SimulationConfig

class dynode.config.simulation_config.SimulationConfig(*, initializer: Initializer, compartments: List[Compartment], parameters: Params)

Bases: BaseModel

An ODE compartment model configuration file.

__init__(**data: Any) → None

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Methods

flatten_bins()	Flatten all compartments down to list of bins.
flatten_dims()	Flatten all compartments down to list of dimensions.
get_compartment(compartment_name)	Search for and return a Compartment if it exists.

Attributes

idx	An enum-like structure for compartments and their dimensions.
model_config	Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
initializer
compartments
parameters

model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': True}

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

initializer: Initializer

compartments: List[Compartment]

parameters: Params

property idx

An enum-like structure for compartments and their dimensions.

Note

This is a cache property, so it will only be computed once, modifications to the compartments will not change the enum after it is created.

Returns

SimpleNamespace: A namespace containing compartments and their dimensions.

_validate_no_shared_compartment_names() → Self

Validate that no two compartments have the same name.

_validate_shared_compartment_dimensions() → Self

Validate that any dimensions with same name across compartments are equal.

_validate_immune_histories() → Self

Validate that the immune history dimensions within each compartment are initialized from the same strain definitions.

Example

If you have 2 strains, x and y, - a FullStratifiedImmuneHistory should have 4 bins, none, x, y, x_y - a LastStrainImmuneHistory should have 3 bins, none, x, y - Neither class should bins with any other strain z or exclude one of the required bins.

_create_introduction_ages_mask_encoding() → Self

Parse Strain’s introduction_ages to a binary mask.

_validate_introduced_strains() → Self

Validate that all introduced strains have the same age binning as defined by the Model’s compartments.

get_compartment(compartment_name: str) → Compartment

Search for and return a Compartment if it exists.

Parameters

compartment_namestr

name of the compartment to return

Returns

Compartment

Compartment class with matching name.

Raises

AssertionError

raise if compartment_name not found within self.compartments

flatten_bins() → list[Bin]

Flatten all compartments down to list of bins.

Returns

list[Bin]

flattened compartments’ bin objects.

Note

This operation preserves the order of the compartments, dimensions, and bins in the final flattened output.

flatten_dims() → list[Dimension]

Flatten all compartments down to list of dimensions.

Returns

list[Dimension]

flattened compartments’ Dimension objects.

Note

This operation preserves the order of the compartments, and dimensions, in the final flattened output.

_abc_impl = <_abc._abc_data object>