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HistoUtils.py
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1 #!/usr/bin/env python
2 # =============================================================================
3 # This module contains set of simple and useful utilities for booking and
4 # manipulations with Gaudi-AIDA histograms, inspired by Thomas' request
5 # @author Vanya BELYAEV ibelyaev@physics.syr.edu
6 # @date 2007-08-03
7 # =============================================================================
8 """
9 This module contains set of simple and useful utilities for booking and
10 manipulations with Gaudi-AIDA histograms, inspired by Thomas' request
11
12 The module contains following public symbols:
13
14 - book for booking of various 1D,2D&3D-histograms
15 - bookProf for booking of various 1D&2D-profiles
16 - getAsAIDA for retrieval of histograms/profiles from HTS in AIDA format
17 - getAsROOT for retrieval of histograms/profiles from HTS in ROOT format
18 - fill for smart filling of 1D-histogram (AIDA or ROOT)
19 - aida2root for conversion of AIDA histogram to ROOT
20 - HistoStats for many statistical information
21 - HistoFile class for storing histograms to a file
22 - histoDump for dumping of the histogram in text format (a'la HBOOK)
23 - dumpHisto for dumping of the histogram in text format (a'la HBOOK)
24
25 """
26 # =============================================================================
27 __author__ = "Vanya BELYAEV ibelyaev@physics.syr.edu"
28 # =============================================================================
29 __all__ = (
30 'book', # book AIDA histogram using Histogram Service
31 'bookProf', # book AIDA profile histogram using Histogram Service
32 'getAsAIDA', # get the histogram form Histogram Service as AIDA histogram
33 'getAsROOT', # get the histogram form Histogram Service as AIDA histogram
34 'fill', # "power-fill" method for filling of histograms
35 'aida2root', # AIDA -> ROOT converter
36 'HistoStats', # statistical information for 1D-histograms
37 'HistoFile', # class for storing histograms to a file
38 'histoDump', # dump histogramintext format a'la HBOOK
39 'dumpHisto' # dump histogramintext format a'la HBOOK
40 )
41 # =============================================================================
42 # import core of Gaudi
43 import ROOT
44 from GaudiPython.Bindings import AppMgr
45 from GaudiPython.Bindings import iHistogramSvc
46 from GaudiPython.Bindings import gbl as cpp
47 HID = cpp.GaudiAlg.ID
48
49 ## global flag
50 useROOT = False
51
52 # =============================================================================
53 # Helper private auxiliary function to get Application Manager
54
55
56 def _getAppMgr(**kwargs):
57 """
58 Helper private auxiliary function to get Application Manager
59 """
60 gaudi = kwargs.get('gaudi', None)
61 if not gaudi:
62 gaudi = AppMgr()
63 if not gaudi:
64 raise RuntimeError, 'Unable to get valid ApplicationMgr'
65
66 state = gaudi._isvc.FSMState()
67 if state < cpp.Gaudi.StateMachine.CONFIGURED:
68 gaudi.config()
69 state = gaudi._isvc.FSMState()
70 if state < cpp.Gaudi.StateMachine.INITIALIZED:
71 gaudi.initialize()
72
73 return gaudi # RETURN
74
75 # =============================================================================
76 # Helper private auxiliary function to get iHistogramSvs
77
78
79 def _getHistoSvc(**kwargs):
80 """
81 Helper private auxiliary function to get iHistogramSvs
82 """
83 svc = kwargs.get('service', None)
84 if not svc:
85 svc = kwargs.get('svc', None)
86 else:
87 return svc # RETURN
88 gaudi = _getAppMgr(**kwargs)
89 return gaudi.histsvc() # RETURN
90
91 # =============================================================================
92 # Helper private auxiliary function to get iDataSvs
93
94
95 def _getEvtSvc(**kwargs):
96 """
97 Helper private auxiliary function to get iDataSvs
98 """
99 svc = kwargs.get('service', None)
100 if not svc:
101 svc = kwargs.get('svc', None)
102 else:
103 return svc # RETURN
104 gaudi = _getAppMgr(**kwargs)
105 return gaudi.evtsvc() # RETURN
106
107 # =============================================================================
108 # The trivial function to book the various 1D,2D&3D-histograms
109
110
111 def book(*args, **kwargs):
112 """
113 The trivial function to book the various 1D,2D&3D-histograms
114
115 (1) book the trivial 1D histogram with full path
116
117 >>> h1D = book ( 'path/to/my/histo' , ## path in Histogram Transient Store
118 'cosine of decay angle ' , ## histogram title
119 100 , ## number of bins
120 -1 , ## low edge
121 100 ) ## high edge
