Iftach Sadeh / ctools

Commit 4dc88fd65f7ae20f164316b4ad27f5f9296b9588

Authored by Jürgen Knödlseder
1 parent 996c4df2

Merge in cterror application.

Inline Side-by-side
Showing 9 changed files with 142 additions and 117 deletions
pyext/cterror.i
  View file @4dc88fd
1 1 /***************************************************************************
2   - * cterror - Parameter error calculation tool *
  2 + * cterror - Parameter error calculation tool *
3 3 * ----------------------------------------------------------------------- *
4 4 * copyright (C) 2015 by Florent Forest *
5 5 * ----------------------------------------------------------------------- *
... ... @@ -38,7 +38,7 @@
38 38 ***************************************************************************/
39 39 class cterror : public ctool {
40 40  
41   - public:
  41 +public:
42 42 // Constructors and destructors
43 43 cterror(void);
44 44 explicit cterror(const GObservations& obs);
... ... @@ -52,9 +52,9 @@ class cterror : public ctool {
52 52 void save(void);
53 53 const GObservations& obs(void) const;
54 54 const GOptimizer* opt(void) const;
55   -
56 55 };
57 56  
  57 +
58 58 /***********************************************************************//**
59 59 * @brief Parameter error calculation tool Python extensions
60 60 ***************************************************************************/
... ...
pyext/ctools/obsutils.py
  View file @4dc88fd
... ... @@ -140,9 +140,10 @@ def fit(obs, log=False, debug=False, chatter=2, edisp=False):
140 140 Parameters:
141 141 obs - Observation container
142 142 Keywords:
143   - log - Create log file(s)
144   - debug - Create screen dump
145   - edisp - Apply energy dispersion?
  143 + log - Create log file(s)
  144 + debug - Create screen dump
  145 + chatter - Chatter level
  146 + edisp - Apply energy dispersion?
146 147 """
147 148 # Allocate ctlike application
148 149 like = ctools.ctlike(obs)
... ... @@ -167,19 +168,21 @@ def fit(obs, log=False, debug=False, chatter=2, edisp=False):
167 168 # Return observations
168 169 return like
169 170  
170   -# ================ #
171   -# Run cterror #
172   -# ================ #
173   -def cterror(obs, log=False, debug=False):
  171 +
  172 +# ============================================================== #
  173 +# Fit observations and determine errors using likelihood profile #
  174 +# ============================================================== #
  175 +def cterror(obs, log=False, debug=False, chatter=2):
174 176 """
175 177 Perform maximum likelihood fitting of observations in the container.
176 178  
177 179 Parameters:
178 180 obs - Observation container
179 181 Keywords:
180   - log - Create log file(s)
181   - debug - Create screen dump
182   - edisp - Apply energy dispersion?
  182 + log - Create log file(s)
  183 + debug - Create screen dump
  184 + chatter - Chatter level
  185 + edisp - Apply energy dispersion?
183 186 """
184 187 # Allocate cterror application
185 188 error = ctools.cterror(obs)
... ... @@ -192,6 +195,9 @@ def cterror(obs, log=False, debug=False):
192 195 if debug:
193 196 error["debug"].boolean(True)
194 197  
  198 + # Set chatter level
  199 + error["chatter"].chatter = chatter
  200 +
195 201 # Run cterror application.
196 202 error.run()
197 203  
... ...
scripts/cspull.py
  View file @4dc88fd
... ... @@ -47,6 +47,8 @@ class cspull(ctools.cscript):
47 47 self.obs = None
48 48 self.model = None
49 49 self.m_inmodel = None
  50 + self.m_edisp = False
  51 + self.m_profile = False
50 52  
51 53 # Make sure that parfile exists
52 54 file = self.parfile()
... ... @@ -103,6 +105,7 @@ class cspull(ctools.cscript):
103 105 pars.append(gammalib.GApplicationPar("irf","s","a","South_50h","","","Instrument response function"))
104 106 pars.append(gammalib.GApplicationPar("deadc","r","h","0.95","0","1","Deadtime correction factor"))
105 107 pars.append(gammalib.GApplicationPar("edisp","b","h","no","","","Apply energy dispersion?"))
  108 + pars.append(gammalib.GApplicationPar("profile","b","h","no","","","Use likelihood profile method for errors?"))
