Gibbs sampling

src/main/java/blog/bn/CBN.java

@@ -36,23 +36,31 @@
 package blog.bn;
 
 import blog.common.DGraph;
+import blog.world.PartialWorld;
 
 /**
  * A contingent bayes net (CBN) contains a set of random variables V. For each
  * random variable X in V, there is an associated domain dom(X) and decision
  * tree T_X. The decision tree is a binary tree where each node is a predicate
  * on some subset of V. Each leaf of T_X is a probability distribution
  * parametrized by a subset of V. (Summarized from Arora et. al, UAI-10)
- *
- * TODO: As the requirements for CBNs become clearer, add actual methods here
- *
- * @author rbharath
- * @date Aug 11, 2012
+ * 
+ * @author Da Tang
+ * @since Sep 07, 2014
  */
 
-public interface CBN extends DGraph { 
-	/**
-	 * An empty CBN
-	 */
-	static final CBN EMPTY_CBN = new DefaultCBN();
+public interface CBN extends DGraph {
+  /**
+   * An empty CBN
+   */
+  static final CBN EMPTY_CBN = new DefaultCBN();
+
+  /**
+   * Calculating whether an edge Y -> Z is contingent on variable X or not in
+   * the
+   * PartialWorld or not.
+   * 
+   */
+  boolean isContingentOn(PartialWorld world, BayesNetVar X, BayesNetVar Y,
+      BayesNetVar Z);
 }

src/main/java/blog/bn/DefaultCBN.java

@@ -37,27 +37,76 @@
 
 import java.util.HashMap;
 import java.util.Iterator;
+import java.util.LinkedList;
 import java.util.Map;
 
 import blog.common.DefaultDGraph;
-import blog.common.DefaultDGraph.NodeInfo;
+import blog.common.Util;
+import blog.sample.TraceParentRecEvalContext;
+import blog.world.PartialWorld;
 
 /**
- * This class provides a default implementation of CBNs. Over the next few weeks,
- * all inference algorithms will be modified to use CBNs.
+ * This class provides a default implementation of CBNs.
+ * Uses a DefaultCBN rather than a DefaultDGraph, so as to avoid
+ * ClassCastExceptions.
+ * 
+ * @author Da Tang
+ * @since Sep 7, 2014
  */
 
 public class DefaultCBN extends DefaultDGraph implements CBN {
-	/**
-	 * Uses a DefaultCBN rather than a DefaultDGraph, so as to avoid ClassCastExceptions
-	 */
-	public Object clone() {
-		DefaultCBN clone = new DefaultCBN();
-		clone.nodeInfo = (Map) ((HashMap) nodeInfo).clone();
-		for (Iterator iter = clone.nodeInfo.entrySet().iterator(); iter.hasNext();) {
-			Map.Entry entry = (Map.Entry) iter.next();
-			entry.setValue(((NodeInfo) entry.getValue()).clone());
-		}
-		return clone;
-	}
+  /**
+   * clone method for the class Default CBN.
+   */
+  public Object clone() {
+    DefaultCBN clone = new DefaultCBN();
+    clone.nodeInfo = (Map) ((HashMap) nodeInfo).clone();
+    for (Iterator iter = clone.nodeInfo.entrySet().iterator(); iter.hasNext();) {
+      Map.Entry entry = (Map.Entry) iter.next();
+      entry.setValue(((NodeInfo) entry.getValue()).clone());
+    }
+    return clone;
+  }
+
+  @Override
+  public boolean isContingentOn(PartialWorld world, BayesNetVar X,
+      BayesNetVar Y, BayesNetVar Z) {
+    TraceParentRecEvalContext context = new TraceParentRecEvalContext(world);
+    if (Z instanceof VarWithDistrib) {
+      ((VarWithDistrib) Z).getDistrib(context);
+    } else if (Z instanceof DerivedVar) {
+      ((DerivedVar) Z).getValue(context);
+    } else {
+      return true;
+    }
+
+    LinkedList<BayesNetVar> parentTrace = new LinkedList<BayesNetVar>();
+    parentTrace.addAll(context.getParentTrace());
+
+    int x = parentTrace.indexOf(X), y = parentTrace.indexOf(Y);
+    if (x < 0 || y < 0) {
+      return false;
+    }
+    if (X instanceof NumberVar) {
+      if (x < y && world.getCBN().getAncestors(Y).contains(X)) {
+        if (Util.verbose()) {
+          System.out.println("\t Contingent relations type 1: " + X.toString()
+              + " " + Y.toString() + " " + Z.toString());
+        }
+        return true;
+      } else {
+        return false;
+      }
+    } else {
+      if (x < y) {
+        if (Util.verbose()) {
+          System.out.println("\t Contingent relations type 2: " + X.toString()
+              + " " + Y.toString() + " " + Z.toString());
+        }
+        return true;
+      } else {
+        return false;
+      }
+    }
+  }
 }

