1 // This file is part of Eigen, a lightweight C++ template library
2 // for linear algebra.
3 //
4 // Copyright (C) 2009 Benoit Jacob <[email protected]>
5 //
6 // This Source Code Form is subject to the terms of the Mozilla
7 // Public License v. 2.0. If a copy of the MPL was not distributed
8 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
9
10 #define TEST_ENABLE_TEMPORARY_TRACKING
11
12 #include "main.h"
13
14 using namespace std;
permutationmatrices(const MatrixType & m)15 template<typename MatrixType> void permutationmatrices(const MatrixType& m)
16 {
17 typedef typename MatrixType::Scalar Scalar;
18 enum { Rows = MatrixType::RowsAtCompileTime, Cols = MatrixType::ColsAtCompileTime,
19 Options = MatrixType::Options };
20 typedef PermutationMatrix<Rows> LeftPermutationType;
21 typedef Transpositions<Rows> LeftTranspositionsType;
22 typedef Matrix<int, Rows, 1> LeftPermutationVectorType;
23 typedef Map<LeftPermutationType> MapLeftPerm;
24 typedef PermutationMatrix<Cols> RightPermutationType;
25 typedef Transpositions<Cols> RightTranspositionsType;
26 typedef Matrix<int, Cols, 1> RightPermutationVectorType;
27 typedef Map<RightPermutationType> MapRightPerm;
28
29 Index rows = m.rows();
30 Index cols = m.cols();
31
32 MatrixType m_original = MatrixType::Random(rows,cols);
33 LeftPermutationVectorType lv;
34 randomPermutationVector(lv, rows);
35 LeftPermutationType lp(lv);
36 RightPermutationVectorType rv;
37 randomPermutationVector(rv, cols);
38 RightPermutationType rp(rv);
39 LeftTranspositionsType lt(lv);
40 RightTranspositionsType rt(rv);
41 MatrixType m_permuted = MatrixType::Random(rows,cols);
42
43 VERIFY_EVALUATION_COUNT(m_permuted = lp * m_original * rp, 1); // 1 temp for sub expression "lp * m_original"
44
45 for (int i=0; i<rows; i++)
46 for (int j=0; j<cols; j++)
47 VERIFY_IS_APPROX(m_permuted(lv(i),j), m_original(i,rv(j)));
48
49 Matrix<Scalar,Rows,Rows> lm(lp);
50 Matrix<Scalar,Cols,Cols> rm(rp);
51
52 VERIFY_IS_APPROX(m_permuted, lm*m_original*rm);
53
54 m_permuted = m_original;
55 VERIFY_EVALUATION_COUNT(m_permuted = lp * m_permuted * rp, 1);
56 VERIFY_IS_APPROX(m_permuted, lm*m_original*rm);
57
58 LeftPermutationType lpi;
59 lpi = lp.inverse();
60 VERIFY_IS_APPROX(lpi*m_permuted,lp.inverse()*m_permuted);
61
62 VERIFY_IS_APPROX(lp.inverse()*m_permuted*rp.inverse(), m_original);
63 VERIFY_IS_APPROX(lv.asPermutation().inverse()*m_permuted*rv.asPermutation().inverse(), m_original);
64 VERIFY_IS_APPROX(MapLeftPerm(lv.data(),lv.size()).inverse()*m_permuted*MapRightPerm(rv.data(),rv.size()).inverse(), m_original);
65
66 VERIFY((lp*lp.inverse()).toDenseMatrix().isIdentity());
67 VERIFY((lv.asPermutation()*lv.asPermutation().inverse()).toDenseMatrix().isIdentity());
68 VERIFY((MapLeftPerm(lv.data(),lv.size())*MapLeftPerm(lv.data(),lv.size()).inverse()).toDenseMatrix().isIdentity());
69
70 LeftPermutationVectorType lv2;
71 randomPermutationVector(lv2, rows);
72 LeftPermutationType lp2(lv2);
73 Matrix<Scalar,Rows,Rows> lm2(lp2);
74 VERIFY_IS_APPROX((lp*lp2).toDenseMatrix().template cast<Scalar>(), lm*lm2);
75 VERIFY_IS_APPROX((lv.asPermutation()*lv2.asPermutation()).toDenseMatrix().template cast<Scalar>(), lm*lm2);
76 VERIFY_IS_APPROX((MapLeftPerm(lv.data(),lv.size())*MapLeftPerm(lv2.data(),lv2.size())).toDenseMatrix().template cast<Scalar>(), lm*lm2);
77
78 LeftPermutationType identityp;
79 identityp.setIdentity(rows);
80 VERIFY_IS_APPROX(m_original, identityp*m_original);
81
82 // check inplace permutations
83 m_permuted = m_original;
84 VERIFY_EVALUATION_COUNT(m_permuted.noalias()= lp.inverse() * m_permuted, 1); // 1 temp to allocate the mask
