Commit d774f1a08d403756bc8e8c118213703babafa5ca
Merge branch 'integration' into devel
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pyext/ctools/__init__.py
| ... | ... | @@ -3,9 +3,6 @@ import gammalib |
| 3 | 3 | |
| 4 | 4 | # Import sub modules |
| 5 | 5 | from .tools import * |
| 6 | -#import obsutils (require explicit from ctools import obsutils) | |
| 7 | -#import analysisutils (require explicit from ctools import obsutils) | |
| 8 | -#import plotutils (require explicit from ctools import obsutils) | |
| 9 | 6 | |
| 10 | 7 | # Remove swig register stuff |
| 11 | 8 | bad_entries = [entry for entry in list(locals()) | ... | ... |
pyext/ctools/analysisutils.py deleted
| 1 | -# ========================================================================== | |
| 2 | -# This script provides a number of functions that are useful for CTA data | |
| 3 | -# analysis. | |
| 4 | -# | |
| 5 | -# Copyright (C) 2014 David Sanchez | |
| 6 | -# | |
| 7 | -# This program is free software: you can redistribute it and/or modify | |
| 8 | -# it under the terms of the GNU General Public License as published by | |
| 9 | -# the Free Software Foundation, either version 3 of the License, or | |
| 10 | -# (at your option) any later version. | |
| 11 | -# | |
| 12 | -# This program is distributed in the hope that it will be useful, | |
| 13 | -# but WITHOUT ANY WARRANTY; without even the implied warranty of | |
| 14 | -# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the | |
| 15 | -# GNU General Public License for more details. | |
| 16 | -# | |
| 17 | -# You should have received a copy of the GNU General Public License | |
| 18 | -# along with this program. If not, see <http://www.gnu.org/licenses/>. | |
| 19 | -# | |
| 20 | -# ========================================================================== | |
| 21 | -import ctools as ct | |
| 22 | -import gammalib as gl | |
| 23 | -from math import sqrt,log10,floor | |
| 24 | -import sys | |
| 25 | - | |
| 26 | -class base(object): | |
| 27 | - def __init__(self): | |
| 28 | - self.classname = self.__class__.__name__ | |
| 29 | - self.errorcolor = "\033[31m"#red | |
| 30 | - self.infocolor = "\033[34m"#blue | |
| 31 | - self.warningcolor = "\033[33m"#yellow | |
| 32 | - self.successcolor = "\033[32m"#green | |
| 33 | - self.endcolor = "\033[0m"#reset | |
| 34 | - self.prependfunction = True | |
| 35 | - self.basemembers = ["classname","errorcolor","infocolor","warningcolor","successcolor","endcolor","prependfunction"] | |
| 36 | - | |
| 37 | - def error(self,message, functionname = ""): | |
| 38 | - printstring = "" | |
| 39 | - if functionname == "": | |
| 40 | - printstring = "\n"+self.errorcolor+"*** Error ["+self.classname+"]: "+message+" ***\n"+self.endcolor | |
| 41 | - else: | |
| 42 | - printstring = "\n"+self.errorcolor+"*** Error ["+self.classname+"::"+functionname+"]: "+message+" ***\n"+self.endcolor | |
| 43 | - sys.exit(printstring) | |
| 44 | - | |
| 45 | - def info(self,message,newline=True): | |
| 46 | - printstring = self.infocolor+"["+self.classname+"]: "+message+self.endcolor | |
| 47 | - if newline: | |
| 48 | - print(printstring) | |
| 49 | - else: | |
| 50 | - print(self.infocolor+message+self.endcolor) | |
| 51 | - sys.stdout.flush() | |
| 52 | - | |
| 53 | - def warning(self,message,functionname = ""): | |
| 54 | - printstring = "" | |
| 55 | - if functionname == "": | |
| 56 | - printstring = self.warningcolor+"["+self.classname+"] Warning: "+message+self.endcolor | |
| 57 | - else: | |
| 58 | - printstring = self.warningcolor+"["+self.classname+"::"+functionname+"] Warning: "+message+self.endcolor | |
| 59 | - print(printstring) | |
| 60 | - | |
| 61 | - def success(self,message): | |
| 62 | - printstring = self.successcolor+"["+self.classname+"]: "+message+self.endcolor | |
| 63 | - print(printstring) | |
| 64 | - | |
| 65 | - def progress(self,message="."): | |
| 66 | - string = self.infocolor+message+self.endcolor | |
| 67 | - print(string) | |
| 68 | - | |
| 69 | - | |
| 70 | -class ResultsSorage(dict,base): | |
| 71 | - """class to store the results in the good format""" | |
| 72 | - def __init__(self,*arg,**kw): | |
| 73 | - super(ResultsSorage, self).__init__(*arg, **kw) | |
| 74 | - base.__init__(self) | |
| 75 | - self["dnde"] = {} | |
| 76 | - self["ulim_dnde"] = [] | |
| 77 | - self["time"] = {} | |
| 78 | - self["ener"] = {} | |
| 79 | - self["TS"] = [] | |
| 80 | - self["Iflux"] = {} | |
| 81 | - | |
| 82 | - self["time"]["tmin_value"] = [] | |
| 83 | - self["time"]["tmax_value"] = [] | |
| 84 | - self["time"]["unit"] = "sec" | |
| 85 | - | |
| 86 | - self["ener"]["value"] = [] | |
| 87 | - self["ener"]["ed_value"] = [] | |
| 88 | - self["ener"]["eu_value"] = [] | |
| 89 | - self["ener"]["unit"] = "MeV" | |
| 90 | - | |
| 91 | - self["dnde"]["value"] = [] | |
| 92 | - self["dnde"]["ed_value"] = [] | |
| 93 | - self["dnde"]["eu_value"] = [] | |
| 94 | - self["dnde"]["unit"] = "ph/cm2/s/MeV" | |
| 95 | - | |
| 96 | - self["Iflux"]["value"] = [] | |
| 97 | - self["Iflux"]["ed_value"] = [] | |
| 98 | - self["Iflux"]["eu_value"] = [] | |
| 99 | - self["Iflux"]["unit"] = "ph/cm2/s" | |
| 100 | - | |
| 101 | - def Print(self): | |
| 102 | - self.success("Results are :") | |
| 103 | - for k in self.iterkeys(): | |
| 104 | - self.info("Key name : "+k) | |
| 105 | - try : | |
| 106 | - for ki in self[k].iterkeys(): | |
| 107 | - print("\t",ki,"\t",self[k][ki]) | |
| 108 | - except: | |
| 109 | - print(self[k]) | |
| 110 | - print() | |
