y**2*z**2 + x**2*y**2 + 20*x**2*y*z + 30*x**2*y + x**2*z**2 + 10*x**2*z + x*y**3*z + 30*x*y**2*z + 20*x*y**2 + x*y*z**3 + 10*x*y*z**2 + x*y*z + 610*x*y + 20*x*z**2 + 230*x*z + 300*x + y**2*z**2 + 10*y**2*z + 30*y*z**2 + 320*y*z + 200*y + 600*z + 6000 def _f_2(): R, x, y, z = ring("x,y,z", ZZ) return x**5*y**3 + x**5*y**2*z + x**5*y*z**2 + x**5*z**3 + x**3*y**2 + x**3*y*z + 90*x**3*y + 90*x**3*z + x**2*y**2*z - 11*x**2*y**2 + x**2*z**3 - 11*x**2*z**2 + y*z - 11*y + 90*z - 990 def _f_3(): R, x, y, z = ring("x,y,z", ZZ) return x**5*y**2 + x**4*z**4 + x**4 + x**3*y**3*z + x**3*z + x**2*y**4 + x**2*y**3*z**3 + x**2*y*z**5 + x**2*y*z + x*y**2*z**4 + x*y**2 + x*y*z**7 + x*y*z**3 + x*y*z**2 + y**2*z + y*z**4 def _f_4(): R, x, y, z = ring("x,y,z", ZZ) return -x**9*y**8*z - x**8*y**5*z**3 - x**7*y**12*z**2 - 5*x**7*y**8 - x**6*y**9*z**4 + x**6*y**7*z**3 + 3*x**6*y**7*z - 5*x**6*y**5*z**2 - x**6*y**4*z**3 + x**5*y**4*z**5 + 3*x**5*y**4*z**3 - x**5*y*z**5 + x**4*y**11*z**4 + 3*x**4*y**11*z**2 - x**4*y**8*z**4 + 5*x**4*y**7*z**2 + 15*x**4*y**7 - 5*x**4*y**4*z**2 + x**3*y**8*z**6 + 3*x**3*y**8*z**4 - x**3*y**5*z**6 + 5*x**3*y**4*z**4 + 15*x**3*y**4*z**2 + x**3*y**3*z**5 + 3*x**3*y**3*z**3 - 5*x**3*y*z**4 + x**2*z**7 + 3*x**2*z**5 + x*y**7*z**6 + 3*x*y**7*z**4 + 5*x*y**3*z**4 + 15*x*y**3*z**2 + y**4*z**8 + 3*y**4*z**6 + 5*z**6 + 15*z**4 def _f_5(): R, x, y, z = ring("x,y,z", ZZ) return -x**3 - 3*x**2*y + 3*x**2*z - 3*x*y**2 + 6*x*y*z - 3*x*z**2 - y**3 + 3*y**2*z - 3*y*z**2 + z**3 def _f_6(): R, x, y, z, t = ring("x,y,z,t", ZZ) return 2115*x**4*y + 45*x**3*z**3*t**2 - 45*x**3*t**2 - 423*x*y**4 - 47*x*y**3 + 141*x*y*z**3 + 94*x*y*z*t - 9*y**3*z**3*t**2 + 9*y**3*t**2 - y**2*z**3*t**2 + y**2*t**2 + 3*z**6*t**2 + 2*z**4*t**3 - 3*z**3*t**2 - 2*z*t**3 def _w_1(): R, x, y, z = ring("x,y,z", ZZ) return 4*x**6*y**4*z**2 + 4*x**6*y**3*z**3 - 4*x**6*y**2*z**4 - 4*x**6*y*z**5 + x**5*y**4*z**3 + 12*x**5*y**3*z - x**5*y**2*z**5 + 12*x**5*y**2*z**2 - 12*x**5*y*z**3 - 12*x**5*z**4 + 8*x**4*y**4 + 6*x**4*y**3*z**2 + 8*x**4*y**3*z - 4*x**4*y**2*z**4 + 4*x**4*y**2*z**3 - 8*x**4*y**2*z**2 - 4*x**4*y*z**5 - 2*x**4*y*z**4 - 8*x**4*y*z**3 + 2*x**3*y**4*z + x**3*y**3*z**3 - x**3*y**2*z**5 - 2*x**3*y**2*z**3 + 9*x**3*y**2*z - 12*x**3*y*z**3 + 12*x**3*y*z**2 - 12*x**3*z**4 + 3*x**3*z**3 + 6*x**2*y**3 - 6*x**2*y**2*z**2 + 8*x**2*y**2*z - 2*x**2*y*z**4 - 8*x**2*y*z**3 + 2*x**2*y*z**2 + 2*x*y**3*z - 2*x*y**2*z**3 - 3*x*y*z + 3*x*z**3 - 2*y**2 + 2*y*z**2 def _w_2(): R, x, y = ring("x,y", ZZ) return 24*x**8*y**3 + 48*x**8*y**2 + 24*x**7*y**5 - 72*x**7*y**2 + 25*x**6*y**4 + 2*x**6*y**3 + 4*x**6*y + 8*x**6 + x**5*y**6 + x**5*y**3 - 12*x**5 + x**4*y**5 - x**4*y**4 - 2*x**4*y**3 + 292*x**4*y**2 - x**3*y**6 + 3*x**3*y**3 - x**2*y**5 + 12*x**2*y**3 + 48*x**2 - 12*y**3 def f_polys(): return _f_0(), _f_1(), _f_2(), _f_3(), _f_4(), _f_5(), _f_6() def w_polys(): return _w_1(), _w_2()