aboutsummaryrefslogtreecommitdiffhomepage
path: root/test/adjoint.cpp
blob: bdea51c108369532a03276feef70988e9078684a (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.

#define EIGEN_NO_STATIC_ASSERT

#include "main.h"

template<bool IsInteger> struct adjoint_specific;

template<> struct adjoint_specific<true> {
  template<typename Vec, typename Mat, typename Scalar>
  static void run(const Vec& v1, const Vec& v2, Vec& v3, const Mat& square, Scalar s1, Scalar s2) {
    VERIFY(test_isApproxWithRef((s1 * v1 + s2 * v2).dot(v3),     numext::conj(s1) * v1.dot(v3) + numext::conj(s2) * v2.dot(v3), 0));
    VERIFY(test_isApproxWithRef(v3.dot(s1 * v1 + s2 * v2),       s1*v3.dot(v1)+s2*v3.dot(v2), 0));
    
    // check compatibility of dot and adjoint
    VERIFY(test_isApproxWithRef(v1.dot(square * v2), (square.adjoint() * v1).dot(v2), 0));
  }
};

template<> struct adjoint_specific<false> {
  template<typename Vec, typename Mat, typename Scalar>
  static void run(const Vec& v1, const Vec& v2, Vec& v3, const Mat& square, Scalar s1, Scalar s2) {
    typedef typename NumTraits<Scalar>::Real RealScalar;
    using std::abs;
    
    RealScalar ref = NumTraits<Scalar>::IsInteger ? RealScalar(0) : (std::max)((s1 * v1 + s2 * v2).norm(),v3.norm());
    VERIFY(test_isApproxWithRef((s1 * v1 + s2 * v2).dot(v3),     numext::conj(s1) * v1.dot(v3) + numext::conj(s2) * v2.dot(v3), ref));
    VERIFY(test_isApproxWithRef(v3.dot(s1 * v1 + s2 * v2),       s1*v3.dot(v1)+s2*v3.dot(v2), ref));
  
    VERIFY_IS_APPROX(v1.squaredNorm(),                v1.norm() * v1.norm());
    // check normalized() and normalize()
    VERIFY_IS_APPROX(v1, v1.norm() * v1.normalized());
    v3 = v1;
    v3.normalize();
    VERIFY_IS_APPROX(v1, v1.norm() * v3);
    VERIFY_IS_APPROX(v3, v1.normalized());
    VERIFY_IS_APPROX(v3.norm(), RealScalar(1));

    // check null inputs
    VERIFY_IS_APPROX((v1*0).normalized(), (v1*0));
#if (!EIGEN_ARCH_i386) || defined(EIGEN_VECTORIZE)
    RealScalar very_small = (std::numeric_limits<RealScalar>::min)();
    VERIFY( (v1*very_small).norm() == 0 );
    VERIFY_IS_APPROX((v1*very_small).normalized(), (v1*very_small));
    v3 = v1*very_small;
    v3.normalize();
    VERIFY_IS_APPROX(v3, (v1*very_small));
#endif
    
    // check compatibility of dot and adjoint
    ref = NumTraits<Scalar>::IsInteger ? 0 : (std::max)((std::max)(v1.norm(),v2.norm()),(std::max)((square * v2).norm(),(square.adjoint() * v1).norm()));
    VERIFY(internal::isMuchSmallerThan(abs(v1.dot(square * v2) - (square.adjoint() * v1).dot(v2)), ref, test_precision<Scalar>()));
    
    // check that Random().normalized() works: tricky as the random xpr must be evaluated by
    // normalized() in order to produce a consistent result.
    VERIFY_IS_APPROX(Vec::Random(v1.size()).normalized().norm(), RealScalar(1));
  }
};

template<typename MatrixType> void adjoint(const MatrixType& m)
{
  /* this test covers the following files:
     Transpose.h Conjugate.h Dot.h
  */
  using std::abs;
  typedef typename MatrixType::Index Index;
  typedef typename MatrixType::Scalar Scalar;
  typedef typename NumTraits<Scalar>::Real RealScalar;
  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> SquareMatrixType;
  const Index PacketSize = internal::packet_traits<Scalar>::size;
  
  Index rows = m.rows();
  Index cols = m.cols();

  MatrixType m1 = MatrixType::Random(rows, cols),
             m2 = MatrixType::Random(rows, cols),
             m3(rows, cols),
             square = SquareMatrixType::Random(rows, rows);
  VectorType v1 = VectorType::Random(rows),
             v2 = VectorType::Random(rows),
             v3 = VectorType::Random(rows),
             vzero = VectorType::Zero(rows);

  Scalar s1 = internal::random<Scalar>(),
         s2 = internal::random<Scalar>();

  // check basic compatibility of adjoint, transpose, conjugate
  VERIFY_IS_APPROX(m1.transpose().conjugate().adjoint(),    m1);
  VERIFY_IS_APPROX(m1.adjoint().conjugate().transpose(),    m1);

  // check multiplicative behavior
  VERIFY_IS_APPROX((m1.adjoint() * m2).adjoint(),           m2.adjoint() * m1);
  VERIFY_IS_APPROX((s1 * m1).adjoint(),                     numext::conj(s1) * m1.adjoint());

