1c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This file is part of Eigen, a lightweight C++ template library 2c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// for linear algebra. Eigen itself is part of the KDE project. 3c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// 4c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr> 5c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com> 6c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// 7c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This Source Code Form is subject to the terms of the Mozilla 8c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Public License v. 2.0. If a copy of the MPL was not distributed 9c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. 10c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 11c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include "main.h" 12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include <functional> 13c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include <Eigen/Array> 14c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 15c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathusing namespace std; 16c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 17c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar> struct AddIfNull { 18c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath const Scalar operator() (const Scalar a, const Scalar b) const {return a<=1e-3 ? b : a;} 19c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath enum { Cost = NumTraits<Scalar>::AddCost }; 20c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}; 21c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 22c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename MatrixType> void cwiseops(const MatrixType& m) 23c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 24c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef typename MatrixType::Scalar Scalar; 25c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef typename NumTraits<Scalar>::Real RealScalar; 26c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType; 27c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 28c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath int rows = m.rows(); 29c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath int cols = m.cols(); 30c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 31c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath MatrixType m1 = MatrixType::Random(rows, cols), 32c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m2 = MatrixType::Random(rows, cols), 33c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m3(rows, cols), 34c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m4(rows, cols), 35c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath mzero = MatrixType::Zero(rows, cols), 36c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath mones = MatrixType::Ones(rows, cols), 37c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath identity = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> 38615d816d068b4d0f5e8df601930b5f160bf7eda1Tim Murray ::Identity(rows, rows); 39615d816d068b4d0f5e8df601930b5f160bf7eda1Tim Murray VectorType vzero = VectorType::Zero(rows), 40c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath vones = VectorType::Ones(rows), 41c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath v3(rows); 42c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 43c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath int r = ei_random<int>(0, rows-1), 44c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath c = ei_random<int>(0, cols-1); 45c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 46c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Scalar s1 = ei_random<Scalar>(); 47c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 48c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // test Zero, Ones, Constant, and the set* variants 49c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m3 = MatrixType::Constant(rows, cols, s1); 50c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath for (int j=0; j<cols; ++j) 51c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath for (int i=0; i<rows; ++i) 52c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 53c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(mzero(i,j), Scalar(0)); 54c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(mones(i,j), Scalar(1)); 55c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m3(i,j), s1); 56c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 57c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY(mzero.isZero()); 58c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY(mones.isOnes()); 59c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY(m3.isConstant(s1)); 60c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY(identity.isIdentity()); 61c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m4.setConstant(s1), m3); 62c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m4.setConstant(rows,cols,s1), m3); 63c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m4.setZero(), mzero); 64c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m4.setZero(rows,cols), mzero); 65c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m4.setOnes(), mones); 66c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m4.setOnes(rows,cols), mones); 67c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m4.fill(s1); 68c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m4, m3); 69c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 70c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(v3.setConstant(rows, s1), VectorType::Constant(rows,s1)); 71c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(v3.setZero(rows), vzero); 72c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(v3.setOnes(rows), vones); 73c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 74c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m2 = m2.template binaryExpr<AddIfNull<Scalar> >(mones); 75c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 76c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m1.cwise().pow(2), m1.cwise().abs2()); 77c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m1.cwise().pow(2), m1.cwise().square()); 78c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m1.cwise().pow(3), m1.cwise().cube()); 79c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 80c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m1 + mones, m1.cwise()+Scalar(1)); 81c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m1 - mones, m1.cwise()-Scalar(1)); 82c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m3 = m1; m3.cwise() += 1; 83c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m1 + mones, m3); 84c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m3 = m1; m3.cwise() -= 1; 85c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m1 - mones, m3); 86c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 87c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m2, m2.cwise() * mones); 88c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m1.cwise() * m2, m2.cwise() * m1); 89c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m3 = m1; 90c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m3.cwise() *= m2; 91c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m3, m1.cwise() * m2); 92c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 93c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(mones, m2.cwise()/m2); 94c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath if(NumTraits<Scalar>::HasFloatingPoint) 95c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 96c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m1.cwise() / m2, m1.cwise() * (m2.cwise().inverse())); 97c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m3 = m1.cwise().abs().cwise().sqrt(); 98c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m3.cwise().square(), m1.cwise().abs()); 99c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m1.cwise().square().cwise().sqrt(), m1.cwise().abs()); 100c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m1.cwise().abs().cwise().log().cwise().exp() , m1.cwise().abs()); 101c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 102c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m1.cwise().pow(2), m1.cwise().square()); 103c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m3 = (m1.cwise().abs().cwise()<=RealScalar(0.01)).select(mones,m1); 104c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m3.cwise().pow(-1), m3.cwise().inverse()); 105c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m3 = m1.cwise().abs(); 106c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m3.cwise().pow(RealScalar(0.5)), m3.cwise().sqrt()); 107c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 108c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// VERIFY_IS_APPROX(m1.cwise().tan(), m1.cwise().sin().cwise() / m1.cwise().cos()); 109c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(mones, m1.cwise().sin().cwise().square() + m1.cwise().cos().cwise().square()); 110c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m3 = m1; 111c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m3.cwise() /= m2; 112c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX(m3, m1.cwise() / m2); 113c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 114c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 115c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // check min 116c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX( m1.cwise().min(m2), m2.cwise().min(m1) ); 117c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX( m1.cwise().min(m1+mones), m1 ); 118c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX( m1.cwise().min(m1-mones), m1-mones ); 119c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 120c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // check max 121c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX( m1.cwise().max(m2), m2.cwise().max(m1) ); 122c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX( m1.cwise().max(m1-mones), m1 ); 123c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY_IS_APPROX( m1.cwise().max(m1+mones), m1+mones ); 124c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 125c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY( (m1.cwise() == m1).all() ); 126c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY( (m1.cwise() != m2).any() ); 127c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY(!(m1.cwise() == (m1+mones)).any() ); 128c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath if (rows*cols>1) 129c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 130c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m3 = m1; 131c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m3(r,c) += 1; 132c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY( (m1.cwise() == m3).any() ); 133c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY( !(m1.cwise() == m3).all() ); 134c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 135c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY( (m1.cwise().min(m2).cwise() <= m2).all() ); 136c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY( (m1.cwise().max(m2).cwise() >= m2).all() ); 137c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY( (m1.cwise().min(m2).cwise() < (m1+mones)).all() ); 138c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY( (m1.cwise().max(m2).cwise() > (m1-mones)).all() ); 139c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 140c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY( (m1.cwise()<m1.unaryExpr(bind2nd(plus<Scalar>(), Scalar(1)))).all() ); 141c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY( !(m1.cwise()<m1.unaryExpr(bind2nd(minus<Scalar>(), Scalar(1)))).all() ); 142c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath VERIFY( !(m1.cwise()>m1.unaryExpr(bind2nd(plus<Scalar>(), Scalar(1)))).any() ); 143c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} 144c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 145c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathvoid test_eigen2_cwiseop() 146c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 147c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath for(int i = 0; i < g_repeat ; i++) { 148c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_1( cwiseops(Matrix<float, 1, 1>()) ); 149c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_2( cwiseops(Matrix4d()) ); 150c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_3( cwiseops(MatrixXf(3, 3)) ); 151c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_3( cwiseops(MatrixXf(22, 22)) ); 152c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_4( cwiseops(MatrixXi(8, 12)) ); 153c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath CALL_SUBTEST_5( cwiseops(MatrixXd(20, 20)) ); 154c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 155c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} 156