"""Polynomial factorization routines in characteristic zero. """ from sympy.polys.galoistools import ( gf_from_int_poly, gf_to_int_poly, gf_lshift, gf_add_mul, gf_mul, gf_div, gf_rem, gf_gcdex, gf_sqf_p, gf_factor_sqf, gf_factor) from sympy.polys.densebasic import ( dup_LC, dmp_LC, dmp_ground_LC, dup_TC, dup_convert, dmp_convert, dup_degree, dmp_degree, dmp_degree_in, dmp_degree_list, dmp_from_dict, dmp_zero_p, dmp_one, dmp_nest, dmp_raise, dup_strip, dmp_ground, dup_inflate, dmp_exclude, dmp_include, dmp_inject, dmp_eject, dup_terms_gcd, dmp_terms_gcd) from sympy.polys.densearith import ( dup_neg, dmp_neg, dup_add, dmp_add, dup_sub, dmp_sub, dup_mul, dmp_mul, dup_sqr, dmp_pow, dup_div, dmp_div, dup_quo, dmp_quo, dmp_expand, dmp_add_mul, dup_sub_mul, dmp_sub_mul, dup_lshift, dup_max_norm, dmp_max_norm, dup_l1_norm, dup_mul_ground, dmp_mul_ground, dup_quo_ground, dmp_quo_ground) from sympy.polys.densetools import ( dup_clear_denoms, dmp_clear_denoms, dup_trunc, dmp_ground_trunc, dup_content, dup_monic, dmp_ground_monic, dup_primitive, dmp_ground_primitive, dmp_eval_tail, dmp_eval_in, dmp_diff_eval_in, dmp_compose, dup_shift, dup_mirror) from sympy.polys.euclidtools import ( dmp_primitive, dup_inner_gcd, dmp_inner_gcd) from sympy.polys.sqfreetools import ( dup_sqf_p, dup_sqf_norm, dmp_sqf_norm, dup_sqf_part, dmp_sqf_part) from sympy.polys.polyutils import _sort_factors from sympy.polys.polyconfig import query from sympy.polys.polyerrors import ( ExtraneousFactors, DomainError, CoercionFailed, EvaluationFailed) from sympy.ntheory import nextprime, isprime, factorint from sympy.utilities import subsets from math import ceil as _ceil, log as _log def dup_trial_division(f, factors, K): """ Determine multiplicities of factors for a univariate polynomial using trial division. """ result = [] for factor in factors: k = 0 while True: q, r = dup_div(f, factor, K) if not r: f, k = q, k + 1 else: break result.append((factor, k)) return _sort_factors(result) def dmp_trial_division(f, factors, u, K): """ Determine multiplicities of factors for a multivariate polynomial using trial division. """ result = [] for factor in factors: k = 0 while True: q, r = dmp_div(f, factor, u, K) if dmp_zero_p(r, u): f, k = q, k + 1 else: break result.append((factor, k)) return _sort_factors(result) def dup_zz_mignotte_bound(f, K): """ The Knuth-Cohen variant of Mignotte bound for univariate polynomials in `K[x]`. Examples ======== >>> from sympy.polys import ring, ZZ >>> R, x = ring("x", ZZ) >>> f = x**3 + 14*x**2 + 56*x + 64 >>> R.dup_zz_mignotte_bound(f) 152 By checking `factor(f)` we can see that max coeff is 8 Also consider a case that `f` is irreducible for example `f = 2*x**2 + 3*x + 4` To avoid a bug for these cases, we return the bound plus the max coefficient of `f` >>> f = 2*x**2 + 3*x + 4 >>> R.dup_zz_mignotte_bound(f) 6 Lastly,To see the difference between the new and the old Mignotte bound consider the irreducible polynomial:: >>> f = 87*x**7 + 4*x**6 + 80*x**5 + 17*x**4 + 9*x**3 + 12*x**2 + 49*x + 26 >>> R.dup_zz_mignotte_bound(f) 744 The new Mignotte bound is 744 whereas the old one (SymPy 1.5.1) is 1937664. References ========== ..[1] [Abbott2013]_ """ from sympy.functions.combinatorial.factorials import binomial d = dup_degree(f) delta = _ceil(d / 2) delta2 = _ceil(delta / 2) # euclidean-norm eucl_norm = K.sqrt( sum( [cf**2 for cf in f] ) ) # biggest values of binomial coefficients (p. 538 of reference) t1 = binomial(delta - 1, delta2) t2 = binomial(delta - 1, delta2 - 1) lc = K.abs(dup_LC(f, K)) # leading coefficient bound = t1 * eucl_norm + t2 * lc # (p. 538 of reference) bound += dup_max_norm(f, K) # add max coeff for irreducible polys bound = _ceil(bound / 2) * 2 # round up to even integer return bound def