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			507 lines
		
	
	
		
			22 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
			
		
		
	
	
			507 lines
		
	
	
		
			22 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
| // This file is part of Eigen, a lightweight C++ template library
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| // for linear algebra.
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| //
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| // Copyright (C) 2016 Gael Guennebaud <gael.guennebaud@inria.fr>
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| //
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| // This Source Code Form is subject to the terms of the Mozilla
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| // Public License v. 2.0. If a copy of the MPL was not distributed
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| // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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| 
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| #include <limits.h>
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| #include "../Eigen/SpecialFunctions"
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| #include "main.h"
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| 
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| // Hack to allow "implicit" conversions from double to Scalar via
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| // comma-initialization.
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| template <typename Derived>
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| Eigen::CommaInitializer<Derived> operator<<(Eigen::DenseBase<Derived>& dense,
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|                                             double v) {
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|   return (dense << static_cast<typename Derived::Scalar>(v));
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| }
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| 
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| template <typename XprType>
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| Eigen::CommaInitializer<XprType>& operator,(
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|     Eigen::CommaInitializer<XprType>& ci, double v) {
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|   return (ci, static_cast<typename XprType::Scalar>(v));
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| }
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| 
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| template <typename X, typename Y>
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| void verify_component_wise(const X& x, const Y& y) {
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|   for (Index i = 0; i < x.size(); ++i) {
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|     if ((numext::isfinite)(y(i)))
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|       VERIFY_IS_APPROX(x(i), y(i));
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|     else if ((numext::isnan)(y(i)))
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|       VERIFY((numext::isnan)(x(i)));
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|     else
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|       VERIFY_IS_EQUAL(x(i), y(i));
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|   }
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| }
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| 
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| template <typename ArrayType>
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| void array_special_functions() {
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|   using std::abs;
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|   using std::sqrt;
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|   typedef typename ArrayType::Scalar Scalar;
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|   typedef typename NumTraits<Scalar>::Real RealScalar;
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| 
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|   Scalar plusinf = std::numeric_limits<Scalar>::infinity();
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|   Scalar nan = std::numeric_limits<Scalar>::quiet_NaN();
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| 
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|   Index rows = internal::random<Index>(1, 30);
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|   Index cols = 1;
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| 
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|   // API
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|   {
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|     ArrayType m1 = ArrayType::Random(rows, cols);
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| #if EIGEN_HAS_C99_MATH
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|     VERIFY_IS_APPROX(m1.lgamma(), lgamma(m1));
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|     VERIFY_IS_APPROX(m1.digamma(), digamma(m1));
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|     VERIFY_IS_APPROX(m1.erf(), erf(m1));
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|     VERIFY_IS_APPROX(m1.erfc(), erfc(m1));
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| #endif  // EIGEN_HAS_C99_MATH
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|   }
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| 
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| #if EIGEN_HAS_C99_MATH
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|   // check special functions (comparing against numpy implementation)
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|   if (!NumTraits<Scalar>::IsComplex) {
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|     {
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|       ArrayType m1 = ArrayType::Random(rows, cols);
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|       ArrayType m2 = ArrayType::Random(rows, cols);
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| 
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|       // Test various propreties of igamma & igammac.  These are normalized
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|       // gamma integrals where
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|       //   igammac(a, x) = Gamma(a, x) / Gamma(a)
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|       //   igamma(a, x) = gamma(a, x) / Gamma(a)
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|       // where Gamma and gamma are considered the standard unnormalized
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|       // upper and lower incomplete gamma functions, respectively.
