def get_mc_name(run):
global all_ds
if all_ds is None:
from pwa.datasets import get_dataset_mapping
all_ds = get_dataset_mapping("mc*")
dataset = all_ds[int(run)]
return "{d.run}_{d.physicsshort}".format(d=dataset)
def mcrescale(self, params):
from pwa.datasets import get_dataset_mapping
from uncertainties import ufloat
datasets = get_dataset_mapping("mc*")
if not exists("pre_rescale"):
makedirs("pre_rescale")
match = re.compile("^.*?-P(.+)-R(\d+).root$").match
lumi = params.lumi
if params.uncert:
lumi = ufloat((lumi, lumi * (params.uncert / 100.)))
for filename in params.files:
m = match(filename)
if not m:
print "Skipping", filename
continue
period, run = m.groups()
dataset = datasets[int(run)]
effective_lumi = dataset.effective_luminosity
factor = dataset.reweight_factor(lumi)
print "Processing", filename, period, run, dataset.physicsshort, effective_lumi, factor
target_name = "mc_{d.run}_{d.physicsshort}.root".format(d=dataset)
prerescale_path = pjoin("pre_rescale", filename)
rename(filename, prerescale_path)
f_in = R.TFile(prerescale_path, "read")
f_out = R.TFile(target_name, "recreate")
from minty.tools.minty_rescale import rescale_dir
rescale_dir(f_in, f_out, factor.nominal_value)
f_out.cd()
save_ufloat("effective_lumi", effective_lumi)
save_ufloat("mc_weight", factor)