| 111 | - | |
| 112 | -class Analyser(base): | |
| 113 | - def __init__(self): | |
| 114 | - super(Analyser,self).__init__() | |
| 115 | - self.info("Creating "+self.classname+" object") | |
| 116 | - self.m_obs = None | |
| 117 | - self.like = None | |
| 118 | - | |
| 119 | - self.m_ebinalg = "LOG" | |
| 120 | - self.m_eunit = "TeV" | |
| 121 | - self.m_enumbins = 10#nbins | |
| 122 | - self.m_usepnt = True # Use pointing for map centre | |
| 123 | - self.m_coordsys = "CEL"#coord | |
| 124 | - self.m_proj = "TAN"#proj | |
| 125 | - self.m_binned = False | |
| 126 | - self.m_edisp = False | |
| 127 | - self.m_stat = "POISSON"#stat | |
| 128 | - | |
| 129 | - self.m_source_set = False | |
| 130 | - self.m_files_set = False | |
| 131 | - self.m_time_set = False | |
| 132 | - self.m_energy_set = False | |
| 133 | - self.m_irfs_set = False | |
| 134 | - self.m_roi_set = False | |
| 135 | - self.m_xml_set = False | |
| 136 | - | |
| 137 | - def set_xml(self,xml): | |
| 138 | - self.m_xml = xml | |
| 139 | - ind = xml.find(".xml") | |
| 140 | - if not ind==-1: | |
| 141 | - self.m_xml_out = xml[:xml.find(".xml")]+"_results"+xml[xml.find(".xml"):] | |
| 142 | - self.m_xml_set = True | |
| 143 | - | |
| 144 | - def set_roi(self,roi): | |
| 145 | - self.m_roi = float(roi) | |
| 146 | - self.m_nxpix = int(self.m_roi*100) #nxpix | |
| 147 | - self.m_nypix = int(self.m_roi*100) #nypix | |
| 148 | - self.m_binsz = 0.05 #binsz | |
| 149 | - self.m_roi_set = True | |
| 150 | - | |
| 151 | - def set_irfs(self,caldb,irf): | |
| 152 | - self.m_caldb = caldb | |
| 153 | - self.m_irf = irf | |
| 154 | - self.m_irfs_set = True | |
| 155 | - | |
| 156 | - def set_Fitsfiles(self,evtfile,tag="CTA_analysis"): | |
| 157 | - self.m_evtfile = "event_selected_"+tag+".fits" | |
| 158 | - self.m_raw_evt = evtfile | |
| 159 | - self.m_cntfile = "countmap_"+tag+".fits" | |
| 160 | - self.m_files_set = True | |
| 161 | - | |
| 162 | - def set_source(self,name,ra,dec): | |
| 163 | - self.m_ra = ra | |
| 164 | - self.m_dec = dec | |
| 165 | - self.m_name = name | |
| 166 | - self.m_source_set = True | |
| 167 | - | |
| 168 | - def validate(self): | |
| 169 | - if not self.m_time_set : | |
| 170 | - self.error("Time range of the observations not set") | |
| 171 | - | |
| 172 | - if not self.m_files_set : | |
| 173 | - self.error("FITS files of the observations not set") | |
| 174 | - | |
| 175 | - if not self.m_source_set : | |
| 176 | - self.error("Source not set") | |
| 177 | - | |
| 178 | - if not self.m_energy_set : | |
| 179 | - self.error("Energy range of the observations not set") | |
| 180 | - | |
| 181 | - if not self.m_irfs_set : | |
| 182 | - self.error("IRFs to use not set") | |
| 183 | - | |
| 184 | - if not self.m_roi_set : | |
| 185 | - self.error("ROI to use not set") | |
| 186 | - | |
| 187 | - if not self.m_xml_set : | |
| 188 | - self.error("XML files for the sky model not set") | |
| 189 | - | |
| 190 | - def copy(self,analyse,tag="CTA_analysis_copy"): | |
| 191 | - self.set_xml(analyse.m_xml) | |
| 192 | - self.set_irfs(analyse.m_caldb,analyse.m_irf) | |
| 193 | - self.set_roi(analyse.m_roi) | |
| 194 | - self.set_time_boundary(analyse.m_tmin,analyse.m_tmax) | |
| 195 | - self.set_energy_boundary(analyse.m_emin,analyse.m_emax) | |
| 196 | - self.set_source(analyse.m_name,analyse.m_ra,analyse.m_dec) | |
| 197 | - self.set_Fitsfiles(analyse.m_evtfile,tag) | |
| 198 | - | |
| 199 | - | |
| 200 | - def set_obs(self,obs): | |
| 201 | - self.m_obs = obs #set the GObservation container | |
| 202 | - | |
| 203 | - def set_time_boundary(self,tmin,tmax): | |
| 204 | - """Set the start and stop time of the observation""" | |
| 205 | - self.m_tmin = float(tmin) | |
| 206 | - self.m_tmax = float(tmax) | |
| 207 | - self.m_time_set = True | |
| 208 | - | |
| 209 | - def set_energy_boundary(self,emin,emax): | |
| 210 | - """Set the energy bounds of the observation""" | |
| 211 | - self.m_emin = emin | |
| 212 | - self.m_emax = emax | |
| 213 | - ebounds = gl.GEbounds(gl.GEnergy(emin, self.m_eunit), \ | |
| 214 | - gl.GEnergy(emax, self.m_eunit)) | |
| 215 | - | |
| 216 | - if self.m_obs: | |
| 217 | - for obs in self.m_obs: | |
| 218 | - obs.events().ebounds(ebounds) | |
| 219 | - self.m_energy_set = True | |
| 220 | - | |
| 221 | - def ctselect(self): | |
| 222 | - # ctselect application and set parameters | |
| 223 | - self.info("Running ctselect to cut on events") | |
| 224 | - self.validate() | |
| 225 | - if self.m_obs: | |
| 226 | - filter = ct.ctselect(self.m_obs) | |
| 227 | - else: | |
| 228 | - filter = ct.ctselect() | |
| 229 | - | |
| 230 | - filter["infile"] = self.m_raw_evt | |
| 231 | - filter["outfile"] = self.m_evtfile | |
| 232 | - filter["usepnt"].boolean(self.m_usepnt) # Use pointing for map centre | |
| 233 | - filter["ra"] = self.m_ra | |
| 234 | - filter["dec"] = self.m_dec | |
| 235 | - filter["rad"] = self.m_roi | |
| 236 | - filter["tmin"] = self.m_tmin | |
| 237 | - filter["tmax"] = self.m_tmax | |
| 238 | - filter["emin"].real(self.m_emin) | |
| 239 | - filter["emax"].real(self.m_emax) | |
| 240 | - filter["expr"] = "" | |
| 241 | - filter.logFileOpen() | |
| 242 | - | |
| 243 | - filter.run() | |
| 244 | - if not(self.m_obs): | |
| 245 | - filter.save() | |
| 246 | - | |
| 247 | - if self.m_obs: | |
| 248 | - # Make a deep copy of the observation that will be returned | |
| 249 | - # (the ctbin object will go out of scope one the function is | |
| 250 | - # left) | |
| 251 | - self.m_obs = filter.obs().copy() | |
