def install_fixtures(self):
db = Database("a")
db.write(lci_fixture)
method = Method(("method", ))
method.register()
method.write(method_fixture)
return db, method
def test_fix_spatial_dictionaries(self):
# TODO: Fix
return
empty = Database("empty")
empty.register(depends=[], geocollections=["foo"])
method = Method(("a", "name"))
method.register(geocollections=["foo"])
rlca = RegionalizationBase({("empty", "nothing"): 1},
method=("a", "name"))
# No-op - `inv_spatial_dict` not yet set...
rlca.fix_spatial_dictionaries()
assert not getattr(rlca, "_mapped_spatial_dict", None)
self.assertFalse(hasattr(rlca, "inv_spatial_dict"))
geomapping.data = {"a": 1, "b": 2}
rlca.inv_spatial_dict = {"a": "foo"}
# Now it does something...
rlca.fix_spatial_dictionaries()
self.assertFalse(hasattr(rlca, "ia_spatial_dict"))
rlca.inv_spatial_dict = {1: "foo"}
rlca.ia_spatial_dict = {2: "bar"}
rlca.fix_spatial_dictionaries()
self.assertEqual(rlca.inv_spatial_dict, {"a": "foo"})
self.assertEqual(rlca.ia_spatial_dict, {"b": "bar"})
def write_methods(self, overwrite=False, verbose=True):
num_methods, num_cfs, num_unlinked = self.statistics(False)
if num_unlinked:
raise ValueError((u"Can't write unlinked methods ({} unlinked cfs)"
).format(num_unlinked))
for ds in self.data:
if ds["name"] in methods:
if overwrite:
del methods[ds["name"]]
else:
raise ValueError(
(u"Method {} already exists. Use "
u"``overwrite=True`` to overwrite existing methods"
).format(ds["name"]))
with warnings.catch_warnings():
warnings.simplefilter("ignore")
method = Method(ds["name"])
method.register(
description=ds["description"],
filename=ds["filename"],
unit=ds["unit"],
)
method.write(self._reformat_cfs(ds["exchanges"]))
method.process()
if verbose:
print(u"Wrote {} LCIA methods with {} characterization factors".
format(num_methods, num_cfs))
def activity_and_method():
database = DatabaseChooser("db")
database.write({
("db", "a"): {
'exchanges': [{
'input': ("db", "a"),
'amount': 2,
'type': 'production',
}, {
'input': ("db", "b"),
'amount': 3,
'type': 'technosphere',
}, {
'input': ("db", "c"),
'amount': 4,
'type': 'biosphere',
}],
'name': 'a'
},
("db", "b"): {'name': 'b'},
("db", "c"): {'name': 'c', 'type': 'biosphere'},
("db", "d"): {
'name': 'd',
'exchanges': [{
'input': ("db", "a"),
'amount': 5,
'type': 'technosphere'
}]
},
})
cfs = [(("db", "c"), 42)]
method = Method(("a method",))
method.register()
method.write(cfs)
return database.get("a"), method
def test_grouping_separate_unit(self):
biosphere_data = {
("biosphere", "1"): {
"categories": ["foo", "this"],
"exchanges": [],
"name": "some bad stuff",
"type": "emission",
"unit": "kg",
},
("biosphere", "2"): {
"categories": ["foo", "that"],
"exchanges": [],
"name": "some bad stuff",
"type": "emission",
"unit": "tonne",
},
}
biosphere = Database("biosphere")
biosphere.register(name="Tests", depends=[])
biosphere.write(biosphere_data)
method = Method(("test", "LCIA", "method"))
method.register(unit="points")
method.write([(("biosphere", "1"), 1.0, "GLO"),
(("biosphere", "2"), 2.0, "GLO")])
answer = {
("some bad stuff", "foo", "kg"): [1.0],
("some bad stuff", "foo", "tonne"): [2.0],
}
self.assertEqual(group_by_emissions(method), answer)
def test_health_check(self):