122
123 (2) book the trivial 1D histogram with directory path and string ID :
124
125 >>> h1D = book ( 'path/to/directory' , ## the path to directory in HTS
126 'H1' , ## string histogram identifier
127 'cosine of decay angle ' , ## histogram title
128 100 , ## number of bins
129 -1 , ## low edge
130 100 ) ## high edge
131
132 (3) book the trivial 1D histogram with directory path and integer ID :
133
134 >>> h1D = book ( 'path/to/directory' , ## the path to directory in HTS
135 124 , ## integer histogram identifier
136 'cosine of decay angle ' , ## histogram title
137 100 , ## number of bins
138 -1 , ## low edge
139 100 ) ## high edge
140
141 (4) book the trivial 2D histogram with full path
142
143 >>> h1D = book ( 'path/to/my/histo' , ## path in Histogram Transient Store
144 'm12**2 versus m13**2' , ## histogram title
145 50 , ## number of X-bins
146 1.0 , ## low X-edge
147 4.0 , ## high X-edge
148 50 , ## number of Y-bins
149 1 , ## low Y-edge
150 2 ) ## high Y-edge
151
152 (5) book the trivial 2D histogram with directory path and literal ID
153
154 >>> h1D = book ( 'path/to/directory' , ## path in Histogram Transient Store
155 'Dalitz1' , ## literal histogram identifier
156 'm12**2 versus m13**2' , ## histogram title
157 50 , ## number of X-bins
158 1.0 , ## low X-edge
159 4.0 , ## high X-edge
160 50 , ## number of Y-bins
161 1 , ## low Y-edge
162 2 ) ## high Y-edge
163
164 (6) book the trivial 2D histogram with directory path and integer ID
165
166 >>> h1D = book ( 'path/to/directory' , ## path in Histogram Transient Store
167 854 , ## integer histogram identifier
168 'm12**2 versus m13**2' , ## histogram title
169 50 , ## number of X-bins
170 1.0 , ## low X-edge
171 4.0 , ## high X-edge
172 50 , ## number of Y-bins
173 1.0 , ## low Y-edge
174 4.0 ) ## high Y-edge
175
176 (7) book the trivial 3D histogram with full path
177
178 >>> h1D = book ( 'path/to/my/histo' , ## path in Histogram Transient Store
179 'x vs y vs z ' , ## histogram title
180 10 , ## number of X-bins
181 -1.0 , ## low X-edge
182 1.0 , ## high X-edge
183 10 , ## number of Y-bins
184 -1.0 , ## low Y-edge
185 1.0 , ## high Y-edge
186 10 , ## number of Z-bins
187 -1.0 , ## low Z-edge
188 1.0 ) ## high Z-edge
189
190 (8) book the trivial 3D histogram with directory path and literal ID
191
192 >>> h1D = book ( 'path/to/directory' , ## path in Histogram Transient Store
193 'xyz' , ## literal histogram identifier
194 'x vs y vs z' , ## histogram title
195 10 , ## number of X-bins
196 -1.0 , ## low X-edge
197 1.0 , ## high X-edge
198 10 , ## number of Y-bins
199 -1.0 , ## low Y-edge
200 1.0 , ## high Y-edge
201 10 , ## number of Z-bins
202 -1.0 , ## low Z-edge
203 1.0 ) ## high Z-edge
204
205 (9) book the trivial 3D histogram with directory path and integer ID
206
207 >>> h1D = book ( 'path/to/directory' , ## path in Histogram Transient Store
208 888 , ## integer histogram identifier
209 'x vs y vs z' , ## histogram title
210 10 , ## number of X-bins
211 -1.0 , ## low X-edge
212 1.0 , ## high X-edge
213 10 , ## number of Y-bins
214 -1.0 , ## low Y-edge
215 1.0 , ## high Y-edge
216 10 , ## number of Z-bins
217 -1.0 , ## low Z-edge
218 1.0 ) ## high Z-edge
219
220 Many other booking methods are available,
221 e.g. for the histograms with non-equidistant bins, see IHistogamSvc::book
222
223 """
224 if useROOT or kwargs.get('useROOT', False) or not kwargs.get('useAIDA', True):
225 from ROOT import TH1D
226 a0 = args[0]
227 a1 = args[1]
228 a2 = args[2]
229 if not str is type(a1):
230 a1 = 'h' + str(a1)
231 if str is type(a2):
232 return TH1D(a0 + a1, a2, *args[3:])
233 else:
234 return TH1D(a0, a1, *args[2:])
235
236 svc = _getHistoSvc(**kwargs)
237 if not svc:
238 raise RuntimeError, 'Unable to get valid HistogramService '
239 # book the histogram using the service
240 return svc.book(*args) # RETURN
241
242
243 book.__doc__ += '\n\n' + '\thelp(iHistogramSvc.book) : \n\n' \
244 + iHistogramSvc.book . __doc__
245 book.__doc__ += '\n\n' + '\thelp(IHistogramSvc::book) : \n\n' \
246 + cpp.IHistogramSvc.book . __doc__
247
248 # =============================================================================
249 # The trivial function to book 1D&2D profile histograms:
250
251
252 def bookProf(*args, **kwargs):
253 """
254
255 The trivial function to book 1D&2D profile histograms:
256
257 (1) book 1D-profile histogram with full path in Histogram Transient Store:
258 >>> histo = bookProf ( 'path/to/my/profile' , ## path in Histogram Transient Store
259 'Energy Correction' , ## the histogram title
260 100 , ## number of X-bins
261 0.0 , ## low X-edge
262 100 ) ## high X-edge
