matchingSegments = IntStream.range(0, activity.numActiveConnected.length)
+ .filter(i -> activity.numActivePotential[i] >= conn.getMinThreshold())
+ .mapToObj(i -> conn.segmentForFlatIdx(i))
+ .collect(Collectors.toList());
+
+ Collections.sort(activeSegments, conn.segmentPositionSortKey);
+ Collections.sort(matchingSegments, conn.segmentPositionSortKey);
+
+ cycle.activeSegments = activeSegments;
+ cycle.matchingSegments = matchingSegments;
+
+ conn.lastActivity = activity;
+ conn.setActiveCells(new LinkedHashSet<>(cycle.activeCells));
conn.setWinnerCells(new LinkedHashSet<>(cycle.winnerCells));
- conn.setActiveSegmentOverlaps(activity.activeSegments);
- conn.setMatchingSegmentOverlaps(activity.matchingSegments);
+ conn.setActiveSegments(activeSegments);
+ conn.setMatchingSegments(matchingSegments);
// Forces generation of the predictive cells from the above active segments
conn.clearPredictiveCells();
conn.getPredictiveCells();
-
- return cycle;
- }
-
- /**
- * Indicates the start of a new sequence and resets the sequence
- * state of the TM.
- *
- * @param connections The {@link Connections} object containing the state
+
+ if(learn) {
+ activeSegments.stream().forEach(s -> conn.recordSegmentActivity(s));
+ conn.startNewIteration();
+ }
+ }
+
+ /**
+ * Indicates the start of a new sequence. Clears any predictions and makes sure
+ * synapses don't grow to the currently active cells in the next time step.
*/
@Override
public void reset(Connections connections) {
connections.getActiveCells().clear();
connections.getWinnerCells().clear();
- connections.getActiveSegmentOverlaps().clear();
- connections.getMatchingSegmentOverlaps().clear();
+ connections.getActiveSegments().clear();
+ connections.getMatchingSegments().clear();
}
/**
- *
- * Determines which cells in a predicted column should be added to
- * winner cells list and calls adaptSegment on the segments that correctly
- * predicted this column.
- *
- * Pseudocode:
- *
- *
- * for each cell in the column that has an active distal dendrite segment
+ * Determines which cells in a predicted column should be added to winner cells
+ * list, and learns on the segments that correctly predicted this column.
+ *
+ * @param conn the connections
+ * @param activeSegments Active segments in the specified column
+ * @param matchingSegments Matching segments in the specified column
+ * @param prevActiveCells Active cells in `t-1`
+ * @param prevWinnerCells Winner cells in `t-1`
+ * @param learn If true, grow and reinforce synapses
+ *
+ *
+ * Pseudocode:
+ * for each cell in the column that has an active distal dendrite segment
* mark the cell as active
* mark the cell as a winner cell
* (learning) for each active distal dendrite segment
- * strengthen active synapses
- * weaken inactive synapses
+ * strengthen active synapses
+ * weaken inactive synapses
+ * grow synapses to previous winner cells
*
- *
*
- * @param conn {@link Connections} instance for the tm
- * @param activeSegments A {@link Iterable} of SegmentOverlap objects for the
- * column compute is operating on that are active
- * @param prevActiveCells Active cells in `t-1`
- * @param permanenceIncrement Amount by which permanences of synapses are
- * incremented during learning.
- * @param permanenceDecrement Amount by which permanences of synapses are
- * decremented during learning.
- * @param learn Determines if permanences are adjusted
- * @return A list of predicted cells that will be added to active cells and winner cells.
- */
- public List activatePredictedColumn(Connections conn, List activeSegments,
- Set prevActiveCells, double permanenceIncrement, double permanenceDecrement, boolean learn) {
-
- List cellsToAdd = new ArrayList<>();
- Cell cell = null;
- for(SegmentOverlap active : activeSegments) {
- boolean newCell = cell != active.segment.getParentCell();
- if(newCell) {
- cell = active.segment.getParentCell();
- cellsToAdd.add(cell);
+ * @return A list of predicted cells that will be added to active cells and winner
+ * cells.
+ */
+ public List activatePredictedColumn(Connections conn, List activeSegments,
+ List matchingSegments, Set prevActiveCells, Set prevWinnerCells,
+ double permanenceIncrement, double permanenceDecrement, boolean learn) {
+
+ List cellsToAdd = new ArrayList<>();
+ Cell previousCell = null;
+ Cell currCell;
+ for(DistalDendrite segment : activeSegments) {
+ if((currCell = segment.getParentCell()) != previousCell) {
+ cellsToAdd.add(currCell);
+ previousCell = currCell;
}
if(learn) {
- adaptSegment(conn, active.segment, prevActiveCells, permanenceIncrement, permanenceDecrement);
+ adaptSegment(conn, segment, prevActiveCells, permanenceIncrement, permanenceDecrement);
+
+ int numActive = conn.getLastActivity().numActivePotential[segment.getIndex()];
+ int nGrowDesired = conn.getMaxNewSynapseCount() - numActive;
+
+ if(nGrowDesired > 0) {
+ growSynapses(conn, prevWinnerCells, segment, conn.getInitialPermanence(),
+ nGrowDesired, conn.getRandom());
+ }
}
}
return cellsToAdd;
- }
-
- /**
+ }
+
+ /**
* Activates all of the cells in an unpredicted active column,
* chooses a winner cell, and, if learning is turned on, either adapts or
* creates a segment. growSynapses is invoked on this segment.
