bw2analyzer.tagged

Module Contents

Functions

aggregate_tagged_graph(graph)	Aggregate a graph produced by recurse_tagged_database by the provided tags.
get_cum_impact(graph[, max_levels])	Add cumulative impact cum_impact to each technosphere level of a tagged graph.
get_multi_cum_impact(graph[, max_levels])	Add cumulative impact cum_impact to each technosphere level of a multi method tagged graph.
multi_aggregate_tagged_graph(graph)	Aggregate a graph produced by multi_recurse_tagged_database by the provided tags.
multi_recurse_tagged_database(activity, amount, ...[, ...])	Traverse a foreground database and assess activities and biosphere flows by tags using multiple methods.
multi_traverse_tagged_databases(functional_unit, methods)	Traverse a functional unit throughout its foreground database(s), and
recurse_tagged_database(activity, amount, method_dict, ...)	Traverse a foreground database and assess activities and biosphere flows by tags.
traverse_tagged_databases(functional_unit, method[, ...])	Traverse a functional unit throughout its foreground database(s) or the

bw2analyzer.tagged.aggregate_tagged_graph(graph)

Aggregate a graph produced by recurse_tagged_database by the provided tags.

Outputs a dictionary with keys of tags and numeric values.

{'a tag': summed LCIA scores}

bw2analyzer.tagged.get_cum_impact(graph, max_levels=100)

Add cumulative impact cum_impact to each technosphere level of a tagged graph.

This function recurses until all levels in the graph have been checked, or the max_levels cutoff is reached

Input arguments:

• graph: A tagged supply chain graph from recurse_tagged_database.

• max_levels: maximum number of graph levels to check before giving up. Default is 100.

Returns:

Tagged supply chain graph with additional cumulative impact cum_impact key at each technosphere level.

bw2analyzer.tagged.get_multi_cum_impact(graph, max_levels=100)

Add cumulative impact cum_impact to each technosphere level of a multi method tagged graph.

This function recurses until all levels in the graph have been checked, or the max_levels cutoff is reached

Input arguments:

• graph: A tagged supply chain graph from multi_recurse_tagged_database.

• max_levels: maximum number of graph levels to check before giving up. Default is 100.

Returns:

Tagged supply chain graph with additional cumulative impact cum_impact key at each technosphere level.

bw2analyzer.tagged.multi_aggregate_tagged_graph(graph)

Aggregate a graph produced by multi_recurse_tagged_database by the provided tags.

Outputs a dictionary with keys of tags and numeric values.

Note: this only aggregates on the primary tag, secondary tags are not aggregated

{'a tag': [list of summed LCIA scores with one sum per method]}

bw2analyzer.tagged.multi_recurse_tagged_database(activity, amount, methods, method_dicts, lca, label, default_tag, secondary_tags=[])

Traverse a foreground database and assess activities and biosphere flows by tags using multiple methods.

Input arguments:

• activity: Activity tuple or object

• amount: float

• methods: list of LCA methods (tuples)

• method_dicts: list of dictionaries of biosphere flow tuples to CFs, e.g. {("biosphere", "foo"): 3} corresponding to methods in methods

• lca: An LCA object that is already initialized, i.e. has already calculated LCI

• label: string

• default_tag: string

• secondary_tags: list of tuples in the format (secondary_label, secondary_default_tag). Default is empty list.

Returns:

{
    'activity': activity object,
    'amount': float,
    'tag': string,
    'secondary_tags': [list of strings],
    'impact': [list of floats (impact of inputs from outside foreground database) with one element per method],
    'biosphere': [{
        'amount': float,
        'impact': [list of floats with one element per method],
        'tag': string,
        'secondary_tags': [list of strings]
    }],
    'technosphere': [this data structure]
}

bw2analyzer.tagged.multi_traverse_tagged_databases(functional_unit, methods, label='tag', default_tag='other', secondary_tags=[])

Traverse a functional unit throughout its foreground database(s), and group impacts (for multiple methods) by tag label.

