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authorAaron LI <aaronly.me@outlook.com>2017-02-17 23:33:55 +0800
committerAaron LI <aaronly.me@outlook.com>2017-02-17 23:33:55 +0800
commitf77885e968e30b28669b4d24af75ec4e7bb0a41e (patch)
tree778137030c73d5070e6cb587e0b7f31d03ed8423 /mass_profile/fit_lt_pl.cpp
parent61c7e9781c1bb3447fc5ae2362ebbac12158e4d3 (diff)
downloadchandra-acis-analysis-f77885e968e30b28669b4d24af75ec4e7bb0a41e.tar.bz2
Remove unused 'fit_{lt,mt}_{bpl,pl}.cpp' tools
Diffstat (limited to 'mass_profile/fit_lt_pl.cpp')
-rw-r--r--mass_profile/fit_lt_pl.cpp239
1 files changed, 0 insertions, 239 deletions
diff --git a/mass_profile/fit_lt_pl.cpp b/mass_profile/fit_lt_pl.cpp
deleted file mode 100644
index fa37249..0000000
--- a/mass_profile/fit_lt_pl.cpp
+++ /dev/null
@@ -1,239 +0,0 @@
-/*
- 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 <iostream>
-#include <sstream>
-#include <fstream>
-#include <models/pl1d.hpp>
-#include <models/lin1d.hpp>
-#include "statistics/chisq.hpp"
-#include "statistics/leastsq.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 x=0;
- double u=0;
- double v=0;
-
- do
- {
- u=rand()/(double)RAND_MAX;
- rand();
- v=rand()/(double)RAND_MAX;
-
- x=std::sqrt(-log(u))*cos(2*pi*v);
- }while(isnan(x));
- return x;
-}
-
-double shuffle_data(double xc,double xl,double xu)
-{
- double result=0;
- assert(!isnan(xc));
- assert(!isnan(xl));
- assert(!isnan(xu));
- if(std_norm_rand()>0)
- {
- result=xc-std::abs(std_norm_rand()*xl);
- }
- else
- {
- result=xc+std::abs(std_norm_rand()*xu);
- }
- assert(!isnan(result));
- return result;
-}
-
-int main(int argc,char* argv[])
-{
- if(argc!=3)
- {
- cerr<<"Usage:"<<argv[0]<<" <a 5 column file with T -Terr +Terr L Lerr> <T lower 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("l-t_result.qdp");
- ofs_result<<"read terr 1"<<endl;
- ofs_result<<"read serr 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 Luminosity (10\\u43\\d erg s\\u-1\\d)"<<endl;
- double yunit=1E43;
- 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 L,Lerr;
- std::string line;
- getline(ifs_data,line);
-
-
- 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>>L>>Lerr;
- //std::cerr<<L<<"\t"<<Lerr<<endl;
- if(!iss.good())
- {
- continue;
- }
- if(T<T_lower_limit||L<0)
- {
- continue;
- }
- if(Lerr<L*.1)
- {
- Lerr=L*.1;
- }
- double Ll=Lerr;
- double Lu=Lerr;
- Tl=std::abs(Tl);
- Tu=std::abs(Tu);
- Ll=std::abs(Ll);
- Lu=std::abs(Lu);
- ofs_result<<T<<"\t"<<-std::abs(Tl)<<"\t"<<+std::abs(Tu)<<"\t"<<L/yunit<<"\t"<<std::abs(Lerr)/yunit<<endl;
- double x=log(T);
- double y=log(L);
- double xu=log(T+Tu)-log(T);
- double xl=log(T-Tl)-log(T);
-
- double yu=log(L+Lu)-log(L);
- double yl=log(L-Ll)-log(L);
- 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(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);
- fit.fit();
- std::vector<double> p=fit.fit();
- for(double i=.5;i<12;i*=1.01)
- {
- ofs_result<<i<<"\t0\t0\t"<<exp(fit.eval_model_raw(log(i),p))/yunit<<"\t0\n";
- }
-
-
- 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(size_t 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()));
- //cerr<<new_x<<"\t"<<new_y<<endl;
- }
- 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<<"L=L0*T^gamma"<<endl;
- std::cout<<"L0= "<<exp(p[1])<<"+/-"<<std_A<<endl;
- std::cout<<"gamma= "<<p[0]<<"+/-"<<std_g<<endl;
- std::cout<<"Num of sources:"<<ds.size()<<endl;
-
-}