263
264 (2) book 1D-profile histogram with directory path and literal ID
265 >>> histo = bookProf ( 'path/to/my/profile' , ## path in Histogram Transient Store
266 'Calibration' , ## the histogram literal identifier
267 'Energy Correction' , ## the histogram title
268 100 , ## number of X-bins
269 0.0 , ## low X-edge
270 100 ) ## high X-edge
271
272 (3) book 1D-profile histogram with directory path and integer ID
273 >>> histo = bookProf ( 'path/to/my/profile' , ## path in Histogram Transient Store
274 418 , ## the histogram integer identifier
275 'Energy Correction' , ## the histogram title
276 100 , ## number of X-bins
277 0.0 , ## low X-edge
278 100 ) ## high X-edge
279
280 (4) book 2D-profile histogram with full path in Histogram Transient Store:
281 >>> histo = bookProf ( 'path/to/my/profile' , ## path in Histogram Transient Store
282 'Energy Correction' , ## the histogram title
283 50 , ## number of X-bins
284 0.0 , ## low X-edge
285 100 , ## high X-edge
286 50 , ## number of Y-bins
287 0.0 , ## low Y-edge
288 100 ) ## high Y-edge
289
290 (5) book 2D-profile histogram with directory path and literal ID
291 >>> histo = bookProf ( 'path/to/my/profile' , ## path in Histogram Transient Store
292 'Calibration' , ## the histogram literal identifier
293 'Energy Correction' , ## the histogram title
294 50 , ## number of X-bins
295 0.0 , ## low X-edge
296 100 , ## high X-edge
297 50 , ## number of Y-bins
298 0.0 , ## low Y-edge
299 100 ) ## high Y-edge
300
301 (6) book 2D-profile histogram with directory path and integer ID
302 >>> histo = bookProf ( 'path/to/my/profile' , ## path in Histogram Transient Store
303 418 , ## the histogram integer identifier
304 'Energy Correction' , ## the histogram title
305 50 , ## number of X-bins
306 0.0 , ## low X-edge
307 100 , ## high X-edge
308 50 , ## number of Y-bins
309 0.0 , ## low Y-edge
310 100 ) ## high Y-edge
311
312 Many other booking methods are available,
313 e.g. for the histograms with non-equidistant bins, see IHistogamSvc::book
314
315 """
316 svc = _getHistoSvc(**kwargs)
317 if not svc:
318 raise RuntimeError, 'Unable to get valid HistogramService '
319 # book the histogram using the service
320 return svc.bookProf(*args) # RETURN
321
322
323 bookProf.__doc__ += '\n\n' + '\thelp(iHistogramSvc.bookProf) : \n\n' \
324 + iHistogramSvc.bookProf . __doc__
325 bookProf.__doc__ += '\n\n' + '\thelp(IHistogramSvc::bookProf) : \n\n' \
326 + cpp.IHistogramSvc.bookProf . __doc__
327
328 # =============================================================================
329 # The most trivial function to retrieve the histogram from Histogram Transient Store
330
331
332 def getAsAIDA(path, **kwargs):
333 """
334
335 The most trivial function to retrieve the histogram from Histogram Transient Store
336 The histogram is returned by reference to its AIDA-representation (if possible)
337
338 >>> h = getAsAIDA ( 'some/path/to/my/histogram' )
339
340 """
341 svc = _getHistoSvc(**kwargs)
342 if not svc:
343 raise RuntimeError, 'Unable to get valid HistogramService '
344 # return the histogram
345 return svc.getAsAIDA(path) # RETURN
346
347
348 getAsAIDA.__doc__ += '\n\n' + '\thelp(iHistogramSvc.getAsAIDA) : \n\n' \
349 + iHistogramSvc.getAsAIDA . __doc__
350 getAsAIDA.__doc__ += '\n\n' + '\thelp(iHistogramSvc.retrieve) : \n\n' \
351 + iHistogramSvc.retrieve . __doc__
352
353 # =============================================================================
354 # The most trivial function to retrieve the histogram from Histogram Transient Store
355
356
357 def getAsROOT(path, **kwargs):
358 """
359
360 The most trivial function to retrieve the histogram from Histogram Transient Store
361 The histogram is returned by reference to its underlying native ROOT-representation (if possible)
362
363 >>> h = getAsROOT ( 'some/path/to/my/histogram' )
364
365 """
366 svc = _getHistoSvc(**kwargs)
367 if not svc:
368 raise RuntimeError, 'Unable to get valid HistogramService '
369 # return the histogram
370 return svc.getAsROOT(path) # RETURN
371
372
373 getAsROOT.__doc__ += '\n\n' + '\thelp(iHistogramSvc.getAsROOT) : \n\n' \
374 + iHistogramSvc.getAsROOT . __doc__
375
376
377 # =============================================================================
378 # The function which allows 'the smart fill' of 1D-histogram
379 def fill(histo, # histogram
380 data, # input data
381 fun=lambda x: x, # function to be used
382 cut=lambda x: True, # cut to be applied
383 **kwargs): # optional extra arguments
384 """
385
386 The function which allows 'the smart fill' of 1D-histogram
387
388 >>> histo = ...
