1 // This file is part of Eigen, a lightweight C++ template library 2 // for linear algebra. Eigen itself is part of the KDE project. 3 // 4 // Copyright (C) 2008 Gael Guennebaud <g.gael (at) free.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 #include <Eigen/Array> 12 13 template<typename MatrixType> void array(const MatrixType& m) 14 { 15 /* this test covers the following files: 16 Array.cpp 17 */ 18 19 typedef typename MatrixType::Scalar Scalar; 20 typedef typename NumTraits<Scalar>::Real RealScalar; 21 typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType; 22 23 int rows = m.rows(); 24 int cols = m.cols(); 25 26 MatrixType m1 = MatrixType::Random(rows, cols), 27 m2 = MatrixType::Random(rows, cols), 28 m3(rows, cols); 29 30 Scalar s1 = ei_random<Scalar>(), 31 s2 = ei_random<Scalar>(); 32 33 // scalar addition 34 VERIFY_IS_APPROX(m1.cwise() + s1, s1 + m1.cwise()); 35 VERIFY_IS_APPROX(m1.cwise() + s1, MatrixType::Constant(rows,cols,s1) + m1); 36 VERIFY_IS_APPROX((m1*Scalar(2)).cwise() - s2, (m1+m1) - MatrixType::Constant(rows,cols,s2) ); 37 m3 = m1; 38 m3.cwise() += s2; 39 VERIFY_IS_APPROX(m3, m1.cwise() + s2); 40 m3 = m1; 41 m3.cwise() -= s1; 42 VERIFY_IS_APPROX(m3, m1.cwise() - s1); 43 44 // reductions 45 VERIFY_IS_APPROX(m1.colwise().sum().sum(), m1.sum()); 46 VERIFY_IS_APPROX(m1.rowwise().sum().sum(), m1.sum()); 47 if (!ei_isApprox(m1.sum(), (m1+m2).sum())) 48 VERIFY_IS_NOT_APPROX(((m1+m2).rowwise().sum()).sum(), m1.sum()); 49 VERIFY_IS_APPROX(m1.colwise().sum(), m1.colwise().redux(internal::scalar_sum_op<Scalar>())); 50 } 51 52 template<typename MatrixType> void comparisons(const MatrixType& m) 53 { 54 typedef typename MatrixType::Scalar Scalar; 55 typedef typename NumTraits<Scalar>::Real RealScalar; 56 typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType; 57 58 int rows = m.rows(); 59 int cols = m.cols(); 60 61 int r = ei_random<int>(0, rows-1), 62 c = ei_random<int>(0, cols-1); 63 64 MatrixType m1 = MatrixType::Random(rows, cols), 65 m2 = MatrixType::Random(rows, cols), 66 m3(rows, cols); 67 68 VERIFY(((m1.cwise() + Scalar(1)).cwise() > m1).all()); 69 VERIFY(((m1.cwise() - Scalar(1)).cwise() < m1).all()); 70 if (rows*cols>1) 71 { 72 m3 = m1; 73 m3(r,c) += 1; 74 VERIFY(! (m1.cwise() < m3).all() ); 75 VERIFY(! (m1.cwise() > m3).all() ); 76 } 77 78 // comparisons to scalar 79 VERIFY( (m1.cwise() != (m1(r,c)+1) ).any() ); 80 VERIFY( (m1.cwise() > (m1(r,c)-1) ).any() ); 81 VERIFY( (m1.cwise() < (m1(r,c)+1) ).any() ); 82 VERIFY( (m1.cwise() == m1(r,c) ).any() ); 83 84 // test Select 85 VERIFY_IS_APPROX( (m1.cwise()<m2).select(m1,m2), m1.cwise().min(m2) ); 86 VERIFY_IS_APPROX( (m1.cwise()>m2).select(m1,m2), m1.cwise().max(m2) ); 87 Scalar mid = (m1.cwise().abs().minCoeff() + m1.cwise().abs().maxCoeff())/Scalar(2); 88 for (int j=0; j<cols; ++j) 89 for (int i=0; i<rows; ++i) 90 m3(i,j) = ei_abs(m1(i,j))<mid ? 