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#include "calc_distance.h"
#include "spline.hpp"
#include <iostream>
#include <string>
#include <vector>
#include <statistics/chisq.hpp>
#include <methods/powell/powell_method.hpp>
#include <data_sets/default_data_set.hpp>
#include <misc/data_loaders.hpp>
#include "methods/aga/aga.hpp"
#include <models/beta1d.hpp>
#include <cstdlib>
using namespace std;
using namespace opt_utilities;
static const double cm=1;
static const double s=1;
static const double km=1000*100;
static const double Mpc=3.08568e+24*cm;
static const double kpc=3.08568e+21*cm;
static const double yr=365.*24.*3600.;
static const double Gyr=1e9*yr;
static const double H=71.*km/s/Mpc;
static const double c=299792458.*100.*cm;
//const double c=3e8*100*cm;
static const double pi=4*atan(1);
static const double omega_m=0.27;
static const double omega_l=0.73;
static const double arcsec2arc_ratio=1./60/60/180*pi;
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;
}
int main(int argc,char* argv[])
{
srand(time(0));
if(argc<5)
{
cerr<<"Usage:"<<argv[0]<<" <sbp data> <ratio file> <z> <r500 in kpc> [Tprofile.dat]"<<endl;
return -1;
}
double z=atof(argv[3]);
assert(z>0);
double d_a_cm=c/H*calc_angular_distance(z);
double d_l_cm=(1+z)*(1+z)*d_a_cm;
double cm_per_pixel=d_a_cm*.492*arcsec2arc_ratio;
//////////////////////////////
//perform a 1-beta fitting////
//////////////////////////////
fitter<double,double,vector<double>,double,string> f;
f.set_statistic(chisq<double,double,vector<double>,double,string>());
f.set_opt_method(powell_method<double,vector<double> >());
f.set_model(beta1d<double>());
dl_x_xe_y_ye<double,double> dl;
ifstream ifs(argv[1]);
ifs>>dl;
f.load_data(dl.get_data_set());
f.fit();
double rmin=f.get_data_set().get_data(0).get_x();
double rmax=f.get_data_set().get_data(f.get_data_set().size()-1).get_x();
ofstream lx_fit_result("lx_fit_result.qdp");
lx_fit_result<<"read terr 1 2\nskip single\n";
for(size_t i=0;i<f.get_data_set().size();++i)
{
lx_fit_result<<f.get_data_set().get_data(i).get_x()<<"\t"<<
-abs(f.get_data_set().get_data(i).get_x_lower_err())<<"\t"<<
abs(f.get_data_set().get_data(i).get_x_upper_err())<<"\t"<<
f.get_data_set().get_data(i).get_y()<<"\t"<<
-abs(f.get_data_set().get_data(i).get_y_lower_err())<<"\t"<<
abs(f.get_data_set().get_data(i).get_y_upper_err())<<endl;
}
lx_fit_result<<"no no no\n";
for(double i=rmin;i<rmax;i+=1)
{
lx_fit_result<<i<<"\t0\t0\t"<<f.eval_model(i,f.get_all_params())<<"\t0\t0"<<endl;
}
for(size_t i=0;i<f.get_num_params();++i)
{
cerr<<f.get_param_info(i).get_name()<<"="<<
f.get_param_info(i).get_value()<<endl;
}
vector<double> p=f.get_all_params();
double r500kpc=atof(argv[4]);
assert(r500kpc>0);
double r500pixel=r500kpc*kpc/cm_per_pixel;
const double dr=1;
double sum_cnt=0;
double sum_flux=0;
spline<double> spl;
ifstream ifs_ratio(argv[2]);
assert(ifs_ratio.is_open());
for(;;)
{
double x,y;
ifs_ratio>>x>>y;
if(!ifs_ratio.good())
{
break;
}
spl.push_point(x,y);
}
spl.gen_spline(0,0);
for(double r=0;r<r500pixel;r+=dr)
{
double r1=r<.2*r500pixel?.2*r500pixel:r;
double sbp=f.eval_model_raw(r1,p);
double cnt=sbp*pi*(2*r+dr)*dr;
double ratio=spl.get_value(r);
//cerr<<sbp<<endl;
sum_cnt+=cnt;
sum_flux+=cnt*ratio;
}
double lx=sum_flux*4*pi*d_l_cm*d_l_cm;
double l_mean=0;
double l2_mean=0;
double cnt=0;
for(int n=0;n<100;++n)
{
cerr<<".";
opt_utilities::default_data_set<double,double> ds(dl.get_data_set());
opt_utilities::default_data_set<double,double> ds1;
for(size_t i=0;i<ds.size();++i)
{
double yc=ds.get_data(i).get_y();
double ye=(std::abs(ds.get_data(i).get_y_lower_err())+std::abs(ds.get_data(i).get_y_lower_err()))/2;
double xc=ds.get_data(i).get_x();
double xe=(std::abs(ds.get_data(i).get_x_lower_err())+std::abs(ds.get_data(i).get_x_lower_err()))/2;
double newy=std_norm_rand()*ye+yc;
//cout<<yc<<"\t"<<newy<<endl;
ds1.add_data(data<double,double>(xc,newy,ye,ye,xe,xe));
}
f.load_data(ds1);
chisq<double,double,vector<double>,double,string> c;
//c.verbose(true);
f.set_statistic(c);
f.fit();
vector<double> p=f.get_all_params();
//cout<<f.get_param_value("beta")<<endl;
double sum_cnt=0;
double sum_flux=0;
for(double r=0;r<r500pixel;r+=dr)
{
double r1=r<.2*r500pixel?.2*r500pixel:r;
double sbp=f.eval_model_raw(r1,p);
double cnt=sbp*pi*(2*r+dr)*dr;
double ratio=spl.get_value(r);
sum_cnt+=cnt;
sum_flux+=cnt*ratio;
}
//cout<<sum_cnt<<endl;
double lx=sum_flux*4*pi*d_l_cm*d_l_cm;
l_mean+=lx;
l2_mean+=lx*lx;
cnt+=1;
//std::cerr<<lx<<endl;
//std::cerr<<f.get_param_value(
}
l_mean/=cnt;
l2_mean/=cnt;
cerr<<endl;
double std_l=std::sqrt(l2_mean-l_mean*l_mean);
double std_l2=0;
if(argc==6)
{
ifstream ifs_tfile(argv[5]);
assert(ifs_tfile.is_open());
double mean_T=0;
int cnt=0;
double mean_Te=0;
for(;;)
{
double r,re,t,te;
ifs_tfile>>r>>re>>t>>te;
if(!ifs_tfile.good())
{
break;
}
cnt+=1;
mean_T+=t;
mean_Te+=te*te;
}
mean_T/=cnt;
mean_Te/=cnt;
mean_Te=std::sqrt(mean_Te);
if(mean_Te>mean_T)
{
mean_Te=mean_T;
}
std_l2=mean_Te/mean_T*lx;
//cout<<mean_Te<<"\t"<<mean_T<<endl;
}
std_l=std::sqrt(std_l*std_l+std_l2*std_l2);
std::cout<<"Lx(bol): "<<lx<<" +/- "<<std_l<<" erg/s #Lx(bol) within r500"<<std::endl;
//std::cout<<sum_cnt<<std::endl;
}
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