1c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This file is part of Eigen, a lightweight C++ template library
2c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// for linear algebra.
3c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//
4c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
5c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//
6c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This Source Code Form is subject to the terms of the Mozilla
7c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Public License v. 2.0. If a copy of the MPL was not distributed
8c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
9c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
10c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define EIGEN2_SUPPORT
11c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include "main.h"
13c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
14c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename MatrixType> void eigen2support(const MatrixType& m)
15c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
16c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename MatrixType::Index Index;
17c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename MatrixType::Scalar Scalar;
18c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
19c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Index rows = m.rows();
20c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Index cols = m.cols();
21c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
22c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  MatrixType m1 = MatrixType::Random(rows, cols),
23c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath             m3(rows, cols);
24c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
25c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  Scalar  s1 = internal::random<Scalar>(),
26c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath          s2 = internal::random<Scalar>();
27c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
28c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  // scalar addition
29c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX(m1.cwise() + s1, s1 + m1.cwise());
30c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX(m1.cwise() + s1, MatrixType::Constant(rows,cols,s1) + m1);
31c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX((m1*Scalar(2)).cwise() - s2, (m1+m1) - MatrixType::Constant(rows,cols,s2) );
32c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  m3 = m1;
33c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  m3.cwise() += s2;
34c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX(m3, m1.cwise() + s2);
35c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  m3 = m1;
36c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  m3.cwise() -= s1;
37c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_APPROX(m3, m1.cwise() - s1);
38c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
39c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_EQUAL((m1.corner(TopLeft,1,1)), (m1.block(0,0,1,1)));
40c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_EQUAL((m1.template corner<1,1>(TopLeft)), (m1.template block<1,1>(0,0)));
41c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_EQUAL((m1.col(0).start(1)), (m1.col(0).segment(0,1)));
42c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_EQUAL((m1.col(0).template start<1>()), (m1.col(0).segment(0,1)));
43c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_EQUAL((m1.col(0).end(1)), (m1.col(0).segment(rows-1,1)));
44c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_EQUAL((m1.col(0).template end<1>()), (m1.col(0).segment(rows-1,1)));
45c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
467faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  using std::cos;
477faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  using numext::real;
487faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  using numext::abs2;
49c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_EQUAL(ei_cos(s1), cos(s1));
50c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_EQUAL(ei_real(s1), real(s1));
51c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY_IS_EQUAL(ei_abs2(s1), abs2(s1));
52c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
53c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  m1.minor(0,0);
54c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
55c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
56c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathvoid test_eigen2support()
57c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
58c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for(int i = 0; i < g_repeat; i++) {
59c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    CALL_SUBTEST_1( eigen2support(Matrix<double,1,1>()) );
60c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    CALL_SUBTEST_2( eigen2support(MatrixXd(1,1)) );
61c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    CALL_SUBTEST_4( eigen2support(Matrix3f()) );
62c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    CALL_SUBTEST_5( eigen2support(Matrix4d()) );
63c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    CALL_SUBTEST_2( eigen2support(MatrixXf(200,200)) );
64c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    CALL_SUBTEST_6( eigen2support(MatrixXcd(100,100)) );
65c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
66c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
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