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|       ArrayType a = m1.abs() + Scalar(2);
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|       ArrayType x = m2.abs() + Scalar(2);
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|       ArrayType zero = ArrayType::Zero(rows, cols);
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|       ArrayType one = ArrayType::Constant(rows, cols, Scalar(1.0));
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|       ArrayType a_m1 = a - one;
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|       ArrayType Gamma_a_x = Eigen::igammac(a, x) * a.lgamma().exp();
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|       ArrayType Gamma_a_m1_x = Eigen::igammac(a_m1, x) * a_m1.lgamma().exp();
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|       ArrayType gamma_a_x = Eigen::igamma(a, x) * a.lgamma().exp();
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|       ArrayType gamma_a_m1_x = Eigen::igamma(a_m1, x) * a_m1.lgamma().exp();
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| 
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|       // Gamma(a, 0) == Gamma(a)
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|       VERIFY_IS_APPROX(Eigen::igammac(a, zero), one);
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| 
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|       // Gamma(a, x) + gamma(a, x) == Gamma(a)
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|       VERIFY_IS_APPROX(Gamma_a_x + gamma_a_x, a.lgamma().exp());
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| 
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|       // Gamma(a, x) == (a - 1) * Gamma(a-1, x) + x^(a-1) * exp(-x)
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|       VERIFY_IS_APPROX(Gamma_a_x, (a - Scalar(1)) * Gamma_a_m1_x +
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|                                       x.pow(a - Scalar(1)) * (-x).exp());
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| 
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|       // gamma(a, x) == (a - 1) * gamma(a-1, x) - x^(a-1) * exp(-x)
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|       VERIFY_IS_APPROX(gamma_a_x, (a - Scalar(1)) * gamma_a_m1_x -
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|                                       x.pow(a - Scalar(1)) * (-x).exp());
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|     }
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|     {
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|       // Verify for large a and x that values are between 0 and 1.
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|       ArrayType m1 = ArrayType::Random(rows, cols);
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|       ArrayType m2 = ArrayType::Random(rows, cols);
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|       int max_exponent = std::numeric_limits<Scalar>::max_exponent10;
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|       ArrayType a = m1.abs() * Scalar(pow(10., max_exponent - 1));
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|       ArrayType x = m2.abs() * Scalar(pow(10., max_exponent - 1));
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|       for (int i = 0; i < a.size(); ++i) {
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|         Scalar igam = numext::igamma(a(i), x(i));
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|         VERIFY(0 <= igam);
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|         VERIFY(igam <= 1);
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|       }
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|     }
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| 
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|     {
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|       // Check exact values of igamma and igammac against a third party
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|       // calculation.
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|       Scalar a_s[] = {Scalar(0), Scalar(1),      Scalar(1.5),
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|                       Scalar(4), Scalar(0.0001), Scalar(1000.5)};
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|       Scalar x_s[] = {Scalar(0), Scalar(1),      Scalar(1.5),
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|                       Scalar(4), Scalar(0.0001), Scalar(1000.5)};
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| 
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|       // location i*6+j corresponds to a_s[i], x_s[j].
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|       Scalar igamma_s[][6] = {
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|           {Scalar(0.0), nan, nan, nan, nan, nan},
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|           {Scalar(0.0), Scalar(0.6321205588285578), Scalar(0.7768698398515702),
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|            Scalar(0.9816843611112658), Scalar(9.999500016666262e-05),
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|            Scalar(1.0)},
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|           {Scalar(0.0), Scalar(0.4275932955291202), Scalar(0.608374823728911),
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|            Scalar(0.9539882943107686), Scalar(7.522076445089201e-07),
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|            Scalar(1.0)},
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|           {Scalar(0.0), Scalar(0.01898815687615381),
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|            Scalar(0.06564245437845008), Scalar(0.5665298796332909),
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|            Scalar(4.166333347221828e-18), Scalar(1.0)},
