F_VN_PredictSampleVector

Compute a vectorial prediction for a single sample.
Can use available TwinCAT Job Tasks for executing parallel code regions.

Syntax

Definition:

FUNCTION F_VN_PredictSampleVector : HRESULT
VAR_INPUT
    ipRegressor  : ITcVnMlModel;
    ipSample     : ITcUnknown;
    ipPrediction : Reference To  ITcVnContainer;
    hrPrev       : HRESULT;
END_VAR

Inputs

Name	Type	Description
ipRegressor	ITcVnMlModel	Regressor to be used
ipSample	ITcUnknown	Container holding a single input sample (ContainerType_Vector_REAL or ContainerType_Vector_LREAL)
ipPrediction	Reference To ITcVnContainer	Returns the predicted output (ContainerType_Vector_REAL or ContainerType_Vector_LREAL, depending on ipSample)
hrPrev	HRESULT	HRESULT indicating the result of previous operations (If SUCCEEDED(hrPrev) equals false, no operation is executed.)

Return value

HRESULT

Further information

The function F_VN_PredictSampleVector calculates the prediction vector of a sample based on a regression model.

Parameter

Regression model

The previously trained regression model must be transferred to ipRegressor.

Sample

The sample container is transferred as ipSample. The container type must be either ContainerType_Vector_REAL or ContainerType_Vector_LREAL.

Prediction

The calculated prediction vector is returned as a container via the reference ipPrediction. The container type is taken from ipSamples.

Expert parameters

The expert variant F_VN_PredictSampleVectorExp contains additional parameters.

Application

For example, the prediction vector of a sample can be calculated as follows:

hr := F_VN_PredictSampleVector(
    ipRegressor := ipRegressor,
    ipSample    := ipSample,
    ipPrediction:= ipPrediction,
    hrPrev      := hr);

Related functions

F_VN_PredictBatch

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