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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
#define EIGEN_NO_STATIC_ASSERT // otherwise we fail at compile time on unused paths
#include "main.h"
template<typename MatrixType, typename Index, typename Scalar> typename StormEigen::internal::enable_if<!NumTraits<typename MatrixType::Scalar>::IsComplex,typename MatrixType::Scalar>::type block_real_only(const MatrixType &m1, Index r1, Index r2, Index c1, Index c2, const Scalar& s1) { // check cwise-Functions:
VERIFY_IS_APPROX(m1.row(r1).cwiseMax(s1), m1.cwiseMax(s1).row(r1)); VERIFY_IS_APPROX(m1.col(c1).cwiseMin(s1), m1.cwiseMin(s1).col(c1));
VERIFY_IS_APPROX(m1.block(r1,c1,r2-r1+1,c2-c1+1).cwiseMin(s1), m1.cwiseMin(s1).block(r1,c1,r2-r1+1,c2-c1+1)); VERIFY_IS_APPROX(m1.block(r1,c1,r2-r1+1,c2-c1+1).cwiseMax(s1), m1.cwiseMax(s1).block(r1,c1,r2-r1+1,c2-c1+1)); return Scalar(0); }
template<typename MatrixType, typename Index, typename Scalar> typename StormEigen::internal::enable_if<NumTraits<typename MatrixType::Scalar>::IsComplex,typename MatrixType::Scalar>::type block_real_only(const MatrixType &, Index, Index, Index, Index, const Scalar&) { return Scalar(0); }
template<typename MatrixType> void block(const MatrixType& m) { typedef typename MatrixType::Index Index; typedef typename MatrixType::Scalar Scalar; typedef typename MatrixType::RealScalar RealScalar; typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType; typedef Matrix<Scalar, 1, MatrixType::ColsAtCompileTime> RowVectorType; typedef Matrix<Scalar, Dynamic, Dynamic> DynamicMatrixType; typedef Matrix<Scalar, Dynamic, 1> DynamicVectorType; Index rows = m.rows(); Index cols = m.cols();
MatrixType m1 = MatrixType::Random(rows, cols), m1_copy = m1, m2 = MatrixType::Random(rows, cols), m3(rows, cols), ones = MatrixType::Ones(rows, cols); VectorType v1 = VectorType::Random(rows);
Scalar s1 = internal::random<Scalar>();
Index r1 = internal::random<Index>(0,rows-1); Index r2 = internal::random<Index>(r1,rows-1); Index c1 = internal::random<Index>(0,cols-1); Index c2 = internal::random<Index>(c1,cols-1);
block_real_only(m1, r1, r2, c1, c1, s1);
//check row() and col()
VERIFY_IS_EQUAL(m1.col(c1).transpose(), m1.transpose().row(c1)); //check operator(), both constant and non-constant, on row() and col()
m1 = m1_copy; m1.row(r1) += s1 * m1_copy.row(r2); VERIFY_IS_APPROX(m1.row(r1), m1_copy.row(r1) + s1 * m1_copy.row(r2)); // check nested block xpr on lhs
m1.row(r1).row(0) += s1 * m1_copy.row(r2); VERIFY_IS_APPROX(m1.row(r1), m1_copy.row(r1) + Scalar(2) * s1 * m1_copy.row(r2)); m1 = m1_copy; m1.col(c1) += s1 * m1_copy.col(c2); VERIFY_IS_APPROX(m1.col(c1), m1_copy.col(c1) + s1 * m1_copy.col(c2)); m1.col(c1).col(0) += s1 * m1_copy.col(c2); VERIFY_IS_APPROX(m1.col(c1), m1_copy.col(c1) + Scalar(2) * s1 * m1_copy.col(c2)); //check block()
Matrix<Scalar,Dynamic,Dynamic> b1(1,1); b1(0,0) = m1(r1,c1);
RowVectorType br1(m1.block(r1,0,1,cols)); VectorType bc1(m1.block(0,c1,rows,1)); VERIFY_IS_EQUAL(b1, m1.block(r1,c1,1,1)); VERIFY_IS_EQUAL(m1.row(r1), br1); VERIFY_IS_EQUAL(m1.col(c1), bc1); //check operator(), both constant and non-constant, on block()
