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89 lines
3.3 KiB
C++
89 lines
3.3 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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// 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 <Eigen/LU>
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#include <algorithm>
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#include "main.h"
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template <typename MatrixType>
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void inverse_permutation_4x4() {
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typedef typename MatrixType::Scalar Scalar;
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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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MatrixType m = PermutationMatrix<4>(indices);
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MatrixType inv = m.inverse();
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double error = double((m * inv - MatrixType::Identity()).norm() /
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NumTraits<Scalar>::epsilon());
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EIGEN_DEBUG_VAR(error)
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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>
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void inverse_general_4x4(int repeat) {
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using std::abs;
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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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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 = abs(m.determinant());
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} while (absdet < NumTraits<Scalar>::epsilon());
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MatrixType inv = m.inverse();
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double error = double((m * inv - MatrixType::Identity()).norm() * absdet /
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NumTraits<Scalar>::epsilon());
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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>()
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<< 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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// FIXME that 1.25 used to be a 1.0 until the NumTraits changes on 28 April
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// 2010, what's going wrong??
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// FIXME that 1.25 used to be 1.2 until we tested gcc 4.1 on 30 June 2010 and
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// got 1.21.
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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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int s = 5; // internal::random<int>(4,10);
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int i = 0; // internal::random<int>(0,s-4);
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int j = 0; // internal::random<int>(0,s-4);
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Matrix<Scalar, 5, 5> mat(s, s);
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mat.setRandom();
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MatrixType submat = mat.template block<4, 4>(i, j);
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MatrixType mat_inv = mat.template block<4, 4>(i, j).inverse();
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VERIFY_IS_APPROX(mat_inv, submat.inverse());
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mat.template block<4, 4>(i, j) = submat.inverse();
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VERIFY_IS_APPROX(mat_inv, (mat.template block<4, 4>(i, j)));
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}
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}
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EIGEN_DECLARE_TEST(prec_inverse_4x4) {
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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_1(
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(inverse_general_4x4<Matrix<float, 4, 4, RowMajor> >(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((
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inverse_general_4x4<Matrix<double, 4, 4, ColMajor> >(200000 * g_repeat)));
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CALL_SUBTEST_2((
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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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