389
390 The most trivial case, fill with the value
391 >>> fill ( histo , 1.0 )
392
393 Fill from any iterable object (sequence)
394 >>> fill ( histo , [1,,2,3,4,5,10] )
395
396 Fill from iterable object and apply the function:
397 >>> fill ( histo , [1,2,3,4,5] , math.sin )
398
399 Use lambda form:
400 >>> fill ( histo , [1,2,3,4,5] , lambda x : x*x )
401
402 The same
403 >>> fill ( histo , [1,2,3,4,5] , fun = lambda x : x*x )
404
405 Use internal attributes:
406 >>> tracks = evtSvc['Rec/Track/Best'] ## iterable container of tracks
407 >>> fill ( histo , tracks , lambda t : t.pt() )
408
409 Apply the predicate: fill only even numbers:
410 >>> fill ( histo , [1,2,3,4,5,6,7] , lambda x : x , lambda y : y%2 )
411
412 The same (omit the trivial function) :
413 >>> fill ( histo , [1,2,3,4,5,6,7] , cut = lambda y : y%2 )
414
415 Apply the predicate: fill only pt for positively charged tracks:
416 >>> tracks = evtSvc['Rec/Track/Best']
417 >>> fill ( histo , tracks , lambda t : t.pt() , lambda t : 0<t.charge() )
418
419 The same:
420 >>> fill ( histo , tracks ,
421 fun = lambda t : t.pt() ,
422 cut = lambda t : 0<t.charge() )
423
424 Ordinary functions are also fine:
425 >>> def myfun ( track ) : return sin( track.pt() + track.p() )
426 >>> def mycut ( track ) : return track.p() > 100 * GeV
427 >>> fill ( histo , tracks , myfun , mycut )
428
429 The 'data' could be the address in TES, in this case the object
430 is retrieved from TES and the method is applied to the objects,
431 retrieved from TES:
432 >>> fill ( histo , ## the reference to the histogram
433 'Rec/Track/Best' , ## the location of objects in TES
434 lambda t : t.pt() ) ## function to be used for histogram fill
435 >>> fill ( histo , ## the reference to the histogram
436 'Rec/Track/Best' , ## the address of objects in TES
437 lambda t : t.pt() , ## the function to be used for histogram fill
438 lambda t : t.charge()>0 ) ## the criteria to select tracks
439
440 The arguments 'fun' and 'cut' could be strings, in this case
441 they are evaluated by python before usage.
442 This option could be often very useful.
443
444 """
445
446 # if value is a string, try to get the objects from TES
447 if type(data) == str:
448 svc = _getEvtSvc(**kwargs)
449 data = svc[data]
450 return fill(histo, data, fun, cut, **kwargs)
451
452 # if the function is a string: evaluate it!
453 if type(fun) == str:
454 fun = eval(fun, globals())
455
456 # if the criterion is a string: evaluate it!
457 if type(cut) == str:
458 cut = eval(cut, globals())
459
460 if not hasattr(data, '__iter__'):
461 data = [data]
462
463 if not hasattr(histo, 'fill') and hasattr(histo, 'Fill'):
464 setattr(histo, 'fill', getattr(histo, 'Fill'))
465
466 for item in data:
467 if not cut(item):
468 continue # CONTINUE
469 histo.fill(fun(item))
470
471 return histo # RETURN
472
473
474 # =============================================================================
475 # AIDA -> ROOT converter
476 aida2root = cpp.Gaudi.Utils.Aida2ROOT.aida2root
477 # =============================================================================
478 # Convert AIDA to ROOT
479
480
481 def _to_root_(self):
482 """
483 Convert AIDA to ROOT
484
485 >>> aida = ... ## get AIDA histogram
486 >>> root = aida.toROOT() ## convert it to ROOT
487
488 """
489 return aida2root(self)
490
491
492 _to_root_ . __doc__ += aida2root . __doc__
493
494 for t in (cpp.AIDA.IHistogram3D,
495 cpp.AIDA.IHistogram2D,
496 cpp.AIDA.IHistogram1D,
497 cpp.AIDA.IProfile2D,
498 cpp.AIDA.IProfile1D):
499 if not hasattr(t, 'Fill') and hasattr(t, 'fill'):
500 setattr(t, 'Fill', getattr(t, 'fill'))
501 for attr in ('toROOT', 'toRoot',
502 'asROOT', 'asRoot',
503 'AsROOT', 'AsRoot'):
504 if not hasattr(t, attr):
505 setattr(t, attr, _to_root_)
506
507 cpp.AIDA.IHistogram3D. __repr__ = lambda s: cpp.GaudiAlg.Print3D.toString(
508 s, HID(s.title()))
509 cpp.AIDA.IHistogram3D. __str__ = cpp.AIDA.IHistogram3D. __repr__
510
511
512 HistoStats = cpp.Gaudi.Utils.HistoStats
513
514 # =============================================================================
515 # Evaluate 'bin-by-bin' momentum of certain order around the value
516
517
518 def _moment_(self, order, value=0):
519 """
520 Evaluate 'bin-by-bin' momentum of order 'order' around the value 'value'
521 for 1D histogram
522
523 >>> h1 = ...
524 >>> print h1.moment ( 5 )
525
526 """
527 return HistoStats.moment(self, order, value)
528
529 # =============================================================================
530 # Evaluate error in 'bin-by-bin' momentum of certain order around the value
531
532
533 def _momentErr_(self, order):
534 """
535 Evaluate error for 'bin-by-bin' momentum of order 'order' around the value 'value'
536 for 1D histogram
537
538 >>> h1 = ...
