apparun.score#

Classes#

Scores for each impact method.

class apparun.score.LCIAScores#

Bases: pydantic.BaseModel

Scores for each impact method.

static sum(lcia_scores: List[LCIAScores]) → LCIAScores#: Sum element-wise all scores for each method. :param lcia_scores: LCIA scores to sum up. :return: summed LCIA scores

to_normalised(method: apparun.impact_methods.MethodUniqueScore | None = MethodUniqueScore.EF30, filenorm: str | None = None) → LCIAScores#: Computes normalisation of LCIAScores using .csv file with impact categories and normalisation factors. :param: method: allows to use default MethodUniqueScore.EF30 or EF31 normalisation factors. :param: filenorm: allows to give a personal .csv file with normalisation factors. :return: LCIAScores after normalisation.

to_unique_score(is_normalised: bool | None = False, is_weighted: bool | None = False, method: apparun.impact_methods.MethodUniqueScore | None = MethodUniqueScore.EF30, filenorm: str | None = None, fileweight: str | None = None) → LCIAScores#: Computes sum of LCIAScores impact category scores into unique score. Possible to apply normalisation and/or weighting before aggregating scores. :param: is_normalised: if True, apply normalisation before sum into unique score. :param: is_weighted: if True, apply weighting (after normalisation) before sum into unique score. :param: method: allows to use default MethodUniqueScore.EF30 or EF31 normalisation and weighting factors. :param: filenorm: allows to give a personal .csv file with normalisation factors. :param: fileweight: allows to give a personal .csv file with weighting factors.

to_weighted(method: apparun.impact_methods.MethodUniqueScore | None = MethodUniqueScore.EF30, fileweight: str | None = None) → LCIAScores#: Computes normalisation of LCIAScores using .csv file with impact categories and normalisation factors. :param: method: allows to use default MethodUniqueScore.EF30 or EF31 weighting factors. :param: fileweight: allows to give a personal .csv file with weighting factors. :return: LCIAScores after normalisation.

property method_names: Set[str]#: Get all LCIA methods assessed. :return: LCIA methods assessed