/**
* Calculates the "Behavioral Recall" metric for a given mined model with respect to a log and a
* reference model.
*
* @param model The resulting Petri net generated by a mining algorithm.
* @param referenceLog The log to be used during the calculation of the behavioral recall value of
* the mined model.
* @param referenceModel The Petri net used to measure behavioral recall of the mined model.
* @param progress Progress
* @return The behavioral recall value (<code>[0, 1]</code>) of the mined model. If the behavioral
* recall value cannot be calculated, the value <code>BenchmarkMetric.INVALID_MEASURE_VALUE
* </code> is returned.
*/
public double measure(
PetriNet model, LogReader referenceLog, PetriNet referenceModel, Progress progress) {
// check precondition: no shared inputs for duplicate tasks
if (model.hasDuplicatesWithSharedInputPlaces() == true
|| referenceModel.hasDuplicatesWithSharedInputPlaces() == true) {
return BenchmarkMetric.INVALID_MEASURE_VALUE;
}
try {
HeuristicsNet HNmodel =
new PetriNetToHeuristicNetConverter()
.toHeuristicsNet(
PetriNetToHeuristicNetConverter.removeUnnecessaryInvisibleTasksFromPetriNet(
(PetriNet) model.clone()));
HeuristicsNet HNreferenceModel =
new PetriNetToHeuristicNetConverter()
.toHeuristicsNet(
PetriNetToHeuristicNetConverter.removeUnnecessaryInvisibleTasksFromPetriNet(
(PetriNet) referenceModel.clone()));
TraceParsing behavioralMetrics = new TraceParsing(referenceLog, HNreferenceModel, HNmodel);
return behavioralMetrics.getRecall();
} catch (Exception e) {
System.err.println(
"BehavioralRecallMetric >>> Could not calculate the behavioral recall value!");
e.printStackTrace();
}
return BenchmarkMetric.INVALID_MEASURE_VALUE;
}
