FmiInputVariable

class mlfmu.types.fmu_component.FmiInputVariable(*, name: str, type: ~mlfmu.types.fmu_component.FmiVariableType = FmiVariableType.REAL, description: str | None = None, variability: ~mlfmu.types.fmu_component.FmiVariability | None = None, startValue: float | str | bool | int | None = 0, isArray: bool = False, length: int | None = None, agentInputIndexes: list[~typing.Annotated[str, ~pydantic.types.StringConstraints(strip_whitespace=True, to_upper=True, to_lower=None, strict=None, min_length=None, max_length=None, pattern=^(\d+|\d+:\d+)$)]] = [], causality: ~mlfmu.types.fmu_component.FmiCausality, variableReferences: list[int], agentStateInitIndexes: list[list[int]] = [])

Bases: InputVariable

Data class representing an input variable in an FMI component.

__init__(**kwargs: Any) → None

Create an FMI input variable.

Parameters:

• causality (FmiCausality, optional) – Causality of the input variable., by default FmiCausality.INPUT

• variable_references (list[int], optional) – List of variable references associated with the input variable., by default []

Methods

__init__(**kwargs)	Create an FMI input variable.
construct([_fields_set])
copy(*[, include, exclude, update, deep])	Returns a copy of the model.
dict(*[, include, exclude, by_alias, ...])
from_orm(obj)
json(*[, include, exclude, by_alias, ...])
model_construct([_fields_set])	Creates a new instance of the Model class with validated data.
model_copy(*[, update, deep])	Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy
model_dump(*[, mode, include, exclude, ...])	Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump
model_dump_json(*[, indent, include, ...])	Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json
model_json_schema([by_alias, ref_template, ...])	Generates a JSON schema for a model class.
model_parametrized_name(params)	Compute the class name for parametrizations of generic classes.
model_post_init(_BaseModel__context)	Override this method to perform additional initialization after __init__ and model_construct.
model_rebuild(*[, force, raise_errors, ...])	Try to rebuild the pydantic-core schema for the model.
model_validate(obj, *[, strict, ...])	Validate a pydantic model instance.
model_validate_json(json_data, *[, strict, ...])	Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing
model_validate_strings(obj, *[, strict, context])	Validate the given object with string data against the Pydantic model.
parse_file(path, *[, content_type, ...])
parse_obj(obj)
parse_raw(b, *[, content_type, encoding, ...])
schema([by_alias, ref_template])
schema_json(*[, by_alias, ref_template])
update_forward_refs(**localns)
validate(value)

Attributes

model_computed_fields
model_config	Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
model_extra	Get extra fields set during validation.
model_fields
model_fields_set	Returns the set of fields that have been explicitly set on this model instance.
causality	The causality of the input variable.
variable_references	The list of variable references associated with the input variable.
agent_state_init_indexes	List of state initialization indexes for ONNX model - concerns mapping of FMU input variables to ONNX states.
agent_input_indexes	Index or range of indices of ONNX (agent) inputs to which this FMU signal shall be linked to.
name	Unique name for the port.
type	Data type as defined by FMI standard.
description	Short FMU variable description.
variability	Signal variability as defined by FMI.
start_value	Initial value of the signal at time step 1.
is_array	When dealing with an array signal, it is essential to specify the LENGTH parameter.
length	Defines the number of entries in the signal if the signal is array.

agent_state_init_indexes: list[list[int]]

List of state initialization indexes for ONNX model - concerns mapping of FMU input variables to ONNX states.

causality: FmiCausality

The causality of the input variable.

model_config: ClassVar[ConfigDict] = {'alias_generator': <function to_camel>, 'populate_by_name': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

variable_references: list[int]

The list of variable references associated with the input variable.