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226 lines
8.8 KiB
C++
226 lines
8.8 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) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
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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> void block(const MatrixType& m)
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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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typedef Matrix<Scalar, Dynamic, Dynamic> DynamicMatrixType;
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typedef Matrix<Scalar, Dynamic, 1> DynamicVectorType;
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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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mzero = MatrixType::Zero(rows, cols),
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ones = MatrixType::Ones(rows, cols);
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VectorType v1 = VectorType::Random(rows),
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v2 = VectorType::Random(rows),
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v3 = VectorType::Random(rows),
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vzero = VectorType::Zero(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_EQUAL(m1.col(c1).transpose(), m1.transpose().row(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_EQUAL(b1, m1.block(r1,c1,1,1));
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VERIFY_IS_EQUAL(m1.row(r1), br1);
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VERIFY_IS_EQUAL(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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const int BlockRows = EIGEN_ENUM_MIN(MatrixType::RowsAtCompileTime,2);
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const int BlockCols = EIGEN_ENUM_MIN(MatrixType::ColsAtCompileTime,5);
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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_EQUAL(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_EQUAL(v1.template head<2>(), v1.block(0,0,2,1));
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VERIFY_IS_EQUAL(v1.template head<2>(), v1.head(2));
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VERIFY_IS_EQUAL(v1.template head<2>(), v1.segment(0,2));
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VERIFY_IS_EQUAL(v1.template head<2>(), v1.template segment<2>(0));
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int i = rows-2;
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VERIFY_IS_EQUAL(v1.template tail<2>(), v1.block(i,0,2,1));
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VERIFY_IS_EQUAL(v1.template tail<2>(), v1.tail(2));
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VERIFY_IS_EQUAL(v1.template tail<2>(), v1.segment(i,2));
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VERIFY_IS_EQUAL(v1.template tail<2>(), v1.template segment<2>(i));
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i = ei_random(0,rows-2);
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VERIFY_IS_EQUAL(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).dot(ones.col(c2))) == RealScalar(rows));
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VERIFY(ei_real(ones.row(r1).dot(ones.row(r2))) == RealScalar(cols));
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// now test some block-inside-of-block.
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// expressions with direct access
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VERIFY_IS_EQUAL( (m1.block(r1,c1,rows-r1,cols-c1).block(r2-r1,c2-c1,rows-r2,cols-c2)) , (m1.block(r2,c2,rows-r2,cols-c2)) );
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VERIFY_IS_EQUAL( (m1.block(r1,c1,r2-r1+1,c2-c1+1).row(0)) , (m1.row(r1).segment(c1,c2-c1+1)) );
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VERIFY_IS_EQUAL( (m1.block(r1,c1,r2-r1+1,c2-c1+1).col(0)) , (m1.col(c1).segment(r1,r2-r1+1)) );
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VERIFY_IS_EQUAL( (m1.block(r1,c1,r2-r1+1,c2-c1+1).transpose().col(0)) , (m1.row(r1).segment(c1,c2-c1+1)) );
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VERIFY_IS_EQUAL( (m1.transpose().block(c1,r1,c2-c1+1,r2-r1+1).col(0)) , (m1.row(r1).segment(c1,c2-c1+1)) );
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// expressions without direct access
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VERIFY_IS_EQUAL( ((m1+m2).block(r1,c1,rows-r1,cols-c1).block(r2-r1,c2-c1,rows-r2,cols-c2)) , ((m1+m2).block(r2,c2,rows-r2,cols-c2)) );
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VERIFY_IS_EQUAL( ((m1+m2).block(r1,c1,r2-r1+1,c2-c1+1).row(0)) , ((m1+m2).row(r1).segment(c1,c2-c1+1)) );
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VERIFY_IS_EQUAL( ((m1+m2).block(r1,c1,r2-r1+1,c2-c1+1).col(0)) , ((m1+m2).col(c1).segment(r1,r2-r1+1)) );
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VERIFY_IS_EQUAL( ((m1+m2).block(r1,c1,r2-r1+1,c2-c1+1).transpose().col(0)) , ((m1+m2).row(r1).segment(c1,c2-c1+1)) );
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VERIFY_IS_EQUAL( ((m1+m2).transpose().block(c1,r1,c2-c1+1,r2-r1+1).col(0)) , ((m1+m2).row(r1).segment(c1,c2-c1+1)) );
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// evaluation into plain matrices from expressions with direct access (stress MapBase)
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DynamicMatrixType dm;
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DynamicVectorType dv;
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dm.setZero();
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dm = m1.block(r1,c1,rows-r1,cols-c1).block(r2-r1,c2-c1,rows-r2,cols-c2);
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VERIFY_IS_EQUAL(dm, (m1.block(r2,c2,rows-r2,cols-c2)));
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dm.setZero();
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dv.setZero();
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dm = m1.block(r1,c1,r2-r1+1,c2-c1+1).row(0).transpose();
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dv = m1.row(r1).segment(c1,c2-c1+1);
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VERIFY_IS_EQUAL(dv, dm);
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dm.setZero();
