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
|
/**
\file vchisq.hpp
\brief chi-square statistic
\author Junhua Gu
*/
#ifndef VCHI_SQ_HPP
#define VCHI_SQ_HPP
#define OPT_HEADER
#include <core/fitter.hpp>
#include <iostream>
#include <vector>
#include <misc/optvec.hpp>
#include <cmath>
using std::cerr;
using std::endl;
namespace opt_utilities
{
template<typename T>
class vchisq
:public statistic<std::vector<T>,std::vector<T>,std::vector<T>,T,std::string>
{
private:
bool verb;
bool limit_bound;
typedef std::vector<T> Tp;
vchisq<T>* do_clone()const
{
return new vchisq<T>(*this);
}
const char* do_get_type_name()const
{
return "chi^2 statistic";
}
public:
void verbose(bool v)
{
verb=v;
}
void set_limit()
{
limit_bound=true;
}
void clear_limit()
{
limit_bound=false;
}
public:
vchisq()
:verb(false),limit_bound(false)
{}
T do_eval(const std::vector<T>& p)
{
if(limit_bound)
{
if(!this->get_fitter().get_model().meets_constraint(p))
{
return 1e99;
}
}
T result(0);
std::vector<float> vx;
std::vector<float> vy;
std::vector<float> vye;
std::vector<float> my;
float x1=1e99,x2=-1e99,y1=1e99,y2=-1e99;
int n=0;
if(verb)
{
n++;
if(n%100==0)
{
vx.resize(this->get_data_set().get_data(0).get_y().size());
vy.resize(this->get_data_set().get_data(0).get_y().size());
vye.resize(this->get_data_set().get_data(0).get_y().size());
my.resize(this->get_data_set().get_data(0).get_y().size());
}
}
for(int i=(this->get_data_set()).size()-1;i>=0;--i)
{
const std::vector<double> y_model(this->eval_model(this->get_data_set().get_data(i).get_x(),p));
const std::vector<double>& y=this->get_data_set().get_data(i).get_y();
const std::vector<double>& ye=this->get_data_set().get_data(i).get_y_lower_err();
for(size_t j=0;j<y.size();++j)
{
double chi=(y_model[j]-y[j])/ye[j];
result+=chi*chi;
}
if(verb&&n%100==0)
{
for(size_t j=0;j<y.size();++j)
{
vx.at(j)=((this->get_data_set().get_data(i).get_x().at(j)+this->get_data_set().get_data(i).get_x().at(j+1))/2.);
vy.at(j)=(y[j]);
vye.at(j)=ye[j];
my.at(j)=(y_model[j]);
x1=std::min(vx.at(j),x1);
y1=std::min(vy.at(j),y1);
x2=std::max(vx.at(j),x2);
y2=std::max(vy.at(j),y2);
vye[j]=log10(vy[j]+vye[j])-log10(vy[j]);
vx[j]=log10(vx[j]);
vy[j]=log10(vy[j]);
my[j]=log10(my[j]);
}
}
}
if(verb)
{
if(n%100==0)
{
cerr<<result<<"\t";
for(size_t i=0;i<get_size(p);++i)
{
cerr<<get_element(p,i)<<",";
}
cerr<<endl;
}
}
return result;
}
};
}
#endif
|