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|           {Scalar(0.0), Scalar(0.9999780593618628), Scalar(0.9999899967080838),
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|            Scalar(0.9999996219837988), Scalar(0.9991370418689945), Scalar(1.0)},
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|           {Scalar(0.0), Scalar(0.0), Scalar(0.0), Scalar(0.0), Scalar(0.0),
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|            Scalar(0.5042041932513908)}};
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|       Scalar igammac_s[][6] = {
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|           {nan, nan, nan, nan, nan, nan},
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|           {Scalar(1.0), Scalar(0.36787944117144233),
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|            Scalar(0.22313016014842982), Scalar(0.018315638888734182),
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|            Scalar(0.9999000049998333), Scalar(0.0)},
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|           {Scalar(1.0), Scalar(0.5724067044708798), Scalar(0.3916251762710878),
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|            Scalar(0.04601170568923136), Scalar(0.9999992477923555),
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|            Scalar(0.0)},
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|           {Scalar(1.0), Scalar(0.9810118431238462), Scalar(0.9343575456215499),
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|            Scalar(0.4334701203667089), Scalar(1.0), Scalar(0.0)},
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|           {Scalar(1.0), Scalar(2.1940638138146658e-05),
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|            Scalar(1.0003291916285e-05), Scalar(3.7801620118431334e-07),
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|            Scalar(0.0008629581310054535), Scalar(0.0)},
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|           {Scalar(1.0), Scalar(1.0), Scalar(1.0), Scalar(1.0), Scalar(1.0),
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|            Scalar(0.49579580674813944)}};
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| 
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|       for (int i = 0; i < 6; ++i) {
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|         for (int j = 0; j < 6; ++j) {
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|           if ((std::isnan)(igamma_s[i][j])) {
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|             VERIFY((std::isnan)(numext::igamma(a_s[i], x_s[j])));
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|           } else {
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|             VERIFY_IS_APPROX(numext::igamma(a_s[i], x_s[j]), igamma_s[i][j]);
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|           }
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| 
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|           if ((std::isnan)(igammac_s[i][j])) {
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|             VERIFY((std::isnan)(numext::igammac(a_s[i], x_s[j])));
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|           } else {
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|             VERIFY_IS_APPROX(numext::igammac(a_s[i], x_s[j]), igammac_s[i][j]);
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|           }
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|         }
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|       }
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|     }
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|   }
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| #endif  // EIGEN_HAS_C99_MATH
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| 
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|   // Check the ndtri function against scipy.special.ndtri
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|   {
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|     ArrayType x(7), res(7), ref(7);
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|     x << 0.5, 0.2, 0.8, 0.9, 0.1, 0.99, 0.01;
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|     ref << 0., -0.8416212335729142, 0.8416212335729142, 1.2815515655446004,
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|         -1.2815515655446004, 2.3263478740408408, -2.3263478740408408;
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|     CALL_SUBTEST(verify_component_wise(ref, ref););
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|     CALL_SUBTEST(res = x.ndtri(); verify_component_wise(res, ref););
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|     CALL_SUBTEST(res = ndtri(x); verify_component_wise(res, ref););
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| 
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|     // ndtri(normal_cdf(x)) ~= x
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|     CALL_SUBTEST(ArrayType m1 = ArrayType::Random(32); using std::sqrt;
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| 
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|                  ArrayType cdf_val = (m1 / Scalar(sqrt(2.))).erf();
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|                  cdf_val = (cdf_val + Scalar(1)) / Scalar(2);
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|                  verify_component_wise(cdf_val.ndtri(), m1););
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|   }
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| 
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|   // Check the zeta function against scipy.special.zeta
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|   {
