apparun.impact_model#

Classes#

`ImpactModel`	Impact model contains all the information required to compute the impact of an
`LcaPractitioner`	Information about a LCA practitioner.
`LcaStudy`	Information about LCA study, in order to understand its scope and for
`ModelMetadata`	Contain information various information about the context of production of the

class apparun.impact_model.ImpactModel#

Bases: pydantic.BaseModel

Impact model contains all the information required to compute the impact of an LCA built with Appa Build.

static from_dict(impact_model: dict) → ImpactModel#: Convert dict to ImpactModel object. :param impact_model: dict containing construction parameters of the impact model. :return: constructed impact model.

from_tree_children() → List[ImpactModel]#: Create a new impact model for each of Impact Model tree root node’s children. Parameters of the impact model are copied, so unused parameters can remain in newly created impact models. :return: a list of newly created impact models.

static from_yaml(filepath: str) → ImpactModel#: Convert a yaml file to an ImpactModel object. :param filepath: yaml file containing construction parameters of the impact model. :return: constructed impact model.

get_nodes_scores(by_property: str | None = None, **params) → List[apparun.tree_node.NodeScores]#: Get impact scores of the each node for each impact method, according to the parameters. :param by_property: if different than None, results will be pooled by nodes sharing the same property value. Property name is the value of by_property. :param params: value, or list of values of the impact model’s parameters. List of values must have the same length. If single values are provided alongside a list of values, it will be duplicated to the appropriate length. :return: a list of dict mapping impact names and corresponding score, or list of scores, for each node/property value.

get_scores(**params) → apparun.score.LCIAScores#: Get impact scores of the root node for each impact method, according to the parameters. :param params: value, or list of values of the impact model’s parameters. List of values must have the same length. If single values are provided alongside a list of values, it will be duplicated to the appropriate length. :return: a dict mapping impact names and corresponding score, or list of scores.

get_sobol_s1_indices(n, all_nodes: bool = False) → List[Dict[str, str | numpy.ndarray]]#: Get sobol first indices, which corresponds to the contribution of each parameter to total result variance. :param n: number of samples to draw with monte carlo. :param all_nodes: if True, sobol s1 indices will be computed for each node. Else, only for root node (FU). :return: unpivoted dataframe containing sobol first indices for each parameter, impact method, and node name if all_nodes is True.

to_yaml(filepath: str, compile_models: bool = True)#: Convert self to yaml file. :param filepath: filepath of the yaml file to create. :param compile_models: if True, all models in tree nodes will be compiled. ImpactModel will be bigger, but its execution will be faster at first use.

transform_parameters(parameters: Dict[str, List[str | float] | str | float]) → Dict[str, List[str | float] | str | float]#: Transform all the parameters’ values, so it can be fed into a node’s compute method. See ImpactModelParam’s transform methods for more information. :param parameters: a dict mapping parameters’ name and parameters’ value, or list of values. :return: a dict mapping parameters’ name and parameters’ transformed value, or list of transformed values.

property transformation_table: Dict[str, Callable[[str | float], Dict[str, float]]]#: Map each parameter to its transform method. :return: a dict mapping impact model’s parameters’ name with their transform method.

class apparun.impact_model.LcaPractitioner#

Bases: pydantic.BaseModel

Information about a LCA practitioner.

class apparun.impact_model.LcaStudy#

Bases: pydantic.BaseModel

Information about LCA study, in order to understand its scope and for reproducibility.

class apparun.impact_model.ModelMetadata#

Bases: pydantic.BaseModel

Contain information various information about the context of production of the impact model.

static from_dict(model_metadata: dict) → ModelMetadata#: Convert dict to ModelMetadata object. :param model_metadata: dict containing construction parameters of the model metadata. :return: constructed model metadata.