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root/cvsroot/UserCode/VHbb/python/evaluateMVA.py

Comparing UserCode/VHbb/python/evaluateMVA.py (file contents):
Revision 1.4 by peller, Thu May 10 16:16:05 2012 UTC vs.
Revision 1.14 by peller, Thu Sep 27 07:34:24 2012 UTC

#	Line 9 | Line 9 | from copy import copy
9		#suppres the EvalInstace conversion warning bug
10		import warnings
11		warnings.filterwarnings( action='ignore', category=RuntimeWarning, message='creating converter.*' )
12	<	from ConfigParser import SafeConfigParser
13	<	from samplesinfo import sample
12	>	from optparse import OptionParser
13	>	from BetterConfigParser import BetterConfigParser
14	>	from samplesclass import sample
15		from mvainfos import mvainfo
16		import pickle
17		from progbar import progbar
#	Line 19 | Line 20 | from printcolor import printc
20		#CONFIGURE
21
22		#load config
23	<	config = SafeConfigParser()
24	<	config.read('./config')
23	>	#os.mkdir(path+'/sys')
24	>	argv = sys.argv
25	>	parser = OptionParser()
26	>	parser.add_option("-U", "--update", dest="update", default=0,
27	>	help="update infofile")
28	>	parser.add_option("-D", "--discr", dest="discr", default="",
29	>	help="discriminators to be added")
30	>	parser.add_option("-P", "--path", dest="path", default="",
31	>	help="path to samples")
32	>	parser.add_option("-S", "--samples", dest="names", default="",
33	>	help="samples you want to run on")
34	>	parser.add_option("-C", "--config", dest="config", default=[], action="append",
35	>	help="configuration file")
36	>	(opts, args) = parser.parse_args(argv)
37	>	if opts.config =="":
38	>	opts.config = "config"
39	>	config = BetterConfigParser()
40	>	#config.read('./config7TeV_ZZ')
41	>	config.read(opts.config)
42	>	anaTag = config.get("Analysis","tag")
43
44		#get locations:
45		Wdir=config.get('Directories','Wdir')
46	<
28	<	MVAdir=config.get('Directories','MVAdir')
46	>	MVASubdir=config.get('Directories','MVAdir')
47
48		#systematics
49		systematics=config.get('systematics','systematics')
50		systematics=systematics.split(' ')
51
52		#TreeVar Array
53	<	MVA_Vars={}
54	<	for systematic in systematics:
55	<	MVA_Vars[systematic]=config.get('treeVars',systematic)
56	<	MVA_Vars[systematic]=MVA_Vars[systematic].split(' ')
53	>	#MVA_Vars={}
54	>	#for systematic in systematics:
55	>	#    MVA_Vars[systematic]=config.get('treeVars',systematic)
56	>	#    MVA_Vars[systematic]=MVA_Vars[systematic].split(' ')
57
58		######################
59		#Evaluate multi: Must Have same treeVars!!!
60
61	<	Apath=sys.argv[1]
62	<	arglist=sys.argv[2] #RTight_blavla,bsbsb
61	>	Apath=opts.path
62	>	infofile = open(Apath+'/samples.info','r')
63	>	info = pickle.load(infofile)
64	>	infofile.close()
65	>	arglist=opts.discr #RTight_blavla,bsbsb
66
67	<	namelistIN=sys.argv[3]
67	>	namelistIN=opts.names
68		namelist=namelistIN.split(',')
69
70	<	doinfo=bool(int(sys.argv[4]))
70	>	doinfo=bool(int(opts.update))
71
72		MVAlist=arglist.split(',')
73	+	MVAdir=config.get('Directories','vhbbpath')
74
75		#CONFIG
76		#factory
#	Line 62 | Line 84 | factoryname=config.get('factory','factor
84		#MVAinfofiles=[]
85		MVAinfos=[]
86		for MVAname in MVAlist:
87	<	MVAinfofile = open(Wdir+'/weights/'+factoryname+'_'+MVAname+'.info','r')
87	>	MVAinfofile = open(MVAdir+'/data/'+factoryname+'_'+MVAname+'.info','r')
88		MVAinfos.append(pickle.load(MVAinfofile))
89		MVAinfofile.close()
90
#	Line 89 | Line 111 | for MVA in MVAlist:
111
112		#define variables and specatators
113		MVA_var_buffer = []
114	+	MVA_var_buffer4 = []
115		for i in range(len( MVA_Vars['Nominal'])):
116		MVA_var_buffer.append(array( 'f', [ 0 ] ))
117		for reader in readers:
