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  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
60template<typename VectorType> void vectorVisitor(const VectorType& w)
61{
62  typedef typename VectorType::Scalar Scalar;
63  typedef typename VectorType::Index Index;
64
65  Index size = w.size();
66
67  // construct a random vector where all coefficients are different
68  VectorType v;
69  v = VectorType::Random(size);
70  for(Index i = 0; i < size; i++)
71    for(Index i2 = 0; i2 < i; i2++)
72      while(v(i) == v(i2)) // yes, ==
73        v(i) = internal::random<Scalar>();
74
75  Scalar minc = Scalar(1000), maxc = Scalar(-1000);
76  Index minidx=0,maxidx=0;
77  for(Index i = 0; i < size; i++)
78  {
79    if(v(i) < minc)
80    {
81      minc = v(i);
82      minidx = i;
83    }
84    if(v(i) > maxc)
85    {
86      maxc = v(i);
87      maxidx = i;
88    }
89  }
90  Index eigen_minidx, eigen_maxidx;
91  Scalar eigen_minc, eigen_maxc;
92  eigen_minc = v.minCoeff(&eigen_minidx);
93  eigen_maxc = v.maxCoeff(&eigen_maxidx);
94  VERIFY(minidx == eigen_minidx);
95  VERIFY(maxidx == eigen_maxidx);
96  VERIFY_IS_APPROX(minc, eigen_minc);
97  VERIFY_IS_APPROX(maxc, eigen_maxc);
98  VERIFY_IS_APPROX(minc, v.minCoeff());
99  VERIFY_IS_APPROX(maxc, v.maxCoeff());
100}
101
102void test_visitor()
103{
104  for(int i = 0; i < g_repeat; i++) {
105    CALL_SUBTEST_1( matrixVisitor(Matrix<float, 1, 1>()) );
106    CALL_SUBTEST_2( matrixVisitor(Matrix2f()) );
107    CALL_SUBTEST_3( matrixVisitor(Matrix4d()) );
108    CALL_SUBTEST_4( matrixVisitor(MatrixXd(8, 12)) );
109    CALL_SUBTEST_5( matrixVisitor(Matrix<double,Dynamic,Dynamic,RowMajor>(20, 20)) );
110    CALL_SUBTEST_6( matrixVisitor(MatrixXi(8, 12)) );
111  }
112  for(int i = 0; i < g_repeat; i++) {
113    CALL_SUBTEST_7( vectorVisitor(Vector4f()) );
114    CALL_SUBTEST_8( vectorVisitor(VectorXd(10)) );
115    CALL_SUBTEST_9( vectorVisitor(RowVectorXd(10)) );
116    CALL_SUBTEST_10( vectorVisitor(VectorXf(33)) );
117  }
118}
119