aboutsummaryrefslogtreecommitdiffhomepage
path: root/unsupported/test/kronecker_product.cpp
blob: b5b764c65369f012188b9c5a00d2d822cef4322b (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
// 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>
// Copyright (C) 2012 Chen-Pang He <jdh8@ms63.hinet.net>
//
// 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/.


#ifdef EIGEN_TEST_PART_1

#include "sparse.h"
#include <Eigen/SparseExtra>
#include <Eigen/KroneckerProduct>

template<typename MatrixType>
void check_dimension(const MatrixType& ab, const int rows,  const 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);
}


EIGEN_DECLARE_TEST(kronecker_product)
{
  // DM = dense matrix; SM = sparse matrix

  Matrix<double, 2, 3> DM_a;
  SparseMatrix<double> SM_a(2,3);
  SM_a.insert(0,0) = DM_a.coeffRef(0,0) = -0.4461540300782201;
  SM_a.insert(0,1) = DM_a.coeffRef(0,1) = -0.8057364375283049;
  SM_a.insert(0,2) = DM_a.coeffRef(0,2) =  0.3896572459516341;
  SM_a.insert(1,0) = DM_a.coeffRef(1,0) = -0.9076572187376921;
  SM_a.insert(1,1) = DM_a.coeffRef(1,1) =  0.6469156566545853;
  SM_a.insert(1,2) = DM_a.coeffRef(1,2) = -0.3658010398782789;

  MatrixXd             DM_b(3,2);
  SparseMatrix<double> SM_b(3,2);
  SM_b.insert(0,0) = DM_b.coeffRef(0,0) =  0.9004440976767099;
  SM_b.insert(0,1) = DM_b.coeffRef(0,1) = -0.2368830858139832;
  SM_b.insert(1,0) = DM_b.coeffRef(1,0) = -0.9311078389941825;
  SM_b.insert(1,1) = DM_b.coeffRef(1,1) =  0.5310335762980047;
  SM_b.insert(2,0) = DM_b.coeffRef(2,0) = -0.1225112806872035;
  SM_b.insert(2,1) = DM_b.coeffRef(2,1) =  0.5903998022741264;

  SparseMatrix<double,RowMajor> SM_row_a(SM_a), SM_row_b(SM_b);

  // test DM_fixedSize = kroneckerProduct(DM_block,DM)
  Matrix<double, 6, 6> DM_fix_ab = kroneckerProduct(DM_a.topLeftCorner<2,3>(),DM_b);

  CALL_SUBTEST(check_kronecker_product(DM_fix_ab));
  CALL_SUBTEST(check_kronecker_product(kroneckerProduct(DM_a.topLeftCorner<2,3>(),DM_b)));

  for(int i=0;i<DM_fix_ab.rows();++i)
    for(int j=0;j<DM_fix_ab.cols();++j)
       VERIFY_IS_APPROX(kroneckerProduct(DM_a,DM_b).coeff(i,j), DM_fix_ab(i,j));

  // test DM_block = kroneckerProduct(DM,DM)
  MatrixXd DM_block_ab(10,15);
  DM_block_ab.block<6,6>(2,5) = kroneckerProduct(DM_a,DM_b);
  CALL_SUBTEST(check_kronecker_product(DM_block_ab.block<6,6>(2,5)));

  // test DM = kroneckerProduct(DM,DM)
  MatrixXd DM_ab = kroneckerProduct(DM_a,DM_b);
  CALL_SUBTEST(check_kronecker_product(DM_ab));
  CALL_SUBTEST(check_kronecker_product(kroneckerProduct(DM_a,DM_b)));

  // test SM = kroneckerProduct(SM,DM)
  SparseMatrix<double> SM_ab = kroneckerProduct(SM_a,DM_b);
  CALL_SUBTEST(check_kronecker_product(SM_ab));
  SparseMatrix<double,RowMajor> SM_ab2 = kroneckerProduct(SM_a,DM_b);
  CALL_SUBTEST(check_kronecker_product(SM_ab2));
  CALL_SUBTEST(check_kronecker_product(kroneckerProduct(SM_a,DM_b)));