#	Line 100 | Line 123 | for i in range(len( MVA_Vars['Nominal'])
123		#        reader.AddSpectator(spectators[i],MVA_spectator_buffer[i])
124		#Load raeder
125		for i in range(0,len(readers)):
126	<	readers[i].BookMVA(MVAinfos[i].MVAname,MVAinfos[i].getweightfile())
126	>	readers[i].BookMVA(MVAinfos[i].MVAname,MVAdir+'/data/'+MVAinfos[i].getweightfile())
127		#--> Now the MVA is booked
128
129		#Apply samples
#	Line 110 | Line 133 | infofile.close()
133
134		#eval
135		for job in Ainfo:
136	<
137	<	if job.name in namelist:
138	<	#get trees:
139	<	input = TFile.Open(job.getpath(),'read')
140	<	outfile = TFile.Open(job.path+'/'+MVAdir+job.prefix+job.identifier+'.root','recreate')
118	<	input.cd()
119	<	obj = ROOT.TObject
120	<	for key in ROOT.gDirectory.GetListOfKeys():
136	>	if eval(job.active):
137	>	if job.name in namelist:
138	>	#get trees:
139	>	input = TFile.Open(Apath+'/'+job.getpath(),'read')
140	>	outfile = TFile.Open(Apath+'/'+MVASubdir+job.prefix+job.identifier+'.root','recreate')
141		input.cd()
142	<	obj = key.ReadObj()
143	<	#print obj.GetName()
144	<	if obj.GetName() == job.tree:
145	<	continue
142	>	obj = ROOT.TObject
143	>	for key in ROOT.gDirectory.GetListOfKeys():
144	>	input.cd()
145	>	obj = key.ReadObj()
146	>	#print obj.GetName()
147	>	if obj.GetName() == job.tree:
148	>	continue
149	>	outfile.cd()
150	>	#print key.GetName()
151	>	obj.Write(key.GetName())
152	>	tree = input.Get(job.tree)
153	>	nEntries = tree.GetEntries()
154		outfile.cd()
155	<	#print key.GetName()
156	<	obj.Write(key.GetName())
157	<	tree = input.Get(job.tree)
158	<	nEntries = tree.GetEntries()
159	<	outfile.cd()
160	<	newtree = tree.CloneTree(0)
161	<
162	<	#MCs:
163	<	if job.type != 'DATA':
164	<	MVA_formulas={}
165	<	for systematic in systematics:
166	<	#print '\t\t - ' + systematic
167	<	MVA_formulas[systematic]=[]
155	>	newtree = tree.CloneTree(0)
156	>
157	>	#MCs:
158	>	if job.type != 'DATA':
159	>	MVA_formulas={}
160	>	MVA_formulas4={}
161	>	for systematic in systematics:
162	>	#print '\t\t - ' + systematic
163	>	MVA_formulas[systematic]=[]
164	>	MVA_formulas4[systematic]=[]
165	>	#create TTreeFormulas
166	>	for j in range(len( MVA_Vars['Nominal'])):
167	>	MVA_formulas[systematic].append(ROOT.TTreeFormula("MVA_formula%s_%s"%(j,systematic),MVA_Vars[systematic][j],tree))
168	>	MVA_formulas4[systematic].append(ROOT.TTreeFormula("MVA_formula4%s_%s"%(j,systematic),MVA_Vars['Nominal'][j]+'+('+MVA_Vars[systematic][j]+'-'+MVA_Vars['Nominal'][j]+')*4',tree))#HERE change
169	>	outfile.cd()
170	>	#Setup Branches
171	>	MVAbranches=[]
172	>	MVAbranches4=[]
173	>	for i in range(0,len(readers)):
174	>	MVAbranches.append(array('f',[0]*9))
175	>	MVAbranches4.append(array('f',[0]*9))
176	>	newtree.Branch(MVAinfos[i].MVAname,MVAbranches[i],'nominal:JER_up:JER_down:JES_up:JES_down:beff_up:beff_down:bmis_up:bmis_down/F')
177	>	newtree.Branch(MVAinfos[i].MVAname+'_4',MVAbranches4[i],'nominal:JER_up:JER_down:JES_up:JES_down:beff_up:beff_down:bmis_up:bmis_down/F')
178	>	print '\n--> ' + job.name +':'
179	>	#progbar setup
180	>	if nEntries >= longe:
181	>	step=int(nEntries/longe)
182	>	long=longe
183	>	else:
184	>	long=nEntries
185	>	step = 1
186	>	bar=progbar(long)
187	>	#Fill event by event:
188	>	for entry in range(0,nEntries):
189	>	if entry % step == 0:
190	>	bar.move()
191	>	#load entry
192	>	tree.GetEntry(entry)
193	>	for systematic in systematics:
194	>	for j in range(len( MVA_Vars['Nominal'])):
195	>	MVA_var_buffer[j][0] = MVA_formulas[systematic][j].EvalInstance()
196	>
197	>	for j in range(0,len(readers)):
198	>	MVAbranches[j][systematics.index(systematic)] = readers[j].EvaluateMVA(MVAinfos[j].MVAname)
199	>
200	>	for j in range(len( MVA_Vars['Nominal'])):
201	>	MVA_var_buffer[j][0] = MVA_formulas4[systematic][j].EvalInstance()
