32 |
|
config.read(opts.config) |
33 |
|
anaTag = config.get("Analysis","tag") |
34 |
|
|
35 |
– |
TrainFlag = eval(config.get('Analysis','TrainFlag')) |
36 |
– |
|
37 |
– |
if TrainFlag: |
38 |
– |
MC_rescale_factor=2. |
39 |
– |
print 'I RESCALE BY 2.0' |
40 |
– |
else: MC_rescale_factor = 1. |
35 |
|
|
36 |
|
path = opts.path |
37 |
|
region = opts.region |
104 |
|
|
105 |
|
#GETALL AT ONCE |
106 |
|
|
107 |
< |
Plotter=HistoMaker(path,config,region,options,MC_rescale_factor) |
107 |
> |
Plotter=HistoMaker(path,config,region,options) |
108 |
|
|
109 |
|
#print '\nProducing Plot of %s\n'%vars[v] |
110 |
|
Lhistos = [[] for _ in range(0,len(vars))] |
139 |
|
for v in range(0,len(vars)): |
140 |
|
Lhistos[v].append(hTempList[v]) |
141 |
|
Ltyps[v].append(Group[job.subnames[subsample]]) |
142 |
+ |
print job.subnames[subsample] |
143 |
|
|
144 |
|
else: |
145 |
|
if job.name in samples: |
146 |
< |
#print job.getpath() |
146 |
> |
print job.name |
147 |
|
hTempList, typList = Plotter.getHistoFromTree(job) |
148 |
|
for v in range(0,len(vars)): |
149 |
|
Lhistos[v].append(hTempList[v]) |