nullary.cpp revision c981c48f5bc9aefeffc0bcb0cc3934c2fae179dd 
1// This file is part of Eigen, a lightweight C++ template library
2// for linear algebra.
3//
4// Copyright (C) 2010-2011 Jitse Niesen <jitse@maths.leeds.ac.uk>
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>
13bool equalsIdentity(const MatrixType& A)
14{
15  typedef typename MatrixType::Index Index;
16  typedef typename MatrixType::Scalar Scalar;
17  Scalar zero = static_cast<Scalar>(0);
18
19  bool offDiagOK = true;
20  for (Index i = 0; i < A.rows(); ++i) {
21    for (Index j = i+1; j < A.cols(); ++j) {
22      offDiagOK = offDiagOK && (A(i,j) == zero);
23    }
24  }
25  for (Index i = 0; i < A.rows(); ++i) {
26    for (Index j = 0; j < (std::min)(i, A.cols()); ++j) {
27      offDiagOK = offDiagOK && (A(i,j) == zero);
28    }
29  }
30
31  bool diagOK = (A.diagonal().array() == 1).all();
32  return offDiagOK && diagOK;
33}
34
35template<typename VectorType>
36void testVectorType(const VectorType& base)
37{
38  typedef typename internal::traits<VectorType>::Index Index;
39  typedef typename internal::traits<VectorType>::Scalar Scalar;
40
41  const Index size = base.size();
42
43  Scalar high = internal::random<Scalar>(-500,500);
44  Scalar low = (size == 1 ? high : internal::random<Scalar>(-500,500));
45  if (low>high) std::swap(low,high);
46
47  const Scalar step = ((size == 1) ? 1 : (high-low)/(size-1));
48
49  // check whether the result yields what we expect it to do
50  VectorType m(base);
51  m.setLinSpaced(size,low,high);
52
53  VectorType n(size);
54  for (int i=0; i<size; ++i)
55    n(i) = low+i*step;
56
57  VERIFY_IS_APPROX(m,n);
58
59  // random access version
60  m = VectorType::LinSpaced(size,low,high);
61  VERIFY_IS_APPROX(m,n);
62
63  // Assignment of a RowVectorXd to a MatrixXd (regression test for bug #79).
64  VERIFY( (MatrixXd(RowVectorXd::LinSpaced(3, 0, 1)) - RowVector3d(0, 0.5, 1)).norm() < std::numeric_limits<Scalar>::epsilon() );
65
66  // These guys sometimes fail! This is not good. Any ideas how to fix them!?
67  //VERIFY( m(m.size()-1) == high );
68  //VERIFY( m(0) == low );
69
70  // sequential access version
71  m = VectorType::LinSpaced(Sequential,size,low,high);
72  VERIFY_IS_APPROX(m,n);
73
74  // These guys sometimes fail! This is not good. Any ideas how to fix them!?
75  //VERIFY( m(m.size()-1) == high );
76  //VERIFY( m(0) == low );
77
78  // check whether everything works with row and col major vectors
79  Matrix<Scalar,Dynamic,1> row_vector(size);
80  Matrix<Scalar,1,Dynamic> col_vector(size);
81  row_vector.setLinSpaced(size,low,high);
82  col_vector.setLinSpaced(size,low,high);
83  VERIFY( row_vector.isApprox(col_vector.transpose(), NumTraits<Scalar>::epsilon()));
84
85  Matrix<Scalar,Dynamic,1> size_changer(size+50);
86  size_changer.setLinSpaced(size,low,high);
87  VERIFY( size_changer.size() == size );
88
89  typedef Matrix<Scalar,1,1> ScalarMatrix;
90  ScalarMatrix scalar;
91  scalar.setLinSpaced(1,low,high);
92  VERIFY_IS_APPROX( scalar, ScalarMatrix::Constant(high) );
93  VERIFY_IS_APPROX( ScalarMatrix::LinSpaced(1,low,high), ScalarMatrix::Constant(high) );
94}
95
96template<typename MatrixType>
97void testMatrixType(const MatrixType& m)
98{
99  typedef typename MatrixType::Index Index;
100  const Index rows = m.rows();
101  const Index cols = m.cols();
102
103  MatrixType A;
104  A.setIdentity(rows, cols);
105  VERIFY(equalsIdentity(A));
106  VERIFY(equalsIdentity(MatrixType::Identity(rows, cols)));
107}
108
109void test_nullary()
110{
111  CALL_SUBTEST_1( testMatrixType(Matrix2d()) );
112  CALL_SUBTEST_2( testMatrixType(MatrixXcf(internal::random<int>(1,300),internal::random<int>(1,300))) );
113  CALL_SUBTEST_3( testMatrixType(MatrixXf(internal::random<int>(1,300),internal::random<int>(1,300))) );
114
115  for(int i = 0; i < g_repeat; i++) {
116    CALL_SUBTEST_4( testVectorType(VectorXd(internal::random<int>(1,300))) );
117    CALL_SUBTEST_5( testVectorType(Vector4d()) );  // regression test for bug 232
118    CALL_SUBTEST_6( testVectorType(Vector3d()) );
119    CALL_SUBTEST_7( testVectorType(VectorXf(internal::random<int>(1,300))) );
120    CALL_SUBTEST_8( testVectorType(Vector3f()) );
121    CALL_SUBTEST_8( testVectorType(Matrix<float,1,1>()) );
122  }
123}
124