def test_units_are_olcaunits(self):
import olca.units as olcaunits
""" Test that units are openlca reference units
"""
for c_ in flow_list_specs["flow_classes"]:
flowables = read_in_flowclass_file(c_, "Flowables")
# Get units and test that they are olca ref units
ref_units = pd.unique(flowables['Unit'])
for unt in ref_units:
olcaref = olcaunits.unit_ref(unt)
if olcaref is None:
log.debug(unt + ' in Flowables for class ' + c_ +
' is not an olca ref unit')
self.assertIsNotNone(olcaref)
try:
altunits_for_class = read_in_flowclass_file(
c_, 'FlowableAltUnits')
alt_units_with_ref = list(
altunits_for_class['Alternate Unit']) + list(
altunits_for_class['Reference Unit'])
alt_units_with_ref_unique = set(alt_units_with_ref)
for unt in alt_units_with_ref_unique:
olcaref = olcaunits.unit_ref(unt)
if olcaref is None:
log.debug(unt + ' in alt units for class ' + c_ +
' is not an olca ref unit')
self.assertIsNotNone(olcaref)
except FileNotFoundError:
altunits_for_class = None
c = {}
c['Context'] = i
for f in field_to_keep:
c[f] = row[f]
c_group.append(c)
class_contexts_list.extend(c_group)
class_contexts = pd.DataFrame(class_contexts_list)
# Merge this table now with the flowables and primary contexts with the full contexts per class, creating flows for each compartment relevant for that flow type, using major
flows = pd.merge(flowables_w_primary_contexts,
class_contexts,
on=['Class', 'Directionality', 'Environmental Media'])
#Drop duplicate flows if they exist
if len(flows[flows.duplicated(keep=False)]) > 0:
log.debug("Duplicate flows exist. They will be removed.")
flows = flows.drop_duplicates()
#If both the flowable and context are preferred, make this a preferred flow
flows['Preferred'] = 0
flows.loc[(flows['Flowable Preferred'] == 1) &
(flows['ContextPreferred'] == 1), 'Preferred'] = 1
#Drop unneeded columns
cols_to_drop = [
'Flowable Preferred', 'ContextPreferred', 'Directionality',
'Environmental Media'
]
flows = flows.drop(columns=cols_to_drop)
# Drop excluded flows based on CSV input file
import pandas as pd
import fedelemflowlist
from fedelemflowlist.globals import flowmappingpath, flowmapping_fields, log
#Add source name here. The .csv mapping file with this name must be in the flowmapping directory
#None can be used to update UUIDs in all mapping files
source = None
if __name__ == '__main__':
# Pull in mapping file
mapping = fedelemflowlist.get_flowmapping(source)
mapping_length = len(mapping)
all_flows = fedelemflowlist.get_flows()
all_flows = all_flows[['Flowable', 'Context', 'Flow UUID', 'Unit']]
mapping_w_flowinfo = pd.merge(mapping, all_flows,
left_on=['TargetFlowName', 'TargetFlowContext', 'TargetUnit'],
right_on=['Flowable', 'Context', 'Unit'])
mapping_w_flowinfo = mapping_w_flowinfo.drop(columns=['TargetFlowUUID', 'Flowable',
'Context', 'Unit'])
mapping_w_flowinfo = mapping_w_flowinfo.rename(columns={'Flow UUID': 'TargetFlowUUID'})
mapping_merged_len = len(mapping_w_flowinfo)
if mapping_length > mapping_merged_len:
log.debug("Not all flows were mapped to flows in the list")
flowmapping_order = list(flowmapping_fields.keys())
mapping_w_flowinfo = mapping_w_flowinfo[flowmapping_order]
for s in pd.unique(mapping_w_flowinfo['SourceListName']):
mapping = mapping_w_flowinfo[mapping_w_flowinfo['SourceListName'] == s]
mapping.to_csv(flowmappingpath + s + '.csv', index=False)