1 // This file is part of Eigen, a lightweight C++ template library 2 // for linear algebra. 3 // 4 // Copyright (C) 2008-2009 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 MatrixType> void array_for_matrix(const MatrixType& m) 13 { 14 typedef typename MatrixType::Index Index; 15 typedef typename MatrixType::Scalar Scalar; 16 typedef typename NumTraits<Scalar>::Real RealScalar; 17 typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> ColVectorType; 18 typedef Matrix<Scalar, 1, MatrixType::ColsAtCompileTime> RowVectorType; 19 20 Index rows = m.rows(); 21 Index cols = m.cols(); 22 23 MatrixType m1 = MatrixType::Random(rows, cols), 24 m2 = MatrixType::Random(rows, cols), 25 m3(rows, cols); 26 27 ColVectorType cv1 = ColVectorType::Random(rows); 28 RowVectorType rv1 = RowVectorType::Random(cols); 29 30 Scalar s1 = internal::random<Scalar>(), 31 s2 = internal::random<Scalar>(); 32 33 // scalar addition 34 VERIFY_IS_APPROX(m1.array() + s1, s1 + m1.array()); 35 VERIFY_IS_APPROX((m1.array() + s1).matrix(), MatrixType::Constant(rows,cols,s1) + m1); 36 VERIFY_IS_APPROX(((m1*Scalar(2)).array() - s2).matrix(), (m1+m1) - MatrixType::Constant(rows,cols,s2) ); 37 m3 = m1; 38 m3.array() += s2; 39 VERIFY_IS_APPROX(m3, (m1.array() + s2).matrix()); 40 m3 = m1; 41 m3.array() -= s1; 42 VERIFY_IS_APPROX(m3, (m1.array() - s1).matrix()); 43 44 // reductions 45 VERIFY_IS_MUCH_SMALLER_THAN(m1.colwise().sum().sum() - m1.sum(), m1.cwiseAbs().maxCoeff()); 46 VERIFY_IS_MUCH_SMALLER_THAN(m1.rowwise().sum().sum() - m1.sum(), m1.cwiseAbs().maxCoeff()); 47 VERIFY_IS_MUCH_SMALLER_THAN(m1.colwise().sum() + m2.colwise().sum() - (m1+m2).colwise().sum(), (m1+m2).cwiseAbs().maxCoeff()); 48 VERIFY_IS_MUCH_SMALLER_THAN(m1.rowwise().sum() - m2.rowwise().sum() - (m1-m2).rowwise().sum(), (m1-m2).cwiseAbs().maxCoeff()); 49 VERIFY_IS_APPROX(m1.colwise().sum(), m1.colwise().redux(internal::scalar_sum_op<Scalar>())); 50 51 // vector-wise ops 52 m3 = m1; 53 VERIFY_IS_APPROX(m3.colwise() += cv1, m1.colwise() + cv1); 54 m3 = m1; 55 VERIFY_IS_APPROX(m3.colwise() -= cv1, m1.colwise() - cv1); 56 m3 = m1; 57 VERIFY_IS_APPROX(m3.rowwise() += rv1, m1.rowwise() + rv1); 58 m3 = m1; 59 VERIFY_IS_APPROX(m3.rowwise() -= rv1, m1.rowwise() - rv1); 60 61 // empty objects 62 VERIFY_IS_APPROX(m1.block(0,0,0,cols).colwise().sum(), RowVectorType::Zero(cols)); 63 VERIFY_IS_APPROX(m1.block(0,0,rows,0).rowwise().prod(), ColVectorType::Ones(rows)); 64 65 // verify the const accessors exist 66 const Scalar& ref_m1 = m.matrix().array().coeffRef(0); 67 const Scalar& ref_m2 = m.matrix().array().coeffRef(0,0); 68 const Scalar& ref_a1 = m.array().matrix().coeffRef(0); 69 const Scalar& ref_a2 = m.array().matrix().coeffRef(0,0); 70 VERIFY(&ref_a1 == &ref_m1); 71 VERIFY(&ref_a2 == &ref_m2); 72 } 73 74 template<typename MatrixType> void comparisons(const