| 252 | - | |
| 253 | - def ctbin(self,log=False,debug=False): | |
| 254 | - # ctbin application and set parameters | |
| 255 | - self.validate() | |
| 256 | - self.info("Running ctbin to create count map") | |
| 257 | - if self.m_obs: | |
| 258 | - bin = ct.ctbin(self.m_obs) | |
| 259 | - else: | |
| 260 | - bin = ct.ctbin() | |
| 261 | - bin["evfile"] = self.m_evtfile | |
| 262 | - bin["outfile"] = self.m_cntfile | |
| 263 | - bin["ebinalg"] = self.m_ebinalg | |
| 264 | - bin["emin"] = self.m_emin | |
| 265 | - bin["emax"] = self.m_emax | |
| 266 | - Nbdecade = log10(self.m_emax)-log10(self.m_emin)#Compute the number of decade | |
| 267 | - bin["enumbins"] = int(self.m_enumbins*Nbdecade) | |
| 268 | - bin["usepnt"] = self.m_usepnt # Use pointing for map centre | |
| 269 | - bin["nxpix"] = self.m_nxpix | |
| 270 | - bin["nypix"] = self.m_nypix | |
| 271 | - bin["binsz"] = self.m_binsz | |
| 272 | - bin["coordsys"] = self.m_coordsys | |
| 273 | - bin["proj"] = self.m_proj | |
| 274 | - | |
| 275 | - # Optionally open the log file | |
| 276 | - if log: | |
| 277 | - bin.logFileOpen() | |
| 278 | - | |
| 279 | - # Optionally switch-on debugging model | |
| 280 | - if debug: | |
| 281 | - bin["debug"] = True | |
| 282 | - | |
| 283 | - # Run ctbin application. This will loop over all observations in | |
| 284 | - # the container and bin the events in counts maps | |
| 285 | - bin.execute() | |
| 286 | - if self.m_obs: | |
| 287 | - # Make a deep copy of the observation that will be returned | |
| 288 | - # (the ctbin object will go out of scope one the function is | |
| 289 | - # left) | |
| 290 | - self.m_obs = bin.obs().copy() | |
| 291 | - | |
| 292 | - def create_fit(self,log=False,debug=False): | |
| 293 | - self.validate() | |
| 294 | - # create ctlike instance with given parameters | |
| 295 | - self.info("Fitting Data using ctlike") | |
| 296 | - if self.m_obs: | |
| 297 | - self.like = ct.ctlike(self.m_obs) | |
| 298 | - else: | |
| 299 | - self.like = ct.ctlike() | |
| 300 | - if self.m_binned: | |
| 301 | - self.like["infile"] = self.m_cntfile | |
| 302 | - else: | |
| 303 | - self.like["infile"] = self.m_evtfile | |
| 304 | - | |
| 305 | - self.like["stat"] = self.m_stat | |
| 306 | - self.like["caldb"] = self.m_caldb | |
| 307 | - self.like["irf"] = self.m_irf | |
| 308 | - self.like["srcmdl"] = self.m_xml | |
| 309 | - self.like["edisp"] = self.m_edisp | |
| 310 | - self.like["outmdl"] = self.m_xml_out | |
| 311 | - | |
| 312 | - # Optionally open the log file | |
| 313 | - if log: | |
| 314 | - self.like.logFileOpen() | |
| 315 | - # Optionally switch-on debugging model | |
| 316 | - if debug: | |
| 317 | - self.like["debug"] = True | |
| 318 | - | |
| 319 | - def fit(self,log=False,debug=False): | |
| 320 | - self.validate() | |
| 321 | - if not(self.like): | |
| 322 | - self.warning("ctlike object not created, creating now") | |
| 323 | - self.create_fit(log,debug) | |
| 324 | - | |
| 325 | - # Run ctlike application. | |
| 326 | - self.like.run() | |
| 327 | - # Save the results in XML | |
| 328 | - self.like.save() | |
| 329 | - self.success("Fit performed") | |
| 330 | - | |
| 331 | - def PrintResults(self,srcname = ""): | |
| 332 | - self.info("Results of the Fit") | |
| 333 | - for m in self.like.obs().models(): | |
| 334 | - if srcname == m.name() or srcname=="": | |
| 335 | - print("Model : "+m.name()) | |
| 336 | - print(m) | |
| 337 | - | |
| 338 | - def GetSrcResuls(self,Res,srcname,E0=None,factor = 1e6,tmin=None,tmax=None): | |
| 339 | - """function to get and store the results of a fit""" | |
| 340 | - results = self.GetSrcParams(srcname) | |
| 341 | - | |
| 342 | - if 1: | |
| 343 | - # #Time | |
| 344 | - # if (tmin is not None) or (tmax is not None) : | |
| 345 | - # Res["time"]["tmin_value"].append(tmin) | |
| 346 | - # Res["time"]["tmax_value"].append(tmax) | |
| 347 | - # Res["time"]["unit"] = "sec" | |
| 348 | - # else: | |
| 349 | - Res["time"]["tmin_value"].append(self.m_tmin) | |
| 350 | - Res["time"]["tmax_value"].append(self.m_tmax) | |
| 351 | - Res["time"]["unit"] = "sec" | |
| 352 | - | |
| 353 | - #Energy | |
| 354 | - if (E0 is not None): | |
| 355 | - Res["ener"]["value"].append(E0*factor) | |
| 356 | - Res["ener"]["ed_value"].append((E0-self.m_emin)*factor) | |
| 357 | - Res["ener"]["eu_value"].append((self.m_emax-E0)*factor) | |
| 358 | - Res["ener"]["unit"] = "MeV" | |
| 359 | - else: | |
| 360 | - Res["ener"]["value"].append(sqrt(self.m_emin*self.m_emax)) | |
| 361 | - Res["ener"]["ed_value"].append(-self.m_emin+sqrt(self.m_emin*self.m_emax)) | |
| 362 | - Res["ener"]["eu_value"].append(self.m_emax-sqrt(self.m_emin*self.m_emax)) | |
| 363 | - Res["ener"]["unit"] = self.m_eunit | |
| 364 | - | |
| 365 | - Res["Iflux"]["value"].append(results["flux"]) | |
| 366 | - Res["Iflux"]["eu_value"].append(results["eflux"]) | |
| 367 | - Res["Iflux"]["ed_value"].append(results["eflux"]) | |
| 368 | - # Res["Iflux"]["unit"] = "unit" | |
| 369 | - | |
| 370 | - m = self.GetModel(srcname) | |
| 371 | - Res["dnde"]["value"].append(m.spectral()[0].value()) | |
| 372 | - Res["dnde"]["eu_value"].append(m.spectral()[0].error()) | |
| 373 | - Res["dnde"]["ed_value"].append(m.spectral()[0].error()) | |
| 374 | - | |
| 375 | - Res["TS"].append(100) | |
| 376 | - | |
| 377 | - UL = UpperLimitComputer(self,srcname) | |
| 378 | - UL.run() | |
| 379 | - Res["ulim_dnde"].append(0) | |
| 380 | - # del UL | |
| 381 | - return Res | |
| 382 | - | |
