def _write_flows(self, pw: pack.Writer):
altflowlist = fedelemflowlist.get_alt_conversion()
for _, row in self.flow_list.iterrows():
description = "From FedElemFlowList_" + flow_list_specs[
'list_version'] + '.'
flow_class = row.get("Class")
if flow_class is not None:
description += " Flow Class: %s." % flow_class
preferred = row.get("Preferred", 0)
if preferred == 1 or preferred == "1":
description += " Preferred flow."
else:
description += " Not a preferred flow."
flow = olca.Flow()
flow.description = description
flow.id = row["Flow UUID"]
flow.name = row["Flowable"]
flow.cas = row.get("CAS No", None)
flow.formula = row.get("Formula", None)
flow.version = flow_list_specs['list_version']
flow.last_change = datetime.datetime.now().isoformat()
flow.flow_type = olca.FlowType.ELEMENTARY_FLOW
context_uid = self._context_uids.get(row['Context'].lower())
if context_uid is not None:
flow.category = olca.ref(olca.Category, context_uid)
fp = olca.FlowPropertyFactor()
fp.reference_flow_property = True
fp.conversion_factor = 1.0
fp.flow_property = units.property_ref(row["Unit"])
if fp.flow_property is None:
log.warning("unknown unit %s in flow %s", row["Unit"],
row["Flow UUID"])
flow.flow_properties = [fp]
#Add in alternate unit flow propert(ies), if an alternate unit exists
#in the flows list, uses short list of altflowlist to assign one or more
#alternate units
if row["AltUnit"] is not None:
#create dataframe of all alternate units for this flowable
altunits = altflowlist[altflowlist['Flowable'] ==
row["Flowable"]]
for i, alternate in altunits.iterrows():
altfp = olca.FlowPropertyFactor()
altfp.reference_flow_property = False
altfp.conversion_factor = alternate[
'AltUnitConversionFactor']
altfp.flow_property = units.property_ref(
alternate["AltUnit"])
if altfp.flow_property is None:
log.warning("unknown altunit %s in flow %s",
alternate["AltUnit"], row["Flow UUID"])
else:
flow.flow_properties.append(altfp)
pw.write(flow)
def get(subset=None) -> pd.DataFrame:
"""
Returns a dataframe of inventory based methods.
:param subset: a list of dictionary keys from available inventories, if
none selected all availabile inventories will be generated
:return: df in standard LCIAmethod format
"""
method = df.data_frame(list())
method['Characterization Factor'] = pd.to_numeric(
method['Characterization Factor'])
if subset == None:
list_of_inventories = subsets.get_subsets()
else:
list_of_inventories = subset
alt_units = flowlist.get_alt_conversion()
for inventory in list_of_inventories:
flows = flowlist.get_flows(subset=inventory)
flows.drop([
'Formula', 'Synonyms', 'Class', 'External Reference', 'Preferred',
'AltUnit', 'AltUnitConversionFactor'
],
axis=1,
inplace=True)
flows['Indicator'] = inventory
flows['Indicator unit'] = subsets.get_inventory_unit(inventory)
flows['Characterization Factor'] = 1
# Apply unit conversions where flow unit differs from indicator unit
flows_w_conversion = pd.merge(
flows,
alt_units,
how='left',
left_on=['Flowable', 'Indicator unit', 'Unit'],
right_on=['Flowable', 'AltUnit', 'Unit'])
flows_w_conversion.loc[(flows_w_conversion['AltUnit'] ==
flows_w_conversion['Indicator unit']),
'Characterization Factor'] = flows_w_conversion[
'AltUnitConversionFactor']
flows_w_conversion.drop(
['AltUnit', 'AltUnitConversionFactor', 'InverseConversionFactor'],
axis=1,
inplace=True)
method = pd.concat([method, flows_w_conversion], ignore_index=True)
method['Method'] = 'Inventory'
return method
Requires target unit to be the primary unit. Existing conversion factor must be
set to 1 to avoid replacing manual conversion factors. Mapping file must already
conform to mapping format.
"""
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 add conversions in all mapping files
source = 'ReCiPe2016'
if __name__ == '__main__':
# Pull in mapping file
mapping = fedelemflowlist.get_flowmapping(source)
conversions = fedelemflowlist.get_alt_conversion()
# merge in conversion factors where source unit = alternate unit
mapping_w_conversion = pd.merge(
mapping,
conversions,
how='left',
left_on=['TargetFlowName', 'SourceUnit', 'TargetUnit'],
right_on=['Flowable', 'AltUnit', 'Unit'])
# update conversion factor where current conversion is 1 and the updated conversion exists
converted1 = mapping_w_conversion['InverseConversionFactor'].notnull()
converted2 = mapping_w_conversion['ConversionFactor'] == 1
mapping_w_conversion['Convert'] = converted1 & converted2
mapping_w_conversion.loc[
(mapping_w_conversion['Convert'] == True),
'ConversionFactor'] = mapping_w_conversion['InverseConversionFactor']
converted = mapping_w_conversion['Convert'].sum()