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82f0ce2726
This provide several advantages: - more flexibility in designing unit tests - unit tests can be glued to speed up compilation - unit tests are compiled with same predefined macros, which is a requirement for zapcc
95 lines
3.0 KiB
C++
95 lines
3.0 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) 2012 Alexey Korepanov <kaikaikai@yandex.ru>
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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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#define EIGEN_RUNTIME_NO_MALLOC
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#include "main.h"
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#include <limits>
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#include <Eigen/Eigenvalues>
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template<typename MatrixType> void real_qz(const MatrixType& m)
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{
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/* this test covers the following files:
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RealQZ.h
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*/
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using std::abs;
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typedef typename MatrixType::Scalar Scalar;
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Index dim = m.cols();
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MatrixType A = MatrixType::Random(dim,dim),
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B = MatrixType::Random(dim,dim);
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// Regression test for bug 985: Randomly set rows or columns to zero
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Index k=internal::random<Index>(0, dim-1);
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switch(internal::random<int>(0,10)) {
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case 0:
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A.row(k).setZero(); break;
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case 1:
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A.col(k).setZero(); break;
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case 2:
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B.row(k).setZero(); break;
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case 3:
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B.col(k).setZero(); break;
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default:
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break;
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}
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RealQZ<MatrixType> qz(dim);
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// TODO enable full-prealocation of required memory, this probably requires an in-place mode for HessenbergDecomposition
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//Eigen::internal::set_is_malloc_allowed(false);
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qz.compute(A,B);
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//Eigen::internal::set_is_malloc_allowed(true);
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VERIFY_IS_EQUAL(qz.info(), Success);
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// check for zeros
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bool all_zeros = true;
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for (Index i=0; i<A.cols(); i++)
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for (Index j=0; j<i; j++) {
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if (abs(qz.matrixT()(i,j))!=Scalar(0.0))
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{
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std::cerr << "Error: T(" << i << "," << j << ") = " << qz.matrixT()(i,j) << std::endl;
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all_zeros = false;
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}
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if (j<i-1 && abs(qz.matrixS()(i,j))!=Scalar(0.0))
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{
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std::cerr << "Error: S(" << i << "," << j << ") = " << qz.matrixS()(i,j) << std::endl;
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all_zeros = false;
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}
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if (j==i-1 && j>0 && abs(qz.matrixS()(i,j))!=Scalar(0.0) && abs(qz.matrixS()(i-1,j-1))!=Scalar(0.0))
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{
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std::cerr << "Error: S(" << i << "," << j << ") = " << qz.matrixS()(i,j) << " && S(" << i-1 << "," << j-1 << ") = " << qz.matrixS()(i-1,j-1) << std::endl;
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all_zeros = false;
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}
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}
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VERIFY_IS_EQUAL(all_zeros, true);
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VERIFY_IS_APPROX(qz.matrixQ()*qz.matrixS()*qz.matrixZ(), A);
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VERIFY_IS_APPROX(qz.matrixQ()*qz.matrixT()*qz.matrixZ(), B);
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VERIFY_IS_APPROX(qz.matrixQ()*qz.matrixQ().adjoint(), MatrixType::Identity(dim,dim));
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VERIFY_IS_APPROX(qz.matrixZ()*qz.matrixZ().adjoint(), MatrixType::Identity(dim,dim));
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}
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EIGEN_DECLARE_TEST(real_qz)
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{
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int s = 0;
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for(int i = 0; i < g_repeat; i++) {
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CALL_SUBTEST_1( real_qz(Matrix4f()) );
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s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/4);
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CALL_SUBTEST_2( real_qz(MatrixXd(s,s)) );
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// some trivial but implementation-wise tricky cases
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CALL_SUBTEST_2( real_qz(MatrixXd(1,1)) );
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CALL_SUBTEST_2( real_qz(MatrixXd(2,2)) );
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CALL_SUBTEST_3( real_qz(Matrix<double,1,1>()) );
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CALL_SUBTEST_4( real_qz(Matrix2d()) );
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}
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TEST_SET_BUT_UNUSED_VARIABLE(s)
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}
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