m1.block(r1,c1,r2-r1+1,c2-c1+1) = s1 * m2.block(0, 0, r2-r1+1,c2-c1+1); 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);
enum { BlockRows = 2, BlockCols = 5 }; if (rows>=5 && cols>=8) { // test fixed block() as lvalue
m1.template block<BlockRows,BlockCols>(1,1) *= s1; // test operator() on fixed block() both as constant and non-constant
m1.template block<BlockRows,BlockCols>(1,1)(0, 3) = m1.template block<2,5>(1,1)(1,2); // check that fixed block() and block() agree
Matrix<Scalar,Dynamic,Dynamic> b = m1.template block<BlockRows,BlockCols>(3,3); VERIFY_IS_EQUAL(b, m1.block(3,3,BlockRows,BlockCols));
// same tests with mixed fixed/dynamic size
m1.template block<BlockRows,Dynamic>(1,1,BlockRows,BlockCols) *= s1; m1.template block<BlockRows,Dynamic>(1,1,BlockRows,BlockCols)(0,3) = m1.template block<2,5>(1,1)(1,2); Matrix<Scalar,Dynamic,Dynamic> b2 = m1.template block<Dynamic,BlockCols>(3,3,2,5); VERIFY_IS_EQUAL(b2, m1.block(3,3,BlockRows,BlockCols)); }
if (rows>2) { // test sub vectors
VERIFY_IS_EQUAL(v1.template head<2>(), v1.block(0,0,2,1)); VERIFY_IS_EQUAL(v1.template head<2>(), v1.head(2)); VERIFY_IS_EQUAL(v1.template head<2>(), v1.segment(0,2)); VERIFY_IS_EQUAL(v1.template head<2>(), v1.template segment<2>(0)); Index i = rows-2; VERIFY_IS_EQUAL(v1.template tail<2>(), v1.block(i,0,2,1)); VERIFY_IS_EQUAL(v1.template tail<2>(), v1.tail(2)); VERIFY_IS_EQUAL(v1.template tail<2>(), v1.segment(i,2)); VERIFY_IS_EQUAL(v1.template tail<2>(), v1.template segment<2>(i)); i = internal::random<Index>(0,rows-2); VERIFY_IS_EQUAL(v1.segment(i,2), v1.template segment<2>(i)); }
// stress some basic stuffs with block matrices
VERIFY(numext::real(ones.col(c1).sum()) == RealScalar(rows)); VERIFY(numext::real(ones.row(r1).sum()) == RealScalar(cols));
VERIFY(numext::real(ones.col(c1).dot(ones.col(c2))) == RealScalar(rows)); VERIFY(numext::real(ones.row(r1).dot(ones.row(r2))) == RealScalar(cols)); // chekc that linear acccessors works on blocks
m1 = m1_copy; if((MatrixType::Flags&RowMajorBit)==0) VERIFY_IS_EQUAL(m1.leftCols(c1).coeff(r1+c1*rows), m1(r1,c1)); else VERIFY_IS_EQUAL(m1.topRows(r1).coeff(c1+r1*cols), m1(r1,c1));
// now test some block-inside-of-block.
// expressions with direct access
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)) ); VERIFY_IS_EQUAL( (m1.block(r1,c1,r2-r1+1,c2-c1+1).row(0)) , (m1.row(r1).segment(c1,c2-c1+1)) ); VERIFY_IS_EQUAL( (m1.block(r1,c1,r2-r1+1,c2-c1+1).col(0)) , (m1.col(c1).segment(r1,r2-r1+1)) ); VERIFY_IS_EQUAL( (m1.block(r1,c1,r2-r1+1,c2-c1+1).transpose().col(0)) , (m1.row(r1).segment(c1,c2-c1+1)).transpose() ); VERIFY_IS_EQUAL( (m1.transpose().block(c1,r1,c2-c1+1,r2-r1+1).col(0)) , (m1.row(r1).segment(c1,c2-c1+1)).transpose() );
// expressions without direct access
VERIFY_IS_APPROX( ((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)) ); VERIFY_IS_APPROX( ((m1+m2).block(r1,c1,r2-r1+1,c2-c1+1).row(0)) , ((m1+m2).row(r1).segment(c1,c2-c1+1)) ); VERIFY_IS_APPROX( ((m1+m2).block(r1,c1,r2-r1+1,c2-c1+1).col(0)) , ((m1+m2).col(c1).segment(r1,r2-r1+1)) ); VERIFY_IS_APPROX( ((m1+m2).block(r1,c1,r2-r1+1,c2-c1+1).transpose().col(0)) , ((m1+m2).row(r1).segment(c1,c2-c1+1)).transpose() ); VERIFY_IS_APPROX( ((m1+m2).transpose().block(c1,r1,c2-c1+1,r2-r1+1).col(0)) , ((m1+m2).row(r1).segment(c1,c2-c1+1)).transpose() );
