binned_extended_logLL_fit.inl File Reference

#include <iostream>
#include <assert.h>
#include <time.h>
#include <chrono>
#include <random>
#include <algorithm>
#include <tclap/CmdLine.h>
#include <hydra/device/System.h>
#include <hydra/Function.h>
#include <hydra/Lambda.h>
#include <hydra/Random.h>
#include <hydra/LogLikelihoodFCN.h>
#include <hydra/Parameter.h>
#include <hydra/UserParameters.h>
#include <hydra/Pdf.h>
#include <hydra/AddPdf.h>
#include <hydra/DenseHistogram.h>
#include <hydra/functions/Gaussian.h>
#include <hydra/functions/Exponential.h>
#include <hydra/RandomFill.h>
#include "Minuit2/FunctionMinimum.h"
#include "Minuit2/MnUserParameterState.h"
#include "Minuit2/MnPrint.h"
#include "Minuit2/MnMigrad.h"
#include "Minuit2/MnMinimize.h"

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Macros
#define	BINNED_EXTENDED_LOGLL_FIT_INL_

Functions
cmd	add (EArg)
	catch (TCLAP::ArgException &e)
	declarg (_X, double) int main(int argv
TCLAP::ValueArg< size_t >	EArg ("n", "number-of-events","Number of events", true, 10e6, "size_t")
Hist_Data	Fill (data_d.begin(), data_d.end())
std::cout<< std::endl<< "Generated data:"<< std::endl;for(size_t i=0;i< 10;i++) std::cout<< "["<< i<< "] :"<< data_d[i]<< std::endl;hydra::DenseHistogram< double, 1, hydra::device::sys_t >	Hist_Data (100, min, max)
MnMigrad	migrad_d (fcn, fcn.GetParameters().GetMnState(), strategy)
cmd	parse (argv, argc)
model	SetExtended (1)
MnStrategy	strategy (2)

Variables
char **	argc
std::cout<< fcn.GetParameters().GetMnState()<< std::endl;auto start_d=std::chrono::high_resolution_clock::now();FunctionMinimum minimum_d=FunctionMinimum(migrad_d(std::numeric_limits< unsigned int >::max(), 1));auto end_d=std::chrono::high_resolution_clock::now();std::chrono::duration< double, std::milli >	elapsed_d = end_d - start_d
auto	Exp_PDF
auto	fcn = hydra::make_loglikehood_fcn( model, Hist_Data)
auto	Gauss1_PDF
auto	Gauss2_PDF
double	max = 10.0
hydra::Parameter	mean1_p = hydra::Parameter::Create().Name("Mean_1").Value( 2.5) .Error(0.0001).Limits(0.0, 10.0)
hydra::Parameter	mean2_p = hydra::Parameter::Create().Name("Mean_2").Value(5.0) .Error(0.0001).Limits(0.0, 10.0)
double	min = 0.0
auto	model = hydra::add_pdfs( {N_Gauss_1_p, N_Gauss_2_p, N_Exp_p }, Gauss1_PDF, Gauss2_PDF, Exp_PDF)
hydra::Parameter	N_Exp_p ("N_Exp", nentries, sqrt(nentries), nentries-nentries/2, nentries+nentries/2)
hydra::Parameter	N_Gauss_1_p ("N_Gauss1", nentries, sqrt(nentries), nentries-nentries/2, nentries+nentries/2)
hydra::Parameter	N_Gauss_2_p ("N_Gauss2", nentries, sqrt(nentries), nentries-nentries/2, nentries+nentries/2)
	nentries = EArg.getValue()
hydra::Parameter	sigma1_p = hydra::Parameter::Create().Name("Sigma_1").Value(0.5).Error(0.0001).Limits(0.01, 1.5)
hydra::Parameter	sigma2_p = hydra::Parameter::Create().Name("Sigma_2").Value(0.5).Error(0.0001).Limits(0.01, 1.5)
hydra::Parameter	tau_p = hydra::Parameter::Create().Name("Tau").Value(1.0).Error(0.0001).Limits(-2.0, 2.0)
	try

Macro Definition Documentation

BINNED_EXTENDED_LOGLL_FIT_INL_

#define BINNED_EXTENDED_LOGLL_FIT_INL_

Function Documentation

add()

cmd add

(

EArg

)

catch()

catch

(

TCLAP::ArgException &

e

)

declarg()

declarg	(	_X	,
		double
	)

Examples:

binned_extended_logLL_fit.inl.

EArg()

TCLAP::ValueArg<size_t> EArg	(	"n"	,
		"number-of-events"	,
		"Number of events"	,
		true	,
		10e6	,
		"size_t"
	)

Examples:

binned_extended_logLL_fit.inl.

Fill()

Hist_Data Fill	(	data_d.	begin(),
		data_d.	end()
	)

Hist_Data()

std::cout<< std::endl<< "Generated data:"<< std::endl; for(size_t i=0; i<10; i++) std::cout << "[" << i << "] :" << data_d[i] << std::endl; hydra::DenseHistogram<double,1, hydra::device::sys_t> Hist_Data	(	100	,
		min	,
		max
	)

Examples:

binned_extended_logLL_fit.inl.

migrad_d()

MnMigrad migrad_d	(	fcn	,
		fcn.	GetParameters).GetMnState(,
		strategy
	)

Examples:

basic_fit_range_semantics.inl, binned_extended_logLL_fit.inl, breit_wigner_plus_polynomial.inl, crystal_ball_plus_exponential.inl, dalitz_plot.C, dalitz_plot.inl, double_gaussian_plus_exponential.inl, extended_logLL_fit.inl, fit_convoluted_pdfs.inl, fit_johnson.C, fractional_logLL_fit.inl, gaussian_plus_argus.inl, multidimensional_fit.inl, and splot.inl.

