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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
87 lines
2.7 KiB
C++
87 lines
2.7 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 Gael Guennebaud <g.gael@free.fr>
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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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#include <Eigen/Array>
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template<typename MatrixType> void replicate(const MatrixType& m)
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{
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/* this test covers the following files:
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Replicate.cpp
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*/
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typedef typename MatrixType::Scalar Scalar;
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typedef typename NumTraits<Scalar>::Real RealScalar;
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typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
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typedef Matrix<Scalar, Dynamic, Dynamic> MatrixX;
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typedef Matrix<Scalar, Dynamic, 1> VectorX;
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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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MatrixX x1, x2;
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VectorX vx1;
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int f1 = ei_random<int>(1,10),
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f2 = ei_random<int>(1,10);
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x1.resize(rows*f1,cols*f2);
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for(int j=0; j<f2; j++)
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for(int i=0; i<f1; i++)
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x1.block(i*rows,j*cols,rows,cols) = m1;
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VERIFY_IS_APPROX(x1, m1.replicate(f1,f2));
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x2.resize(2*rows,3*cols);
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x2 << m2, m2, m2,
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m2, m2, m2;
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VERIFY_IS_APPROX(x2, (m2.template replicate<2,3>()));
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x2.resize(rows,f1);
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for (int j=0; j<f1; ++j)
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x2.col(j) = v1;
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VERIFY_IS_APPROX(x2, v1.rowwise().replicate(f1));
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vx1.resize(rows*f2);
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for (int j=0; j<f2; ++j)
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vx1.segment(j*rows,rows) = v1;
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VERIFY_IS_APPROX(vx1, v1.colwise().replicate(f2));
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}
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void test_array_replicate()
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{
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for(int i = 0; i < g_repeat; i++) {
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CALL_SUBTEST_1( replicate(Matrix<float, 1, 1>()) );
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CALL_SUBTEST_2( replicate(Vector2f()) );
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CALL_SUBTEST_3( replicate(Vector3d()) );
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CALL_SUBTEST_4( replicate(Vector4f()) );
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CALL_SUBTEST_5( replicate(VectorXf(16)) );
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CALL_SUBTEST_6( replicate(VectorXcd(10)) );
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}
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}
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