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dv.setZero();
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dm = m1.col(c1).segment(r1,r2-r1+1);
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dv = m1.block(r1,c1,r2-r1+1,c2-c1+1).col(0);
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VERIFY_IS_EQUAL(dv, dm);
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dm.setZero();
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dv.setZero();
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dm = m1.block(r1,c1,r2-r1+1,c2-c1+1).transpose().col(0);
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dv = m1.row(r1).segment(c1,c2-c1+1);
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VERIFY_IS_EQUAL(dv, dm);
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dm.setZero();
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dv.setZero();
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dm = m1.row(r1).segment(c1,c2-c1+1).transpose();
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dv = m1.transpose().block(c1,r1,c2-c1+1,r2-r1+1).col(0);
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VERIFY_IS_EQUAL(dv, dm);
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}
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template<typename MatrixType>
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void compare_using_data_and_stride(const MatrixType& m)
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{
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int rows = m.rows();
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int cols = m.cols();
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int size = m.size();
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int innerStride = m.innerStride();
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int outerStride = m.outerStride();
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int rowStride = m.rowStride();
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int colStride = m.colStride();
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const typename MatrixType::Scalar* data = m.data();
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for(int j=0;j<cols;++j)
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for(int i=0;i<rows;++i)
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VERIFY(m.coeff(i,j) == data[i*rowStride + j*colStride]);
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if(!MatrixType::IsVectorAtCompileTime)
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{
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for(int j=0;j<cols;++j)
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for(int i=0;i<rows;++i)
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VERIFY(m.coeff(i,j) == data[(MatrixType::Flags&RowMajorBit)
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? i*outerStride + j*innerStride
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: j*outerStride + i*innerStride]);
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}
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if(MatrixType::IsVectorAtCompileTime)
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{
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VERIFY(innerStride == int((&m.coeff(1))-(&m.coeff(0))));
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for (int i=0;i<size;++i)
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VERIFY(m.coeff(i) == data[i*innerStride]);
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}
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}
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template<typename MatrixType>
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void data_and_stride(const MatrixType& m)
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{
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int rows = m.rows();
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int cols = m.cols();
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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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MatrixType m1 = MatrixType::Random(rows, cols);
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compare_using_data_and_stride(m1.block(r1, c1, r2-r1+1, c2-c1+1));
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compare_using_data_and_stride(m1.transpose().block(c1, r1, c2-c1+1, r2-r1+1));
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compare_using_data_and_stride(m1.row(r1));
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compare_using_data_and_stride(m1.col(c1));
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compare_using_data_and_stride(m1.row(r1).transpose());
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compare_using_data_and_stride(m1.col(c1).transpose());
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}
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void test_block()
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{
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for(int i = 0; i < g_repeat; i++) {
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CALL_SUBTEST_1( block(Matrix<float, 1, 1>()) );
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CALL_SUBTEST_2( block(Matrix4d()) );
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CALL_SUBTEST_3( block(MatrixXcf(3, 3)) );
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CALL_SUBTEST_4( block(MatrixXi(8, 12)) );
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CALL_SUBTEST_5( block(MatrixXcd(20, 20)) );
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CALL_SUBTEST_6( block(MatrixXf(20, 20)) );
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CALL_SUBTEST_8( block(Matrix<float,Dynamic,4>(3, 4)) );
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#ifndef EIGEN_DEFAULT_TO_ROW_MAJOR
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CALL_SUBTEST_6( data_and_stride(MatrixXf(ei_random(5,50), ei_random(5,50))) );
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CALL_SUBTEST_7( data_and_stride(Matrix<int,Dynamic,Dynamic,RowMajor>(ei_random(5,50), ei_random(5,50))) );
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#endif
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}
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}
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