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82f0ce2726
This provide several advantages: - more flexibility in designing unit tests - unit tests can be glued to speed up compilation - unit tests are compiled with same predefined macros, which is a requirement for zapcc
253 lines
8.9 KiB
C++
253 lines
8.9 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) 2011 Kolja Brix <brix@igpm.rwth-aachen.de>
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// Copyright (C) 2011 Andreas Platen <andiplaten@gmx.de>
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// Copyright (C) 2012 Chen-Pang He <jdh8@ms63.hinet.net>
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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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#ifdef EIGEN_TEST_PART_1
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#include "sparse.h"
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#include <Eigen/SparseExtra>
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#include <Eigen/KroneckerProduct>
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template<typename MatrixType>
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void check_dimension(const MatrixType& ab, const int rows, const int cols)
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{
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VERIFY_IS_EQUAL(ab.rows(), rows);
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VERIFY_IS_EQUAL(ab.cols(), cols);
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}
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template<typename MatrixType>
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void check_kronecker_product(const MatrixType& ab)
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{
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VERIFY_IS_EQUAL(ab.rows(), 6);
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VERIFY_IS_EQUAL(ab.cols(), 6);
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VERIFY_IS_EQUAL(ab.nonZeros(), 36);
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VERIFY_IS_APPROX(ab.coeff(0,0), -0.4017367630386106);
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VERIFY_IS_APPROX(ab.coeff(0,1), 0.1056863433932735);
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VERIFY_IS_APPROX(ab.coeff(0,2), -0.7255206194554212);
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VERIFY_IS_APPROX(ab.coeff(0,3), 0.1908653336744706);
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VERIFY_IS_APPROX(ab.coeff(0,4), 0.350864567234111);
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VERIFY_IS_APPROX(ab.coeff(0,5), -0.0923032108308013);
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VERIFY_IS_APPROX(ab.coeff(1,0), 0.415417514804677);
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VERIFY_IS_APPROX(ab.coeff(1,1), -0.2369227701722048);
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VERIFY_IS_APPROX(ab.coeff(1,2), 0.7502275131458511);
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VERIFY_IS_APPROX(ab.coeff(1,3), -0.4278731019742696);
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VERIFY_IS_APPROX(ab.coeff(1,4), -0.3628129162264507);
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VERIFY_IS_APPROX(ab.coeff(1,5), 0.2069210808481275);
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VERIFY_IS_APPROX(ab.coeff(2,0), 0.05465890160863986);
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VERIFY_IS_APPROX(ab.coeff(2,1), -0.2634092511419858);
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VERIFY_IS_APPROX(ab.coeff(2,2), 0.09871180285793758);
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VERIFY_IS_APPROX(ab.coeff(2,3), -0.4757066334017702);
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VERIFY_IS_APPROX(ab.coeff(2,4), -0.04773740823058334);
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VERIFY_IS_APPROX(ab.coeff(2,5), 0.2300535609645254);
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VERIFY_IS_APPROX(ab.coeff(3,0), -0.8172945853260133);
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VERIFY_IS_APPROX(ab.coeff(3,1), 0.2150086428359221);
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VERIFY_IS_APPROX(ab.coeff(3,2), 0.5825113847292743);
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VERIFY_IS_APPROX(ab.coeff(3,3), -0.1532433770097174);
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VERIFY_IS_APPROX(ab.coeff(3,4), -0.329383387282399);
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VERIFY_IS_APPROX(ab.coeff(3,5), 0.08665207912033064);
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VERIFY_IS_APPROX(ab.coeff(4,0), 0.8451267514863225);
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VERIFY_IS_APPROX(ab.coeff(4,1), -0.481996458918977);
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VERIFY_IS_APPROX(ab.coeff(4,2), -0.6023482390791535);
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VERIFY_IS_APPROX(ab.coeff(4,3), 0.3435339347164565);
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VERIFY_IS_APPROX(ab.coeff(4,4), 0.3406002157428891);
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VERIFY_IS_APPROX(ab.coeff(4,5), -0.1942526344200915);
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VERIFY_IS_APPROX(ab.coeff(5,0), 0.1111982482925399);
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VERIFY_IS_APPROX(ab.coeff(5,1), -0.5358806424754169);
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VERIFY_IS_APPROX(ab.coeff(5,2), -0.07925446559335647);
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VERIFY_IS_APPROX(ab.coeff(5,3), 0.3819388757769038);
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VERIFY_IS_APPROX(ab.coeff(5,4), 0.04481475387219876);
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VERIFY_IS_APPROX(ab.coeff(5,5), -0.2159688616158057);
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}
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template<typename MatrixType>
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void check_sparse_kronecker_product(const MatrixType& ab)
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{
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VERIFY_IS_EQUAL(ab.rows(), 12);
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VERIFY_IS_EQUAL(ab.cols(), 10);
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VERIFY_IS_EQUAL(ab.nonZeros(), 3*2);
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VERIFY_IS_APPROX(ab.coeff(3,0), -0.04);
