flixOpt.effects

This module contains the effects of the flixOpt framework. Furthermore, it contains the EffectCollection, which is used to collect all effects of a system. Different Datatypes are used to represent the effects with assigned values by the user, which are then transformed into the internal data structure.

Classes

Effect

Effect(label: str, unit: str, description: str, meta_data: Optional[Dict] = None, is_standard: bool = False, is_objective: bool = False, specific_share_to_other_effects_operation: EffectValues = None, specific_share_to_other_effects_invest: EffectValuesInvest = None, minimum_operation: Optional[Skalar] = None, maximum_operation: Optional[Skalar] = None, minimum_invest: Optional[Skalar] = None, maximum_invest: Optional[Skalar] = None, minimum_operation_per_hour: Optional[Numeric_TS] = None, maximum_operation_per_hour: Optional[Numeric_TS] = None, minimum_total: Optional[Skalar] = None, maximum_total: Optional[Skalar] = None)

Bases: Element

Effect, i.g. costs, CO2 emissions, area, ... Components, FLows, and so on can contribute to an Effect. One Effect is chosen as the Objective of the Optimization

Parameters:

Name	Type	Description	Default
`label`	`str`	name	required
`unit`	`str`	unit of effect, i.g. €, kg_CO2, kWh_primaryEnergy	required
`description`	`str`	long name	required
`meta_data`	`Optional[Dict]`	used to store more information about the element. Is not used internally, but saved in the results	`None`
`is_standard`	`boolean`	true, if Standard-Effect (for direct input of value without effect (alternatively to dict)) , else false	`False`
`is_objective`	`boolean`	true, if optimization target	`False`
`specific_share_to_other_effects_operation`	`effectType: TS, ...}, i.g. 180 €/t_CO2, input as {costs: 180`	share to other effects (only operation)	`effectType: TS`
`specific_share_to_other_effects_invest`	`effectType: TS, ...}, i.g. 180 €/t_CO2, input as {costs: 180`	share to other effects (only invest).	`effectType: TS`
`minimum_operation`	`scalar`	minimal sum (only operation) of the effect	`None`
`maximum_operation`	`scalar`	maximal sum (nur operation) of the effect.	`None`
`minimum_operation_per_hour`	`scalar or TS`	maximum value per hour (only operation) of effect (=sum of all effect-shares) for each timestep!	`None`
`maximum_operation_per_hour`	`scalar or TS`	minimum value per hour (only operation) of effect (=sum of all effect-shares) for each timestep!	`None`
`minimum_invest`	`scalar`	minimal sum (only invest) of the effect	`None`
`maximum_invest`	`scalar`	maximal sum (only invest) of the effect	`None`
`minimum_total`	`sclalar`	min sum of effect (invest+operation).	`None`
`maximum_total`	`scalar`	max sum of effect (invest+operation).	`None`
`**kwargs`	`TYPE`	DESCRIPTION.	required

Returns:

Type	Description
`None.`

Functions

infos

infos(use_numpy=True, use_element_label=False) -> Dict

Generate a dictionary representation of the object's constructor arguments. Excludes default values and empty dictionaries and lists. Converts data to be compatible with JSON.

Parameters:

use_numpy bool: Whether to convert NumPy arrays to lists. Defaults to True. If True, numeric numpy arrays (np.ndarray) are preserved as-is. If False, they are converted to lists. use_element_label bool: Whether to use the element label instead of the infos of the element. Defaults to False. Note that Elements used as keys in dictionaries are always converted to their labels.

Returns: Dict: A dictionary representation of the object's constructor arguments.

to_json

to_json(path: Union[str, Path])

Saves the element to a json file. This not meant to be reloaded and recreate the object, but rather used to document or compare the object.

Parameters:

path : Union[str, pathlib.Path] The path to the json file.

EffectCollection

EffectCollection(label: str)

Handling all Effects

Functions

nested_values_to_time_series

nested_values_to_time_series(nested_values: Dict[Element, Numeric_TS], label_suffix: str, parent_element: Element) -> ElementTimeSeries

Creates TimeSeries from nested values, which are a Dict of Elements to values. The resulting label of the TimeSeries is the label of the parent_element, followed by the label of the element in the nested_values and the label_suffix.

effect_values_to_time_series

effect_values_to_time_series(label_suffix: str, nested_values: EffectValues, parent_element: Element) -> Optional[EffectTimeSeries]

Creates TimeSeries from EffectValues. The resulting label of the TimeSeries is the label of the parent_element, followed by the label of the Effect in the nested_values and the label_suffix. If the key in the EffectValues is None, the alias 'Standart_Effect' is used

as_effect_dict

as_effect_dict(effect_values: EffectValues) -> Optional[EffectDict]

Converts effect values into a dictionary. If a scalar is provided, it is associated with a default effect type.

Examples:

costs = 20 -> {None: 20} costs = None -> None costs = {effect1: 20, effect2: 0.3} -> {effect1: 20, effect2: 0.3}

Parameters:

Name	Type	Description	Default
`effect_values`	`None, int, float, TimeSeries, or dict`	The effect values to convert, either a scalar, TimeSeries, or a dictionary.	required

Returns:

Type	Description
`dict or None`	A dictionary with None or Effect as the key, or None if input is None.