106 109 pars.append(gammalib.GApplicationPar("ntrials","i","a","10","","","Number of trials"))
107 110 pars.append(gammalib.GApplicationPar("ra","r","a","83.6331","0","360","RA of pointing (deg)"))
108 111 pars.append(gammalib.GApplicationPar("dec","r","a","22.0145","-90","90","Dec of pointing (deg)"))
... ... @@ -160,6 +163,7 @@ class cspull(ctools.cscript):
160 163 self.m_ntrials = self["ntrials"].integer()
161 164 self.m_edisp = self["edisp"].boolean()
162 165 self.m_offset = self["offset"].real()
  166 + self.m_profile = self["profile"].boolean()
163 167  
164 168 # Set some fixed parameters
165 169 self.m_log = False # Logging in client tools
... ... @@ -297,9 +301,12 @@ class cspull(ctools.cscript):
297 301 self.log("\n")
298 302  
299 303 # Fit model
300   - #like = obsutils.fit(obs, edisp=self.m_edisp, \
301   - # log=self.m_log, debug=self.m_debug)
302   - like = obsutils.cterror(obs, log=self.m_log, debug=self.m_debug)
  304 + if self.m_profile:
  305 + like = obsutils.cterror(obs, \
  306 + log=self.m_log, debug=self.m_debug)
  307 + else:
  308 + like = obsutils.fit(obs, edisp=self.m_edisp, \
  309 + log=self.m_log, debug=self.m_debug)
303 310  
304 311 # Store results
305 312 logL = like.opt().value()
... ...
src/cterror/cterror.cpp
  View file @4dc88fd
1 1 /***************************************************************************
2   - * cterror - Parameter error calculation tool *
  2 + * cterror - Parameter error calculation tool *
3 3 * ----------------------------------------------------------------------- *
4 4 * copyright (C) 2015 by Florent Forest *
5 5 * ----------------------------------------------------------------------- *
... ... @@ -72,7 +72,7 @@ cterror::cterror(void) : ctool(CTERROR_NAME, CTERROR_VERSION)
72 72 * observations container.
73 73 ***************************************************************************/
74 74 cterror::cterror(const GObservations& obs) :
75   - ctool(CTERROR_NAME, CTERROR_VERSION)
  75 + ctool(CTERROR_NAME, CTERROR_VERSION)
76 76 {
77 77 // Initialise members
78 78 init_members();
... ... @@ -93,7 +93,7 @@ cterror::cterror(const GObservations& obs) :
93 93 * @param[in] argv Array of command line arguments.
94 94 ***************************************************************************/
95 95 cterror::cterror(int argc, char *argv[]) :
96   - ctool(CTERROR_NAME, CTERROR_VERSION, argc, argv)
  96 + ctool(CTERROR_NAME, CTERROR_VERSION, argc, argv)
97 97 {
98 98 // Initialise members
99 99 init_members();
... ... @@ -198,7 +198,6 @@ void cterror::clear(void)
198 198  
199 199 /***********************************************************************//**
200 200 * @brief Computes
201   - *
202 201 ***************************************************************************/
203 202 void cterror::run(void)
204 203 {
... ... @@ -228,11 +227,9 @@ void cterror::run(void)
228 227 log << m_obs << std::endl;
229 228 }
230 229  
231   - // Save original models
232   - GModels models_orig = m_obs.models();
233   -
234 230 // Allocate optimizer
235 231 m_opt = new GOptimizerLM();
  232 +
236 233 // Optimize and save best log-likelihood
237 234 m_obs.optimize(*m_opt);
238 235 m_obs.errors(*m_opt);
... ... @@ -249,35 +246,44 @@ void cterror::run(void)
249 246 log << m_obs.models() << std::endl;
250 247 }
251 248  
252   -
253 249 // Continue only if source model exists
254 250 if (m_obs.models().contains(m_srcname)) {
255 251  
256   - GModels& models = const_cast<GModels&>(m_obs.models());
257   - m_skymodel = dynamic_cast<GModelSky*>(models[m_srcname]);
258   - if (m_skymodel == NULL) {
  252 + // Save best fitting models
  253 + GModels models_best = m_obs.models();
  254 +
  255 + // Get pointer on sky model
  256 + GModelSky* model = dynamic_cast<GModelSky*>(models_best[m_srcname]);
  257 + if (model == NULL) {
259 258 std::string msg = "Source \""+m_srcname+"\" is not a sky model. "
260   - "Please specify the name of a sky model for "
261   - "parameter error computation.";
  259 + "Please specify the name of a sky model for "
  260 + "parameter error computation.";
262 261 throw GException::invalid_value(G_RUN, msg);
263 262 }
264 263  
265   - int npars = m_skymodel->spectral()->size();
  264 + // Get number of spectral parameters
  265 + int npars = model->spectral()->size();
266 266  
  267 + // Loop over spectral parameters of sky model
  268 + for (int i = 0; i < npars; ++i) {
