A CPOTrained always has access to some kind of state that represents information gotten from the training data, as well as the parameters it was called with.

Only primitive CPOTrained objects can be inspected like this. If the supplied CPOTrained is not primitive, split it into its constituents using as.list.CPOTrained.

The structure of the internal state depends on the CPO backend used. For Functional CPO, the state is the environment of the retrafo function, turned into a list. For Object based CPO, the state is a list containing the parameters, as well as the control object generated by the trafo function.

The object can be slightly modified and used to create a new CPOTrained object using makeCPOTrainedFromState.

getCPOTrainedState(trained.object)

## Arguments

trained.object [CPOTrained] The object to get the state of.

## Value

[list]. A named list, containing the complete internal state of the CPOTrained.

Other state functions: makeCPOTrainedFromState()
Other retrafo related: CPOTrained, NULLCPO, %>>%(), applyCPO(), as.list.CPO, clearRI(), getCPOClass(), getCPOName(), getCPOOperatingType(), getCPOPredictType(), getCPOProperties(), getCPOTrainedCPO(), getCPOTrainedCapability(), is.retrafo(), makeCPOTrainedFromState(), pipeCPO(), print.CPOConstructor()
Other inverter related: CPOTrained, NULLCPO, %>>%(), applyCPO(), as.list.CPO, clearRI(), getCPOClass(), getCPOName(), getCPOOperatingType(), getCPOPredictType(), getCPOProperties(), getCPOTrainedCPO(), getCPOTrainedCapability(), is.inverter(), makeCPOTrainedFromState(), pipeCPO(), print.CPOConstructor()