bw2data.weighting_normalization

Module Contents

Classes

Normalization	LCIA normalization data - used to transform meaningful units, like mass or damage, into "person-equivalents" or some such thing.
Weighting	LCIA weighting data - used to combine or compare different impact categories.

class bw2data.weighting_normalization.Normalization(name)

Bases: bw2data.ia_data_store.ImpactAssessmentDataStore

LCIA normalization data - used to transform meaningful units, like mass or damage, into “person-equivalents” or some such thing.

The data schema for IA normalization is:

Schema([
    [valid_tuple, maybe_uncertainty]
])

where:

• valid_tuple is a dataset identifier, like ("biosphere", "CO2")

• maybe_uncertainty is either a number or an uncertainty dictionary

_metadata

matrix = 'normalization_matrix'

validator

process_row(row)

Given (flow key, amount), return a dictionary for array insertion.

class bw2data.weighting_normalization.Weighting(name)

Bases: bw2data.ia_data_store.ImpactAssessmentDataStore

LCIA weighting data - used to combine or compare different impact categories.

The data schema for weighting is a one-element list:

Schema(All(
    [uncertainty_dict],
    Length(min=1, max=1)
))

_metadata

matrix = 'weighting_matrix'

validator

process_row(row)

Return an empty tuple (as dtype_fields is empty), and the weighting uncertainty dictionary.

write(data)

Because of DataStore assumptions, need a one-element list