def test_catalan(): n = Symbol('n', integer=True) m = Symbol('n', integer=True, positive=True) catalans = [1, 1, 2, 5, 14, 42, 132, 429, 1430, 4862, 16796, 58786] for i, c in enumerate(catalans): assert catalan(i) == c assert catalan(n).rewrite(factorial).subs(n, i) == c assert catalan(n).rewrite(Product).subs(n, i).doit() == c assert catalan(x) == catalan(x) assert catalan(2 * x).rewrite(binomial) == binomial(4 * x, 2 * x) / (2 * x + 1) assert catalan(Rational(1, 2)).rewrite(gamma) == 8 / (3 * pi) assert catalan(Rational(1, 2)).rewrite(factorial).rewrite(gamma) ==\ 8 / (3 * pi) assert catalan(3 * x).rewrite(gamma) == 4**( 3 * x) * gamma(3 * x + Rational(1, 2)) / (sqrt(pi) * gamma(3 * x + 2)) assert catalan(x).rewrite(hyper) == hyper((-x + 1, -x), (2, ), 1) assert catalan(n).rewrite(factorial) == factorial( 2 * n) / (factorial(n + 1) * factorial(n)) assert isinstance(catalan(n).rewrite(Product), catalan) assert isinstance(catalan(m).rewrite(Product), Product) assert diff(catalan(x), x) == (polygamma(0, x + Rational(1, 2)) - polygamma(0, x + 2) + log(4)) * catalan(x) assert catalan(x).evalf() == catalan(x) c = catalan(S.Half).evalf() assert str(c) == '0.848826363156775' c = catalan(I).evalf(3) assert str((re(c), im(c))) == '(0.398, -0.0209)'
def test_catalan(): n = Symbol('n', integer=True) m = Symbol('n', integer=True, positive=True) catalans = [1, 1, 2, 5, 14, 42, 132, 429, 1430, 4862, 16796, 58786] for i, c in enumerate(catalans): assert catalan(i) == c assert catalan(n).rewrite(factorial).subs(n, i) == c assert catalan(n).rewrite(Product).subs(n, i).doit() == c assert catalan(x) == catalan(x) assert catalan(2*x).rewrite(binomial) == binomial(4*x, 2*x)/(2*x + 1) assert catalan(Rational(1, 2)).rewrite(gamma) == 8/(3*pi) assert catalan(Rational(1, 2)).rewrite(factorial).rewrite(gamma) ==\ 8 / (3 * pi) assert catalan(3*x).rewrite(gamma) == 4**( 3*x)*gamma(3*x + Rational(1, 2))/(sqrt(pi)*gamma(3*x + 2)) assert catalan(x).rewrite(hyper) == hyper((-x + 1, -x), (2,), 1) assert catalan(n).rewrite(factorial) == factorial(2*n) / (factorial(n + 1) * factorial(n)) assert isinstance(catalan(n).rewrite(Product), catalan) assert isinstance(catalan(m).rewrite(Product), Product) assert diff(catalan(x), x) == (polygamma( 0, x + Rational(1, 2)) - polygamma(0, x + 2) + log(4))*catalan(x) assert catalan(x).evalf() == catalan(x) c = catalan(S.Half).evalf() assert str(c) == '0.848826363156775' c = catalan(I).evalf(3) assert str((re(c), im(c))) == '(0.398, -0.0209)'
def gamma_rat(x): # helper to simplify ratios of gammas was = x.count(gamma) xx = x.replace(gamma, lambda n: _rf(1, (n - 1).expand() ).replace(_rf, lambda a, b: gamma(a + b)/gamma(a))) if xx.count(gamma) < was: x = xx return x
def test_ccode_exceptions(): assert ccode(gamma(x), standard='C99') == "tgamma(x)" gamma_c89 = ccode(gamma(x), standard='C89') assert 'not supported in c' in gamma_c89.lower() gamma_c89 = ccode(gamma(x), standard='C89', allow_unknown_functions=False) assert 'not supported in c' in gamma_c89.lower() gamma_c89 = ccode(gamma(x), standard='C89', allow_unknown_functions=True) assert 'not supported in c' not in gamma_c89.lower()
def test_ccode_exceptions(): assert ccode(gamma(x), standard='C99') == "tgamma(x)" assert 'not supported in c' in ccode(gamma(x), standard='C89').lower() assert ccode(ceiling(x)) == "ceil(x)" assert ccode(Abs(x)) == "fabs(x)" assert ccode(gamma(x)) == "tgamma(x)" r, s = symbols('r,s', real=True) assert ccode(Mod(ceiling(r), ceiling(s))) == "((ceil(r)) % (ceil(s)))" assert ccode(Mod(r, s)) == "fmod(r, s)"
def test_ccode_exceptions(): assert ccode(gamma(x), standard='C99') == "tgamma(x)" gamma_c89 = ccode(gamma(x), standard='C89') assert 'not supported in c' in gamma_c89.lower() gamma_c89 = ccode(gamma(x), standard='C89', allow_unknown_functions=False) assert 'not supported in c' in gamma_c89.lower() gamma_c89 = ccode(gamma(x), standard='C89', allow_unknown_functions=True) assert not 'not supported in c' in gamma_c89.lower() assert ccode(ceiling(x)) == "ceil(x)" assert ccode(Abs(x)) == "fabs(x)" assert ccode(gamma(x)) == "tgamma(x)" r, s = symbols('r,s', real=True) assert ccode(Mod(ceiling(r), ceiling(s))) == "((ceil(r)) % (ceil(s)))" assert ccode(Mod(r, s)) == "fmod(r, s)"
def test_Function(): assert mcode(f(x, y, z)) == "f[x, y, z]" assert mcode(sin(x)**cos(x)) == "Sin[x]^Cos[x]" assert mcode(conjugate(x)) == "Conjugate[x]" assert mcode(Max(x, y, z) * Min(y, z)) == "Max[x, y, z]*Min[y, z]" assert mcode(fresnelc(x)) == "FresnelC[x]" assert mcode(fresnels(x)) == "FresnelS[x]" assert mcode(gamma(x)) == "Gamma[x]" assert mcode(uppergamma(x, y)) == "Gamma[x, y]" assert mcode(polygamma(x, y)) == "PolyGamma[x, y]" assert mcode(loggamma(x)) == "LogGamma[x]" assert mcode(erf(x)) == "Erf[x]" assert mcode(erfc(x)) == "Erfc[x]" assert mcode(erfi(x)) == "Erfi[x]" assert mcode(erf2(x, y)) == "Erf[x, y]" assert mcode(expint(x, y)) == "ExpIntegralE[x, y]" assert mcode(erfcinv(x)) == "InverseErfc[x]" assert mcode(erfinv(x)) == "InverseErf[x]" assert mcode(erf2inv(x, y)) == "InverseErf[x, y]" assert mcode(Ei(x)) == "ExpIntegralEi[x]" assert mcode(Ci(x)) == "CosIntegral[x]" assert mcode(li(x)) == "LogIntegral[x]" assert mcode(Si(x)) == "SinIntegral[x]" assert mcode(Shi(x)) == "SinhIntegral[x]" assert mcode(Chi(x)) == "CoshIntegral[x]" assert mcode(beta(x, y)) == "Beta[x, y]" assert mcode(factorial(x)) == "Factorial[x]" assert mcode(factorial2(x)) == "Factorial2[x]" assert mcode(subfactorial(x)) == "Subfactorial[x]" assert mcode(FallingFactorial(x, y)) == "FactorialPower[x, y]" assert mcode(RisingFactorial(x, y)) == "Pochhammer[x, y]" assert mcode(catalan(x)) == "CatalanNumber[x]" assert mcode(harmonic(x)) == "HarmonicNumber[x]" assert mcode(harmonic(x, y)) == "HarmonicNumber[x, y]"