MatrixType& m) 75 { 76 typedef typename MatrixType::Index Index; 77 typedef typename MatrixType::Scalar Scalar; 78 typedef typename NumTraits<Scalar>::Real RealScalar; 79 typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType; 80 81 Index rows = m.rows(); 82 Index cols = m.cols(); 83 84 Index r = internal::random<Index>(0, rows-1), 85 c = internal::random<Index>(0, cols-1); 86 87 MatrixType m1 = MatrixType::Random(rows, cols), 88 m2 = MatrixType::Random(rows, cols), 89 m3(rows, cols); 90 91 VERIFY(((m1.array() + Scalar(1)) > m1.array()).all()); 92 VERIFY(((m1.array() - Scalar(1)) < m1.array()).all()); 93 if (rows*cols>1) 94 { 95 m3 = m1; 96 m3(r,c) += 1; 97 VERIFY(! (m1.array() < m3.array()).all() ); 98 VERIFY(! (m1.array() > m3.array()).all() ); 99 } 100 101 // comparisons to scalar 102 VERIFY( (m1.array() != (m1(r,c)+1) ).any() ); 103 VERIFY( (m1.array() > (m1(r,c)-1) ).any() ); 104 VERIFY( (m1.array() < (m1(r,c)+1) ).any() ); 105 VERIFY( (m1.array() == m1(r,c) ).any() ); 106 107 // test Select 108 VERIFY_IS_APPROX( (m1.array()<m2.array()).select(m1,m2), m1.cwiseMin(m2) ); 109 VERIFY_IS_APPROX( (m1.array()>m2.array()).select(m1,m2), m1.cwiseMax(m2) ); 110 Scalar mid = (m1.cwiseAbs().minCoeff() + m1.cwiseAbs().maxCoeff())/Scalar(2); 111 for (int j=0; j<cols; ++j) 112 for (int i=0; i<rows; ++i) 113 m3(i,j) = internal::abs(m1(i,j))<mid ? 0 : m1(i,j); 114 VERIFY_IS_APPROX( (m1.array().abs()<MatrixType::Constant(rows,cols,mid).array()) 115 .select(MatrixType::Zero(rows,cols),m1), m3); 116 // shorter versions: 117 VERIFY_IS_APPROX( (m1.array().abs()<MatrixType::Constant(rows,cols,mid).array()) 118 .select(0,m1), m3); 119 VERIFY_IS_APPROX( (m1.array().abs()>=MatrixType::Constant(rows,cols,mid).array()) 120 .select(m1,0), m3); 121 // even shorter version: 122 VERIFY_IS_APPROX( (m1.array().abs()<mid).select(0,m1), m3); 123 124 // count 125 VERIFY(((m1.array().abs()+1)>RealScalar(0.1)).count() == rows*cols); 126 127 typedef Matrix<typename MatrixType::Index, Dynamic, 1> VectorOfIndices; 128 129 // TODO allows colwise/rowwise for array 130 VERIFY_IS_APPROX(((m1.array().abs()+1)>RealScalar(0.1)).matrix().colwise().count(), VectorOfIndices::Constant(cols,rows).transpose()); 131 VERIFY_IS_APPROX(((m1.array().abs()+1)>RealScalar(0.1)).matrix().rowwise().count(), VectorOfIndices::Constant(rows, cols)); 132 } 133 134 template<typename VectorType> void lpNorm(const VectorType& v) 135 { 136 VectorType u = VectorType::Random(v.size()); 137 138 VERIFY_IS_APPROX(u.template lpNorm<Infinity>(), u.cwiseAbs().maxCoeff()); 139 VERIFY_IS_APPROX(u.template lpNorm<1>(), u.cwiseAbs().sum()); 140 VERIFY_IS_APPROX(u.template lpNorm<2>(), internal::sqrt(u.array().abs().square().sum())); 141 VERIFY_IS_APPROX(internal::pow(u.template lpNorm<5>(), typename VectorType::RealScalar(5)), u.array().abs().pow(5).sum()); 