/*************************************************************************** * ctulimit - Upper limit calculation tool * * ----------------------------------------------------------------------- * * copyright (C) 2015 by Michael Mayer * * ----------------------------------------------------------------------- * * * * This program is free software: you can redistribute it and/or modify * * it under the terms of the GNU General Public License as published by * * the Free Software Foundation, either version 3 of the License, or * * (at your option) any later version. * * * * This program is distributed in the hope that it will be useful, * * but WITHOUT ANY WARRANTY; without even the implied warranty of * * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * * GNU General Public License for more details. * * * * You should have received a copy of the GNU General Public License * * along with this program. If not, see . * * * ***************************************************************************/ /** * @file ctulimit.hpp * @brief Upper limit calculation tool interface implementation * @author Michael Mayer */ /* __ Includes ___________________________________________________________ */ #ifdef HAVE_CONFIG_H #include #endif #include #include "ctulimit.hpp" #include "GTools.hpp" #include "GOptimizer.hpp" /* __ Method name definitions ____________________________________________ */ #define G_GET_PARAMETERS "ctulimit::get_parameters()" #define G_GET_MODEL_PARAMETER "ctulimit::get_model_parameter()" #define G_UL_BISECTION "ctulimit::ul_bisection(double&, double&)" #define G_EVALUATE "ctulimit::evaluate(double&)" /* __ Debug definitions __________________________________________________ */ /* __ Coding definitions _________________________________________________ */ /*========================================================================== = = = Constructors/destructors = = = ==========================================================================*/ /***********************************************************************//** * @brief Void constructor ***************************************************************************/ ctulimit::ctulimit(void) : ctool(CTULIMIT_NAME, CTULIMIT_VERSION) { // Initialise members init_members(); // Return return; } /***********************************************************************//** * @brief Observations constructor * * param[in] obs Observation container. * * This method creates an instance of the class by copying an existing * observations container. ***************************************************************************/ ctulimit::ctulimit(const GObservations& obs) : ctool(CTULIMIT_NAME, CTULIMIT_VERSION) { // Initialise members init_members(); // Set observations m_obs = obs; // Return return; } /***********************************************************************//** * @brief Command line constructor * * @param[in] argc Number of arguments in command line. * @param[in] argv Array of command line arguments. ***************************************************************************/ ctulimit::ctulimit(int argc, char *argv[]) : ctool(CTULIMIT_NAME, CTULIMIT_VERSION, argc, argv) { // Initialise members init_members(); // Return return; } /***********************************************************************//** * @brief Copy constructor * * @param[in] app Application. ***************************************************************************/ ctulimit::ctulimit(const ctulimit& app) : ctool(app) { // Initialise members init_members(); // Copy members copy_members(app); // Return return; } /***********************************************************************//** * @brief Destructor ***************************************************************************/ ctulimit::~ctulimit(void) { // Free members free_members(); // Return return; } /*========================================================================== = = = Operators = = = ==========================================================================*/ /***********************************************************************//** * @brief Assignment operator * * @param[in] app Application. * @return Application. ***************************************************************************/ ctulimit& ctulimit::operator=(const ctulimit& app) { // Execute only if object is not identical if (this != &app) { // Copy base class members this->ctool::operator=(app); // Free members free_members(); // Initialise members init_members(); // Copy members copy_members(app); } // endif: object was not identical // Return this object return *this; } /*========================================================================== = = = Public methods = = = ==========================================================================*/ /***********************************************************************//** * @brief Clear instance ***************************************************************************/ void ctulimit::clear(void) { // Free members free_members(); this->ctool::free_members(); this->GApplication::free_members(); // Initialise members this->GApplication::init_members(); this->ctool::init_members(); init_members(); // Return return; } /***********************************************************************//** * @brief Computes the upper limit * * This method calculates the upper limit depending on the given algorithm ***************************************************************************/ void ctulimit::run(void) { // If we're in debug mode then all output is also dumped on the screen if (logDebug()) { log.cout(true); } // Get task parameters get_parameters(); // Write parameters into logger if (logTerse()) { log_parameters(); log << std::endl; } // Write observation(s) into logger if (logTerse()) { log << std::endl; if (m_obs.size() > 1) { log.header1("Observations"); } else { log.header1("Observation"); } log << m_obs << std::endl; } // Save original models GModels models_orig = m_obs.models(); // Initialise best fit optimizer GOptimizerLM best_opt; // Save original log-likelihood. If the value is zero it has never been // computed hence we compute it now. m_best_logL = m_obs.logL(); if (m_best_logL == 0.0) { // Write header if (logTerse()) { log << std::endl; log.header1("Compute best-fit likelihood"); } // Optimize and save best log-likelihood m_obs.optimize(m_opt); m_obs.errors(m_opt); m_best_logL = m_obs.logL(); // Store optimizer for later recovery best_opt = m_opt; // Write optimised model into logger if (logTerse()) { log << m_opt << std::endl; log << gammalib::parformat("Maximum log likelihood"); log << gammalib::str(m_best_logL,3) << std::endl; log << m_obs.models() << std::endl; } } // endif: likelihood was zero // Extract current value double value = m_model_par->factor_value(); // Compute parameter bracketing double parmin = std::max(m_model_par->factor_min(), value - m_sigma_min * m_model_par->factor_error()); double parmax = std::min(m_model_par->factor_max(), value + m_sigma_max * m_model_par->factor_error()); // Write header if (logTerse()) { log << std::endl; log.header1("Compute upper limit"); log << gammalib::parformat("Model name"); log << m_skymodel->name() << std::endl; log << gammalib::parformat("Parameter name"); log << m_model_par->name() << std::endl; log << gammalib::parformat("Confidence level"); log << m_confidence*100.0 << "%" << std::endl; log << gammalib::parformat("Log-likelihood difference"); log << m_dlogL << std::endl; log << gammalib::parformat("Initial parameter range"); log << "["; log << parmin; log << ", "; log << parmax; log << "]" << std::endl; } // Compute upper limit ulimit_bisection(parmin, parmax); // Write final parameter range if (logTerse()) { log << gammalib::parformat("Final parameter"); log << m_model_par->value() << std::endl; } // Get reference energy for differential upper limit GEnergy eref = GEnergy(m_eref, "TeV"); // Create energy range for flux limits GEnergy emin = GEnergy(m_emin, "TeV"); GEnergy emax = GEnergy(m_emax, "TeV"); // Compute upper limit intensity and fluxes m_diff_ulimit = m_skymodel->spectral()->eval(eref, GTime()); m_flux_ulimit = m_skymodel->spectral()->flux(emin, emax); m_eflux_ulimit = m_skymodel->spectral()->eflux(emin, emax); // Write results to logfile if (logTerse()) { log << std::endl; log.header1("Upper limit results"); log << gammalib::parformat("Differential flux limit"); log << m_diff_ulimit; log << " ph/cm2/s/MeV at "; log << m_eref << " TeV"; log << std::endl; log << gammalib::parformat("Integral flux limit"); log << m_flux_ulimit; log << " ph/cm2/s within ["; log << m_emin << "-" << m_emax; log << "] TeV"; log << std::endl; log << gammalib::parformat("Energy flux limit"); log << m_eflux_ulimit; log << " erg/cm2/s within ["; log << m_emin << "-" << m_emax; log << "] TeV"; log << std::endl; } // Recover original models m_obs.models(models_orig); // Recover optimizer m_opt = best_opt; // Return return; } /***********************************************************************//** * @brief Save maps * * This method saves the upper limit to an ascii file. * * @todo No yet implemented as we have no clear use case yet for saving * the result. ***************************************************************************/ void ctulimit::save(void) { // Write header if (logTerse()) { log << std::endl; log.header1("Save upper limit"); } /* // Get output filename m_outfile = (*this)["outfile"].filename(); // Create CSV table with 3 columns GCsv table(1, 3); table.real(0, 0, m_diff_ulimit); table.real(0, 1, m_flux_ulimit); table.real(0, 2, m_eflux_ulimit); // Save CSV table table.save(m_outfile, " ", clobber()); */ // Return return; } /*========================================================================== = = = Private methods = = = ==========================================================================*/ /***********************************************************************//** * @brief Initialise class members ***************************************************************************/ void ctulimit::init_members(void) { // Initialise user parameters m_srcname.clear(); m_confidence = 0.95; m_sigma_min = 0.0; m_sigma_max = 0.0; m_eref = 0.0; m_emin = 0.0; m_emax = 0.0; m_tol = 1.0e-6; m_max_iter = 50; // Initialise protected members m_obs.clear(); m_opt.clear(); m_dlogL = 0.0; m_skymodel = NULL; m_model_par = NULL; m_best_logL = 0.0; m_flux_ulimit = 0.0; m_diff_ulimit = 0.0; m_eflux_ulimit = 0.0; // Set optimizer parameters m_opt.max_iter(m_max_iter); m_opt.max_stalls(10); // Return return; } /***********************************************************************//** * @brief Copy class members * * @param[in] app Application. ***************************************************************************/ void ctulimit::copy_members(const ctulimit& app) { // Copy user parameters m_srcname = app.m_srcname; m_confidence = app.m_confidence; m_sigma_min = app.m_sigma_min; m_sigma_max = app.m_sigma_max; m_eref = app.m_eref; m_emin = app.m_emin; m_emax = app.m_emax; m_tol = app.m_tol; m_max_iter = app.m_max_iter; // Copy protected members m_obs = app.m_obs; m_dlogL = app.m_dlogL; m_best_logL = app.m_best_logL; m_diff_ulimit = app.m_diff_ulimit; m_flux_ulimit = app.m_flux_ulimit; m_eflux_ulimit = app.m_eflux_ulimit; m_opt = app.m_opt; // Extract model parameter get_model_parameter(); // Return return; } /***********************************************************************//** * @brief Delete class members ***************************************************************************/ void ctulimit::free_members(void) { // Return return; } /***********************************************************************//** * @brief Get application parameters * * @exception GException::invalid_value * Test source not found. * * Get all task parameters from parameter file or (if required) by querying * the user. ***************************************************************************/ void ctulimit::get_parameters(void) { // If there are no observations in container then load them via user // parameters if (m_obs.size() == 0) { // Throw exception if no input observation file is given require_inobs(G_GET_PARAMETERS); // Build observation container m_obs = get_observations(); } // endif: there was no observation in the container // If there is are no models associated with the observations then // load now the model definition if (m_obs.models().size() == 0) { // Get models XML filename std::string filename = (*this)["inmodel"].filename(); // Setup models for optimizing. m_obs.models(GModels(filename)); } // endif: no models were associated with observations // Get name of test source and check container for this name m_srcname = (*this)["srcname"].string(); if (!m_obs.models().contains(m_srcname)) { std::string msg = "Source \""+m_srcname+"\" not found in model " "container. Please add a source with that name " "or check for possible typos."; throw GException::invalid_value(G_GET_PARAMETERS, msg); } // Get relevant model and parameter for upper limit computation get_model_parameter(); // Get confidence level and transform into log-likelihood difference m_confidence = (*this)["confidence"].real(); double sigma = gammalib::erfinv(m_confidence) * gammalib::sqrt_two; m_dlogL = (sigma*sigma) / 2.0; // Read starting boundaries for bisection m_sigma_min = (*this)["sigma_min"].real(); m_sigma_max = (*this)["sigma_max"].real(); // Read energy values m_eref = (*this)["eref"].real(); m_emin = (*this)["emin"].real(); m_emax = (*this)["emax"].real(); // Read precision m_tol = (*this)["tol"].real(); m_max_iter = (*this)["max_iter"].integer(); // Return return; } /***********************************************************************//** * @brief Get application parameters * * @exception GException::invalid_value * Did not find a valid model parameter * * Extracts