def test_C99CodePrinter__precision(): n = symbols('n', integer=True) f32_printer = C99CodePrinter(dict(type_aliases={real: float32})) f64_printer = C99CodePrinter(dict(type_aliases={real: float64})) f80_printer = C99CodePrinter(dict(type_aliases={real: float80})) assert f32_printer.doprint(sin(x+2.1)) == 'sinf(x + 2.1F)' assert f64_printer.doprint(sin(x+2.1)) == 'sin(x + 2.1000000000000001)' assert f80_printer.doprint(sin(x+Float('2.0'))) == 'sinl(x + 2.0L)' for printer, suffix in zip([f32_printer, f64_printer, f80_printer], ['f', '', 'l']): def check(expr, ref): assert printer.doprint(expr) == ref.format(s=suffix, S=suffix.upper()) check(Abs(n), 'abs(n)') check(Abs(x + 2.0), 'fabs{s}(x + 2.0{S})') check(sin(x + 4.0)**cos(x - 2.0), 'pow{s}(sin{s}(x + 4.0{S}), cos{s}(x - 2.0{S}))') check(exp(x*8.0), 'exp{s}(8.0{S}*x)') check(exp2(x), 'exp2{s}(x)') check(expm1(x*4.0), 'expm1{s}(4.0{S}*x)') check(Mod(n, 2), '((n) % (2))') check(Mod(2*n + 3, 3*n + 5), '((2*n + 3) % (3*n + 5))') check(Mod(x + 2.0, 3.0), 'fmod{s}(1.0{S}*x + 2.0{S}, 3.0{S})') check(Mod(x, 2.0*x + 3.0), 'fmod{s}(1.0{S}*x, 2.0{S}*x + 3.0{S})') check(log(x/2), 'log{s}((1.0{S}/2.0{S})*x)') check(log10(3*x/2), 'log10{s}((3.0{S}/2.0{S})*x)') check(log2(x*8.0), 'log2{s}(8.0{S}*x)') check(log1p(x), 'log1p{s}(x)') check(2**x, 'pow{s}(2, x)') check(2.0**x, 'pow{s}(2.0{S}, x)') check(x**3, 'pow{s}(x, 3)') check(x**4.0, 'pow{s}(x, 4.0{S})') check(sqrt(3+x), 'sqrt{s}(x + 3)') check(Cbrt(x-2.0), 'cbrt{s}(x - 2.0{S})') check(hypot(x, y), 'hypot{s}(x, y)') check(sin(3.*x + 2.), 'sin{s}(3.0{S}*x + 2.0{S})') check(cos(3.*x - 1.), 'cos{s}(3.0{S}*x - 1.0{S})') check(tan(4.*y + 2.), 'tan{s}(4.0{S}*y + 2.0{S})') check(asin(3.*x + 2.), 'asin{s}(3.0{S}*x + 2.0{S})') check(acos(3.*x + 2.), 'acos{s}(3.0{S}*x + 2.0{S})') check(atan(3.*x + 2.), 'atan{s}(3.0{S}*x + 2.0{S})') check(atan2(3.*x, 2.*y), 'atan2{s}(3.0{S}*x, 2.0{S}*y)') check(sinh(3.*x + 2.), 'sinh{s}(3.0{S}*x + 2.0{S})') check(cosh(3.*x - 1.), 'cosh{s}(3.0{S}*x - 1.0{S})') check(tanh(4.0*y + 2.), 'tanh{s}(4.0{S}*y + 2.0{S})') check(asinh(3.*x + 2.), 'asinh{s}(3.0{S}*x + 2.0{S})') check(acosh(3.*x + 2.), 'acosh{s}(3.0{S}*x + 2.0{S})') check(atanh(3.*x + 2.), 'atanh{s}(3.0{S}*x + 2.0{S})') check(erf(42.*x), 'erf{s}(42.0{S}*x)') check(erfc(42.*x), 'erfc{s}(42.0{S}*x)') check(gamma(x), 'tgamma{s}(x)') check(loggamma(x), 'lgamma{s}(x)') check(ceiling(x + 2.), "ceil{s}(x + 2.0{S})") check(floor(x + 2.), "floor{s}(x + 2.0{S})") check(fma(x, y, -z), 'fma{s}(x, y, -z)') check(Max(x, 8.0, x**4.0), 'fmax{s}(8.0{S}, fmax{s}(x, pow{s}(x, 4.0{S})))') check(Min(x, 2.0), 'fmin{s}(2.0{S}, x)')
def test_catalan(): assert catalan(1) == 1 assert catalan(2) == 2 assert catalan(3) == 5 assert catalan(4) == 14 assert catalan(x) == catalan(x) assert catalan(2*x).rewrite(binomial) == binomial(4*x, 2*x)/(2*x + 1) assert catalan(Rational(1, 2)).rewrite(gamma) == 8/(3*pi) assert catalan(3*x).rewrite(gamma) == 4**( 3*x)*gamma(3*x + Rational(1, 2))/(sqrt(pi)*gamma(3*x + 2)) assert catalan(x).rewrite(hyper) == hyper((-x + 1, -x), (2,), 1) assert diff(catalan(x), x) == (polygamma( 0, x + Rational(1, 2)) - polygamma(0, x + 2) + log(4))*catalan(x) c = catalan(0.5).evalf() assert str(c) == '0.848826363156775'
def test_catalan(): assert catalan(1) == 1 assert catalan(2) == 2 assert catalan(3) == 5 assert catalan(4) == 14 assert catalan(x) == catalan(x) assert catalan(2 * x).rewrite(binomial) == binomial(4 * x, 2 * x) / (2 * x + 1) assert catalan(Rational(1, 2)).rewrite(gamma) == 8 / (3 * pi) assert catalan(3 * x).rewrite(gamma) == 4**( 3 * x) * gamma(3 * x + Rational(1, 2)) / (sqrt(pi) * gamma(3 * x + 2)) assert catalan(x).rewrite(hyper) == hyper((-x + 1, -x), (2, ), 1) assert diff(catalan(x), x) == (polygamma(0, x + Rational(1, 2)) - polygamma(0, x + 2) + log(4)) * catalan(x) c = catalan(0.5).evalf() assert str(c) == '0.848826363156775'
def test_catalan(): n = Symbol("n", integer=True) m = Symbol("m", integer=True, positive=True) k = Symbol("k", integer=True, nonnegative=True) p = Symbol("p", nonnegative=True) catalans = [1, 1, 2, 5, 14, 42, 132, 429, 1430, 4862, 16796, 58786] for i, c in enumerate(catalans): assert catalan(i) == c assert catalan(n).rewrite(factorial).subs(n, i) == c assert catalan(n).rewrite(Product).subs(n, i).doit() == c assert unchanged(catalan, x) assert catalan(2 * x).rewrite(binomial) == binomial(4 * x, 2 * x) / (2 * x + 1) assert catalan(S.Half).rewrite(gamma) == 8 / (3 * pi) assert catalan(S.Half).rewrite(factorial).rewrite(gamma) == 8 / (3 * pi) assert catalan(3 * x).rewrite(gamma) == 4**( 3 * x) * gamma(3 * x + S.Half) / (sqrt(pi) * gamma(3 * x + 2)) assert catalan(x).rewrite(hyper) == hyper((-x + 1, -x), (2, ), 1) assert catalan(n).rewrite(factorial) == factorial( 2 * n) / (factorial(n + 1) * factorial(n)) assert isinstance(catalan(n).rewrite(Product), catalan) assert isinstance(catalan(m).rewrite(Product), Product) assert diff(catalan(x), x) == (polygamma(0, x + S.Half) - polygamma(0, x + 2) + log(4)) * catalan(x) assert catalan(x).evalf() == catalan(x) c = catalan(S.Half).evalf() assert str(c) == "0.848826363156775" c = catalan(I).evalf(3) assert str((re(c), im(c))) == "(0.398, -0.0209)" # Assumptions assert catalan(p).is_positive is True assert catalan(k).is_integer is True assert catalan(m + 3).is_composite is True
