|  | // This file is part of Eigen, a lightweight C++ template library | 
|  | // for linear algebra. | 
|  | // | 
|  | // Copyright (C) 2011 Benoit Jacob <jacob.benoit.1@gmail.com> | 
|  | // Copyright (C) 2015 Gael Guennebaud <gael.guennebaud@inria.fr> | 
|  | // | 
|  | // This Source Code Form is subject to the terms of the Mozilla | 
|  | // Public License v. 2.0. If a copy of the MPL was not distributed | 
|  | // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. | 
|  |  | 
|  | #define TEST_ENABLE_TEMPORARY_TRACKING | 
|  | #define EIGEN_NO_STATIC_ASSERT | 
|  |  | 
|  | #include "main.h" | 
|  |  | 
|  | template<typename ArrayType> void vectorwiseop_array(const ArrayType& m) | 
|  | { | 
|  | typedef typename ArrayType::Index Index; | 
|  | typedef typename ArrayType::Scalar Scalar; | 
|  | typedef Array<Scalar, ArrayType::RowsAtCompileTime, 1> ColVectorType; | 
|  | typedef Array<Scalar, 1, ArrayType::ColsAtCompileTime> RowVectorType; | 
|  |  | 
|  | Index rows = m.rows(); | 
|  | Index cols = m.cols(); | 
|  | Index r = internal::random<Index>(0, rows-1), | 
|  | c = internal::random<Index>(0, cols-1); | 
|  |  | 
|  | ArrayType m1 = ArrayType::Random(rows, cols), | 
|  | m2(rows, cols), | 
|  | m3(rows, cols); | 
|  |  | 
|  | ColVectorType colvec = ColVectorType::Random(rows); | 
|  | RowVectorType rowvec = RowVectorType::Random(cols); | 
|  |  | 
|  | // test addition | 
|  |  | 
|  | m2 = m1; | 
|  | m2.colwise() += colvec; | 
|  | VERIFY_IS_APPROX(m2, m1.colwise() + colvec); | 
|  | VERIFY_IS_APPROX(m2.col(c), m1.col(c) + colvec); | 
|  |  | 
|  | VERIFY_RAISES_ASSERT(m2.colwise() += colvec.transpose()); | 
|  | VERIFY_RAISES_ASSERT(m1.colwise() + colvec.transpose()); | 
|  |  | 
|  | m2 = m1; | 
|  | m2.rowwise() += rowvec; | 
|  | VERIFY_IS_APPROX(m2, m1.rowwise() + rowvec); | 
|  | VERIFY_IS_APPROX(m2.row(r), m1.row(r) + rowvec); | 
|  |  | 
|  | VERIFY_RAISES_ASSERT(m2.rowwise() += rowvec.transpose()); | 
|  | VERIFY_RAISES_ASSERT(m1.rowwise() + rowvec.transpose()); | 
|  |  | 
|  | // test substraction | 
|  |  | 
|  | m2 = m1; | 
|  | m2.colwise() -= colvec; | 
|  | VERIFY_IS_APPROX(m2, m1.colwise() - colvec); | 
|  | VERIFY_IS_APPROX(m2.col(c), m1.col(c) - colvec); | 
|  |  | 
|  | VERIFY_RAISES_ASSERT(m2.colwise() -= colvec.transpose()); | 
|  | VERIFY_RAISES_ASSERT(m1.colwise() - colvec.transpose()); | 
|  |  | 
|  | m2 = m1; | 
|  | m2.rowwise() -= rowvec; | 
|  | VERIFY_IS_APPROX(m2, m1.rowwise() - rowvec); | 
|  | VERIFY_IS_APPROX(m2.row(r), m1.row(r) - rowvec); | 
|  |  | 
