gemseo / problems / scalable / data_driven

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factory module

Scalable model factory

This module contains the ScalableModelFactory which is a factory to create a ScalableModel from its class name by means of the ScalableModelFactory.create() method. It is also possible to get a list of available scalable models (see ScalableModelFactory.scalable_models method) and to check is a type of scalable model is available (see ScalableModelFactory.is_available() method)

class gemseo.problems.scalable.data_driven.factory.ScalableModelFactory[source]

Bases: BaseFactory

This factory instantiates a class:.ScalableModel from its class name.

The class can be internal to GEMSEO or located in an external module whose path is provided to the constructor.

Return type:

BaseFactory

create(model_name, data, sizes=None, **parameters)[source]

Create a scalable model.

Parameters:

  • model_name (str) – name of the scalable model (its class name)

  • data (Dataset) – learning dataset.

  • sizes (dict) – sizes of input and output variables. If None, use the original sizes. Default: None.

  • parameters – model parameters

  • class_name – The name of the class.

  • **args – The positional arguments to be passed to the class constructor.

  • **kwargs – The keyword arguments to be passed to the class constructor.

Returns:

model_name scalable model

Returns:

The instance of the class.

Raises:

TypeError – If the class cannot be instantiated.

get_class(name)

Return a class from its name.

Parameters:

name (str) – The name of the class.

Returns:

The class.

Raises:

ImportError – If the class is not available.

Return type:

type

get_default_option_values(name)

Return the constructor kwargs default values of a class.

Parameters:

name (str) – The name of the class.

Returns:

The mapping from the argument names to their default values.

Return type:

dict[str, str | int | float | bool]

get_default_sub_option_values(name, **options)

Return the default values of the sub options of a class.

Parameters:

  • name (str) – The name of the class.

  • **options (str) – The options to be passed to the class required to deduce the sub options.

Returns:

The JSON grammar.

Return type:

JSONGrammar

get_library_name(name)

Return the name of the library related to the name of a class.

Parameters:

name (str) – The name of the class.

Returns:

The name of the library.

Return type:

str

get_options_doc(name)

Return the constructor documentation of a class.

Parameters:

name (str) – The name of the class.

Returns:

The mapping from the argument names to their documentation.

Return type:

dict[str, str]

get_options_grammar(name, write_schema=False, schema_path=None)

Return the options JSON grammar for a class.

Attempt to generate a JSONGrammar from the arguments of the __init__ method of the class.

Parameters:

  • name (str) – The name of the class.

  • write_schema (bool) –

    If True, write the JSON schema to a file.

    By default it is set to False.

  • schema_path (str | None) – The path to the JSON schema file. If None, the file is saved in the current directory in a file named after the name of the class.

Returns:

The JSON grammar.

Return type:

JSONGrammar

get_sub_options_grammar(name, **options)

Return the JSONGrammar of the sub options of a class.

Parameters:

  • name (str) – The name of the class.

  • **options (str) – The options to be passed to the class required to deduce the sub options.

Returns:

The JSON grammar.

Return type:

JSONGrammar

is_available(name)

Return whether a class can be instantiated.

Parameters:

name (str) – The name of the class.

Returns:

Whether the class can be instantiated.

Return type:

bool

update()

Search for the classes that can be instantiated.

The search is done in the following order:

  1. The fully qualified module names

  2. The plugin packages

  3. The packages from the environment variables

Return type:

None

PLUGIN_ENTRY_POINT: ClassVar[str] = 'gemseo_plugins'

The name of the setuptools entry point for declaring plugins.

property class_names: list[str]

The sorted names of the available classes.

failed_imports: dict[str, str]

The class names bound to the import errors.

property scalable_models: list[str]

Lists the available classes for scalable models.

Returns:

the list of classes names.

Return type:

list(str)