conversor fix: #59 and using global random seed

IDSIA · Feb 14, 2021 · a3beffb · a3beffb
1 parent 8d232d7
commit a3beffb
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Showing 3 changed files with 10 additions and 3 deletions.
diff --git a/src/main/java/ch/idsia/crema/factor/convert/ExtensiveLinearToRandomBayesianFactor.java b/src/main/java/ch/idsia/crema/factor/convert/ExtensiveLinearToRandomBayesianFactor.java
@@ -5,14 +5,15 @@
 import ch.idsia.crema.factor.credal.linear.ExtensiveLinearFactor;
 import ch.idsia.crema.solver.LinearSolver;
 import ch.idsia.crema.solver.commons.Simplex;
+import ch.idsia.crema.utility.RandomUtil;
 import org.apache.commons.math3.optim.nonlinear.scalar.GoalType;
 
 import java.util.Random;
 
 // FIXME rename
 @SuppressWarnings("rawtypes")
 public class ExtensiveLinearToRandomBayesianFactor implements Converter<ExtensiveLinearFactor, BayesianFactor> {
-	private final Random random = new Random();
+	private final Random random = RandomUtil.getRandom();
 
 	public BayesianFactor apply(ExtensiveLinearFactor s) {
 		return apply(s, -1);

diff --git a/src/main/java/ch/idsia/crema/factor/convert/SeparateLinearToRandomBayesian.java b/src/main/java/ch/idsia/crema/factor/convert/SeparateLinearToRandomBayesian.java
@@ -7,6 +7,7 @@
 import ch.idsia.crema.solver.LinearSolver;
 import ch.idsia.crema.solver.SolverFactory;
 import ch.idsia.crema.utility.ArraysUtil;
+import ch.idsia.crema.utility.RandomUtil;
 import org.apache.commons.math3.optim.nonlinear.scalar.GoalType;
 
 import java.util.Random;
@@ -31,7 +32,7 @@ public class SeparateLinearToRandomBayesian implements Converter<SeparateLinearF
 	private boolean log = false;
 
 	public SeparateLinearToRandomBayesian() {
-		random = new Random();
+		random = RandomUtil.getRandom();
 	}
 
 	public SeparateLinearToRandomBayesian(int seed) {

diff --git a/src/main/java/ch/idsia/crema/inference/approxlp/CredalApproxLP.java b/src/main/java/ch/idsia/crema/inference/approxlp/CredalApproxLP.java
@@ -28,12 +28,17 @@ public M getInferenceModel(int target, TIntIntMap evidence) {
 		return (M) removeBarren.execute(new CutObservedSepHalfspace().execute(model, evidence), target, evidence);
 	}
 
+	@Override
+	public IntervalFactor query(int target) throws InterruptedException{
+		return query(target, new TIntIntHashMap());
+	}
+
 	@Override
 	public IntervalFactor query(int target, TIntIntMap evidence) throws InterruptedException {
 
 		M infModel = getInferenceModel(target, evidence);
 
-		TIntIntMap filteredEvidence = new TIntIntHashMap(evidence);
+		TIntIntMap filteredEvidence = new TIntIntHashMap();
 
 		// update the evidence
 		for (int v : evidence.keys()) {