Model

class glotaran.model.model.Model(*, megacomplex_types: dict[str, type[Megacomplex]], default_megacomplex_type: str | None = None, dataset_group_models: dict[str, DatasetGroupModel] = None)[source]

Bases: object

A base class for global analysis models.

Attributes Summary

`dataset_group_models`
`default_megacomplex`	The default megacomplex used by this model.
`global_dimension`	Deprecated use `Scheme.global_dimensions['<dataset_name>']` instead
`global_megacomplex`	Alias for glotaran.model.megacomplex.
`megacomplex_types`	The megacomplex types used by this model.
`model_dimension`	Deprecated use `Scheme.model_dimensions['<dataset_name>']` instead
`model_items`	The model_items types used by this model.

Methods Summary

`as_dict`
`from_dict`	Creates a model from a dictionary.
`get_dataset_groups`
`get_parameters`
`is_groupable`
`loader`	Create a Model instance from the specs defined in a file.
`markdown`	Formats the model as Markdown string.
`need_index_dependent`	Returns true if e.g.
`problem_list`	Returns a list with all problems in the model and missing parameters if specified.
`valid`	Returns True if the number problems in the model is 0, else False
`validate`	Returns a string listing all problems in the model and missing parameters if specified.

Methods Documentation

as_dict() → dict[source]

property dataset_group_models: dict[str, DatasetGroupModel]

property default_megacomplex: str: The default megacomplex used by this model.

classmethod from_dict(model_dict: dict[str, Any], *, megacomplex_types: dict[str, type[Megacomplex]] | None = None, default_megacomplex_type: str | None = None) → Model[source]

Creates a model from a dictionary.

Parameters

model_dict (dict[str, Any]) – Dictionary containing the model.
megacomplex_types (dict[str, type[Megacomplex]] | None) – Overwrite ‘megacomplex_types’ in model_dict for testing.
default_megacomplex_type (str | None) – Overwrite ‘default_megacomplex’ in model_dict for testing.

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

get_parameters() → list[str][source]

property global_dimension: Deprecated use Scheme.global_dimensions['<dataset_name>'] instead

property global_megacomplex: dict[str, Megacomplex]: Alias for glotaran.model.megacomplex. Needed internally.

is_groupable(parameters: ParameterGroup, data: dict[str, xr.DataArray]) → bool[source]

loader(format_name: str = 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: Optional[glotaran.parameter.parameter_group.ParameterGroup] = None, initial_parameters: Optional[glotaran.parameter.parameter_group.ParameterGroup] = None, base_heading_level: int = 1) → glotaran.utils.ipython.MarkdownStr[source]

Formats the model as Markdown string.

Parameters will be included if specified.

Parameters

parameter (ParameterGroup) – Parameter to include.
initial_parameters (ParameterGroup) – 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’.

property megacomplex_types: dict[str, type[Megacomplex]]: The megacomplex types used by this model.

property model_dimension: Deprecated use Scheme.model_dimensions['<dataset_name>'] instead

property model_items: dict[str, type[object]]: The model_items types used by this model.

need_index_dependent() → bool[source]: Returns true if e.g. clp_relations with intervals are present.

problem_list(parameters: ParameterGroup = None) → list[str][source]

Returns a list with all problems in the model and missing parameters if specified.

Parameters: parameter – The parameter to validate.

valid(parameters: Optional[glotaran.parameter.parameter_group.ParameterGroup] = None) → bool[source]

Returns True if the number problems in the model is 0, else False

Parameters: parameter – The parameter to validate.

validate(parameters: Optional[glotaran.parameter.parameter_group.ParameterGroup] = None, raise_exception: bool = False) → str[source]

Returns a string listing all problems in the model and missing parameters if specified.

Parameters: parameter – The parameter to validate.