kronecker_product.cpp
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1 // This file is part of Eigen, a lightweight C++ template library
2 // for linear algebra.
3 //
4 // Copyright (C) 2011 Kolja Brix <brix@igpm.rwth-aachen.de>
5 // Copyright (C) 2011 Andreas Platen <andiplaten@gmx.de>
6 // Copyright (C) 2012 Chen-Pang He <jdh8@ms63.hinet.net>
7 //
8 // This Source Code Form is subject to the terms of the Mozilla
9 // Public License v. 2.0. If a copy of the MPL was not distributed
10 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
11 
12 #ifdef EIGEN_TEST_PART_1
13 
14 #include "sparse.h"
15 #include <Eigen/SparseExtra>
16 #include <Eigen/KroneckerProduct>
17 
18 template<typename MatrixType>
19 void check_dimension(const MatrixType& ab, const int rows, const int cols)
20 {
21  VERIFY_IS_EQUAL(ab.rows(), rows);
22  VERIFY_IS_EQUAL(ab.cols(), cols);
23 }
24 
25 
26 template<typename MatrixType>
27 void check_kronecker_product(const MatrixType& ab)
28 {
29  VERIFY_IS_EQUAL(ab.rows(), 6);
30  VERIFY_IS_EQUAL(ab.cols(), 6);
31  VERIFY_IS_EQUAL(ab.nonZeros(), 36);
32  VERIFY_IS_APPROX(ab.coeff(0,0), -0.4017367630386106);
33  VERIFY_IS_APPROX(ab.coeff(0,1), 0.1056863433932735);
34  VERIFY_IS_APPROX(ab.coeff(0,2), -0.7255206194554212);
35  VERIFY_IS_APPROX(ab.coeff(0,3), 0.1908653336744706);
36  VERIFY_IS_APPROX(ab.coeff(0,4), 0.350864567234111);
37  VERIFY_IS_APPROX(ab.coeff(0,5), -0.0923032108308013);
38  VERIFY_IS_APPROX(ab.coeff(1,0), 0.415417514804677);
39  VERIFY_IS_APPROX(ab.coeff(1,1), -0.2369227701722048);
40  VERIFY_IS_APPROX(ab.coeff(1,2), 0.7502275131458511);
41  VERIFY_IS_APPROX(ab.coeff(1,3), -0.4278731019742696);
42  VERIFY_IS_APPROX(ab.coeff(1,4), -0.3628129162264507);
43  VERIFY_IS_APPROX(ab.coeff(1,5), 0.2069210808481275);
44  VERIFY_IS_APPROX(ab.coeff(2,0), 0.05465890160863986);
45  VERIFY_IS_APPROX(ab.coeff(2,1), -0.2634092511419858);
46  VERIFY_IS_APPROX(ab.coeff(2,2), 0.09871180285793758);
47  VERIFY_IS_APPROX(ab.coeff(2,3), -0.4757066334017702);
48  VERIFY_IS_APPROX(ab.coeff(2,4), -0.04773740823058334);
49  VERIFY_IS_APPROX(ab.coeff(2,5), 0.2300535609645254);
50  VERIFY_IS_APPROX(ab.coeff(3,0), -0.8172945853260133);
51  VERIFY_IS_APPROX(ab.coeff(3,1), 0.2150086428359221);
52  VERIFY_IS_APPROX(ab.coeff(3,2), 0.5825113847292743);
53  VERIFY_IS_APPROX(ab.coeff(3,3), -0.1532433770097174);
54  VERIFY_IS_APPROX(ab.coeff(3,4), -0.329383387282399);
55  VERIFY_IS_APPROX(ab.coeff(3,5), 0.08665207912033064);
56  VERIFY_IS_APPROX(ab.coeff(4,0), 0.8451267514863225);