dmp_zz_mignotte_bound(f, u, K): """Mignotte bound for multivariate polynomials in `K[X]`. """ a = dmp_max_norm(f, u, K) b = abs(dmp_ground_LC(f, u, K)) n = sum(dmp_degree_list(f, u)) return K.sqrt(K(n + 1))*2**n*a*b def dup_zz_hensel_step(m, f, g, h, s, t, K): """ One step in Hensel lifting in `Z[x]`. Given positive integer `m` and `Z[x]` polynomials `f`, `g`, `h`, `s` and `t` such that:: f = g*h (mod m) s*g + t*h = 1 (mod m) lc(f) is not a zero divisor (mod m) lc(h) = 1 deg(f) = deg(g) + deg(h) deg(s) < deg(h) deg(t) < deg(g) returns polynomials `G`, `H`, `S` and `T`, such that:: f = G*H (mod m**2) S*G + T*H = 1 (mod m**2) References ========== .. [1] [Gathen99]_ """ M = m**2 e = dup_sub_mul(f, g, h, K) e = dup_trunc(e, M, K) q, r = dup_div(dup_mul(s, e, K), h, K) q = dup_trunc(q, M, K) r = dup_trunc(r, M, K) u = dup_add(dup_mul(t, e, K), dup_mul(q, g, K), K) G = dup_trunc(dup_add(g, u, K), M, K) H = dup_trunc(dup_add(h, r, K), M, K) u = dup_add(dup_mul(s, G, K), dup_mul(t, H, K), K) b = dup_trunc(dup_sub(u, [K.one], K), M, K) c, d = dup_div(dup_mul(s, b, K), H, K) c = dup_trunc(c, M, K) d = dup_trunc(d, M, K) u = dup_add(dup_mul(t, b, K), dup_mul(c, G, K), K) S = dup_trunc(dup_sub(s, d, K), M, K) T = dup_trunc(dup_sub(t, u, K), M, K) return G, H, S, T def dup_zz_hensel_lift(p, f, f_list, l, K): r""" Multifactor Hensel lifting in `Z[x]`. Given a prime `p`, polynomial `f` over `Z[x]` such that `lc(f)` is a unit modulo `p`, monic pair-wise coprime polynomials `f_i` over `Z[x]` satisfying:: f = lc(f) f_1 ... f_r (mod p) and a positive integer `l`, returns a list of monic polynomials `F_1,\ F_2,\ \dots,\ F_r` satisfying:: f = lc(f) F_1 ... F_r (mod p**l) F_i = f_i (mod p), i = 1..r References ========== .. [1] [Gathen99]_ """ r = len(f_list) lc = dup_LC(f, K) if r == 1: F = dup_mul_ground(f, K.gcdex(lc, p**l)[0], K) return [ dup_trunc(F, p**l, K) ] m = p k = r // 2 d = int(_ceil(_log(l, 2))) g = gf_from_int_poly([lc], p) for f_i in f_list[:k]: g = gf_mul(g, gf_from_int_poly(f_i, p), p, K) h = gf_from_int_poly(f_list[k], p) for f_i in f_list[k + 1:]: h = gf_mul(h, gf_from_int_poly(f_i, p), p, K) s, t, _ = gf_gcdex(g, h, p, K) g = gf_to_int_poly(g, p) h = gf_to_int_poly(h, p) s = gf_to_int_poly(s, p) t = gf_to_int_poly(t, p) for _ in range(1, d + 1): (g, h, s, t), m = dup_zz_hensel_step(m, f, g, h, s, t, K), m**2 return dup_zz_hensel_lift(p, g, f_list[:k], l, K) \ + dup_zz_hensel_lift(p, h, f_list[k:], l, K) def _test_pl(fc, q, pl): if q > pl // 2: q = q - pl if not q: return True return fc % q == 0 def dup_zz_zassenhaus(f, K): """Factor primitive square-free polynomials in `Z[x]`. """ n = dup_degree(f) if n == 1: return [f] fc = f[-1] A = dup_max_norm(f, K) b = dup_LC(f, K) B = int(abs(K.sqrt(K(n + 1))*2**n*A*b)) C = int((n + 1)**(2*n)*A**(2*n - 1)) gamma = int(_ceil(2*_log(C, 2))) bound = int(2*gamma*_log(gamma)) a = [] # choose a prime number `p` such that `f` be square free in Z_p # if there are many factors in Z_p, choose among a few different `p` # the one with fewer factors for px in range(3, bound + 1): if not isprime(px) or b % px == 0: continue px = K.convert(px) F = gf_from_int_poly(f, px) if not gf_sqf_p(F, px, K): continue fsqfx = gf_factor_sqf(F, px, K)[1] a.append((px, fsqfx)) if len(fsqfx) < 15 or len(a) > 4: break p, fsqf = min(a, key=lambda x: len(x[1])) l = int(_ceil(_log(2*B + 1, p))) modular = [gf_to_int_poly(ff, p) for ff in fsqf] g = dup_zz_hensel_lift(p, f, modular, l, K) sorted_T = range(len(g)) T = set(sorted_T) factors, s = [], 1 pl = p**l while 2*s <= len(T): for S in subsets(sorted_T, s): # lift the constant coefficient of the product `G` of the factors # in the subset `S`; if it is does not divide `fc`, `G` does # not divide the input polynomial if b == 1: q = 1 for i in S: q = q*g[i][-1] q = q % pl if