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
12template<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
59template<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
100void 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