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VERIFY_IS_APPROX(ab.coeff(5,1), 0.05);
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VERIFY_IS_APPROX(ab.coeff(0,6), -0.08);
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VERIFY_IS_APPROX(ab.coeff(2,7), 0.10);
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VERIFY_IS_APPROX(ab.coeff(6,8), 0.12);
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VERIFY_IS_APPROX(ab.coeff(8,9), -0.15);
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}
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EIGEN_DECLARE_TEST(kronecker_product)
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{
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// DM = dense matrix; SM = sparse matrix
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Matrix<double, 2, 3> DM_a;
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SparseMatrix<double> SM_a(2,3);
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SM_a.insert(0,0) = DM_a.coeffRef(0,0) = -0.4461540300782201;
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SM_a.insert(0,1) = DM_a.coeffRef(0,1) = -0.8057364375283049;
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SM_a.insert(0,2) = DM_a.coeffRef(0,2) = 0.3896572459516341;
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SM_a.insert(1,0) = DM_a.coeffRef(1,0) = -0.9076572187376921;
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SM_a.insert(1,1) = DM_a.coeffRef(1,1) = 0.6469156566545853;
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SM_a.insert(1,2) = DM_a.coeffRef(1,2) = -0.3658010398782789;
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MatrixXd DM_b(3,2);
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SparseMatrix<double> SM_b(3,2);
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SM_b.insert(0,0) = DM_b.coeffRef(0,0) = 0.9004440976767099;
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SM_b.insert(0,1) = DM_b.coeffRef(0,1) = -0.2368830858139832;
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SM_b.insert(1,0) = DM_b.coeffRef(1,0) = -0.9311078389941825;
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SM_b.insert(1,1) = DM_b.coeffRef(1,1) = 0.5310335762980047;
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SM_b.insert(2,0) = DM_b.coeffRef(2,0) = -0.1225112806872035;
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SM_b.insert(2,1) = DM_b.coeffRef(2,1) = 0.5903998022741264;
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SparseMatrix<double,RowMajor> SM_row_a(SM_a), SM_row_b(SM_b);
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// test DM_fixedSize = kroneckerProduct(DM_block,DM)
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Matrix<double, 6, 6> DM_fix_ab = kroneckerProduct(DM_a.topLeftCorner<2,3>(),DM_b);
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CALL_SUBTEST(check_kronecker_product(DM_fix_ab));
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CALL_SUBTEST(check_kronecker_product(kroneckerProduct(DM_a.topLeftCorner<2,3>(),DM_b)));
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for(int i=0;i<DM_fix_ab.rows();++i)
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for(int j=0;j<DM_fix_ab.cols();++j)
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VERIFY_IS_APPROX(kroneckerProduct(DM_a,DM_b).coeff(i,j), DM_fix_ab(i,j));
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// test DM_block = kroneckerProduct(DM,DM)
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MatrixXd DM_block_ab(10,15);
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DM_block_ab.block<6,6>(2,5) = kroneckerProduct(DM_a,DM_b);
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CALL_SUBTEST(check_kronecker_product(DM_block_ab.block<6,6>(2,5)));
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// test DM = kroneckerProduct(DM,DM)
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MatrixXd DM_ab = kroneckerProduct(DM_a,DM_b);
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CALL_SUBTEST(check_kronecker_product(DM_ab));
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CALL_SUBTEST(check_kronecker_product(kroneckerProduct(DM_a,DM_b)));
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// test SM = kroneckerProduct(SM,DM)
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SparseMatrix<double> SM_ab = kroneckerProduct(SM_a,DM_b);
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CALL_SUBTEST(check_kronecker_product(SM_ab));
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SparseMatrix<double,RowMajor> SM_ab2 = kroneckerProduct(SM_a,DM_b);
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CALL_SUBTEST(check_kronecker_product(SM_ab2));
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CALL_SUBTEST(check_kronecker_product(kroneckerProduct(SM_a,DM_b)));
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// test SM = kroneckerProduct(DM,SM)
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SM_ab.setZero();
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SM_ab.insert(0,0)=37.0;
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SM_ab = kroneckerProduct(DM_a,SM_b);
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CALL_SUBTEST(check_kronecker_product(SM_ab));
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SM_ab2.setZero();
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SM_ab2.insert(0,0)=37.0;
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SM_ab2 = kroneckerProduct(DM_a,SM_b);
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CALL_SUBTEST(check_kronecker_product(SM_ab2));
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CALL_SUBTEST(check_kronecker_product(kroneckerProduct(DM_a,SM_b)));
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// test SM = kroneckerProduct(SM,SM)
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SM_ab.resize(2,33);
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SM_ab.insert(0,0)=37.0;
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SM_ab = kroneckerProduct(SM_a,SM_b);
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CALL_SUBTEST(check_kronecker_product(SM_ab));
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SM_ab2.resize(5,11);
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SM_ab2.insert(0,0)=37.0;
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SM_ab2 = kroneckerProduct(SM_a,SM_b);
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CALL_SUBTEST(check_kronecker_product(SM_ab2));
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CALL_SUBTEST(check_kronecker_product(kroneckerProduct(SM_a,SM_b)));