267 269  
268   - for (int i = 0; i < npars; ++i)
269   - {
  270 + // Skip parameter if it is fixed
  271 + if (model->spectral()->at(i).is_fixed()) {
  272 + continue;
  273 + }
270 274  
271   - // Re-optimize
272   - m_obs.optimize(*m_opt);
  275 + // Initialise with best fitting models
  276 + m_obs.models(models_best);
273 277  
274   - if(m_skymodel->spectral()->at(i).is_fixed())
275   - continue;
  278 + // Get pointer on sky model parameter
  279 + GModels& current_models = const_cast<GModels&>(m_obs.models());
  280 + GModelSky* current_model = dynamic_cast<GModelSky*>(current_models[m_srcname]);
  281 + m_model_par = &(current_model->spectral()->at(i));
276 282  
277   - m_model_par = &(m_skymodel->spectral()->at(i));
  283 + // Extract current value
  284 + m_value = m_model_par->factor_value();
278 285  
279 286 // Compute parameter bracketing
280   - m_value = m_model_par->factor_value();
281 287 double parmin = std::max(m_model_par->factor_min(),
282 288 m_value - 10*m_model_par->factor_error());
283 289 double parmax = std::min(m_model_par->factor_max(),
... ... @@ -288,7 +294,7 @@ void cterror::run(void)
288 294 log << std::endl;
289 295 log.header1("Compute parameter error");
290 296 log << gammalib::parformat("Model name");
291   - log << m_skymodel->name() << std::endl;
  297 + log << model->name() << std::endl;
292 298 log << gammalib::parformat("Parameter name");
293 299 log << m_model_par->name() << std::endl;
294 300 log << gammalib::parformat("Confidence level");
... ... @@ -304,43 +310,38 @@ void cterror::run(void)
304 310 }
305 311  
306 312 // Compute lower boundary
307   - error_bisection(parmin, m_value);
308   - double value_lo = m_model_par->factor_value();
  313 + double value_lo = error_bisection(parmin, m_value);
309 314  
  315 + // Dump lower parameter value
310 316 if (logTerse()) {
311 317 log << gammalib::parformat("Final lower parameter value");
312 318 log << value_lo << std::endl;
313 319 }
314 320  
315   - // Reset parameter to original value
316   - m_model_par->factor_value(m_value);
317   -
318 321 // Compute upper boundary
319   - error_bisection(m_value, parmax);
320   - double value_hi = m_model_par->factor_value();
  322 + double value_hi = error_bisection(m_value, parmax);
321 323  
  324 + // Dump upper parameter value
322 325 if (logTerse()) {
323 326 log << gammalib::parformat("Final upper parameter");
324 327 log << value_hi << std::endl;
325 328 }
326 329  
327   - // Reset parameter to original value
328   - m_model_par->factor_value(m_value);
329   -
330 330 // Compute errors
331   - m_error = 0.5*(value_hi - value_lo);
332   - double error_max = std::max(value_hi-m_value, m_value-value_lo);
333   - double error_min = std::min(value_hi-m_value, m_value-value_lo);
334   -
  331 + m_error = 0.5 * (value_hi - value_lo);
  332 + double error_neg = value_lo - m_value;
  333 + double error_pos = value_hi - m_value;
  334 + //double error_max = std::max(value_hi-m_value, m_value-value_lo);
  335 + //double error_min = std::min(value_hi-m_value, m_value-value_lo);
335 336  
336 337 // Write results to logfile
337 338 if (logTerse()) {
338 339 log << std::endl;
339 340 log.header1("Error results");
340   - log << gammalib::parformat("Max error");
341   - log << error_max;
342   - log << gammalib::parformat("Min error");
343   - log << error_min;
  341 + log << gammalib::parformat("Negative error");
  342 + log << error_neg;
  343 + log << gammalib::parformat("Positive error");
  344 + log << error_pos;
344 345 log << gammalib::parformat("Mean parameter error");
345 346 log << m_error;
346 347 log << " " << m_model_par->unit();
... ... @@ -351,24 +352,24 @@ void cterror::run(void)
351 352 }
352 353  
353 354 // Save error result
354   - m_model_par->factor_error(m_error);
  355 + model->spectral()->at(i).factor_error(m_error);
355 356  
356   - }
  357 + } // endfor: looped over spectral parameters
357 358  
358   - }
  359 + // Restore best fitting models (now with new errors computed)
  360 + m_obs.models(models_best);
359 361  
  362 + } // endif: source model exists
360 363  
361 364 // Return
362 365 return;
363 366 }
364 367  
  368 +
365 369 /***********************************************************************//**
366   - * @brief Save maps
  370 + * @brief Save source model
367 371 *
368   - * This method saves the error to an ascii file.
