1 | // This file is part of Eigen, a lightweight C++ template library
|
---|
2 | // for linear algebra.
|
---|
3 | //
|
---|
4 | // Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
|
---|
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 | #include "main.h"
|
---|
11 |
|
---|
12 | template<typename MatrixType> void matrixVisitor(const MatrixType& p)
|
---|
13 | {
|
---|
14 | typedef typename MatrixType::Scalar Scalar;
|
---|
15 | typedef typename MatrixType::Index Index;
|
---|
16 |
|
---|
17 | Index rows = p.rows();
|
---|
18 | Index cols = p.cols();
|
---|
19 |
|
---|
20 | // construct a random matrix where all coefficients are different
|
---|
21 | MatrixType m;
|
---|
22 | m = MatrixType::Random(rows, cols);
|
---|
23 | for(Index i = 0; i < m.size(); i++)
|
---|
24 | for(Index i2 = 0; i2 < i; i2++)
|
---|
25 | while(m(i) == m(i2)) // yes, ==
|
---|
26 | m(i) = internal::random<Scalar>();
|
---|
27 |
|
---|
28 | Scalar minc = Scalar(1000), maxc = Scalar(-1000);
|
---|
29 | Index minrow=0,mincol=0,maxrow=0,maxcol=0;
|
---|
30 | for(Index j = 0; j < cols; j++)
|
---|
31 | for(Index i = 0; i < rows; i++)
|
---|
32 | {
|
---|
33 | if(m(i,j) < minc)
|
---|
34 | {
|
---|
35 | minc = m(i,j);
|
---|
36 | minrow = i;
|
---|
37 | mincol = j;
|
---|
38 | }
|
---|
39 | if(m(i,j) > maxc)
|
---|
40 | {
|
---|
41 | maxc = m(i,j);
|
---|
42 | maxrow = i;
|
---|
43 | maxcol = j;
|
---|
44 | }
|
---|
45 | }
|
---|
46 | Index eigen_minrow, eigen_mincol, eigen_maxrow, eigen_maxcol;
|
---|
47 | Scalar eigen_minc, eigen_maxc;
|
---|
48 | eigen_minc = m.minCoeff(&eigen_minrow,&eigen_mincol);
|
---|
49 | eigen_maxc = m.maxCoeff(&eigen_maxrow,&eigen_maxcol);
|
---|
50 | VERIFY(minrow == eigen_minrow);
|
---|
51 | VERIFY(maxrow == eigen_maxrow);
|
---|
52 | VERIFY(mincol == eigen_mincol);
|
---|
53 | VERIFY(maxcol == eigen_maxcol);
|
---|
54 | VERIFY_IS_APPROX(minc, eigen_minc);
|
---|
55 | VERIFY_IS_APPROX(maxc, eigen_maxc);
|
---|
56 | VERIFY_IS_APPROX(minc, m.minCoeff());
|
---|
57 | VERIFY_IS_APPROX(maxc, m.maxCoeff());
|
---|
58 |
|
---|
59 | eigen_maxc = (m.adjoint()*m).maxCoeff(&eigen_maxrow,&eigen_maxcol);
|
---|
60 | eigen_maxc = (m.adjoint()*m).eval().maxCoeff(&maxrow,&maxcol);
|
---|
61 | VERIFY(maxrow == eigen_maxrow);
|
---|
62 | VERIFY(maxcol == eigen_maxcol);
|
---|
63 | }
|
---|
64 |
|
---|
65 | template<typename VectorType> void vectorVisitor(const VectorType& w)
|
---|
66 | {
|
---|
67 | typedef typename VectorType::Scalar Scalar;
|
---|
68 | typedef typename VectorType::Index Index;
|
---|
69 |
|
---|
70 | Index size = w.size();
|
---|