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|     ArrayType x(10), q(10), res(10), ref(10);
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|     x << 1.5, 4, 10.5, 10000.5, 3, 1, 0.9, 2, 3, 4;
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|     q << 2, 1.5, 3, 1.0001, -2.5, 1.2345, 1.2345, -1, -2, -3;
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|     ref << 1.61237534869, 0.234848505667, 1.03086757337e-5, 0.367879440865,
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|         0.054102025820864097, plusinf, nan, plusinf, nan, plusinf;
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|     CALL_SUBTEST(verify_component_wise(ref, ref););
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|     CALL_SUBTEST(res = x.zeta(q); verify_component_wise(res, ref););
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|     CALL_SUBTEST(res = zeta(x, q); verify_component_wise(res, ref););
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|   }
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| 
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|   // digamma
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|   {
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|     ArrayType x(9), res(9), ref(9);
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|     x << 1, 1.5, 4, -10.5, 10000.5, 0, -1, -2, -3;
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|     ref << -0.5772156649015329, 0.03648997397857645, 1.2561176684318,
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|         2.398239129535781, 9.210340372392849, nan, nan, nan, nan;
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|     CALL_SUBTEST(verify_component_wise(ref, ref););
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| 
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|     CALL_SUBTEST(res = x.digamma(); verify_component_wise(res, ref););
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|     CALL_SUBTEST(res = digamma(x); verify_component_wise(res, ref););
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|   }
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| 
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| #if EIGEN_HAS_C99_MATH
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|   {
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|     ArrayType n(16), x(16), res(16), ref(16);
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|     n << 1, 1, 1, 1.5, 17, 31, 28, 8, 42, 147, 170, -1, 0, 1, 2, 3;
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|     x << 2, 3, 25.5, 1.5, 4.7, 11.8, 17.7, 30.2, 15.8, 54.1, 64, -1, -2, -3, -4,
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|         -5;
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|     ref << 0.644934066848, 0.394934066848, 0.0399946696496, nan, 293.334565435,
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|         0.445487887616, -2.47810300902e-07, -8.29668781082e-09, -0.434562276666,
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|         0.567742190178, -0.0108615497927, nan, nan, plusinf, nan, plusinf;
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|     CALL_SUBTEST(verify_component_wise(ref, ref););
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| 
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|     if (sizeof(RealScalar) >= 8) {  // double
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|       // Reason for commented line:
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|       // http://eigen.tuxfamily.org/bz/show_bug.cgi?id=1232
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|       //       CALL_SUBTEST( res = x.polygamma(n); verify_component_wise(res,
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|       //       ref); );
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|       CALL_SUBTEST(res = polygamma(n, x); verify_component_wise(res, ref););
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|     } else {
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|       //       CALL_SUBTEST( res = x.polygamma(n);
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|       //       verify_component_wise(res.head(8), ref.head(8)); );
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|       CALL_SUBTEST(res = polygamma(n, x);
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|                    verify_component_wise(res.head(8), ref.head(8)););
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|     }
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|   }
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| #endif
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| 
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| #if EIGEN_HAS_C99_MATH
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|   {
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|     // Inputs and ground truth generated with scipy via:
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|     //   a = np.logspace(-3, 3, 5) - 1e-3
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|     //   b = np.logspace(-3, 3, 5) - 1e-3
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|     //   x = np.linspace(-0.1, 1.1, 5)
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|     //   (full_a, full_b, full_x) = np.vectorize(lambda a, b, x: (a, b,
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|     //   x))(*np.ix_(a, b, x))
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|     //   full_a = full_a.flatten().tolist()  # same for full_b, full_x
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|     //   v = scipy.special.betainc(full_a, full_b, full_x).flatten().tolist()
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|     //
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|     // Note in Eigen, we call betainc with arguments in the order (x, a, b).