369   - *
370   - * @todo No yet implemented as we have no clear use case yet for saving
371   - * the result.
  372 + * This method saves the soutce model to an XML file.
372 373 ***************************************************************************/
373 374 void cterror::save(void)
374 375 {
... ... @@ -378,9 +379,8 @@ void cterror::save(void)
378 379 log.header1("Save results");
379 380 }
380 381  
381   -
382 382 // Get output filename
383   - std::string outmodel = (*this)["outfile"].filename();
  383 + std::string outmodel = (*this)["outmodel"].filename();
384 384  
385 385 // Write results out as XML model
386 386 if (gammalib::toupper(outmodel) != "NONE") {
... ... @@ -391,6 +391,7 @@ void cterror::save(void)
391 391 return;
392 392 }
393 393  
  394 +
394 395 /*==========================================================================
395 396 = =
396 397 = Private methods =
... ... @@ -405,8 +406,6 @@ void cterror::init_members(void)
405 406 // Initialise user parameters
406 407 m_srcname.clear();
407 408 m_confidence = 0.68;
408   - m_sigma_min = 0.0;
409   - m_sigma_max = 0.0;
410 409 m_tol = 1.0e-3;
411 410 m_max_iter = 50;
412 411 m_value = 0.0;
... ... @@ -415,9 +414,8 @@ void cterror::init_members(void)
415 414 // Initialise protected members
416 415 m_obs.clear();
417 416 m_dlogL = 0.0;
418   - m_skymodel = NULL;
419   - m_model_par = NULL;
420 417 m_best_logL = 0.0;
  418 + m_model_par = NULL;
421 419  
422 420 // Return
423 421 return;
... ... @@ -434,15 +432,14 @@ void cterror::copy_members(const cterror&amp; app)
434 432 // Copy user parameters
435 433 m_srcname = app.m_srcname;
436 434 m_confidence = app.m_confidence;
437   - m_sigma_min = app.m_sigma_min;
438   - m_sigma_max = app.m_sigma_max;
439 435 m_tol = app.m_tol;
440 436 m_max_iter = app.m_max_iter;
441 437  
442 438 // Copy protected members
443   - m_obs = app.m_obs;
444   - m_dlogL = app.m_dlogL;
445   - m_best_logL = app.m_best_logL;
  439 + m_obs = app.m_obs;
  440 + m_dlogL = app.m_dlogL;
  441 + m_best_logL = app.m_best_logL;
  442 + m_model_par = NULL;
446 443  
447 444 // Return
448 445 return;
... ... @@ -506,19 +503,13 @@ void cterror::get_parameters(void)
506 503  
507 504 // Get confidence level and transform into log-likelihood difference
508 505 m_confidence = (*this)["confidence"].real();
509   -
510 506 double sigma = gammalib::erfinv(m_confidence) * gammalib::sqrt_two;
511 507 m_dlogL = (sigma*sigma) / 2.0;
512 508  
513   - // Read starting boundaries for bisection
514   - m_sigma_min = (*this)["sigma_min"].real();
515   - m_sigma_max = (*this)["sigma_max"].real();
516   -
517   - // Read precision
  509 + // Read other parameters
518 510 m_tol = (*this)["tol"].real();
519 511 m_max_iter = (*this)["max_iter"].integer();
520 512  
521   -
522 513 // Return
523 514 return;
524 515 }
... ... @@ -532,7 +523,7 @@ void cterror::get_parameters(void)
532 523 *
533 524 * This method calculates the error using a bisection method.