71 |
|
---|
72 | // construct a random vector where all coefficients are different
|
---|
73 | VectorType v;
|
---|
74 | v = VectorType::Random(size);
|
---|
75 | for(Index i = 0; i < size; i++)
|
---|
76 | for(Index i2 = 0; i2 < i; i2++)
|
---|
77 | while(v(i) == v(i2)) // yes, ==
|
---|
78 | v(i) = internal::random<Scalar>();
|
---|
79 |
|
---|
80 | Scalar minc = v(0), maxc = v(0);
|
---|
81 | Index minidx=0, maxidx=0;
|
---|
82 | for(Index i = 0; i < size; i++)
|
---|
83 | {
|
---|
84 | if(v(i) < minc)
|
---|
85 | {
|
---|
86 | minc = v(i);
|
---|
87 | minidx = i;
|
---|
88 | }
|
---|
89 | if(v(i) > maxc)
|
---|
90 | {
|
---|
91 | maxc = v(i);
|
---|
92 | maxidx = i;
|
---|
93 | }
|
---|
94 | }
|
---|
95 | Index eigen_minidx, eigen_maxidx;
|
---|
96 | Scalar eigen_minc, eigen_maxc;
|
---|
97 | eigen_minc = v.minCoeff(&eigen_minidx);
|
---|
98 | eigen_maxc = v.maxCoeff(&eigen_maxidx);
|
---|
99 | VERIFY(minidx == eigen_minidx);
|
---|
100 | VERIFY(maxidx == eigen_maxidx);
|
---|
101 | VERIFY_IS_APPROX(minc, eigen_minc);
|
---|
102 | VERIFY_IS_APPROX(maxc, eigen_maxc);
|
---|
103 | VERIFY_IS_APPROX(minc, v.minCoeff());
|
---|
104 | VERIFY_IS_APPROX(maxc, v.maxCoeff());
|
---|
105 |
|
---|
106 | Index idx0 = internal::random<Index>(0,size-1);
|
---|
107 | Index idx1 = eigen_minidx;
|
---|
108 | Index idx2 = eigen_maxidx;
|
---|
109 | VectorType v1(v), v2(v);
|
---|
110 | v1(idx0) = v1(idx1);
|
---|
111 | v2(idx0) = v2(idx2);
|
---|
112 | v1.minCoeff(&eigen_minidx);
|
---|
113 | v2.maxCoeff(&eigen_maxidx);
|
---|
114 | VERIFY(eigen_minidx == (std::min)(idx0,idx1));
|
---|
115 | VERIFY(eigen_maxidx == (std::min)(idx0,idx2));
|
---|
116 | }
|
---|
117 |
|
---|
118 | void test_visitor()
|
---|
119 | {
|
---|
120 | for(int i = 0; i < g_repeat; i++) {
|
---|
121 | CALL_SUBTEST_1( matrixVisitor(Matrix<float, 1, 1>()) );
|
---|
122 | CALL_SUBTEST_2( matrixVisitor(Matrix2f()) );
|
---|
123 | CALL_SUBTEST_3( matrixVisitor(Matrix4d()) );
|
---|
124 | CALL_SUBTEST_4( matrixVisitor(MatrixXd(8, 12)) );
|
---|
125 | CALL_SUBTEST_5( matrixVisitor(Matrix<double,Dynamic,Dynamic,RowMajor>(20, 20)) );
|
---|
126 | CALL_SUBTEST_6( matrixVisitor(MatrixXi(8, 12)) );
|
---|
127 | }
|
---|
128 | for(int i = 0; i < g_repeat; i++) {
|
---|
129 | CALL_SUBTEST_7( vectorVisitor(Vector4f()) );
|
---|
130 | CALL_SUBTEST_7( vectorVisitor(Matrix<int,12,1>()) );
|
---|
131 | CALL_SUBTEST_8( vectorVisitor(VectorXd(10)) );
|
---|
132 | CALL_SUBTEST_9( vectorVisitor(RowVectorXd(10)) );
|
---|
133 | CALL_SUBTEST_10( vectorVisitor(VectorXf(33)) );
|
---|
134 | }
|
---|
135 | }
|
---|