def test_ccode_functions2(): assert ccode(ceiling(x)) == "ceil(x)" assert ccode(Abs(x)) == "fabs(x)" assert ccode(gamma(x)) == "tgamma(x)" r, s = symbols('r,s', real=True) assert ccode(Mod(ceiling(r), ceiling(s))) == '((ceil(r) % ceil(s)) + '\ 'ceil(s)) % ceil(s)' assert ccode(Mod(r, s)) == "fmod(r, s)" p1, p2 = symbols('p1 p2', integer=True, positive=True) assert ccode(Mod(p1, p2)) == 'p1 % p2' assert ccode(Mod(p1, p2 + 3)) == 'p1 % (p2 + 3)' assert ccode(Mod(-3, -7, evaluate=False)) == '(-3) % (-7)' assert ccode(-Mod(3, 7, evaluate=False)) == '-(3 % 7)' assert ccode(r * Mod(p1, p2)) == 'r*(p1 % p2)' assert ccode(Mod(p1, p2)**s) == 'pow(p1 % p2, s)' n = symbols('n', integer=True, negative=True) assert ccode(Mod(-n, p2)) == '(-n) % p2'
def test_ccode_functions(): assert ccode(sin(x) ** cos(x)) == "pow(sin(x), cos(x))" assert ccode(ceiling(x)) == "ceil(x)" assert ccode(Abs(x)) == "fabs(x)" assert ccode(gamma(x)) == "tgamma(x)"
def test_C99CodePrinter__precision(): n = symbols("n", integer=True) f32_printer = C99CodePrinter(dict(type_aliases={real: float32})) f64_printer = C99CodePrinter(dict(type_aliases={real: float64})) f80_printer = C99CodePrinter(dict(type_aliases={real: float80})) assert f32_printer.doprint(sin(x + 2.1)) == "sinf(x + 2.1F)" assert f64_printer.doprint(sin(x + 2.1)) == "sin(x + 2.1000000000000001)" assert f80_printer.doprint(sin(x + Float("2.0"))) == "sinl(x + 2.0L)" for printer, suffix in zip([f32_printer, f64_printer, f80_printer], ["f", "", "l"]): def check(expr, ref): assert printer.doprint(expr) == ref.format(s=suffix, S=suffix.upper()) check(Abs(n), "abs(n)") check(Abs(x + 2.0), "fabs{s}(x + 2.0{S})") check( sin(x + 4.0) ** cos(x - 2.0), "pow{s}(sin{s}(x + 4.0{S}), cos{s}(x - 2.0{S}))", ) check(exp(x * 8.0), "exp{s}(8.0{S}*x)") check(exp2(x), "exp2{s}(x)") check(expm1(x * 4.0), "expm1{s}(4.0{S}*x)") check(Mod(n, 2), "((n) % (2))") check(Mod(2 * n + 3, 3 * n + 5), "((2*n + 3) % (3*n + 5))") check(Mod(x + 2.0, 3.0), "fmod{s}(1.0{S}*x + 2.0{S}, 3.0{S})") check(Mod(x, 2.0 * x + 3.0), "fmod{s}(1.0{S}*x, 2.0{S}*x + 3.0{S})") check(log(x / 2), "log{s}((1.0{S}/2.0{S})*x)") check(log10(3 * x / 2), "log10{s}((3.0{S}/2.0{S})*x)") check(log2(x * 8.0), "log2{s}(8.0{S}*x)") check(log1p(x), "log1p{s}(x)") check(2 ** x, "pow{s}(2, x)") check(2.0 ** x, "pow{s}(2.0{S}, x)") check(x ** 3, "pow{s}(x, 3)") check(x ** 4.0, "pow{s}(x, 4.0{S})") check(sqrt(3 + x), "sqrt{s}(x + 3)") check(Cbrt(x - 2.0), "cbrt{s}(x - 2.0{S})") check(hypot(x, y), "hypot{s}(x, y)") check(sin(3.0 * x + 2.0), "sin{s}(3.0{S}*x + 2.0{S})") check(cos(3.0 * x - 1.0), "cos{s}(3.0{S}*x - 1.0{S})") check(tan(4.0 * y + 2.0), "tan{s}(4.0{S}*y + 2.0{S})") check(asin(3.0 * x + 2.0), "asin{s}(3.0{S}*x + 2.0{S})") check(acos(3.0 * x + 2.0), "acos{s}(3.0{S}*x + 2.0{S})") check(atan(3.0 * x + 2.0), "atan{s}(3.0{S}*x + 2.0{S})") check(atan2(3.0 * x, 2.0 * y), "atan2{s}(3.0{S}*x, 2.0{S}*y)") check(sinh(3.0 * x + 2.0), "sinh{s}(3.0{S}*x + 2.0{S})") check(cosh(3.0 * x - 1.0), "cosh{s}(3.0{S}*x - 1.0{S})") check(tanh(4.0 * y + 2.0), "tanh{s}(4.0{S}*y + 2.0{S})") check(asinh(3.0 * x + 2.0), "asinh{s}(3.0{S}*x + 2.0{S})") check(acosh(3.0 * x + 2.0), "acosh{s}(3.0{S}*x + 2.0{S})") check(atanh(3.0 * x + 2.0), "atanh{s}(3.0{S}*x + 2.0{S})") check(erf(42.0 * x), "erf{s}(42.0{S}*x)") check(erfc(42.0 * x), "erfc{s}(42.0{S}*x)") check(gamma(x), "tgamma{s}(x)") check(loggamma(x), "lgamma{s}(x)") check(ceiling(x + 2.0), "ceil{s}(x + 2.0{S})") check(floor(x + 2.0), "floor{s}(x + 2.0{S})") check(fma(x, y, -z), "fma{s}(x, y, -z)") check(Max(x, 8.0, x ** 4.0), "fmax{s}(8.0{S}, fmax{s}(x, pow{s}(x, 4.0{S})))") check(Min(x, 2.0), "fmin{s}(2.0{S}, x)")
def test_rcode_exceptions(): assert rcode(ceiling(x)) == "ceiling(x)" assert rcode(Abs(x)) == "abs(x)" assert rcode(gamma(x)) == "gamma(x)"
def _gammasimp(expr, as_comb): """ Helper function for gammasimp and combsimp. Explanation =========== Simplifies expressions written in terms of gamma function. If as_comb is True, it tries to preserve integer arguments. See docstring of gammasimp for more information. This was part of combsimp() in combsimp.py. """ expr = expr.replace(gamma, lambda n: _rf(1, (n - 1).expand())) if as_comb: expr = expr.replace(_rf, lambda a, b: gamma(b + 1)) else: expr = expr.replace(_rf, lambda a, b: gamma(a + b) / gamma(a)) def rule_gamma(expr, level=0): """ Simplify products of gamma functions further. """ if expr.is_Atom: return expr def gamma_rat(x): # helper to simplify ratios of gammas was = x.count(gamma) xx = x.replace( gamma, lambda n: _rf(1, (n - 1).expand()).replace( _rf, lambda a, b: gamma(a + b) / gamma(a))) if xx.count(gamma) < was: x = xx return x def gamma_factor(x): # return True if there is a gamma factor in shallow args if isinstance(x, gamma): return True if x.is_Add or x.is_Mul: return any(gamma_factor(xi) for xi in x.args) if x.is_Pow and (x.exp.is_integer or x.base.is_positive): return gamma_factor(x.base) return False # recursion step if level == 0: expr = expr.func(*[rule_gamma(x, level + 1) for x in expr.args]) level += 1 if not expr.is_Mul: return expr # non-commutative step if level == 1: args, nc = expr.args_cnc() if not args: return expr if nc: return rule_gamma(Mul._from_args(args), level + 1) * Mul._from_args(nc) level += 1 # pure gamma handling, not factor absorption if level == 2: T, F = sift(expr.args, gamma_factor, binary=True) gamma_ind = Mul(*F) d = Mul(*T) nd, dd = d.as_numer_denom() for ipass in range(2): args = list(ordered(Mul.make_args(nd))) for i, ni in enumerate(args): if ni.is_Add: ni, dd = Add(*[ rule_gamma(gamma_rat(a / dd), level + 1) for a in ni.args ]).as_numer_denom() args[i] = ni if not dd.has(gamma): break nd = Mul(*args) if ipass == 0 and not gamma_factor(nd): break nd, dd = dd, nd # now process in reversed order expr = gamma_ind * nd / dd if not (expr.is_Mul and (gamma_factor(dd) or gamma_factor(nd))): return expr level += 1 # iteration until constant if level == 3: while True: was = expr expr = rule_gamma(expr, 4) if expr == was: return expr numer_gammas = [] denom_gammas = [] numer_others = [] denom_others = [] def explicate(p): if p is S.One: return None, [] b, e = p.as_base_exp() if e.is_Integer: if isinstance(b, gamma): return True, [b.args[0]] * e else: return False, [b] * e else: return False, [p] newargs = list(ordered(expr.args)) while newargs: n, d = newargs.pop().as_numer_denom() isg, l = explicate(n) if isg: numer_gammas.extend(l) elif isg is False: numer_others.extend(l) isg, l = explicate(d) if isg: denom_gammas.extend(l) elif isg is False: denom_others.extend(l) # =========== level 2 work: pure gamma manipulation ========= if not as_comb: # Try to reduce the number of gamma factors by applying the # reflection formula gamma(x)*gamma(1-x) = pi/sin(pi*x) for gammas, numer, denom in [ (numer_gammas, numer_others, denom_others), (denom_gammas, denom_others, numer_others) ]: new = [] while gammas: g1 = gammas.pop() if g1.is_integer: new.append(g1) continue for i, g2 in enumerate(gammas): n = g1 + g2 - 1 if not n.is_Integer: continue numer.append(S.Pi) denom.append(sin(S.Pi * g1)) gammas.pop(i) if n > 0: for k in range(n): numer.append(1 - g1 + k) elif n < 0: for k in range(-n): denom.append(-g1 - k) break else: new.append(g1) # /!\ updating IN PLACE gammas[:] = new # Try to reduce the number of gammas by using the duplication # theorem to cancel an upper and lower: gamma(2*s)/gamma(s) = # 2**(2*s + 1)/(4*sqrt(pi))*gamma(s + 1/2). Although this could # be done with higher argument ratios like gamma(3*x)/gamma(x), # this would not reduce the number of gammas as in this case. for ng, dg, no, do in [ (numer_gammas, denom_gammas, numer_others, denom_others), (denom_gammas, numer_gammas, denom_others, numer_others) ]: while True: for x in ng: for y in dg: n = x - 2 * y if n.is_Integer: break else: continue break else: break ng.remove(x) dg.remove(y) if n > 0: for k in range(n): no.append(2 * y + k) elif n < 0: for k in range(-n): do.append(2 * y - 1 - k) ng.append(y + S.Half) no.append(2**(2 * y - 1)) do.append(sqrt(S.Pi)) # Try to reduce the number of gamma factors by applying the # multiplication theorem (used when n gammas with args differing # by 1/n mod 1 are encountered). # # run of 2 with args differing by 1/2 # # >>> gammasimp(gamma(x)*gamma(x+S.Half)) # 2*sqrt(2)*2**(-2*x - 1/2)*sqrt(pi)*gamma(2*x) # # run of 3 args differing by 1/3 (mod 1) # # >>> gammasimp(gamma(x)*gamma(x+S(1)/3)*gamma(x+S(2)/3)) # 6*3**(-3*x - 1/2)*pi*gamma(3*x) # >>> gammasimp(gamma(x)*gamma(x+S(1)/3)*gamma(x+S(5)/3)) # 2*3**(-3*x - 1/2)*pi*(3*x + 2)*gamma(3*x) # def _run(coeffs): # find runs in coeffs such that the difference in terms (mod 1) # of t1, t2, ..., tn is 1/n u = list(uniq(coeffs)) for i in range(len(u)): dj = ([((u[j] - u[i]) % 1, j) for j in range(i + 1, len(u))]) for one, j in dj: if one.p == 1 and one.q != 1: n = one.q got = [i] get = list(range(1, n)) for d, j in dj: m = n * d if m.is_Integer and m in get: get.remove(m) got.append(j) if not get: break else: continue for i, j in enumerate(got): c = u[j] coeffs.remove(c) got[i] = c return one.q, got[0], got[1:] def _mult_thm(gammas, numer, denom): # pull off and analyze the leading coefficient from each gamma arg # looking for runs in those Rationals # expr -> coeff + resid -> rats[resid] = coeff rats = {} for g in gammas: c, resid = g.as_coeff_Add() rats.setdefault(resid, []).append(c) # look for runs in Rationals for each resid keys = sorted(rats, key=default_sort_key) for resid in keys: coeffs = list(sorted(rats[resid])) new = [] while True: run = _run(coeffs) if run is None: break # process the sequence that was found: # 1) convert all the gamma functions to have the right # argument (could be off by an integer) # 2) append the factors corresponding to the theorem # 3) append the new gamma function n, ui, other = run # (1) for u in other: con = resid + u - 1 for k in range(int(u - ui)): numer.append(con - k) con = n * (resid + ui) # for (2) and (3) # (2) numer.append( (2 * S.Pi)**(S(n - 1) / 2) * n**(S.Half - con)) # (3) new.append(con) # restore resid to coeffs rats[resid] = [resid + c for c in coeffs] + new # rebuild the gamma arguments g = [] for resid in keys: g += rats[resid] # /!\ updating IN PLACE gammas[:] = g for l, numer, denom in [(numer_gammas, numer_others, denom_others), (denom_gammas, denom_others, numer_others) ]: _mult_thm(l, numer, denom) # =========== level >= 2 work: factor absorption ========= if level >= 2: # Try to absorb factors into the gammas: x*gamma(x) -> gamma(x + 1) # and gamma(x)/(x - 1) -> gamma(x - 1) # This code (in particular repeated calls to find_fuzzy) can be very # slow. def find_fuzzy(l, x): if not l: return S1, T1 = compute_ST(x) for y in l: S2, T2 = inv[y] if T1 != T2 or (not S1.intersection(S2) and (S1 != set() or S2 != set())): continue # XXX we want some simplification (e.g. cancel or # simplify) but no matter what it's slow. a = len(cancel(x / y).free_symbols) b = len(x.free_symbols) c = len(y.free_symbols) # TODO is there a better heuristic? if a == 0 and (b > 0 or c > 0): return y # We thus try to avoid expensive calls by building the following # "invariants": For every factor or gamma function argument # - the set of free symbols S # - the set of functional components T # We will only try to absorb if T1==T2 and (S1 intersect S2 != emptyset # or S1 == S2 == emptyset) inv = {} def compute_ST(expr): if expr in inv: return inv[expr] return (expr.free_symbols, expr.atoms(Function).union( {e.exp for e in expr.atoms(Pow)})) def update_ST(expr): inv[expr] = compute_ST(expr) for expr in numer_gammas + denom_gammas + numer_others + denom_others: update_ST(expr) for gammas, numer, denom in [ (numer_gammas, numer_others, denom_others), (denom_gammas, denom_others, numer_others) ]: new = [] while gammas: g = gammas.pop() cont = True while cont: cont = False y = find_fuzzy(numer, g) if y is not None: numer.remove(y) if y != g: numer.append(y / g) update_ST(y / g) g += 1 cont = True y = find_fuzzy(denom, g - 1) if y is not None: denom.remove(y) if y != g - 1: numer.append((g - 1) / y) update_ST((g - 1) / y) g -= 1 cont = True new.append(g) # /!\ updating IN PLACE gammas[:] = new # =========== rebuild expr ================================== return Mul(*[gamma(g) for g in numer_gammas]) \ / Mul(*[gamma(g) for g in denom_gammas]) \ * Mul(*numer_others) / Mul(*denom_others) was = factor(expr) # (for some reason we cannot use Basic.replace in this case) expr = rule_gamma(was) if expr != was: expr = factor(expr) expr = expr.replace( gamma, lambda n: expand_func(gamma(n)) if n.is_Rational else gamma(n)) return expr