|  | VERIFY_RAISES_ASSERT(m2.rowwise() -= rowvec.transpose()); | 
|  | VERIFY_RAISES_ASSERT(m1.rowwise() - rowvec.transpose()); | 
|  |  | 
|  | // test multiplication | 
|  |  | 
|  | m2 = m1; | 
|  | m2.colwise() *= colvec; | 
|  | VERIFY_IS_APPROX(m2, m1.colwise() * colvec); | 
|  | VERIFY_IS_APPROX(m2.col(c), m1.col(c) * colvec); | 
|  |  | 
|  | VERIFY_RAISES_ASSERT(m2.colwise() *= colvec.transpose()); | 
|  | VERIFY_RAISES_ASSERT(m1.colwise() * colvec.transpose()); | 
|  |  | 
|  | m2 = m1; | 
|  | m2.rowwise() *= rowvec; | 
|  | VERIFY_IS_APPROX(m2, m1.rowwise() * rowvec); | 
|  | VERIFY_IS_APPROX(m2.row(r), m1.row(r) * rowvec); | 
|  |  | 
|  | VERIFY_RAISES_ASSERT(m2.rowwise() *= rowvec.transpose()); | 
|  | VERIFY_RAISES_ASSERT(m1.rowwise() * rowvec.transpose()); | 
|  |  | 
|  | // test quotient | 
|  |  | 
|  | m2 = m1; | 
|  | m2.colwise() /= colvec; | 
|  | VERIFY_IS_APPROX(m2, m1.colwise() / colvec); | 
|  | VERIFY_IS_APPROX(m2.col(c), m1.col(c) / colvec); | 
|  |  | 
|  | VERIFY_RAISES_ASSERT(m2.colwise() /= colvec.transpose()); | 
|  | VERIFY_RAISES_ASSERT(m1.colwise() / colvec.transpose()); | 
|  |  | 
|  | m2 = m1; | 
|  | m2.rowwise() /= rowvec; | 
|  | VERIFY_IS_APPROX(m2, m1.rowwise() / rowvec); | 
|  | VERIFY_IS_APPROX(m2.row(r), m1.row(r) / rowvec); | 
|  |  | 
|  | VERIFY_RAISES_ASSERT(m2.rowwise() /= rowvec.transpose()); | 
|  | VERIFY_RAISES_ASSERT(m1.rowwise() / rowvec.transpose()); | 
|  |  | 
|  | m2 = m1; | 
|  | // yes, there might be an aliasing issue there but ".rowwise() /=" | 
|  | // is supposed to evaluate " m2.colwise().sum()" into a temporary to avoid | 
|  | // evaluating the reduction multiple times | 
|  | if(ArrayType::RowsAtCompileTime>2 || ArrayType::RowsAtCompileTime==Dynamic) | 
|  | { | 
|  | m2.rowwise() /= m2.colwise().sum(); | 
|  | VERIFY_IS_APPROX(m2, m1.rowwise() / m1.colwise().sum()); | 
|  | } | 
|  |  | 
|  | // all/any | 
|  | Array<bool,Dynamic,Dynamic> mb(rows,cols); | 
|  | mb = (m1.real()<=0.7).colwise().all(); | 
|  | VERIFY( (mb.col(c) == (m1.real().col(c)<=0.7).all()).all() ); | 
|  | mb = (m1.real()<=0.7).rowwise().all(); | 
|  | VERIFY( (mb.row(r) == (m1.real().row(r)<=0.7).all()).all() ); | 
|  |  | 
|  | mb = (m1.real()>=0.7).colwise().any(); | 
|  | VERIFY( (mb.col(c) == (m1.real().col(c)>=0.7).any()).all() ); | 
|  | mb = (m1.real()>=0.7).rowwise().any(); | 
|  | VERIFY( (mb.row(r) == (m1.real().row(r)>=0.7).any()).all() ); | 
|  | } | 
|  |  | 
|  | template<typename MatrixType> void vectorwiseop_matrix(const MatrixType& m) | 
|  | { | 
|  | typedef typename MatrixType::Index Index; | 
