public void CalculateAligningObservedFitnessWithNoisyLogTest()
{
// Arrange
// Act
var fitness = AlignmentBased.TestAlignment(log, log_noisy);
// Assert
Assert.AreEqual(-1, fitness);
}
public static double TestAlignment(Dictionary <List <string>, int> trace_frequencies,
Dictionary <List <string>, int> trace_frequencies_noisy)
{
var minedNet = AlphaMiner.mine(trace_frequencies);
var completelyFits = true;
AlignmentBased res = new AlignmentBased();
foreach (KeyValuePair <List <string>, int> trace in trace_frequencies_noisy)
{
string alignment = "";
res.traceCount += 1;
bool match = true;
// Console.WriteLine(" \n");
minedNet.InitializeTokens();
minedNet.AddMarking(1);
foreach (var step in trace.Key)
{
// Console.Write(step+"-");
var transitionId = minedNet.TransitionNameToId(step);
var isEnabled = minedNet.IsEnabled(transitionId);
if (!isEnabled)
{
match = false;
// Console.WriteLine(step);
FindOptimalAlignment(trace, minedNet, transitionId, alignment);
completelyFits = false;
break;
}
else
{
alignment += step + " - ";
}
minedNet.FireTransition(transitionId);
}
if (match == true)
{
res.totalFitness += 1;
}
}
if (completelyFits)
{
Console.WriteLine("Fitness: " + res.totalFitness / res.traceCount);
return((double)res.totalFitness / res.traceCount);
}
else
{
return(-1);
}
}
