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15ca6659ac
order, one bit for enabling/disabling auto-alignment. If you want to disable, do: Matrix<float,4,1,Matrix_DontAlign> The Matrix_ prefix is the only way I can see to avoid ambiguity/pollution. The old RowMajor, ColMajor constants are deprecated, remain for now. * this prompted several improvements in matrix_storage. ei_aligned_array renamed to ei_matrix_array and moved there. The %16==0 tests are now much more centralized in 1 place there. * unalignedassert test: updated * update FindEigen2.cmake from KDElibs * determinant test: use VERIFY_IS_APPROX to fix false positives; add testing of 1 big matrix
77 lines
2.8 KiB
C++
77 lines
2.8 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra. Eigen itself is part of the KDE project.
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//
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// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
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// Copyright (C) 2008 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/LU>
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template<typename MatrixType> void determinant(const MatrixType& m)
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{
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/* this test covers the following files:
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Determinant.h
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*/
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int size = m.rows();
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MatrixType m1(size, size), m2(size, size);
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m1.setRandom();
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m2.setRandom();
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typedef typename MatrixType::Scalar Scalar;
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Scalar x = ei_random<Scalar>();
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VERIFY_IS_APPROX(MatrixType::Identity(size, size).determinant(), Scalar(1));
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VERIFY_IS_APPROX((m1*m2).determinant(), m1.determinant() * m2.determinant());
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if(size==1) return;
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int i = ei_random<int>(0, size-1);
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int j;
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do {
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j = ei_random<int>(0, size-1);
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} while(j==i);
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m2 = m1;
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m2.row(i).swap(m2.row(j));
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VERIFY_IS_APPROX(m2.determinant(), -m1.determinant());
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m2 = m1;
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m2.col(i).swap(m2.col(j));
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VERIFY_IS_APPROX(m2.determinant(), -m1.determinant());
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VERIFY_IS_APPROX(m2.determinant(), m2.transpose().determinant());
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VERIFY_IS_APPROX(ei_conj(m2.determinant()), m2.adjoint().determinant());
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m2 = m1;
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m2.row(i) += x*m2.row(j);
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VERIFY_IS_APPROX(m2.determinant(), m1.determinant());
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m2 = m1;
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m2.row(i) *= x;
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VERIFY_IS_APPROX(m2.determinant(), m1.determinant() * x);
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}
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void test_determinant()
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{
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for(int i = 0; i < g_repeat; i++) {
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CALL_SUBTEST( determinant(Matrix<float, 1, 1>()) );
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CALL_SUBTEST( determinant(Matrix<double, 2, 2>()) );
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CALL_SUBTEST( determinant(Matrix<double, 3, 3>()) );
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CALL_SUBTEST( determinant(Matrix<double, 4, 4>()) );
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CALL_SUBTEST( determinant(Matrix<std::complex<double>, 10, 10>()) );
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CALL_SUBTEST( determinant(MatrixXd(20, 20)) );
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}
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CALL_SUBTEST( determinant(MatrixXd(200, 200)) );
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}
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