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42e2578ef9
so let's declare them after and do the respective fixes ;)
129 lines
4.4 KiB
C++
129 lines
4.4 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) 2010-2011 Jitse Niesen <jitse@maths.leeds.ac.uk>
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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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template<typename MatrixType>
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bool equalsIdentity(const MatrixType& A)
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{
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typedef typename MatrixType::Index Index;
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typedef typename MatrixType::Scalar Scalar;
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Scalar zero = static_cast<Scalar>(0);
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bool offDiagOK = true;
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for (Index i = 0; i < A.rows(); ++i) {
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for (Index j = i+1; j < A.cols(); ++j) {
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offDiagOK = offDiagOK && (A(i,j) == zero);
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}
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}
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for (Index i = 0; i < A.rows(); ++i) {
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for (Index j = 0; j < (std::min)(i, A.cols()); ++j) {
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offDiagOK = offDiagOK && (A(i,j) == zero);
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}
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}
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bool diagOK = (A.diagonal().array() == 1).all();
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return offDiagOK && diagOK;
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}
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template<typename VectorType>
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void testVectorType(const VectorType& base)
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{
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typedef typename internal::traits<VectorType>::Index Index;
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typedef typename internal::traits<VectorType>::Scalar Scalar;
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Scalar low = internal::random<Scalar>(-500,500);
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Scalar high = internal::random<Scalar>(-500,500);
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if (low>high) std::swap(low,high);
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const Index size = base.size();
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const Scalar step = (high-low)/(size-1);
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// check whether the result yields what we expect it to do
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VectorType m(base);
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m.setLinSpaced(size,low,high);
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VectorType n(size);
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for (int i=0; i<size; ++i)
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n(i) = low+i*step;
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VERIFY_IS_APPROX(m,n);
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// random access version
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m = VectorType::LinSpaced(size,low,high);
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VERIFY_IS_APPROX(m,n);
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// Assignment of a RowVectorXd to a MatrixXd (regression test for bug #79).
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VERIFY( (MatrixXd(RowVectorXd::LinSpaced(3, 0, 1)) - RowVector3d(0, 0.5, 1)).norm() < std::numeric_limits<Scalar>::epsilon() );
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// These guys sometimes fail! This is not good. Any ideas how to fix them!?
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// VERIFY( m(m.size()-1) == high );
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// VERIFY( m(0) == low );
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// sequential access version
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m = VectorType::LinSpaced(Sequential,size,low,high);
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VERIFY_IS_APPROX(m,n);
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// These guys sometimes fail! This is not good. Any ideas how to fix them!?
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//VERIFY( m(m.size()-1) == high );
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//VERIFY( m(0) == low );
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// check whether everything works with row and col major vectors
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Matrix<Scalar,Dynamic,1> row_vector(size);
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Matrix<Scalar,1,Dynamic> col_vector(size);
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row_vector.setLinSpaced(size,low,high);
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col_vector.setLinSpaced(size,low,high);
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VERIFY( row_vector.isApprox(col_vector.transpose(), NumTraits<Scalar>::epsilon()));
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Matrix<Scalar,Dynamic,1> size_changer(size+50);
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size_changer.setLinSpaced(size,low,high);
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VERIFY( size_changer.size() == size );
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}
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template<typename MatrixType>
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void testMatrixType(const MatrixType& m)
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{
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typedef typename MatrixType::Index Index;
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const Index rows = m.rows();
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const Index cols = m.cols();
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MatrixType A;
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A.setIdentity(rows, cols);
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VERIFY(equalsIdentity(A));
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VERIFY(equalsIdentity(MatrixType::Identity(rows, cols)));
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}
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void test_nullary()
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{
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CALL_SUBTEST_1( testMatrixType(Matrix2d()) );
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CALL_SUBTEST_2( testMatrixType(MatrixXcf(internal::random<int>(1,300),internal::random<int>(1,300))) );
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CALL_SUBTEST_3( testMatrixType(MatrixXf(internal::random<int>(1,300),internal::random<int>(1,300))) );
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for(int i = 0; i < g_repeat; i++) {
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CALL_SUBTEST_4( testVectorType(VectorXd(internal::random<int>(1,300))) );
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CALL_SUBTEST_5( testVectorType(Vector4d()) ); // regression test for bug 232
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CALL_SUBTEST_6( testVectorType(Vector3d()) );
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CALL_SUBTEST_7( testVectorType(VectorXf(internal::random<int>(1,300))) );
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CALL_SUBTEST_8( testVectorType(Vector3f()) );
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}
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}
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