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.

See also

scaler dimension_reduction

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

Bases: object

A data transformer fitted from some samples.

Parameters:

name (str) –
A name for this transformer.

By default it is set to “Transformer”.
**parameters (ParameterType) – The parameters of the transformer.

compute_jacobian(data)[source]

Compute the Jacobian of transform().

Parameters:: data (ndarray) – The data where the Jacobian is to be computed, shaped as (n_observations, n_features) or (n_features, ).
Returns:: The Jacobian matrix, shaped according to data.
Return type:: NoReturn

compute_jacobian_inverse(data)[source]

Compute the Jacobian of the inverse_transform().

Parameters:: data (ndarray) – The data where the Jacobian is to be computed, shaped as (n_observations, n_features) or (n_features, ).
Returns:: The Jacobian matrix, shaped according to data..
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:

data (ndarray) – The data to be fitted, shaped as (n_observations, n_features) or (n_observations, ).
args (float | int | str) –

Return type:

None

fit_transform(data, *args)[source]

Fit the transformer to the data and transform the data.

Parameters:

data (ndarray) – The data to be transformed, shaped as (n_observations, n_features) or (n_observations, ).
args (float | int | str) –

Returns:

The transformed data, shaped as data.

Return type:

ndarray

inverse_transform(data)[source]

Perform an inverse transform on the data.

Parameters:: data (ndarray) – The data to be inverse transformed, shaped as (n_observations, n_features) or (n_features, ).
Returns:: The inverse transformed data, shaped as data.
Return type:: NoReturn

abstract transform(data)[source]

Transform the data.

Parameters:: data (ndarray) – The data to be transformed, shaped as (n_observations, n_features) or (n_features, ).
Returns:: The transformed data, shaped as data.
Return type:: ndarray

CROSSED: ClassVar[bool] = False: Whether the fit() method requires two data arrays.

property is_fitted: bool: Whether the transformer has been fitted from some data.

name: str: The name of the transformer.

property parameters: dict[str, Union[bool, int, float, numpy.ndarray, str, NoneType]]: The parameters of the transformer.

class gemseo.mlearning.transformers.transformer.TransformerFactory[source]

Bases: BaseFactory

A factory of Transformer.

Return type:: BaseFactory

failed_imports: dict[str, str]: The class names bound to the import errors.

Examples using Transformer¶

KL-SVD on Burgers equation

PCA on Burgers equation

Quality measure for surrogate model comparison

Scaler example

Transformer pipeline example