534 525 ***************************************************************************/
535   -void cterror::error_bisection(const double& min, const double& max)
  526 +double cterror::error_bisection(const double& min, const double& max)
536 527 {
537 528 // Copy values to working values
538 529 double wrk_min = min;
... ... @@ -541,6 +532,9 @@ void cterror::error_bisection(const double&amp; min, const double&amp; max)
541 532 // Initialise iteration counter
542 533 int iter = 0;
543 534  
  535 + // Initialize mid value
  536 + double mid = (wrk_min + wrk_max) / 2.0;
  537 +
544 538 // Loop until breaking condition is reached
545 539 while (true) {
546 540  
... ... @@ -556,8 +550,7 @@ void cterror::error_bisection(const double&amp; min, const double&amp; max)
556 550  
557 551 // Throw exception if maximum iterations are reached
558 552 if (iter > m_max_iter) {
559   - if(wrk_min - m_model_par->factor_min() < m_tol)
560   - {
  553 + if(wrk_min - m_model_par->factor_min() < m_tol) {
561 554 std::string msg = "The "+m_model_par->name()+" parameter minimum has been"
562 555 " reached during error calculation. To obtain accurate "
563 556 " errors, consider to set the minimum to a lower value,"
... ... @@ -567,8 +560,7 @@ void cterror::error_bisection(const double&amp; min, const double&amp; max)
567 560 }
568 561 break;
569 562 }
570   - else if(m_model_par->factor_max() - wrk_max < m_tol)
571   - {
  563 + else if(m_model_par->factor_max() - wrk_max < m_tol) {
572 564 std::string msg = "The "+m_model_par->name()+" parameter maximum has been"
573 565 " reached during error calculation. To obtain accurate "
574 566 " errors, consider to set the maxmimum to a higher value"
... ... @@ -578,8 +570,7 @@ void cterror::error_bisection(const double&amp; min, const double&amp; max)
578 570 }
579 571 break;
580 572 }
581   - else
582   - {
  573 + else {
583 574 std::string msg = "The maximum number of "+gammalib::str(m_max_iter)+
584 575 " has been reached. You may consider to increase"
585 576 " the \"max_iter\" parameter, and re-run cterror.";
... ... @@ -588,7 +579,7 @@ void cterror::error_bisection(const double&amp; min, const double&amp; max)
588 579 }
589 580  
590 581 // Compute center of boundary
591   - double mid = (wrk_min + wrk_max) / 2.0;
  582 + mid = (wrk_min + wrk_max) / 2.0;
592 583  
593 584 // Calculate function value
594 585 double eval_mid = evaluate(mid);
... ... @@ -598,9 +589,9 @@ void cterror::error_bisection(const double&amp; min, const double&amp; max)
598 589 break;
599 590 }
600 591  
601   - // If we are on the crescent side of the parabola
602   - if (mid > m_value)
603   - {
  592 + // If we are on the crescent side of the parabola ...
