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
|
// Copyright (c) 2009 libmv authors.
//
// Permission is hereby granted, free of charge, to any person obtaining a copy
// of this software and associated documentation files (the "Software"), to
// deal in the Software without restriction, including without limitation the
// rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
// sell copies of the Software, and to permit persons to whom the Software is
// furnished to do so, subject to the following conditions:
//
// The above copyright notice and this permission notice shall be included in
// all copies or substantial portions of the Software.
//
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
// IN THE SOFTWARE.
#include "testing/testing.h"
#include "libmv/numeric/dogleg.h"
using namespace libmv;
namespace {
class F {
public:
typedef Vec4 FMatrixType;
typedef Vec3 XMatrixType;
Vec4 operator()(const Vec3 &x) const {
double x1 = x.x() - 2;
double y1 = x.y() - 5;
double z1 = x.z();
Vec4 fx; fx << x1*x1 + z1*z1,
y1*y1 + z1*z1,
z1*z1,
x1*x1;
return fx;
}
};
TEST(Dogleg, SimpleCase) {
Vec3 x; x << 0.76026643, -30.01799744, 0.55192142;
F f;
Dogleg<F>::SolverParameters params;
Dogleg<F> lm(f);
/* TODO(sergey): Better error handling. */
/* Dogleg<F>::Results results = */ lm.minimize(params, &x);
Vec3 expected_min_x; expected_min_x << 2, 5, 0;
EXPECT_MATRIX_NEAR(expected_min_x, x, 1e-5);
}
// Example 3.2 from [1]; page 11 of the pdf, 20 of the document. This is a
// tricky problem because of the singluar Jacobian near the origin.
class F32 {
public:
typedef Vec2 FMatrixType;
typedef Vec2 XMatrixType;
Vec2 operator()(const Vec2 &x) const {
double x1 = x(0);
double x2 = 10*x(0)/(x(0) + 0.1) + 2*x(1)*x(1);
Vec2 fx; fx << x1, x2;
return fx;
}
};
class JF32 {
public:
JF32(const F32 &f) { (void) f; }
Mat2 operator()(const Vec2 &x) {
Mat2 J; J << 1, 0,
1./pow(x(0) + 0.1, 2), 4*x(1)*x(1);
return J;
}
};
// TODO(keir): Re-enable this when the dogleg code properly handles singular
// normal equations.
/*
TEST(Dogleg, Example32) {
Vec2 x; x << 3, 1;
F32 f;
CheckJacobian<F32, JF32>(f, x);
Dogleg<F32, JF32> dogleg(f);
Dogleg<F32, JF32>::Results results = dogleg.minimize(&x);
Vec2 expected_min_x; expected_min_x << 0, 0;
EXPECT_MATRIX_NEAR(expected_min_x, x, 1e-5);
}
*/
} // namespace
|