Input arguments:

• functional_unit: A functional unit dictionary, e.g. {("foo", "bar"): 42}.

• methods: A list of method names, e.g. [("foo", "bar"), ("baz", "qux"), ...]

• label: The label of the tag classifier. Default is "tag"

• default_tag: The tag classifier to use if none was given. Default is "other"

• secondary_tags: List of tuples in the format (secondary_label, secondary_default_tag). Default is empty list.

Returns:

Aggregated tags dictionary from aggregate_tagged_graph, and tagged supply chain graph from recurse_tagged_database.

bw2analyzer.tagged.recurse_tagged_database(activity, amount, method_dict, lca, label, default_tag, secondary_tags=[], fg_databases=None, warned=False)

Traverse a foreground database and assess activities and biosphere flows by tags.

Input arguments:

• activity: Activity tuple or object

• amount: float

• method_dict: Dictionary of biosphere flow tuples to CFs, e.g. {("biosphere", "foo"): 3}

• lca: An LCA object that is already initialized, i.e. has already calculated LCI and LCIA with same method as in method_dict

• label: string

• default_tag: string

• secondary_tags: List of tuples in the format (secondary_label, secondary_default_tag). Default is empty list.

• fg_databases: a list of foreground databases to be traversed, e.g. [‘foreground’, ‘biomass’, ‘machinery’]

  It’s not recommended to include all databases of a project in the list to be traversed, especially not ecoinvent itself

Returns:

{
    'activity': activity object,
    'amount': float,
    'tag': string,
    'secondary_tags': [list of strings],
    'impact': float (impact of inputs from outside foreground database),
    'biosphere': [{
        'amount': float,
        'impact': float,
        'tag': string,
        'secondary_tags': [list of strings]
    }],
    'technosphere': [this data structure]
}

bw2analyzer.tagged.traverse_tagged_databases(functional_unit, method, label='tag', default_tag='other', secondary_tags=[], fg_databases=None)

Traverse a functional unit throughout its foreground database(s) or the listed databses in fg_databses, and group impacts by tag label.

Contribution analysis work by linking impacts to individual activities. However, you also might want to group impacts in other ways. For example, give individual biosphere exchanges their own grouping, or aggregate two activities together.

Consider this example system, where the letters are the tag labels, and the numbers are exchange amounts. The functional unit is one unit of the tree root.

In this supply chain, tags are applied to activities and biosphere exchanges. If a biosphere exchange is not tagged, it inherits the tag of its producing activity. Similarly, links to other databases are assessed with the usual LCA machinery, and the total LCA score is tagged according to its consuming activity. If an activity does not have a tag, a default tag is applied.

We can change our visualization to show the use of the default tags:

And then we can manually calculate the tagged impacts. Normally we would need to know the actual biosphere flows and their respective characterization factors (CF), but in this example we assume that each CF is one. Our result, group by tags, would therefore be:

• A: \(6 + 27 = 33\)

• B: \(30 + 44 = 74\)

• C: \(5 + 16 + 48 = 69\)

• D: \(14\)

This function will only traverse the foreground database, i.e. the database of the functional unit activity. A functional unit can have multiple starting nodes; in this case, all foreground databases are traversed.

Input arguments:

• functional_unit: A functional unit dictionary, e.g. {("foo", "bar"): 42}.

• method: A method name, e.g. ("foo", "bar")

• label: The label of the tag classifier. Default is "tag"

• default_tag: The tag classifier to use if none was given. Default is "other"

• secondary_tags: List of tuples in the format (secondary_label, secondary_default_tag). Default is empty list.

• fg_databases: a list of foreground databases to be traversed, e.g. [‘foreground’, ‘biomass’, ‘machinery’]

  It’s not recommended to include all databases of a project in the list to be traversed, especially not ecoinvent itself

Returns:

Aggregated tags dictionary from aggregate_tagged_graph, and tagged supply chain graph from recurse_tagged_database.