| 383 | - def GetSrcParams(self,srcname): | |
| 384 | - results = {} | |
| 385 | - found = False | |
| 386 | - m = self.GetModel(srcname) | |
| 387 | - results["flux"] = m.spectral().flux(gl.GEnergy(self.m_emin,self.m_eunit),gl.GEnergy(self.m_emax,self.m_eunit)) | |
| 388 | - results["eflux"] = m.spectral().eflux(gl.GEnergy(self.m_emin,self.m_eunit),gl.GEnergy(self.m_emax,self.m_eunit)) | |
| 389 | - for par in m.spectral(): | |
| 390 | - if par.is_free(): | |
| 391 | - results[par.name()] = par.value() | |
| 392 | - results["e"+par.name()] = par.error() | |
| 393 | - | |
| 394 | - return results | |
| 395 | - | |
| 396 | - def GetModel(self,srcname): | |
| 397 | - found = False | |
| 398 | - for m in self.like.obs().models(): | |
| 399 | - if m.name() == srcname: | |
| 400 | - return m | |
| 401 | - self.error("source "+srcname+" not in the source list") | |
| 402 | - | |
| 403 | - | |
| 404 | -def MakeEbin(analyse,nbins,srcname,binned = False): | |
| 405 | - #Store the results | |
| 406 | - Res = ResultsSorage() | |
| 407 | - | |
| 408 | - #check the source name, exit is the srcname is false | |
| 409 | - analyse.GetModel(srcname) | |
| 410 | - | |
| 411 | - #compute the conversion factor to have energy in MeV | |
| 412 | - Energy_list = {"MeV":1,"GeV":1e3,"TeV":1e6} #TODO | |
| 413 | - factor = Energy_list[analyse.m_eunit] | |
| 414 | - | |
| 415 | - for i in xrange(nbins): | |
| 416 | - obs_copy = analyse.like.obs().copy() | |
| 417 | - emin = pow(10,log10(analyse.m_emin) + (log10(analyse.m_emax)-log10(analyse.m_emin))/(nbins)*i) | |
| 418 | - emax = pow(10,log10(analyse.m_emin) + (log10(analyse.m_emax)-log10(analyse.m_emin))/(nbins)*(i+1)) | |
| 419 | - E0 = pow(10, (log10(emin) + log10(emax)) / 2) | |
| 420 | - print("Making energy bin between %2.1e"%(emin)+analyse.m_eunit+" and %2.1e"%(emax)+analyse.m_eunit) | |
| 421 | - | |
| 422 | - # change the PivotEnergy to E0 | |
| 423 | - m = obs_copy.models()[srcname] | |
| 424 | - for par in m.spectral(): | |
| 425 | - if par.name() == "PivotEnergy": | |
| 426 | - par.value(E0*factor) | |
| 427 | - | |
| 428 | - ana_bin = Analyser() | |
| 429 | - | |
| 430 | - #copy the obs object | |
| 431 | - ana_bin.set_obs(obs_copy) | |
| 432 | - | |
| 433 | - #copy the analyser parameters | |
| 434 | - ana_bin.copy(analyse) | |
| 435 | - | |
| 436 | - # Set energy boundaries | |
| 437 | - ana_bin.set_energy_boundary(emin,emax) | |
| 438 | - ana_bin.ctselect() | |
| 439 | - | |
| 440 | - # if binned: | |
| 441 | - # ana_bin.ctbin() | |
| 442 | - | |
| 443 | - # Create the fit object | |
| 444 | - ana_bin.create_fit(log=False,debug=False) | |
| 445 | - | |
| 446 | - # Run ctlike application. | |
| 447 | - ana_bin.like.run() | |
| 448 | - | |
| 449 | - #Retrive the results in the good format | |
| 450 | - Res = ana_bin.GetSrcResuls(Res,srcname,E0,factor) | |
| 451 | - | |
| 452 | - del ana_bin | |
| 453 | - return Res | |
| 454 | - | |
| 455 | -def MakeLC(analyse,nbins,srcname,binned = False): | |
| 456 | - #Store the results | |
| 457 | - Res = ResultsSorage() | |
| 458 | - | |
| 459 | - #check the source name, exit is the srcname is false | |
| 460 | - analyse.GetModel(srcname) | |
| 461 | - | |
| 462 | - for i in xrange(nbins): | |
| 463 | - obs_copy = analyse.like.obs().copy() | |
| 464 | - tmin = analyse.m_tmin + (analyse.m_tmax-analyse.m_tmin)/(nbins)*i | |
| 465 | - tmax = analyse.m_tmin + (analyse.m_tmax-analyse.m_tmin)/(nbins)*(i+1) | |
| 466 | - print("Making time bin between %2.1e"%(tmin)+" and %2.1e"%(tmax)) | |
| 467 | - | |
| 468 | - ana_bin = Analyser() | |
| 469 | - | |
| 470 | - #copy the obs object | |
| 471 | - ana_bin.set_obs(obs_copy) | |
| 472 | - | |
| 473 | - #copy the analyser parameters | |
| 474 | - ana_bin.copy(analyse) | |
| 475 | - | |
| 476 | - # Set energy boundaries | |
| 477 | - ana_bin.set_time_boundary(tmin,tmax) | |
| 478 | - ana_bin.ctselect() | |
| 479 | - | |
| 480 | - # if binned: | |
| 481 | - # ana_bin.ctbin() | |
| 482 | - | |
| 483 | - # Create the fit object | |
| 484 | - ana_bin.create_fit(log=False,debug=False) | |
| 485 | - | |
| 486 | - # Run ctlike application. | |
| 487 | - ana_bin.like.run() | |
| 488 | - | |
| 489 | - #Retrive the results in the good format | |
| 490 | - Res = ana_bin.GetSrcResuls(Res,srcname,tmin=tmin,tmax=tmax) | |
| 491 | - | |
| 492 | - del ana_bin | |
| 493 | - return Res | |
| 494 | - | |
| 495 | -class UpperLimitComputer(base): | |
| 496 | - def __init__(self,analyser,srcname,parname = "Prefactor"): | |
| 497 | - super(UpperLimitComputer,self).__init__() | |
| 498 | - self.info("Creating "+self.classname+" object") | |
| 499 | - # self.like = analyser.like.copy() | |
| 500 | - obs = analyser.like.obs().copy() | |
| 501 | - self.like = ct.ctlike(obs) | |
| 502 | - self.succes = False | |
| 503 | - | |
| 504 | - # get spectral model | |
| 505 | - self.model = self.like.obs().models()[srcname] | |
| 506 | - self.spec = self.model.spectral() | |
| 507 | - self.parname = parname | |
| 508 | - self.bestloglike = analyser.like.opt().value() | |
| 509 | - self.dloglike = 3.84/2.0 #95% CL now | |
| 510 | - | |
| 511 | - def _bisec(self,a,b,tol = 1e-12): | |
| 512 | - """iterative function to find the roots""" | |
| 513 | - if (self._func(a)==0.): | |
| 514 | - return a | |
| 515 | - elif (self._func(b)==0): | |
| 516 | - return b | |
| 517 | - elif (self._func(b)*self._func(a)>0.): | |
| 518 | - self.warning("Finding root for upper limit calculation failed") | |
| 519 | - return 0 | |
| 520 | - mid = (a+b)/2 | |
