def write_workspaces(path, prefix, year_mass_category_channel,
controls=None,
silence=False):
log.info("writing workspaces ...")
if controls is None:
controls = []
if not os.path.exists(path):
mkdir_p(path)
for year, mass_category_channel in year_mass_category_channel.items():
# write workspaces for each year
for mass, category_channel in mass_category_channel.items():
if isinstance(controls, dict):
if isinstance(controls[year], dict):
mass_controls = controls[year][mass].values()
else:
mass_controls = controls[year]
else:
mass_controls = controls
channels = []
# make workspace for each category
# include the control region in each
for category, channel in category_channel.items():
name = "{0}_{1}_{2}_{3}".format(
prefix, year % 1000, category, mass)
log.info("writing {0} ...".format(name))
# make workspace
measurement = histfactory.make_measurement(
name, [channel] + mass_controls,
POI=POI,
const_params=CONST_PARAMS)
workspace = histfactory.make_workspace(measurement, name=name,
silence=silence)
with root_open(os.path.join(path, '{0}.root'.format(name)),
'recreate') as workspace_file:
workspace.Write()
# mu=1 for Asimov data
#measurement.SetParamValue('SigXsecOverSM', 1)
histfactory.write_measurement(measurement,
root_file=workspace_file,
xml_path=os.path.join(path, name),
silence=silence)
channels.append(channel)
# make combined workspace
name = "{0}_{1}_combination_{2}".format(prefix, year % 1000, mass)
log.info("writing {0} ...".format(name))
measurement = histfactory.make_measurement(
name, channels + mass_controls,
POI=POI,
const_params=CONST_PARAMS)
workspace = histfactory.make_workspace(measurement, name=name,
silence=silence)
with root_open(os.path.join(path, '{0}.root'.format(name)),
'recreate') as workspace_file:
workspace.Write()
# mu=1 for Asimov data
#measurement.SetParamValue('SigXsecOverSM', 1)
histfactory.write_measurement(measurement,
root_file=workspace_file,
xml_path=os.path.join(path, name),
silence=silence)
# write combined workspaces over all years
years = year_mass_category_channel.keys()
if len(years) == 1:
return
masses = year_mass_category_channel[years[0]].keys()
categories = year_mass_category_channel[years[0]][masses[0]].keys()
for mass in masses:
if isinstance(controls, dict):
if isinstance(controls[year], dict):
mass_controls = [control for year in years
for control in controls[year][mass].values()]
else:
mass_controls = [control for year in years
for control in controls[year]]
else:
mass_controls = controls
channels = []
# make workspace for each category
# include the control region in each
# TODO: categories might be different across years
"""
for category in categories:
cat_channels = [year_mass_category_channel[year][mass][category]
for year in years]
name = "{0}_full_{1}_{2}".format(
prefix, category, mass)
log.info("writing {0} ...".format(name))
# make workspace
measurement = histfactory.make_measurement(
name, cat_channels + mass_controls,
POI=POI,
const_params=CONST_PARAMS)
workspace = histfactory.make_workspace(measurement, name=name,
silence=silence)
with root_open(os.path.join(path, '{0}.root'.format(name)),
'recreate') as workspace_file:
workspace.Write()
# mu=1 for Asimov data
#measurement.SetParamValue('SigXsecOverSM', 1)
