Configuration

configuration

Representations of parsed configuration files.

AxesGroupModel = dict[IdentifierString, AxisModel] module-attribute

Type alias for the axes block in a configuration file.

AxisModel = Annotated[ContinuousAxisModel | CategoricalAxisModel, Field(discriminator='kind')] module-attribute

Discriminated union of all axis configuration models.

ModuleGroupModel = Annotated[dict[IdentifierString, ModuleModel], BeforeValidator(_to_default_dict)] module-attribute

Module group configuration model for flepimop2.

CategoricalAxisModel

Bases: BaseModel

Configuration model for a categorical axis.

Attributes:

Name	Type	Description
kind	Literal['categorical']	Discriminator field; always "categorical".
labels	tuple[str, ...]	Ordered sequence of string category labels.
values	tuple[int, ...]	Integer values associated with each label (e.g. for ordinal data or spline interpolation). Must be the same length as labels. Defaults to 1, 2, ..., N where N is len(labels).

Examples:

>>> from flepimop2.configuration._axes import CategoricalAxisModel
>>> CategoricalAxisModel(labels=("foo", "bar", "baz"))
CategoricalAxisModel(kind='categorical', labels=('foo', 'bar', 'baz'), values=(1, 2, 3))

ConfigurationModel

Bases: YamlSerializableBaseModel

Configuration model for flepimop2.

This model serves as the parent container for a parsed configuration file.

Attributes:

Name	Type	Description
name	str | None	An optional name for the configuration.
engines	ModuleGroupModel	A dictionary of engine configurations.
systems	ModuleGroupModel	A dictionary of system configurations.
backends	ModuleGroupModel	A dictionary of backend configurations.
process	ModuleGroupModel	A dictionary of process configurations.
parameters	ModuleGroupModel	A dictionary of parameter configurations.
simulate	dict[IdentifierString, SimulateSpecificationModel]	A dictionary of simulation configurations.

ContinuousAxisModel

Bases: BaseModel

Configuration model for a continuous (float) axis.

Attributes:

Name	Type	Description
kind	Literal['continuous']	Discriminator field; always "continuous".
domain	tuple[float, float]	A [lo, hi] pair of floats defining the axis extent.
size	int	Number of evenly-spaced points. Required for continuous axes.
spacing	Literal['linear', 'log']	Whether points are spaced "linear" or "log"-uniformly.

Examples:

>>> from flepimop2.configuration._axes import ContinuousAxisModel
>>> ContinuousAxisModel(domain=(0.0, 12.0), size=5, spacing="linear")
ContinuousAxisModel(kind='continuous', domain=(0.0, 12.0), size=5, spacing='linear')

ModuleModel

Bases: BaseModel

Module configuration model for flepimop2.

Attributes:

Name	Type	Description
module	str	The module identifier for the configuration. Concrete subclasses may leave this as a general string field or specialize it to a fixed Literal[...] module path.

__pydantic_init_subclass__(**kwargs) classmethod

Finalize the module field for ModuleABC subclasses after model creation.

This keeps the explicit declaration API working while also allowing the shared module="..." class-definition shortcut implemented in ModuleABC.

Parameters:

Name	Type	Description	Default
**kwargs	Any	Additional keyword arguments passed to parent classes.	{}

Source code in src/flepimop2/configuration/_module.py

@classmethod
def __pydantic_init_subclass__(cls, **kwargs: Any) -> None:  # noqa: PLW3201
    """
    Finalize the `module` field for `ModuleABC` subclasses after model creation.

    This keeps the explicit declaration API working while also allowing the
    shared `module="..."` class-definition shortcut implemented in `ModuleABC`.

    Args:
        **kwargs: Additional keyword arguments passed to parent classes.

    """
    super().__pydantic_init_subclass__(**kwargs)
    if not issubclass(cls, ModuleABC):
        return
    module = getattr(cls, "module", None)
    field = cls.model_fields.get("module")
    if not isinstance(module, str) or field is None:
        return
    field.annotation = cast("Any", Literal[module])
    field.default = module
    cls.model_rebuild(force=True)

SimulateSpecificationModel

Bases: BaseModel

Model for specifying a simulation for flepimop2.

Attributes:

Name	Type	Description
engine	IdentifierString	The name of the engine to use for the simulation.
system	IdentifierString	The name of the system to simulate.
backend	IdentifierString	The name of the backend to use for the simulation.
times	RangeSpec	A list of time points at which to perform the simulation.
params	dict[str, float] | None	Optional dictionary of parameters for the simulation.
scenario	IdentifierString | None	Optional name of the scenario to use for the simulation.

t_eval property

Get the evaluation times as a NumPy array.

Returns:

Type	Description
Float64NDArray	A NumPy array of evaluation times.