db = Database("a")
db.write(lci_fixture)
method = Method(("method",))
method.register()
method.write(method_fixture)
dhc = DHCMock("a").check()
def test_geocollections_mismatch(self):
inventory = Database("inventory")
inventory.register(geocollections=["places"])
method = Method(("a", "method"))
method.register(geocollections=['regions'])
with self.assertRaises(GeocollectionsMismatch):
LCA({("inventory", "foo"): 1}, method=("a", "method"))
def add_example_database(overwrite=True):
from ..importers.excel import (
assign_only_product_as_production,
convert_activity_parameters_to_list,
convert_uncertainty_types_to_integers,
csv_add_missing_exchanges_section,
csv_drop_unknown,
csv_numerize,
csv_restore_booleans,
csv_restore_tuples,
drop_falsey_uncertainty_fields_but_keep_zeros,
ExcelImporter,
set_code_by_activity_hash,
strip_biosphere_exc_locations,
)
if "Mobility example" in databases:
if not overwrite:
print("Example already imported, use `overwrite=True` to delete")
return
else:
del databases["Mobility example"]
if ("IPCC", "simple") in methods:
del methods[("IPCC", "simple")]
importer = ExcelImporter(
os.path.join(dirpath, "examples",
"sample_parameterized_database.xlsx"))
importer.strategies = [
csv_restore_tuples,
csv_restore_booleans,
csv_numerize,
csv_drop_unknown,
csv_add_missing_exchanges_section,
strip_biosphere_exc_locations,
set_code_by_activity_hash,
assign_only_product_as_production,
drop_falsey_uncertainty_fields_but_keep_zeros,
convert_uncertainty_types_to_integers,
convert_activity_parameters_to_list,
]
importer.apply_strategies()
importer.match_database(fields=['name'])
importer.write_database(activate_parameters=True)
group = "Mobility exchanges"
Group.delete().where(Group.name == group).execute()
group = Group.create(name=group)
for ds in Database("Mobility example"):
parameters.add_exchanges_to_group(group, ds)
parameters.recalculate()
ipcc = Method(("IPCC", "simple"))
ipcc.register()
ipcc.write([(("Mobility example", "CO2"), 1)])
def test_site_generic_method_error(self):
empty = Database("empty")
empty.register(depends=[], geocollections=[])
method = Method(("a", "name"))
method.register()
with self.assertRaises(SiteGenericMethod):
rlca = RegionalizationBase({("empty", "nothing"): 1},
method=("a", "name"))
rlca.get_ia_geocollections()
def test_missing_intersection_error(self):
empty = Database("empty")
empty.register(depends=[], geocollections=["foo"])
method = Method(("a", "name"))
method.register(geocollections=["bar"])
with self.assertRaises(MissingIntersection):
rlca = RegionalizationBase({("empty", "nothing"): 1},
method=("a", "name"))
rlca.inventory_geocollections = rlca.get_inventory_geocollections()
rlca.ia_geocollections = rlca.get_ia_geocollections()
rlca.needed_intersections()
def create_methods(self):
gw = [
[("b", "bad"), 1],
]
method = Method(("foo", ))
method.register()
method.write(gw)
method.process()
fake_dynamic_method = DynamicIAMethod("Dynamic foo")
fake_dynamic_method.register()
fake_dynamic_method.write({x[0]: x[1] for x in gw})
def build_databases():
Database("biosphere").write({
("biosphere", "1"): {'type': 'emission'},
("biosphere", "2"): {'type': 'emission'},
})
Database("test").write({
("test", "1"): {
