bw_timex.matrix_modifier

Module Contents

Classes

MatrixModifier

Class for adding and re-linking time-explicit processes in the LCA matrices.

class bw_timex.matrix_modifier.MatrixModifier(timeline: pandas.DataFrame, database_dates_static: dict, demand_timing: dict, nodes: dict, interdatabase_activity_mapping: bw_timex.helper_classes.InterDatabaseMapping, name: str | None = None)

Class for adding and re-linking time-explicit processes in the LCA matrices.

This is done by creating datapackages that add or change matrix entries in the technosphere and biosphere matrices, based on a process timeline (from TimelineBuilder.build_timeline()). “Temporal markets” are created for processes that are linked to background databases, temporally distributing the amounts to time-explicit background databases.

Initializes the MatrixModifier object and creates empty sets to collect the ids of temporalized processes and temporal markets.

Parameters:

• timeline (pd.DataFrame) – A DataFrame of the timeline of exchanges

• database_dates_static (dict) – A dictionary mapping the static background databases to dates.

• demand_timing (dict) – A dictionary mapping the demand to its timing.

• name (str, optional) – An optional name for the MatrixModifier instance. Default is None.

create_datapackage() → None

Creates a list of datapackages for the technosphere and biosphere matrices, by calling the respective functions.

Parameters:

None

Returns:

A list of the technosphere and biosphere datapackages.

Return type:

list

create_technosphere_datapackage() → bw_processing.Datapackage

Creates the modifications to the technosphere matrix in form of a datapackage. Datapackages add or overwrite data points in the LCA matrices before LCA calculations. The technosphere datapackage adds the temporalized processes from the timeline to the technosphere matrix.

The heavy lifting of this method happens in the method add_row_to_technosphere_datapackage(). Here, each node with a temporal distribution is “exploded”, which means each occurrence of this node (e.g. steel production on 2020-01-01 and steel production on 2015-01-01) becomes a separate, time-explicit new node, by adding the new elements to the technosphere matrix. For processes at the intersection with background databases, the timing of the exchanges determines which background database to link to in so called “Temporal Markets”.

Parameters:

None

Returns:

A datapackage containing the modifications for the technosphere matrix.

Return type:

bwp.Datapackage

create_biosphere_datapackage() → bw_processing.Datapackage

Creates the modifications to the biosphere matrix in form of a datapackage. Datapackages add or overwrite data points in the LCA matrices before LCA calculations. It adds the biosphere flows to the exploded technosphere processes.

This function iterates over each unique producer, and for each biosphere exchange of the original activity, it creates a new biosphere exchange for the new “temporalized” node.

Temporal markets have no biosphere exchanges, as they only divide the amount of a technosphere exchange between the different databases.

Parameters:

None

Returns:

A datapackage containing the modifications for the biosphere matrix.

Return type:

bwp.Datapackage

add_row_to_technosphere_datapackage(row: pandas.core.frame, datapackage: bw_processing.Datapackage, new_nodes: set) → None

This adds the modifications to the technosphere matrix for each time-dependent exchange as datapackage elements to a given bwp.Datapackage.

Modifications include:

1) Exploded processes: new matrix elements for time-explicit consumer and time-explicit producer, representing the temporal edge between them.

2) Temporal markets: new matrix entries for “temporal markets” and links to the producers in temporally matching background databases. Processes in the background databases are matched on name, reference product and location.

3. Diagonal entries: ones on the diagonal for new nodes.

This function also collects the ids of new nodes, temporalized nodes and temporal markets.

Parameters:

• row (pd.core.frame) – A row of the timeline DataFrame representing an temporalized edge

• datapackage (bwp.Datapackage) – Append to this datapackage, if available. Otherwise create a new datapackage.

• new_nodes (set) – Set of tuples (node_id, production_amount) to which new node ids are added.

Returns:

Adds elements for this edge to the bwp.Datapackage and stores the ids of new nodes, temporalized nodes and temporal markets.

Return type:

None