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|     ArrayType a(125);
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|     ArrayType b(125);
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|     ArrayType x(125);
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|     ArrayType v(125);
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|     ArrayType res(125);
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| 
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|     a << 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
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|         0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
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|         0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
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|         0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
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|         0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
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|         0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
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|         0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
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|         0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
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|         0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
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|         0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
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|         0.03062277660168379, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999,
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|         0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999,
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|         0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999,
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|         31.62177660168379, 31.62177660168379, 31.62177660168379,
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|         31.62177660168379, 31.62177660168379, 31.62177660168379,
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|         31.62177660168379, 31.62177660168379, 31.62177660168379,
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|         31.62177660168379, 31.62177660168379, 31.62177660168379,
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|         31.62177660168379, 31.62177660168379, 31.62177660168379,
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|         31.62177660168379, 31.62177660168379, 31.62177660168379,
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|         31.62177660168379, 31.62177660168379, 31.62177660168379,
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|         31.62177660168379, 31.62177660168379, 31.62177660168379,
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|         31.62177660168379, 999.999, 999.999, 999.999, 999.999, 999.999, 999.999,
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|         999.999, 999.999, 999.999, 999.999, 999.999, 999.999, 999.999, 999.999,
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|         999.999, 999.999, 999.999, 999.999, 999.999, 999.999, 999.999, 999.999,
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|         999.999, 999.999, 999.999;
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| 
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|     b << 0.0, 0.0, 0.0, 0.0, 0.0, 0.03062277660168379, 0.03062277660168379,
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|         0.03062277660168379, 0.03062277660168379, 0.03062277660168379, 0.999,
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|         0.999, 0.999, 0.999, 0.999, 31.62177660168379, 31.62177660168379,
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|         31.62177660168379, 31.62177660168379, 31.62177660168379, 999.999,
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|         999.999, 999.999, 999.999, 999.999, 0.0, 0.0, 0.0, 0.0, 0.0,
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|         0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
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|         0.03062277660168379, 0.03062277660168379, 0.999, 0.999, 0.999, 0.999,
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|         0.999, 31.62177660168379, 31.62177660168379, 31.62177660168379,
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|         31.62177660168379, 31.62177660168379, 999.999, 999.999, 999.999,
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|         999.999, 999.999, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03062277660168379,
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|         0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
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|         0.03062277660168379, 0.999, 0.999, 0.999, 0.999, 0.999,
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|         31.62177660168379, 31.62177660168379, 31.62177660168379,
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|         31.62177660168379, 31.62177660168379, 999.999, 999.999, 999.999,
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|         999.999, 999.999, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03062277660168379,
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|         0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
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|         0.03062277660168379, 0.999, 0.999, 0.999, 0.999, 0.999,
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|         31.62177660168379, 31.62177660168379, 31.62177660168379,
