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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
/**
* 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);
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;
rep.nodeTypeSamples = out_d.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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