  // check basic properties of dot, squaredNorm
  VERIFY_IS_APPROX(numext::conj(v1.dot(v2)),               v2.dot(v1));
  VERIFY_IS_APPROX(numext::real(v1.dot(v1)),               v1.squaredNorm());
  
  adjoint_specific<NumTraits<Scalar>::IsInteger>::run(v1, v2, v3, square, s1, s2);
  
  VERIFY_IS_MUCH_SMALLER_THAN(abs(vzero.dot(v1)),  static_cast<RealScalar>(1));
  
  // like in testBasicStuff, test operator() to check const-qualification
  Index r = internal::random<Index>(0, rows-1),
      c = internal::random<Index>(0, cols-1);
  VERIFY_IS_APPROX(m1.conjugate()(r,c), numext::conj(m1(r,c)));
  VERIFY_IS_APPROX(m1.adjoint()(c,r), numext::conj(m1(r,c)));

  // check inplace transpose
  m3 = m1;
  m3.transposeInPlace();
  VERIFY_IS_APPROX(m3,m1.transpose());
  m3.transposeInPlace();
  VERIFY_IS_APPROX(m3,m1);
  
  if(PacketSize<m3.rows() && PacketSize<m3.cols())
  {
    m3 = m1;
    Index i = internal::random<Index>(0,m3.rows()-PacketSize);
    Index j = internal::random<Index>(0,m3.cols()-PacketSize);
    m3.template block<PacketSize,PacketSize>(i,j).transposeInPlace();
    VERIFY_IS_APPROX( (m3.template block<PacketSize,PacketSize>(i,j)), (m1.template block<PacketSize,PacketSize>(i,j).transpose()) );
    m3.template block<PacketSize,PacketSize>(i,j).transposeInPlace();
    VERIFY_IS_APPROX(m3,m1);
  }

  // check inplace adjoint
  m3 = m1;
  m3.adjointInPlace();
  VERIFY_IS_APPROX(m3,m1.adjoint());
  m3.transposeInPlace();
  VERIFY_IS_APPROX(m3,m1.conjugate());

  // check mixed dot product
  typedef Matrix<RealScalar, MatrixType::RowsAtCompileTime, 1> RealVectorType;
  RealVectorType rv1 = RealVectorType::Random(rows);
  VERIFY_IS_APPROX(v1.dot(rv1.template cast<Scalar>()), v1.dot(rv1));
  VERIFY_IS_APPROX(rv1.template cast<Scalar>().dot(v1), rv1.dot(v1));
}

void test_adjoint()
{
  for(int i = 0; i < g_repeat; i++) {
    CALL_SUBTEST_1( adjoint(Matrix<float, 1, 1>()) );
    CALL_SUBTEST_2( adjoint(Matrix3d()) );
    CALL_SUBTEST_3( adjoint(Matrix4f()) );
    
    CALL_SUBTEST_4( adjoint(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2), internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2))) );
    CALL_SUBTEST_5( adjoint(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
    CALL_SUBTEST_6( adjoint(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
    
    // Complement for 128 bits vectorization:
    CALL_SUBTEST_8( adjoint(Matrix2d()) );
    CALL_SUBTEST_9( adjoint(Matrix<int,4,4>()) );
    
    // 256 bits vectorization:
    CALL_SUBTEST_10( adjoint(Matrix<float,8,8>()) );
    CALL_SUBTEST_11( adjoint(Matrix<double,4,4>()) );
    CALL_SUBTEST_12( adjoint(Matrix<int,8,8>()) );
  }
  // test a large static matrix only once
  CALL_SUBTEST_7( adjoint(Matrix<float, 100, 100>()) );

#ifdef EIGEN_TEST_PART_13
  {
    MatrixXcf a(10,10), b(10,10);
    VERIFY_RAISES_ASSERT(a = a.transpose());
    VERIFY_RAISES_ASSERT(a = a.transpose() + b);
    VERIFY_RAISES_ASSERT(a = b + a.transpose());
    VERIFY_RAISES_ASSERT(a = a.conjugate().transpose());
    VERIFY_RAISES_ASSERT(a = a.adjoint());
    VERIFY_RAISES_ASSERT(a = a.adjoint() + b);
    VERIFY_RAISES_ASSERT(a = b + a.adjoint());

    // no assertion should be triggered for these cases:
    a.transpose() = a.transpose();
    a.transpose() += a.transpose();
    a.transpose() += a.transpose() + b;
    a.transpose() = a.adjoint();
    a.transpose() += a.adjoint();
    a.transpose() += a.adjoint() + b;

    // regression tests for check_for_aliasing
    MatrixXd c(10,10);
    c = 1.0 * MatrixXd::Ones(10,10) + c;
    c = MatrixXd::Ones(10,10) * 1.0 + c;
    c = c + MatrixXd::Ones(10,10) .cwiseProduct( MatrixXd::Zero(10,10) );
    c = MatrixXd::Ones(10,10) * MatrixXd::Zero(10,10);
  }
#endif
}