def test_ccode_exceptions(): assert ccode(ceiling(x)) == "ceil(x)" assert ccode(Abs(x)) == "fabs(x)" assert ccode(gamma(x)) == "tgamma(x)"
def test_rcode_functions(): assert rcode(sin(x)**cos(x)) == "sin(x)^cos(x)" assert rcode(factorial(x) + gamma(y)) == "factorial(x) + gamma(y)" assert rcode(beta(Min(x, y), Max(x, y))) == "beta(min(x, y), max(x, y))"
def combsimp(expr): r""" Simplify combinatorial expressions. This function takes as input an expression containing factorials, binomials, Pochhammer symbol and other "combinatorial" functions, and tries to minimize the number of those functions and reduce the size of their arguments. The result is be given in terms of binomials and factorials. The algorithm works by rewriting all combinatorial functions as expressions involving rising factorials (Pochhammer symbols) and applies recurrence relations and other transformations applicable to rising factorials, to reduce their arguments, possibly letting the resulting rising factorial to cancel. Rising factorials with the second argument being an integer are expanded into polynomial forms and finally all other rising factorial are rewritten in terms more familiar functions. If the initial expression contained any combinatorial functions, the result is expressed using binomial coefficients and gamma functions. If the initial expression consisted of gamma functions alone, the result is expressed in terms of gamma functions. If the result is expressed using gamma functions, the following three additional steps are performed: 1. Reduce the number of gammas by applying the reflection theorem gamma(x)*gamma(1-x) == pi/sin(pi*x). 2. Reduce the number of gammas by applying the multiplication theorem gamma(x)*gamma(x+1/n)*...*gamma(x+(n-1)/n) == C*gamma(n*x). 3. Reduce the number of prefactors by absorbing them into gammas, where possible. All transformation rules can be found (or was derived from) here: 1. http://functions.wolfram.com/GammaBetaErf/Pochhammer/17/01/02/ 2. http://functions.wolfram.com/GammaBetaErf/Pochhammer/27/01/0005/ Examples ======== >>> from sympy.simplify import combsimp >>> from sympy import factorial, binomial >>> from sympy.abc import n, k >>> combsimp(factorial(n)/factorial(n - 3)) n*(n - 2)*(n - 1) >>> combsimp(binomial(n+1, k+1)/binomial(n, k)) (n + 1)/(k + 1) """ # as a rule of thumb, if the expression contained gammas initially, it # probably makes sense to retain them as_gamma = not expr.has(factorial, binomial) expr = expr.replace( binomial, lambda n, k: _rf( (n - k + 1).expand(), k.expand()) / _rf(1, k.expand())) expr = expr.replace(factorial, lambda n: _rf(1, n.expand())) expr = expr.rewrite(gamma) expr = expr.replace(gamma, lambda n: _rf(1, (n - 1).expand())) if as_gamma: expr = expr.replace(_rf, lambda a, b: gamma(a + b) / gamma(a)) else: expr = expr.replace(_rf, lambda a, b: binomial(a + b - 1, b) * factorial(b)) def rule(n, k): coeff, rewrite = S.One, False cn, _n = n.as_coeff_Add() if _n and cn.is_Integer and cn: coeff *= _rf(_n + 1, cn) / _rf(_n - k + 1, cn) rewrite = True n = _n # this sort of binomial has already been removed by # rising factorials but is left here in case the order # of rule application is changed if k.is_Add: ck, _k = k.as_coeff_Add() if _k and ck.is_Integer and ck: coeff *= _rf(n - ck - _k + 1, ck) / _rf(_k + 1, ck) rewrite = True k = _k if rewrite: return coeff * binomial(n, k) expr = expr.replace(binomial, rule) def rule_gamma(expr, level=0): """ Simplify products of gamma functions further. """ if expr.is_Atom: return expr def gamma_rat(x): # helper to simplify ratios of gammas was = x.count(gamma) xx = x.replace( gamma, lambda n: _rf(1, (n - 1).expand()).replace( _rf, lambda a, b: gamma(a + b) / gamma(a))) if xx.count(gamma) < was: x = xx return x def gamma_factor(x): # return True if there is a gamma factor in shallow args if x.func is gamma: return True if x.is_Add or x.is_Mul: return any(gamma_factor(xi) for xi in x.args) if x.is_Pow and (x.exp.is_integer or x.base.is_positive): return gamma_factor(x.base) return False # recursion step if level == 0: expr = expr.func(*[rule_gamma(x, level + 1) for x in expr.args]) level += 1 if not expr.is_Mul: return expr # non-commutative step if level == 1: args, nc = expr.args_cnc() if not args: return expr if nc: return rule_gamma(Mul._from_args(args), level + 1) * Mul._from_args(nc) level += 1 # pure gamma handling, not factor absorbtion if level == 2: sifted = sift(expr.args, gamma_factor) gamma_ind = Mul(*sifted.pop(False, [])) d = Mul(*sifted.pop(True, [])) assert not sifted nd, dd = d.as_numer_denom() for ipass in range(2): args = list(ordered(Mul.make_args(nd))) for i, ni in enumerate(args): if ni.is_Add: ni, dd = Add(*[ rule_gamma(gamma_rat(a / dd), level + 1) for a in ni.args ]).as_numer_denom() args[i] = ni if not dd.has(gamma): break nd = Mul(*args) if ipass == 0 and not gamma_factor(nd): break