apparun.tree_node

Classes

NodeProperties	Properties of an impact model node. Can be used by to break the results down
NodeScores	Gathers all useful information to exploit computed node wise LCIA results.

Module Contents

class apparun.tree_node.NodeProperties

Bases: pydantic.BaseModel

Properties of an impact model node. Can be used by to break the results down according to life cycle phase, for exemple. Properties can be key/value (ex: {“phase”: “production”} or flags (ex: {production_phase: True}).

classmethod from_dict(properties: Dict[str, str | float | bool]) → NodeProperties

Construct using dict. :param properties: properties of the node. :return: constructed NodeProperties

get_property_value(property_name: str) → str | bool | None

Gives the value of a property by name, returns None if property doesn’t exist. :param property_name: name of the property to get value :return: value of the property, None if doesn’t exist

properties: Dict[str, str | float | bool]

class apparun.tree_node.NodeScores

Bases: pydantic.BaseModel

Gathers all useful information to exploit computed node wise LCIA results.

static combine_by_property(nodes_scores: List[NodeScores], property_name: str) → List[NodeScores]

Sum up (element wise) the scores of each node sharing the same property value, for each method. :param nodes_scores: node scores to combine according to property value. :param property_name: name of the property under consideration :return: list of newly created nodes. Name of the node will be the property value.

to_unpivoted_df() → pandas.DataFrame

lcia_scores: apparun.score.LCIAScores

Computed LCIA scores, for each method.

name: str

Node name/property value, if results have been combined by property value.

parent: str

Name of parent node.

properties: NodeProperties

Properties of the node.