0 : m1(i,j); 91 VERIFY_IS_APPROX( (m1.cwise().abs().cwise()<MatrixType::Constant(rows,cols,mid)) 92 .select(MatrixType::Zero(rows,cols),m1), m3); 93 // shorter versions: 94 VERIFY_IS_APPROX( (m1.cwise().abs().cwise()<MatrixType::Constant(rows,cols,mid)) 95 .select(0,m1), m3); 96 VERIFY_IS_APPROX( (m1.cwise().abs().cwise()>=MatrixType::Constant(rows,cols,mid)) 97 .select(m1,0), m3); 98 // even shorter version: 99 VERIFY_IS_APPROX( (m1.cwise().abs().cwise()<mid).select(0,m1), m3); 100 101 // count 102 VERIFY(((m1.cwise().abs().cwise()+1).cwise()>RealScalar(0.1)).count() == rows*cols); 103 VERIFY_IS_APPROX(((m1.cwise().abs().cwise()+1).cwise()>RealScalar(0.1)).colwise().count().template cast<int>(), RowVectorXi::Constant(cols,rows)); 104 VERIFY_IS_APPROX(((m1.cwise().abs().cwise()+1).cwise()>RealScalar(0.1)).rowwise().count().template cast<int>(), VectorXi::Constant(rows, cols)); 105 } 106 107 template<typename VectorType> void lpNorm(const VectorType& v) 108 { 109 VectorType u = VectorType::Random(v.size()); 110 111 VERIFY_IS_APPROX(u.template lpNorm<Infinity>(), u.cwise().abs().maxCoeff()); 112 VERIFY_IS_APPROX(u.template lpNorm<1>(), u.cwise().abs().sum()); 113 VERIFY_IS_APPROX(u.template lpNorm<2>(), ei_sqrt(u.cwise().abs().cwise().square().sum())); 114 VERIFY_IS_APPROX(ei_pow(u.template lpNorm<5>(), typename VectorType::RealScalar(5)), u.cwise().abs().cwise().pow(5).sum()); 115 } 116 117 void test_eigen2_array() 118 { 119 for(int i = 0; i < g_repeat; i++) { 120 CALL_SUBTEST_1( array(Matrix<float, 1, 1>()) ); 121 CALL_SUBTEST_2( array(Matrix2f()) ); 122 CALL_SUBTEST_3( array(Matrix4d()) ); 123 CALL_SUBTEST_4( array(MatrixXcf(3, 3)) ); 124 CALL_SUBTEST_5( array(MatrixXf(8, 12)) ); 125 CALL_SUBTEST_6( array(MatrixXi(8, 12)) ); 126 } 127 for(int i = 0; i < g_repeat; i++) { 128 CALL_SUBTEST_1( comparisons(Matrix<float, 1, 1>()) ); 129 CALL_SUBTEST_2( comparisons(Matrix2f()) ); 130 CALL_SUBTEST_3( comparisons(Matrix4d()) ); 131 CALL_SUBTEST_5( comparisons(MatrixXf(8, 12)) ); 132 CALL_SUBTEST_6( comparisons(MatrixXi(8, 12)) ); 133 } 134 for(int i = 0; i < g_repeat; i++) { 135 CALL_SUBTEST_1( lpNorm(Matrix<float, 1, 1>()) ); 136 CALL_SUBTEST_2( lpNorm(Vector2f()) ); 137 CALL_SUBTEST_3( lpNorm(Vector3d()) ); 138 CALL_SUBTEST_4( lpNorm(Vector4f()) ); 139 CALL_SUBTEST_5( lpNorm(VectorXf(16)) ); 140 CALL_SUBTEST_7( lpNorm(VectorXcd(10)) ); 141 } 142 } 143