539 >>> print h1.momentErr ( 5 )
540
541 """
542 return HistoStats.momentErr(self, order)
543 # =============================================================================
544 # Evaluate 'bin-by-bin' central momentum (around mean value)
545
546
547 def _centralMoment_(self, order):
548 """
549 Evaluate 'bin-by-bin' central momentum (around mean value)
550 for 1D histogram
551
552 >>> h1 = ...
553 >>> print h1.centralMoment ( 5 )
554
555 """
556 return HistoStats.centralMoment(self, order)
557
558 # =============================================================================
559 # Evaluate error in 'bin-by-bin' momentum of certain order around the value
560
561
562 def _centralMomentErr_(self, order):
563 """
564 Evaluate error for 'bin-by-bin' central momentum (around mean value)
565 for 1D histogram
566
567 >>> h1 = ...
568 >>> print h1.centralMomentErr ( 5 )
569
570 """
571 return HistoStats.centralMomentErr(self, order)
572
573 # =============================================================================
574 # Evaluate 'bin-by-bin' skewness for 1D histogram
575
576
577 def _skewness_(self):
578 """
579 Evaluate 'bin-by-bin' skewness for 1D AIDA histogram
580
581 >>> h1 = ...
582 >>> print h1.skewness()
583
584 """
585 return HistoStats.skewness(self)
586
587 # =============================================================================
588 # Evaluate error for 'bin-by-bin' skewness for 1D histogram
589
590
591 def _skewnessErr_(self):
592 """
593 Evaluate error for 'bin-by-bin' skewness
594
595 >>> h1 = ...
596 >>> print h1.skewnessErr()
597
598 """
599 return HistoStats.skewnessErr(self)
600
601 # =============================================================================
602 # Evaluate 'bin-by-bin' kurtosis for 1D histogram
603
604
605 def _kurtosis_(self):
606 """
607 Evaluate 'bin-by-bin' kurtosis
608
609 >>> h1 = ...
610 >>> print h1.kurtosis ()
611
612 """
613 return HistoStats.kurtosis(self)
614
615 # =============================================================================
616 # Evaluate error for 'bin-by-bin' kurtosis for 1D histogram
617
618
619 def _kurtosisErr_(self):
620 """
621 Evaluate error for 'bin-by-bin' kurtotis for 1D AIDA histogram
622
623 >>> h1 = ...
624 >>> print h1.kurtotisErr()
625
626 """
627 return HistoStats.kurtosisErr(self)
628
629 # =============================================================================
630
631
632 def _nEff_(self):
633 """
634 Number of equivalent entries
635 """
636 return HistoStats.nEff(self)
637 # =============================================================================
638
639
640 def _mean_(self):
641 """
642 Evaluate the MEAN value
643 """
644 return HistoStats.mean(self)
645 # =============================================================================
646
647
648 def _meanErr_(self):
649 """
650 Evaluate the error for MEAN estimate
651 """
652 return HistoStats.meanErr(self)
653
654 # =============================================================================
655
656
657 def _rms_(self):
658 """
659 Evaluate the RMS for AIDA histogram
660 """
661 return HistoStats.rms(self)
662 # =============================================================================
663
664
665 def _rmsErr_(self):
666 """
667 Evaluate the error for RMS estimate
668 """
669 return HistoStats.rmsErr(self)
670
671 # =============================================================================
672
673
674 def _sumBinHeightErr_(self):
675 """
676 Get an error in the sum bin height ('in-range integral')
677 """
678 return HistoStats.sumBinHeightErr(self)
679
680 # =============================================================================
681
682
683 def _sumAllBinHeightErr_(self):
684 """ Get an error in the sum bin height ('in-range integral') """
685 return HistoStats.sumAllBinHeightErr(self)
686
687 # =============================================================================
688
689
690 def _overflowEntriesFrac_(self):
691 """
692 The fraction of overflow entries (useful for shape comparison)
693 """
694 return HistoStats.overflowEntriesFrac(self)
695 # =============================================================================
696
697
698 def _overflowEntriesFracErr_(self):
699 """
700 The error for fraction of overflow entries (useful for shape comparison)
701 """
702 return HistoStats.overflowEntriesFracErr(self)
703 # =============================================================================
704
705
706 def _underflowEntriesFrac_(self):
707 """
708 The fraction of underflow entries (useful for shape comparison)
709 """
710 return HistoStats.underflowEntriesFrac(self)
711 # =============================================================================
712
713
714 def _underflowEntriesFracErr_(self):
715 """
716 The error for fraction of underflow entries (useful for shape comparison)
717 """
718 return HistoStats.underflowEntriesFracErr(self)
719
720 # =============================================================================
721
722
723 def _overflowIntegralFrac_(self):
724 """
725 The fraction of overflow integral (useful for shape comparison)
726 """
727 return HistoStats.overflowIntegralFrac(self)
728 # =============================================================================
729
730
731 def _overflowIntegralFracErr_(self):
732 """
733 The error for fraction of overflow integral (useful for shape comparison)
734 """
735 return HistoStats.overflowIntegralFracErr(self)
736 # =============================================================================
737
738
739 def _underflowIntegralFrac_(self):
740 """
741 The fraction of underflow integral (useful for shape comparison)
742 """
743 return HistoStats.underflowIntegralFrac(self)
744 # =============================================================================
745
746
747 def _underflowIntegralFracErr_(self):
748 """
749 The error for fraction of underflow integral (useful for shape comparison)
750 """
751 return HistoStats.underflowIntegralFracErr(self)
752
753 # =============================================================================
754 # get number of entries in histogram up to the certain bin (not-included)
755 # get number of entries in histogram form the certain
756 # minimal bin up to the certain maximal bin (not-included)
757
758
759 def _nEntries_(self, i1, i2=-10000000):
760 """
761 Get number of entries in histogram up to the certain bin (not-included)
762
763 attention: underflow bin is included!