src/main/java/blog/bn/PatchCBN.java

@@ -35,23 +35,70 @@
 
 package blog.bn;
 
-import blog.common.ParentUpdateDGraph;
+import java.util.LinkedList;
+
 import blog.common.DGraph;
+import blog.common.ParentUpdateDGraph;
+import blog.common.Util;
+import blog.sample.TraceParentRecEvalContext;
+import blog.world.PartialWorld;
 
 /**
  * A patch data structure to an underlying CBN that represents changes to
- * the set of nodes and to the parent sets of existing nodes. Currently is a 
+ * the set of nodes and to the parent sets of existing nodes. Currently is a
  * thin wrapper over ParentUpdateDGraph.
- *
+ * 
  * @author rbharath
  * @date August 12, 2012
  */
 public class PatchCBN extends ParentUpdateDGraph implements CBN {
-	/**
-	 * Creates a new ParentUpdateDGraph that represents no changes to the given
-	 * underlying graph.
-	 */
-	public PatchCBN(CBN underlying) {
-        super((DGraph) underlying);
-	}
+  /**
+   * Creates a new ParentUpdateDGraph that represents no changes to the given
+   * underlying graph.
+   */
+  public PatchCBN(CBN underlying) {
+    super((DGraph) underlying);
+  }
+
+  @Override
+  public boolean isContingentOn(PartialWorld world, BayesNetVar X,
+      BayesNetVar Y, BayesNetVar Z) {
+    TraceParentRecEvalContext context = new TraceParentRecEvalContext(world);
+    if (Z instanceof VarWithDistrib) {
+      ((VarWithDistrib) Z).getDistrib(context);
+    } else if (Z instanceof DerivedVar) {
+      ((DerivedVar) Z).getValue(context);
+    } else {
+      return true;
+    }
+
+    LinkedList<BayesNetVar> parentTrace = new LinkedList<BayesNetVar>();
+    parentTrace.addAll(context.getParentTrace());
+
+    int x = parentTrace.indexOf(X), y = parentTrace.indexOf(Y);
+    if (x < 0 || y < 0) {
+      return false;
+    }
+    if (X instanceof NumberVar) {
+      if (x < y && world.getCBN().getAncestors(Y).contains(X)) {
+        if (Util.verbose()) {
+          System.out.println("\t Contingent relations type 1: " + X.toString()
+              + " " + Y.toString() + " " + Z.toString());
+        }
+        return true;
+      } else {
+        return false;
+      }
+    } else {
+      if (x < y) {
+        if (Util.verbose()) {
+          System.out.println("\t Contingent relations type 2: " + X.toString()
+              + " " + Y.toString() + " " + Z.toString());
+        }
+        return true;
+      } else {
+        return false;
+      }
+    }
+  }
 }

src/main/java/blog/sample/AbstractProposer.java

@@ -123,7 +123,7 @@ public PartialWorldDiff reduceToCore(PartialWorld curWorld, BayesNetVar var) {
   }
 
   public double proposeNextState(PartialWorldDiff proposedWorld,
-      BayesNetVar var, int i) {
+      BayesNetVar var, Object value) {
     return 0;
   }