ACRF-example-fixes

src/cc/mallet/grmm/examples/CrossTemplate1.java

@@ -20,24 +20,26 @@ public class CrossTemplate1 extends ACRF.SequenceTemplate {
   private int lvl1 = 0;
   private int lvl2 = 1;
 
-  public CrossTemplate1 (int lvl1, int lvl2)
-  {
+  public CrossTemplate1(int lvl1, int lvl2) {
     this.lvl1 = lvl1;
     this.lvl2 = lvl2;
   }
 
-  protected void addInstantiatedCliques (ACRF.UnrolledGraph graph, FeatureVectorSequence fvs, LabelsAssignment lblseq)
-  {
-    for (int t = 0; t < lblseq.size() - 1; t++) {
-      Variable var1 = lblseq.varOfIndex (t, lvl1);
-      Variable var2 = lblseq.varOfIndex (t + 1, lvl2);
-      assert var1 != null : "Couldn't get label factor "+lvl1+" time "+t;
-      assert var2 != null : "Couldn't get label factor "+lvl2+" time "+(t+1);
+  protected void addInstantiatedCliques(ACRF.UnrolledGraph graph, FeatureVectorSequence fvs, LabelsAssignment lblseq) {
+    for (int t = 0; t < lblseq.maxTime() - 1; t++) {
+      try {
+        Variable var1 = lblseq.varOfIndex(t, lvl1);
+        Variable var2 = lblseq.varOfIndex(t + 1, lvl2);
+        assert var2 != null : "Couldn't get label factor " + lvl2 + " time " + (t + 1);
+        assert var1 != null : "Couldn't get label factor " + lvl1 + " time " + t;
 
-      Variable[] vars = new Variable[] { var1, var2 };
-      FeatureVector fv = fvs.getFeatureVector (t);
-      ACRF.UnrolledVarSet vs = new ACRF.UnrolledVarSet (graph, this, vars, fv);
-      graph.addClique (vs);
+        Variable[] vars = new Variable[]{var1, var2};
+        FeatureVector fv = fvs.getFeatureVector(t);
+        ACRF.UnrolledVarSet vs = new ACRF.UnrolledVarSet(graph, this, vars, fv);
+        graph.addClique(vs);
+      } catch (ArrayIndexOutOfBoundsException e) {
+        throw e;
+      }
     }
   }
 

src/cc/mallet/grmm/examples/SimpleCrfExample.java

@@ -45,7 +45,7 @@ public static void main (String[] args) throws FileNotFoundException
                                          true));
 
     InstanceList testing = new InstanceList (pipe);
-    training.addThruPipe (new LineGroupIterator (new FileReader (testFile),
+    testing.addThruPipe (new LineGroupIterator (new FileReader (testFile),
                                          Pattern.compile ("\\s*"),
                                          true));
 

src/cc/mallet/grmm/inference/TRP.java

@@ -543,7 +543,7 @@ public void computeMarginals (FactorGraph m)
       dumpForIter (iter, tree);
     }
     iterUsed = iter;
-    logger.info ("TRP used " + iter + " iterations.");
+    logger.fine ("TRP used " + iter + " iterations.");
 
     doneWithGraph (m);
   }

src/cc/mallet/grmm/learning/ACRF.java

@@ -37,7 +37,7 @@
  * Class for Arbitrary CRFs.  These are CRFs with completely
  *  arbitrary graphical structure.  The user passes in a list
  *  of instances of ACRF.CliqueFactory, which get to look at
- *  the sequence and decide what 
+ *  the sequence and decide what
  *
  * @author <a href="mailto:[email protected]">Charles Sutton</a>
  * @version $Id: ACRF.java,v 1.1 2007/10/22 21:37:43 mccallum Exp $
@@ -157,7 +157,7 @@ public void setGaussianPriorVariance (double gaussianPriorVariance)
   {
     this.gaussianPriorVariance = gaussianPriorVariance;
   }
-  
+
 
   public void setGraphProcessor (GraphPostProcessor graphProcessor)
   {
@@ -791,7 +791,7 @@ private void computeCPFs ()
         addFactorInternal (clique, ptl);
         clique.tmpl.modifyPotential (this, clique, ptl);
         uvsMap.put (ptl, clique);
-        
+
         // sigh
         LogTableFactor unif = new LogTableFactor (clique);
         residTmp.add (Factors.distLinf (unif, ptl));
@@ -1823,17 +1823,25 @@ public void addInstantiatedCliques (ACRF.UnrolledGraph graph,
                                         FeatureVectorSequence fvs,
                                         LabelsAssignment lblseq)
     {
+      if (lblseq.maxTime() == 1) {
+        Variable v1 = lblseq.varOfIndex(0, factor);
+        FeatureVector fv = fvs.getFeatureVector(0);
+        ACRF.UnrolledVarSet clique = new ACRF.UnrolledVarSet(graph, this, new Variable[]{v1}, fv);
+        graph.addClique(clique);
+        return;
+      }
+
       for (int i = 0; i < lblseq.maxTime() - 1; i++) {
-        Variable v1 = lblseq.varOfIndex (i, factor);
-        Variable v2 = lblseq.varOfIndex (i + 1, factor);
-        FeatureVector fv = fvs.getFeatureVector (i);
+        Variable v1 = lblseq.varOfIndex(i, factor);
+        Variable v2 = lblseq.varOfIndex(i + 1, factor);
+        FeatureVector fv = fvs.getFeatureVector(i);
 
-        Variable[] vars = new Variable[] { v1, v2 };
-        assert v1 != null : "Couldn't get label factor "+factor+" time "+i;
-        assert v2 != null : "Couldn't get label factor "+factor+" time "+(i+1);
+        Variable[] vars = new Variable[]{v1, v2};
+        assert v1 != null : "Couldn't get label factor " + factor + " time " + i;
+        assert v2 != null : "Couldn't get label factor " + factor + " time " + (i + 1);
 
-        ACRF.UnrolledVarSet clique = new ACRF.UnrolledVarSet (graph, this, vars, fv);
-        graph.addClique (clique);
+        ACRF.UnrolledVarSet clique = new ACRF.UnrolledVarSet(graph, this, vars, fv);
+        graph.addClique(clique);
       }
     }