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():
modulepath = os.path.dirname(os.path.realpath(__file__)).replace('\\', '/')
outputpath = modulepath + '/../output/'
os.makedirs(outputpath, exist_ok=True)
log.basicConfig(level=log.INFO)
data = lciafmt.get_method(lciafmt.Method.TRACI)
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
mapped_data = lciafmt.map_flows(data, system="TRACI2.1")
# write the result to JSON-LD and CSV
if mod is not None:
outputpath = outputpath + mod + "_"
mapped_data.to_csv(outputpath + "traci_2.1.csv", index=False)
json_pack = outputpath + "traci_2.1_json.zip"
if os.path.exists(json_pack):
os.remove(json_pack)
lciafmt.to_jsonld(mapped_data, json_pack)
def main():
modulepath = os.path.dirname(os.path.realpath(__file__)).replace('\\', '/')
outputpath = modulepath + '/../output/'
os.makedirs(outputpath, exist_ok=True)
log.basicConfig(level=log.INFO)
data = lciafmt.get_method(lciafmt.Method.RECIPE_2016)
#export lcia to csv before mapping
data.to_csv(outputpath + 'Recipe_source.csv', index=False)
# 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
mapped_data = lciafmt.map_flows(data,
system="ReCiPe2016",
case_insensitive=True)
# write the result to JSON-LD and CSV
for method in mapped_data['Method'].unique():
mapped_data[mapped_data['Method'] == method].to_csv(
outputpath + method.replace('/', '_') + ".csv", index=False)
json_pack = outputpath + "recipe_2016_json.zip"
if os.path.exists(json_pack):
os.remove(json_pack)
lciafmt.to_jsonld(mapped_data, 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():
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():
save_json(method, mapped_data, m)
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():
modulepath = os.path.dirname(os.path.realpath(__file__)).replace('\\', '/')
outputpath = modulepath + '/../output/'
os.makedirs(outputpath, exist_ok=True)
log.basicConfig(level=log.INFO)
data = lciafmt.get_method(lciafmt.Method.TRACI)
# 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
mapped_data = lciafmt.map_flows(data, system="TRACI2.1")
# write the result to JSON-LD and CSV
mapped_data.to_csv(outputpath + "traci_2.1.csv", index=False)
json_pack = outputpath + "traci_2.1_json.zip"
if os.path.exists(json_pack):
os.remove(json_pack)
lciafmt.to_jsonld(mapped_data, json_pack)
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)
and TRACI2.1 from the lcia_formatter
Requires lciafmt from lcia_formatter (https://github.com/USEPA/lciaformatter)
BEWARE this will replace the existing mapping file if it exists in /flowmapping
"""
import pandas as pd
import fedelemflowlist
from fedelemflowlist.globals import inputpath, flowmappingpath
lcia_name = 'TRACI2.1'
if __name__ == '__main__':
## Bring in TRACI flowables and contexts from the lcia_formatter
import lciafmt
lcia_lciafmt = lciafmt.get_method('TRACI 2.1')
""" due to substances listed more than once with different names
this replaces all instances of the Original Flowable with a New Flowable
based on a csv input file, otherwise zero values for CFs will override
when there are duplicate names"""
flowables_replace = pd.read_csv(inputpath + '/TRACI_2.1_replacement.csv')
for index, row in flowables_replace.iterrows():
orig = row['Original Flowable']
new = row['New Flowable']
lcia_lciafmt['Flowable'] = lcia_lciafmt['Flowable'].replace(orig, new)
""" due to substances listed more than once with the same name but different CAS
this replaces all instances of the Original Flowable with a New Flowable
based on a csv input file according to the CAS"""
flowables_split = pd.read_csv(inputpath + '/TRACI_2.1_split.csv')
for index, row in flowables_split.iterrows():
CAS = row['CAS']
