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 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 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