def store_to_pool(self, stream_stack_n_data):
"""
Keep stacks and data histograms in histopool, for later use.
The stream has to be splitted in a stack and a data stream and to be
rejoined in the end.
"""
stream_stack_n_data = itertools.chain(stream_stack_n_data) # resolve grouping
stream_data, stream_stacks = gen.split_data_mc(stream_stack_n_data) # split (stacks are mc)
stream_stacks = gen.pool_store_items(stream_stacks) # store
stream_data = gen.pool_store_items(stream_data) # store
stream_stack_n_data = itertools.izip(stream_stacks, stream_data) # join stream again
return stream_stack_n_data
def store_to_pool(self, stream_stack_n_data):
"""
Keep stacks and data histograms in histopool, for later use.
The stream has to be splitted in a stack and a data stream and to be
rejoined in the end.
"""
stream_stack_n_data = itertools.chain(
stream_stack_n_data) # resolve grouping
stream_data, stream_stacks = gen.split_data_mc(
stream_stack_n_data) # split (stacks are mc)
stream_stacks = gen.pool_store_items(stream_stacks) # store
stream_data = gen.pool_store_items(stream_data) # store
stream_stack_n_data = itertools.izip(stream_stacks,
stream_data) # join stream again
return stream_stack_n_data
def set_up_stacking(self):
self.result.fitter = self.fitter.__class__.__name__
mc_tmplts = self.fetch_mc_templates()
self.n_templates = len(mc_tmplts)
settings.post_proc_dict[self.name+"_mc_tmplts"] = mc_tmplts[:]
# do fit procedure
self.fitted = gen.op.sum(self.fitted)
self.x_min, self.x_max = find_x_range(self.fitted.histo)
self.fitter.build_fit_function(
self.fitted, mc_tmplts, self.x_min, self.x_max
)
self.fitter.do_the_fit()
self.fitter.scale_templates_to_fit(mc_tmplts)
self.fitter.make_fit_result(self.result, mc_tmplts)
fit_textbox = self.make_fit_textbox()
textboxes = {mc_tmplts[0].name: fit_textbox}
self.canvas_decorators.append(
rnd.TextBoxDecorator(None, True, textbox_dict=textboxes)
)
tmplt_stacks = [gen.op.stack(mc_tmplts)]
stream_stack = [(tmplt_stacks[0], self.fitted)]
self.stream_stack = gen.pool_store_items(stream_stack)
del self.fitter
def set_up_stacking(self):
wrps = gen.pool_content()
wrps = gen.filter(
wrps,
{"analyzer": re.compile("CutFlow")}
)
wrps = gen.group(wrps)
stream_stack = gen.mc_stack_n_data_sum(
wrps,
use_all_data_lumi=True
)
def assign_name(wrp): wrp.name = "CombinedCutflow"
self.stream_stack = gen.pool_store_items(stream_stack, assign_name)
def run(self):
wrps = gen.fs_content()
wrps = gen.filter(
wrps,
{"analyzer": re.compile("CutFlow*")}
)
wrps = gen.filter_active_samples(wrps)
wrps = sorted(wrps, key = sample_key_func)
wrps = gen.load(wrps)
grps = gen.group(wrps, sample_key_func)
wrps = (self.combine_cutflow_histo(g) for g in grps)
wrps = gen.pool_store_items(wrps)
wrps = list(wrps)
self.result = wrps
count = len(wrps)
self.message("INFO: "+self.name+" stored "+str(count)+" histos in pool.")
def set_up_stacking(self):
stream_stack = gen.fs_mc_stack(self.filter_dict)
self.stream_stack = gen.pool_store_items(stream_stack)