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|         31.62177660168379, 31.62177660168379, 999.999, 999.999, 999.999,
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|         999.999, 999.999, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03062277660168379,
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|         0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
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|         0.03062277660168379, 0.999, 0.999, 0.999, 0.999, 0.999,
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|         31.62177660168379, 31.62177660168379, 31.62177660168379,
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|         31.62177660168379, 31.62177660168379, 999.999, 999.999, 999.999,
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|         999.999, 999.999;
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| 
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|     x << -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5,
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|         0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2,
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|         0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1,
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|         0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1,
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|         -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8,
 | |
|         1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5,
 | |
|         0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2,
 | |
|         0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1,
 | |
|         0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1;
 | |
| 
 | |
|     v << nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,
 | |
|         nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,
 | |
|         nan, nan, nan, 0.47972119876364683, 0.5, 0.5202788012363533, nan, nan,
 | |
|         0.9518683957740043, 0.9789663010413743, 0.9931729188073435, nan, nan,
 | |
|         0.999995949033062, 0.9999999999993698, 0.9999999999999999, nan, nan,
 | |
|         0.9999999999999999, 0.9999999999999999, 0.9999999999999999, nan, nan,
 | |
|         nan, nan, nan, nan, nan, 0.006827081192655869, 0.0210336989586256,
 | |
|         0.04813160422599567, nan, nan, 0.20014344256217678, 0.5000000000000001,
 | |
|         0.7998565574378232, nan, nan, 0.9991401428435834, 0.999999999698403,
 | |
|         0.9999999999999999, nan, nan, 0.9999999999999999, 0.9999999999999999,
 | |
|         0.9999999999999999, nan, nan, nan, nan, nan, nan, nan,
 | |
|         1.0646600232370887e-25, 6.301722877826246e-13, 4.050966937974938e-06,
 | |
|         nan, nan, 7.864342668429763e-23, 3.015969667594166e-10,
 | |
|         0.0008598571564165444, nan, nan, 6.031987710123844e-08,
 | |
|         0.5000000000000007, 0.9999999396801229, nan, nan, 0.9999999999999999,
 | |
|         0.9999999999999999, 0.9999999999999999, nan, nan, nan, nan, nan, nan,
 | |
|         nan, 0.0, 7.029920380986636e-306, 2.2450728208591345e-101, nan, nan,
 | |
|         0.0, 9.275871147869727e-302, 1.2232913026152827e-97, nan, nan, 0.0,
 | |
|         3.0891393081932924e-252, 2.9303043666183996e-60, nan, nan,
 | |
|         2.248913486879199e-196, 0.5000000000004947, 0.9999999999999999, nan;
 | |
| 
 | |
|     CALL_SUBTEST(res = betainc(a, b, x); verify_component_wise(res, v););
 | |
|   }
 | |
| 
 | |
|   // Test various properties of betainc
 | |
|   {
 | |
|     ArrayType m1 = ArrayType::Random(32);
 | |
|     ArrayType m2 = ArrayType::Random(32);
 | |
|     ArrayType m3 = ArrayType::Random(32);
 | |
|     ArrayType one = ArrayType::Constant(32, Scalar(1.0));
 | |
|     const Scalar eps = std::numeric_limits<Scalar>::epsilon();
 | |
|     ArrayType a = (m1 * Scalar(4)).exp();
 | |
|     ArrayType b = (m2 * Scalar(4)).exp();
 | |
|     ArrayType x = m3.abs();
 | |
| 
 | |
|     // betainc(a, 1, x) == x**a
 | |
|     CALL_SUBTEST(ArrayType test = betainc(a, one, x);
 | |
|                  ArrayType expected = x.pow(a);
 | |
|                  verify_component_wise(test, expected););
 | |
| 
 | |
|     // betainc(1, b, x) == 1 - (1 - x)**b
 | |
|     CALL_SUBTEST(ArrayType test = betainc(one, b, x);
 | |
|                  ArrayType expected = one - (one - x).pow(b);
 | |
|                  verify_component_wise(test, expected););
 | |
| 
 | |
|     // betainc(a, b, x) == 1 - betainc(b, a, 1-x)
 | |
|     CALL_SUBTEST(ArrayType test = betainc(a, b, x) + betainc(b, a, one - x);
 | |
|                  ArrayType expected = one;
 | |
|                  verify_component_wise(test, expected););
 | |
| 
 | |
|     // betainc(a+1, b, x) = betainc(a, b, x) - x**a * (1 - x)**b / (a * beta(a,
 | |
|     // b))
 | |
|     CALL_SUBTEST(
 | |
|         ArrayType num = x.pow(a) * (one - x).pow(b);
 | |
|         ArrayType denom =
 | |
|             a * (a.lgamma() + b.lgamma() - (a + b).lgamma()).exp();
 | |
|         // Add eps to rhs and lhs so that component-wise test doesn't result in
 | |
|         // nans when both outputs are zeros.
 | |
|         ArrayType expected = betainc(a, b, x) - num / denom + eps;
 | |
|         ArrayType test = betainc(a + one, b, x) + eps;
 | |
|         if (sizeof(Scalar) >= 8) {  // double
 | |
|           verify_component_wise(test, expected);
 | |
|         } else {
 | |
|           // Reason for limited test:
 | |
|           // http://eigen.tuxfamily.org/bz/show_bug.cgi?id=1232
 | |
|           verify_component_wise(test.head(8), expected.head(8));
 | |
|         });
 | |
| 
 | |
|     // betainc(a, b+1, x) = betainc(a, b, x) + x**a * (1 - x)**b / (b * beta(a,
 | |
|     // b))
 | |
|     CALL_SUBTEST(
 | |
|         // Add eps to rhs and lhs so that component-wise test doesn't result in
 | |
|         // nans when both outputs are zeros.