| 521 | - err = abs(a-b)/2 | |
| 522 | - fm = self._func(mid) | |
| 523 | - if (err<tol or self._func(mid)==0.): | |
| 524 | - self.succes = True | |
| 525 | - return mid | |
| 526 | - elif (fm*self._func(a)<0): | |
| 527 | - b = mid | |
| 528 | - else : | |
| 529 | - a = mid | |
| 530 | - return self._bisec(a,b) | |
| 531 | - | |
| 532 | - def _func(self,value): | |
| 533 | - """function to be minimized""" | |
| 534 | - # get parmeter value | |
| 535 | - val = value*self.spec[self.parname].scale() | |
| 536 | - | |
| 537 | - # ensure value to be above minimum boundary | |
| 538 | - if val <= self.spec[self.parname].min(): | |
| 539 | - return 0.0-self.self.bestloglike-self.dloglike | |
| 540 | - | |
| 541 | - # set value | |
| 542 | - self.spec[self.parname].value(val) | |
| 543 | - | |
| 544 | - # Recalculate likelihood | |
| 545 | - self.like.run() | |
| 546 | - logl = self.like.opt().value() | |
| 547 | - | |
| 548 | - # Return likelihood difference | |
| 549 | - return (logl-self.bestloglike-self.dloglike) | |
| 550 | - | |
| 551 | - def run(self): | |
| 552 | - | |
| 553 | - # get spectral parameters and set start value | |
| 554 | - value = self.spec[self.parname].value() | |
| 555 | - error = self.spec[self.parname].error() | |
| 556 | - scale = self.spec[self.parname].scale() | |
| 557 | - | |
| 558 | - #Fix all parameters | |
| 559 | - for model in self.like.obs().models(): | |
| 560 | - for par in model: | |
| 561 | - par.fix() | |
| 562 | - | |
| 563 | - | |
| 564 | - # set start value to 2 sigma above fit value | |
| 565 | - self.startpar = value / scale + 2* error/scale | |
| 566 | - | |
| 567 | - # set start (a) and (b) depend on the CL asked | |
| 568 | - a= value / scale + (self.dloglike/4.)*error/scale | |
| 569 | - b=value / scale + (self.dloglike*2)* error/scale | |
| 570 | - ul = self._bisec(a,b) | |
| 571 | - | |
| 572 | - self.ulimit = ul*self.spec[self.parname].scale() | |
| 573 | - # Test for convergence | |
| 574 | - if self.succes: | |
| 575 | - self.success("Upper limit of parameter \""+self.parname +"\" determined to "+str(self.ulimit)) |
pyext/ctools/plotutils.py deleted
| 1 | -# ========================================================================== | |
| 2 | -# This script provides a number of functions that are useful for plotting. | |
| 3 | -# | |
| 4 | -# Copyright (C) 2014 David Sanchez | |
| 5 | -# | |
| 6 | -# This program is free software: you can redistribute it and/or modify | |
| 7 | -# it under the terms of the GNU General Public License as published by | |
| 8 | -# the Free Software Foundation, either version 3 of the License, or | |
| 9 | -# (at your option) any later version. | |
| 10 | -# | |
| 11 | -# This program is distributed in the hope that it will be useful, | |
| 12 | -# but WITHOUT ANY WARRANTY; without even the implied warranty of | |
| 13 | -# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the | |
| 14 | -# GNU General Public License for more details. | |
| 15 | -# | |
| 16 | -# You should have received a copy of the GNU General Public License | |
| 17 | -# along with this program. If not, see <http://www.gnu.org/licenses/>. | |
| 18 | -# | |
| 19 | -# ========================================================================== | |
| 20 | -import ctools as ct | |
| 21 | -import gammalib as gl | |
| 22 | -from math import log10,pow,sqrt | |
| 23 | -import os | |
| 24 | - | |
| 25 | -try: | |
| 26 | - import matplotlib.pyplot as plt | |
| 27 | - import matplotlib.gridspec as gridspec | |
| 28 | - has_matplotlib = True | |
| 29 | -except: | |
| 30 | - has_matplotlib = False | |
| 31 | - | |
| 32 | -try: | |
| 33 | - import aplpy | |
| 34 | - has_aplpy = True | |
| 35 | -except: | |
| 36 | - has_aplpy = False | |
| 37 | - | |
| 38 | -class options(object): | |
| 39 | - def __init__(self): | |
| 40 | - self.fmt = 'o' | |
| 41 | - self.color = BLUE | |
| 42 | - self.linecolor = 'black' | |
| 43 | - self.markercolor = self.color | |
| 44 | - self.tslim = 4.0 | |
| 45 | - self.elinewidth = 2.0 | |
| 46 | - self.linewidth = 2.0 | |
| 47 | - self.linestyle = '--' | |
| 48 | - self.capsize = 5.0 | |
| 49 | - self.markersize = 5.0 | |
| 50 | - self.limlength = 0.4 | |
| 51 | - self.label = "_nolegend_" | |
| 52 | - | |
| 53 | -import analysisutils | |
| 54 | - | |
| 55 | -class SpectralBase(object): | |
| 56 | - def __init__(self,sed=True,sed_factor=1.): | |
| 57 | - self.m_sed_factor = sed_factor | |
| 58 | - self.m_sed = sed | |
| 59 | - | |
| 60 | - def _convertSED(self,tab,energy): | |
| 61 | - """convert the a table storing dN/dE in sed with right units""" | |
| 62 | - | |
| 63 | - if len(tab) != len(energy): | |
| 64 | - self.error("input table and energy table does not match") | |
| 65 | - return | |
| 66 | - if self.m_sed: | |
| 67 | - for i in xrange(len(tab)): | |
| 68 | - tab[i] *= energy[i]**2*self.m_sed_factor | |
| 69 | - return tab | |
| 70 | - | |
| 71 | -BLUE="#337EF5" | |
| 72 | -GREY='grey' | |
| 73 | -GREEN = '#21851D' | |
| 74 | -RED = '#BD0B0B' | |
| 75 | -YELLOW = '#D4CF44' | |
| 76 | -ORANGE = '#D19534' | |
| 77 | - | |
| 78 | - | |
| 79 | -class residuals(analysisutils.base,options,SpectralBase): | |
| 80 | - def __init__(self,spectrum,datapoint,sed,sed_factor,eunit="TeV"): | |
| 81 | - super(residuals,self).__init__() | |
| 82 | - options.__init__(self) | |
| 83 | - SpectralBase.__init__(self,sed,sed_factor) | |
| 84 | - | |
| 85 | - # load the gammalib spectrum object | |
| 86 | - self.spectrum = spectrum | |
