/*************************************************************************** * ctlike - Maximum likelihood fitting tool * * ----------------------------------------------------------------------- * * copyright (C) 2010-2014 by Juergen Knoedlseder * * ----------------------------------------------------------------------- * * * * 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 ctlike.cpp * @brief Maximum likelihood fitting tool implementation * @author Juergen Knoedlseder */ /* __ Includes ___________________________________________________________ */ #ifdef HAVE_CONFIG_H #include #endif #include #include "ctlike.hpp" #include "GTools.hpp" /* __ Method name definitions ____________________________________________ */ #define G_GET_PARAMETERS "ctlike::get_parameters()" /* __ Debug definitions __________________________________________________ */ /* __ Coding definitions _________________________________________________ */ /*========================================================================== = = = Constructors/destructors = = = ==========================================================================*/ /***********************************************************************//** * @brief Void constructor ***************************************************************************/ ctlike::ctlike(void) : ctool(CTLIKE_NAME, CTLIKE_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. ***************************************************************************/ ctlike::ctlike(const GObservations& obs) : ctool(CTLIKE_NAME, CTLIKE_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. ***************************************************************************/ ctlike::ctlike(int argc, char *argv[]) : ctool(CTLIKE_NAME, CTLIKE_VERSION, argc, argv) { // Initialise members init_members(); // Return return; } /***********************************************************************//** * @brief Copy constructor * * @param[in] app Application. ***************************************************************************/ ctlike::ctlike(const ctlike& app) : ctool(app) { // Initialise members init_members(); // Copy members copy_members(app); // Return return; } /***********************************************************************//** * @brief Destructor ***************************************************************************/ ctlike::~ctlike(void) { // Free members free_members(); // Return return; } /*========================================================================== = = = Operators = = = ==========================================================================*/ /***********************************************************************//** * @brief Assignment operator * * @param[in] app Application. * @return Application. ***************************************************************************/ ctlike& ctlike::operator=(const ctlike& 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 ctlike::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 Run maximum likelihood analysis * * The following analysis steps are performed: * 1. Read the parameters (and write them into logger) * 2. Load observation * 3. Setup models for optimizing * 4. Optimize model (and write result into logger) ***************************************************************************/ void ctlike::run(void) { // Switch screen logging on in debug mode if (logDebug()) { log.cout(true); } // Get parameters get_parameters(); // Write parameters into logger if (logTerse()) { log_parameters(); log << std::endl; } // Set energy dispersion flag for all CTA observations and save old // values in save_edisp vector std::vector save_edisp; save_edisp.assign(m_obs.size(), false); for (int i = 0; i < m_obs.size(); ++i) { GCTAObservation* obs = dynamic_cast(m_obs[i]); if (obs != NULL) { save_edisp[i] = obs->response()->apply_edisp(); obs->response()->apply_edisp(m_apply_edisp); } } // 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; } // Optimize model parameters using LM optimizer optimize_lm(); // Store Npred double npred = m_obs.npred(); // Store models for which TS should be computed std::vector ts_srcs; GModels models_orig = m_obs.models(); for (int i = 0; i < models_orig.size(); ++i) { GModel* model = models_orig[i]; if (model->tscalc()) { ts_srcs.push_back(model->name()); } } // Compute TS values if requested if (ts_srcs.size() > 0) { // Store original maximum likelihood and models double logL_src = m_logL; GModels models = m_obs.models(); // Loop over stored models, remove source and refit for (int i = 0; i < ts_srcs.size(); ++i) { models.remove(ts_srcs[i]); m_obs.models(models); double logL_nosrc = reoptimize_lm(); double ts = 2.0 * (logL_src-logL_nosrc); models_orig[ts_srcs[i]]->ts(ts); models = models_orig; } // Restore best fit values m_obs.models(models_orig); } // Compute number of observed events in all observations double num_events = 0.0; for (int i = 0; i < m_obs.size(); ++i) { num_events += m_obs[i]->events()->number(); } // Write results into logger if (logTerse()) { log << std::endl; log.header1("Maximum likelihood optimization results"); log << *m_opt << std::endl; log << gammalib::parformat("Maximum log likelihood"); log << gammalib::str(m_logL,3) << std::endl; log << gammalib::parformat("Observed events (Nobs)"); log << gammalib::str(num_events, 3) << std::endl; log << gammalib::parformat("Predicted events (Npred)"); log << gammalib::str(npred, 3); log << " (Nobs - Npred = "; log << gammalib::str(num_events-npred); log << ")" << std::endl; log << m_obs.models() << std::endl; } // Restore energy dispersion flag for all CTA observations for (int i = 0; i < m_obs.size(); ++i) { GCTAObservation* obs = dynamic_cast(m_obs[i]); if (obs != NULL) { obs->response()->apply_edisp(save_edisp[i]); } } // Return return; } /***********************************************************************//** * @brief Save results * * This method saves the fit results in a XML file. ***************************************************************************/ void ctlike::save(void) { // Write header if (logTerse()) { log << std::endl; log.header1("Save results"); } // Get output filename m_outmdl = (*this)["outmdl"].filename(); // Write results out as XML model if (gammalib::toupper(m_outmdl) != "NONE") { m_obs.models().save(m_outmdl); } // Return return; } /***********************************************************************//** * @brief Get application parameters * * Get all required task parameters from the parameter file or (if specified) * by querying the user. Observation dependent parameters will only be read * if the observation container is actually empty. Observation dependent * parameters are: * "stat" (statistics to be used for observation), * "caldb" (calibration database), * "irf" (instrument response function), and * "infile" (input file name). * The model will only be loaded if no model components exist in the * observation container. * * This method handles both loading of FITS files and of handling XML * observation definition files. ***************************************************************************/ void ctlike::get_parameters(void) { // If there are no observations in container then add a single CTA // observation using the parameters from the parameter file if (m_obs.size() == 0) { // Allocate CTA observation GCTAObservation obs; // Get event file name std::string filename = (*this)["infile"].filename(); // Try first to open as FITS file try { // Load data obs.load(filename); // Get other task parameters std::string statistics = gammalib::toupper((*this)["stat"].string()); // Set statistics obs.statistics(statistics); // Set response set_obs_response(&obs); // Append observation to container m_obs.append(obs); } // ... otherwise try to open as XML file catch (GException::fits_open_error &e) { // Load observations from XML file m_obs.load(filename); // For all observations that have no response, set the response // from the task parameters set_response(m_obs); } // endcatch: file was an XML file } // 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)["srcmdl"].filename(); // Setup models for optimizing. m_obs.models(GModels(filename)); } // endif: no models were associated with observations // Get other parameters m_refit = (*this)["refit"].boolean(); m_apply_edisp = (*this)["edisp"].boolean(); // Optionally read ahead parameters so that they get correctly // dumped into the log file if (read_ahead()) { m_outmdl = (*this)["outmdl"].filename(); } // Return return; } /***********************************************************************//** * @brief Optimize model parameters using Levenberg-Marquardt method ***************************************************************************/ void ctlike::optimize_lm(void) { // Free any existing optimizer if (m_opt != NULL) delete m_opt; m_opt = NULL; // Allocate optimizer. The logger is only passed to the optimizer // constructor if optimizer logging is requested. GOptimizerLM* opt = (logTerse()) ? new GOptimizerLM(log) : new GOptimizerLM(); // Assign optimizer m_opt = opt; // Set optimizer parameters opt->max_iter(m_max_iter); opt->max_stalls(m_max_stall); // Write Header for optimization and indent for optimizer logging if (logTerse()) { log << std::endl; log.header1("Maximum likelihood optimisation"); log.indent(1); } // Perform LM optimization m_obs.optimize(*opt); // Optionally refit if (m_refit) { // Dump new header log.indent(0); if (logTerse()) { log << std::endl; log.header1("Maximum likelihood re-optimisation"); log.indent(1); } // Optimise again m_obs.optimize(*opt); } // Compute errors m_obs.errors(*opt); // Store maximum log likelihood value m_logL = -(opt->value()); // Remove indent log.indent(0); // Return return; } /***********************************************************************//** * @brief Re-optimize model parameters using Levenberg-Marquardt method * for TS computation ***************************************************************************/ double ctlike::reoptimize_lm(void) { // Allocate optimizer. The logger is only passed to the optimizer // constructor if optimizer logging is requested. GOptimizerLM* opt = (logTerse()) ? new GOptimizerLM(log) : new GOptimizerLM(); // Set optimizer parameters opt->max_iter(m_max_iter); opt->max_stalls(m_max_stall); // Write Header for optimization and indent for optimizer logging if (logTerse()) { log << std::endl; log.header1("Maximum likelihood re-optimisation"); log.indent(1); } // Perform LM optimization m_obs.optimize(*opt); // Optionally refit if (m_refit) { m_obs.optimize(*opt); } // Store maximum log likelihood value double logL = -(opt->value()); // Write optimization results log.indent(0); if (logTerse()) { log << std::endl; log.header1("Maximum likelihood re-optimization results"); log << *opt << std::endl; } // Return return (logL); } /*========================================================================== = = = Private methods = = = ==========================================================================*/ /***********************************************************************//** * @brief Initialise class members ***************************************************************************/ void ctlike::init_members(void) { // Initialise members m_outmdl.clear(); m_obs.clear(); m_refit = false; m_max_iter = 100; // Set maximum number of iterations m_max_stall = 10; // Set maximum number of stalls m_logL = 0.0; m_opt = NULL; m_apply_edisp = false; // Set logger properties log.date(true); // Return return; } /***********************************************************************//** * @brief Copy class members * * @param[in] app Application. ***************************************************************************/ void ctlike::copy_members(const ctlike& app) { // Copy attributes m_refit = app.m_refit; m_outmdl = app.m_outmdl; m_obs = app.m_obs; m_max_iter = app.m_max_iter; m_max_stall = app.m_max_stall; m_logL = app.m_logL; m_opt = app.m_opt->clone(); m_apply_edisp = app.m_apply_edisp; // Return return; } /***********************************************************************//** * @brief Delete class members ***************************************************************************/ void ctlike::free_members(void) { // Free members if (m_opt != NULL) delete m_opt; // Mark pointers as free m_opt = NULL; // Return return; }