1 // This file is part of Eigen, a lightweight C++ template library 2 // for linear algebra. 3 // 4 // Copyright (C) 2009 Gael Guennebaud <gael.guennebaud (at) inria.fr> 5 // 6 // This Source Code Form is subject to the terms of the Mozilla 7 // Public License v. 2.0. If a copy of the MPL was not distributed 8 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. 9 10 #include "main.h" 11 12 template<typename T> bool isNotNaN(const T& x) 13 { 14 return x==x; 15 } 16 17 // workaround aggressive optimization in ICC 18 template<typename T> EIGEN_DONT_INLINE T sub(T a, T b) { return a - b; } 19 20 template<typename T> bool isFinite(const T& x) 21 { 22 return isNotNaN(sub(x,x)); 23 } 24 25 template<typename T> EIGEN_DONT_INLINE T copy(const T& x) 26 { 27 return x; 28 } 29 30 template<typename MatrixType> void stable_norm(const MatrixType& m) 31 { 32 /* this test covers the following files: 33 StableNorm.h 34 */ 35 typedef typename MatrixType::Index Index; 36 typedef typename MatrixType::Scalar Scalar; 37 typedef typename NumTraits<Scalar>::Real RealScalar; 38 39 // Check the basic machine-dependent constants. 40 { 41 int ibeta, it, iemin, iemax; 42 43 ibeta = std::numeric_limits<RealScalar>::radix; // base for floating-point numbers 44 it = std::numeric_limits<RealScalar>::digits; // number of base-beta digits in mantissa 45 iemin = std::numeric_limits<RealScalar>::min_exponent; // minimum exponent 46 iemax = std::numeric_limits<RealScalar>::max_exponent; // maximum exponent 47 48 VERIFY( (!(iemin > 1 - 2*it || 1+it>iemax || (it==2 && ibeta<5) || (it<=4 && ibeta <= 3 ) || it<2)) 49 && "the stable norm algorithm cannot be guaranteed on this computer"); 50 } 51 52 53 Index rows = m.rows(); 54 Index cols = m.cols(); 55 56 Scalar big = internal::random<Scalar>() * ((std::numeric_limits<RealScalar>::max)() * RealScalar(1e-4)); 57 Scalar small = internal::random<Scalar>() * ((std::numeric_limits<RealScalar>::min)() * RealScalar(1e4)); 58 59 MatrixType vzero = MatrixType::Zero(rows, cols), 60 vrand = MatrixType::Random(rows, cols), 61 vbig(rows, cols), 62 vsmall(rows,cols); 63 64 vbig.fill(big); 65 vsmall.fill(small); 66 67 VERIFY_IS_MUCH_SMALLER_THAN(vzero.norm(), static_cast<RealScalar>(1)); 68 VERIFY_IS_APPROX(vrand.stableNorm(), vrand.norm()); 69 VERIFY_IS_APPROX(vrand.blueNorm(), vrand.norm()); 70 VERIFY_IS_APPROX(vrand.hypotNorm(), vrand.norm()); 71 72 RealScalar size = static_cast<RealScalar>(m.size()); 73 74 // test isFinite 75 VERIFY(!isFinite( std::numeric_limits<RealScalar>::infinity())); 76 VERIFY(!isFinite(internal::sqrt(-internal::abs(big)))); 77 78 // test overflow 79 VERIFY(isFinite(internal::sqrt(size)*internal::abs(big))); 80 VERIFY_IS_NOT_APPROX(internal::sqrt(copy(vbig.squaredNorm())), internal::abs(internal::sqrt(size)*big)); // here the default norm must fail 81 VERIFY_IS_APPROX(vbig.stableNorm(), internal::sqrt(size)*internal::abs(big)); 82 VERIFY_IS_APPROX(vbig.blueNorm(), internal::sqrt(size)*internal::abs(big)); 83 VERIFY_IS_APPROX(vbig.hypotNorm(), internal::sqrt(size)*internal::abs(big)); 84 85 // test underflow 86 VERIFY(isFinite(internal::sqrt(size)*internal::abs(small))); 87 VERIFY_IS_NOT_APPROX(internal::sqrt(copy(vsmall.squaredNorm())), internal::abs(internal::sqrt(size)*small)); // here the default norm must fail 88 VERIFY_IS_APPROX(vsmall.stableNorm(), internal::sqrt(size)*internal::abs(small)); 89 VERIFY_IS_APPROX(vsmall.blueNorm(), internal::sqrt(size)*internal::abs(small)); 90 VERIFY_IS_APPROX(vsmall.hypotNorm(), internal::sqrt(size)*internal::abs(small)); 91 92 // Test compilation of cwise() version 93 VERIFY_IS_APPROX(vrand.colwise().stableNorm(), vrand.colwise().norm()); 94 VERIFY_IS_APPROX(vrand.colwise().blueNorm(), vrand.colwise().norm()); 95 VERIFY_IS_APPROX(vrand.colwise().hypotNorm(), vrand.colwise().norm()); 96 VERIFY_IS_APPROX(vrand.rowwise().stableNorm(), vrand.rowwise().norm()); 97 VERIFY_IS_APPROX(vrand.rowwise().blueNorm(), vrand.rowwise().norm()); 98 VERIFY_IS_APPROX(vrand.rowwise().hypotNorm(), vrand.rowwise().norm()); 99 } 100 101 void test_stable_norm() 102 { 103 for(int i = 0; i < g_repeat; i++) { 104 CALL_SUBTEST_1( stable_norm(Matrix<float, 1, 1>()) ); 105 CALL_SUBTEST_2( stable_norm(Vector4d()) ); 106 CALL_SUBTEST_3( stable_norm(VectorXd(internal::random<int>(10,2000))) ); 107 CALL_SUBTEST_4( stable_norm(VectorXf(internal::random<int>(10,2000))) ); 108 CALL_SUBTEST_5( stable_norm(VectorXcd(internal::random<int>(10,2000))) ); 109 } 110 } 111