764
765 >>> h1
766 >>> print h1.nEntries ( 10 )
767
768 Get number of entries in histogram form the certain
769 minimal bin up to the certain maximal bin (not-included)
770
771 >>> h1
772 >>> print h1.nEntries ( 10 , 15 )
773
774 """
775 if i2 < i1 or i2 < 0:
776 return HistoStats.nEntries(self, i1)
777 return HistoStats.nEntries(self, i1, i2)
778 # =============================================================================
779
780
781 def _nEntriesFrac_(self, i1, i2=-10000000):
782 """
783 Get the fraction of entries in histogram up to the certain bin (not-included)
784
785 attention: underflow bin is included!
786
787 >>> h1
788 >>> print h1.nEntriesFrac ( 10 )
789
790 Get the fraction of entries in histogram form the certain
791 minimal bin up to the certain maximal bin (not-included)
792
793 >>> h1
794 >>> print h1.nEntriesFrac ( 10 , 15 )
795
796 """
797 if i2 < i1 or i2 < 0:
798 return HistoStats.nEntriesFrac(self, i1)
799 return HistoStats.nEntriesFrac(self, i1, i2)
800 # =============================================================================
801
802
803 def _nEntriesFracErr_(self, i1, i2=-10000000):
804 """
805 Get error for fraction of entries in histogram up to the certain bin (not-included)
806
807 attention: underflow bin is included!
808
809 >>> h1
810 >>> print h1.nEntriesFracErr( 10 )
811
812 Get error fraction of entries in histogram form the certain
813 minimal bin up to the certain maximal bin (not-included)
814
815 >>> h1
816 >>> print h1.nEntriesFracErr ( 10 , 15 )
817
818 """
819 if i2 < i1 or i2 < 0:
820 return HistoStats.nEntriesFracErr(self, i1)
821 return HistoStats.nEntriesFracErr(self, i1, i2)
822
823
824 # =============================================================================
825 i1DH = cpp.AIDA.IHistogram1D
826
827 if not hasattr(i1DH, 'moment'):
828 i1DH.moment = _moment_
829 if not hasattr(i1DH, 'momentErr'):
830 i1DH.momentErr = _momentErr_
831 if not hasattr(i1DH, 'centralMoment'):
832 i1DH.centralMoment = _centralMoment_
833 if not hasattr(i1DH, 'momentMomentErr'):
834 i1DH.centralMomentErr = _centralMomentErr_
835 if not hasattr(i1DH, 'nEff'):
836 i1DH.nEff = _nEff_
837 if not hasattr(i1DH, 'mean'):
838 i1DH.mean = _mean_
839 if not hasattr(i1DH, 'meanErr'):
840 i1DH.meanErr = _meanErr_
841 if not hasattr(i1DH, 'rms'):
842 i1DH.rms = _rms_
843 if not hasattr(i1DH, 'rmsErr'):
844 i1DH.rmsErr = _rmsErr_
845 if not hasattr(i1DH, 'skewness'):
846 i1DH.skewness = _skewness_
847 if not hasattr(i1DH, 'skewnessErr'):
848 i1DH.skewnessErr = _skewnessErr_
849 if not hasattr(i1DH, 'kurtosis'):
850 i1DH.kurtosis = _kurtosis_
851 if not hasattr(i1DH, 'kurtosisErr'):
852 i1DH.kurtosisErr = _kurtosisErr_
853
854 if not hasattr(i1DH, 'overflowEntriesFrac'):
855 i1DH.overflowEntriesFrac = _overflowEntriesFrac_
856 if not hasattr(i1DH, 'overflowEntriesFracErr'):
857 i1DH.overflowEntriesFracErr = _overflowEntriesFracErr_
858 if not hasattr(i1DH, 'underflowEntriesFrac'):
859 i1DH.underflowEntriesFrac = _underflowEntriesFrac_
860 if not hasattr(i1DH, 'underflowEntriesFracErr'):
861 i1DH.underflowEntriesFracErr = _underflowEntriesFracErr_
862
863 if not hasattr(i1DH, 'overflowIntegralFrac'):
864 i1DH.overflowIntegralFrac = _overflowIntegralFrac_
865 if not hasattr(i1DH, 'overflowIntegralFracErr'):
866 i1DH.overflowIntegralFracErr = _overflowIntegralFracErr_
867 if not hasattr(i1DH, 'underflowIntegralFrac'):
868 i1DH.underflowIntegralFrac = _underflowIntegralFrac_
869 if not hasattr(i1DH, 'underflowIntegralFracErr'):
870 i1DH.underflowIntegralFracErr = _underflowIntegralFracErr_
871
872 if not hasattr(i1DH, 'nEntries'):
873 i1DH.nEntries = _nEntries_
874 if not hasattr(i1DH, 'nEntriesFrac'):
875 i1DH.nEntriesFrac = _nEntriesFrac_
876 if not hasattr(i1DH, 'nEntriesFracErr'):
877 i1DH.nEntriesFracErr = _nEntriesFracErr_
878
879 # ============================================================================
880
881
882 def _path_(self):
883 """