not _test_pl(fc, q, pl): continue else: G = [b] for i in S: G = dup_mul(G, g[i], K) G = dup_trunc(G, pl, K) G = dup_primitive(G, K)[1] q = G[-1] if q and fc % q != 0: continue H = [b] S = set(S) T_S = T - S if b == 1: G = [b] for i in S: G = dup_mul(G, g[i], K) G = dup_trunc(G, pl, K) for i in T_S: H = dup_mul(H, g[i], K) H = dup_trunc(H, pl, K) G_norm = dup_l1_norm(G, K) H_norm = dup_l1_norm(H, K) if G_norm*H_norm <= B: T = T_S sorted_T = [i for i in sorted_T if i not in S] G = dup_primitive(G, K)[1] f = dup_primitive(H, K)[1] factors.append(G) b = dup_LC(f, K) break else: s += 1 return factors + [f] def dup_zz_irreducible_p(f, K): """Test irreducibility using Eisenstein's criterion. """ lc = dup_LC(f, K) tc = dup_TC(f, K) e_fc = dup_content(f[1:], K) if e_fc: e_ff = factorint(int(e_fc)) for p in e_ff.keys(): if (lc % p) and (tc % p**2): return True def dup_cyclotomic_p(f, K, irreducible=False): """ Efficiently test if ``f`` is a cyclotomic polynomial. Examples ======== >>> from sympy.polys import ring, ZZ >>> R, x = ring("x", ZZ) >>> f = x**16 + x**14 - x**10 + x**8 - x**6 + x**2 + 1 >>> R.dup_cyclotomic_p(f) False >>> g = x**16 + x**14 - x**10 - x**8 - x**6 + x**2 + 1 >>> R.dup_cyclotomic_p(g) True """ if K.is_QQ: try: K0, K = K, K.get_ring() f = dup_convert(f, K0, K) except CoercionFailed: return False elif not K.is_ZZ: return False lc = dup_LC(f, K) tc = dup_TC(f, K) if lc != 1 or (tc != -1 and tc != 1): return False if not irreducible: coeff, factors = dup_factor_list(f, K) if coeff != K.one or factors != [(f, 1)]: return False n = dup_degree(f) g, h = [], [] for i in range(n, -1, -2): g.insert(0, f[i]) for i in range(n - 1, -1, -2): h.insert(0, f[i]) g = dup_sqr(dup_strip(g), K) h = dup_sqr(dup_strip(h), K) F = dup_sub(g, dup_lshift(h, 1, K), K) if K.is_negative(dup_LC(F, K)): F = dup_neg(F, K) if F == f: return True g = dup_mirror(f, K) if K.is_negative(dup_LC(g, K)): g = dup_neg(g, K) if F == g and dup_cyclotomic_p(g, K): return True G = dup_sqf_part(F, K) if dup_sqr(G, K) == F and dup_cyclotomic_p(G, K): return True return False def dup_zz_cyclotomic_poly(n, K): """Efficiently generate n-th cyclotomic polynomial. """ h = [K.one, -K.one] for p, k in factorint(n).items(): h = dup_quo(dup_inflate(h, p, K), h, K) h = dup_inflate(h, p**(k - 1), K) return h def _dup_cyclotomic_decompose(n, K): H = [[K.one, -K.one]] for p, k in factorint(n).items(): Q = [ dup_quo(dup_inflate(h, p, K), h, K) for h in H ] H.extend(Q) for i in range(1, k): Q = [ dup_inflate(q, p, K) for q in Q ] H.extend(Q) return H def dup_zz_cyclotomic_factor(f, K): """ Efficiently factor polynomials `x**n - 1` and `x**n + 1` in `Z[x]`. Given a univariate polynomial `f` in `Z[x]` returns a list of factors of `f`, provided that `f` is in the form `x**n - 1` or `x**n + 1` for `n >= 1`. Otherwise returns None. Factorization is performed using cyclotomic decomposition of `f`, which makes this method much faster that any other direct factorization approach (e.g. Zassenhaus's). References ========== .. [1] [Weisstein09]_ """ lc_f, tc_f = dup_LC(f, K), dup_TC(f, K) if dup_degree(f) <= 0: return None if lc_f != 1 or tc_f not in [-1, 1]: return None if any(bool(cf) for cf in f[1:-1]): return None n = dup_degree(f) F = _dup_cyclotomic_decompose(n, K) if not K.is_one(tc_f): return F else: H = [] for h in _dup_cyclotomic_decompose(2*n, K): if h not in F: H.append(h) return H def dup_zz_factor_sqf(f, K): """Factor square-free (non-primitive) polynomials in `Z[x]`. """ cont, g = dup_primitive(f, K) n = dup_degree(g) if dup_LC(g, K) < 0: cont, g = -cont, dup_neg(g, K) if n <= 0: return cont, [] elif n == 1: return cont, [g] if query('USE_IRREDUCIBLE_IN_FACTOR'): if dup_zz_irreducible_p(g, K): return cont, [g] factors = None if query('USE_CYCLOTOMIC_FACTOR'): factors = dup_zz_cyclotomic_factor(g, K) if factors is None: factors = dup_zz_zassenhaus(g, K) return cont, _sort_factors(factors, multiple=False) def dup_zz_factor(f, K): """ Factor (non square-free) polynomials in `Z[x]`. Given a univariate polynomial `f` in `Z[x]` computes its complete factorization `f_1, ..., f_n` into irreducibles over integers:: f = content(f) f_1**k_1 ... f_n**k_n The factorization is computed by reducing the input polynomial into a primitive square-free polynomial and factoring it using Zassenhaus algorithm. Trial division is used to recover the multiplicities of factors. The result is returned as a tuple consisting of:: (content(f), [(f_1, k_1), ..., (f_n, k_n)) Examples ======== Consider the polynomial `f = 2*x**4 - 2`:: >>> from sympy.polys import ring, ZZ >>> R, x = ring("x", ZZ) >>> R.dup_zz_factor(2*x**4 - 2) (2, [(x - 1, 1), (x + 1, 1), (x**2 + 1, 1)]) In result we got the following factorization:: f = 2 (x - 1) (x + 1) (x**2 + 1) Note that this is a complete factorization over integers, however over Gaussian integers we can factor the last term. By default, polynomials `x**n - 1` and `x**n + 1` are factored using cyclotomic decomposition to speedup computations. To disable this behaviour set cyclotomic=False. References ========== .. [1] [Gathen99]_ """ cont, g = dup_primitive(f, K) n = dup_degree(g) if dup_LC(g, K) < 0: cont, g = -cont, dup_neg(g, K) if n <= 0: return cont, [] elif n == 1: return cont, [(g, 1)] if query('USE_IRREDUCIBLE_IN_FACTOR'): if dup_zz_irreducible_p(g, K): return cont, [(g, 1)] g = dup_sqf_part(g, K) H = None if query('USE_CYCLOTOMIC_FACTOR'): H = dup_zz_cyclotomic_factor(g, K) if H is None: H = dup_zz_zassenhaus(g, K) factors = dup_trial_division(f, H, K) return cont, factors def dmp_zz_wang_non_divisors(E, cs, ct, K): """Wang/EEZ: Compute a set of valid divisors. """ result = [ cs*ct ] for q in E: q = abs(q) for r in reversed(result): while r != 1: r = K.gcd(r, q) q = q // r if K.is_one(q): return None result.append(q) return result[1:] def dmp_zz_wang_test_points(f, T, ct, A, u, K): """Wang/EEZ: Test evaluation points for suitability. """ if not dmp_eval_tail(dmp_LC(f, K), A, u - 1, K): raise EvaluationFailed('no luck') g = dmp_eval_tail(f, A, u, K) if not dup_sqf_p(g, K): raise EvaluationFailed('no luck') c, h = dup_primitive(g, K) if K.is_negative(dup_LC(h, K)): c, h = -c, dup_neg(h, K) v = u - 1 E = [ dmp_eval_tail(t, A, v, K) for t, _ in T ] D = dmp_zz_wang_non_divisors(E, c, ct, K) if D is not None: return c, h, E else: raise EvaluationFailed('no luck') def dmp_zz_wang_lead_coeffs(f, T, cs, E, H, A, u, K): """Wang/EEZ: Compute correct leading coefficients. """ C, J, v = [], [0]*len(E), u - 1 for h in H: c = dmp_one(v, K) d = dup_LC(h, K)*cs for i in reversed(range(len(E))): k, e, (t, _) = 0, E[i], T[i] while not (d % e): d, k = d//e, k + 1 if k != 0: c, J[i] = dmp_mul(c, dmp_pow(t, k, v, K), v, K), 1 C.append(c) if not all(J): raise ExtraneousFactors # pragma: no cover CC, HH = [], [] for c, h in zip(C, H): d = dmp_eval_tail(c, A, v, K) lc = dup_LC(h, K) if K.is_one(cs): cc = lc//d else: g = K.gcd(lc, d) d, cc = d//g, lc//g h, cs = dup_mul_ground(h, d, K), cs//d c = dmp_mul_ground(c, cc, v, K) CC.append(c) HH.append(h) if K.is_one(cs): return f, HH, CC CCC, HHH = [], [] for c, h in zip(CC, HH): CCC.append(dmp_mul_ground(c, cs, v, K)) HHH.append(dmp_mul_ground(h, cs, 0, K)) f = dmp_mul_ground(f, cs**(len(H) - 1), u, K) return f, HHH, CCC def dup_zz_diophantine(F, m, p, K): """Wang/EEZ: Solve univariate Diophantine equations. """ if len(F) == 2: a, b = F f = gf_from_int_poly(a, p) g = gf_from_int_poly(b, p) s, t, G = gf_gcdex(g, f, p, K) s = gf_lshift(s, m, K) t = gf_lshift(t, m, K) q, s = gf_div(s, f, p, K) t = gf_add_mul(t, q, g, p, K) s = gf_to_int_poly(s, p) t = gf_to_int_poly(t, p) result = [s, t] else: G = [F[-1]] for f in reversed(F[1:-1]): G.insert(0, dup_mul(f, G[0], K)) S, T = [], [[1]] for f, g in zip(F, G): t, s = dmp_zz_diophantine([g, f], T[-1], [], 0, p, 1, K) T.append(t) S.append(s) result, S = [], S + [T[-1]] for s, f in zip(S, F): s = gf_from_int_poly(s, p) f = gf_from_int_poly(f, p) r = gf_rem(gf_lshift(s, m, K), f, p, K) s = gf_to_int_poly(r, p) result.append(s) return result def dmp_zz_diophantine(F, c, A, d, p, u, K): """Wang/EEZ: Solve multivariate Diophantine equations. """ if not A: S = [ [] for _ in F ] n = dup_degree(c) for i, coeff in enumerate(c): if not coeff: continue T = dup_zz_diophantine(F, n - i, p, K) for j, (s, t) in enumerate(zip(S, T)): t = dup_mul_ground(t, coeff, K) S[j] = dup_trunc(dup_add(s, t, K), p, K) else: n = len(A) e = dmp_expand(F, u, K) a, A = A[-1], A[:-1] B, G = [], [] for f in F: B.append(dmp_quo(e, f, u, K)) G.append(dmp_eval_in(f, a, n, u, K)) C = dmp_eval_in(c, a, n, u, K) v = u - 1 S = dmp_zz_diophantine(G, C, A, d, p, v, K) S = [ dmp_raise(s, 1, v, K) for s in S ] for s, b in zip(S, B): c = dmp_sub_mul(c, s, b, u, K) c = dmp_ground_trunc(c, p, u, K) m = dmp_nest([K.one, -a], n, K) M = dmp_one(n, K) for k in K.map(range(0, d)): if dmp_zero_p(c, u): break M = dmp_mul(M, m, u, K) C = dmp_diff_eval_in(c, k + 1, a, n, u, K) if not dmp_zero_p(C, v): C = dmp_quo_ground(C, K.factorial(k + 1), v, K) T = dmp_zz_diophantine(G, C, A, d, p, v, K) for i, t in enumerate(T): T[i] = dmp_mul(dmp_raise(t, 1, v, K), M, u, K) for i, (s, t) in enumerate(zip(S, T)): S[i] = dmp_add(s, t, u, K) for t, b in zip(T, B): c = dmp_sub_mul(c, t, b, u, K) c = dmp_ground_trunc(c, p, u, K) S = [ dmp_ground_trunc(s, p, u, K) for s in S ] return S def dmp_zz_wang_hensel_lifting(f, H, LC, A, p, u, K): """Wang/EEZ: Parallel Hensel lifting algorithm. """ S, n, v = [f], len(A), u - 1 H = list(H) for i, a in enumerate(reversed(A[1:])): s = dmp_eval_in(S[0], a, n - i, u - i, K) S.insert(0, dmp_ground_trunc(s, p, v - i, K)) d = max(dmp_degree_list(f, u)[1:]) for j, s, a in zip(range(2, n + 2), S, A): G, w = list(H), j - 1 I, J = A[:j - 2], A[j - 1:] for i, (h, lc) in enumerate(zip(H, LC)): lc = dmp_ground_trunc(dmp_eval_tail(lc, J, v, K), p, w - 1, K) H[i] = [lc] + dmp_raise(h[1:], 1, w - 1, K) m = dmp_nest([K.one, -a], w, K) M = dmp_one(w, K) c = dmp_sub(s, dmp_expand(H, w, K), w, K) dj = dmp_degree_in(s, w, w) for k in K.map(range(0, dj)): if dmp_zero_p(c, w): break M = dmp_mul(M, m, w, K) C = dmp_diff_eval_in(c, k + 1, a, w, w, K) if not dmp_zero_p(C, w - 1): C = dmp_quo_ground(C, K.factorial(k + 1), w - 1, K) T = dmp_zz_diophantine(G, C, I, d, p, w - 1, K) for i, (h, t) in enumerate(zip(H, T)): h = dmp_add_mul(h, dmp_raise(t, 1, w - 1, K), M, w, K) H[i] = dmp_ground_trunc(h, p, w, K) h = dmp_sub(s, dmp_expand(H, w, K), w, K) c = dmp_ground_trunc(h, p, w, K) if dmp_expand(H, u, K) != f: raise ExtraneousFactors # pragma: no cover else: return H def dmp_zz_wang(f, u, K, mod=None, seed=None): r""" Factor primitive square-free polynomials in `Z[X]`. Given a multivariate polynomial `f` in `Z[x_1,...,x_n]`, which is primitive and square-free in `x_1`, computes factorization of `f` into irreducibles over integers. The procedure is based on Wang's Enhanced Extended Zassenhaus algorithm. The algorithm works by viewing `f` as a univariate polynomial in `Z[x_2,...,x_n][x_1]`, for which an evaluation mapping is computed:: x_2 -> a_2, ..., x_n -> a_n where `a_i`, for `i = 2, \dots, n`, are carefully chosen integers. The mapping is used to transform `f` into a univariate polynomial in `Z[x_1]`, which can be factored efficiently using Zassenhaus algorithm. The last step is to lift univariate factors to obtain true multivariate factors. For this purpose