def test_add_impact_scores_to_act_existing_db(data_for_testing):
"""Test adding agg dataset to existing database"""
Database('agg').register()
assert 'agg' in databases
assert len(Database('agg')) == 0
add_impact_scores_to_act(act_code='A',
agg_db='agg',
up_db='techno_UP',
selected_methods=[
data_for_testing['m1_name'],
data_for_testing['m2_name']
],
biosphere='biosphere',
overwrite=False,
create_ef_on_the_fly=True,
create_agg_database_on_fly=False)
assert 'agg' in databases
assert len(Database('agg')) == 1
assert ('agg', 'A') in Database('agg')
act = get_activity(('agg', 'A'))
act_bio_exc = {exc.input.key: exc['amount'] for exc in act.biosphere()}
assert len(act_bio_exc) == 2
lca = LCA({('techno_UP', 'A'): 1}, method=data_for_testing['m1_name'])
lca.lci()
lca.lcia()
assert lca.score == act_bio_exc[(
'biosphere', Method(data_for_testing['m1_name']).get_abbreviation())]
lca.switch_method(method=data_for_testing['m2_name'])
lca.lcia()
assert lca.score == act_bio_exc[(
'biosphere', Method(data_for_testing['m2_name']).get_abbreviation())]
def single_worker(self, sample):
'''
Computes the lcia impacts for the given data sampling corresponding to the initial morris problem.
Returns an array containing the aggregated score and then the impacts for each category.
'''
lca = LCA(self.demand, self.method)
lca.load_lci_data()
if lca.lcia:
lca.load_lcia_data()
if lca.weighting:
lca.load_weighting_data
for a_ij, value in zip(self.A_indices, sample[:len(self.A_indices)]):
#print('aij',tuple(a_ij),value, lca.technosphere_matrix[tuple(a_ij)])
lca.technosphere_matrix[tuple(a_ij)] = value
#print(lca.technosphere_matrix[tuple(a_ij)])
for b_ij, value in zip(self.B_indices, sample[len(self.A_indices):]):
#print('bij',tuple(b_ij),value)
lca.biosphere_matrix[tuple(b_ij)] = value
if not hasattr(lca, "demand_array"):
lca.build_demand_array()
import warnings
with warnings.catch_warnings():
warnings.simplefilter("ignore")
lca.lci_calculation()
if lca.lcia:
lca.lcia_calculation()
return np.concatenate(
([lca.score],
np.array(lca.characterized_inventory.sum(axis=1).ravel())[0]))
def test_aggregated_LCIA_single_method_augment_on_fly(data_for_testing):
projects.set_current(data_for_testing['project'])
assert "techno_UP" in databases
assert "biosphere" in databases
assert "techno_agg_LCIA" not in databases
assert data_for_testing['m1_name'] in methods
DatabaseAggregator(up_db_name="techno_UP",
agg_db_name="techno_agg_LCIA",
database_type='LCIA',
method_list=[data_for_testing['m1_name']],
biosphere='biosphere',
overwrite=False).generate()
assert "techno_agg_LCIA" in databases
assert len(Database("techno_agg_LCIA")) == len(Database("techno_UP"))
lca_unit_process = LCA({("techno_UP", "A"): 1},
method=data_for_testing['m1_name'])
lca_unit_process.lci()
lca_unit_process.lcia()
lca_LCIA = LCA({("techno_agg_LCIA", "A"): 1},
method=data_for_testing['m1_name'])
lca_LCIA.lci()
lca_LCIA.lcia()
assert lca_unit_process.score == lca_LCIA.score
def test_aggregated_LCIA_multiple_methods_already_augmented(data_for_testing):
projects.set_current(data_for_testing['project'])
assert "techno_UP" in databases
assert "biosphere" in databases
assert "techno_agg_LCIA" not in databases
assert data_for_testing['m1_name'] in methods
assert data_for_testing['m2_name'] in methods
assert len(methods) == 2
add_all_unit_score_exchanges_and_cfs(biosphere='biosphere')
agg_db = DatabaseAggregator(
up_db_name="techno_UP",
agg_db_name="techno_agg_LCIA",
database_type='LCIA',
method_list=[data_for_testing['m1_name'], data_for_testing['m2_name']],
biosphere='biosphere',
overwrite=False).generate()
assert "techno_agg_LCIA" in databases
assert len(Database("techno_agg_LCIA")) == len(Database("techno_UP"))
lca_unit_process = LCA({("techno_UP", "A"): 1},
method=data_for_testing['m1_name'])
lca_unit_process.lci()
lca_unit_process.lcia()
lca_LCIA = LCA({("techno_agg_LCIA", "A"): 1},
method=data_for_testing['m1_name'])
lca_LCIA.lci()
lca_LCIA.lcia()
assert lca_unit_process.score == lca_LCIA.score
score_in_B = lca_LCIA.biosphere_matrix[lca_LCIA.biosphere_dict[(
'biosphere', Method(data_for_testing['m1_name']).get_abbreviation())],
lca_LCIA.activity_dict[(
"techno_agg_LCIA", "A")]]
assert score_in_B == lca_LCIA.score
lca_unit_process = LCA({("techno_UP", "A"): 1},
method=data_for_testing['m2_name'])
lca_unit_process.lci()
lca_unit_process.lcia()
lca_LCIA = LCA({("techno_agg_LCIA", "A"): 1},
method=data_for_testing['m2_name'])
lca_LCIA.lci()
lca_LCIA.lcia()
assert lca_unit_process.score == lca_LCIA.score
score_in_B = lca_LCIA.biosphere_matrix[lca_LCIA.biosphere_dict[(
'biosphere', Method(data_for_testing['m2_name']).get_abbreviation())],
lca_LCIA.activity_dict[(
"techno_agg_LCIA", "A")]]
assert score_in_B == lca_LCIA.score
def test_aggregated_LCI(data_for_testing):
projects.set_current(data_for_testing['project'])
assert "techno_UP" in databases
assert "biosphere" in databases
assert "techno_agg_LCI" not in databases
assert data_for_testing['m1_name'] in methods
agg_db = DatabaseAggregator(up_db_name="techno_UP",
agg_db_name="techno_agg_LCI",
database_type='LCI',
method_list=[data_for_testing['m1_name']],
biosphere='biosphere',
overwrite=False).generate()
assert "techno_agg_LCI" in databases
assert len(Database("techno_agg_LCI")) == len(Database("techno_UP"))
lca_unit_process = LCA({("techno_UP", "A"): 1},
method=data_for_testing['m1_name'])
lca_unit_process.lci()
lca_unit_process.lcia()
lca_LCI = LCA({("techno_agg_LCI", "A"): 1},
method=data_for_testing['m1_name'])
lca_LCI.lci()
lca_LCI.lcia()
for act, col in lca_LCI.activity_dict.items():
row = lca_LCI.product_dict[act]
# Make sure production is 1
assert lca_LCI.technosphere_matrix[row, col] == 1.0
# Make sure other elements of the technosphere matrix are 0
#assert lca_LCI.technosphere_matrix.sum(axis=0)[col]==1
for ef, ef_row in lca_unit_process.biosphere_dict.items():
up_lci = lca_unit_process.inventory.sum(axis=1)[ef_row]
LCI_lci = lca_LCI.biosphere_matrix[lca_LCI.biosphere_dict[ef],
lca_LCI.activity_dict[(
"techno_agg_LCI", "A")]]
assert up_lci == LCI_lci
assert lca_unit_process.score == lca_LCI.score