| 87 | - self.SetDataPoint(datapoint) | |
| 88 | - | |
| 89 | - self.xerrors = True | |
| 90 | - self.refUnit = eunit # reference unit for conversion | |
| 91 | - | |
| 92 | - def SetDataPoint(self,datapoint): | |
| 93 | - self.m_point_info = datapoint | |
| 94 | - self.Npt = len(self.m_point_info["dnde"]["value"]) | |
| 95 | - | |
| 96 | - def _plt_residuals(self): | |
| 97 | - th_val = [] | |
| 98 | - index = [] | |
| 99 | - ed_y = [] | |
| 100 | - eu_y = [] | |
| 101 | - y = [] | |
| 102 | - | |
| 103 | - Energy_list = {"MeV":1,"GeV":1e-3,"TeV":1e-6} #TODO | |
| 104 | - for i in range(self.Npt): | |
| 105 | - if self.m_point_info["TS"][i] >= self.tslim: | |
| 106 | - th_val.append(self.spectrum.eval(gl.GEnergy(self.m_point_info["ener"]["value"][i],self.m_point_info["ener"]["unit"]),gl.GTime(0))) | |
| 107 | - index.append(i) | |
| 108 | - else: | |
| 109 | - th_val.append(0) | |
| 110 | - if self.m_sed: | |
| 111 | - self._convertSED(th_val,self.m_point_info["ener"]) | |
| 112 | - for i in index: | |
| 113 | - y.append((self.m_point_info["dnde"]["value"][i] - th_val[i]) / th_val[i]) | |
| 114 | - ed_y.append(self.m_point_info["dnde"]["ed_value"][i]/th_val[i]) | |
| 115 | - eu_y.append(self.m_point_info["dnde"]["eu_value"][i]/th_val[i]) | |
| 116 | - | |
| 117 | - if self.xerrors: | |
| 118 | - plt.errorbar(self.m_point_info["ener"]["value"], y, xerr=[self.m_point_info["ener"]["ed_value"],self.m_point_info["ener"]["ed_value"]],yerr=[ed_y,eu_y],fmt=self.fmt,color=self.markercolor,elinewidth=self.elinewidth) | |
| 119 | - else: | |
| 120 | - plt.errorbar(self.m_point_info["ener"]["value"], y, yerr=[ed_y,eu_y],fmt=self.fmt,color=self.markercolor,elinewidth=self.elinewidth) | |
| 121 | - | |
| 122 | - plt.axhline(0.0,color=self.linecolor,lw=self.linewidth,ls=self.linestyle) | |
| 123 | - | |
| 124 | - | |
| 125 | -class ulimgraph(analysisutils.base,options,SpectralBase): | |
| 126 | - def __init__(self,datapoint,sed,sed_factor,eunit='TeV'): | |
| 127 | - super(ulimgraph,self).__init__() | |
| 128 | - #~ super(ulimgraph,self).__init__() | |
| 129 | - options.__init__(self) | |
| 130 | - SpectralBase.__init__(self,sed,sed_factor) | |
| 131 | - | |
| 132 | - self.xerrors=True | |
| 133 | - self.nlims = -1 | |
| 134 | - self.refUnit = eunit | |
| 135 | - self.SetDataPoint(datapoint) | |
| 136 | - | |
| 137 | - def SetDataPoint(self,datapoint): | |
| 138 | - self.m_point_info = datapoint | |
| 139 | - self.Npt = len(self.m_point_info["dnde"]["value"]) | |
| 140 | - | |
| 141 | - def _plt_points(self): | |
| 142 | - results = analysisutils.ResultsSorage() | |
| 143 | - | |
| 144 | - Energy_list = {"MeV":1,"GeV":1e-3,"TeV":1e-6} #TODO | |
| 145 | - for i in range(self.Npt): | |
| 146 | - | |
| 147 | - self.m_point_info["ener"]["value"][i]*=Energy_list[self.refUnit] | |
| 148 | - self.m_point_info["ener"]["ed_value"][i]*=Energy_list[self.refUnit] | |
| 149 | - self.m_point_info["ener"]["eu_value"][i]*=Energy_list[self.refUnit] | |
| 150 | - self.m_point_info["ener"]["unit"] = self.refUnit | |
| 151 | - | |
| 152 | - if self.m_point_info["TS"][i] >= self.tslim: | |
| 153 | - | |
| 154 | - if self.m_point_info["dnde"]["ed_value"][i]>self.m_point_info["dnde"]["value"][i]: | |
| 155 | - self.warning("\tflux error: "+str(self.m_point_info["dnde"]["ed_value"][i])+" is larger than flux value "+str(self.m_point_info["dnde"]["ed_value"][i])) | |
| 156 | - self.warning("\tTS value is however TS="+str(self.m_point_info["TS"][i])+", weird!") | |
| 157 | - else : | |
| 158 | - self.m_point_info["dnde"]["ed_value"][i] = 0 | |
| 159 | - self.m_point_info["dnde"]["eu_value"][i] = 0 | |
| 160 | - | |
| 161 | - if self.xerrors: | |
| 162 | - plt.errorbar(self.m_point_info["ener"]["value"], self.m_point_info["dnde"]["value"], xerr=[self.m_point_info["ener"]["ed_value"], self.m_point_info["ener"]["eu_value"]],yerr=[self.m_point_info["dnde"]["ed_value"], self.m_point_info["dnde"]["eu_value"]],fmt=self.fmt,color=self.markercolor,elinewidth=self.elinewidth) | |
| 163 | - else: | |
| 164 | - plt.errorbar(self.m_point_info["ener"]["value"], self.m_point_info["dnde"]["value"],yerr=[results["dnde"]["ed_value"],results["dnde"]["eu_value"]],fmt=self.fmt,color=self.markercolor,elinewidth=self.elinewidth) | |
| 165 | - | |
| 166 | - def _plt_limits(self): | |
| 167 | - ed_flux = [] | |
| 168 | - eu_flux = [] | |
| 169 | - flux = [] | |
| 170 | - ener = [] | |
| 171 | - | |
| 172 | - drawn_lims = 0 | |
| 173 | - Energy_list = {"MeV":1,"GeV":1e-3,"TeV":1e-6} #TODO | |
| 174 | - for i in range(self.Npt): | |
| 175 | - if self.m_point_info["TS"][i] < self.tslim: | |
| 176 | - self.info("Plot an upper limit for E = "+self.m_point_info["ener"]["value"][i]+" with a TS = "+self.m_point_info["TS"][i]) | |
| 177 | - if drawn_lims >= self.nlims and self.nlims!=-1: | |
| 178 | - break | |
| 179 | - | |
| 180 | - ed_flux.append(self.limlength*self.m_point_info["ulim_dnde"][i]) | |
| 181 | - eu_flux.append(0.0) | |
| 182 | - flux.append(self.m_point_info["ulim_dnde"][i]) | |
| 183 | - drawn_lims+=1 | |
| 184 | - | |
| 185 | - # if self.xerrors: | |
| 186 | - # plt.errorbar(self.m_point_info["ener"]["value"], self.m_point_info["dnde"]["value"], xerr=[self.m_point_info["ener"]["ed_value"], self.m_point_info["ener"]["eu_value"]],yerr=[self.m_point_info["dnde"]["ed_value"],self.m_point_info["dnde"]["eu_value"]],fmt=self.fmt,markersize=0.0,elinewidth=self.elinewidth,lolims=True,capsize=self.capsize,label='_nolegend_',mfc = self.color,ecolor=self.color,ms =self.markersize) | |
