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84 lines
3.1 KiB
84 lines
3.1 KiB
// 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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// This Source Code Form is subject to the terms of the Mozilla
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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#include "main.h"
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#include <Eigen/LU>
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#include <algorithm>
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template<typename T> std::string type_name() { return "other"; }
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template<> std::string type_name<float>() { return "float"; }
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template<> std::string type_name<double>() { return "double"; }
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template<> std::string type_name<int>() { return "int"; }
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template<> std::string type_name<std::complex<float> >() { return "complex<float>"; }
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template<> std::string type_name<std::complex<double> >() { return "complex<double>"; }
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template<> std::string type_name<std::complex<int> >() { return "complex<int>"; }
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#define EIGEN_DEBUG_VAR(x) std::cerr << #x << " = " << x << std::endl;
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template<typename T> inline typename NumTraits<T>::Real epsilon()
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{
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return std::numeric_limits<typename NumTraits<T>::Real>::epsilon();
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}
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template<typename MatrixType> void inverse_permutation_4x4()
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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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Vector4i indices(0,1,2,3);
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for(int i = 0; i < 24; ++i)
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{
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MatrixType m = MatrixType::Zero();
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m(indices(0),0) = 1;
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m(indices(1),1) = 1;
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m(indices(2),2) = 1;
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m(indices(3),3) = 1;
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MatrixType inv = m.inverse();
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double error = double( (m*inv-MatrixType::Identity()).norm() / epsilon<Scalar>() );
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VERIFY(error == 0.0);
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std::next_permutation(indices.data(),indices.data()+4);
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}
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}
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template<typename MatrixType> void inverse_general_4x4(int repeat)
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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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double error_sum = 0., error_max = 0.;
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for(int i = 0; i < repeat; ++i)
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{
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MatrixType m;
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RealScalar absdet;
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do {
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m = MatrixType::Random();
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absdet = ei_abs(m.determinant());
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} while(absdet < 10 * epsilon<Scalar>());
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MatrixType inv = m.inverse();
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double error = double( (m*inv-MatrixType::Identity()).norm() * absdet / epsilon<Scalar>() );
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error_sum += error;
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error_max = std::max(error_max, error);
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}
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std::cerr << "inverse_general_4x4, Scalar = " << type_name<Scalar>() << std::endl;
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double error_avg = error_sum / repeat;
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EIGEN_DEBUG_VAR(error_avg);
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EIGEN_DEBUG_VAR(error_max);
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VERIFY(error_avg < (NumTraits<Scalar>::IsComplex ? 8.0 : 1.25));
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VERIFY(error_max < (NumTraits<Scalar>::IsComplex ? 64.0 : 20.0));
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}
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void test_eigen2_prec_inverse_4x4()
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{
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CALL_SUBTEST_1((inverse_permutation_4x4<Matrix4f>()));
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CALL_SUBTEST_1(( inverse_general_4x4<Matrix4f>(200000 * g_repeat) ));
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CALL_SUBTEST_2((inverse_permutation_4x4<Matrix<double,4,4,RowMajor> >()));
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CALL_SUBTEST_2(( inverse_general_4x4<Matrix<double,4,4,RowMajor> >(200000 * g_repeat) ));
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CALL_SUBTEST_3((inverse_permutation_4x4<Matrix4cf>()));
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CALL_SUBTEST_3((inverse_general_4x4<Matrix4cf>(50000 * g_repeat)));
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}
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