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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2011 Kolja Brix <brix@igpm.rwth-aachen.de>
// Copyright (C) 2011 Andreas Platen <andiplaten@gmx.de>
//
// Eigen is free software; you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public
// License as published by the Free Software Foundation; either
// version 3 of the License, or (at your option) any later version.
//
// Alternatively, you can redistribute it and/or
// modify it under the terms of the GNU General Public License as
// published by the Free Software Foundation; either version 2 of
// the License, or (at your option) any later version.
//
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
// GNU General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License and a copy of the GNU General Public License along with
// Eigen. If not, see <http://www.gnu.org/licenses/>.
#include "sparse.h"
#include <Eigen/SparseExtra>
#include <Eigen/KroneckerProduct>
template<typename MatrixType>
void check_dimension(const MatrixType& ab, const unsigned int rows, const unsigned int cols)
{
VERIFY_IS_EQUAL(ab.rows(), rows);
VERIFY_IS_EQUAL(ab.cols(), cols);
}
template<typename MatrixType>
void check_kronecker_product(const MatrixType& ab)
{
VERIFY_IS_EQUAL(ab.rows(), 6);
VERIFY_IS_EQUAL(ab.cols(), 6);
VERIFY_IS_EQUAL(ab.nonZeros(), 36);
VERIFY_IS_APPROX(ab.coeff(0,0), -0.4017367630386106);
VERIFY_IS_APPROX(ab.coeff(0,1), 0.1056863433932735);
VERIFY_IS_APPROX(ab.coeff(0,2), -0.7255206194554212);
VERIFY_IS_APPROX(ab.coeff(0,3), 0.1908653336744706);
VERIFY_IS_APPROX(ab.coeff(0,4), 0.350864567234111);
VERIFY_IS_APPROX(ab.coeff(0,5), -0.0923032108308013);
VERIFY_IS_APPROX(ab.coeff(1,0), 0.415417514804677);
VERIFY_IS_APPROX(ab.coeff(1,1), -0.2369227701722048);
VERIFY_IS_APPROX(ab.coeff(1,2), 0.7502275131458511);
VERIFY_IS_APPROX(ab.coeff(1,3), -0.4278731019742696);
VERIFY_IS_APPROX(ab.coeff(1,4), -0.3628129162264507);
VERIFY_IS_APPROX(ab.coeff(1,5), 0.2069210808481275);
VERIFY_IS_APPROX(ab.coeff(2,0), 0.05465890160863986);
VERIFY_IS_APPROX(ab.coeff(2,1), -0.2634092511419858);
VERIFY_IS_APPROX(ab.coeff(2,2), 0.09871180285793758);
VERIFY_IS_APPROX(ab.coeff(2,3), -0.4757066334017702);
VERIFY_IS_APPROX(ab.coeff(2,4), -0.04773740823058334);
VERIFY_IS_APPROX(ab.coeff(2,5), 0.2300535609645254);
VERIFY_IS_APPROX(ab.coeff(3,0), -0.8172945853260133);
VERIFY_IS_APPROX(ab.coeff(3,1), 0.2150086428359221);
VERIFY_IS_APPROX(ab.coeff(3,2), 0.5825113847292743);
VERIFY_IS_APPROX(ab.coeff(3,3), -0.1532433770097174);
VERIFY_IS_APPROX(ab.coeff(3,4), -0.329383387282399);
VERIFY_IS_APPROX(ab.coeff(3,5), 0.08665207912033064);
VERIFY_IS_APPROX(ab.coeff(4,0), 0.8451267514863225);
VERIFY_IS_APPROX(ab.coeff(4,1), -0.481996458918977);
VERIFY_IS_APPROX(ab.coeff(4,2), -0.6023482390791535);
VERIFY_IS_APPROX(ab.coeff(4,3), 0.3435339347164565);
VERIFY_IS_APPROX(ab.coeff(4,4), 0.3406002157428891);
VERIFY_IS_APPROX(ab.coeff(4,5), -0.1942526344200915);
VERIFY_IS_APPROX(ab.coeff(5,0), 0.1111982482925399);
VERIFY_IS_APPROX(ab.coeff(5,1), -0.5358806424754169);
VERIFY_IS_APPROX(ab.coeff(5,2), -0.07925446559335647);
VERIFY_IS_APPROX(ab.coeff(5,3), 0.3819388757769038);
VERIFY_IS_APPROX(ab.coeff(5,4), 0.04481475387219876);
VERIFY_IS_APPROX(ab.coeff(5,5), -0.2159688616158057);
}
template<typename MatrixType>
void check_sparse_kronecker_product(const MatrixType& ab)
{
VERIFY_IS_EQUAL(ab.rows(), 12);
