bw_temporalis.lca

Exceptions

MultipleTechnosphereExchanges

Common base class for all non-exit exceptions.

Classes

NoExchange	The edge was created dynamically via a datapackage. There is no edge in the database.
TemporalisLCA	Calculate an LCA using graph traversal, with edges using temporal distributions.

Module Contents

exception bw_temporalis.lca.MultipleTechnosphereExchanges

Bases: Exception

Common base class for all non-exit exceptions.

Initialize self. See help(type(self)) for accurate signature.

class bw_temporalis.lca.NoExchange

The edge was created dynamically via a datapackage. There is no edge in the database.

class bw_temporalis.lca.TemporalisLCA(lca_object: bw2calc.LCA, starting_datetime: datetime.datetime | str = 'now', cutoff: float | None = 0.0005, biosphere_cutoff: float | None = 1e-06, max_calc: int | None = 2000, static_activity_indices: set[int] | None = None, skip_coproducts: bool | None = False, functional_unit_unique_id: int | None = -1, graph_traversal: bw_graph_tools.NewNodeEachVisitGraphTraversal | None = NewNodeEachVisitGraphTraversal)

Calculate an LCA using graph traversal, with edges using temporal distributions.

Edges with temporal distributions should store this information using “temporal_distributions”:

```python

exchange[“temporal_distribution”] = bw_temporalis.TemporalDistribution(

times=numpy.array([-2, -1, 0, 1, 2], dtype=”timedelta64[s]”), values=numpy.ones(5)

)

```

Temporal distribution times must always have the data type timedelta64[s]. Not all edges need to have temporal distributions.

Temporal distributions are not density functions - their values should sum to the exchange amount.

As graph traversal is much slower than matrix calculations, we can limit which nodes get traversed in several ways:

• All activities in a database marked as static

• Any activity ids passed in static_activity_indices

• Any activities whose cumulative impact is below the cutoff score

The output of a Temporalis LCA calculation is a bw_temporalis.Timeline, which can be characterized.

Parameters:

• lca_object (bw2calc.LCA) – The already instantiated and calculated LCA class (i.e. .lci() and .lcia() have already been done)

• starting_datetime (datetime.datetime | str) – When the functional unit happens. Must be a point in time. Normally something like “now” or “2023-01-01”.

• cutoff (float) – The fraction of the total score below which graph traversal should stop. In range (0, 1).

• biosphere_cutoff (float) – The fraction of the total score below which we don’t include separate biosphere nodes to be characterized in the Timeline. In range (0, 1).

• max_calc (int) – Total number of LCA inventory calculations to perform during graph traversal

• static_activity_indices (set[int]) – Activity database node id values where graph traversal will stop

• skip_coproducts (bool) – Should we also traverse edges for the other products in multioutput activities?

• functional_unit_unique_id (int) – The unique id of the functional unit. Strongly recommended to leave as default.

• graph_traversal (bw_graph_tools.NewNodeEachVisitGraphTraversal) – Optional subclass of NewNodeEachVisitGraphTraversal for advanced usage

_exchange_iterator(input_id: int, output_id: int) → list[bw2data.backends.ExchangeDataset]

_exchange_value(exchange: bw2data.backends.ExchangeDataset | NoExchange, row_id: int, col_id: int, matrix_label: str) → float | bw_temporalis.temporal_distribution.TemporalDistribution

build_timeline(node_timeline: bool | None = False) → bw_temporalis.timeline.Timeline

get_biosphere_exchanges(flow_id: int, activity_id: int) → collections.abc.Iterable[bw2data.backends.ExchangeDataset]

get_technosphere_exchange(input_id: int, output_id: int) → bw2data.backends.ExchangeDataset

edge_mapping

edges

flow_mapping

flows

lca_object

nodes

t0

unique_id = -1