Transform (CADETProcess.transform)

Transform (`CADETProcess.transform`)#

This module provides functionality for transforming data.

`TransformBase`([lb_input, ub_input, ...])	Base class for parameter transformation.
`NoTransform`([lb_input, ub_input, ...])	A class that implements no transformation.
`NormLinearTransform`([lb_input, ub_input, ...])	A class that implements a normalized linear transformation.
`NormLogTransform`([lb_input, ub_input, ...])	A class that implements a normalized logarithmic transformation.
`AutoTransform`(*args[, threshold])	A class that implements an automatic parameter transformation.

class CADETProcess.transform.AutoTransform(*args, threshold=1000, **kwargs)[source]#

A class that implements an automatic parameter transformation.

Transforms the input value to the range [0, 1] using either the NormLinearTransform or the NormLogTransform based on the input parameter space.

See also

TransformBase
NormLinearTransform
NormLogTransform

Attributes:

linearNormLinearTransform: Instance of the linear normalization transform.
logNormLogTransform: Instance of the logarithmic normalization transform.

Methods

`plot`(ax[, use_log_scale])	Plot the transformed space against the input space.
`transform`(x)	Transform the input parameter space to the output parameter space.
`untransform`(x)	Transform the output parameter space to the input parameter space.

property is_linear#: bool: True if transformation is linear.

property lb#: {float, array-like}: The lower bounds of the output parameter space.

property lb_input#: {float, array-like}: The lower bounds of the input parameter space.

property ub#: {float, array-like}: The upper bounds of the output parameter space.

property ub_input#: {float, array-like}: The upper bounds of the input parameter space.

property use_linear#: bool: Indicates whether linear transformation is used.

property use_log#: bool: Indicates whether logarithmic transformation is used.

class CADETProcess.transform.NoTransform(lb_input=-inf, ub_input=inf, allow_extended_input=False, allow_extended_output=False)[source]#

A class that implements no transformation.

Returns the input values without any transformation.

See also

TransformBase: The base class for parameter transformation.

Attributes:

is_linear: bool: True if transformation is linear.
lb: {float, array-like}: The lower bounds of the output parameter space.
lb_input: {float, array-like}: The lower bounds of the input parameter space.
ub: {float, array-like}: The upper bounds of the output parameter space.
ub_input: {float, array-like}: The upper bounds of the input parameter space.

Methods

`plot`(ax[, use_log_scale])	Plot the transformed space against the input space.
`transform`(x)	Transform the input parameter space to the output parameter space.
`untransform`(x)	Transform the output parameter space to the input parameter space.

property is_linear#: bool: True if transformation is linear.

property lb#: {float, array-like}: The lower bounds of the output parameter space.

property ub#: {float, array-like}: The upper bounds of the output parameter space.

class CADETProcess.transform.NormLinearTransform(lb_input=-inf, ub_input=inf, allow_extended_input=False, allow_extended_output=False)[source]#

A class that implements a normalized linear transformation.

Transforms the input value to the range [0, 1] by normalizing it using the lower and upper bounds of the input parameter space.

See also

TransformBase: The base class for parameter transformation.

Attributes:

is_linear: bool: True if transformation is linear.
lb: {float, array-like}: The lower bounds of the output parameter space.
lb_input: {float, array-like}: The lower bounds of the input parameter space.
ub: {float, array-like}: The upper bounds of the output parameter space.
ub_input: {float, array-like}: The upper bounds of the input parameter space.

Methods

`plot`(ax[, use_log_scale])	Plot the transformed space against the input space.
`transform`(x)	Transform the input parameter space to the output parameter space.
`untransform`(x)	Transform the output parameter space to the input parameter space.

property is_linear#: bool: True if transformation is linear.

property lb#: {float, array-like}: The lower bounds of the output parameter space.

property ub#: {float, array-like}: The upper bounds of the output parameter space.

class CADETProcess.transform.NormLogTransform(lb_input=-inf, ub_input=inf, allow_extended_input=False, allow_extended_output=False)[source]#

A class that implements a normalized logarithmic transformation.

