// This file is part of Eigen, a lightweight C++ template library // for linear algebra. Eigen itself is part of the KDE project. // // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com> // // 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/. #include "main.h" // check minor separately in order to avoid the possible creation of a zero-sized // array. Comes from a compilation error with gcc-3.4 or gcc-4 with -ansi -pedantic. // Another solution would be to declare the array like this: T m_data[Size==0?1:Size]; in ei_matrix_storage // but this is probably not bad to raise such an error at compile time... template<typename Scalar, int _Rows, int _Cols> struct CheckMinor { typedef Matrix<Scalar, _Rows, _Cols> MatrixType; CheckMinor(MatrixType& m1, int r1, int c1) { int rows = m1.rows(); int cols = m1.cols(); Matrix<Scalar, Dynamic, Dynamic> mi = m1.minor(0,0).eval(); VERIFY_IS_APPROX(mi, m1.block(1,1,rows-1,cols-1)); mi = m1.minor(r1,c1); VERIFY_IS_APPROX(mi.transpose(), m1.transpose().minor(c1,r1)); //check operator(), both constant and non-constant, on minor() m1.minor(r1,c1)(0,0) = m1.minor(0,0)(0,0); } }; template<typename Scalar> struct CheckMinor<Scalar,1,1> { typedef Matrix<Scalar, 1, 1> MatrixType; CheckMinor(MatrixType&, int, int) {} }; template<typename MatrixType> void submatrices(const MatrixType& m) { /* this test covers the following files: Row.h Column.h Block.h Minor.h DiagonalCoeffs.h */ typedef typename MatrixType::Scalar Scalar; typedef typename MatrixType::RealScalar RealScalar; typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType; typedef Matrix<Scalar, 1, MatrixType::ColsAtCompileTime> RowVectorType; int rows = m.rows(); int cols = m.cols(); MatrixType m1 = MatrixType::Random(rows, cols), m2 = MatrixType::Random(rows, cols), m3(rows, cols), mzero = MatrixType::Zero(rows, cols), ones = MatrixType::Ones(rows, cols), identity = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> ::Identity(rows, rows), square = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> ::Random(rows, rows); VectorType v1 = VectorType::Random(rows), v2 = VectorType::Random(rows), v3 = VectorType::Random(rows), vzero = VectorType::Zero(rows); Scalar s1 = ei_random<Scalar>(); int r1 = ei_random<int>(0,rows-1); int r2 = ei_random<int>(r1,rows-1); int c1 = ei_random<int>(0,cols-1); int c2 = ei_random<int>(c1,cols-1); //check row() and col() VERIFY_IS_APPROX(m1.col(c1).transpose(), m1.transpose().row(c1)); VERIFY_IS_APPROX(square.row(r1).eigen2_dot(m1.col(c1)), (square.lazy() * m1.conjugate())(r1,c1)); //check operator(), both constant and non-constant, on row() and col() m1.row(r1) += s1 * m1.row(r2); m1.col(c1) += s1 * m1.col(c2); //check block() Matrix<Scalar,Dynamic,Dynamic> b1(1,1); b1(0,0) = m1(r1,c1); RowVectorType br1(m1.block(r1,0,1,cols)); VectorType bc1(m1.block(0,c1,rows,1)); VERIFY_IS_APPROX(b1, m1.block(r1,c1,1,1)); VERIFY_IS_APPROX(m1.row(r1), br1); VERIFY_IS_APPROX(m1.col(c1), bc1); //check operator(), both constant and non-constant, on block() m1.block(r1,c1,r2-r1+1,c2-c1+1) = s1 * m2.block(0, 0, r2-r1+1,c2-c1+1); m1.block(r1,c1,r2-r1+1,c2-c1+1)(r2-r1,c2-c1) = m2.block(0, 0, r2-r1+1,c2-c1+1)(0,0); //check minor() CheckMinor<Scalar, MatrixType::RowsAtCompileTime, MatrixType::ColsAtCompileTime> checkminor(m1,r1,c1); //check diagonal() VERIFY_IS_APPROX(m1.diagonal(), m1.transpose().diagonal()); m2.diagonal() = 2 * m1.diagonal(); m2.diagonal()[0] *= 3; VERIFY_IS_APPROX(m2.diagonal()[0], static_cast<Scalar>(6) * m1.diagonal()[0]); enum { BlockRows = EIGEN_SIZE_MIN_PREFER_FIXED(MatrixType::RowsAtCompileTime,2), BlockCols = EIGEN_SIZE_MIN_PREFER_FIXED(MatrixType::ColsAtCompileTime,5) }; if (rows>=5 && cols>=8) { // test fixed block() as lvalue m1.template block<BlockRows,BlockCols>(1,1) *= s1; // test operator() on fixed block() both as constant and non-constant m1.template block<BlockRows,BlockCols>(1,1)(0, 3) = m1.template block<2,5>(1,1)(1,2); // check that fixed block() and block() agree Matrix<Scalar,Dynamic,Dynamic> b = m1.template block<BlockRows,BlockCols>(3,3); VERIFY_IS_APPROX(b, m1.block(3,3,BlockRows,BlockCols)); } if (rows>2) { // test sub vectors VERIFY_IS_APPROX(v1.template start<2>(), v1.block(0,0,2,1)); VERIFY_IS_APPROX(v1.template start<2>(), v1.start(2)); VERIFY_IS_APPROX(v1.template start<2>(), v1.segment(0,2)); VERIFY_IS_APPROX(v1.template start<2>(), v1.template segment<2>(0)); int i = rows-2; VERIFY_IS_APPROX(v1.template end<2>(), v1.block(i,0,2,1)); VERIFY_IS_APPROX(v1.template end<2>(), v1.end(2)); VERIFY_IS_APPROX(v1.template end<2>(), v1.segment(i,2)); VERIFY_IS_APPROX(v1.template end<2>(), v1.template segment<2>(i)); i = ei_random(0,rows-2); VERIFY_IS_APPROX(v1.segment(i,2), v1.template segment<2>(i)); } // stress some basic stuffs with block matrices VERIFY(ei_real(ones.col(c1).sum()) == RealScalar(rows)); VERIFY(ei_real(ones.row(r1).sum()) == RealScalar(cols)); VERIFY(ei_real(ones.col(c1).eigen2_dot(ones.col(c2))) == RealScalar(rows)); VERIFY(ei_real(ones.row(r1).eigen2_dot(ones.row(r2))) == RealScalar(cols)); } void test_eigen2_submatrices() { for(int i = 0; i < g_repeat; i++) { CALL_SUBTEST_1( submatrices(Matrix<float, 1, 1>()) ); CALL_SUBTEST_2( submatrices(Matrix4d()) ); CALL_SUBTEST_3( submatrices(MatrixXcf(3, 3)) ); CALL_SUBTEST_4( submatrices(MatrixXi(8, 12)) ); CALL_SUBTEST_5( submatrices(MatrixXcd(20, 20)) ); CALL_SUBTEST_6( submatrices(MatrixXf(20, 20)) ); } }