  // test SM = kroneckerProduct(DM,SM)
  SM_ab.setZero();
  SM_ab.insert(0,0)=37.0;
  SM_ab = kroneckerProduct(DM_a,SM_b);
  CALL_SUBTEST(check_kronecker_product(SM_ab));
  SM_ab2.setZero();
  SM_ab2.insert(0,0)=37.0;
  SM_ab2 = kroneckerProduct(DM_a,SM_b);
  CALL_SUBTEST(check_kronecker_product(SM_ab2));
  CALL_SUBTEST(check_kronecker_product(kroneckerProduct(DM_a,SM_b)));

  // test SM = kroneckerProduct(SM,SM)
  SM_ab.resize(2,33);
  SM_ab.insert(0,0)=37.0;
  SM_ab = kroneckerProduct(SM_a,SM_b);
  CALL_SUBTEST(check_kronecker_product(SM_ab));
  SM_ab2.resize(5,11);
  SM_ab2.insert(0,0)=37.0;
  SM_ab2 = kroneckerProduct(SM_a,SM_b);
  CALL_SUBTEST(check_kronecker_product(SM_ab2));
  CALL_SUBTEST(check_kronecker_product(kroneckerProduct(SM_a,SM_b)));

  // test SM = kroneckerProduct(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;
  SM_ab = kroneckerProduct(SM_a,SM_b);
  CALL_SUBTEST(check_sparse_kronecker_product(SM_ab));

  // test dimension of result of DM = kroneckerProduct(DM,DM)
  MatrixXd DM_a2(2,1);
  MatrixXd DM_b2(5,4);
  MatrixXd DM_ab2 = kroneckerProduct(DM_a2,DM_b2);
  CALL_SUBTEST(check_dimension(DM_ab2,2*5,1*4));
  DM_a2.resize(10,9);
  DM_b2.resize(4,8);
  DM_ab2 = kroneckerProduct(DM_a2,DM_b2);
  CALL_SUBTEST(check_dimension(DM_ab2,10*4,9*8));

  for(int i = 0; i < g_repeat; i++)
  {
    double density = Eigen::internal::random<double>(0.01,0.5);
    int ra = Eigen::internal::random<int>(1,50);
    int ca = Eigen::internal::random<int>(1,50);
    int rb = Eigen::internal::random<int>(1,50);
    int cb = Eigen::internal::random<int>(1,50);
    SparseMatrix<float,ColMajor> sA(ra,ca), sB(rb,cb), sC;
    SparseMatrix<float,RowMajor> sC2;
    MatrixXf dA(ra,ca), dB(rb,cb), dC;
    initSparse(density, dA, sA);
    initSparse(density, dB, sB);

    sC = kroneckerProduct(sA,sB);
    dC = kroneckerProduct(dA,dB);
    VERIFY_IS_APPROX(MatrixXf(sC),dC);

    sC = kroneckerProduct(sA.transpose(),sB);
    dC = kroneckerProduct(dA.transpose(),dB);
    VERIFY_IS_APPROX(MatrixXf(sC),dC);

    sC = kroneckerProduct(sA.transpose(),sB.transpose());
    dC = kroneckerProduct(dA.transpose(),dB.transpose());
    VERIFY_IS_APPROX(MatrixXf(sC),dC);

    sC = kroneckerProduct(sA,sB.transpose());
    dC = kroneckerProduct(dA,dB.transpose());
    VERIFY_IS_APPROX(MatrixXf(sC),dC);

    sC2 = kroneckerProduct(sA,sB);
    dC = kroneckerProduct(dA,dB);
    VERIFY_IS_APPROX(MatrixXf(sC2),dC);

    sC2 = kroneckerProduct(dA,sB);
    dC = kroneckerProduct(dA,dB);
    VERIFY_IS_APPROX(MatrixXf(sC2),dC);

    sC2 = kroneckerProduct(sA,dB);
    dC = kroneckerProduct(dA,dB);
    VERIFY_IS_APPROX(MatrixXf(sC2),dC);

    sC2 = kroneckerProduct(2*sA,sB);
    dC = kroneckerProduct(2*dA,dB);
    VERIFY_IS_APPROX(MatrixXf(sC2),dC);
  }
}

#endif

#ifdef EIGEN_TEST_PART_2

// simply check that for a dense kronecker product, sparse module is not needed
#include "main.h"
#include <Eigen/KroneckerProduct>

EIGEN_DECLARE_TEST(kronecker_product)
{
  MatrixXd a(2,2), b(3,3), c;
  a.setRandom();
  b.setRandom();
  c = kroneckerProduct(a,b);
  VERIFY_IS_APPROX(c.block(3,3,3,3), a(1,1)*b);
}

#endif