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
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
|
/*
Perform a double-beta density model fitting to the surface brightness data
Author: Junhua Gu
Last modified: 2011.01.01
This code is distributed with no warrant
*/
//#define HAVE_X_ERROR
#include <iomanip>
#include <iostream>
#include <sstream>
#include <fstream>
#include <models/pl1d.hpp>
#include <models/lin1d.hpp>
#include "statistics/chisq.hpp"
#include "statistics/leastsq.hpp"
#include "statistics/robust_chisq.hpp"
#include <data_sets/default_data_set.hpp>
#include <methods/powell/powell_method.hpp>
#include <core/freeze_param.hpp>
using namespace std;
using namespace opt_utilities;
//double s=5.63136645E20;
const double kpc=3.086E21;//kpc in cm
const double Mpc=kpc*1000;
const double pi=4*atan(1);
double std_norm_rand()
{
double u=0;
double v=0;
while(u<=0||v<=0)
{
u=rand()/(double)RAND_MAX;
rand();
v=rand()/(double)RAND_MAX;
}
double x=std::sqrt(-log(u))*cos(2*pi*v);
return x;
}
double shuffle_data(double xc,double xl,double xu)
{
if(std_norm_rand()>0)
{
double result=xc-std::abs(std_norm_rand()*xl);
return result;
}
else
{
double result= xc+std::abs(std_norm_rand()*xu);
return result;
}
}
int main(int argc,char* argv[])
{
if(argc!=3)
{
cerr<<"Usage:"<<argv[0]<<" <a 6 column file with T -Terr +Terr M -Merr +Merr> <lower T limit>"<<endl;
return -1;
}
double T_lower_limit(atof(argv[2]));
ifstream ifs_data(argv[1]);
default_data_set<double,double> ds;
ofstream ofs_result("m-t_result.qdp");
ofs_result<<"read terr 1 2"<<endl;
ofs_result<<"skip single"<<endl;
ofs_result<<"log"<<endl;
//ofs_result<<"li on 2"<<endl;
ofs_result<<"time off"<<endl;
ofs_result<<"la f"<<endl;
ofs_result<<"la x temperature (keV)"<<endl;
ofs_result<<"la y mass (M\\dsun\\u)"<<endl;
double sxx=0;
double s1=0;
double sx=0;
double sy=0;
double sxy=0;
bool is_first_nonono=true;
for(;;)
{
double T,Tl,Tu;
double M,Ml,Mu;
std::string line;
getline(ifs_data,line);
//ifs_data>>T>>Tl>>Tu>>M>>Ml>>Mu;
if(!ifs_data.good())
{
break;
}
line+=" ";
istringstream iss(line);
if(line[0]=='#')
{
if(!is_first_nonono)
{
ofs_result<<"no no no"<<endl;
}
else
{
is_first_nonono=false;
}
continue;
}
iss>>T>>Tl>>Tu>>M>>Ml>>Mu;
//std::cerr<<L<<"\t"<<Lerr<<endl;
if(!iss.good())
{
continue;
}
if(T<T_lower_limit||M<0)
{
continue;
}
if(std::abs(Mu)<M*.1||std::abs(Ml)<M*.1)
{
cerr<<"mass error less than 10%, skipped"<<endl;
cerr<<line<<endl;
continue;
}
#if 1
if(std::abs(Tu)<.1||std::abs(Tl)<.1)
{
cerr<<"T error less than 10%, skipped"<<endl;
cerr<<line<<endl;
continue;
}
#endif
if(std::abs(Mu)+std::abs(Ml)<M*.1)
{
double k=M*.1/(std::abs(Mu)+std::abs(Ml));
Mu*=k;
Ml*=k;
}
Tl=std::abs(Tl);
Tu=std::abs(Tu);
Ml=std::abs(Ml);
Mu=std::abs(Mu);
ofs_result<<T<<"\t"<<-std::abs(Tl)<<"\t"<<+std::abs(Tu)<<"\t"<<M<<"\t"<<-std::abs(Ml)<<"\t"<<+std::abs(Mu)<<endl;
double x=log(T);
double y=log(M);
double xu=log(T+Tu)-log(T);
double xl=log(T-Tl)-log(T);
double yu=log(M+Mu)-log(M);
double yl=log(M-Ml)-log(M);