Transforms the input value to the range [0, 1] using a logarithmic transformation with the lower and upper bounds of the input parameter space.

See also

TransformBase: The base class for parameter transformation.

Attributes:

is_linear: bool: True if transformation is linear.
lb: {float, array-like}: The lower bounds of the output parameter space.
lb_input: {float, array-like}: The lower bounds of the input parameter space.
ub: {float, array-like}: The upper bounds of the output parameter space.
ub_input: {float, array-like}: The upper bounds of the input parameter space.

Methods

`plot`(ax[, use_log_scale])	Plot the transformed space against the input space.
`transform`(x)	Transform the input parameter space to the output parameter space.
`untransform`(x)	Transform the output parameter space to the input parameter space.

property is_linear#: bool: True if transformation is linear.

property lb#: {float, array-like}: The lower bounds of the output parameter space.

property ub#: {float, array-like}: The upper bounds of the output parameter space.

class CADETProcess.transform.TransformBase(lb_input=-inf, ub_input=inf, allow_extended_input=False, allow_extended_output=False)[source]#

Base class for parameter transformation.

This class provides an interface for transforming an input parameter space to some output parameter space.

Raises:

ValueError: If lb_input and ub_input have different shapes.

Notes

This is an abstract base class and cannot be instantiated directly.
The transform method must be implemented by a subclass.

Examples

>>> class MyTransform(TransformBase):
...     def transform(self, x):
...         return x ** 2
...
>>> t = MyTransform(lb_input=0, ub_input=10, lb=-100, ub=100)
>>> t.transform(3)
9

Attributes:

lb_input{float, array-like}: {float, array-like}: The lower bounds of the input parameter space.
ub_input{float, array-like}: {float, array-like}: The upper bounds of the input parameter space.
lb{float, array-like}: {float, array-like}: The lower bounds of the output parameter space.
ub{float, array-like}: {float, array-like}: The upper bounds of the output parameter space.
allow_extended_inputbool: If True, the input value may exceed the lower/upper bounds. Else, an exception is thrown.
allow_extended_outputbool: If True, the output value may exceed the lower/upper bounds. Else, an exception is thrown.

Methods

`plot`(ax[, use_log_scale])	Plot the transformed space against the input space.
`transform`(x)	Transform the input parameter space to the output parameter space.
`untransform`(x)	Transform the output parameter space to the input parameter space.

abstract property is_linear#: bool: True if transformation is linear.

abstract property lb#

{float, array-like}: The lower bounds of the output parameter space.

Must be implemented in the child class.

property lb_input#: {float, array-like}: The lower bounds of the input parameter space.

plot(ax, use_log_scale=False)[source]#

Plot the transformed space against the input space.

Parameters:

axmatplotlib.axes.Axes: The axes object to plot on.
use_log_scalebool, optional: If True, use a logarithmic scale for the x-axis.

transform(x)[source]#

Transform the input parameter space to the output parameter space.

Applies the transformation function _transform to x after performing input bounds checking. If the transformed value exceeds the output bounds, an error is raised.

Parameters:

x{float, array}: Input parameter values.

Returns:

{float, array}: Transformed parameter values.

abstract property ub#

{float, array-like}: The upper bounds of the output parameter space.

Must be implemented in the child class.

property ub_input#: {float, array-like}: The upper bounds of the input parameter space.

untransform(x)[source]#

Transform the output parameter space to the input parameter space.

Applies the transformation function _untransform to x after performing output bounds checking. If the transformed value exceeds the input bounds, an error is raised.

Parameters:

x{float, array}: Output parameter values.

Returns:

{float, array}: Transformed parameter values.

Transform (CADETProcess.transform)

Contents

Transform (CADETProcess.transform)#

Transform (`CADETProcess.transform`)#