| 187 | - # else: | |
| 188 | - plt.errorbar(ener, flux, yerr=[ed_flux, eu_flux],fmt=self.fmt,markersize=0.0,elinewidth=self.elinewidth,lolims=True,capsize=self.capsize,label='_nolegend_',mfc = self.color,ecolor=self.color,ms =self.markersize) | |
| 189 | - | |
| 190 | - | |
| 191 | -class LightCurvePlotter(analysisutils.base,options): | |
| 192 | - """ Class to plot the Light curve""" | |
| 193 | - def __init__(self,srcname,datapoint): | |
| 194 | - super(LightCurvePlotter,self).__init__() | |
| 195 | - options.__init__(self) | |
| 196 | - self.m_name = srcname | |
| 197 | - self.m_data = datapoint #data point in a Results Storage class | |
| 198 | - | |
| 199 | - def draw(self): | |
| 200 | - if not(has_matplotlib): | |
| 201 | - self.warning("matplotlib module not found, can draw") | |
| 202 | - return | |
| 203 | - | |
| 204 | - time = [] | |
| 205 | - dtime = [] | |
| 206 | - flux = [] | |
| 207 | - dflux_ed = [] | |
| 208 | - dflux_eu = [] | |
| 209 | - for i in range(len(self.m_data["time"]["tmin_value"])): | |
| 210 | - time.append((self.m_data["time"]["tmin_value"][i]+self.m_data["time"]["tmax_value"][i])/2) | |
| 211 | - dtime.append((self.m_data["time"]["tmax_value"][i]-self.m_data["time"]["tmin_value"][i])/2) | |
| 212 | - flux.append(self.m_data["Iflux"]["value"][i]) | |
| 213 | - dflux_eu.append(self.m_data["Iflux"]["eu_value"][i]) | |
| 214 | - dflux_ed.append(self.m_data["Iflux"]["ed_value"][i]) | |
| 215 | - | |
| 216 | - plt.figure("results",figsize=(12,7),edgecolor="w") | |
| 217 | - unit = self.m_data["time"]["unit"] | |
| 218 | - plt.xlabel("Time ["+ unit+"]",fontsize=15) | |
| 219 | - unit = self.m_data["Iflux"]["unit"] | |
| 220 | - plt.ylabel("E$^{2}$ dN/dE ["+unit+"]",fontsize=15) | |
| 221 | - | |
| 222 | - print(time) | |
| 223 | - print(dtime) | |
| 224 | - print(flux) | |
| 225 | - print(dflux_ed) | |
| 226 | - print(dflux_eu) | |
| 227 | - plt.errorbar(time,flux,xerr=[dtime,dtime],yerr=[dflux_ed,dflux_eu],fmt=self.fmt,color=self.markercolor,elinewidth=self.elinewidth) | |
| 228 | - plt.show() | |
| 229 | - | |
| 230 | -class SpectrumPlotter(analysisutils.base,SpectralBase): | |
| 231 | - """ Class to compute and plot the spectra (i.e best fit model and butterfly). | |
| 232 | - if data points are provided, only change applied is energy unit convertion to match the butterfly one | |
| 233 | - (i.e. no dN/dE to SED conversion). | |
| 234 | - It is currently assumed that the unit is MeV for the energy of the data point. this will be change | |
| 235 | - once the I/O container format will be defined.""" | |
| 236 | - def __init__(self,srcname,like,datapoint,emin=0.1,emax=100,energy = "TeV",SED = True ,npt = 50): | |
| 237 | - super(SpectrumPlotter,self).__init__() | |
| 238 | - | |
| 239 | - self.m_ebound = [emin,emax] | |
| 240 | - self.m_name = srcname | |
| 241 | - self.m_like = like | |
| 242 | - self.m_spectral = like.obs().models()[srcname].spectral() | |
| 243 | - self.m_energy = [] | |
| 244 | - self.m_flux = [] | |
| 245 | - self.m_error = [] | |
| 246 | - self.m_but = [] | |
| 247 | - self.m_enebut = [] | |
| 248 | - self.m_npt = npt | |
| 249 | - self.m_covar = gl.GMatrix(1,1) | |
| 250 | - self.covar() | |
| 251 | - #~ this part take care of the style : SED or differential flux | |
| 252 | - #~ in the case of SED, the y-unit is erg/cm2/s | |
| 253 | - self.m_sed = SED | |
| 254 | - self.eunit = energy | |
| 255 | - self.m_sed_factor = 1. | |
| 256 | - self._validateUnits() | |
| 257 | - SpectralBase.__init__(self,self.m_sed,self.m_sed_factor) | |
| 258 | - | |
| 259 | - #Assume MeV for the energy #TODO | |
| 260 | - self.points = ulimgraph(datapoint,self.m_sed,gl.MeV2erg,energy) | |
| 261 | - self.residuals = residuals(self.m_spectral,datapoint,self.m_sed,gl.MeV2erg,energy) | |
| 262 | - | |
| 263 | - def _validateUnits(self): | |
| 264 | - Energy_list = {"MeV":1,"GeV":1e3,"TeV":1e6} | |
| 265 | - if not(Energy_list.has_key(self.eunit)): | |
| 266 | - self.warning("Change energy unit to TeV") | |
| 267 | - self.eunit = "TeV" | |
| 268 | - | |
| 269 | - if self.m_sed: | |
| 270 | - self.m_sed_factor = gl.MeV2erg*Energy_list[self.eunit]**2 | |
| 271 | - | |
| 272 | - def covar(self): | |
| 273 | - # Get covariance matrix if fit has converged | |
| 274 | - try: | |
| 275 | - fullcovar = self.m_like.obs().function().curvature().invert() | |
| 276 | - except: | |
| 277 | - self.warning("Covariance matrix not determined successfully") | |
| 278 | - return | |
| 279 | - #~ get the matrix element of the source of interest | |
| 280 | - #~ 1) get the right element indices | |
| 281 | - idx = 0 | |
| 282 | - par_index_map = [] | |
| 283 | - for m in self.m_like.obs().models() : | |
| 284 | - if m.name()!= self.m_name: | |
| 285 | - idx += m.size() | |
| 286 | - continue | |
| 287 | - idx += m.spatial().size() | |
| 288 | - for par in m.spectral(): | |
| 289 | - if par.is_free(): | |
| 290 | - par_index_map.append(idx) | |
| 291 | - idx += 1 | |
| 292 | - | |
| 293 | - #~ 2) get the elemets and store them in a matrix | |
| 294 | - self.m_covar = gl.GMatrix(len(par_index_map),len(par_index_map)) | |
| 295 | - i = 0 | |
| 296 | - for xpar in par_index_map: | |
| 297 | - j = 0 | |
| 298 | - for ypar in par_index_map: | |
| 299 | - self.m_covar[i,j] = fullcovar[xpar,ypar] | |
| 300 | - j += 1 | |
| 301 | - i += 1 | |
| 302 | - self.success("Covariance Matrix succesfuly computed") | |
| 303 | - | |
| 304 | - def _makespectrum(self): | |
| 305 | - for i in xrange(self.m_npt): | |