if(isnan(x)||isnan(y)||isnan(yl)||isnan(yu)||
isnan(xl)||isnan(xu))
{
std::cerr<<"one data with error > data, skipped"<<endl;
std::cerr<<line<<endl;
continue;
}
sxx+=x*x;
sx+=x;
sy+=y;
sxy+=y*x;
s1+=1;
data<double,double> d(x,y,std::abs(yl),std::abs(yu),
std::abs(xl),std::abs(xu));
ds.add_data(d);
}
double M=sxx*s1-sx*sx;
double Ma=sxy*s1-sy*sx;
double Mb=sxx*sy-sx*sxy;
double k0=Ma/M;
double b0=Mb/M;
ofs_result<<"no no no"<<endl;
fitter<double,double,vector<double>,double,std::string> fit;
fit.set_opt_method(powell_method<double,vector<double> >());
fit.set_statistic(chisq<double,double,vector<double>,double,std::string>());
//fit.set_statistic(robust_chisq<double,double,vector<double>,double,std::string>());
//fit.set_statistic(leastsq<double,double,vector<double>,double,std::string>());
fit.set_model(lin1d<double>());
fit.load_data(ds);
cerr<<"k0="<<k0<<endl;
cerr<<"b0="<<b0<<endl;
cerr<<"Ampl0="<<exp(b0)<<endl;
cerr<<"gamma0="<<k0<<endl;
fit.set_param_value("k",k0);
fit.set_param_value("b",b0);
std::vector<double> p=fit.get_all_params();
std::cout<<"chi="<<fit.get_statistic().eval(p)<<std::endl;
fit.fit();
fit.fit();
p=fit.fit();
std::cout<<"chi="<<fit.get_statistic().eval(p)<<std::endl;
for(double i=.5;i<12;i*=1.01)
{
ofs_result<<i<<"\t0\t0\t"<<exp(fit.eval_model_raw(log(i),p))<<"\t0\t0\n";
}
ofstream ofs_resid("resid.qdp");
ofs_resid<<"read terr 1 2 3"<<endl;
ofs_resid<<"skip single"<<endl;
ofs_resid<<"ma 3 on 1"<<endl;
ofs_resid<<"log x"<<endl;
for(int i=0;i<ds.size();++i)
{
double x=ds.get_data(i).get_x();
double y=ds.get_data(i).get_y();
double xe1=-ds.get_data(i).get_x_lower_err()*0;
double xe2=ds.get_data(i).get_x_upper_err()*0;
double ye1=-ds.get_data(i).get_y_lower_err();
double ye2=ds.get_data(i).get_y_upper_err();
ofs_resid<<exp(x)<<"\t"<<0<<"\t"<<0<<"\t"<<y-fit.eval_model_raw(x,p)<<"\t"<<ye1<<"\t"<<ye2<<"\t"<<"0\t0\t0"<<endl;
}
double mean_A=0;
double mean_A2=0;
double mean_g=0;
double mean_g2=0;
int cnt=0;
for(int n=0;n<100;++n)
{
++cnt;
cerr<<".";
opt_utilities::default_data_set<double,double> ds1;
for(int i=0;i<ds.size();++i)
{
double new_x=shuffle_data(ds.get_data(i).get_x(),
ds.get_data(i).get_x_lower_err(),
ds.get_data(i).get_x_upper_err());
double new_y=shuffle_data(ds.get_data(i).get_y(),
ds.get_data(i).get_y_lower_err(),
ds.get_data(i).get_y_upper_err());
ds1.add_data(data<double,double>(new_x,new_y,
ds.get_data(i).get_y_lower_err(),
ds.get_data(i).get_y_upper_err(),
ds.get_data(i).get_y_lower_err(),
ds.get_data(i).get_y_upper_err()));
}
fit.load_data(ds1);
fit.fit();
double k=fit.get_param_value("k");
double b=fit.get_param_value("b");
double A=exp(b);
double g=k;
mean_A+=A;
mean_A2+=A*A;
mean_g+=g;
mean_g2+=g*g;
}
std::cerr<<endl;
mean_A/=cnt;
mean_A2/=cnt;
mean_g/=cnt;
mean_g2/=cnt;
double std_A=std::sqrt(mean_A2-mean_A*mean_A);
double std_g=std::sqrt(mean_g2-mean_g*mean_g);
std::cerr<<"M=M0*T^gamma"<<endl;
std::cout<<"M0= "<<exp(p[1])<<"+/-"<<std_A<<endl;
std::cout<<"gamma= "<<p[0]<<"+/-"<<std_g<<endl;
std::cout<<"Num of sources:"<<ds.size()<<endl;
}
|