884 Get the path in THS for the given AIDA object:
885
886 >>> aida =
887 >>> print aida.path()
888
889 """
890 return cpp.Gaudi.Utils.Histos.path(self)
891
892
893 iBH = cpp.AIDA.IBaseHistogram
894 if not hasattr(iBH, 'path'):
895 iBH.path = _path_
896 if not hasattr(iBH, 'TESpath'):
897 iBH.TESpath = _path_
898 if not hasattr(iBH, 'location'):
899 iBH.location = _path_
900
901
902 # =============================================================================
903 def __dumpHisto__(histo, *args):
904 """
905
906 Dump the histogram/profile in text format (a'la HBOOK)
907
908 >>> histo
909 >>> print dumpHisto ( histo )
910
911 >>> print histo.dump()
912 >>> print histo.dump( 20 , 20 )
913 >>> print histo.dump( 20 , 20 , True )
914
915 Uses:
916
917 """
918 return cpp.Gaudi.Utils.Histos.histoDump(histo, *args)
919
920
921 __dumpHisto__ .__doc__ = '\n' + cpp.Gaudi.Utils.Histos.histoDump . __doc__
922
923 # =============================================================================
924 # the actual function for text dump of the histogram
925 histoDump = __dumpHisto__
926 dumpHisto = __dumpHisto__
927
928 for t in (cpp.AIDA.IHistogram1D,
929 cpp.AIDA.IProfile1D,
930 ROOT.TH1D,
931 ROOT.TH1F,
932 ROOT.TH1,
933 ROOT.TProfile):
934 for method in ('dump',
935 'dumpHisto',
936 'dumpAsText'):
937 if not hasattr(t, method):
938 setattr(t, method, __dumpHisto__)
939
940 # ==============================================================================
941
942
943 class HistoFile:
944 """
945 Class to write histograms to a ROOT file.
946 hFile = HistoFile("myFile.root")
947 myHisto = ...
948 hFile.save(myHisto)
949 myHisto0 = ...
950 myHisto1 = ...
951 myHisto2 = ...
952 hFile.save(myHisto0, myHisto1, myHisto2)
953 histoList = [h0, h1, h2, h3]
954 hFile.save(histoList)
955 ...
956 hWriter.close()
957 """
958 __author__ = "Juan Palacios juan.palacios@nikhef.nl"
959
960 def __init__(self, fileName):
961 self.file = ROOT.TFile(fileName, "RECREATE")
962 from GaudiPython import gbl
963 self.aida2root = gbl.Gaudi.Utils.Aida2ROOT.aida2root
964 self.aidaTypes = [gbl.AIDA.IHistogram1D,
965 gbl.AIDA.IHistogram2D,
966 gbl.AIDA.IHistogram3D,
967 gbl.AIDA.IProfile1D,
968 gbl.AIDA.IProfile2D,
969 gbl.AIDA.IHistogram]
970
971 def __convertibleType(self, histo):
972 histoType = type(histo)
973 for t in self.aidaTypes:
974 if histoType == t:
975 return True
976 return False
977
978 def save(self, *args):
979 """
980 This function stores histograms on the file for future saving.
981 It takes an arbitrary number of AIDA or ROOT histograms or
982 a list of them.
983 """
984 if args:
985 if type(args[0]) == list:
986 histoList = args[0]
987 else:
988 histoList = args
989 for h in histoList:
990 if self.__convertibleType(h):
991 h = self.aida2root(h)
992 h.Write()
993
994 def close(self):
995 self.file.Write()
996 self.file.Close()
997
998
999 # =============================================================================
1000 if '__main__' == __name__:
1001 import sys
1002 print __doc__
1003 for o in __all__:
1004 print o
1005 print sys.modules[__name__].__dict__[o].__doc__
1006
1007
1008 # =============================================================================
1009 # The END
1010 # =============================================================================
GaudiPython.HistoUtils.HistoFile.file
file
Definition: HistoUtils.py:961
GaudiPython.HistoUtils._skewness_
def _skewness_(self)
Definition: HistoUtils.py:577
GaudiPython.HistoUtils._underflowIntegralFrac_
def _underflowIntegralFrac_(self)
Definition: HistoUtils.py:739
GaudiPython.HistoUtils._nEntriesFracErr_
def _nEntriesFracErr_(self, i1, i2=-10000000)
Definition: HistoUtils.py:803
GaudiPython.HistoUtils._getHistoSvc
def _getHistoSvc(kwargs)
Definition: HistoUtils.py:79
GaudiPython.HistoUtils._to_root_
def _to_root_(self)
Definition: HistoUtils.py:481
GaudiPython.HistoUtils.HistoFile.close
def close(self)
Definition: HistoUtils.py:994
GaudiPython.HistoUtils.getAsAIDA