|  | typedef typename MatrixType::Scalar Scalar; | 
|  | typedef typename NumTraits<Scalar>::Real RealScalar; | 
|  | typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> ColVectorType; | 
|  | typedef Matrix<Scalar, 1, MatrixType::ColsAtCompileTime> RowVectorType; | 
|  | typedef Matrix<RealScalar, MatrixType::RowsAtCompileTime, 1> RealColVectorType; | 
|  | typedef Matrix<RealScalar, 1, MatrixType::ColsAtCompileTime> RealRowVectorType; | 
|  |  | 
|  | Index rows = m.rows(); | 
|  | Index cols = m.cols(); | 
|  | Index r = internal::random<Index>(0, rows-1), | 
|  | c = internal::random<Index>(0, cols-1); | 
|  |  | 
|  | MatrixType m1 = MatrixType::Random(rows, cols), | 
|  | m2(rows, cols), | 
|  | m3(rows, cols); | 
|  |  | 
|  | ColVectorType colvec = ColVectorType::Random(rows); | 
|  | RowVectorType rowvec = RowVectorType::Random(cols); | 
|  | RealColVectorType rcres; | 
|  | RealRowVectorType rrres; | 
|  |  | 
|  | // test addition | 
|  |  | 
|  | m2 = m1; | 
|  | m2.colwise() += colvec; | 
|  | VERIFY_IS_APPROX(m2, m1.colwise() + colvec); | 
|  | VERIFY_IS_APPROX(m2.col(c), m1.col(c) + colvec); | 
|  |  | 
|  | if(rows>1) | 
|  | { | 
|  | VERIFY_RAISES_ASSERT(m2.colwise() += colvec.transpose()); | 
|  | VERIFY_RAISES_ASSERT(m1.colwise() + colvec.transpose()); | 
|  | } | 
|  |  | 
|  | m2 = m1; | 
|  | m2.rowwise() += rowvec; | 
|  | VERIFY_IS_APPROX(m2, m1.rowwise() + rowvec); | 
|  | VERIFY_IS_APPROX(m2.row(r), m1.row(r) + rowvec); | 
|  |  | 
|  | if(cols>1) | 
|  | { | 
|  | VERIFY_RAISES_ASSERT(m2.rowwise() += rowvec.transpose()); | 
|  | VERIFY_RAISES_ASSERT(m1.rowwise() + rowvec.transpose()); | 
|  | } | 
|  |  | 
|  | // test substraction | 
|  |  | 
|  | m2 = m1; | 
|  | m2.colwise() -= colvec; | 
|  | VERIFY_IS_APPROX(m2, m1.colwise() - colvec); | 
|  | VERIFY_IS_APPROX(m2.col(c), m1.col(c) - colvec); | 
|  |  | 
|  | if(rows>1) | 
|  | { | 
|  | VERIFY_RAISES_ASSERT(m2.colwise() -= colvec.transpose()); | 
|  | VERIFY_RAISES_ASSERT(m1.colwise() - colvec.transpose()); | 
|  | } | 
|  |  | 
|  | m2 = m1; | 
|  | m2.rowwise() -= rowvec; | 
|  | VERIFY_IS_APPROX(m2, m1.rowwise() - rowvec); | 
|  | VERIFY_IS_APPROX(m2.row(r), m1.row(r) - rowvec); | 
|  |  | 
|  | if(cols>1) | 
|  | { | 
|  | VERIFY_RAISES_ASSERT(m2.rowwise() -= rowvec.transpose()); | 
|  | VERIFY_RAISES_ASSERT(m1.rowwise() - rowvec.transpose()); | 
|  | } | 
|  |  | 
|  | // test norm | 
|  | rrres = m1.colwise().norm(); | 
|  | VERIFY_IS_APPROX(rrres(c), m1.col(c).norm()); | 
|  | rcres = m1.rowwise().norm(); | 
