F_VN_InverseFeatureScalingExp_REAL

Apply the inverse of feature scaling to a single value. [fA, fB] should be used if the scaling has been performed using TCVN_FST1_MINMAX with a predetermined output range.

Syntax

Definition:

FUNCTION F_VN_InverseFeatureScalingExp_REAL : HRESULT
VAR_INPUT
    fSample        : REAL;
    ipScales       : ITcVnContainer;
END_VAR
VAR_IN_OUT
    fInverseSample : REAL;
END_VAR
VAR_INPUT
    fA             : LREAL;
    fB             : LREAL;
    hrPrev         : HRESULT;
END_VAR

Inputs

Name	Type	Description
fSample	REAL	Sample value
ipScales	ITcVnContainer	Container with the scaling parameters of each feature (type ContainerType_Vector_REAL or ContainerType_Vector_LREAL).
fA	LREAL	represents the lower bound of the range for TCVN_FST1_MINMAX
fB	LREAL	represents the upper bound of the range for TCVN_FST1_MINMAX
hrPrev	HRESULT	HRESULT indicating the result of previous operations (If SUCCEEDED(hrPrev) equals false, no operation is executed.)

In/Outputs

Name	Type	Description
fInverseSample	REAL	Returns the inversed sample.

Return value

HRESULT

Further information

The function F_VN_InverseFeatureScalingExp_REAL is the expert variant of F_VN_InverseFeatureScaling_REAL. It contains additional parameters.

Parameter

Samples

A sample of the type REAL must be transferred to fSample.

Scaling

A container with the scaling type and the corresponding scaling parameters must be transferred to ipScales. The container can be calculated using the function F_VN_GetFeatureScales or created using the structure described there.

Scaled sample

The inversely scaled feature is returned via fInverseSample.

Defining the output range

If the scaling type TCVN_FST1_MINMAX is used, the value range of the output values can also be specified via fA and fB.

Application

For example, an inverse feature scaling for a sample looks like this:

hr := F_VN_InverseFeatureScalingExp_REAL(
    fSample        := fSample,
    ipScales       := ipScales,
    fInverseSample := fSampleInvertedScaling,
    fA             := 0.1,
    fB             := 0.9,
    hrPrev         := hr);

Related functions

Required License

TC3 Machine Learning Realtime Inference

System Requirements

Development environment	Target platform	PLC libraries to include
TwinCAT V3.1.4024.59 or later	PC or CX (x64) with min. PL50, e.g. Intel 4-core Atom CPU	Tc3_Vision