143 lines
5.6 KiB
C++
143 lines
5.6 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) 2006-2008 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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// check minor separately in order to avoid the possible creation of a zero-sized
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// array. Comes from a compilation error with gcc-3.4 or gcc-4 with -ansi -pedantic.
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// Another solution would be to declare the array like this: T m_data[Size==0?1:Size]; in ei_matrix_storage
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// but this is probably not bad to raise such an error at compile time...
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template<typename Scalar, int _Rows, int _Cols> struct CheckMinor
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{
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typedef Matrix<Scalar, _Rows, _Cols> MatrixType;
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CheckMinor(MatrixType& m1, int r1, int c1)
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{
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int rows = m1.rows();
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int cols = m1.cols();
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Matrix<Scalar, Dynamic, Dynamic> mi = m1.minor(0,0).eval();
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VERIFY_IS_APPROX(mi, m1.block(1,1,rows-1,cols-1));
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mi = m1.minor(r1,c1);
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VERIFY_IS_APPROX(mi.transpose(), m1.transpose().minor(c1,r1));
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//check operator(), both constant and non-constant, on minor()
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m1.minor(r1,c1)(0,0) = m1.minor(0,0)(0,0);
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}
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};
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template<typename Scalar> struct CheckMinor<Scalar,1,1>
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{
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typedef Matrix<Scalar, 1, 1> MatrixType;
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CheckMinor(MatrixType&, int, int) {}
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};
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template<typename MatrixType> void submatrices(const MatrixType& m)
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{
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/* this test covers the following files:
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Row.h Column.h Block.h Minor.h DiagonalCoeffs.h
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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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typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
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typedef Matrix<Scalar, 1, MatrixType::ColsAtCompileTime> RowVectorType;
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int rows = m.rows();
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int cols = m.cols();
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MatrixType m1 = MatrixType::Random(rows, cols),
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m2 = MatrixType::Random(rows, cols),
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m3(rows, cols),
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ones = MatrixType::Ones(rows, cols),
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square = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>
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::Random(rows, rows);
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VectorType v1 = VectorType::Random(rows);
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Scalar s1 = ei_random<Scalar>();
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int r1 = ei_random<int>(0,rows-1);
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int r2 = ei_random<int>(r1,rows-1);
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int c1 = ei_random<int>(0,cols-1);
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int c2 = ei_random<int>(c1,cols-1);
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//check row() and col()
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VERIFY_IS_APPROX(m1.col(c1).transpose(), m1.transpose().row(c1));
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VERIFY_IS_APPROX(square.row(r1).eigen2_dot(m1.col(c1)), (square.lazy() * m1.conjugate())(r1,c1));
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//check operator(), both constant and non-constant, on row() and col()
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m1.row(r1) += s1 * m1.row(r2);
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m1.col(c1) += s1 * m1.col(c2);
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//check block()
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Matrix<Scalar,Dynamic,Dynamic> b1(1,1); b1(0,0) = m1(r1,c1);
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RowVectorType br1(m1.block(r1,0,1,cols));
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VectorType bc1(m1.block(0,c1,rows,1));
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VERIFY_IS_APPROX(b1, m1.block(r1,c1,1,1));
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VERIFY_IS_APPROX(m1.row(r1), br1);
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VERIFY_IS_APPROX(m1.col(c1), bc1);
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//check operator(), both constant and non-constant, on block()
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m1.block(r1,c1,r2-r1+1,c2-c1+1) = s1 * m2.block(0, 0, r2-r1+1,c2-c1+1);
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m1.block(r1,c1,r2-r1+1,c2-c1+1)(r2-r1,c2-c1) = m2.block(0, 0, r2-r1+1,c2-c1+1)(0,0);
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//check minor()
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CheckMinor<Scalar, MatrixType::RowsAtCompileTime, MatrixType::ColsAtCompileTime> checkminor(m1,r1,c1);
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//check diagonal()
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VERIFY_IS_APPROX(m1.diagonal(), m1.transpose().diagonal());
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m2.diagonal() = 2 * m1.diagonal();
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m2.diagonal()[0] *= 3;
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VERIFY_IS_APPROX(m2.diagonal()[0], static_cast<Scalar>(6) * m1.diagonal()[0]);
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enum {
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BlockRows = EIGEN_SIZE_MIN_PREFER_FIXED(MatrixType::RowsAtCompileTime,2),
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BlockCols = EIGEN_SIZE_MIN_PREFER_FIXED(MatrixType::ColsAtCompileTime,5)
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};
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if (rows>=5 && cols>=8)
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{
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// test fixed block() as lvalue
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m1.template block<BlockRows,BlockCols>(1,1) *= s1;
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// test operator() on fixed block() both as constant and non-constant
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m1.template block<BlockRows,BlockCols>(1,1)(0, 3) = m1.template block<2,5>(1,1)(1,2);
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// check that fixed block() and block() agree
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Matrix<Scalar,Dynamic,Dynamic> b = m1.template block<BlockRows,BlockCols>(3,3);
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VERIFY_IS_APPROX(b, m1.block(3,3,BlockRows,BlockCols));
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}
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if (rows>2)
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{
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// test sub vectors
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VERIFY_IS_APPROX(v1.template start<2>(), v1.block(0,0,2,1));
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VERIFY_IS_APPROX(v1.template start<2>(), v1.start(2));
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VERIFY_IS_APPROX(v1.template start<2>(), v1.segment(0,2));
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VERIFY_IS_APPROX(v1.template start<2>(), v1.template segment<2>(0));
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int i = rows-2;
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VERIFY_IS_APPROX(v1.template end<2>(), v1.block(i,0,2,1));
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VERIFY_IS_APPROX(v1.template end<2>(), v1.end(2));
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VERIFY_IS_APPROX(v1.template end<2>(), v1.segment(i,2));
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VERIFY_IS_APPROX(v1.template end<2>(), v1.template segment<2>(i));
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i = ei_random(0,rows-2);
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VERIFY_IS_APPROX(v1.segment(i,2), v1.template segment<2>(i));
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}
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// stress some basic stuffs with block matrices
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VERIFY(ei_real(ones.col(c1).sum()) == RealScalar(rows));
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VERIFY(ei_real(ones.row(r1).sum()) == RealScalar(cols));
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VERIFY(ei_real(ones.col(c1).eigen2_dot(ones.col(c2))) == RealScalar(rows));
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VERIFY(ei_real(ones.row(r1).eigen2_dot(ones.row(r2))) == RealScalar(cols));
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}
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void test_eigen2_submatrices()
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{
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for(int i = 0; i < g_repeat; i++) {
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CALL_SUBTEST_1( submatrices(Matrix<float, 1, 1>()) );
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CALL_SUBTEST_2( submatrices(Matrix4d()) );
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CALL_SUBTEST_3( submatrices(MatrixXcf(3, 3)) );
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CALL_SUBTEST_4( submatrices(MatrixXi(8, 12)) );
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CALL_SUBTEST_5( submatrices(MatrixXcd(20, 20)) );
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CALL_SUBTEST_6( submatrices(MatrixXf(20, 20)) );
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}
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}
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