nd, dd = dd, nd # now process in reversed order expr = gamma_ind * nd / dd if not (expr.is_Mul and (gamma_factor(dd) or gamma_factor(nd))): return expr level += 1 # iteration until constant if level == 3: while True: was = expr expr = rule_gamma(expr, 4) if expr == was: return expr numer_gammas = [] denom_gammas = [] numer_others = [] denom_others = [] def explicate(p): if p is S.One: return None, [] b, e = p.as_base_exp() if e.is_Integer: if b.func is gamma: return True, [b.args[0]] * e else: return False, [b] * e else: return False, [p] newargs = list(ordered(expr.args)) while newargs: n, d = newargs.pop().as_numer_denom() isg, l = explicate(n) if isg: numer_gammas.extend(l) elif isg is False: numer_others.extend(l) isg, l = explicate(d) if isg: denom_gammas.extend(l) elif isg is False: denom_others.extend(l) # =========== level 2 work: pure gamma manipulation ========= # Try to reduce the number of gamma factors by applying the # reflection formula gamma(x)*gamma(1-x) = pi/sin(pi*x) for gammas, numer, denom in [ (numer_gammas, numer_others, denom_others), (denom_gammas, denom_others, numer_others) ]: new = [] while gammas: g1 = gammas.pop() if g1.is_integer: new.append(g1) continue for i, g2 in enumerate(gammas): n = g1 + g2 - 1 if not n.is_Integer: continue numer.append(S.Pi) denom.append(sin(S.Pi * g1)) gammas.pop(i) if n > 0: for k in range(n): numer.append(1 - g1 + k) elif n < 0: for k in range(-n): denom.append(-g1 - k) break else: new.append(g1) # /!\ updating IN PLACE gammas[:] = new # Try to reduce the number of gammas by using the duplication # theorem to cancel an upper and lower: gamma(2*s)/gamma(s) = # 2**(2*s + 1)/(4*sqrt(pi))*gamma(s + 1/2). Although this could # be done with higher argument ratios like gamma(3*x)/gamma(x), # this would not reduce the number of gammas as in this case. for ng, dg, no, do in [ (numer_gammas, denom_gammas, numer_others, denom_others), (denom_gammas, numer_gammas, denom_others, numer_others) ]: while True: for x in ng: for y in dg: n = x - 2 * y if n.is_Integer: break else: continue break else: break ng.remove(x) dg.remove(y) if n > 0: for k in range(n): no.append(2 * y + k) elif n < 0: for k in range(-n): do.append(2 * y - 1 - k) ng.append(y + S(1) / 2) no.append(2**(2 * y - 1)) do.append(sqrt(S.Pi)) # Try to reduce the number of gamma factors by applying the # multiplication theorem (used when n gammas with args differing # by 1/n mod 1 are encountered). # # run of 2 with args differing by 1/2 # # >>> combsimp(gamma(x)*gamma(x+S.Half)) # 2*sqrt(2)*2**(-2*x - 1/2)*sqrt(pi)*gamma(2*x) # # run of 3 args differing by 1/3 (mod 1) # # >>> combsimp(gamma(x)*gamma(x+S(1)/3)*gamma(x+S(2)/3)) # 6*3**(-3*x - 1/2)*pi*gamma(3*x) # >>> combsimp(gamma(x)*gamma(x+S(1)/3)*gamma(x+S(5)/3)) # 2*3**(-3*x - 1/2)*pi*(3*x + 2)*gamma(3*x) # def _run(coeffs): # find runs in coeffs such that the difference in terms (mod 1) # of t1, t2, ..., tn is 1/n u = list(uniq(coeffs)) for i in range(len(u)): dj = ([((u[j] - u[i]) % 1, j) for j in range(i + 1, len(u))]) for one, j in dj: if one.p == 1 and one.q != 1: n = one.q got = [i] get = list(range(1, n)) for d, j in dj: m = n * d if m.is_Integer and m in get: get.remove(m) got.append(j) if not get: break else: continue for i, j in enumerate(got): c = u[j] coeffs.remove(c) got[i] = c return one.q, got[0], got[1:] def _mult_thm(gammas, numer, denom): # pull off and analyze the leading coefficient from each gamma arg # looking for runs in those Rationals # expr -> coeff + resid -> rats[resid] = coeff rats = {} for g in gammas: c, resid = g.as_coeff_Add() rats.setdefault(resid, []).append(c) # look for runs in Rationals for each resid keys = sorted(rats, key=default_sort_key) for resid in keys: coeffs = list(sorted(rats[resid])) new = [] while True: run = _run(coeffs) if run is None: break # process the sequence that was found: # 1) convert all the gamma functions to have the right # argument (could be off by an integer) # 2) append the factors corresponding to the theorem # 3) append the new gamma function n, ui, other = run # (1) for u in other: con = resid + u - 1 for k in range(int(u - ui)): numer.append(con - k) con = n * (resid + ui) # for (2) and (3) # (2) numer.append( (2 * S.Pi)**(S(n - 1) / 2) * n**(S(1) / 2 - con)) # (3) new.append(con) # restore resid to coeffs rats[resid] = [resid + c for c in coeffs] + new # rebuild the gamma arguments g = [] for resid in keys: g += rats[resid] # /!\ updating IN PLACE gammas[:] = g for l, numer, denom in [(numer_gammas, numer_others, denom_others), (denom_gammas, denom_others, numer_others)]: _mult_thm(l, numer, denom) # =========== level >= 2 work: factor absorbtion ========= if level >= 2: # Try to absorb factors into the gammas: x*gamma(x) -> gamma(x + 1) # and gamma(x)/(x - 1) -> gamma(x - 1) # This code (in particular repeated calls to find_fuzzy) can be very # slow. def find_fuzzy(l, x): if not l: return S1, T1 = compute_ST(x) for y in l: S2, T2 = inv[y] if T1 != T2 or (not S1.intersection(S2) and (S1 != set() or S2 != set())): continue # XXX we want some simplification (e.g. cancel or # simplify) but no matter what it's slow. a = len(cancel(x / y).free_symbols) b = len(x.free_symbols) c = len(y.free_symbols) # TODO is there a better heuristic? if a == 0 and (b > 0 or c > 0): return y # We thus try to avoid expensive calls by building the following # "invariants": For every factor or gamma function argument # - the set of free symbols S # - the set of functional components T # We will only try to absorb if T1==T2 and (S1 intersect S2 != emptyset # or S1 == S2 == emptyset) inv = {} def compute_ST(expr): if expr in inv: return inv[expr] return (expr.free_symbols, expr.atoms(Function).union( set(e.exp for e in expr.atoms(Pow)))) def update_ST(expr): inv[expr] = compute_ST(expr) for expr in numer_gammas + denom_gammas + numer_others + denom_others: update_ST(expr) for gammas, numer, denom in [ (numer_gammas, numer_others, denom_others), (denom_gammas, denom_others, numer_others) ]: new = [] while gammas: g = gammas.pop() cont = True while cont: cont = False y = find_fuzzy(numer, g) if y is not None: numer.remove(y) if y != g: numer.append(y / g) update_ST(y / g) g += 1 cont = True y = find_fuzzy(denom, g - 1) if y is not None: denom.remove(y) if y != g - 1: numer.append((g - 1) / y) update_ST((g - 1) / y) g -= 1 cont = True new.append(g) # /!