  593 + if (mid > m_value) {
  594 +
604 595 // Change boundaries for further iteration
605 596 if (eval_mid > 0.0) {
606 597 wrk_max = mid;
... ... @@ -609,9 +600,10 @@ void cterror::error_bisection(const double&amp; min, const double&amp; max)
609 600 wrk_min = mid;
610 601 }
611 602 }
612   - // If we are on the decrescent side of the parabola
613   - else
614   - {
  603 +
  604 + // ... otherwise we are on the decrescent side of the parabola
  605 + else {
  606 +
615 607 // Change boundaries for further iteration
616 608 if (eval_mid > 0.0) {
617 609 wrk_min = mid;
... ... @@ -626,8 +618,8 @@ void cterror::error_bisection(const double&amp; min, const double&amp; max)
626 618  
627 619 } // endwhile
628 620  
629   - // Return
630   - return;
  621 + // Return mid value
  622 + return mid;
631 623  
632 624 }
633 625  
... ... @@ -652,15 +644,12 @@ double cterror::evaluate(const double&amp; value)
652 644 // Change parameter factor
653 645 m_model_par->factor_value(value);
654 646  
655   - //Fix parameter
  647 + // Fix parameter
656 648 m_model_par->fix();
657 649  
658 650 // Re-optimize
659 651 m_obs.optimize(*m_opt);
660 652  
661   - // Evaluate likelihood for new model container
662   - m_obs.eval();
663   -
664 653 // Retrieve likelihood
665 654 logL = m_obs.logL();
666 655  
... ... @@ -673,7 +662,7 @@ double cterror::evaluate(const double&amp; value)
673 662 else {
674 663 std::string msg = "Value of parameter \""+m_model_par->name()+"\" "
675 664 "outside of validity range requested. To omit "
676   - "this error please enlarge the parameter range "
  665 + "this error please enlarge the parameter range "
677 666 "in the model XML file.";
678 667 throw GException::invalid_value(G_EVALUATE, msg);
679 668 }
... ... @@ -681,7 +670,6 @@ double cterror::evaluate(const double&amp; value)
681 670 // Compute function value
682 671 double logL_difference = logL - m_best_logL - m_dlogL;
683 672  
684   -
685 673 // Return
686 674 return logL_difference;
687 675 }
... ...
src/cterror/cterror.hpp
  View file @4dc88fd
1 1 /***************************************************************************
2   - * cterror - Parameter error calculation tool *
  2 + * cterror - Parameter error calculation tool *
3 3 * ----------------------------------------------------------------------- *
4 4 * copyright (C) 2015 by Florent Forest *
5 5 * ----------------------------------------------------------------------- *
... ... @@ -70,13 +70,11 @@ protected:
70 70 void free_members(void);
71 71 void get_parameters(void);
72 72 double evaluate(const double& value);
73   - void error_bisection(const double& min, const double& max);
  73 + double error_bisection(const double& min, const double& max);
74 74  
75 75 // User parameters
76 76 std::string m_srcname; //!< Name of source which is moved around
77 77 double m_confidence; //!< Confidence level
78   - double m_sigma_min; //!< Starting value minimum (multiple fit errors above fit values)
79   - double m_sigma_max; //!< Starting value maximum (multiple fit errors above fit values)
80 78 double m_tol; //!< Tolerance for limit determination
81 79 int m_max_iter; //!< Maximum number of iterations
82 80 double m_value; //!< Parameter value
... ... @@ -85,7 +83,6 @@ protected:
85 83 // Protected members
86 84 GObservations m_obs; //!< Observation container
87 85 double m_dlogL; //!< Likelihood difference for upper limit computation
88   - GModelSky* m_skymodel; //!< Pointer to sky model
89 86 GModelPar* m_model_par; //!< Pointer to model parameter
90 87 double m_best_logL; //!< Best fit log likelihood of given model
91 88 GOptimizerLM* m_opt;
... ...
src/cterror/cterror.par
  View file @4dc88fd
... ... @@ -19,20 +19,18 @@
19 19 #===================
20 20 inobs, f, a, "events.fits",,, "Input event list, counts cube or observation definition file"
21 21 inmodel, f, a, "$CTOOLS/share/models/crab.xml",,, "Source model"
22   -outfile, f, a, "results.xml",,, "Save results"
  22 +outmodel, f, a, "results.xml",,, "Source model output file"
23 23 srcname, s, a, "Crab",,, "Source of interest"
24 24 expcube, f, a, "NONE",,, "Exposure cube file (only needed for stacked analysis)"
25 25 psfcube, f, a, "NONE",,, "PSF cube file (only needed for stacked analysis)"
26 26 bkgcube, f, a, "NONE",,, "Background cube file (only needed for stacked analysis)"
27   -caldb, s, a, "dummy",,, "Calibration database"
28   -irf, s, a, "cta_dummy_irf",,, "Instrument response function"
  27 +caldb, s, a, "prod2",,, "Calibration database"
  28 +irf, s, a, "South_50h",,, "Instrument response function"
29 29  
30 30 #
31 31 # Upper limit calculation parameters
32 32 #===================================
33 33 confidence, r, h, 0.68,0.0,1.0, "Confidence level"
34   -sigma_min, r, h, 0.0,,, "Start minimum value (multiple sigmas above fit value)"
35   -sigma_max, r, h, 10.0,,, "Start maximum value (multiple sigmas above fit value)"
36 34 tol, r, h, 1e-3,,, "Computation tolerance"
37 35 max_iter, i, h, 50,,, "Maximum number of iterations"
38 36  
... ...
