From f77885e968e30b28669b4d24af75ec4e7bb0a41e Mon Sep 17 00:00:00 2001
From: Aaron LI <aaronly.me@outlook.com>
Date: Fri, 17 Feb 2017 23:33:55 +0800
Subject: Remove unused 'fit_{lt,mt}_{bpl,pl}.cpp' tools

---
 mass_profile/fit_lt_pl.cpp | 239 ---------------------------------------------
 1 file changed, 239 deletions(-)
 delete mode 100644 mass_profile/fit_lt_pl.cpp

(limited to 'mass_profile/fit_lt_pl.cpp')

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;
-
-}
-- 
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