def _write_table(self, data_out, table):
data_out.mkdir(table.name)
data_out.cd(table.name)
# if no independent variables, use bins of unit width and centred on integers (1, 2, 3, etc.)
if not table.independent_variables and table.dependent_variables:
if table.dependent_variables[0]['values']:
table.independent_variables.append({'header': {'name': 'Bin number'}, 'values': []})
for i, value in enumerate(table.dependent_variables[0]['values']):
table.independent_variables[0]['values'].append({'low': i+0.5, 'high': i+1.5})
# if any non-numeric independent variable values, use bins of unit width and centred on integers (1, 2, 3, etc.)
# store original variables as alphanumeric labels to be passed to ROOT histograms
for ii, independent_variable in enumerate(table.independent_variables):
if False in ObjectWrapper.is_number_var(independent_variable):
independent_variable_bins = \
{'header': {'name': independent_variable['header']['name'] + ' bin'},
'values': [], 'labels': []}
for i, value in enumerate(independent_variable['values']):
independent_variable_bins['values'].append({'low': i + 0.5, 'high': i + 1.5})
if 'value' in value:
independent_variable_bins['labels'].append(str(value['value']))
else:
independent_variable_bins['labels'].append(str(value['low']) + '-' + str(value['high']))
table.independent_variables[ii] = independent_variable_bins
if self.hepdata_doi:
table_doi = 'doi:' + self.hepdata_doi + '/t' + str(table.index)
else:
table_doi = table.name
f = ObjectFactory(self.class_list, table.independent_variables, table.dependent_variables)
for graph in f.get_next_object():
graph.SetTitle(table_doi)
graph.Write()
def _write_table(self, data_out, table):
# if any non-numeric independent variables, use bins of unit width and centred on integers (1, 2, 3, etc.)
for ii, independent_variable in enumerate(table.independent_variables):
if False in ObjectWrapper.is_number_var(independent_variable):
for i, value in enumerate(independent_variable['values']):
table.independent_variables[ii]['values'][i] = {
'low': i + 0.5,
'high': i + 1.5
}
table_num = str(table.index)
if self.hepdata_doi:
table_doi = 'doi:' + self.hepdata_doi + '/t' + table_num
else:
table_doi = table.name
f = ObjectFactory(self.class_list, table.independent_variables,
table.dependent_variables)
for idep, graph in enumerate(f.get_next_object()):
rivet_identifier = 'd' + table_num.zfill(2) + '-x01-y' + str(
idep + 1).zfill(2)
# Allow the standard Rivet identifier to be overridden by a custom value specified in the qualifiers.
if 'qualifiers' in table.dependent_variables[idep]:
for qualifier in table.dependent_variables[idep]['qualifiers']:
if qualifier['name'] == 'Custom Rivet identifier':
rivet_identifier = qualifier['value']
rivet_path = '/REF/' + self.rivet_analysis_name + '/' + rivet_identifier
graph.setTitle(table_doi)
graph.setPath(rivet_path)
graph.setAnnotation('IsRef', '1')
yoda.core.writeYODA(graph, data_out)
data_out.write('\n')
def match(cls, independent_variables_map, dependent_variable):
if not ObjectWrapper.match(independent_variables_map, dependent_variable):
return False
elif len(independent_variables_map) == cls.dim:
for independent_variable in independent_variables_map:
if not independent_variable['values']:
return False
return True
return False
def match(cls, independent_variables_map, dependent_variable):
if not ObjectWrapper.match(independent_variables_map, dependent_variable):
return False
elif len(independent_variables_map) == cls.dim:
for independent_variable in independent_variables_map:
if not independent_variable['values']:
return False
return True
return False
def _write_table(self, data_out, table):
data_out.mkdir(
table.name.replace('/', '-').replace('$', '').replace('\\', ''))
data_out.cd(
table.name.replace('/', '-').replace('$', '').replace('\\', ''))
# if no independent variables, use bins of unit width and centred on integers (1, 2, 3, etc.)
if not table.independent_variables and table.dependent_variables:
if table.dependent_variables[0]['values']:
table.independent_variables.append({
'header': {
'name': 'Bin number'
},
'values': []
})
for i, value in enumerate(
table.dependent_variables[0]['values']):
table.independent_variables[0]['values'].append({
'low':
i + 0.5,
'high':
i + 1.5
})
# if any non-numeric independent variable values, use bins of unit width and centred on integers (1, 2, 3, etc.)
# store original variables as alphanumeric labels to be passed to ROOT histograms
for ii, independent_variable in enumerate(table.independent_variables):
if False in ObjectWrapper.is_number_var(independent_variable):
independent_variable_bins = \
{'header': {'name': independent_variable['header']['name'] + ' bin'},
'values': [], 'labels': []}
for i, value in enumerate(independent_variable['values']):
independent_variable_bins['values'].append({
'low': i + 0.5,
'high': i + 1.5
})
if 'value' in value:
independent_variable_bins['labels'].append(
str(value['value']))
else:
independent_variable_bins['labels'].append(
str(value['low']) + '-' + str(value['high']))
table.independent_variables[ii] = independent_variable_bins
if self.hepdata_doi:
table_doi = 'doi:' + self.hepdata_doi + '/t' + str(table.index)
else:
table_doi = table.name
f = ObjectFactory(self.class_list, table.independent_variables,
table.dependent_variables)
for graph in f.get_next_object():
graph.SetTitle(table_doi)
graph.Write()
def _write_table(self, data_out, table):
# if any non-numeric independent variables, use bins of unit width and centred on integers (1, 2, 3, etc.)
for ii, independent_variable in enumerate(table.independent_variables):
if False in ObjectWrapper.is_number_var(independent_variable):
for i, value in enumerate(independent_variable['values']):
table.independent_variables[ii]['values'][i] = {'low': i + 0.5, 'high': i + 1.5}
table_num = str(table.index)
if self.hepdata_doi:
table_doi = 'doi:' + self.hepdata_doi + '/t' + table_num
else:
table_doi = table.name
f = ObjectFactory(self.class_list, table.independent_variables, table.dependent_variables)
for idep, graph in enumerate(f.get_next_object()):
graph.title = table_doi
graph.path = '/REF/' + self.rivet_analysis_name + '/' \
+ 'd' + table_num.zfill(2) + '-x01-y' + str(idep + 1).zfill(2)
graph.setAnnotation('IsRef', '1')
yoda.core.writeYODA(graph, data_out)
def _write_table(self, data_out, table):
# if any non-numeric independent variables, use bins of unit width and centred on integers (1, 2, 3, etc.)
for ii, independent_variable in enumerate(table.independent_variables):
if False in ObjectWrapper.is_number_var(independent_variable):
for i, value in enumerate(independent_variable['values']):
table.independent_variables[ii]['values'][i] = {'low': i + 0.5, 'high': i + 1.5}
table_num = str(table.index)
if self.hepdata_doi:
table_doi = 'doi:' + self.hepdata_doi + '/t' + table_num
else:
table_doi = table.name
f = ObjectFactory(self.class_list, table.independent_variables, table.dependent_variables)
for idep, graph in enumerate(f.get_next_object()):
graph.title = table_doi
graph.path = '/REF/' + self.rivet_analysis_name + '/' \
+ 'd' + table_num.zfill(2) + '-x01-y' + str(idep + 1).zfill(2)
graph.setAnnotation('IsRef', '1')
yoda.core.writeYODA(graph, data_out)