def fillIntoTree(out_tree, branches, cfg, hist_cfg, vcfgs, total_scale, plot, verbose, friend_func):
if isinstance(cfg, HistogramCfg):
# Loop over sub-cfgs and fill them
total_scale *= cfg.total_scale if cfg.total_scale else 1.
for sub_cfg in cfg.cfgs:
fillIntoTree(out_tree, branches, sub_cfg, cfg, vcfgs, total_scale, plot, verbose, friend_func)
return
file_name = '/'.join([cfg.ana_dir, cfg.dir_name, cfg.tree_prod_name, 'tree.root'])
# Attaches tree to plot
ttree = plot.readTree(file_name, cfg.tree_name, verbose=verbose, friend_func=friend_func)
norm_cut = hist_cfg.cut
shape_cut = hist_cfg.cut
if cfg.norm_cut:
norm_cut = cfg.norm_cut
if cfg.shape_cut:
shape_cut = cfg.shape_cut
full_weight = branches[-1]
weight = hist_cfg.weight
if cfg.weight_expr:
weight = '*'.join([weight, cfg.weight_expr])
if hist_cfg.weight:
norm_cut = '({c}) * {we}'.format(c=norm_cut, we=weight)
shape_cut = '({c}) * {we}'.format(c=shape_cut, we=weight)
# and this one too
sample_weight = cfg.scale * total_scale
if not cfg.is_data:
sample_weight *= hist_cfg.lumi*cfg.xsec/cfg.sumweights
formula = TTreeFormula('weight_formula', norm_cut, ttree)
formula.GetNdata()
# Add weight as tree variable
# Then loop over ttree
# And save this to the other tree
#
# Create TTreeFormulas for all vars
for var in vcfgs:
if var.drawname != var.name:
var.formula = TTreeFormula('formula'+var.name, var.drawname, ttree)
var.formula.GetNdata()
for i in xrange(ttree.GetEntries()):
ttree.GetEntry(i)
w = formula.EvalInstance()
if w == 0.:
continue
full_weight[0] = w * sample_weight
if abs(full_weight[0]) > 1000.:
print "WARNING, unusually large weight", w, sample_weight
import pdb; pdb.set_trace()
print '\nWeight:', full_weight[0]
print cfg.name
print norm_cut
for branch, var in zip(branches, vcfgs):
branch[0] = var.formula.EvalInstance() if hasattr(var, 'formula') else getattr(ttree, var.name)
out_tree.Fill()
if shape_cut != norm_cut:
print 'WARNING: different norm and shape cuts currently not supported in HistCreator.createTrees'
tree_out = tree_in.CopyTree(cut_str)
tree_out.Write()
# file_out.Close()
new_file_out = TFile(file_out_name.replace('.root', '_weight.root'),
'RECREATE')
weight_tree = tree_out.CloneTree(0)
scale = int_lumi * sample.xsec * sample.scale / sample.sumweights
full_weight = array('f', [0.])
new_b = weight_tree.Branch('full_weight', full_weight, 'full_weight/F')
formula = TTreeFormula('weight_formula', weight, tree_out)
formula.GetNdata()
# ATTENTION THIS MAY NOT WORK!
for i in xrange(tree_out.GetEntries()):
tree_out.GetEntry(i)
full_weight[0] = formula.EvalInstance() * scale
# print full_weight[0]
# new_b.Fill()
weight_tree.Fill()
# tree_out.Fill()
new_file_out.Write()
new_file_out.Close()
file_out.Close()
print 'Writing file', file_out_name