histfactory.write_measurement(measurement,
root_file=workspace_file,
xml_path=os.path.join(path, name),
silence=silence)
channels.extend(cat_channels)
"""
channels = [chan for year in years
for chan in year_mass_category_channel[year][mass].values()]
# make combined workspace
name = "{0}_full_combination_{1}".format(prefix, mass)
log.info("writing {0} ...".format(name))
measurement = histfactory.make_measurement(
name, channels + mass_controls,
POI=POI,
const_params=CONST_PARAMS)
workspace = histfactory.make_workspace(measurement, name=name,
silence=silence)
with root_open(os.path.join(path, '{0}.root'.format(name)),
'recreate') as workspace_file:
workspace.Write()
# mu=1 for Asimov data
#measurement.SetParamValue('SigXsecOverSM', 1)
histfactory.write_measurement(measurement,
root_file=workspace_file,
xml_path=os.path.join(path, name),
silence=silence)
def write_workspaces(path, prefix, year_mass_category_channel,
controls=None, shapeControls=None,
silence=False):
log.info("writing workspaces ... for {0}".format(str(year_mass_category_channel)))
if controls is None:
controls = []
if shapeControls is None:
shapeControls = []
if not os.path.exists(path):
mkdir_p(path)
for year, mass_category_channel in year_mass_category_channel.items():
# write workspaces for each year
for mass, category_channel in mass_category_channel.items():
if isinstance(controls, dict):
log.info("controls are dicks")
if isinstance(controls[year], dict):
log.info("controls by year are dicks")
mass_controls = controls[year][mass].values()
else:
log.info("controls years are dicks")
mass_controls = controls[year]
else:
mass_controls = controls
if isinstance(shapeControls, dict):
log.info("shapeControls are dicks")
if isinstance(shapeControls[year], dict):
log.info("shapeControls by year are dicks")
shape_controls = shapeControls[year][mass].values()
else:
log.info("shapeControls years are dicks")
shape_controls = shapeControls[year]
else:
shape_controls = shapeControls
log.info("comparing {0} with {1}".format(str(mass_controls),str(shape_controls)))
channels = []
# make workspace for each category
# include the control region in each
nCategories=0
for category, channel in category_channel.items():
nCategories+=1
name = "{0}_{1}_{2}_{3}".format(
prefix, year % 1000, category, mass)
log.info("writing {0} ...".format(name))
if mass<0.:
parity='m'
else:
parity='p'
newname = "AllSys_cp_{}_0_{:02.0f}_{}".format(parity, abs(mass*100), prefix)
# print newname
measurement = histfactory.make_measurement(
newname, [channel] + mass_controls + shape_controls,
POI=POI,
const_params=CONST_PARAMS)
workspace = histfactory.make_workspace(measurement, name=newname,
silence=silence)
with root_open(os.path.join(path, '{0}.root'.format(newname)),
'recreate') as workspace_file:
workspace.Write()
# mu=1 for Asimov data
# measurement.SetParamValue('ATLAS_epsilon', 1)
histfactory.write_measurement(measurement,
root_file=workspace_file,
xml_path=os.path.join(path, newname),
silence=silence)
channels.append(channel)
log.info("length of channels is {0}".format(str(len(channels))))
def write_workspaces(path,
prefix,
year_mass_category_channel,
controls=None,
silence=False):
log.info("writing workspaces ...")
