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2840ac7e94
* renaming, e.g. LU ---> FullPivLU * split tests framework: more robust, e.g. dont generate empty tests if a number is skipped * make all remaining tests use that splitting, as needed. * Fix 4x4 inversion (see stable branch) * Transform::inverse() and geo_transform test : adapt to new inverse() API, it was also trying to instantiate inverse() for 3x4 matrices. * CMakeLists: more robust regexp to parse the version number * misc fixes in unit tests
109 lines
4.6 KiB
C++
109 lines
4.6 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
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//
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// Eigen is free software; you can redistribute it and/or
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// modify it under the terms of the GNU Lesser General Public
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// License as published by the Free Software Foundation; either
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// version 3 of the License, or (at your option) any later version.
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//
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// Alternatively, you can redistribute it and/or
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// modify it under the terms of the GNU General Public License as
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// published by the Free Software Foundation; either version 2 of
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// the License, or (at your option) any later version.
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//
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// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
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// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
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// GNU General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public
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// License and a copy of the GNU General Public License along with
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// Eigen. If not, see <http://www.gnu.org/licenses/>.
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#include "main.h"
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using namespace std;
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template<typename MatrixType> void diagonalmatrices(const MatrixType& m)
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{
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typedef typename MatrixType::Scalar Scalar;
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typedef typename MatrixType::RealScalar RealScalar;
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enum { Rows = MatrixType::RowsAtCompileTime, Cols = MatrixType::ColsAtCompileTime };
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typedef Matrix<Scalar, Rows, 1> VectorType;
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typedef Matrix<Scalar, 1, Cols> RowVectorType;
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typedef Matrix<Scalar, Rows, Rows> SquareMatrixType;
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typedef DiagonalMatrix<Scalar, Rows> LeftDiagonalMatrix;
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typedef DiagonalMatrix<Scalar, Cols> RightDiagonalMatrix;
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typedef Matrix<Scalar, Rows==Dynamic?Dynamic:2*Rows, Cols==Dynamic?Dynamic:2*Cols> BigMatrix;
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int rows = m.rows();
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int cols = m.cols();
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MatrixType m1 = MatrixType::Random(rows, cols),
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m2 = MatrixType::Random(rows, cols);
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VectorType v1 = VectorType::Random(rows),
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v2 = VectorType::Random(rows);
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RowVectorType rv1 = RowVectorType::Random(cols),
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rv2 = RowVectorType::Random(cols);
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LeftDiagonalMatrix ldm1(v1), ldm2(v2);
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RightDiagonalMatrix rdm1(rv1), rdm2(rv2);
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SquareMatrixType sq_m1 (v1.asDiagonal());
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VERIFY_IS_APPROX(sq_m1, v1.asDiagonal().toDenseMatrix());
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sq_m1 = v1.asDiagonal();
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VERIFY_IS_APPROX(sq_m1, v1.asDiagonal().toDenseMatrix());
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SquareMatrixType sq_m2 = v1.asDiagonal();
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VERIFY_IS_APPROX(sq_m1, sq_m2);
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ldm1 = v1.asDiagonal();
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LeftDiagonalMatrix ldm3(v1);
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VERIFY_IS_APPROX(ldm1.diagonal(), ldm3.diagonal());
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LeftDiagonalMatrix ldm4 = v1.asDiagonal();
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VERIFY_IS_APPROX(ldm1.diagonal(), ldm4.diagonal());
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sq_m1.block(0,0,rows,rows) = ldm1;
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VERIFY_IS_APPROX(sq_m1, ldm1.toDenseMatrix());
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sq_m1.transpose() = ldm1;
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VERIFY_IS_APPROX(sq_m1, ldm1.toDenseMatrix());
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int i = ei_random<int>(0, rows-1);
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int j = ei_random<int>(0, cols-1);
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VERIFY_IS_APPROX( ((ldm1 * m1)(i,j)) , ldm1.diagonal()(i) * m1(i,j) );
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VERIFY_IS_APPROX( ((ldm1 * (m1+m2))(i,j)) , ldm1.diagonal()(i) * (m1+m2)(i,j) );
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VERIFY_IS_APPROX( ((m1 * rdm1)(i,j)) , rdm1.diagonal()(j) * m1(i,j) );
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VERIFY_IS_APPROX( ((v1.asDiagonal() * m1)(i,j)) , v1(i) * m1(i,j) );
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VERIFY_IS_APPROX( ((m1 * rv1.asDiagonal())(i,j)) , rv1(j) * m1(i,j) );
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VERIFY_IS_APPROX( (((v1+v2).asDiagonal() * m1)(i,j)) , (v1+v2)(i) * m1(i,j) );
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VERIFY_IS_APPROX( (((v1+v2).asDiagonal() * (m1+m2))(i,j)) , (v1+v2)(i) * (m1+m2)(i,j) );
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VERIFY_IS_APPROX( ((m1 * (rv1+rv2).asDiagonal())(i,j)) , (rv1+rv2)(j) * m1(i,j) );
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VERIFY_IS_APPROX( (((m1+m2) * (rv1+rv2).asDiagonal())(i,j)) , (rv1+rv2)(j) * (m1+m2)(i,j) );
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BigMatrix big;
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big.setZero(2*rows, 2*cols);
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big.block(i,j,rows,cols) = m1;
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big.block(i,j,rows,cols) = v1.asDiagonal() * big.block(i,j,rows,cols);
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VERIFY_IS_APPROX((big.block(i,j,rows,cols)) , v1.asDiagonal() * m1 );
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big.block(i,j,rows,cols) = m1;
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big.block(i,j,rows,cols) = big.block(i,j,rows,cols) * rv1.asDiagonal();
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VERIFY_IS_APPROX((big.block(i,j,rows,cols)) , m1 * rv1.asDiagonal() );
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}
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void test_diagonalmatrices()
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{
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for(int i = 0; i < g_repeat; i++) {
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CALL_SUBTEST_1( diagonalmatrices(Matrix<float, 1, 1>()) );
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CALL_SUBTEST_2( diagonalmatrices(Matrix3f()) );
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CALL_SUBTEST_3( diagonalmatrices(Matrix<double,3,3,RowMajor>()) );
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CALL_SUBTEST_4( diagonalmatrices(Matrix4d()) );
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CALL_SUBTEST_5( diagonalmatrices(Matrix<float,4,4,RowMajor>()) );
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CALL_SUBTEST_6( diagonalmatrices(MatrixXcf(3, 5)) );
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CALL_SUBTEST_7( diagonalmatrices(MatrixXi(10, 8)) );
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CALL_SUBTEST_8( diagonalmatrices(Matrix<double,Dynamic,Dynamic,RowMajor>(20, 20)) );
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CALL_SUBTEST_9( diagonalmatrices(MatrixXf(21, 24)) );
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}
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}
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