\ updating IN PLACE gammas[:] = new # =========== rebuild expr ================================== return Mul(*[gamma(g) for g in numer_gammas]) \ / Mul(*[gamma(g) for g in denom_gammas]) \ * Mul(*numer_others) / Mul(*denom_others) # (for some reason we cannot use Basic.replace in this case) was = factor(expr) expr = rule_gamma(was) if expr != was: expr = factor(expr) return expr
def fdiff(self, argindex=1): if argindex == 1: from sympy.functions import gamma, polygamma return gamma(self[0]+1)*polygamma(0,self[0]+1) else: raise ArgumentIndexError(self, argindex)
def test_rcode_functions(): assert rcode(sin(x) ** cos(x)) == "sin(x)^cos(x)" assert rcode(factorial(x) + gamma(y)) == "factorial(x) + gamma(y)" assert rcode(beta(Min(x, y), Max(x, y))) == "beta(min(x, y), max(x, y))"
def test_functions_special(): assert oclcode(erf(x)) == "erf(x)" assert oclcode(erfc(x)) == "erfc(x)" assert oclcode(gamma(x)) == "tgamma(x)" assert oclcode(loggamma(x)) == "lgamma(x)"
def _gammasimp(expr, as_comb): """ Helper function for gammasimp and combsimp. Simplifies expressions written in terms of gamma function. If as_comb is True, it tries to preserve integer arguments. See docstring of gammasimp for more information. This was part of combsimp() in combsimp.py. """ expr = expr.replace(gamma, lambda n: _rf(1, (n - 1).expand())) if as_comb: expr = expr.replace(_rf, lambda a, b: gamma(b + 1)) else: expr = expr.replace(_rf, lambda a, b: gamma(a + b)/gamma(a)) def rule(n, k): coeff, rewrite = S.One, False cn, _n = n.as_coeff_Add() if _n and cn.is_Integer and cn: coeff *= _rf(_n + 1, cn)/_rf(_n - k + 1, cn) rewrite = True n = _n # this sort of binomial has already been removed by # rising factorials but is left here in case the order # of rule application is changed if k.is_Add: ck, _k = k.as_coeff_Add() if _k and ck.is_Integer and ck: coeff *= _rf(n - ck - _k + 1, ck)/_rf(_k + 1, ck) rewrite = True k = _k if count_ops(k) > count_ops(n - k): rewrite = True k = n - k if rewrite: return coeff*binomial(n, k) expr = expr.replace(binomial, rule) def rule_gamma(expr, level=0): """ Simplify products of gamma functions further. """ if expr.is_Atom: return expr def gamma_rat(x): # helper to simplify ratios of gammas was = x.count(gamma) xx = x.replace(gamma, lambda n: _rf(1, (n - 1).expand() ).replace(_rf, lambda a, b: gamma(a + b)/gamma(a))) if xx.count(gamma) < was: x = xx return x def gamma_factor(x): # return True if there is a gamma factor in shallow args if isinstance(x, gamma): return True if x.is_Add or x.is_Mul: return any(gamma_factor(xi) for xi in x.args) if x.is_Pow and (x.exp.is_integer or x.base.is_positive): return gamma_factor(x.base) return False # recursion step if level == 0: expr = expr.func(*[rule_gamma(x, level + 1) for x in expr.args]) level += 1 if not expr.is_Mul: return expr # non-commutative step if level == 1: args, nc = expr.args_cnc() if not args: return expr if nc: return rule_gamma(Mul._from_args(args), level + 1)*Mul._from_args(nc) level += 1 # pure gamma handling, not factor absorption if level == 2: T, F = sift(expr.args, gamma_factor, binary=True) gamma_ind = Mul(*F) d = Mul(*T) nd, dd = d.as_numer_denom() for ipass in range(2): args = list(ordered(Mul.make_args(nd))) for i, ni in enumerate(args): if ni.is_Add: ni, dd = Add(*[ rule_gamma(gamma_rat(a/dd), level + 1) for a in ni.args] ).as_numer_denom() args[i] = ni if not dd.has(gamma): break nd = Mul(*args) if ipass == 0 and not gamma_factor(nd): break nd, dd = dd, nd # now process in reversed order expr = gamma_ind*nd/dd if not (expr.is_Mul and (gamma_factor(dd) or gamma_factor(nd))): return expr level += 1 # iteration until constant if level == 3: while True: was = expr expr = rule_gamma(expr, 4) if expr == was: return expr numer_gammas = [] denom_gammas = [] numer_others = [] denom_others = [] def explicate(p): if p is S.One: return None, [] b, e = p.as_base_exp() if e.is_Integer: if isinstance(b, gamma): return True, [b.args[0]]*e else: return False, [b]*e else: return False, [p] newargs = list(ordered(expr.args)) while newargs: n, d = newargs.pop().as_numer_denom() isg, l = explicate(n) if isg: numer_gammas.extend(l) elif isg is False: numer_others.extend(l) isg, l = explicate(d) if isg: denom_gammas.extend(l) elif isg is False: denom_others.extend(l) # =========== level 2 work: pure gamma manipulation ========= if not as_comb: # Try to reduce the number of gamma factors by applying the # reflection formula gamma(x)*gamma(1-x) = pi/sin(pi*x) for gammas, numer, denom in [( numer_gammas, numer_others, denom_others), (denom_gammas, denom_others, numer_others)]: new = [] while gammas: g1 = gammas.pop() if g1.is_integer: new.append(g1) continue for i, g2 in enumerate(gammas): n = g1 + g2 - 1 if not n.is_Integer: continue numer.append(S.Pi) denom.append(sin(S.Pi*g1)) gammas.pop(i) if n > 0: for k in range(n): numer.append(1 - g1 + k) elif n < 0: for k in range(-n): denom.append(-g1 - k) break else: new.append(g1) # /!