1c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This file is part of Eigen, a lightweight C++ template library
2c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// for linear algebra.
3c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//
4c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
5c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
6c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//
7c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This Source Code Form is subject to the terms of the Mozilla
8c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Public License v. 2.0. If a copy of the MPL was not distributed
9c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
10c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
11c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define EIGEN2_SUPPORT
12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define EIGEN_NO_STATIC_ASSERT
13c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include "main.h"
14c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include <functional>
15c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
16c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#ifdef min
17c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#undef min
18c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#endif
19c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
20c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#ifdef max
21c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#undef max
22c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#endif
23c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
24c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathusing namespace std;
25c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
26c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar> struct AddIfNull {
27c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    const Scalar operator() (const Scalar a, const Scalar b) const {return a<=1e-3 ? b : a;}
28c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    enum { Cost = NumTraits<Scalar>::AddCost };
29c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
30c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
31c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename MatrixType> void cwiseops(const MatrixType& m)
32c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
33c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename MatrixType::Index Index;
34c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename MatrixType::Scalar Scalar;
35c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename NumTraits<Scalar>::Real RealScalar;
36c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
37c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
38c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Index rows = m.rows();
39c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Index cols = m.cols();
40c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
41c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  MatrixType m1 = MatrixType::Random(rows, cols),
42c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath             m2 = MatrixType::Random(rows, cols),
43c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath             m3(rows, cols),
44c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath             m4(rows, cols),
45c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath             mzero = MatrixType::Zero(rows, cols),
46c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath             mones = MatrixType::Ones(rows, cols),
47c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath             identity = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>
48c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath                              ::Identity(rows, rows);
49c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VectorType vzero = VectorType::Zero(rows),
50c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath             vones = VectorType::Ones(rows),
51c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath             v3(rows);
52c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
53c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Index r = internal::random<Index>(0, rows-1),
54c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        c = internal::random<Index>(0, cols-1);
55c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
56c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Scalar s1 = internal::random<Scalar>();
57c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
58c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // test Zero, Ones, Constant, and the set* variants
59c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  m3 = MatrixType::Constant(rows, cols, s1);
60c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int j=0; j<cols; ++j)
61c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for (int i=0; i<rows; ++i)
62c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
63c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      VERIFY_IS_APPROX(mzero(i,j), Scalar(0));
64c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      VERIFY_IS_APPROX(mones(i,j), Scalar(1));
65c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      VERIFY_IS_APPROX(m3(i,j), s1);
66c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
67c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY(mzero.isZero());
68c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY(mones.isOnes());
69c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY(m3.isConstant(s1));
70c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY(identity.isIdentity());
71c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX(m4.setConstant(s1), m3);
72c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX(m4.setConstant(rows,cols,s1), m3);
73c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX(m4.setZero(), mzero);
74c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX(m4.setZero(rows,cols), mzero);
75c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX(m4.setOnes(), mones);
76c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX(m4.setOnes(rows,cols), mones);
77c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  m4.fill(s1);
78c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX(m4, m3);
79c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
80c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX(v3.setConstant(rows, s1), VectorType::Constant(rows,s1));
81c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX(v3.setZero(rows), vzero);
82c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX(v3.setOnes(rows), vones);
83c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
84c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  m2 = m2.template binaryExpr<AddIfNull<Scalar> >(mones);
85c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
86c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX(m1.cwise().pow(2), m1.cwise().abs2());
87c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX(m1.cwise().pow(2), m1.cwise().square());
