gemseo /
mlearning /
transformers /
scalerShow inherited members
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.

class gemseo.mlearning.transformers.scaler.scaler.Scaler(name='Scaler', offset=0.0, coefficient=1.0)[source]
Bases: Transformer
Data scaler.
 Parameters:
name (str) –
A name for this transformer.
By default it is set to “Scaler”.
offset (float  ndarray) –
The offset of the linear transformation.
By default it is set to 0.0.
coefficient (float  ndarray) –
The coefficient of the linear transformation.
By default it is set to 1.0.

compute_jacobian(data, *args, **kwargs)
Force a NumPy array to be 2D and evaluate the function f
with it.
 Parameters:
data (ndarray) – A 1D or 2D NumPy array.
*args (Any) – The description is missing.
**kwargs (Any) – The description is missing.
 Returns:
Any kind of output;
if a NumPy array,
its dimension is made consistent with the shape of data
.
 Return type:
Any

compute_jacobian_inverse(data, *args, **kwargs)
Force a NumPy array to be 2D and evaluate the function f
with it.
 Parameters:
data (ndarray) – A 1D or 2D NumPy array.
*args (Any) – The description is missing.
**kwargs (Any) – The description is missing.
 Returns:
Any kind of output;
if a NumPy array,
its dimension is made consistent with the shape of data
.
 Return type:
Any

inverse_transform(data, *args, **kwargs)
Force a NumPy array to be 2D and evaluate the function f
with it.
 Parameters:
data (ndarray) – A 1D or 2D NumPy array.
*args (Any) – The description is missing.
**kwargs (Any) – The description is missing.
 Returns:
Any kind of output;
if a NumPy array,
its dimension is made consistent with the shape of data
.
 Return type:
Any

transform(data, *args, **kwargs)
Force a NumPy array to be 2D and evaluate the function f
with it.
 Parameters:
data (ndarray) – A 1D or 2D NumPy array.
*args (Any) – The description is missing.
**kwargs (Any) – The description is missing.
 Returns:
Any kind of output;
if a NumPy array,
its dimension is made consistent with the shape of data
.
 Return type:
Any

property coefficient: ndarray
The scaling coefficient.

name: str
The name of the transformer.

property offset: ndarray
The scaling offset.