57  VERIFY_IS_APPROX(ab.coeff(4,1), -0.481996458918977);
58  VERIFY_IS_APPROX(ab.coeff(4,2), -0.6023482390791535);
59  VERIFY_IS_APPROX(ab.coeff(4,3), 0.3435339347164565);
60  VERIFY_IS_APPROX(ab.coeff(4,4), 0.3406002157428891);
61  VERIFY_IS_APPROX(ab.coeff(4,5), -0.1942526344200915);
62  VERIFY_IS_APPROX(ab.coeff(5,0), 0.1111982482925399);
63  VERIFY_IS_APPROX(ab.coeff(5,1), -0.5358806424754169);
64  VERIFY_IS_APPROX(ab.coeff(5,2), -0.07925446559335647);
65  VERIFY_IS_APPROX(ab.coeff(5,3), 0.3819388757769038);
66  VERIFY_IS_APPROX(ab.coeff(5,4), 0.04481475387219876);
67  VERIFY_IS_APPROX(ab.coeff(5,5), -0.2159688616158057);
68 }
69 
70 
71 template<typename MatrixType>
72 void check_sparse_kronecker_product(const MatrixType& ab)
73 {
74  VERIFY_IS_EQUAL(ab.rows(), 12);
75  VERIFY_IS_EQUAL(ab.cols(), 10);
76  VERIFY_IS_EQUAL(ab.nonZeros(), 3*2);
77  VERIFY_IS_APPROX(ab.coeff(3,0), -0.04);
78  VERIFY_IS_APPROX(ab.coeff(5,1), 0.05);
79  VERIFY_IS_APPROX(ab.coeff(0,6), -0.08);
80  VERIFY_IS_APPROX(ab.coeff(2,7), 0.10);
81  VERIFY_IS_APPROX(ab.coeff(6,8), 0.12);
82  VERIFY_IS_APPROX(ab.coeff(8,9), -0.15);
83 }
84 
85 
86 void test_kronecker_product()
87 {
88  // DM = dense matrix; SM = sparse matrix
89 
90  Matrix<double, 2, 3> DM_a;
91  SparseMatrix<double> SM_a(2,3);
92  SM_a.insert(0,0) = DM_a.coeffRef(0,0) = -0.4461540300782201;
93  SM_a.insert(0,1) = DM_a.coeffRef(0,1) = -0.8057364375283049;
94  SM_a.insert(0,2) = DM_a.coeffRef(0,2) = 0.3896572459516341;
95  SM_a.insert(1,0) = DM_a.coeffRef(1,0) = -0.9076572187376921;
96  SM_a.insert(1,1) = DM_a.coeffRef(1,1) = 0.6469156566545853;
97  SM_a.insert(1,2) = DM_a.coeffRef(1,2) = -0.3658010398782789;
98 
99  MatrixXd DM_b(3,2);
100  SparseMatrix<double> SM_b(3,2);
101  SM_b.insert(0,0) = DM_b.coeffRef(0,0) = 0.9004440976767099;
102  SM_b.insert(0,1) = DM_b.coeffRef(0,1) = -0.2368830858139832;
103  SM_b.insert(1,0) = DM_b.coeffRef(1,0) = -0.9311078389941825;
104  SM_b.insert(1,1) = DM_b.coeffRef(1,1) = 0.5310335762980047;
105  SM_b.insert(2,0) = DM_b.coeffRef(2,0) = -0.1225112806872035;
106  SM_b.insert(2,1) = DM_b.coeffRef(2,1) = 0.5903998022741264;
107 
108  SparseMatrix<double,RowMajor> SM_row_a(SM_a), SM_row_b(SM_b);
109 
110  // test DM_fixedSize = kroneckerProduct(DM_block,DM)
111  Matrix<double, 6, 6> DM_fix_ab = kroneckerProduct(DM_a.topLeftCorner<2,3>(),DM_b);
112 
113  CALL_SUBTEST(check_kronecker_product(DM_fix_ab));
114  CALL_SUBTEST(check_kronecker_product(kroneckerProduct(DM_a.topLeftCorner<2,3>(),DM_b)));