// evaluation into plain matrices from expressions with direct access (stress MapBase)
DynamicMatrixType dm; DynamicVectorType dv; dm.setZero(); dm = m1.block(r1,c1,rows-r1,cols-c1).block(r2-r1,c2-c1,rows-r2,cols-c2); VERIFY_IS_EQUAL(dm, (m1.block(r2,c2,rows-r2,cols-c2))); dm.setZero(); dv.setZero(); dm = m1.block(r1,c1,r2-r1+1,c2-c1+1).row(0).transpose(); dv = m1.row(r1).segment(c1,c2-c1+1); VERIFY_IS_EQUAL(dv, dm); dm.setZero(); dv.setZero(); dm = m1.col(c1).segment(r1,r2-r1+1); dv = m1.block(r1,c1,r2-r1+1,c2-c1+1).col(0); VERIFY_IS_EQUAL(dv, dm); dm.setZero(); dv.setZero(); dm = m1.block(r1,c1,r2-r1+1,c2-c1+1).transpose().col(0); dv = m1.row(r1).segment(c1,c2-c1+1); VERIFY_IS_EQUAL(dv, dm); dm.setZero(); dv.setZero(); dm = m1.row(r1).segment(c1,c2-c1+1).transpose(); dv = m1.transpose().block(c1,r1,c2-c1+1,r2-r1+1).col(0); VERIFY_IS_EQUAL(dv, dm); }
template<typename MatrixType> void compare_using_data_and_stride(const MatrixType& m) { typedef typename MatrixType::Index Index; Index rows = m.rows(); Index cols = m.cols(); Index size = m.size(); Index innerStride = m.innerStride(); Index outerStride = m.outerStride(); Index rowStride = m.rowStride(); Index colStride = m.colStride(); const typename MatrixType::Scalar* data = m.data();
for(int j=0;j<cols;++j) for(int i=0;i<rows;++i) VERIFY(m.coeff(i,j) == data[i*rowStride + j*colStride]);
if(!MatrixType::IsVectorAtCompileTime) { for(int j=0;j<cols;++j) for(int i=0;i<rows;++i) VERIFY(m.coeff(i,j) == data[(MatrixType::Flags&RowMajorBit) ? i*outerStride + j*innerStride : j*outerStride + i*innerStride]); }
if(MatrixType::IsVectorAtCompileTime) { VERIFY(innerStride == int((&m.coeff(1))-(&m.coeff(0)))); for (int i=0;i<size;++i) VERIFY(m.coeff(i) == data[i*innerStride]); } }
template<typename MatrixType> void data_and_stride(const MatrixType& m) { typedef typename MatrixType::Index Index; Index rows = m.rows(); Index cols = m.cols();
Index r1 = internal::random<Index>(0,rows-1); Index r2 = internal::random<Index>(r1,rows-1); Index c1 = internal::random<Index>(0,cols-1); Index c2 = internal::random<Index>(c1,cols-1);
MatrixType m1 = MatrixType::Random(rows, cols); compare_using_data_and_stride(m1.block(r1, c1, r2-r1+1, c2-c1+1)); compare_using_data_and_stride(m1.transpose().block(c1, r1, c2-c1+1, r2-r1+1)); compare_using_data_and_stride(m1.row(r1)); compare_using_data_and_stride(m1.col(c1)); compare_using_data_and_stride(m1.row(r1).transpose()); compare_using_data_and_stride(m1.col(c1).transpose()); }
void test_block() { for(int i = 0; i < g_repeat; i++) { CALL_SUBTEST_1( block(Matrix<float, 1, 1>()) ); CALL_SUBTEST_2( block(Matrix4d()) ); CALL_SUBTEST_3( block(MatrixXcf(3, 3)) ); CALL_SUBTEST_4( block(MatrixXi(8, 12)) ); CALL_SUBTEST_5( block(MatrixXcd(20, 20)) ); CALL_SUBTEST_6( block(MatrixXf(20, 20)) );
CALL_SUBTEST_8( block(Matrix<float,Dynamic,4>(3, 4)) );
#ifndef EIGEN_DEFAULT_TO_ROW_MAJOR
CALL_SUBTEST_6( data_and_stride(MatrixXf(internal::random(5,50), internal::random(5,50))) ); CALL_SUBTEST_7( data_and_stride(Matrix<int,Dynamic,Dynamic,RowMajor>(internal::random(5,50), internal::random(5,50))) ); #endif
} }
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