VERIFY_IS_EQUAL(ab.cols(), 10);
VERIFY_IS_EQUAL(ab.nonZeros(), 3*2);
VERIFY_IS_APPROX(ab.coeff(3,0), -0.04);
VERIFY_IS_APPROX(ab.coeff(5,1), 0.05);
VERIFY_IS_APPROX(ab.coeff(0,6), -0.08);
VERIFY_IS_APPROX(ab.coeff(2,7), 0.10);
VERIFY_IS_APPROX(ab.coeff(6,8), 0.12);
VERIFY_IS_APPROX(ab.coeff(8,9), -0.15);
}
void test_kronecker_product()
{
// DM = dense matrix; SM = sparse matrix
Matrix<double, 2, 3> DM_a;
MatrixXd DM_b(3,2);
SparseMatrix<double> SM_a(2,3);
SparseMatrix<double> SM_b(3,2);
SM_a.insert(0,0) = DM_a(0,0) = -0.4461540300782201;
SM_a.insert(0,1) = DM_a(0,1) = -0.8057364375283049;
SM_a.insert(0,2) = DM_a(0,2) = 0.3896572459516341;
SM_a.insert(1,0) = DM_a(1,0) = -0.9076572187376921;
SM_a.insert(1,1) = DM_a(1,1) = 0.6469156566545853;
SM_a.insert(1,2) = DM_a(1,2) = -0.3658010398782789;
SM_b.insert(0,0) = DM_b(0,0) = 0.9004440976767099;
SM_b.insert(0,1) = DM_b(0,1) = -0.2368830858139832;
SM_b.insert(1,0) = DM_b(1,0) = -0.9311078389941825;
SM_b.insert(1,1) = DM_b(1,1) = 0.5310335762980047;
SM_b.insert(2,0) = DM_b(2,0) = -0.1225112806872035;
SM_b.insert(2,1) = DM_b(2,1) = 0.5903998022741264;
SparseMatrix<double,RowMajor> SM_row_a(SM_a), SM_row_b(SM_b);
// test kroneckerProduct(DM_block,DM,DM_fixedSize)
Matrix<double, 6, 6> DM_fix_ab;
DM_fix_ab(0,0)=37.0;
kroneckerProduct(DM_a.block(0,0,2,3),DM_b,DM_fix_ab);
CALL_SUBTEST(check_kronecker_product(DM_fix_ab));
// test kroneckerProduct(DM,DM,DM_block)
MatrixXd DM_block_ab(10,15);
DM_block_ab(0,0)=37.0;
kroneckerProduct(DM_a,DM_b,DM_block_ab.block(2,5,6,6));
CALL_SUBTEST(check_kronecker_product(DM_block_ab.block(2,5,6,6)));
// test kroneckerProduct(DM,DM,DM)
MatrixXd DM_ab(1,5);
DM_ab(0,0)=37.0;
kroneckerProduct(DM_a,DM_b,DM_ab);
CALL_SUBTEST(check_kronecker_product(DM_ab));
// test kroneckerProduct(SM,DM,SM)
SparseMatrix<double> SM_ab(1,20);
SM_ab.insert(0,0)=37.0;
kroneckerProduct(SM_a,DM_b,SM_ab);
CALL_SUBTEST(check_kronecker_product(SM_ab));
SparseMatrix<double,RowMajor> SM_ab2(10,3);
SM_ab2.insert(0,0)=37.0;
kroneckerProduct(SM_a,DM_b,SM_ab2);
CALL_SUBTEST(check_kronecker_product(SM_ab2));
// test kroneckerProduct(DM,SM,SM)
SM_ab.insert(0,0)=37.0;
kroneckerProduct(DM_a,SM_b,SM_ab);
CALL_SUBTEST(check_kronecker_product(SM_ab));
SM_ab2.insert(0,0)=37.0;
kroneckerProduct(DM_a,SM_b,SM_ab2);
CALL_SUBTEST(check_kronecker_product(SM_ab2));
// test kroneckerProduct(SM,SM,SM)
SM_ab.resize(2,33);
SM_ab.insert(0,0)=37.0;
kroneckerProduct(SM_a,SM_b,SM_ab);
CALL_SUBTEST(check_kronecker_product(SM_ab));
SM_ab2.resize(5,11);
SM_ab2.insert(0,0)=37.0;
kroneckerProduct(SM_a,SM_b,SM_ab2);
CALL_SUBTEST(check_kronecker_product(SM_ab2));
// test kroneckerProduct(SM,SM,SM) with sparse pattern
SM_a.resize(4,5);
SM_b.resize(3,2);
SM_a.resizeNonZeros(0);
SM_b.resizeNonZeros(0);
SM_a.insert(1,0) = -0.1;
SM_a.insert(0,3) = -0.2;
SM_a.insert(2,4) = 0.3;
SM_a.finalize();
SM_b.insert(0,0) = 0.4;
SM_b.insert(2,1) = -0.5;
SM_b.finalize();
SM_ab.resize(1,1);
SM_ab.insert(0,0)=37.0;
kroneckerProduct(SM_a,SM_b,SM_ab);
CALL_SUBTEST(check_sparse_kronecker_product(SM_ab));
// test dimension of result of kroneckerProduct(DM,DM,DM)
MatrixXd DM_a2(2,1);
MatrixXd DM_b2(5,4);
MatrixXd DM_ab2;
kroneckerProduct(DM_a2,DM_b2,DM_ab2);
CALL_SUBTEST(check_dimension(DM_ab2,2*5,1*4));
DM_a2.resize(10,9);
DM_b2.resize(4,8);
kroneckerProduct(DM_a2,DM_b2,DM_ab2);
CALL_SUBTEST(check_dimension(DM_ab2,10*4,9*8));
}
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