115 
116  for(int i=0;i<DM_fix_ab.rows();++i)
117  for(int j=0;j<DM_fix_ab.cols();++j)
118  VERIFY_IS_APPROX(kroneckerProduct(DM_a,DM_b).coeff(i,j), DM_fix_ab(i,j));
119 
120  // test DM_block = kroneckerProduct(DM,DM)
121  MatrixXd DM_block_ab(10,15);
122  DM_block_ab.block<6,6>(2,5) = kroneckerProduct(DM_a,DM_b);
123  CALL_SUBTEST(check_kronecker_product(DM_block_ab.block<6,6>(2,5)));
124 
125  // test DM = kroneckerProduct(DM,DM)
126  MatrixXd DM_ab = kroneckerProduct(DM_a,DM_b);
127  CALL_SUBTEST(check_kronecker_product(DM_ab));
128  CALL_SUBTEST(check_kronecker_product(kroneckerProduct(DM_a,DM_b)));
129 
130  // test SM = kroneckerProduct(SM,DM)
131  SparseMatrix<double> SM_ab = kroneckerProduct(SM_a,DM_b);
132  CALL_SUBTEST(check_kronecker_product(SM_ab));
133  SparseMatrix<double,RowMajor> SM_ab2 = kroneckerProduct(SM_a,DM_b);
134  CALL_SUBTEST(check_kronecker_product(SM_ab2));
135  CALL_SUBTEST(check_kronecker_product(kroneckerProduct(SM_a,DM_b)));
136 
137  // test SM = kroneckerProduct(DM,SM)
138  SM_ab.setZero();
139  SM_ab.insert(0,0)=37.0;
140  SM_ab = kroneckerProduct(DM_a,SM_b);
141  CALL_SUBTEST(check_kronecker_product(SM_ab));
142  SM_ab2.setZero();
143  SM_ab2.insert(0,0)=37.0;
144  SM_ab2 = kroneckerProduct(DM_a,SM_b);
145  CALL_SUBTEST(check_kronecker_product(SM_ab2));
146  CALL_SUBTEST(check_kronecker_product(kroneckerProduct(DM_a,SM_b)));
147 
148  // test SM = kroneckerProduct(SM,SM)
149  SM_ab.resize(2,33);
150  SM_ab.insert(0,0)=37.0;
151  SM_ab = kroneckerProduct(SM_a,SM_b);
152  CALL_SUBTEST(check_kronecker_product(SM_ab));
153  SM_ab2.resize(5,11);
154  SM_ab2.insert(0,0)=37.0;
155  SM_ab2 = kroneckerProduct(SM_a,SM_b);
156  CALL_SUBTEST(check_kronecker_product(SM_ab2));
157  CALL_SUBTEST(check_kronecker_product(kroneckerProduct(SM_a,SM_b)));
158 
159  // test SM = kroneckerProduct(SM,SM) with sparse pattern
160  SM_a.resize(4,5);
161  SM_b.resize(3,2);
162  SM_a.resizeNonZeros(0);
163  SM_b.resizeNonZeros(0);
164  SM_a.insert(1,0) = -0.1;
165  SM_a.insert(0,3) = -0.2;
166  SM_a.insert(2,4) = 0.3;
167  SM_a.finalize();
168 
169  SM_b.insert(0,0) = 0.4;
170  SM_b.insert(2,1) = -0.5;
171  SM_b.finalize();
172  SM_ab.resize(1,1);
173  SM_ab.insert(0,0)=37.0;
174  SM_ab = kroneckerProduct(SM_a,SM_b);
175  CALL_SUBTEST(check_sparse_kronecker_product(SM_ab));
176 
177  // test dimension of result of DM = kroneckerProduct(DM,DM)
178  MatrixXd DM_a2(2,1);
179  MatrixXd DM_b2(5,4);
180  MatrixXd DM_ab2 = kroneckerProduct(DM_a2,DM_b2);
