scaler module¶
Scaling a variable with a linear transformation.
The Scaler
class implements the default scaling method
applying to some parameter \(z\):
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.
See also
- class gemseo.mlearning.transform.scaler.scaler.Scaler(name='Scaler', offset=0.0, coefficient=1.0)[source]¶
Bases:
gemseo.mlearning.transform.transformer.Transformer
Data scaler.
- Parameters
- Return type
None
- 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
- 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
- duplicate()¶
Duplicate the current object.
- Returns
A deepcopy of the current instance.
- Return type
- fit(data, *args)¶
Fit the transformer to the data.
- Parameters
data (numpy.ndarray) – The data to be fitted.
- Return type
NoReturn
- fit_transform(data, *args)¶
Fit the transformer to the data and transform the data.
- Parameters
data (numpy.ndarray) – The data to be transformed.
- Returns
The transformed data.
- Return type
- 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
- transform(data)[source]¶
Transform the data.
- Parameters
data (numpy.ndarray) – The data to be transformed.
- Returns
The transformed data.
- Return type
- CROSSED = False¶