Model

class glotaran.model.model.Model(*, clp_penalties=_Nothing.NOTHING, clp_constraints=_Nothing.NOTHING, clp_relations=_Nothing.NOTHING, dataset_groups: dict[str, DatasetGroupModel | Any] = _Nothing.NOTHING, dataset: dict[str, DatasetModel], megacomplex=_Nothing.NOTHING, weights=_Nothing.NOTHING)[source]

Bases: object

A model for global target analysis.

Method generated by attrs for class Model.

Attributes Summary

`source_path`
`clp_penalties`
`clp_constraints`
`clp_relations`
`dataset_groups`
`dataset`
`megacomplex`
`weights`

Methods Summary

`as_dict`	Get the model as dictionary.
`create_class`	Create model class.
`create_class_from_megacomplexes`	Create model class for megacomplexes.
`generate_parameters`	Generate parameters for the model.
`get_dataset_groups`	Get the dataset groups.
`get_issues`	Get issues.
`get_parameter_labels`	Get all parameter labels.
`iterate_all_items`	Iterate the individual items.
`iterate_items`	Iterate items.
`loader`	Create a Model instance from the specs defined in a file.
`markdown`	Format the model as Markdown string.
`valid`	Check if the model is valid.
`validate`	Get a string listing all issues in the model and missing parameters if specified.

Methods Documentation

as_dict() → dict[source]

Get the model as dictionary.

Return type:: dict

clp_constraints: list[ClpConstraint]

clp_penalties: list[ClpPenalty]

clp_relations: list[ClpRelation]

classmethod create_class(attributes: dict[str, Attribute]) → type[Model][source]

Create model class.

Parameters:: attributes (dict[str, Attribute]) – The model attributes.
Return type:: type[Model]

classmethod create_class_from_megacomplexes(megacomplexes: Iterable[type[Megacomplex]]) → type[Model][source]

Create model class for megacomplexes.

Parameters:: megacomplexes (list[type[Megacomplex]]) – The megacomplexes.
Return type:: type[Model]

dataset: dict[str, DatasetModel]

dataset_groups: dict[str, DatasetGroupModel]

generate_parameters() → Parameters[source]

Generate parameters for the model.

Returns:

Parameters – The generated parameters.
.. # noqa (D414)

get_dataset_groups() → dict[str, DatasetGroup][source]

Get the dataset groups.

Return type:: dict[str, DatasetGroup]
Raises:: ModelError – Raised if a dataset group is unknown.

get_issues(*, parameters: Parameters | None = None) → list[ItemIssue][source]

Get issues.

Parameters:: parameters (Parameters | None) – The parameters.
Return type:: list[ItemIssue]

get_parameter_labels() → set[str][source]

Get all parameter labels.

Return type:: set[str]

iterate_all_items() → Generator[Item, None, None][source]

Iterate the individual items.

Yields:: Item – The individual item.

iterate_items() → Generator[tuple[str, dict[str, Item] | list[Item]], None, None][source]

Iterate items.

Yields:: tuple[str, dict[str, Item] | list[Item]] – The name of the item and the individual items of the type.

loader(format_name: str | None = None, **kwargs: Any) → Model

Create a Model instance from the specs defined in a file.

Parameters:

file_name (StrOrPath) – File containing the model specs.
format_name (str) – Format the file is in, if not provided it will be inferred from the file extension.
**kwargs (Any) – Additional keyword arguments passes to the load_model implementation of the project io plugin.

Returns:

Model instance created from the file.

Return type:

Model

markdown(parameters: Parameters | None = None, initial_parameters: Parameters | None = None, base_heading_level: int = 1) → MarkdownStr[source]

Format the model as Markdown string.

Parameters will be included if specified.

Parameters:

parameters (Parameters | None) – Parameter to include.
initial_parameters (Parameters | None) – Initial values for the parameters.
base_heading_level (int) –
Base heading level of the markdown sections.

E.g.:
- If it is 1 the string will start with ‘# Model’.
- If it is 3 the string will start with ‘### Model’.

Return type:

MarkdownStr

megacomplex: dict[str, Megacomplex]

source_path: str | None

valid(parameters: Parameters | None = None) → bool[source]

Check if the model is valid.

Parameters:: parameters (Parameters | None) – The parameters.
Return type:: bool

validate(parameters: Parameters | None = None, raise_exception: bool = False) → MarkdownStr[source]

Get a string listing all issues in the model and missing parameters if specified.

Parameters:

parameters (Parameters | None) – The parameters.
raise_exception (bool) – Whether to raise an exception on failed validation.

Return type:

MarkdownStr

Raises:

ModelError – Raised if validation fails and raise_exception is true.

weights: list[Weight]