Changed temporal input into Classifiers to activeCells; changed tests to accommodate; changed ArrayUtils.isSparse to short circuit when false for speed up; Added SDR class for sdr operations

Author: cogmission

src/main/java/org/numenta/nupic/Parameters.java

@@ -474,6 +474,7 @@ public void apply(Object cn) {
         Set<KEY> presentKeys = paramMap.keySet();
         synchronized (paramMap) {
             for (KEY key : presentKeys) {
+                if(key == KEY.RANDOM) continue;
                 beanUtil.setSimpleProperty(cn, key.fieldName, getParameterByKey(key));
             }
         }

src/main/java/org/numenta/nupic/algorithms/TemporalMemory.java

@@ -311,13 +311,14 @@ public void learnOnSegments(Connections c, Set<DistalDendrite> prevActiveSegment
     public void computePredictiveCells(Connections c, ComputeCycle cycle, Set<Cell> activeCells) {
         TObjectIntMap<DistalDendrite> numActiveConnectedSynapsesForSegment = new TObjectIntHashMap<>();
         TObjectIntMap<DistalDendrite> numActiveSynapsesForSegment = new TObjectIntHashMap<>();
+        double connectedPermanence = c.getConnectedPermanence();
 
         for(Cell cell : activeCells) {
             for(Synapse syn : c.getReceptorSynapses(cell)) {
                 DistalDendrite segment = (DistalDendrite)syn.getSegment();
                 double permanence = syn.getPermanence();
 
-                if(permanence >= c.getConnectedPermanence()) {
+                if(permanence >= connectedPermanence) {
                     numActiveConnectedSynapsesForSegment.adjustOrPutValue(segment, 1, 1);    
 
                     if(numActiveConnectedSynapsesForSegment.get(segment) >= c.getActivationThreshold()) {
@@ -454,22 +455,6 @@ public Cell getLeastUsedCell(Connections c, List<Cell> columnCells) {
         return l.get(randomIdx);
     }
 
-    /**
-     * Used locally to return results of column Burst
-     */
-    class BurstResult {
-        Set<Cell> activeCells;
-        Set<Cell> winnerCells;
-        Set<DistalDendrite> learningSegments;
-        
-        public BurstResult(Set<Cell> activeCells, Set<Cell> winnerCells, Set<DistalDendrite> learningSegments) {
-            super();
-            this.activeCells = activeCells;
-            this.winnerCells = winnerCells;
-            this.learningSegments = learningSegments;
-        }
-    }
-    
     /**
      * Used locally to return best cell/segment pair
      */

src/main/java/org/numenta/nupic/network/Inference.java

@@ -22,11 +22,15 @@
 package org.numenta.nupic.network;
 
 import java.util.Map;
+import java.util.Set;
 
+import org.numenta.nupic.ComputeCycle;
 import org.numenta.nupic.algorithms.CLAClassifier;
 import org.numenta.nupic.algorithms.ClassifierResult;
 import org.numenta.nupic.algorithms.SpatialPooler;
+import org.numenta.nupic.algorithms.TemporalMemory;
 import org.numenta.nupic.encoders.Encoder;
+import org.numenta.nupic.model.Cell;
 import org.numenta.nupic.util.NamedTuple;
 
 import rx.functions.Func1;
@@ -48,6 +52,11 @@ public interface Inference {
      * @return
      */
     public int getRecordNum();
+    /**
+     * Returns the {@link ComputeCycle}
+     * @return
+     */
+    public ComputeCycle getComputeCycle();
     /**
      * Returns a custom Object during sequence processing where one or more 
      * {@link Func1}(s) were added to a {@link Layer} in between algorithmic
@@ -108,20 +117,25 @@ public interface Inference {
      * Returns the column activation from a {@link SpatialPooler}
      * @return
      */
-    public int[] getActiveColumns();
+    public int[] getFeedForwardActiveColumns();
     /**
      * Returns the column activations in sparse form
      * @return
      */
-    public int[] getSparseActives();
+    public int[] getFeedForwardSparseActives();
+    /**
+     * Returns the column activation from a {@link TemporalMemory}
+     * @return
+     */
+    public Set<Cell> getActiveCells();
     /**
      * Returns the predicted output from the last inference cycle.
      * @return
      */
-    public int[] getPreviousPrediction();
+    public Set<Cell> getPreviousPredictiveCells();
     /**
      * Returns the currently predicted columns.
      * @return
      */
-    public int[] getPredictedColumns();
+    public Set<Cell> getPredictiveCells();
 }