/***********************************************************************//**
* @brief Test binned optimizer
***************************************************************************/
void TestGCTAOptimize::test_binned_optimizer(void)
{
// Declare observations
GObservations obs;
GCTAObservation run;
// Load binned CTA observation
test_try("Load binned CTA observation");
try {
run.load_binned(cta_cntmap);
run.response(cta_irf,cta_caldb);
obs.append(run);
test_try_success();
}
catch (std::exception &e) {
test_try_failure(e);
}
// Load models from XML file
obs.models(cta_model_xml);
// Perform LM optimization
double fit_results[] = {83.6331, 0,
22.0145, 0,
5.616410411e-16, 1.904730785e-17,
-2.481781246, -0.02580905077,
300000, 0,
1, 0,
2.933677595, 0.06639644824,
6.550723074e-05, 1.945714239e-06,
-1.833781187, -0.0161464076,
1000000, 0,
1, 0};
test_try("Perform LM optimization");
try {
GOptimizerLM opt;
opt.max_iter(100);
obs.optimize(opt);
test_try_success();
for (int i = 0, j = 0; i < obs.models().size(); ++i) {
GModel* model = obs.models()[i];
for (int k = 0; k < model->size(); ++k) {
GModelPar& par = (*model)[k];
std::string msg = "Verify optimization result for " + par.print();
test_value(par.real_value(), fit_results[j++], 5.0e-5, msg);
test_value(par.real_error(), fit_results[j++], 5.0e-5, msg);
}
}
}
catch (std::exception &e) {
test_try_failure(e);
}
// Exit test
return;
}
/***********************************************************************//**
* @brief Test unbinned optimizer
***************************************************************************/
void TestGCTAOptimize::test_unbinned_optimizer(void)
{
// Declare observations
GObservations obs;
GCTAObservation run;
// Load unbinned CTA observation
test_try("Load unbinned CTA observation");
try {
run.load_unbinned(cta_events);
run.response(cta_irf,cta_caldb);
obs.append(run);
test_try_success();
}
catch (std::exception &e) {
test_try_failure(e);
}
// Load models from XML file
obs.models(cta_model_xml);
// Perform LM optimization
double fit_results[] = {83.6331, 0,
22.0145, 0,
5.656246512e-16, 1.91458426e-17,
-2.484100472, -0.02573396361,
300000, 0,
1, 0,
2.993705325, 0.03572658413,
6.490832107e-05, 1.749021094e-06,
-1.833584022, -0.01512223495,
1000000, 0,
1, 0};
test_try("Perform LM optimization");
try {
GOptimizerLM opt;
opt.max_iter(100);
obs.optimize(opt);
test_try_success();
for (int i = 0, j = 0; i < obs.models().size(); ++i) {
GModel* model = obs.models()[i];
for (int k = 0; k < model->size(); ++k) {
GModelPar& par = (*model)[k];
std::string msg = "Verify optimization result for " + par.print();
test_value(par.real_value(), fit_results[j++], 5.0e-5, msg);
test_value(par.real_error(), fit_results[j++], 5.0e-5, msg);
}
}
}
catch (std::exception &e) {
test_try_failure(e);
}
// Exit test
return;
}
/***********************************************************************//**
* @brief Test binned optimizer
*
* @param[in] datadir Directory of test data.
* @param[in] irf Instrument response function.
* @param[in] fit_results Expected fit result.
*
* Verifies the ability optimize binned Fermi/LAT data.
***************************************************************************/
void TestGLATOptimize::test_one_binned_optimizer(const std::string& datadir,
const std::string& irf,
const double* fit_results)
{
// Set filenames
std::string lat_srcmap = datadir+"/srcmap.fits";
std::string lat_expmap = datadir+"/binned_expmap.fits";
std::string lat_ltcube = datadir+"/ltcube.fits";
std::string lat_model_xml = datadir+"/source_model.xml";
// Setup GObservations for optimizing
GObservations obs;
GLATObservation run;
test_try("Setup for optimization");
try {
run.load_binned(lat_srcmap, lat_expmap, lat_ltcube);
run.response(irf, lat_caldb);
obs.append(run);
test_try_success();
}
catch (std::exception &e) {
test_try_failure(e);
}
// Load models from XML file
obs.models(lat_model_xml);
// Setup LM optimizer
test_try("Perform LM optimization");
try {
GOptimizerLM opt;
opt.max_iter(1000);
obs.optimize(opt);
obs.errors(opt);
test_try_success();
for (int i = 0, j = 0; i < obs.models().size(); ++i) {
const GModel* model = obs.models()[i];
for (int k = 0; k < model->size(); ++k) {
GModelPar par = (*model)[k];
std::string msg = "Verify optimization result for " + par.print();
test_value(par.value(), fit_results[j++], 5.0e-5, msg);
test_value(par.error(), fit_results[j++], 5.0e-5, msg);
}
}
}
catch (std::exception &e) {
test_try_failure(e);
}
// Exit test
return;
}
/***********************************************************************//**
* @brief Test observations optimizer.
