def get_mapped_method(method_id, indicators=None, methods=None):
"""Obtains a mapped method stored as parquet, if that file does not exist
locally, it is generated"""
method_id = util.check_as_class(method_id)
mapped_method = util.read_method(method_id)
if mapped_method is None:
util.log.info('generating ' + method_id.name)
method = get_method(method_id)
if 'mapping' in method_id.get_metadata():
mapping_system = method_id.get_metadata()['mapping']
case_insensitive = method_id.get_metadata()['case_insensitivity']
if case_insensitive:
method['Flowable'] = method['Flowable'].str.lower()
mapped_method = map_flows(method, system=mapping_system, case_insensitive=case_insensitive)
mapped_method = util.collapse_indicators(mapped_method)
util.store_method(mapped_method, method_id)
else:
mapped_method = method
if indicators is not None:
mapped_method = mapped_method[mapped_method['Indicator'].isin(indicators)]
if len(mapped_method) == 0:
util.log.error('indicator not found')
if methods is not None:
mapped_method = mapped_method[mapped_method['Method'].isin(methods)]
if len(mapped_method) == 0:
util.log.error('specified method not found')
return mapped_method
def main():
os.makedirs(outputpath, exist_ok=True)
log.basicConfig(level=log.INFO)
file = method.get_filename()
data = lciafmt.get_method(method, endpoint=False)
data_endpoint = lciafmt.get_method(method, endpoint=True)
data = data.append(data_endpoint, ignore_index=True)
# map the flows to the Fed.LCA commons flows
# set preserve_unmapped=True if you want to keep unmapped
# flows in the resulting data frame
mapping = method.get_metadata()['mapping']
mapped_data = lciafmt.map_flows(data, system=mapping)
mapped_data = collapse_indicators(mapped_data)
# write the result to parquet and JSON-LD
store_method(mapped_data, method)
for m in mapped_data['Method'].unique():
json_pack = outputpath + m + "_json.zip"
if os.path.exists(json_pack):
os.remove(json_pack)
data_for_json = mapped_data[mapped_data['Method'] == m]
lciafmt.to_jsonld(data_for_json, json_pack)
def main():
os.makedirs(outputpath, exist_ok=True)
log.basicConfig(level=log.INFO)
data = lciafmt.get_method(method, endpoint=False, summary=False)
data_endpoint = lciafmt.get_method(method,
endpoint=True,
summary=apply_summary)
data = data.append(data_endpoint, ignore_index=True)
# make flowables case insensitive to handle lack of consistent structure in source file
data['Flowable'] = data['Flowable'].str.lower()
# map the flows to the Fed.LCA commons flows
# set preserve_unmapped=True if you want to keep unmapped
# flows in the resulting data frame
mapping = method.get_metadata()['mapping']
mapped_data = lciafmt.map_flows(data,
system=mapping,
case_insensitive=True)
# write the result to parquet and JSON-LD
store_method(mapped_data, method)
for m in mapped_data['Method'].unique():
mapped_data[mapped_data['Method'] == m].to_csv(
outputpath + m.replace('/', '_') + ".csv", index=False)
json_pack = outputpath + m.replace('/', '_') + "_json.zip"
if os.path.exists(json_pack):
os.remove(json_pack)
data_for_json = mapped_data[mapped_data['Method'] == m]
lciafmt.to_jsonld(data_for_json, json_pack)
def main():
os.makedirs(outputpath, exist_ok=True)
log.basicConfig(level=log.INFO)
file = method.get_filename()
data = lciafmt.get_method(method)
if mod is not None:
log.info("getting modified CFs")
modified_cfs=lciafmt.get_modification(mod,"TRACI2.1")
data = data.merge(modified_cfs,how='left',on=['Flowable','Context','Indicator'])
data.loc[data['Updated CF'].notnull(),'Characterization Factor']=data['Updated CF']
data = data.drop(columns=['Updated CF','Note'])
data['Method']="TRACI 2.1 ("+mod+" mod)"
# map the flows to the Fed.LCA commons flows
# set preserve_unmapped=True if you want to keep unmapped
# flows in the resulting data frame
mapping = method.get_metadata()['mapping']
mapped_data = lciafmt.map_flows(data, system=mapping)
# write the result to parquet and JSON-LD
store_method(mapped_data, method)
if mod is not None:
file=mod+"_"+file
json_pack = outputpath+file+"_json.zip"
if os.path.exists(json_pack):
os.remove(json_pack)
lciafmt.to_jsonld(mapped_data, json_pack)
def main():
log.debug('Subsets available: ' + ", ".join(map(str, fedefl.subset_list.get_subsets())))
subsets = None
inventory_methods = lciafmt.get_method(method_id='FEDEFL Inventory',subset=subsets)
store_method(inventory_methods, method)
save_json(method, inventory_methods)
def main():
os.makedirs(outputpath, exist_ok=True)
log.basicConfig(level=log.INFO)
file = method.get_filename()
log.info(fedefl.subset_list.get_subsets())
subsets = None
inventory_methods = lciafmt.get_method(method_id='FEDEFL Inventory',subset=subsets)
store_method(inventory_methods, method)
json_pack = outputpath+file+"_json.zip"
if os.path.exists(json_pack):
os.remove(json_pack)
def main():
data = lciafmt.get_method(method)
# map the flows to the Fed.LCA commons flows
# set preserve_unmapped=True if you want to keep unmapped
# flows in the resulting data frame
mapping = method.get_metadata()['mapping']
mapped_data = lciafmt.map_flows(data, system=mapping)
mapped_data = collapse_indicators(mapped_data)
# write the result to parquet and JSON-LD
store_method(mapped_data, method)
for m in mapped_data['Method'].unique():
save_json(method, mapped_data, m)
def main():
data = lciafmt.get_method(method)
if mod is not None:
log.info("getting modified CFs")
modified_cfs=get_modification(mod,"TRACI2.1")
data = data.merge(modified_cfs,how='left',on=['Flowable','Context','Indicator'])
data.loc[data['Updated CF'].notnull(),'Characterization Factor']=data['Updated CF']
data = data.drop(columns=['Updated CF','Note'])
data['Method']="TRACI 2.1 ("+mod+" mod)"
# map the flows to the Fed.LCA commons flows
# set preserve_unmapped=True if you want to keep unmapped
# flows in the resulting data frame
mapping = method.get_metadata()['mapping']
mapped_data = lciafmt.map_flows(data, system=mapping)
# write the result to parquet and JSON-LD
store_method(mapped_data, method)
save_json(method, mapped_data)
def main():
data = lciafmt.get_method(method, endpoint=True, summary=apply_summary)
# make flowables case insensitive to handle lack of consistent structure in source file
data['Flowable'] = data['Flowable'].str.lower()
# map the flows to the Fed.LCA commons flows
# set preserve_unmapped=True if you want to keep unmapped
# flows in the resulting data frame
mapping = method.get_metadata()['mapping']
mapped_data = lciafmt.map_flows(data,
system=mapping,
case_insensitive=True)
mapped_data = collapse_indicators(mapped_data)
# write the result to parquet and JSON-LD
store_method(mapped_data, method)
for m in mapped_data['Method'].unique():
save_json(method, mapped_data, m)