gemseo / mlearning / transform

transformer module

A transformer to apply operations on NumPy arrays.

The abstract Transformer class implements the concept of a data transformer. Inheriting classes shall implement the Transformer.fit(), Transformer.transform() and possibly Transformer.inverse_transform() methods.

class gemseo.mlearning.transform.transformer.Transformer(name='Transformer', **parameters)[source]

Bases: object

Transformer baseclass.

Parameters:
  • name (str) –

    A name for this transformer.

    By default it is set to “Transformer”.

  • **parameters (str) – The parameters of the transformer.

compute_jacobian(data)[source]

Compute Jacobian of transformer.transform().

Parameters:

data (ndarray) – The data where the Jacobian is to be computed.

Returns:

The Jacobian matrix.

Return type:

NoReturn

compute_jacobian_inverse(data)[source]

Compute Jacobian of the transformer.inverse_transform().

Parameters:

data (ndarray) – The data where the Jacobian is to be computed.

Returns:

The Jacobian matrix.

Return type:

NoReturn

duplicate()[source]

Duplicate the current object.

Returns:

A deepcopy of the current instance.

Return type:

Transformer

fit(data, *args)[source]

Fit the transformer to the data.

Parameters:
Return type:

NoReturn

fit_transform(data, *args)[source]

Fit the transformer to the data and transform the data.

Parameters:
Returns:

The transformed data.

Return type:

ndarray

inverse_transform(data)[source]

Perform an inverse transform on the data.

Parameters:

data (ndarray) – The data to be inverse transformed.

Returns:

The inverse transformed data.

Return type:

NoReturn

transform(data)[source]

Transform the data.

Parameters:

data (ndarray) – The data to be transformed.

Returns:

The transformed data.

Return type:

NoReturn

CROSSED = False
name: str

The name of the transformer.

parameters: str

The parameters of the transformer.

class gemseo.mlearning.transform.transformer.TransformerFactory(*args, **kwargs)[source]

Bases: Factory

A factory of Transformer.

Parameters:
  • base_class – The base class to be considered.

  • module_names – The fully qualified modules names to be searched.

  • args (Any) –

  • kwargs (Any) –

static cache_clear()
create(class_name, **options)

Return an instance of a class.

Parameters:
  • class_name (str) – The name of the class.

  • **options (Any) – The arguments to be passed to the class constructor.

Returns:

The instance of the class.

Raises:

TypeError – If the class cannot be instantiated.

Return type:

Any

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[Any]

get_default_options_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_options_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 = 'gemseo_plugins'
property classes: list[str]

Return the available classes.

Returns:

The sorted names of the available classes.

Examples using Transformer

KL-SVD on Burgers equation

KL-SVD on Burgers equation

KL-SVD on Burgers equation
PCA on Burgers equation

PCA on Burgers equation

PCA on Burgers equation
Quality measure for surrogate model comparison

Quality measure for surrogate model comparison

Quality measure for surrogate model comparison
Mixture of experts

Mixture of experts

Mixture of experts
Scaler example

Scaler example

Scaler example
Transformer pipeline example

Transformer pipeline example

Transformer pipeline example