ctprob.cpp
17.3 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
/***************************************************************************
* ctprob - Computes event probability for a given model *
* ----------------------------------------------------------------------- *
* copyright (C) 2017 by Leonardo Di Venere *
* ----------------------------------------------------------------------- *
* *
* 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 <http://www.gnu.org/licenses/>. *
* *
***************************************************************************/
/**
* @file ctprob.cpp
* @brief Event probability computation tool implementation
* @author Leonardo Di Venere
*/
/* __ Includes ___________________________________________________________ */
#ifdef HAVE_CONFIG_H
#include <config.h>
#endif
#include <cstdlib>
#include "ctprob.hpp"
#include "GTools.hpp"
/* __ Method name definitions ____________________________________________ */
#define G_EVALUATE_PROB "ctprob::evaluate_probability(GCTAObservation*)"
/* __ Debug definitions __________________________________________________ */
/* __ Coding definitions _________________________________________________ */
/*==========================================================================
= =
= Constructors/destructors =
= =
==========================================================================*/
/***********************************************************************//**
* @brief Void constructor
***************************************************************************/
ctprob::ctprob(void) : ctobservation(CTPROB_NAME, VERSION)
{
// Initialise members
init_members();
// Return
return;
}
/***********************************************************************//**
* @brief Observations constructor
*
* param[in] obs Observation container.
*
* Creates an instance of the class that is initialised using the information
* provided in an observation container.
***************************************************************************/
ctprob::ctprob(const GObservations& obs) :
ctobservation(CTPROB_NAME, VERSION, obs)
{
// Initialise members
init_members();
// Return
return;
}
/***********************************************************************//**
* @brief Command line constructor
*
* @param[in] argc Number of arguments in command line.
* @param[in] argv Array of command line arguments.
***************************************************************************/
ctprob::ctprob(int argc, char *argv[]) :
ctobservation(CTPROB_NAME, VERSION, argc, argv)
{
// Initialise members
init_members();
// Return
return;
}
/***********************************************************************//**
* @brief Copy constructor
*
* @param[in] app Application.
***************************************************************************/
ctprob::ctprob(const ctprob& app) : ctobservation(app)
{
// Initialise members
init_members();
// Copy members
copy_members(app);
// Return
return;
}
/***********************************************************************//**
* @brief Destructor
***************************************************************************/
ctprob::~ctprob(void)
{
// Free members
free_members();
// Return
return;
}
/*==========================================================================
= =
= Operators =
= =
==========================================================================*/
/***********************************************************************//**
* @brief Assignment operator
*
* @param[in] app Application.
* @return Application.
***************************************************************************/
ctprob& ctprob::operator=(const ctprob& app)
{
// Execute only if object is not identical
if (this != &app) {
// Copy base class members
this->ctobservation::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 ctprob tool
*
* Clears ctprob tool.
***************************************************************************/
void ctprob::clear(void)
{
// Free members
free_members();
this->ctobservation::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();
this->ctobservation::init_members();
init_members();
// Write header into logger
log_header();
// Return
return;
}
/***********************************************************************//**
* @brief Runs the ctprob tool
*
* This method reads in the application parameters and loops over all
* unbinned observations to compute the probability for each event that it
* comes from one of the model components.
***************************************************************************/
void ctprob::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<bool> save_edisp = set_edisp(m_obs, m_apply_edisp);
// Write input observation container into logger
log_observations(NORMAL, m_obs, "Input observation");
// Write header into logger
log_header1(TERSE, "Compute event probabilities");
// Initialise counters
int n_observations = 0;
// Loop over all unbinned CTA observations in the container
for (GCTAObservation* obs = first_unbinned_observation(); obs != NULL;
obs = next_unbinned_observation()) {
// Increment counter
n_observations++;
// Evaluate event probabilities
evaluate_probability(obs);
} // endfor: looped over observations
// If more than a single observation has been handled then make sure that
// an XML file will be used for storage
if (n_observations > 1) {
m_use_xml = true;
}
// Write observation(s) into logger
log_observations(NORMAL, m_obs, "Output observation");
// Restore energy dispersion flags of all CTA observations
restore_edisp(m_obs, save_edisp);
// Optionally publish event list(s)
if ((*this)["publish"].boolean()) {
publish();
}
// Return
return;
}
/***********************************************************************//**
* @brief Save the selected event list(s)
*
* This method saves the selected event list(s) into FITS file(s). There are
* two modes, depending on the m_use_xml flag.
*
* If m_use_xml is true, all selected event list(s) will be saved into FITS
* files, where the output filenames are constructued from the input
* filenames by prepending the m_prefix string to name. Any path information
* will be stripped form the input name, hence event files will be written
* into the local working directory (unless some path information is present
* in the prefix). In addition, an XML file will be created that gathers
* the filename information for the selected event list(s). If an XML file
* was present on input, all metadata information will be copied from this
* input file.
*
* If m_use_xml is false, the selected event list will be saved into a FITS
* file.
***************************************************************************/
void ctprob::save(void)
{
// Write header into logger
log_header1(TERSE, gammalib::number("Save event list", m_obs.size()));
// Case A: Save event file(s) and XML metadata information
if (m_use_xml) {
save_events_xml();
}
// Case B: Save event file as FITS file
else {
save_events_fits();
}
// Return
return;
}
/***********************************************************************//**
* @brief Publish event lists
*
* @param[in] name Event list name.
