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package ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.io
import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.app.Domain
import ca.mcgill.ecse.dslreasoner.realistic.metrics.calculator.metrics.MetricSampleGroup
import hu.bme.mit.inf.dslreasoner.domains.yakindu.sgraph.yakindumm.impl.YakindummPackageImpl
import java.util.HashMap
/**
* Read the sample of the distribution of a metric provided the csv file of the metric
*/
class RepMetricsReader {
static def read(Domain d){
var reader = new GraphReader(YakindummPackageImpl.eINSTANCE, '.xmi');
var domainRepPath = DataName.REP_PATH + d.name + '/';
var rep = new MetricSampleGroup()
var out_d = readMetrics(reader, domainRepPath + DataName.OUT_D_REP);
rep.mpcSamples = readMetrics(reader, domainRepPath + DataName.MPC_REP).mpcSamples;
rep.outDegreeSamples = out_d.outDegreeSamples;
rep.naSamples = readMetrics(reader, domainRepPath + DataName.NA_REP).naSamples;
rep.typedOutDegreeSamples = out_d.typedOutDegreeSamples;
rep.edgeTypeSamples = out_d.edgeTypeSamples;
//TODO: Parameterize the prior node distribution
var nodeTypeSamples = new HashMap<String, Double>();
nodeTypeSamples.put('Entry', 0.04257802080554814);
nodeTypeSamples.put('Choice', 0.1267671379034409);
nodeTypeSamples.put('State', 0.1596092291277674);
nodeTypeSamples.put('Transition', 0.6138636969858629);
nodeTypeSamples.put('Statechart', 0.010136036276340358);
nodeTypeSamples.put('Region', 0.04467858095492131);
nodeTypeSamples.put('Exit', 0.0018338223526273673);
nodeTypeSamples.put('FinalState', 0.0005334755934915977);
rep.nodeTypeSamples = nodeTypeSamples;
return rep;
}
/**
* Read representative model
*/
private static def readMetrics(GraphReader r, String path){
var model = r.readModels(path).head;
return model.evaluateAllMetricsToSamples();
}
}
class DataName{
public static val REP_PATH = 'data/';
public static val MPC_REP = 'mpc_rep';
public static val NA_REP = 'na_rep';
public static val OUT_D_REP = 'out_d_rep';
}
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