 | |
|         ArrayType num = x.pow(a) * (one - x).pow(b);
 | |
|         ArrayType denom =
 | |
|             b * (a.lgamma() + b.lgamma() - (a + b).lgamma()).exp();
 | |
|         ArrayType expected = betainc(a, b, x) + num / denom + eps;
 | |
|         ArrayType test = betainc(a, b + one, x) + eps;
 | |
|         verify_component_wise(test, expected););
 | |
|   }
 | |
| #endif  // EIGEN_HAS_C99_MATH
 | |
| 
 | |
| /* Code to generate the data for the following two test cases.
 | |
| N = 5
 | |
| np.random.seed(3)
 | |
| 
 | |
| a = np.logspace(-2, 3, 6)
 | |
| a = np.ravel(np.tile(np.reshape(a, [-1, 1]), [1, N]))
 | |
| x = np.random.gamma(a, 1.0)
 | |
| x = np.maximum(x, np.finfo(np.float32).tiny)
 | |
| 
 | |
| def igamma(a, x):
 | |
|   return mpmath.gammainc(a, 0, x, regularized=True)
 | |
| 
 | |
| def igamma_der_a(a, x):
 | |
|   res = mpmath.diff(lambda a_prime: igamma(a_prime, x), a)
 | |
|   return np.float64(res)
 | |
| 
 | |
| def gamma_sample_der_alpha(a, x):
 | |
|   igamma_x = igamma(a, x)
 | |
|   def igammainv_of_igamma(a_prime):
 | |
|     return mpmath.findroot(lambda x_prime: igamma(a_prime, x_prime) -
 | |
|         igamma_x, x, solver='newton')
 | |
|   return np.float64(mpmath.diff(igammainv_of_igamma, a))
 | |
| 
 | |
| v_igamma_der_a = np.vectorize(igamma_der_a)(a, x)
 | |
| v_gamma_sample_der_alpha = np.vectorize(gamma_sample_der_alpha)(a, x)
 | |
| */
 | |
| 
 | |
| #if EIGEN_HAS_C99_MATH
 | |
|   // Test igamma_der_a
 | |
|   {
 | |
|     ArrayType a(30);
 | |
|     ArrayType x(30);
 | |
|     ArrayType res(30);
 | |
|     ArrayType v(30);
 | |
| 
 | |
|     a << 0.01, 0.01, 0.01, 0.01, 0.01, 0.1, 0.1, 0.1, 0.1, 0.1, 1.0, 1.0, 1.0,
 | |
|         1.0, 1.0, 10.0, 10.0, 10.0, 10.0, 10.0, 100.0, 100.0, 100.0, 100.0,
 | |
|         100.0, 1000.0, 1000.0, 1000.0, 1000.0, 1000.0;
 | |
| 
 | |
|     x << 1.25668890405e-26, 1.17549435082e-38, 1.20938905072e-05,
 | |
|         1.17549435082e-38, 1.17549435082e-38, 5.66572070696e-16,
 | |
|         0.0132865061065, 0.0200034203853, 6.29263709118e-17, 1.37160367764e-06,
 | |
|         0.333412038288, 1.18135687766, 0.580629033777, 0.170631439426,
 | |
|         0.786686768458, 7.63873279537, 13.1944344379, 11.896042354,
 | |
|         10.5830172417, 10.5020942233, 92.8918587747, 95.003720371,
 | |
|         86.3715926467, 96.0330217672, 82.6389930677, 968.702906754,
 | |
|         969.463546828, 1001.79726022, 955.047416547, 1044.27458568;
 | |
| 
 | |
|     v << -32.7256441441, -36.4394150514, -9.66467612263, -36.4394150514,
 | |
|         -36.4394150514, -1.0891900302, -2.66351229645, -2.48666868596,
 | |
|         -0.929700494428, -3.56327722764, -0.455320135314, -0.391437214323,
 | |
|         -0.491352055991, -0.350454834292, -0.471773162921, -0.104084440522,
