/*************************************************************************** * ctlike - Maximum likelihood fitting tool * * ----------------------------------------------------------------------- * * copyright (C) 2010-2016 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 ____________________________________________ */ /* __ 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 ctlike tool * * Clears ctlike tool. ***************************************************************************/ void ctlike::clear(void) { // Free members free_members(); this->ctool::free_members(); // Clear base class (needed to conserve tool name and version) this->GApplication::clear(); // Initialise members this->ctool::init_members(); init_members(); // Write header into logger log_header(); // 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(); // Set energy dispersion flags of all CTA observations and save old // values in save_edisp vector std::vector save_edisp = set_edisp(m_obs, m_apply_edisp); // Write input observation container into logger log_observations(NORMAL, m_obs, "Input observation"); // 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.empty()) { // Store original maximum likelihood and models double logL_src = m_logL; GModels models = m_obs.models(); // Fix spatial parameters if requested if (m_fix_spat_for_ts) { // Loop over all models for (int i = 0; i < models.size(); ++i) { // Continue only if model is skymodel GModelSky* sky= dynamic_cast(models[i]); if (sky != NULL) { // Fix spatial parameters GModelSpatial* spatial = sky->spatial(); for (int j = 0; j < spatial->size(); j++) { (*spatial)[j].fix(); } // endfor: looped over spatial parameters } // endif: there was a sky model } // endfor: looped over models } // endif: spatial parameter should be fixed // 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) { double data = m_obs[i]->events()->number(); if (data >= 0.0) { num_events += data; } } // Write results into logger log_header1(NORMAL, "Maximum likelihood optimisation results"); log_string(NORMAL, m_opt->print(m_chatter)); log_value(NORMAL, "Maximum log likelihood", gammalib::str(m_logL,3)); log_value(NORMAL, "Observed events (Nobs)", gammalib::str(num_events,3)); log_value(NORMAL, "Predicted events (Npred)", gammalib::str(npred,3)+ " (Nobs - Npred = "+gammalib::str(num_events-npred)+")"); log_string(NORMAL, m_obs.models().print(m_chatter)); // Restore energy dispersion flags of all CTA observations restore_edisp(m_obs, save_edisp); // Return return; } /***********************************************************************//** * @brief Save results * * This method saves the fit results in a XML file. ***************************************************************************/ void ctlike::save(void) { // Write header log_header1(TERSE, "Save results"); // Get output filename m_outmodel = (*this)["outmodel"].filename(); // Save only if filename is valid if (is_valid_filename(m_outmodel)) { // Log filename log_value(NORMAL, "Model definition file", m_outmodel.url()); // Write results out as XML model m_obs.models().save(m_outmodel); } // ... otherwise signal that file was not saved else { log_value(NORMAL, "Model definition file", "NONE"); } // 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) { // Setup observations from "inobs" parameter setup_observations(m_obs); // If only single observation is used, read statistics parameter if (!m_use_xml) { // Get other task parameters std::string statistics = gammalib::toupper((*this)["stat"].string()); // Set statistics (*m_obs[0]).statistics(statistics); } // 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 other parameters m_refit = (*this)["refit"].boolean(); m_apply_edisp = (*this)["edisp"].boolean(); m_fix_spat_for_ts = (*this)["fix_spat_for_ts"].boolean(); m_chatter = static_cast((*this)["chatter"].integer()); // Optionally read ahead parameters so that they get correctly // dumped into the log file if (read_ahead()) { m_outmodel = (*this)["outmodel"].filename(); } // Set optimizer logger if (logNormal()) { static_cast(m_opt)->logger(&log); } else { static_cast(m_opt)->logger(NULL); } // Write parameters into logger log_parameters(TERSE); // Return return; } /***********************************************************************//** * @brief Optimise model parameters * * Optimise model parameters using a maximum likelihood fit. ***************************************************************************/ void ctlike::optimize_lm(void) { // Write header log_header1(TERSE, "Maximum likelihood optimisation"); log.indent(1); // Compute number of fitted parameters int nfit = 0; for (int i = 0; i < m_obs.models().size(); ++i) { const GModel* model = m_obs.models()[i]; for (int k = 0; k < model->size(); ++k) { if ((*model)[k].is_free()) { nfit++; } } } // Notify if all parameters are fixed if (nfit == 0) { log_string(TERSE, "WARNING: All model parameters are fixed!"); log_string(TERSE, " ctlike will proceed without fitting parameters."); log_string(TERSE, " All curvature matrix elements will be zero."); } // Perform LM optimization m_obs.optimize(*m_opt); // Optionally refit if (m_refit) { // Dump new header log.indent(0); log_header1(TERSE, "Maximum likelihood re-optimisation"); log.indent(1); // Optimise again m_obs.optimize(*m_opt); } // Optionally show curvature matrix log_header1(EXPLICIT, "Curvature matrix"); log.indent(1); log_string(EXPLICIT, (const_cast (m_obs.function()).curvature())->print()); // Compute errors m_obs.errors(*m_opt); // Store maximum log likelihood value m_logL = -(m_opt->value()); // Remove indent log.indent(0); // Return return; } /***********************************************************************//** * @brief Re-optimise model parameters for TS computation * * Re-optimise the model parameters using a maximum likelihood fit for * computation of the Test Statistic value for a given source. ***************************************************************************/ double ctlike::reoptimize_lm(void) { // Write Header for optimization and indent for optimizer logging log_header1(TERSE, "Maximum likelihood re-optimisation"); log.indent(1); // Create a clone of the optimizer for the re-optimisation GOptimizer* opt = m_opt->clone(); // 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); log_header1(NORMAL, "Maximum likelihood re-optimisation results"); log_string(NORMAL, opt->print(m_chatter)); // Return return (logL); } /*========================================================================== = = = Private methods = = = ==========================================================================*/ /***********************************************************************//** * @brief Initialise class members ***************************************************************************/ void ctlike::init_members(void) { // Initialise members m_outmodel.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; m_fix_spat_for_ts = false; m_chatter = static_cast(2); // Set logger properties log.date(true); // Allocate LM optimizer GOptimizerLM* opt = new GOptimizerLM(); // Set optimizer parameters opt->max_iter(m_max_iter); opt->max_stalls(m_max_stall); // Set optimizer pointer m_opt = opt; // 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_outmodel = app.m_outmodel; 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; m_fix_spat_for_ts = app.m_fix_spat_for_ts; m_chatter = app.m_chatter; // 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; }