| 306 | - #Compute the energy | |
| 307 | - lene = log10(self.m_ebound[0])+log10(self.m_ebound[1])*i/(self.m_npt-1) | |
| 308 | - self.m_energy.append(pow(10,lene)) | |
| 309 | - #Compute the flux | |
| 310 | - self.m_flux.append(self.m_spectral.eval(gl.GEnergy(pow(10,lene),self.eunit),gl.GTime(0))) | |
| 311 | - | |
| 312 | - #Compute the gradients | |
| 313 | - if self.m_covar.size() != 1: | |
| 314 | - self.m_spectral.eval_gradients(gl.GEnergy(pow(10,lene), self.eunit),gl.GTime(0)) | |
| 315 | - #store them into a GVector | |
| 316 | - Derivative = gl.GVector(self.m_covar.size()/2) | |
| 317 | - j = 0 | |
| 318 | - for par in self.m_spectral: | |
| 319 | - if par.is_free(): | |
| 320 | - Derivative[j] = par.factor_gradient() | |
| 321 | - j += 1 | |
| 322 | - #~ computed the error | |
| 323 | - self.m_error.append(sqrt(Derivative * (self.m_covar*Derivative))) | |
| 324 | - | |
| 325 | - #~ convert the flux in sed if asked | |
| 326 | - self.m_flux = self._convertSED(self.m_flux,self.m_energy) | |
| 327 | - if self.m_covar.size() != 1: | |
| 328 | - self.m_error = self._convertSED(self.m_error,self.m_energy) | |
| 329 | - self._makebutterfly() # make the butterfly | |
| 330 | - self.success("Spectrum computed") | |
| 331 | - | |
| 332 | - def _makebutterfly(self): | |
| 333 | - """make the butterfly by appending element in a table""" | |
| 334 | - for i in xrange(self.m_npt): | |
| 335 | - self.m_but.append(self.m_flux[i]+self.m_error[i]) | |
| 336 | - self.m_enebut.append(self.m_energy[i]) | |
| 337 | - for i in xrange(self.m_npt): | |
| 338 | - idx = self.m_npt-i-1 | |
| 339 | - self.m_but.append(self.m_flux[idx]-self.m_error[idx]) | |
| 340 | - self.m_enebut.append(self.m_energy[idx]) | |
| 341 | - self.m_but.append(self.m_but[0]) | |
| 342 | - self.m_enebut.append(self.m_enebut[0]) | |
| 343 | - | |
| 344 | - def write(self): | |
| 345 | - self.warning("write function not yet implemented") | |
| 346 | - | |
| 347 | - def draw(self): | |
| 348 | - """plot the results, provide a file named ptfile for the flux points""" | |
| 349 | - gs = gridspec.GridSpec(2, 1,height_ratios=[3,1]) | |
| 350 | - self._makespectrum() | |
| 351 | - self.write() | |
| 352 | - | |
| 353 | - if not(has_matplotlib): | |
| 354 | - self.warning("matplotlib module not found, can draw") | |
| 355 | - return | |
| 356 | - | |
| 357 | - plt.figure("results",figsize=(12,7),edgecolor="w") | |
| 358 | - | |
| 359 | - sb1 = plt.subplot(gs[0]) | |
| 360 | - plt.loglog() | |
| 361 | - plt.xlabel("Energy ["+ self.eunit+"]",fontsize=15) | |
| 362 | - | |
| 363 | - if self.m_sed: | |
| 364 | - plt.ylabel("E$^{2}$ dN/dE [erg cm$^{2}$ s$^{-1}$]",fontsize=15) | |
| 365 | - else: | |
| 366 | - plt.ylabel("dN/dE [cm$^{-2}$ s$^{-1}$ "+ self.eunit+"$^{-1}$]",fontsize=15) | |
| 367 | - | |
| 368 | - plt.plot(self.m_energy,self.m_flux) | |
| 369 | - plt.plot(self.m_enebut,self.m_but) | |
| 370 | - | |
| 371 | - #~ plot the data points on top of the buterfly | |
| 372 | - self.points._plt_points() | |
| 373 | - self.points._plt_limits() | |
| 374 | - | |
| 375 | - #~ plot the residual points | |
| 376 | - sb2 = plt.subplot(gs[1]) | |
| 377 | - plt.xscale('log') | |
| 378 | - self.residuals._plt_residuals() | |
| 379 | - | |
| 380 | - plt.show() | |
| 381 | - | |
| 382 | - | |
| 383 | -# ============= # | |
| 384 | -# Plot skymaps # | |
| 385 | -# ============= # | |
| 386 | -class MapPlotter(analysisutils.base): | |
| 387 | - def __init__(self,modelmap, countmap): | |
| 388 | - super(MapPlotter,self).__init__() | |
| 389 | - self.modelmap = modelmap | |
| 390 | - self.countmap = countmap | |
| 391 | - | |
| 392 | - if not(has_aplpy) : | |
| 393 | - self.error("Module aplypy needed") | |
| 394 | - if not(has_matplotlib) : | |
| 395 | - self.error("Module matplotlib needed") | |
| 396 | - | |
| 397 | - def draw(self): | |
| 398 | - """ Plot the model map. """ | |
| 399 | - # Load model map | |
| 400 | - fig = plt.figure() | |
| 401 | - f1 = aplpy.FITSFigure(self.countmap, figure=fig, subplot=[0.1,0.1,0.35,0.8]) | |
| 402 | - f1.set_tick_labels_font(size='small') | |
| 403 | - f1.set_axis_labels_font(size='small') | |
| 404 | - f1.show_colorscale() | |
| 405 | - | |
| 406 | - f1.tick_labels.set_yformat('dd:mm:ss') | |
| 407 | - f1.tick_labels.set_xformat('hh:mm:ss') | |
| 408 | - f1.axis_labels.set_xtext('Right Ascension (J2000)') | |
| 409 | - f1.axis_labels.set_ytext('Declination (J2000)') | |
| 410 | - f1.ticks.set_length(10.5, minor_factor=0.5) | |
| 411 | - | |
| 412 | - f2 = aplpy.FITSFigure(self.modelmap, figure=fig, subplot=[0.5,0.1,0.35,0.8]) | |
| 413 | - f2.set_tick_labels_font(size='small') | |
| 414 | - f2.set_axis_labels_font(size='small') | |
| 415 | - f2.show_colorscale() | |
| 416 | - | |
| 417 | - f2.hide_yaxis_label() | |
| 418 | - f2.hide_ytick_labels() | |
| 419 | - | |
| 420 | - fig.canvas.draw() | |
| 421 | - fig.show() |
pyext/setup.py.in
| ... | ... | @@ -121,8 +121,7 @@ setup(name='@PACKAGE_NAME@', |
| 121 | 121 | author='Juergen Knoedlseder', |
| 122 | 122 | author_email='@PACKAGE_BUGREPORT@', |
| 123 | 123 | url='http://gammalib.sourceforge.net/', |
| 124 | - py_modules=['ctools.tools', 'ctools.obsutils', 'ctools.analysisutils', | |
| 125 | - 'ctools.plotutils'], | |
| 124 | + py_modules=['ctools.tools', 'ctools.obsutils'], | |
| 126 | 125 | ext_modules=[Extension('ctools._tools', ['ctools/tools_wrap.cpp'], |
| 127 | 126 | include_dirs=include_dirs, |
| 128 | 127 | library_dirs=library_dirs, | ... | ... |