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// test SM = kroneckerProduct(SM,SM) with sparse pattern
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SM_a.resize(4,5);
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SM_b.resize(3,2);
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SM_a.resizeNonZeros(0);
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SM_b.resizeNonZeros(0);
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SM_a.insert(1,0) = -0.1;
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SM_a.insert(0,3) = -0.2;
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SM_a.insert(2,4) = 0.3;
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SM_a.finalize();
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SM_b.insert(0,0) = 0.4;
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SM_b.insert(2,1) = -0.5;
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SM_b.finalize();
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SM_ab.resize(1,1);
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SM_ab.insert(0,0)=37.0;
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SM_ab = kroneckerProduct(SM_a,SM_b);
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CALL_SUBTEST(check_sparse_kronecker_product(SM_ab));
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// test dimension of result of DM = kroneckerProduct(DM,DM)
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MatrixXd DM_a2(2,1);
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MatrixXd DM_b2(5,4);
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MatrixXd DM_ab2 = kroneckerProduct(DM_a2,DM_b2);
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CALL_SUBTEST(check_dimension(DM_ab2,2*5,1*4));
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DM_a2.resize(10,9);
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DM_b2.resize(4,8);
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DM_ab2 = kroneckerProduct(DM_a2,DM_b2);
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CALL_SUBTEST(check_dimension(DM_ab2,10*4,9*8));
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for(int i = 0; i < g_repeat; i++)
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{
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double density = Eigen::internal::random<double>(0.01,0.5);
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int ra = Eigen::internal::random<int>(1,50);
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int ca = Eigen::internal::random<int>(1,50);
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int rb = Eigen::internal::random<int>(1,50);
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int cb = Eigen::internal::random<int>(1,50);
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SparseMatrix<float,ColMajor> sA(ra,ca), sB(rb,cb), sC;
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SparseMatrix<float,RowMajor> sC2;
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MatrixXf dA(ra,ca), dB(rb,cb), dC;
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initSparse(density, dA, sA);
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initSparse(density, dB, sB);
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sC = kroneckerProduct(sA,sB);
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dC = kroneckerProduct(dA,dB);
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VERIFY_IS_APPROX(MatrixXf(sC),dC);
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sC = kroneckerProduct(sA.transpose(),sB);
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dC = kroneckerProduct(dA.transpose(),dB);
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VERIFY_IS_APPROX(MatrixXf(sC),dC);
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sC = kroneckerProduct(sA.transpose(),sB.transpose());
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dC = kroneckerProduct(dA.transpose(),dB.transpose());
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VERIFY_IS_APPROX(MatrixXf(sC),dC);
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sC = kroneckerProduct(sA,sB.transpose());
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dC = kroneckerProduct(dA,dB.transpose());
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VERIFY_IS_APPROX(MatrixXf(sC),dC);
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sC2 = kroneckerProduct(sA,sB);
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dC = kroneckerProduct(dA,dB);
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VERIFY_IS_APPROX(MatrixXf(sC2),dC);
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sC2 = kroneckerProduct(dA,sB);
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dC = kroneckerProduct(dA,dB);
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VERIFY_IS_APPROX(MatrixXf(sC2),dC);
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sC2 = kroneckerProduct(sA,dB);
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dC = kroneckerProduct(dA,dB);
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VERIFY_IS_APPROX(MatrixXf(sC2),dC);
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sC2 = kroneckerProduct(2*sA,sB);
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dC = kroneckerProduct(2*dA,dB);
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VERIFY_IS_APPROX(MatrixXf(sC2),dC);
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}
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}
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#endif
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#ifdef EIGEN_TEST_PART_2
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// simply check that for a dense kronecker product, sparse module is not needed
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#include "main.h"
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#include <Eigen/KroneckerProduct>
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EIGEN_DECLARE_TEST(kronecker_product)
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{
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MatrixXd a(2,2), b(3,3), c;
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a.setRandom();
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b.setRandom();
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c = kroneckerProduct(a,b);
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VERIFY_IS_APPROX(c.block(3,3,3,3), a(1,1)*b);
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}
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#endif
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