\ updating IN PLACE gammas[:] = new # Try to reduce the number of gammas by using the duplication # theorem to cancel an upper and lower: gamma(2*s)/gamma(s) = # 2**(2*s + 1)/(4*sqrt(pi))*gamma(s + 1/2). Although this could # be done with higher argument ratios like gamma(3*x)/gamma(x), # this would not reduce the number of gammas as in this case. for ng, dg, no, do in [(numer_gammas, denom_gammas, numer_others, denom_others), (denom_gammas, numer_gammas, denom_others, numer_others)]: while True: for x in ng: for y in dg: n = x - 2*y if n.is_Integer: break else: continue break else: break ng.remove(x) dg.remove(y) if n > 0: for k in range(n): no.append(2*y + k) elif n < 0: for k in range(-n): do.append(2*y - 1 - k) ng.append(y + S(1)/2) no.append(2**(2*y - 1)) do.append(sqrt(S.Pi)) # Try to reduce the number of gamma factors by applying the # multiplication theorem (used when n gammas with args differing # by 1/n mod 1 are encountered). # # run of 2 with args differing by 1/2 # # >>> gammasimp(gamma(x)*gamma(x+S.Half)) # 2*sqrt(2)*2**(-2*x - 1/2)*sqrt(pi)*gamma(2*x) # # run of 3 args differing by 1/3 (mod 1) # # >>> gammasimp(gamma(x)*gamma(x+S(1)/3)*gamma(x+S(2)/3)) # 6*3**(-3*x - 1/2)*pi*gamma(3*x) # >>> gammasimp(gamma(x)*gamma(x+S(1)/3)*gamma(x+S(5)/3)) # 2*3**(-3*x - 1/2)*pi*(3*x + 2)*gamma(3*x) # def _run(coeffs): # find runs in coeffs such that the difference in terms (mod 1) # of t1, t2, ..., tn is 1/n u = list(uniq(coeffs)) for i in range(len(u)): dj = ([((u[j] - u[i]) % 1, j) for j in range(i + 1, len(u))]) for one, j in dj: if one.p == 1 and one.q != 1: n = one.q got = [i] get = list(range(1, n)) for d, j in dj: m = n*d if m.is_Integer and m in get: get.remove(m) got.append(j) if not get: break else: continue for i, j in enumerate(got): c = u[j] coeffs.remove(c) got[i] = c return one.q, got[0], got[1:] def _mult_thm(gammas, numer, denom): # pull off and analyze the leading coefficient from each gamma arg # looking for runs in those Rationals # expr -> coeff + resid -> rats[resid] = coeff rats = {} for g in gammas: c, resid = g.as_coeff_Add() rats.setdefault(resid, []).append(c) # look for runs in Rationals for each resid keys = sorted(rats, key=default_sort_key) for resid in keys: coeffs = list(sorted(rats[resid])) new = [] while True: run = _run(coeffs) if run is None: break # process the sequence that was found: # 1) convert all the gamma functions to have the right # argument (could be off by an integer) # 2) append the factors corresponding to the theorem # 3) append the new gamma function n, ui, other = run # (1) for u in other: con = resid + u - 1 for k in range(int(u - ui)): numer.append(con - k) con = n*(resid + ui) # for (2) and (3) # (2) numer.append((2*S.Pi)**(S(n - 1)/2)* n**(S(1)/2 - con)) # (3) new.append(con) # restore resid to coeffs rats[resid] = [resid + c for c in coeffs] + new # rebuild the gamma arguments g = [] for resid in keys: g += rats[resid] # /!\ updating IN PLACE gammas[:] = g for l, numer, denom in [(numer_gammas, numer_others, denom_others), (denom_gammas, denom_others, numer_others)]: _mult_thm(l, numer, denom) # =========== level >= 2 work: factor absorption ========= if level >= 2: # Try to absorb factors into the gammas: x*gamma(x) -> gamma(x + 1) # and gamma(x)/(x - 1) -> gamma(x - 1) # This code (in particular repeated calls to find_fuzzy) can be very # slow. def find_fuzzy(l, x): if not l: return S1, T1 = compute_ST(x) for y in l: S2, T2 = inv[y] if T1 != T2 or (not S1.intersection(S2) and (S1 != set() or S2 != set())): continue # XXX we want some simplification (e.g. cancel or # simplify) but no matter what it's slow. a = len(cancel(x/y).free_symbols) b = len(x.free_symbols) c = len(y.free_symbols) # TODO is there a better heuristic? if a == 0 and (b > 0 or c > 0): return y # We thus try to avoid expensive calls by building the following # "invariants": For every factor or gamma function argument # - the set of free symbols S # - the set of functional components T # We will only try to absorb if T1==T2 and (S1 intersect S2 != emptyset # or S1 == S2 == emptyset) inv = {} def compute_ST(expr): if expr in inv: return inv[expr] return (expr.free_symbols, expr.atoms(Function).union( set(e.exp for e in expr.atoms(Pow)))) def update_ST(expr): inv[expr] = compute_ST(expr) for expr in numer_gammas + denom_gammas + numer_others + denom_others: update_ST(expr) for gammas, numer, denom in [( numer_gammas, numer_others, denom_others), (denom_gammas, denom_others, numer_others)]: new = [] while gammas: g = gammas.pop() cont = True while cont: cont = False y = find_fuzzy(numer, g) if y is not None: numer.remove(y) if y != g: numer.append(y/g) update_ST(y/g) g += 1 cont = True y = find_fuzzy(denom, g - 1) if y is not None: denom.remove(y) if y != g - 1: numer.append((g - 1)/y) update_ST((g - 1)/y) g -= 1 cont = True new.append(g) # /!\ updating IN PLACE gammas[:] = new # =========== rebuild expr ================================== return Mul(*[gamma(g) for g in numer_gammas]) \ / Mul(*[gamma(g) for g in denom_gammas]) \ * Mul(*numer_others) / Mul(*denom_others) # (for some reason we cannot use Basic.replace in this case) was = factor(expr) expr = rule_gamma(was) if expr != was: expr = factor(expr) expr = expr.replace(gamma, lambda n: expand_func(gamma(n)) if n.is_Rational else gamma(n)) return expr
def test_ccode_functions(): assert ccode(sin(x)**cos(x)) == "pow(sin(x), cos(x))" assert ccode(ceiling(x)) == "ceil(x)" assert ccode(Abs(x)) == "fabs(x)" assert ccode(gamma(x)) == "tgamma(x)"
def test_ccode_exceptions(): assert ccode(gamma(x), standard='C99') == "tgamma(x)" assert 'not supported in c' in ccode(gamma(x), standard='C89').lower() assert ccode(ceiling(x)) == "ceil(x)" assert ccode(Abs(x)) == "fabs(x)" assert ccode(gamma(x)) == "tgamma(x)"