@@ -278,15 +331,13 @@ public List activatePredictedColumn(Connections conn, List
*
* @param conn Connections instance for the TM
* @param column Bursting {@link Column}
+ * @param matchingSegments List of matching {@link DistalDendrite}s
* @param prevActiveCells Active cells in `t-1`
* @param prevWinnerCells Winner cells in `t-1`
- * @param initialPermanence Initial permanence of a new synapse.
- * @param maxNewSynapseCount The maximum number of synapses added to
- a segment during learning
* @param permanenceIncrement Amount by which permanences of synapses
- are decremented during learning
+ * are decremented during learning
* @param permanenceDecrement Amount by which permanences of synapses
- are incremented during learning
+ * are incremented during learning
* @param random Random number generator
* @param learn Whether or not learning is enabled
*
@@ -294,7 +345,7 @@ public List activatePredictedColumn(Connections conn, List
* cells list of the processed column's cells
* bestCell the best cell
*/
- public Tuple burstColumn(Connections conn, Column column, List matchingSegments,
+ public Tuple burstColumn(Connections conn, Column column, List matchingSegments,
Set prevActiveCells, Set prevWinnerCells, double permanenceIncrement, double permanenceDecrement,
Random random, boolean learn) {
@@ -302,15 +353,19 @@ public Tuple burstColumn(Connections conn, Column column, List m
Cell bestCell = null;
if(!matchingSegments.isEmpty()) {
- SegmentOverlap bestSegment = matchingSegments.stream().max((so1, so2) -> so1.overlap - so2.overlap).get();
- bestCell = bestSegment.segment.getParentCell();
+ int[] numPoten = conn.getLastActivity().numActivePotential;
+ Comparator cmp = (dd1,dd2) -> numPoten[dd1.getIndex()] - numPoten[dd2.getIndex()];
+
+ DistalDendrite bestSegment = matchingSegments.stream().max(cmp).get();
+ bestCell = bestSegment.getParentCell();
+
if(learn) {
- adaptSegment(conn, bestSegment.segment, prevActiveCells, permanenceIncrement, permanenceDecrement);
+ adaptSegment(conn, bestSegment, prevActiveCells, permanenceIncrement, permanenceDecrement);
- int nGrowDesired = conn.getMaxNewSynapseCount() - bestSegment.overlap;
+ int nGrowDesired = conn.getMaxNewSynapseCount() - numPoten[bestSegment.getIndex()];
if(nGrowDesired > 0) {
- growSynapses(conn, prevWinnerCells, bestSegment.segment, conn.getInitialPermanence(),
+ growSynapses(conn, prevWinnerCells, bestSegment, conn.getInitialPermanence(),
nGrowDesired, random);
}
}
@@ -341,29 +396,32 @@ public Tuple burstColumn(Connections conn, Column column, List m
*
*
* @param conn Connections instance for the tm
- * @param matchingSegments An iterable of SegmentOverlap objects
+ * @param activeSegments An iterable of {@link DistalDendrite} actives
+ * @param matchingSegments An iterable of {@link DistalDendrite} matching
* for the column compute is operating on
* that are matching; None if empty
* @param prevActiveCells Active cells in `t-1`
- * @param predictedSegmentDecrement Amount by which permanences of synapses
+ * @param prevWinnerCells Winner cells in `t-1`
* are decremented during learning.
+ * @param predictedSegmentDecrement Amount by which segments are punished for incorrect predictions
*/
- public void punishPredictedColumn(Connections conn, List matchingSegments,
- Set prevActiveCells, double predictedSegmentDecrement) {
+ public void punishPredictedColumn(Connections conn, List activeSegments,
+ List matchingSegments, Set prevActiveCells, Set prevWinnerCells,
+ double predictedSegmentDecrement) {
if(predictedSegmentDecrement > 0) {
- for(SegmentOverlap segment : matchingSegments) {
- adaptSegment(conn, segment.segment, prevActiveCells, -conn.getPredictedSegmentDecrement(), 0);
+ for(DistalDendrite segment : matchingSegments) {
+ adaptSegment(conn, segment, prevActiveCells, -conn.getPredictedSegmentDecrement(), 0);
}
}
}
+
+
+ ////////////////////////////
+ // Helper Methods //
+ ////////////////////////////
-
- ////////////////////////////////
- // Helper Functions //
- ////////////////////////////////
-
- /**
+ /**
* Gets the cell with the smallest number of segments.
