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 Vision Machine Learning

System Requirements

Development environment	Target platform	PLC libraries to include
TwinCAT V3.1.4024.54 or later	PC or CX (x64) with PL50, e.g. Intel 4-core Atom CPU	Tc3_Vision