*
* @param[in] mode Testing mode.
*
* This method supports two testing modes: 0 = unbinned and 1 = binned.
***************************************************************************/
void TestOpenMP::test_observations_optimizer(const int& mode)
{
// Create Test Model
GTestModelData model;
// Create Models conteners
GModels models;
models.append(model);
// Time iterval
GTime tmin(0.0);
GTime tmax(1800.0);
// Rate : events/sec
double rate = RATE;
// Create observations
GObservations obs;
// Add some observation
for (int i = 0; i < 6; ++i) {
// Random Generator
GRan ran;
ran.seed(i);
// Allocate events pointer
GEvents *events;
// Create either a event list or an event cube
if (mode == UN_BINNED) {
events = model.generateList(rate,tmin,tmax,ran);
}
else {
events = model.generateCube(rate,tmin,tmax,ran);
}
// Create an observation
GTestObservation ob;
ob.id(gammalib::str(i));
// Add events to the observation
ob.events(*events);
ob.ontime(tmax.secs()-tmin.secs());
obs.append(ob);
// Delete events pointer
delete events;
}
// Add the model to the observation
obs.models(models);
// Create a GLog for show the interations of optimizer.
GLog log;
// Create an optimizer.
GOptimizerLM opt(log);
opt.max_stalls(50);
// Optimize
obs.optimize(opt);
// Get the result
GModelPar result = (*(obs.models()[0]))[0];
// Check if converged
test_assert(opt.status()==0, "Check if converged",
"Optimizer did not converge");
// Check if value is correct
test_value(result.factor_value(),RATE,result.factor_error()*3);
// Return
return;
}
/***********************************************************************//**
* @brief Create output observation container.
*
* Creates an output observation container that combines all input CTA
* observation into a single cube-style observation. All non CTA observations
* present in the observation container are kept. The method furthermore
* conserves any response information in case that a single CTA observation
* is provided. This supports the original binned analysis.
***************************************************************************/
void ctbin::obs_cube(void)
{
// If we have only a single CTA observation in the container, then
// keep that observation and just attach the event cube to it. Reset
// the filename, otherwise we still will have the old event filename
// in the log file.
if (m_obs.size() == 1) {
// Attach event cube to CTA observation
GCTAObservation* obs = dynamic_cast<GCTAObservation*>(m_obs[0]);
if (obs != NULL) {
obs->events(this->cube());
obs->eventfile("");
}
}
// ... otherwise put a single CTA observation in container
else {
// Allocate observation container
GObservations container;
// Allocate CTA observation.
GCTAObservation obs;
// Attach event cube to CTA observation
obs.events(this->cube());
// Set map centre as pointing
GSkyPixel pixel(0.5*double(m_cube.nx()), 0.5*double(m_cube.ny()));
GSkyDir centre = m_cube.pix2dir(pixel);
GCTAPointing pointing(centre);
// Compute deadtime correction
double deadc = (m_ontime > 0.0) ? m_livetime / m_ontime : 0.0;
// Set CTA observation attributes
obs.pointing(pointing);
obs.obs_id(0);
obs.ra_obj(centre.ra_deg()); //!< Dummy
obs.dec_obj(centre.dec_deg()); //!< Dummy
obs.ontime(m_ontime);
obs.livetime(m_livetime);
obs.deadc(deadc);
// Set models in observation container
container.models(m_obs.models());
// Append CTA observation
container.append(obs);
// Copy over all remaining non-CTA observations
for (int i = 0; i < m_obs.size(); ++i) {
GCTAObservation* obs = dynamic_cast<GCTAObservation*>(m_obs[i]);
if (obs == NULL) {
container.append(*m_obs[i]);
}
}
// Set observation container
m_obs = container;
} // endelse: there was not a single CTA observation
// Return
return;
}
/***********************************************************************//**
* @brief Set models
*
* @param[in] models Model container.
*
* Set model container that should be used for model generation.
***************************************************************************/
inline
void ctmodel::models(const GModels& models)
{
m_obs.models(models);
return;
}