'exchanges': [{
'amount': 0.5,
'minimum': 0.2,
'maximum': 0.8,
'input': ('test', "2"),
'type': 'technosphere',
'uncertainty type': 4 # Uniform
}, {
'amount': 100,
'minimum': 50,
'maximum': 500,
'input': ('biosphere', "1"),
'type': 'biosphere',
'loc': 100,
'scale': 20,
'uncertainty type': 3 # Normal
}],
'type': 'process',
},
("test", "2"): {
'exchanges': [{
'amount': -0.42,
'input': ('biosphere', "2"),
'type': 'biosphere',
}],
'type': 'process',
'unit': 'kg'
},
})
method = Method(("a", "method"))
method.register()
method.write([
(("biosphere", "1"), 1),
(("biosphere", "2"), {
'amount': 10,
'uncertainty type': 5, # Triangular
'loc': 10,
'minimum': 8,
'maximum': 15
}),
])
def activity_and_method():
database = DatabaseChooser("db")
database.write({
("db", "a"): {
"exchanges": [
{
"input": ("db", "a"),
"amount": 2,
"type": "production",
},
{
"input": ("db", "b"),
"amount": 3,
"type": "technosphere",
},
{
"input": ("db", "c"),
"amount": 4,
"type": "biosphere",
},
],
"name":
"a",
},
("db", "b"): {
"name": "b"
},
("db", "c"): {
"name": "c",
"type": "biosphere"
},
("db", "d"): {
"name":
"d",
"exchanges": [{
"input": ("db", "a"),
"amount": 5,
"type": "technosphere"
}],
},
})
cfs = [(("db", "c"), 42)]
method = Method(("a method", ))
method.register()
method.write(cfs)
return database.get("a"), method
def test_combine_methods(self):
d = Database("biosphere")
d.register(depends=[])
d.write(biosphere)
m1 = Method(("test method 1",))
m1.register(unit="p")
m1.write([(("biosphere", 1), 1, "GLO"), (("biosphere", 2), 2, "GLO")])
m2 = Method(("test method 2",))
m2.register(unit="p")
m2.write([(("biosphere", 2), 10, "GLO")])
combine_methods(("test method 3",), ("test method 1",), ("test method 2",))
cm = Method(("test method 3",))
self.assertEqual(
sorted(cm.load()),
[(("biosphere", 1), 1, "GLO"), (("biosphere", 2), 12, "GLO")],
)
self.assertEqual(methods[["test method 3"]]["unit"], "p")
def build_databases():
Database("biosphere").write({
("biosphere", "1"): {'type': 'emission'},
("biosphere", "2"): {'type': 'emission'},
})
Database("test").write({
("test", "1"): {
'exchanges': [{
'amount': 0.5,
'minimum': 0.2,
'maximum': 0.8,
'input': ('test', "2"),
'type': 'technosphere',
'uncertainty type': 4
}, {
'amount': 1,
'minimum': 0.5,
'maximum': 1.5,
'input': ('biosphere', "1"),
'type': 'biosphere',
'uncertainty type': 4
}],
'type': 'process',
},
("test", "2"): {
'exchanges': [{
'amount': 0.1,
'minimum': 0,
'maximum': 0.2,
'input': ('biosphere', "2"),
'type': 'biosphere',
'uncertainty type': 4
}],
'type': 'process',
'unit': 'kg'
},
})
method = Method(("a", "method"))
method.register()
method.write([
(("biosphere", "1"), 1),
(("biosphere", "2"), 2),
])
def to_worst_case_method(self,
name,
lower=None,
upper=None,
dynamic=True,
register=True):
"""Create a static LCA method using the worst case for each dynamic CF function.
Default time interval over which to test for maximum CF is `datetime.now()` to `datetime.now()+relativedelta(years=100)`.
Args:
* *name* (string): method name.
* *lower* (datetime, default=datetime(2010, 1, 1): lower bound of the interval to consider.
* *upper* (datetime, default=lower + relativedelta(years=100): upper bound of the interval to consider.