142 } 143 144 template<typename MatrixType> void cwise_min_max(const MatrixType& m) 145 { 146 typedef typename MatrixType::Index Index; 147 typedef typename MatrixType::Scalar Scalar; 148 149 Index rows = m.rows(); 150 Index cols = m.cols(); 151 152 MatrixType m1 = MatrixType::Random(rows, cols); 153 154 // min/max with array 155 Scalar maxM1 = m1.maxCoeff(); 156 Scalar minM1 = m1.minCoeff(); 157 158 VERIFY_IS_APPROX(MatrixType::Constant(rows,cols, minM1), m1.cwiseMin(MatrixType::Constant(rows,cols, minM1))); 159 VERIFY_IS_APPROX(m1, m1.cwiseMin(MatrixType::Constant(rows,cols, maxM1))); 160 161 VERIFY_IS_APPROX(MatrixType::Constant(rows,cols, maxM1), m1.cwiseMax(MatrixType::Constant(rows,cols, maxM1))); 162 VERIFY_IS_APPROX(m1, m1.cwiseMax(MatrixType::Constant(rows,cols, minM1))); 163 164 // min/max with scalar input 165 VERIFY_IS_APPROX(MatrixType::Constant(rows,cols, minM1), m1.cwiseMin( minM1)); 166 VERIFY_IS_APPROX(m1, m1.cwiseMin( maxM1)); 167 168 VERIFY_IS_APPROX(MatrixType::Constant(rows,cols, maxM1), m1.cwiseMax( maxM1)); 169 VERIFY_IS_APPROX(m1, m1.cwiseMax( minM1)); 170 171 } 172 173 void test_array_for_matrix() 174 { 175 for(int i = 0; i < g_repeat; i++) { 176 CALL_SUBTEST_1( array_for_matrix(Matrix<float, 1, 1>()) ); 177 CALL_SUBTEST_2( array_for_matrix(Matrix2f()) ); 178 CALL_SUBTEST_3( array_for_matrix(Matrix4d()) ); 179 CALL_SUBTEST_4( array_for_matrix(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); 180 CALL_SUBTEST_5( array_for_matrix(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); 181 CALL_SUBTEST_6( array_for_matrix(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); 182 } 183 for(int i = 0; i < g_repeat; i++) { 184 CALL_SUBTEST_1( comparisons(Matrix<float, 1, 1>()) ); 185 CALL_SUBTEST_2( comparisons(Matrix2f()) ); 186 CALL_SUBTEST_3( comparisons(Matrix4d()) ); 187 CALL_SUBTEST_5( comparisons(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); 188 CALL_SUBTEST_6( comparisons(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); 189 } 190 for(int i = 0; i < g_repeat; i++) { 191 CALL_SUBTEST_1( cwise_min_max(Matrix<float, 1, 1>()) ); 192 CALL_SUBTEST_2( cwise_min_max(Matrix2f()) ); 193 CALL_SUBTEST_3( cwise_min_max(Matrix4d()) ); 194 CALL_SUBTEST_5( cwise_min_max(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); 195 CALL_SUBTEST_6( cwise_min_max(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); 196 } 197 for(int i = 0; i < g_repeat; i++) { 198 CALL_SUBTEST_1( lpNorm(Matrix<float, 1, 1>()) ); 199 CALL_SUBTEST_2( lpNorm(Vector2f()) ); 200 CALL_SUBTEST_7( lpNorm(Vector3d()) ); 201 CALL_SUBTEST_8( lpNorm(Vector4f()) ); 202 CALL_SUBTEST_5( lpNorm(VectorXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); 203 CALL_SUBTEST_4( lpNorm(VectorXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); 204 } 205 } 206