202	>
203	>	for j in range(0,len(readers)):
204	>	MVAbranches4[j][systematics.index(systematic)] = readers[j].EvaluateMVA(MVAinfos[j].MVAname)
205	>	#Fill:
206	>	newtree.Fill()
207	>	newtree.AutoSave()
208	>	outfile.Close()
209	>
210	>	#DATA:
211	>	if job.type == 'DATA':
212	>	#MVA Formulas
213	>	MVA_formulas_Nominal = []
214		#create TTreeFormulas
215		for j in range(len( MVA_Vars['Nominal'])):
216	<	MVA_formulas[systematic].append(ROOT.TTreeFormula("MVA_formula%s_%s"%(j,systematic),MVA_Vars[systematic][j],tree))
217	<	outfile.cd()
218	<	#Setup Branches
219	<	MVAbranches=[]
220	<	for i in range(0,len(readers)):
221	<	MVAbranches.append(array('f',[0]*9))
222	<	newtree.Branch(MVAinfos[i].MVAname,MVAbranches[i],'nominal:JER_up:JER_down:JES_up:JES_down:beff_up:beff_down:bmis_up:bmis_down/F')
223	<	print '\n--> ' + job.name +':'
224	<	#progbar setup
225	<	if nEntries >= longe:
226	<	step=int(nEntries/longe)
227	<	long=longe
228	<	else:
229	<	long=nEntries
230	<	step = 1
231	<	bar=progbar(long)
232	<	#Fill event by event:
233	<	for entry in range(0,nEntries):
234	<	if entry % step == 0:
235	<	bar.move()
236	<	#load entry
237	<	tree.GetEntry(entry)
238	<	for systematic in systematics:
216	>	MVA_formulas_Nominal.append(ROOT.TTreeFormula("MVA_formula%s_Nominal"%j, MVA_Vars['Nominal'][j],tree))
217	>	outfile.cd()
218	>	MVAbranches=[]
219	>	for i in range(0,len(readers)):
220	>	MVAbranches.append(array('f',[0]))
221	>	newtree.Branch(MVAinfos[i].MVAname,MVAbranches[i],'nominal/F')
222	>	newtree.Branch(MVAinfos[i].MVAname+'_4',MVAbranches[i],'nominal/F')
223	>	#progbar
224	>	print '\n--> ' + job.name +':'
225	>	if nEntries >= longe:
226	>	step=int(nEntries/longe)
227	>	long=longe
228	>	else:
229	>	long=nEntries
230	>	step = 1
231	>	bar=progbar(long)
232	>	#Fill event by event:
233	>	for entry in range(0,nEntries):
234	>	if entry % step == 0:
235	>	bar.move()
236	>	#load entry
237	>	tree.GetEntry(entry)
238	>	#nominal:
239		for j in range(len( MVA_Vars['Nominal'])):
240	<	MVA_var_buffer[j][0] = MVA_formulas[systematic][j].EvalInstance()
241	<
240	>	MVA_var_buffer[j][0] = MVA_formulas_Nominal[j].EvalInstance()
241	>
242		for j in range(0,len(readers)):
243	<	MVAbranches[j][systematics.index(systematic)] = readers[j].EvaluateMVA(MVAinfos[j].MVAname)
244	<	#Fill:
245	<	newtree.Fill()
246	<	newtree.AutoSave()
173	<	outfile.Close()
174	<
175	<	#DATA:
176	<	if job.type == 'DATA':
177	<	#MVA Formulas
178	<	MVA_formulas_Nominal = []
179	<	#create TTreeFormulas
180	<	for j in range(len( MVA_Vars['Nominal'])):
181	<	MVA_formulas_Nominal.append(ROOT.TTreeFormula("MVA_formula%s_Nominal"%j, MVA_Vars['Nominal'][j],tree))
182	<	outfile.cd()
183	<	MVAbranches=[]
184	<	for i in range(0,len(readers)):
185	<	MVAbranches.append(array('f',[0]))
186	<	newtree.Branch(MVAinfos[i].MVAname,MVAbranches[i],'nominal/F')
187	<	#progbar
188	<	print '\n--> ' + job.name +':'
189	<	if nEntries >= longe:
190	<	step=int(nEntries/longe)
191	<	long=longe
192	<	else:
193	<	long=nEntries
194	<	step = 1
195	<	bar=progbar(long)
196	<	#Fill event by event:
197	<	for entry in range(0,nEntries):
198	<	if entry % step == 0:
199	<	bar.move()
200	<	#load entry
201	<	tree.GetEntry(entry)
202	<	#nominal:
203	<	for j in range(len( MVA_Vars['Nominal'])):
204	<	MVA_var_buffer[j][0] = MVA_formulas_Nominal[j].EvalInstance()
205	<
206	<	for j in range(0,len(readers)):
207	<	MVAbranches[j][0]= readers[j].EvaluateMVA(MVAinfos[j].MVAname)
208	<	newtree.Fill()
209	<	newtree.AutoSave()
210	<	outfile.Close()
243	>	MVAbranches[j][0]= readers[j].EvaluateMVA(MVAinfos[j].MVAname)
244	>	newtree.Fill()
245	>	newtree.AutoSave()
246	>	outfile.Close()
247
248		print '\n'
249

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