***************************************************************************/
void ctprob::publish(const std::string& name)
{
// Write header into logger
log_header1(TERSE, gammalib::number("Publish event list", m_obs.size()));
// Loop over all observation in the container
for (int i = 0; i < m_obs.size(); ++i) {
// Get CTA observation
GCTAObservation* obs = dynamic_cast<GCTAObservation*>(m_obs[i]);
// Handle only CTA observations
if (obs != NULL) {
// Continue only if there is an event list
if (obs->events()->size() != 0) {
// Set default name if user name is empty
std::string user_name(name);
if (user_name.empty()) {
user_name = CTPROB_NAME;
}
// If there are several event lists then add an index
if (m_use_xml) {
user_name += gammalib::str(i);
}
// Write event list name into logger
log_value(NORMAL, "Event list name", user_name);
// Write events into in-memory FITS file
GFits fits;
obs->write(fits);
// Publish
fits.publish(gammalib::extname_cta_events, user_name);
} // endif: there were events
} // endif: observation was a CTA observation
} // endfor: looped over observations
// Return
return;
}
/*==========================================================================
= =
= Private methods =
= =
==========================================================================*/
/***********************************************************************//**
* @brief Initialise class members
***************************************************************************/
void ctprob::init_members(void)
{
// Initialise parameters
m_apply_edisp = false;
m_publish = false;
m_chatter = static_cast<GChatter>(2);
// Return
return;
}
/***********************************************************************//**
* @brief Copy class members
*
* @param[in] app Application.
***************************************************************************/
void ctprob::copy_members(const ctprob& app)
{
// Copy parameters
m_apply_edisp = app.m_apply_edisp;
m_publish = app.m_publish;
m_chatter = app.m_chatter;
// Return
return;
}
/***********************************************************************//**
* @brief Delete class members
***************************************************************************/
void ctprob::free_members(void)
{
// Return
return;
}
/***********************************************************************//**
* @brief Get application parameters
*
* Get all application parameters by either querying the parameters or by
* retrieving the parameters for the parameter file.
***************************************************************************/
void ctprob::get_parameters(void)
{
// Setup observations from "inobs" parameter. Request response
// information, accept event lists but do not accept counts cubes.
setup_observations(m_obs, true, true, false);
// Read model definition file if required
if (m_obs.models().size() == 0) {
// Get model filename
std::string inmodel = (*this)["inmodel"].filename();
// Load models from file
m_obs.models(inmodel);
} // endif: there were no models
// Get energy dispersion flag parameters
m_apply_edisp = (*this)["edisp"].boolean();
// Get remaining parameters
m_publish = (*this)["publish"].boolean();
m_chatter = static_cast<GChatter>((*this)["chatter"].integer());
// Optionally read ahead parameters so that they get correctly
// dumped into the log file
if (read_ahead()) {
(*this)["outobs"].filename();
(*this)["prefix"].string();
}
// Write parameters into logger
log_parameters(TERSE);
// Return
return;
}
/***********************************************************************//**
* @brief Evaluate probability for events
*
* @param[in,out] obs CTA observation.
*
* @exception GException::invalid_value
* Observation does not contain an event list.
*
* Computes for all events the probability that an event arises from a
* specific model component. The computation is done by by evaluating the
* differential event probability for a given model and normalizing these
* probabilities so that the sum of the probabilities for all model
* components is unity for each event.
*
* The method appends for each model component a single precision column to
* the event list that contains the event probabilities. The name of the
* column is build from the model name prefixed with `PROB_`.
***************************************************************************/
void ctprob::evaluate_probability(GCTAObservation* obs)
{
// Write header into logger
log_header3(NORMAL, "Evaluate events probabilities");
// Make sure that the observation holds a CTA event list. If this
// is not the case then throw an exception.
GCTAEventList* events = dynamic_cast<GCTAEventList*>(const_cast<GEvents*>
(obs->events()));
if (events == NULL) {
std::string msg = "CTA Observation does not contain an event list. An "
"event list is needed to compute the event "
"probabilities.";
throw GException::invalid_value(G_EVALUATE_PROB, msg);
}
// Continue only if there are model components
int nmodels = m_obs.models().size();
if (nmodels > 0) {
// Allocate single precision FITS table columns for all model components
std::vector<GFitsTableFloatCol*> columns;
for (int k = 0; k < nmodels; ++k) {
const std::string colname = "PROB_" + m_obs.models()[k] ->name();
GFitsTableFloatCol* col =
new GFitsTableFloatCol(colname, events->size());
columns.push_back(col);
}
// Loop over all events in the event list
for (int i = 0; i < events->size(); ++i) {
// Initialise total probability
double total = 0.0;
// Get point to event
const GEvent* event = (*events)[i];
// Initialise probability vector
std::vector<double> probabilities(nmodels, 0.0);
// Loop over models
for (int k = 0; k < nmodels; ++k) {
double value = m_obs.models()[k]->eval(*event, *obs);
probabilities[k] = value;
total += value;
}
// Normalize probabilities to unity
if (total > 0.0) {
for (int k = 0; k < nmodels; ++k) {
probabilities[k] /= total;
}
}
// Store probabilities in FITS columns
for (int k = 0; k < nmodels; ++k) {
(*(columns[k]))(i) = probabilities[k];
}
} // endfor: looped over all events
// Append columns to event list
for (int k = 0; k < nmodels; ++k) {
events->append_column(*columns[k]);
}
} // endif: there were model components
// Return
return;
}