def getAsAIDA(path, kwargs)
Definition: HistoUtils.py:332
GaudiPython.HistoUtils._sumBinHeightErr_
def _sumBinHeightErr_(self)
Definition: HistoUtils.py:674
GaudiPython.HistoUtils.HistoFile.__init__
def __init__(self, fileName)
Definition: HistoUtils.py:960
GaudiPython.HistoUtils._sumAllBinHeightErr_
def _sumAllBinHeightErr_(self)
Definition: HistoUtils.py:683
GaudiPython.HistoUtils.book
def book(args, kwargs)
Definition: HistoUtils.py:111
GaudiPython.HistoUtils.HID
HID
Definition: HistoUtils.py:47
GaudiPython.HistoUtils._overflowIntegralFracErr_
def _overflowIntegralFracErr_(self)
Definition: HistoUtils.py:731
GaudiPython.HistoUtils.getAsROOT
def getAsROOT(path, kwargs)
Definition: HistoUtils.py:357
GaudiPython.HistoUtils._path_
def _path_(self)
Definition: HistoUtils.py:882
GaudiPython.HistoUtils._overflowEntriesFrac_
def _overflowEntriesFrac_(self)
Definition: HistoUtils.py:690
GaudiPython.HistoUtils._nEff_
def _nEff_(self)
Definition: HistoUtils.py:632
GaudiPython.HistoUtils._moment_
def _moment_(self, order, value=0)
Definition: HistoUtils.py:518
GaudiPython.HistoUtils._kurtosisErr_
def _kurtosisErr_(self)
Definition: HistoUtils.py:619
GaudiPython.HistoUtils._nEntriesFrac_
def _nEntriesFrac_(self, i1, i2=-10000000)
Definition: HistoUtils.py:781
GaudiPython.HistoUtils.aida2root
aida2root
Definition: HistoUtils.py:476
GaudiPython.HistoUtils._mean_
def _mean_(self)
Definition: HistoUtils.py:640
GaudiPython.HistoUtils._meanErr_
def _meanErr_(self)
Definition: HistoUtils.py:648
GaudiPython.HistoUtils._kurtosis_
def _kurtosis_(self)
Definition: HistoUtils.py:605
GaudiPython.HistoUtils._skewnessErr_
def _skewnessErr_(self)
Definition: HistoUtils.py:591
gaudirun.type
type
Definition: gaudirun.py:133
GaudiPython.HistoUtils._underflowEntriesFrac_
def _underflowEntriesFrac_(self)
Definition: HistoUtils.py:706
GaudiPython.HistoUtils._overflowIntegralFrac_
def _overflowIntegralFrac_(self)
Definition: HistoUtils.py:723
GaudiPython.HistoUtils._overflowEntriesFracErr_
def _overflowEntriesFracErr_(self)
Definition: HistoUtils.py:698
GaudiPython.HistoUtils.HistoFile.aida2root
aida2root
Definition: HistoUtils.py:963
GaudiPython.HistoUtils.HistoFile
Definition: HistoUtils.py:943
GaudiPython.HistoUtils._rmsErr_
def _rmsErr_(self)
Definition: HistoUtils.py:665
GaudiPython.Bindings
Definition: Bindings.py:1
GaudiPython.HistoUtils.bookProf
def bookProf(args, kwargs)
Definition: HistoUtils.py:252
GaudiPython.HistoUtils.HistoFile.save
def save(self, args)
Definition: HistoUtils.py:978
GaudiPython.HistoUtils._underflowEntriesFracErr_
def _underflowEntriesFracErr_(self)
Definition: HistoUtils.py:714
GaudiPython.HistoUtils._centralMomentErr_
def _centralMomentErr_(self, order)
Definition: HistoUtils.py:562
fun
double fun(const std::vector< double > &x)
Definition: PFuncTest.cpp:26
GaudiPython.HistoUtils.fill
def fill(histo, data, fun=lambda x:x, cut=lambda x:True, kwargs)
Definition: HistoUtils.py:383
GaudiPython.HistoUtils._getEvtSvc
def _getEvtSvc(kwargs)
Definition: HistoUtils.py:95
GaudiPython.HistoUtils._nEntries_
def _nEntries_(self, i1, i2=-10000000)
Definition: HistoUtils.py:759
GaudiPython.HistoUtils._momentErr_
def _momentErr_(self, order)
Definition: HistoUtils.py:533
GaudiPython.HistoUtils._centralMoment_
def _centralMoment_(self, order)
Definition: HistoUtils.py:547
GaudiPython.HistoUtils._underflowIntegralFracErr_
def _underflowIntegralFracErr_(self)
Definition: HistoUtils.py:747
GaudiPython.HistoUtils.__dumpHisto__
def __dumpHisto__(histo, args)
Definition: HistoUtils.py:903
GaudiPython.HistoUtils._getAppMgr
def _getAppMgr(kwargs)
Definition: HistoUtils.py:56
GaudiPython.Bindings.AppMgr
Definition: Bindings.py:883
GaudiPython.HistoUtils.HistoFile.aidaTypes
aidaTypes
Definition: HistoUtils.py:964
GaudiPython.HistoUtils.HistoFile.__convertibleType
def __convertibleType(self, histo)
Definition: HistoUtils.py:971
GaudiPython.HistoUtils._rms_
def _rms_(self)
Definition: HistoUtils.py:657