|  | VERIFY_IS_APPROX(rcres(r), m1.row(r).norm()); | 
|  |  | 
|  | VERIFY_IS_APPROX(m1.cwiseAbs().colwise().sum(), m1.colwise().template lpNorm<1>()); | 
|  | VERIFY_IS_APPROX(m1.cwiseAbs().rowwise().sum(), m1.rowwise().template lpNorm<1>()); | 
|  | VERIFY_IS_APPROX(m1.cwiseAbs().colwise().maxCoeff(), m1.colwise().template lpNorm<Infinity>()); | 
|  | VERIFY_IS_APPROX(m1.cwiseAbs().rowwise().maxCoeff(), m1.rowwise().template lpNorm<Infinity>()); | 
|  |  | 
|  | // regression for bug 1158 | 
|  | VERIFY_IS_APPROX(m1.cwiseAbs().colwise().sum().x(), m1.col(0).cwiseAbs().sum()); | 
|  |  | 
|  | // test normalized | 
|  | m2 = m1.colwise().normalized(); | 
|  | VERIFY_IS_APPROX(m2.col(c), m1.col(c).normalized()); | 
|  | m2 = m1.rowwise().normalized(); | 
|  | VERIFY_IS_APPROX(m2.row(r), m1.row(r).normalized()); | 
|  |  | 
|  | // test normalize | 
|  | m2 = m1; | 
|  | m2.colwise().normalize(); | 
|  | VERIFY_IS_APPROX(m2.col(c), m1.col(c).normalized()); | 
|  | m2 = m1; | 
|  | m2.rowwise().normalize(); | 
|  | VERIFY_IS_APPROX(m2.row(r), m1.row(r).normalized()); | 
|  |  | 
|  | // test with partial reduction of products | 
|  | Matrix<Scalar,MatrixType::RowsAtCompileTime,MatrixType::RowsAtCompileTime> m1m1 = m1 * m1.transpose(); | 
|  | VERIFY_IS_APPROX( (m1 * m1.transpose()).colwise().sum(), m1m1.colwise().sum()); | 
|  | Matrix<Scalar,1,MatrixType::RowsAtCompileTime> tmp(rows); | 
|  | VERIFY_EVALUATION_COUNT( tmp = (m1 * m1.transpose()).colwise().sum(), (MatrixType::RowsAtCompileTime==Dynamic ? 1 : 0)); | 
|  |  | 
|  | m2 = m1.rowwise() - (m1.colwise().sum()/m1.rows()).eval(); | 
|  | m1 = m1.rowwise() - (m1.colwise().sum()/m1.rows()); | 
|  | VERIFY_IS_APPROX( m1, m2 ); | 
|  | VERIFY_EVALUATION_COUNT( m2 = (m1.rowwise() - m1.colwise().sum()/m1.rows()), (MatrixType::RowsAtCompileTime==Dynamic && MatrixType::ColsAtCompileTime!=1 ? 1 : 0) ); | 
|  | } | 
|  |  | 
|  | void test_vectorwiseop() | 
|  | { | 
|  | CALL_SUBTEST_1( vectorwiseop_array(Array22cd()) ); | 
|  | CALL_SUBTEST_2( vectorwiseop_array(Array<double, 3, 2>()) ); | 
|  | CALL_SUBTEST_3( vectorwiseop_array(ArrayXXf(3, 4)) ); | 
|  | CALL_SUBTEST_4( vectorwiseop_matrix(Matrix4cf()) ); | 
|  | CALL_SUBTEST_5( vectorwiseop_matrix(Matrix<float,4,5>()) ); | 
|  | CALL_SUBTEST_6( vectorwiseop_matrix(MatrixXd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); | 
|  | CALL_SUBTEST_7( vectorwiseop_matrix(VectorXd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); | 
|  | CALL_SUBTEST_7( vectorwiseop_matrix(RowVectorXd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); | 
|  | } |