181  CALL_SUBTEST(check_dimension(DM_ab2,2*5,1*4));
182  DM_a2.resize(10,9);
183  DM_b2.resize(4,8);
184  DM_ab2 = kroneckerProduct(DM_a2,DM_b2);
185  CALL_SUBTEST(check_dimension(DM_ab2,10*4,9*8));
186 
187  for(int i = 0; i < g_repeat; i++)
188  {
189  double density = Eigen::internal::random<double>(0.01,0.5);
190  int ra = Eigen::internal::random<int>(1,50);
191  int ca = Eigen::internal::random<int>(1,50);
192  int rb = Eigen::internal::random<int>(1,50);
193  int cb = Eigen::internal::random<int>(1,50);
194  SparseMatrix<float,ColMajor> sA(ra,ca), sB(rb,cb), sC;
195  SparseMatrix<float,RowMajor> sC2;
196  MatrixXf dA(ra,ca), dB(rb,cb), dC;
197  initSparse(density, dA, sA);
198  initSparse(density, dB, sB);
199 
200  sC = kroneckerProduct(sA,sB);
201  dC = kroneckerProduct(dA,dB);
202  VERIFY_IS_APPROX(MatrixXf(sC),dC);
203 
204  sC = kroneckerProduct(sA.transpose(),sB);
205  dC = kroneckerProduct(dA.transpose(),dB);
206  VERIFY_IS_APPROX(MatrixXf(sC),dC);
207 
208  sC = kroneckerProduct(sA.transpose(),sB.transpose());
209  dC = kroneckerProduct(dA.transpose(),dB.transpose());
210  VERIFY_IS_APPROX(MatrixXf(sC),dC);
211 
212  sC = kroneckerProduct(sA,sB.transpose());
213  dC = kroneckerProduct(dA,dB.transpose());
214  VERIFY_IS_APPROX(MatrixXf(sC),dC);
215 
216  sC2 = kroneckerProduct(sA,sB);
217  dC = kroneckerProduct(dA,dB);
218  VERIFY_IS_APPROX(MatrixXf(sC2),dC);
219 
220  sC2 = kroneckerProduct(dA,sB);
221  dC = kroneckerProduct(dA,dB);
222  VERIFY_IS_APPROX(MatrixXf(sC2),dC);
223 
224  sC2 = kroneckerProduct(sA,dB);
225  dC = kroneckerProduct(dA,dB);
226  VERIFY_IS_APPROX(MatrixXf(sC2),dC);
227 
228  sC2 = kroneckerProduct(2*sA,sB);
229  dC = kroneckerProduct(2*dA,dB);
230  VERIFY_IS_APPROX(MatrixXf(sC2),dC);
231  }
232 }
233 
234 #endif
235 
236 #ifdef EIGEN_TEST_PART_2
237 
238 // simply check that for a dense kronecker product, sparse module is not needed
239 
240 #include "main.h"
241 #include <Eigen/KroneckerProduct>
242 
243 void test_kronecker_product()
244 {
245  MatrixXd a(2,2), b(3,3), c;
246  a.setRandom();
247  b.setRandom();
248  c = kroneckerProduct(a,b);
249  VERIFY_IS_APPROX(c.block(3,3,3,3), a(1,1)*b);
250 }
251 
252 #endif
Eigen::kroneckerProduct
KroneckerProduct< A, B > kroneckerProduct(const MatrixBase< A > &a, const MatrixBase< B > &b)
Definition: KroneckerTensorProduct.h:271
Eigen::numext::b
EIGEN_DEVICE_FUNC const Scalar & b
Definition: SpecialFunctionsImpl.h:1556

hebiros
Author(s): Xavier Artache , Matthew Tesch
autogenerated on Thu Sep 3 2020 04:08:19