if controls is None:
controls = []
if not os.path.exists(path):
mkdir_p(path)
for year, mass_category_channel in year_mass_category_channel.items():
# write workspaces for each year
for mass, category_channel in mass_category_channel.items():
if isinstance(controls, dict):
if isinstance(controls[year], dict):
mass_controls = controls[year][mass].values()
else:
mass_controls = controls[year]
else:
mass_controls = controls
channels = []
# make workspace for each category
# include the control region in each
for category, channel in category_channel.items():
name = "{0}_{1}_{2}_{3}".format(prefix, year % 1000, category,
mass)
log.info("writing {0} ...".format(name))
# make workspace
measurement = histfactory.make_measurement(
name, [channel] + mass_controls,
POI=POI,
const_params=CONST_PARAMS)
workspace = histfactory.make_workspace(measurement,
name=name,
silence=silence)
with root_open(os.path.join(path, '{0}.root'.format(name)),
'recreate') as workspace_file:
workspace.Write()
# mu=1 for Asimov data
#measurement.SetParamValue('SigXsecOverSM', 1)
histfactory.write_measurement(measurement,
root_file=workspace_file,
xml_path=os.path.join(
path, name),
silence=silence)
channels.append(channel)
# make combined workspace
name = "{0}_{1}_combination_{2}".format(prefix, year % 1000, mass)
log.info("writing {0} ...".format(name))
measurement = histfactory.make_measurement(
name,
channels + mass_controls,
POI=POI,
const_params=CONST_PARAMS)
workspace = histfactory.make_workspace(measurement,
name=name,
silence=silence)
with root_open(os.path.join(path, '{0}.root'.format(name)),
'recreate') as workspace_file:
workspace.Write()
# mu=1 for Asimov data
#measurement.SetParamValue('SigXsecOverSM', 1)
histfactory.write_measurement(measurement,
root_file=workspace_file,
xml_path=os.path.join(
path, name),
silence=silence)
# write combined workspaces over all years
years = year_mass_category_channel.keys()
if len(years) == 1:
return
masses = year_mass_category_channel[years[0]].keys()
categories = year_mass_category_channel[years[0]][masses[0]].keys()
for mass in masses:
if isinstance(controls, dict):
if isinstance(controls[year], dict):
mass_controls = [
control for year in years
for control in controls[year][mass].values()
]
else:
mass_controls = [
control for year in years for control in controls[year]
]
else:
mass_controls = controls
channels = []
# make workspace for each category
# include the control region in each
# TODO: categories might be different across years
"""
for category in categories:
cat_channels = [year_mass_category_channel[year][mass][category]
for year in years]
name = "{0}_full_{1}_{2}".format(
prefix, category, mass)
log.info("writing {0} ...".format(name))
# make workspace
measurement = histfactory.make_measurement(
name, cat_channels + mass_controls,
POI=POI,
const_params=CONST_PARAMS)
workspace = histfactory.make_workspace(measurement, name=name,
silence=silence)
with root_open(os.path.join(path, '{0}.root'.format(name)),
'recreate') as workspace_file:
workspace.Write()
# mu=1 for Asimov data
#measurement.SetParamValue('SigXsecOverSM', 1)
histfactory.write_measurement(measurement,
root_file=workspace_file,
xml_path=os.path.join(path, name),
silence=silence)
channels.extend(cat_channels)
"""
channels = [
chan for year in years
for chan in year_mass_category_channel[year][mass].values()
]
# make combined workspace
name = "{0}_full_combination_{1}".format(prefix, mass)
log.info("writing {0} ...".format(name))
measurement = histfactory.make_measurement(name,
channels + mass_controls,
POI=POI,
const_params=CONST_PARAMS)
workspace = histfactory.make_workspace(measurement,
name=name,
silence=silence)
with root_open(os.path.join(path, '{0}.root'.format(name)),
'recreate') as workspace_file:
workspace.Write()
# mu=1 for Asimov data
#measurement.SetParamValue('SigXsecOverSM', 1)
histfactory.write_measurement(measurement,
root_file=workspace_file,
xml_path=os.path.join(path, name),
silence=silence)
def fit_norms(self, field, template, category, region=None,
max_iter=10, thresh=1e-7):
"""
Derive the normalizations of Ztt and QCD from a fit of some variable
"""
if region is None:
region = self.target_region
# initialize QCD and Ztautau normalizations to 50/50 of data yield
data_yield = self.data.events(category, region)[1].value
ztt_yield = self.ztautau.events(category, region)[1].value
qcd_yield = self.qcd.events(category, region)[1].value
qcd_scale = data_yield / (2 * qcd_yield)
ztt_scale = data_yield / (2 * ztt_yield)
qcd_scale_error = 0.
ztt_scale_error = 0.
qcd_scale_diff = 100.
ztt_scale_diff = 100.