parse()

cmd parse	(	argv	,
		argc
	)

SetExtended()

model SetExtended

(

1

)

strategy()

MnStrategy strategy

(

2

)

Examples:

basic_fit.inl, basic_fit_range_semantics.inl, binned_extended_logLL_fit.inl, breit_wigner_plus_polynomial.inl, crystal_ball_plus_exponential.inl, dalitz_plot.C, dalitz_plot.inl, double_gaussian_plus_exponential.inl, extended_logLL_fit.inl, fit_convoluted_pdfs.inl, fit_gaussian.C, fit_johnson.C, fractional_logLL_fit.inl, gaussian_plus_argus.inl, multidimensional_fit.inl, pseudo_experiment.inl, simultaneous_fit.inl, and splot.inl.

Variable Documentation

argc

char** argc

Initial value:

{
    size_t nentries = 0

Examples:

binned_extended_logLL_fit.inl.

elapsed_d

std::cout<<fcn.GetParameters().GetMnState()<<std::endl; auto start_d = std::chrono::high_resolution_clock::now(); FunctionMinimum minimum_d = FunctionMinimum(migrad_d(std::numeric_limits<unsigned int>::max(), 1)); auto end_d = std::chrono::high_resolution_clock::now(); std::chrono::duration<double, std::milli> elapsed_d = end_d - start_d

Examples:

binned_extended_logLL_fit.inl.

Exp_PDF

auto Exp_PDF

Initial value:

= hydra::make_pdf( hydra::Exponential<_X>(tau_p),
            hydra::AnalyticalIntegral<hydra::Exponential<_X>>(min, max))

Examples:

binned_extended_logLL_fit.inl, and splot.inl.

fcn

auto fcn = hydra::make_loglikehood_fcn( model, Hist_Data)

Examples:

basic_fit_range_semantics.inl, binned_extended_logLL_fit.inl, breit_wigner_plus_polynomial.inl, crystal_ball_plus_exponential.inl, dalitz_plot.C, dalitz_plot.inl, double_gaussian_plus_exponential.inl, extended_logLL_fit.inl, fit_convoluted_pdfs.inl, fit_johnson.C, fractional_logLL_fit.inl, gaussian_plus_argus.inl, multidimensional_fit.inl, pseudo_experiment.inl, and splot.inl.

Gauss1_PDF

auto Gauss1_PDF

Initial value:

= hydra::make_pdf( hydra::Gaussian<_X>(mean1_p, sigma1_p),
            hydra::AnalyticalIntegral<hydra::Gaussian<_X>>(min, max))

Examples:

binned_extended_logLL_fit.inl.

Gauss2_PDF

auto Gauss2_PDF

Initial value:

= hydra::make_pdf(hydra::Gaussian<_X>(mean2_p, sigma2_p),
            hydra::AnalyticalIntegral<hydra::Gaussian<_X>>(min, max))

Examples:

binned_extended_logLL_fit.inl.

max

double max = 10.0

Examples:

binned_extended_logLL_fit.inl.

mean1_p

hydra::Parameter mean1_p = hydra::Parameter::Create().Name("Mean_1").Value( 2.5) .Error(0.0001).Limits(0.0, 10.0)

Examples:

binned_extended_logLL_fit.inl.

mean2_p

hydra::Parameter mean2_p = hydra::Parameter::Create().Name("Mean_2").Value(5.0) .Error(0.0001).Limits(0.0, 10.0)

Examples:

binned_extended_logLL_fit.inl.

min

double min = 0.0

Examples:

binned_extended_logLL_fit.inl.

model

auto model = hydra::add_pdfs( {N_Gauss_1_p, N_Gauss_2_p, N_Exp_p }, Gauss1_PDF, Gauss2_PDF, Exp_PDF)

Examples:

binned_extended_logLL_fit.inl.

N_Exp_p

hydra::Parameter N_Exp_p("N_Exp",nentries, sqrt(nentries), nentries-nentries/2, nentries+nentries/2)

Examples:

binned_extended_logLL_fit.inl, and splot.inl.

N_Gauss_1_p

hydra::Parameter N_Gauss_1_p("N_Gauss1",nentries, sqrt(nentries), nentries-nentries/2, nentries+nentries/2)

Examples:

binned_extended_logLL_fit.inl.

N_Gauss_2_p

hydra::Parameter N_Gauss_2_p("N_Gauss2",nentries, sqrt(nentries), nentries-nentries/2, nentries+nentries/2)

Examples:

binned_extended_logLL_fit.inl.

nentries

nentries = EArg.getValue()

Examples:

binned_extended_logLL_fit.inl.

sigma1_p

hydra::Parameter sigma1_p = hydra::Parameter::Create().Name("Sigma_1").Value(0.5).Error(0.0001).Limits(0.01, 1.5)

Examples:

binned_extended_logLL_fit.inl.

sigma2_p

hydra::Parameter sigma2_p = hydra::Parameter::Create().Name("Sigma_2").Value(0.5).Error(0.0001).Limits(0.01, 1.5)

Examples:

binned_extended_logLL_fit.inl.

tau_p

hydra::Parameter tau_p = hydra::Parameter::Create().Name("Tau").Value(1.0).Error(0.0001).Limits(-2.0, 2.0)

Examples:

binned_extended_logLL_fit.inl, and splot.inl.

try

try

Initial value:

{

        TCLAP::CmdLine cmd("Command line arguments for ", '=')