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
matrixVisitor(const MatrixType & p)12 template<typename MatrixType> void matrixVisitor(const MatrixType& p)
13 {
14 typedef typename MatrixType::Scalar Scalar;
15
16 int rows = p.rows();
17 int cols = p.cols();
18
19 // construct a random matrix where all coefficients are different
20 MatrixType m;
21 m = MatrixType::Random(rows, cols);
22 for(int i = 0; i < m.size(); i++)
23 for(int i2 = 0; i2 < i; i2++)
24 while(m(i) == m(i2)) // yes, ==
25 m(i) = ei_random<Scalar>();
26
27 Scalar minc = Scalar(1000), maxc = Scalar(-1000);
28 int minrow=0,mincol=0,maxrow=0,maxcol=0;
29 for(int j = 0; j < cols; j++)
30 for(int i = 0; i < rows; i++)
31 {
32 if(m(i,j) < minc)
33 {
34 minc = m(i,j);
35 minrow = i;
36 mincol = j;
37 }
38 if(m(i,j) > maxc)
39 {
40 maxc = m(i,j);
41 maxrow = i;
42 maxcol = j;
43 }
44 }
45 int eigen_minrow, eigen_mincol, eigen_maxrow, eigen_maxcol;
46 Scalar eigen_minc, eigen_maxc;
47 eigen_minc = m.minCoeff(&eigen_minrow,&eigen_mincol);
48 eigen_maxc = m.maxCoeff(&eigen_maxrow,&eigen_maxcol);
49 VERIFY(minrow == eigen_minrow);
50 VERIFY(maxrow == eigen_maxrow);
51 VERIFY(mincol == eigen_mincol);
52 VERIFY(maxcol == eigen_maxcol);
53 VERIFY_IS_APPROX(minc, eigen_minc);
54 VERIFY_IS_APPROX(maxc, eigen_maxc);
55 VERIFY_IS_APPROX(minc, m.minCoeff());
56 VERIFY_IS_APPROX(maxc, m.maxCoeff());
57 }
58
vectorVisitor(const VectorType & w)59 template<typename VectorType> void vectorVisitor(const VectorType& w)
60 {
61 typedef typename VectorType::Scalar Scalar;
62
63 int size = w.size();
64
65 // construct a random vector where all coefficients are different
66 VectorType v;
67 v = VectorType::Random(size);
68 for(int i = 0; i < size; i++)
69 for(int i2 = 0; i2 < i; i2++)
70 while(v(i) == v(i2)) // yes, ==
71 v(i) = ei_random<Scalar>();
72
73 Scalar minc = Scalar(1000), maxc = Scalar(-1000);
74 int minidx=0,maxidx=0;
75 for(int i = 0; i < size; i++)
76 {
77 if(v(i) < minc)
78 {
79 minc = v(i);
80 minidx = i;
81 }
82 if(v(i) > maxc)
83 {
84 maxc = v(i);
85 maxidx = i;
86 }
87 }
88 int eigen_minidx, eigen_maxidx;
89 Scalar eigen_minc, eigen_maxc;
90 eigen_minc = v.minCoeff(&eigen_minidx);
91 eigen_maxc = v.maxCoeff(&eigen_maxidx);
92 VERIFY(minidx == eigen_minidx);
93 VERIFY(maxidx == eigen_maxidx);
94 VERIFY_IS_APPROX(minc, eigen_minc);
95 VERIFY_IS_APPROX(maxc, eigen_maxc);
96 VERIFY_IS_APPROX(minc, v.minCoeff());
97 VERIFY_IS_APPROX(maxc, v.maxCoeff());
98 }
99
test_eigen2_visitor()100 void test_eigen2_visitor()
101 {
102 for(int i = 0; i < g_repeat; i++) {
103 CALL_SUBTEST_1( matrixVisitor(Matrix<float, 1, 1>()) );
104 CALL_SUBTEST_2( matrixVisitor(Matrix2f()) );
105 CALL_SUBTEST_3( matrixVisitor(Matrix4d()) );
106 CALL_SUBTEST_4( matrixVisitor(MatrixXd(8, 12)) );
107 CALL_SUBTEST_5( matrixVisitor(Matrix<double,Dynamic,Dynamic,RowMajor>(20, 20)) );
108 CALL_SUBTEST_6( matrixVisitor(MatrixXi(8, 12)) );
109 }
110 for(int i = 0; i < g_repeat; i++) {
111 CALL_SUBTEST_7( vectorVisitor(Vector4f()) );
112 CALL_SUBTEST_4( vectorVisitor(VectorXd(10)) );
113 CALL_SUBTEST_4( vectorVisitor(RowVectorXd(10)) );
114 CALL_SUBTEST_8( vectorVisitor(VectorXf(33)) );
115 }
116 }
117