* *dynamic* (bool, default=True): If total CF function of time of emission
* *register* (bool, default=True): If to register the method
"""
kwargs = {'dynamic': dynamic}
if lower is not None:
kwargs['lower'] = lower
if upper is not None:
kwargs['upper'] = upper
with warnings.catch_warnings():
warnings.simplefilter("ignore")
worst_case_method = Method(tuple(name))
if worst_case_method.name not in methods:
worst_case_method.register(dynamic_method=self.name)
data = self.load()
data.update(self.create_functions())
# for now just characterize all the 'Carbon dioxide, in air' to be sure they are not skipped
# should think better on how to deal with this
method = [[('biosphere3', 'cc6a1abb-b123-4ca6-8f16-38209df609be'),
abs(get_maximum_value(value, **kwargs))]
if key == ('static_forest', "C_biogenic") else
[key, abs(get_maximum_value(value, **kwargs))]
for key, value in data.items()]
#needed for GWP function to avoid registration every time
if not register:
return method
worst_case_method.write(method)
worst_case_method.process() #GIU: guess not needed anymore right?
return worst_case_method
def add_method(add_biosphere):
method = Method(("test method", ))
method.register(unit="kg")
method.write([(("biosphere", 1), 6, "foo"), (("biosphere", 2), 5, "bar")])
def import_data(self):
biosphere_data = {
('biosphere', 'F'): {
'type': 'emission',
'exchanges': [],
},
('biosphere', 'G'): {
'type': 'emission',
'exchanges': [],
}
}
biosphere = Database("biosphere")
biosphere.register(depends=[], geocollections=[])
biosphere.write(biosphere_data)
inventory_data = {
('inventory', 'U'): {
'type':
'process',
'location':
"L",
'exchanges': [
{
'input': ('biosphere', 'F'),
'type': 'biosphere',
'amount': 1
},
{
'input': ('biosphere', 'G'),
'type': 'biosphere',
'amount': 1
},
]
},
('inventory', 'V'): {
'type': 'process',
'location': "M",
'exchanges': []
},
('inventory', 'X'): {
'type': 'process',
'location': "N",
'exchanges': []
},
('inventory', 'Y'): {
'type': 'process',
'location': "O",
'exchanges': []
},
('inventory', 'Z'): {
'type': 'process',
'location': "O",
'exchanges': []
}
}
inventory = Database("inventory")
inventory.register(depends=["biosphere"], geocollections=["places"])
inventory.write(inventory_data)
intersection_data = [
["L", "A", 1],
["M", "A", 2],
["M", "B", 3],
["N", "B", 5],
["N", "C", 8],
["O", "C", 13],
]
inter = Intersection(("places", "regions"))
inter.register()
inter.write(intersection_data)
loading_data = [
[2, "A"],
[4, "B"],
[8, "C"],
]
loading = Loading("loading")
loading.register()
loading.write(loading_data)
method_data = [
[('biosphere', 'F'), 1, "A"],
[('biosphere', 'G'), 2, "A"],
[('biosphere', 'F'), 3, "B"],
[('biosphere', 'G'), 4, "B"],
[('biosphere', 'F'), 5, "C"],
[('biosphere', 'G'), 6, "C"],
]
method = Method(("a", "method"))
method.register(geocollections=['regions'])
method.write(method_data)
def import_data(self):
biosphere_data = {
('biosphere', 'F'): {
'type': 'emission',
'exchanges': [],
},
('biosphere', 'G'): {
'type': 'emission',
'exchanges': [],
}
}
biosphere = Database("biosphere")
biosphere.register(depends=[], geocollections=[])
biosphere.write(biosphere_data)
inventory_data = {
('inventory', 'U'): {
'type': 'process',
'location': "L",
'exchanges': [
{