 | |
|         -0.0723646747909, -0.0992828975532, -0.121638215446, -0.122619605294,
 | |
|         -0.0317670267286, -0.0359974812869, -0.0154359225363, -0.0375775365921,
 | |
|         -0.00794899153653, -0.00777303219211, -0.00796085782042,
 | |
|         -0.0125850719397, -0.00455500206958, -0.00476436993148;
 | |
| 
 | |
|     CALL_SUBTEST(res = igamma_der_a(a, x); verify_component_wise(res, v););
 | |
|   }
 | |
| 
 | |
|   // Test gamma_sample_der_alpha
 | |
|   {
 | |
|     ArrayType alpha(30);
 | |
|     ArrayType sample(30);
 | |
|     ArrayType res(30);
 | |
|     ArrayType v(30);
 | |
| 
 | |
|     alpha << 0.01, 0.01, 0.01, 0.01, 0.01, 0.1, 0.1, 0.1, 0.1, 0.1, 1.0, 1.0,
 | |
|         1.0, 1.0, 1.0, 10.0, 10.0, 10.0, 10.0, 10.0, 100.0, 100.0, 100.0, 100.0,
 | |
|         100.0, 1000.0, 1000.0, 1000.0, 1000.0, 1000.0;
 | |
| 
 | |
|     sample << 1.25668890405e-26, 1.17549435082e-38, 1.20938905072e-05,
 | |
|         1.17549435082e-38, 1.17549435082e-38, 5.66572070696e-16,
 | |
|         0.0132865061065, 0.0200034203853, 6.29263709118e-17, 1.37160367764e-06,
 | |
|         0.333412038288, 1.18135687766, 0.580629033777, 0.170631439426,
 | |
|         0.786686768458, 7.63873279537, 13.1944344379, 11.896042354,
 | |
|         10.5830172417, 10.5020942233, 92.8918587747, 95.003720371,
 | |
|         86.3715926467, 96.0330217672, 82.6389930677, 968.702906754,
 | |
|         969.463546828, 1001.79726022, 955.047416547, 1044.27458568;
 | |
| 
 | |
|     v << 7.42424742367e-23, 1.02004297287e-34, 0.0130155240738,
 | |
|         1.02004297287e-34, 1.02004297287e-34, 1.96505168277e-13, 0.525575786243,
 | |
|         0.713903991771, 2.32077561808e-14, 0.000179348049886, 0.635500453302,
 | |
|         1.27561284917, 0.878125852156, 0.41565819538, 1.03606488534,
 | |
|         0.885964824887, 1.16424049334, 1.10764479598, 1.04590810812,
 | |
|         1.04193666963, 0.965193152414, 0.976217589464, 0.93008035061,
 | |
|         0.98153216096, 0.909196397698, 0.98434963993, 0.984738050206,
 | |
|         1.00106492525, 0.97734200649, 1.02198794179;
 | |
| 
 | |
|     CALL_SUBTEST(res = gamma_sample_der_alpha(alpha, sample);
 | |
|                  verify_component_wise(res, v););
 | |
|   }
 | |
| #endif  // EIGEN_HAS_C99_MATH
 | |
| }
 | |
| 
 | |
| EIGEN_DECLARE_TEST(special_functions) {
 | |
|   CALL_SUBTEST_1(array_special_functions<ArrayXf>());
 | |
|   CALL_SUBTEST_2(array_special_functions<ArrayXd>());
 | |
|   // TODO(cantonios): half/bfloat16 don't have enough precision to reproduce
 | |
|   // results above.
 | |
|   // CALL_SUBTEST_3(array_special_functions<ArrayX<Eigen::half>>());
 | |
|   // CALL_SUBTEST_4(array_special_functions<ArrayX<Eigen::bfloat16>>());
 | |
| }
 | 