a parallel Hensel lifting procedure is used. The parameter ``seed`` is passed to _randint and can be used to seed randint (when an integer) or (for testing purposes) can be a sequence of numbers. References ========== .. [1] [Wang78]_ .. [2] [Geddes92]_ """ from sympy.core.random import _randint randint = _randint(seed) ct, T = dmp_zz_factor(dmp_LC(f, K), u - 1, K) b = dmp_zz_mignotte_bound(f, u, K) p = K(nextprime(b)) if mod is None: if u == 1: mod = 2 else: mod = 1 history, configs, A, r = set(), [], [K.zero]*u, None try: cs, s, E = dmp_zz_wang_test_points(f, T, ct, A, u, K) _, H = dup_zz_factor_sqf(s, K) r = len(H) if r == 1: return [f] configs = [(s, cs, E, H, A)] except EvaluationFailed: pass eez_num_configs = query('EEZ_NUMBER_OF_CONFIGS') eez_num_tries = query('EEZ_NUMBER_OF_TRIES') eez_mod_step = query('EEZ_MODULUS_STEP') while len(configs) < eez_num_configs: for _ in range(eez_num_tries): A = [ K(randint(-mod, mod)) for _ in range(u) ] if tuple(A) not in history: history.add(tuple(A)) else: continue try: cs, s, E = dmp_zz_wang_test_points(f, T, ct, A, u, K) except EvaluationFailed: continue _, H = dup_zz_factor_sqf(s, K) rr = len(H) if r is not None: if rr != r: # pragma: no cover if rr < r: configs, r = [], rr else: continue else: r = rr if r == 1: return [f] configs.append((s, cs, E, H, A)) if len(configs) == eez_num_configs: break else: mod += eez_mod_step s_norm, s_arg, i = None, 0, 0 for s, _, _, _, _ in configs: _s_norm = dup_max_norm(s, K) if s_norm is not None: if _s_norm < s_norm: s_norm = _s_norm s_arg = i else: s_norm = _s_norm i += 1 _, cs, E, H, A = configs[s_arg] orig_f = f try: f, H, LC = dmp_zz_wang_lead_coeffs(f, T, cs, E, H, A, u, K) factors = dmp_zz_wang_hensel_lifting(f, H, LC, A, p, u, K) except ExtraneousFactors: # pragma: no cover if query('EEZ_RESTART_IF_NEEDED'): return dmp_zz_wang(orig_f, u, K, mod + 1) else: raise ExtraneousFactors( "we need to restart algorithm with better parameters") result = [] for f in factors: _, f = dmp_ground_primitive(f, u, K) if K.is_negative(dmp_ground_LC(f, u, K)): f = dmp_neg(f, u, K) result.append(f) return result def dmp_zz_factor(f, u, K): r""" Factor (non square-free) polynomials in `Z[X]`. Given a multivariate polynomial `f` in `Z[x]` computes its complete factorization `f_1, \dots, f_n` into irreducibles over integers:: f = content(f) f_1**k_1 ... f_n**k_n The factorization is computed by reducing the input polynomial into a primitive square-free polynomial and factoring it using Enhanced Extended Zassenhaus (EEZ) algorithm. Trial division is used to recover the multiplicities of factors. The result is returned as a tuple consisting of:: (content(f), [(f_1, k_1), ..., (f_n, k_n)) Consider polynomial `f = 2*(x**2 - y**2)`:: >>> from sympy.polys import ring, ZZ >>> R, x,y = ring("x,y", ZZ) >>> R.dmp_zz_factor(2*x**2 - 2*y**2) (2, [(x - y, 1), (x + y, 1)]) In result we got the following factorization:: f = 2 (x - y) (x + y) References ========== .. [1] [Gathen99]_ """ if not u: return dup_zz_factor(f, K) if dmp_zero_p(f, u): return K.zero, [] cont, g = dmp_ground_primitive(f, u, K) if dmp_ground_LC(g, u, K) < 0: cont, g = -cont, dmp_neg(g, u, K) if all(d <= 0 for d in dmp_degree_list(g, u)): return cont, [] G, g = dmp_primitive(g, u, K) factors = [] if dmp_degree(g, u) > 0: g = dmp_sqf_part(g, u, K) H = dmp_zz_wang(g, u, K) factors = dmp_trial_division(f, H, u, K) for g, k in dmp_zz_factor(G, u - 1, K)[1]: factors.insert(0, ([g], k)) return cont, _sort_factors(factors) def dup_qq_i_factor(f, K0): """Factor univariate polynomials into irreducibles in `QQ_I[x]`. """ # Factor in QQ K1 = K0.as_AlgebraicField() f = dup_convert(f, K0, K1) coeff, factors = dup_factor_list(f, K1) factors = [(dup_convert(fac, K1, K0), i) for fac, i in factors] coeff = K0.convert(coeff, K1) return coeff, factors def dup_zz_i_factor(f, K0): """Factor univariate polynomials into irreducibles in `ZZ_I[x]`. """ # First factor in QQ_I K1 = K0.get_field() f = dup_convert(f, K0, K1) coeff, factors = dup_qq_i_factor(f, K1) new_factors = [] for fac, i in factors: # Extract content fac_denom, fac_num = dup_clear_denoms(fac, K1) fac_num_ZZ_I = dup_convert(fac_num, K1, K0) content, fac_prim = dmp_ground_primitive(fac_num_ZZ_I, 0, K1) coeff = (coeff * content ** i) // fac_denom ** i new_factors.append((fac_prim, i)) factors = new_factors coeff = K0.convert(coeff, K1) return coeff, factors def dmp_qq_i_factor(f, u, K0): """Factor multivariate polynomials into irreducibles in `QQ_I[X]`. """ # Factor in QQ K1 = K0.as_AlgebraicField() f = dmp_convert(f, u, K0, K1) coeff, factors = dmp_factor_list(f, u, K1) factors = [(dmp_convert(fac, u, K1, K0), i) for fac, i in factors] coeff = K0.convert(coeff, K1) return coeff, factors def dmp_zz_i_factor(f, u, K0): """Factor multivariate polynomials into irreducibles in `ZZ_I[X]`. """ # First factor in QQ_I K1 = K0.get_field() f = dmp_convert(f, u, K0, K1) coeff, factors = dmp_qq_i_factor(f, u, K1) new_factors = [] for fac, i in factors: # Extract content fac_denom, fac_num = dmp_clear_denoms(fac, u, K1) fac_num_ZZ_I = dmp_convert(fac_num, u, K1, K0) content, fac_prim = dmp_ground_primitive(fac_num_ZZ_I, u, K1) coeff = (coeff * content ** i) // fac_denom ** i new_factors.append((fac_prim, i)) factors = new_factors coeff = K0.convert(coeff, K1) return coeff, factors def dup_ext_factor(f, K): """Factor univariate polynomials over algebraic number fields. """ n, lc = dup_degree(f), dup_LC(f, K) f = dup_monic(f, K) if n <= 0: return lc, [] if n == 1: return lc, [(f, 1)] f, F = dup_sqf_part(f, K), f s, g, r = dup_sqf_norm(f, K) factors = dup_factor_list_include(r, K.dom) if len(factors) == 1: return lc, [(f, n//dup_degree(f))] H = s*K.unit for i, (factor, _) in enumerate(factors): h = dup_convert(factor, K.dom, K) h, _, g = dup_inner_gcd(h, g, K) h = dup_shift(h, H, K) factors[i] = h factors = dup_trial_division(F, factors, K) return lc, factors def dmp_ext_factor(f, u, K): """Factor multivariate polynomials over algebraic number fields. """ if not u: return dup_ext_factor(f, K) lc = dmp_ground_LC(f, u, K) f = dmp_ground_monic(f, u, K) if all(d <= 0 for d in dmp_degree_list(f, u)): return lc, [] f, F = dmp_sqf_part(f, u, K), f s, g, r = dmp_sqf_norm(f, u, K) factors = dmp_factor_list_include(r, u, K.dom) if len(factors) == 1: factors = [f] else: H = dmp_raise([K.one, s*K.unit], u, 0, K) for i, (factor, _) in enumerate(factors): h = dmp_convert(factor, u, K.dom, K) h, _, g = dmp_inner_gcd(h, g, u, K) h = dmp_compose(h, H, u, K) factors[i] = h return lc, dmp_trial_division(F, factors, u, K) def dup_gf_factor(f, K): """Factor univariate polynomials over finite fields. """ f = dup_convert(f, K, K.dom) coeff, factors = gf_factor(f, K.mod, K.dom) for i, (f, k) in enumerate(factors): factors[i] = (dup_convert(f, K.dom, K), k) return K.convert(coeff, K.dom), factors def dmp_gf_factor(f, u, K): """Factor multivariate polynomials over finite fields. """ raise NotImplementedError('multivariate polynomials over finite fields') def dup_factor_list(f, K0): """Factor univariate polynomials into irreducibles in `K[x]`. """ j, f = dup_terms_gcd(f, K0) cont, f = dup_primitive(f, K0) if K0.is_FiniteField: coeff, factors = dup_gf_factor(f, K0) elif K0.is_Algebraic: coeff, factors = dup_ext_factor(f, K0) elif K0.is_GaussianRing: coeff, factors = dup_zz_i_factor(f, K0) elif K0.is_GaussianField: coeff, factors = dup_qq_i_factor(f, K0) else: if not K0.is_Exact: K0_inexact, K0 = K0, K0.get_exact() f = dup_convert(f, K0_inexact, K0) else: K0_inexact = None if K0.is_Field: K = K0.get_ring() denom, f = dup_clear_denoms(f, K0, K) f = dup_convert(f, K0, K) else: K = K0 if K.is_ZZ: coeff, factors = dup_zz_factor(f, K) elif K.is_Poly: f, u = dmp_inject(f, 0, K) coeff, factors = dmp_factor_list(f, u, K.dom) for i, (f, k) in enumerate(factors): factors[i] = (dmp_eject(f, u, K), k) coeff = K.convert(coeff, K.dom) else: # pragma: no cover raise DomainError('factorization not supported over %s' % K0) if K0.is_Field: for i, (f, k) in enumerate(factors): factors[i] = (dup_convert(f, K, K0), k) coeff = K0.convert(coeff, K) coeff = K0.quo(coeff, denom) if K0_inexact: for i, (f, k) in enumerate(factors): max_norm = dup_max_norm(f, K0) f = dup_quo_ground(f, max_norm, K0) f = dup_convert(f, K0, K0_inexact) factors[i] = (f, k) coeff = K0.mul(coeff, K0.pow(max_norm, k)) coeff = K0_inexact.convert(coeff, K0) K0 = K0_inexact if j: factors.insert(0, ([K0.one, K0.zero], j)) return coeff*cont, _sort_factors(factors) def dup_factor_list_include(f, K): """Factor univariate polynomials into irreducibles in `K[x]`. """ coeff, factors = dup_factor_list(f, K) if not factors: return [(dup_strip([coeff]), 1)] else: g = dup_mul_ground(factors[0][0], coeff, K) return [(g, factors[0][1])] + factors[1:] def dmp_factor_list(f, u, K0): """Factor multivariate polynomials into irreducibles in `K[X]`. """ if not u: return dup_factor_list(f, K0) J, f = dmp_terms_gcd(f, u, K0) cont, f = dmp_ground_primitive(f, u, K0) if K0.is_FiniteField: # pragma: no cover coeff, factors = dmp_gf_factor(f, u, K0) elif K0.is_Algebraic: coeff, factors = dmp_ext_factor(f, u, K0) elif K0.is_GaussianRing: coeff, factors = dmp_zz_i_factor(f, u, K0) elif K0.is_GaussianField: coeff, factors = dmp_qq_i_factor(f, u, K0) else: if not K0.is_Exact: K0_inexact, K0 = K0, K0.get_exact() f = dmp_convert(f, u, K0_inexact, K0) else: K0_inexact = None if K0.is_Field: K = K0.get_ring() denom, f = dmp_clear_denoms(f, u, K0, K) f = dmp_convert(f, u, K0, K) else: K = K0 if K.is_ZZ: levels, f, v = dmp_exclude(f, u, K) coeff, factors = dmp_zz_factor(f, v, K) for i, (f, k) in enumerate(factors): factors[i] = (dmp_include(f, levels, v, K), k) elif K.is_Poly: f, v = dmp_inject(f, u, K) coeff, factors = dmp_factor_list(f, v, K.dom) for i, (f, k) in enumerate(factors): factors[i] = (dmp_eject(f, v, K), k) coeff = K.convert(coeff, K.dom) else: # pragma: no cover raise DomainError('factorization not supported over %s' % K0) if K0.is_Field: for i, (f, k) in enumerate(factors): factors[i] = (dmp_convert(f, u, K, K0), k) coeff = K0.convert(coeff, K) coeff = K0.quo(coeff, denom) if K0_inexact: for i, (f, k) in enumerate(factors): max_norm = dmp_max_norm(f, u, K0) f = dmp_quo_ground(f, max_norm, u, K0) f = dmp_convert(f, u, K0, K0_inexact) factors[i] = (f, k) coeff = K0.mul(coeff, K0.pow(max_norm, k)) coeff = K0_inexact.convert(coeff, K0) K0 = K0_inexact for i, j in enumerate(reversed(J)): if not j: continue term = {(0,)*(u - i) + (1,) + (0,)*i: K0.one} factors.insert(0, (dmp_from_dict(term, u, K0), j)) return coeff*cont, _sort_factors(factors) def dmp_factor_list_include(f, u, K): """Factor multivariate polynomials into irreducibles in `K[X]`. """ if not u: return dup_factor_list_include(f, K) coeff, factors = dmp_factor_list(f, u, K) if not factors: return [(dmp_ground(coeff, u), 1)] else: g = dmp_mul_ground(factors[0][0], coeff, u, K) return [(g, factors[0][1])] + factors[1:] def dup_irreducible_p(f, K): """ Returns ``True`` if a univariate polynomial ``f`` has no factors over its domain. """ return dmp_irreducible_p(f, 0, K) def dmp_irreducible_p(f, u, K): """ Returns ``True`` if a multivariate polynomial ``f`` has no factors over its domain. """ _, factors = dmp_factor_list(f, u, K) if not factors: return True elif len(factors) > 1: return False else: _, k = factors[0] return k == 1