85 VERIFY_IS_APPROX(m_permuted, lp.inverse()*m_original);
86
87 m_permuted = m_original;
88 VERIFY_EVALUATION_COUNT(m_permuted.noalias() = m_permuted * rp.inverse(), 1); // 1 temp to allocate the mask
89 VERIFY_IS_APPROX(m_permuted, m_original*rp.inverse());
90
91 m_permuted = m_original;
92 VERIFY_EVALUATION_COUNT(m_permuted.noalias() = lp * m_permuted, 1); // 1 temp to allocate the mask
93 VERIFY_IS_APPROX(m_permuted, lp*m_original);
94
95 m_permuted = m_original;
96 VERIFY_EVALUATION_COUNT(m_permuted.noalias() = m_permuted * rp, 1); // 1 temp to allocate the mask
97 VERIFY_IS_APPROX(m_permuted, m_original*rp);
98
99 if(rows>1 && cols>1)
100 {
101 lp2 = lp;
102 Index i = internal::random<Index>(0, rows-1);
103 Index j;
104 do j = internal::random<Index>(0, rows-1); while(j==i);
105 lp2.applyTranspositionOnTheLeft(i, j);
106 lm = lp;
107 lm.row(i).swap(lm.row(j));
108 VERIFY_IS_APPROX(lm, lp2.toDenseMatrix().template cast<Scalar>());
109
110 RightPermutationType rp2 = rp;
111 i = internal::random<Index>(0, cols-1);
112 do j = internal::random<Index>(0, cols-1); while(j==i);
113 rp2.applyTranspositionOnTheRight(i, j);
114 rm = rp;
115 rm.col(i).swap(rm.col(j));
116 VERIFY_IS_APPROX(rm, rp2.toDenseMatrix().template cast<Scalar>());
117 }
118
119 {
120 // simple compilation check
121 Matrix<Scalar, Cols, Cols> A = rp;
122 Matrix<Scalar, Cols, Cols> B = rp.transpose();
123 VERIFY_IS_APPROX(A, B.transpose());
124 }
125
126 m_permuted = m_original;
127 lp = lt;
128 rp = rt;
129 VERIFY_EVALUATION_COUNT(m_permuted = lt * m_permuted * rt, 1);
130 VERIFY_IS_APPROX(m_permuted, lp*m_original*rp.transpose());
131
132 VERIFY_IS_APPROX(lt.inverse()*m_permuted*rt.inverse(), m_original);
133
134 // Check inplace transpositions
135 m_permuted = m_original;
136 VERIFY_IS_APPROX(m_permuted = lt * m_permuted, lp * m_original);
137 m_permuted = m_original;
138 VERIFY_IS_APPROX(m_permuted = lt.inverse() * m_permuted, lp.inverse() * m_original);
139 m_permuted = m_original;
140 VERIFY_IS_APPROX(m_permuted = m_permuted * rt, m_original * rt);
141 m_permuted = m_original;
142 VERIFY_IS_APPROX(m_permuted = m_permuted * rt.inverse(), m_original * rt.inverse());
143 }
144
145 template<typename T>
bug890()146 void bug890()
147 {
148 typedef Matrix<T, Dynamic, Dynamic> MatrixType;
149 typedef Matrix<T, Dynamic, 1> VectorType;
150 typedef Stride<Dynamic,Dynamic> S;
151 typedef Map<MatrixType, Aligned, S> MapType;
152 typedef PermutationMatrix<Dynamic> Perm;
153
154 VectorType v1(2), v2(2), op(4), rhs(2);
155 v1 << 666,667;
156 op << 1,0,0,1;
157 rhs << 42,42;
158
159 Perm P(2);
160 P.indices() << 1, 0;
161
162 MapType(v1.data(),2,1,S(1,1)) = P * MapType(rhs.data(),2,1,S(1,1));
163 VERIFY_IS_APPROX(v1, (P * rhs).eval());
164
165 MapType(v1.data(),2,1,S(1,1)) = P.inverse() * MapType(rhs.data(),2,1,S(1,1));
166 VERIFY_IS_APPROX(v1, (P.inverse() * rhs).eval());
167 }
168
EIGEN_DECLARE_TEST(permutationmatrices)169 EIGEN_DECLARE_TEST(permutationmatrices)
170 {
171 for(int i = 0; i < g_repeat; i++) {
172 CALL_SUBTEST_1( permutationmatrices(Matrix<float, 1, 1>()) );
173 CALL_SUBTEST_2( permutationmatrices(Matrix3f()) );
174 CALL_SUBTEST_3( permutationmatrices(Matrix<double,3,3,RowMajor>()) );
175 CALL_SUBTEST_4( permutationmatrices(Matrix4d()) );
176 CALL_SUBTEST_5( permutationmatrices(Matrix<double,40,60>()) );
177 CALL_SUBTEST_6( permutationmatrices(Matrix<double,Dynamic,Dynamic,RowMajor>(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
178 CALL_SUBTEST_7( permutationmatrices(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
179 }
180 CALL_SUBTEST_5( bug890<double>() );
181 }
182