88c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX(m1.cwise().pow(3), m1.cwise().cube());
89c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
90c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX(m1 + mones, m1.cwise()+Scalar(1));
91c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX(m1 - mones, m1.cwise()-Scalar(1));
92c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  m3 = m1; m3.cwise() += 1;
93c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX(m1 + mones, m3);
94c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  m3 = m1; m3.cwise() -= 1;
95c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX(m1 - mones, m3);
96c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
97c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX(m2, m2.cwise() * mones);
98c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX(m1.cwise() * m2,  m2.cwise() * m1);
99c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  m3 = m1;
100c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  m3.cwise() *= m2;
101c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX(m3, m1.cwise() * m2);
102c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
103c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX(mones,    m2.cwise()/m2);
104c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  if(!NumTraits<Scalar>::IsInteger)
105c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
106c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    VERIFY_IS_APPROX(m1.cwise() / m2,    m1.cwise() * (m2.cwise().inverse()));
107c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    m3 = m1.cwise().abs().cwise().sqrt();
108c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    VERIFY_IS_APPROX(m3.cwise().square(), m1.cwise().abs());
109c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    VERIFY_IS_APPROX(m1.cwise().square().cwise().sqrt(), m1.cwise().abs());
110c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    VERIFY_IS_APPROX(m1.cwise().abs().cwise().log().cwise().exp() , m1.cwise().abs());
111c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
112c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    VERIFY_IS_APPROX(m1.cwise().pow(2), m1.cwise().square());
113c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    m3 = (m1.cwise().abs().cwise()<=RealScalar(0.01)).select(mones,m1);
114c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    VERIFY_IS_APPROX(m3.cwise().pow(-1), m3.cwise().inverse());
115c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    m3 = m1.cwise().abs();
116c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    VERIFY_IS_APPROX(m3.cwise().pow(RealScalar(0.5)), m3.cwise().sqrt());
117c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
118c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//     VERIFY_IS_APPROX(m1.cwise().tan(), m1.cwise().sin().cwise() / m1.cwise().cos());
119c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    VERIFY_IS_APPROX(mones, m1.cwise().sin().cwise().square() + m1.cwise().cos().cwise().square());
120c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    m3 = m1;
121c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    m3.cwise() /= m2;
122c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    VERIFY_IS_APPROX(m3, m1.cwise() / m2);
123c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
124c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
125c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // check min
126c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX( m1.cwise().min(m2), m2.cwise().min(m1) );
127c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX( m1.cwise().min(m1+mones), m1 );
128c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX( m1.cwise().min(m1-mones), m1-mones );
129c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
130c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // check max
131c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX( m1.cwise().max(m2), m2.cwise().max(m1) );
132c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX( m1.cwise().max(m1-mones), m1 );
133c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX( m1.cwise().max(m1+mones), m1+mones );
134c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
135c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY( (m1.cwise() == m1).all() );
136c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY( (m1.cwise() != m2).any() );
137c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY(!(m1.cwise() == (m1+mones)).any() );
138c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  if (rows*cols>1)
139c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
140c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    m3 = m1;
141c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    m3(r,c) += 1;
142c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    VERIFY( (m1.cwise() == m3).any() );
143c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    VERIFY( !(m1.cwise() == m3).all() );
144c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
145c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY( (m1.cwise().min(m2).cwise() <= m2).all() );
146c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY( (m1.cwise().max(m2).cwise() >= m2).all() );
147c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY( (m1.cwise().min(m2).cwise() < (m1+mones)).all() );
148c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY( (m1.cwise().max(m2).cwise() > (m1-mones)).all() );
149c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
150c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY( (m1.cwise()<m1.unaryExpr(bind2nd(plus<Scalar>(), Scalar(1)))).all() );
151c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY( !(m1.cwise()<m1.unaryExpr(bind2nd(minus<Scalar>(), Scalar(1)))).all() );
152c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY( !(m1.cwise()>m1.unaryExpr(bind2nd(plus<Scalar>(), Scalar(1)))).any() );
153c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
154c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
155c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathvoid test_cwiseop()
156c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
157c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for(int i = 0; i < g_repeat ; i++) {
158c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    CALL_SUBTEST_1( cwiseops(Matrix<float, 1, 1>()) );
159c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    CALL_SUBTEST_2( cwiseops(Matrix4d()) );
160c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    CALL_SUBTEST_3( cwiseops(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
161c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    CALL_SUBTEST_4( cwiseops(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
162c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    CALL_SUBTEST_5( cwiseops(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
163c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    CALL_SUBTEST_6( cwiseops(MatrixXd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
164c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
165c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
166