it = 0
while (ztt_scale_diff > thresh or qcd_scale_diff > thresh) and it < max_iter:
it += 1
# keep fitting until normalizations converge
self.qcd.scale = qcd_scale
self.ztautau.scale = ztt_scale
channels = self.make_var_channels(
template, field, [category],
region, include_signal=False,
normalize=False)
# create a workspace
measurement = histfactory.make_measurement(
'normalization_{0}'.format(field), channels,
POI=None,
const_params=CONST_PARAMS)
workspace = histfactory.make_workspace(measurement, silence=True)
# fit workspace
minim = workspace.fit()
fit_result = minim.save()
# get fitted norms and errors
qcd = fit_result.floatParsFinal().find(
'ATLAS_norm_HH_{0:d}_QCD'.format(self.year))
ztt = fit_result.floatParsFinal().find(
'ATLAS_norm_HH_{0:d}_Ztt'.format(self.year))
qcd_scale_new = qcd.getVal()
qcd_scale_error = qcd.getError()
ztt_scale_new = ztt.getVal()
ztt_scale_error = ztt.getError()
qcd_scale_diff = abs(qcd_scale_new - 1.)
ztt_scale_diff = abs(ztt_scale_new - 1.)
qcd_scale_error *= qcd_scale / qcd_scale_new
qcd_scale *= qcd_scale_new
ztt_scale_error *= ztt_scale / ztt_scale_new
ztt_scale *= ztt_scale_new
self.qcd.scale = qcd_scale
self.ztautau.scale = ztt_scale
self.qcd.scale_error = qcd_scale_error
self.ztautau.scale_error = ztt_scale_error
return qcd_scale, qcd_scale_error, ztt_scale, ztt_scale_error
def fit_norms(self, field, template, category, region=None,
max_iter=10, thresh=1e-7):
"""
Derive the normalizations of Ztt and QCD from a fit of some variable
"""
if region is None:
region = self.target_region
# initialize QCD and Ztautau normalizations to 50/50 of data yield
data_yield = self.data.events(category, region)[1].value
ztt_yield = self.ztautau.events(category, region)[1].value
qcd_yield = self.qcd.events(category, region)[1].value
qcd_scale = data_yield / (2 * qcd_yield)
ztt_scale = data_yield / (2 * ztt_yield)
qcd_scale_error = 0.
ztt_scale_error = 0.
qcd_scale_diff = 100.
ztt_scale_diff = 100.
it = 0
while (ztt_scale_diff > thresh or qcd_scale_diff > thresh) and it < max_iter:
it += 1
# keep fitting until normalizations converge
self.qcd.scale = qcd_scale
self.ztautau.scale = ztt_scale
channels = self.make_var_channels(
template, field, [category],
region, include_signal=False,
normalize=False)
# create a workspace
measurement = histfactory.make_measurement(
'normalization_{0}'.format(field), channels,
POI=None,
const_params=CONST_PARAMS)
workspace = histfactory.make_workspace(measurement, silence=True)
# fit workspace
minim = workspace.fit()
fit_result = minim.save()
# get fitted norms and errors
qcd = fit_result.floatParsFinal().find(
'ATLAS_norm_HH_{0:d}_QCD'.format(self.year))
ztt = fit_result.floatParsFinal().find(
'ATLAS_norm_HH_{0:d}_Ztt'.format(self.year))
qcd_scale_new = qcd.getVal()
qcd_scale_error = qcd.getError()
ztt_scale_new = ztt.getVal()
ztt_scale_error = ztt.getError()
qcd_scale_diff = abs(qcd_scale_new - 1.)
ztt_scale_diff = abs(ztt_scale_new - 1.)
qcd_scale_error *= qcd_scale / qcd_scale_new
qcd_scale *= qcd_scale_new
ztt_scale_error *= ztt_scale / ztt_scale_new
ztt_scale *= ztt_scale_new
self.qcd.scale = qcd_scale
self.ztautau.scale = ztt_scale
self.qcd.scale_error = qcd_scale_error
self.ztautau.scale_error = ztt_scale_error
return qcd_scale, qcd_scale_error, ztt_scale, ztt_scale_error