test/test_cscripts.sh.in
  View file @4dc88fd
... ... @@ -42,6 +42,7 @@ rm -rf *.fits *.xml *.dat
42 42 #
43 43 # Creates pfiles directory
44 44 # ========================
  45 +rm -rf pfiles
45 46 mkdir -p pfiles
46 47 export PFILES=pfiles
47 48  
... ... @@ -316,3 +317,5 @@ else
316 317 exit 1
317 318 fi
318 319 $ECHO " ok"
  320 +
  321 +ls -la pfiles
... ...
test/test_ctools.sh
  View file @4dc88fd
... ... @@ -47,6 +47,7 @@ ctbkgcube=../src/ctbkgcube/ctbkgcube
47 47 ctcubemask=../src/ctcubemask/ctcubemask
48 48 ctbutterfly=../src/ctbutterfly/ctbutterfly
49 49 ctulimit=../src/ctulimit/ctulimit
  50 +cterror=../src/cterror/cterror
50 51  
51 52  
52 53 #
... ... @@ -61,7 +62,7 @@ rm -rf ulimit.dat butterfly.txt
61 62 # ========================
62 63 rm -rf pfiles
63 64 mkdir -p pfiles
64   -cp -r ../src/*/*.par pfiles/
  65 +#cp -r ../src/*/*.par pfiles/
65 66 export PFILES=pfiles
66 67  
67 68  
... ... @@ -595,3 +596,24 @@ else
595 596 fi
596 597 $ECHO " ok"
597 598  
  599 +
  600 +#
  601 +# Test cterror
  602 +# ============
  603 +$ECHO -n "Test cterror: "
  604 +$cterror inobs="data/crab_events.fits.gz" \
  605 + inmodel="data/crab.xml" \
  606 + outmodel="results_error.xml" \
  607 + srcname="Crab" \
  608 + caldb="irf" \
  609 + irf="cta_dummy_irf"
  610 +$ECHO -n "."
  611 +if [ -s "cterror.log" ]
  612 +then
  613 + $ECHO -n "."
  614 +else
  615 + $ECHO " cterror.log file is not found"
  616 + exit 1
  617 +fi
  618 +$ECHO " ok"
  619 +
... ...
test/test_python.py
  View file @4dc88fd
... ... @@ -2,7 +2,7 @@
2 2 # ==========================================================================
3 3 # This scripts performs unit tests for the ctools package.
4 4 #
5   -# Copyright (C) 2012-2014 Juergen Knoedlseder
  5 +# Copyright (C) 2012-2015 Juergen Knoedlseder
6 6 #
7 7 # This program is free software: you can redistribute it and/or modify
8 8 # it under the terms of the GNU General Public License as published by
... ... @@ -35,6 +35,7 @@ import test_ctbkgcube
35 35 import test_ctcubemask
36 36 import test_ctbutterfly
37 37 import test_ctulimit
  38 +import test_cterror
38 39 import test_pipelines
39 40  
40 41  
... ... @@ -62,6 +63,7 @@ if __name__ == &#39;__main__&#39;:
62 63 suite_ctcubemask = test_ctcubemask.Test()
63 64 suite_ctbutterfly = test_ctbutterfly.Test()
64 65 suite_ctulimit = test_ctulimit.Test()
  66 + suite_cterror = test_cterror.Test()
65 67 suite_pipelines = test_pipelines.Test()
66 68  
67 69 # Setup unit tests
... ... @@ -78,6 +80,7 @@ if __name__ == &#39;__main__&#39;:
78 80 suite_ctcubemask.set()
79 81 suite_ctbutterfly.set()
80 82 suite_ctulimit.set()
  83 + suite_cterror.set()
81 84 suite_pipelines.set()
82 85  
83 86 # Append tests to container
... ... @@ -94,6 +97,7 @@ if __name__ == &#39;__main__&#39;:
94 97 suites.append(suite_ctcubemask)
95 98 suites.append(suite_ctbutterfly)
96 99 suites.append(suite_ctulimit)
  100 + suites.append(suite_cterror)
97 101 suites.append(suite_pipelines)
98 102  
99 103 # Set PFILES environment variable
... ...