'input': ('biosphere', 'F'),
'type': 'biosphere',
'amount': 1
},
{
'input': ('biosphere', 'G'),
'type': 'biosphere',
'amount': 1
},
]
},
('inventory', 'V'): {
'type': 'process',
'location': "M",
'exchanges': []
},
('inventory', 'X'): {
'type': 'process',
'location': "N",
'exchanges': []
},
('inventory', 'Y'): {
'type': 'process',
'location': "O",
'exchanges': []
},
('inventory', 'Z'): {
'type': 'process',
'location': "O",
'exchanges': []
}
}
inventory = Database("inventory")
inventory.register(depends=["biosphere"], geocollections=["places"])
inventory.write(inventory_data)
method_data = [
[('biosphere', 'F'), 1, "L"],
[('biosphere', 'G'), 2, "L"],
]
method = Method(("a", "method"))
method.register(geocollections=['places'])
method.write(method_data)
def test_traverse_tagged_databases_graph_nonunitary_production():
Database("biosphere").write(
{
("biosphere", "bad"): {"name": "bad", "type": "emission"},
("biosphere", "worse"): {"name": "worse", "type": "emission"},
}
)
method = Method(("test method",))
method.register()
method.write(
[(("biosphere", "bad"), 2), (("biosphere", "worse"), 3),]
)
Database("background").write(
{
("background", "first"): {
"exchanges": [
{"input": ("biosphere", "bad"), "amount": 1, "type": "biosphere"},
{
"input": ("background", "first"),
"amount": 5,
"type": "production",
},
],
},
("background", "second"): {
"exchanges": [
{"input": ("biosphere", "worse"), "amount": 1, "type": "biosphere"}
],
},
}
)
Database("foreground").write(
{
("foreground", "fu"): {
"name": "functional unit",
"tag field": "functional unit",
"exchanges": [
{
"input": ("foreground", "i"),
"amount": 1,
"type": "technosphere",
},
{
"input": ("foreground", "iv"),
"amount": 4,
"type": "technosphere",
},
{"input": ("foreground", "fu"), "amount": 2, "type": "production",},
],
},
("foreground", "i"): {
"tag field": "A",
"exchanges": [
{
"input": ("foreground", "ii"),
"amount": 2,
"type": "technosphere",
},
{
"input": ("foreground", "iii"),
"amount": 3,
"type": "technosphere",
},
{
"input": ("biosphere", "bad"),
"amount": 5,
"tag field": "C",
"type": "biosphere",
},
{
"input": ("biosphere", "worse"),
"amount": 6,
"type": "biosphere",
},
],
},
("foreground", "ii"): {
"tag field": "C",
"exchanges": [
{"input": ("biosphere", "bad"), "amount": 8, "type": "biosphere",},
{
"input": ("biosphere", "worse"),
"amount": 7,
"tag field": "D",
"type": "biosphere",
},
{"input": ("foreground", "ii"), "amount": 3, "type": "production",},
],
},
("foreground", "iii"): {
# Default tag: "B"
"exchanges": [
{
"input": ("background", "first"),
"amount": 10,
"type": "technosphere",
},
{
"input": ("biosphere", "bad"),
"tag field": "A",
"amount": 9,
"type": "biosphere",
},
],
},
("foreground", "iv"): {
"tag field": "C",
"exchanges": [
{
"input": ("background", "second"),
"amount": 12,
"type": "technosphere",
},
{
"input": ("biosphere", "worse"),
"tag field": "B",
"amount": 11,
"type": "biosphere",
},
{
"input": ("foreground", "iv"),
"amount": 10,
"type": "production",
},
],
},
}
)
_, graph = traverse_tagged_databases(
{("foreground", "fu"): 2}, ("test method",), label="tag field", default_tag="B"
)
expected = [
{
"amount": 2,
"biosphere": [],
"activity": get_activity(("foreground", "fu")),
"technosphere": [
{
"amount": 1,
"biosphere": [
