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| author | Aaron LI <aaronly.me@outlook.com> | 2017-02-20 12:26:17 +0800 |
|---|---|---|
| committer | Aaron LI <aaronly.me@outlook.com> | 2017-02-20 12:26:17 +0800 |
| commit | 4ea7a05ea9a7352602f1f48a860fd81c36e8bc04 (patch) | |
| tree | beab7ec18d48c3e2093cd35fd8c79bd66f604a03 /src/chisq.hpp | |
| parent | 9cec16d87f6dc2e0b34b605d88d0837a4a48d18c (diff) | |
| download | chandra-acis-analysis-4ea7a05ea9a7352602f1f48a860fd81c36e8bc04.tar.bz2 | |
Rename mass_profile to src; Add install & uninstall to Makefile
Diffstat (limited to 'src/chisq.hpp')
| -rw-r--r-- | src/chisq.hpp | 206 |
1 files changed, 206 insertions, 0 deletions
diff --git a/src/chisq.hpp b/src/chisq.hpp new file mode 100644 index 0000000..0e58200 --- /dev/null +++ b/src/chisq.hpp @@ -0,0 +1,206 @@ +/**
+ \file chisq.hpp
+ \brief chi-square statistic
+ \author Junhua Gu
+ */
+
+#ifndef CHI_SQ_HPP
+#define CHI_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
+{
+ static const int display_interval=10;
+ /**
+ \brief chi-square statistic
+ \tparam Ty the return type of model
+ \tparam Tx the type of the self-var
+ \tparam Tp the type of model parameter
+ \tparam Ts the type of the statistic
+ \tparam Tstr the type of the string used
+ */
+ template<typename Ty,typename Tx,typename Tp,typename Ts,typename Tstr>
+ class chisq
+ :public statistic<Ty,Tx,Tp,Ts,Tstr>
+ {
+ };
+ template<>
+ class chisq<double,double,std::vector<double>,double,std::string>
+ :public statistic<double,double,std::vector<double> ,double,std::string>
+ {
+ public:
+ typedef double Ty;
+ typedef double Tx;
+ typedef std::vector<double> Tp;
+ typedef double Ts;
+ typedef std::string Tstr;
+ private:
+ bool verb;
+ bool limit_bound;
+ int n;
+
+ statistic<Ty,Tx,Tp,Ts,Tstr>* do_clone()const
+ {
+ // return const_cast<statistic<Ty,Tx,Tp>*>(this);
+ return new chisq<Ty,Tx,Tp,Ts,Tstr>(*this);
+ }
+
+ const char* do_get_type_name()const
+ {
+ return "chi^2 statistics (specialized for double)";
+ }
+ public:
+ void verbose(bool v)
+ {
+ verb=v;
+ }
+
+ void set_limit()
+ {
+ limit_bound=true;
+ }
+
+ void clear_limit()
+ {
+ limit_bound=false;
+ }
+ public:
+ chisq()
+ :verb(true),limit_bound(false)
+ {}
+
+ Ty do_eval(const Tp& p)
+ {
+ if(limit_bound)
+ {
+ Tp p1=this->get_fitter().get_model().reform_param(p);
+ for(size_t i=0;i<p1.size();++i)
+ {
+ if(p1[i]>this->get_fitter().get_param_info(i).get_upper_limit()||
+ p1[i]<this->get_fitter().get_param_info(i).get_lower_limit())
+ {
+ return 1e99;
+ }
+ }
+ }
+ Ty result(0);
+ std::vector<float> vx;
+ std::vector<float> vy;
+ std::vector<float> vye1;
+ std::vector<float> vye2;
+ std::vector<float> my;
+ float xmin=1e99,xmax=-1e99,ymin=1e99,ymax=-1e99;
+ if(verb)
+ {
+ n++;
+ if(n%display_interval==0)
+ {
+ vx.resize(this->get_data_set().size());
+ vy.resize(this->get_data_set().size());
+ vye1.resize(this->get_data_set().size());
+ vye2.resize(this->get_data_set().size());
+ my.resize(this->get_data_set().size());
+ }
+ }
+
+ for(int i=(this->get_data_set()).size()-1;i>=0;--i)
+ {
+
+#ifdef HAVE_X_ERROR
+ Tx x1=this->get_data_set().get_data(i).get_x()-this->get_data_set().get_data(i).get_x_lower_err();
+ Tx x2=this->get_data_set().get_data(i).get_x()+this->get_data_set().get_data(i).get_x_upper_err();
+ Tx x=this->get_data_set().get_data(i).get_x();
+ Ty errx1=(this->eval_model(x1,p)-this->eval_model(x,p));
+ Ty errx2=(this->eval_model(x2,p)-this->eval_model(x,p));
+ //Ty errx=0;
+#else
+ Ty errx1=0;
+ Ty errx2=0;
+#endif
+
+ Ty y_model=this->eval_model(this->get_data_set().get_data(i).get_x(),p);
+ Ty y_obs=this->get_data_set().get_data(i).get_y();
+ Ty y_err;
+
+ Ty errx=0;
+ if(errx1<errx2)
+ {
+ if(y_obs<y_model)
+ {
+ errx=errx1>0?errx1:-errx1;
+ }
+ else
+ {
+ errx=errx2>0?errx2:-errx2;
+ }
+ }
+ else
+ {
+ if(y_obs<y_model)
+ {
+ errx=errx2>0?errx2:-errx2;
+ }
+ else
+ {
+ errx=errx1>0?errx1:-errx1;
+ }
+ }
+
+ if(y_model>y_obs)
+ {
+ y_err=this->get_data_set().get_data(i).get_y_upper_err();
+ }
+ else
+ {
+ y_err=this->get_data_set().get_data(i).get_y_lower_err();
+ }
+
+ Ty chi=(y_obs-y_model)/std::sqrt(y_err*y_err+errx*errx);
+
+ result+=chi*chi;
+
+ if(verb&&n%display_interval==0)
+ {
+ vx.at(i)=this->get_data_set().get_data(i).get_x();
+ vy.at(i)=this->get_data_set().get_data(i).get_y();
+ vye1.at(i)=std::abs(this->get_data_set().get_data(i).get_y_lower_err());
+ vye2.at(i)=std::abs(this->get_data_set().get_data(i).get_y_upper_err());
+ my.at(i)=y_model;
+
+ xmin=std::min(vx.at(i),xmin);
+ ymin=std::min(vy.at(i),ymin-vye1[i]);
+ xmax=std::max(vx.at(i),xmax);
+ ymax=std::max(vy.at(i),ymax+vye2[i]);
+ }
+
+ }
+ if(verb)
+ {
+ if(n%display_interval==0)
+ {
+ cerr<<result<<"\t";
+ for(size_t i=0;i<get_size(p);++i)
+ {
+ cerr<<get_element(p,i)<<",";
+ }
+ cerr<<endl;
+ //cerr<<x1<<"\t"<<x2<<endl;
+ }
+ }
+
+ return result;
+ }
+ };
+}
+
+#endif /* CHI_SQ_HPP */
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