gemseo / mlearning / transform / scaler

scaler module

Scaling a variable with a linear transformation.

The Scaler class implements the default scaling method applying to some parameter \(z\):

\[\bar{z} := \text{offset} + \text{coefficient}\times z\]

where \(\bar{z}\) is the scaled version of \(z\). This scaling method is a linear transformation parameterized by an offset and a coefficient.

In this default scaling method, the offset is equal to 0 and the coefficient is equal to 1. Consequently, the scaling operation is the identity: \(\bar{z}=z\). This method has to be overloaded.

Classes:

Scaler([name, offset, coefficient])

Data scaler.

class gemseo.mlearning.transform.scaler.scaler.Scaler(name='Scaler', offset=0.0, coefficient=1.0)[source]

Bases: gemseo.mlearning.transform.transformer.Transformer

Data scaler.

Attributes
  • name (str) – The name of the transformer.

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

Parameters
  • name (str) – A name for this transformer.

  • offset (float) – The offset of the linear transformation.

  • coefficient (float) – The coefficient of the linear transformation.

Return type

None

Attributes:

CROSSED

coefficient

The scaling coefficient.

offset

The scaling offset.

Methods:

compute_jacobian(data)

Compute Jacobian of transformer.transform().

compute_jacobian_inverse(data)

Compute Jacobian of the transformer.inverse_transform().

duplicate()

Duplicate the current object.

fit(data, *args)

Fit the transformer to the data.

fit_transform(data, *args)

Fit the transformer to the data and transform the data.

inverse_transform(data)

Perform an inverse transform on the data.

transform(data)

Transform the data.

CROSSED = False
property coefficient

The scaling coefficient.

compute_jacobian(data)[source]

Compute Jacobian of transformer.transform().

Parameters

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

Returns

The Jacobian matrix.

Return type

numpy.ndarray

compute_jacobian_inverse(data)[source]

Compute Jacobian of the transformer.inverse_transform().

Parameters

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

Returns

The Jacobian matrix.

Return type

numpy.ndarray

duplicate()

Duplicate the current object.

Returns

A deepcopy of the current instance.

Return type

gemseo.mlearning.transform.transformer.Transformer

fit(data, *args)[source]

Fit the transformer to the data.

Parameters
  • data (numpy.ndarray) – The data to be fitted.

  • args (Union[float, int, str]) –

Return type

None

fit_transform(data, *args)

Fit the transformer to the data and transform the data.

Parameters
  • data (numpy.ndarray) – The data to be transformed.

  • args (Union[float, int, str]) –

Returns

The transformed data.

Return type

numpy.ndarray

inverse_transform(data)[source]

Perform an inverse transform on the data.

Parameters

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

Returns

The inverse transformed data.

Return type

numpy.ndarray

property offset

The scaling offset.

transform(data)[source]

Transform the data.

Parameters

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

Returns

The transformed data.

Return type

numpy.ndarray