a pointer to the sky model (m_skymodel) and a pointer to the * relevant model parameter (m_model_par) from the model container. ***************************************************************************/ void ctulimit::get_model_parameter(void) { // Continue only if source model exists if (m_obs.models().contains(m_srcname)) { // Get relevant model and parameter for upper limit computation. GModels& models = const_cast(m_obs.models()); m_skymodel = dynamic_cast(models[m_srcname]); if (m_skymodel == NULL) { std::string msg = "Source \""+m_srcname+"\" is not a sky model. " "Please specify the name of a sky model for " "upper limit computation."; throw GException::invalid_value(G_GET_MODEL_PARAMETER, msg); } if (m_skymodel->spectral()->type() == "NodeFunction") { std::string msg = "\"NodeFunction\" cannot be used as spectral " "model for an upper limit computation. " "Please specify another spectral model."; throw GException::invalid_value(G_GET_MODEL_PARAMETER, msg); } if (m_skymodel->spectral()->has_par("Normalization")) { m_model_par = &(m_skymodel->spectral()->operator[]("Normalization")); } else if (m_skymodel->spectral()->has_par("Prefactor")) { m_model_par = &(m_skymodel->spectral()->operator[]("Prefactor")); } else if (m_skymodel->spectral()->has_par("Integral")) { m_model_par = &(m_skymodel->spectral()->operator[]("Integral")); } else if (m_skymodel->spectral()->has_par("Value")) { m_model_par = &(m_skymodel->spectral()->operator[]("Value")); } else { std::string msg = "Require spectral parameter \"Normalization\", " "\"Prefactor\", \"Integral\" or \"Value\" for " "upper limit computation. The specified source " "\""+m_srcname+"\" does not have such a parameter."; throw GException::invalid_value(G_GET_MODEL_PARAMETER, msg); } } // endif: source model existed // Return return; } /***********************************************************************//** * @brief Performs upper limit computation by using a bisection method * * @param[in] min Minimum parameter value * @param[in] max Maximum parameter value * * This method calculates the upper limit using a bisection method. ***************************************************************************/ void ctulimit::ulimit_bisection(const double& min, const double& max) { // Copy values to working values double wrk_min = min; double wrk_max = max; // Initialise iteration counter int iter = 0; // Loop until breaking condition is reached while (true) { // Log information if (logExplicit()) { log << gammalib::parformat("Iteration "+gammalib::str(iter)); log << "["; log << wrk_min; log << ", "; log << wrk_max; log << "]" << std::endl; } // Throw exception if maximum iterations are reached if (iter > m_max_iter) { std::string msg = "The maximum number of "+gammalib::str(m_max_iter)+ " has been reached. You may consider to increase" " the \"max_iter\" parameter and re-run ctulimit."; throw GException::invalid_value(G_UL_BISECTION, msg); } // Compute center of boundary double mid = (wrk_min + wrk_max) / 2.0; // Calculate function value double eval_mid = evaluate(mid); // Check for convergence inside tolerance if (std::abs(eval_mid) < m_tol) { break; } // Change boundaries for further iteration if (eval_mid > 0.0) { wrk_max = mid; } else if (eval_mid < 0.0) { wrk_min = mid; } // Increment counter iter++; } // endwhile // Return return; } /***********************************************************************//** * @brief Evaluates the log-likelihood * * @param[in] value Parameter factor value * @return Log-likelihood value * * This method evaluates the log-likelihood as a function of the parameter * of interest. ***************************************************************************/ double ctulimit::evaluate(const double& value) { // Initialise log-likelihood value double logL = 0.0; // Check if given parameter is within boundaries if (value > m_model_par->factor_min() && value < m_model_par->factor_max()) { // Change parameter factor m_model_par->factor_value(value); // Fix parameter m_model_par->fix(); // Re-optimize m_obs.optimize(m_opt); // Retrieve likelihood logL = m_obs.logL(); // Free parameter m_model_par->free(); } // endif: value was inside allowed range // ... otherwise signal that the parameter went outside the boundaries else { std::string msg = "Value of parameter \""+m_model_par->name()+"\" " "outside of validity range requested. To omit " "this error please enlarge the parameter range " "in the model XML file."; throw GException::invalid_value(G_EVALUATE, msg); } // Compute function value double logL_difference = logL - m_best_logL - m_dlogL; // Return return logL_difference; }