{"amount": 5, "impact": 10, "tag": "C", "secondary_tags": []},
{"amount": 6, "impact": 18, "tag": "A", "secondary_tags": []},
],
"activity": get_activity(("foreground", "i")),
"technosphere": [
{
"amount": 2,
"biosphere": [
{
"amount": 16 / 3,
"impact": 32 / 3,
"tag": "C",
"secondary_tags": [],
},
{
"amount": 14 / 3,
"impact": 42 / 3,
"tag": "D",
"secondary_tags": [],
},
],
"activity": get_activity(("foreground", "ii")),
"technosphere": [],
"impact": 0,
"tag": "C",
"secondary_tags": [],
},
{
"amount": 3,
"biosphere": [
{
"amount": 27,
"impact": 54,
"tag": "A",
"secondary_tags": [],
}
],
"activity": get_activity(("foreground", "iii")),
"technosphere": [],
"impact": 60 / 5,
"tag": "B",
"secondary_tags": [],
},
],
"impact": 0,
"tag": "A",
"secondary_tags": [],
},
{
"amount": 4,
"biosphere": [
{
"amount": pytest.approx(44 / 10),
"impact": pytest.approx(132 / 10),
"tag": "B",
"secondary_tags": [],
}
],
"activity": get_activity(("foreground", "iv")),
"technosphere": [],
"impact": pytest.approx(144 / 10),
"tag": "C",
"secondary_tags": [],
},
],
"impact": 0,
"tag": "functional unit",
"secondary_tags": [],
}
]
assert graph == expected
def tagged_fixture():
Database("biosphere").write(
{
("biosphere", "bad"): {"name": "bad", "type": "emission"},
("biosphere", "worse"): {"name": "worse", "type": "emission"},
}
)
method = Method(("test method",))
method.register()
method.write(
[(("biosphere", "bad"), 2), (("biosphere", "worse"), 3),]
)
Database("background").write(
{
("background", "first"): {
"exchanges": [
{"input": ("biosphere", "bad"), "amount": 1, "type": "biosphere",}
],
},
("background", "second"): {
"exchanges": [
{"input": ("biosphere", "worse"), "amount": 1, "type": "biosphere",}
],
},
}
)
Database("foreground").write(
{
("foreground", "fu"): {
"name": "functional unit",
"tag field": "functional unit",
"secondary tag": "X",
"exchanges": [
{
"input": ("foreground", "i"),
"amount": 1,
"type": "technosphere",
},
{
"input": ("foreground", "iv"),
"amount": 4,
"type": "technosphere",
},
],
},
("foreground", "i"): {
"tag field": "A",
"secondary tag": "X",
"exchanges": [
{
"input": ("foreground", "ii"),
"amount": 2,
"type": "technosphere",
},
{
"input": ("foreground", "iii"),
"amount": 3,
"type": "technosphere",
},
{
"input": ("biosphere", "bad"),
"amount": 5,
"tag field": "C",
"type": "biosphere",
},
{
"input": ("biosphere", "worse"),
"amount": 6,
"type": "biosphere",
},
],
},
("foreground", "ii"): {
"tag field": "C",
"secondary tag": "X",
"exchanges": [
{"input": ("biosphere", "bad"), "amount": 8, "type": "biosphere",},
{
"input": ("biosphere", "worse"),
"amount": 7,
"tag field": "D",
"secondary tag": "Y",
"type": "biosphere",
},
],
},
("foreground", "iii"): {
# Default tag: "B"
# Default secondary tag: "unknown"
"exchanges": [
{
"input": ("background", "first"),
"amount": 10,
"type": "technosphere",
},
{
"input": ("biosphere", "bad"),
"tag field": "A",
"secondary tag": "Y",
"amount": 9,
"type": "biosphere",
},
],
},
("foreground", "iv"): {
"tag field": "C",
"secondary tag": "Y",
"exchanges": [
{
"input": ("background", "second"),
"amount": 12,
"type": "technosphere",
},
{
"input": ("biosphere", "worse"),
"tag field": "B",
"secondary tag": "Y",
"amount": 11,
"type": "biosphere",
},
],
},
}
)