sknrf.model.transform.base module¶

class sknrf.model.transform.base.GoodnessOfFit(ports=(1,))¶

Bases: AbstractModel

calculate(A, x_, y)¶

Calculate the goodness of fit.

Parameters:

Atensor

MxN problem matrix.

x_tensor

NX1 expected input data

ytensor

1XM actual output data

staticMetaObject = PySide6.QtCore.QMetaObject("GoodnessOfFit" inherits "AbstractModel": )¶

class sknrf.model.transform.base.AbstractTransform(name: str, ports: tuple, instrument_flags=InstrumentFlag.ALL)¶

Bases: Module, AbstractModel

display_order = ['name', 'ports']¶

optimize = True¶

training: bool = True¶

release()¶

color()¶

The color code assigned to the transform.

Returns:

str

A color code.

property ports¶

Tuple[int]: Ports that apply the transform

property instrument_flags¶

Instrument: Instruments that apply the transform

staticMetaObject = PySide6.QtCore.QMetaObject("AbstractTransform" inherits "AbstractModel": )¶