* Break ties randomly.
*
@@ -377,7 +435,7 @@ public Cell leastUsedCell(Connections conn, List cells, Random random) {
List leastUsedCells = new ArrayList<>();
int minNumSegments = Integer.MAX_VALUE;
for(Cell cell : cells) {
- int numSegments = conn.unDestroyedSegmentsForCell(cell).size();
+ int numSegments = conn.numSegments(cell);
if(numSegments < minNumSegments) {
minNumSegments = numSegments;
@@ -416,28 +474,25 @@ public void growSynapses(Connections conn, Set prevWinnerCells, DistalDend
List candidates = new ArrayList<>(prevWinnerCells);
Collections.sort(candidates);
- int eligibleEnd = candidates.size() - 1;
- for(Synapse synapse : conn.unDestroyedSynapsesForSegment(segment)) {
+ for(Synapse synapse : conn.getSynapses(segment)) {
Cell presynapticCell = synapse.getPresynapticCell();
- int index = candidates.subList(0, eligibleEnd + 1).indexOf(presynapticCell);
+ int index = candidates.indexOf(presynapticCell);
if(index != -1) {
- candidates.set(index, candidates.get(eligibleEnd));
- eligibleEnd--;
+ candidates.remove(index);
}
}
- int candidatesLength = eligibleEnd + 1;
+ int candidatesLength = candidates.size();
int nActual = nDesiredNewSynapses < candidatesLength ? nDesiredNewSynapses : candidatesLength;
for(int i = 0;i < nActual;i++) {
- int rand = random.nextInt(candidatesLength);
+ int rand = random.nextInt(candidates.size());
conn.createSynapse(segment, candidates.get(rand), initialPermanence);
- candidates.set(rand, candidates.get(candidatesLength - 1));
- candidatesLength--;
+ candidates.remove(rand);
}
}
-
+
/**
* Updates synapses on segment.
* Strengthens active synapses; weakens inactive synapses.
@@ -451,7 +506,10 @@ public void growSynapses(Connections conn, Set prevWinnerCells, DistalDend
public void adaptSegment(Connections conn, DistalDendrite segment, Set prevActiveCells,
double permanenceIncrement, double permanenceDecrement) {
- for(Synapse synapse : conn.unDestroyedSynapsesForSegment(segment)) {
+ // Destroying a synapse modifies the set that we're iterating through.
+ List synapsesToDestroy = new ArrayList<>();
+
+ for(Synapse synapse : conn.getSynapses(segment)) {
double permanence = synapse.getPermanence();
if(prevActiveCells.contains(synapse.getPresynapticCell())) {
@@ -470,15 +528,62 @@ public void adaptSegment(Connections conn, DistalDendrite segment, Set pre
// permanence = new BigDecimal(permanence).setScale(1, RoundingMode.HALF_UP).doubleValue();
if(permanence < EPSILON) {
- conn.destroySynapse(synapse);
+ synapsesToDestroy.add(synapse);
}else{
synapse.setPermanence(conn, permanence);
}
}
+ for(Synapse s : synapsesToDestroy) {
+ conn.destroySynapse(s);
+ }
+
if(conn.numSynapses(segment) == 0) {
conn.destroySegment(segment);
}
}
+ /**
+ * Used in the {@link TemporalMemory#compute(Connections, int[], boolean)} method
+ * to make pulling values out of the {@link GroupBy2} more readable and named.
+ */
+ @SuppressWarnings("unchecked")
+ public static class ColumnData implements Serializable {
+ /** Default Serial */
+ private static final long serialVersionUID = 1L;
+ Tuple t;
+
+ public ColumnData() {}
+
+ public ColumnData(Tuple t) {
+ this.t = t;
+ }
+
+ public Column column() { return (Column)t.get(0); }
+ public List activeColumns() { return (List)t.get(1); }
+ public List activeSegments() {
+ return ((List)t.get(2)).get(0).equals(Slot.empty()) ?
+ Collections.emptyList() :
+ (List)t.get(2);
+ }
+ public List matchingSegments() {
+ return ((List)t.get(3)).get(0).equals(Slot.empty()) ?
+ Collections.emptyList() :
+ (List)t.get(3);
+ }
+
+ public ColumnData set(Tuple t) { this.t = t; return this; }
+
+ /**
+ * Returns a boolean flag indicating whether the slot contained by the
+ * tuple at the specified index is filled with the special empty
+ * indicator.
+ *
+ * @param memberIndex the index of the tuple to assess.
+ * @return true if not none, false if it is none.
+ */
+ public boolean isNotNone(int memberIndex) {
+ return !((List)t.get(memberIndex)).get(0).equals(NONE);
+ }
+ }
}
diff --git a/src/main/java/org/numenta/nupic/encoders/DeltaEncoder.java b/src/main/java/org/numenta/nupic/encoders/DeltaEncoder.java
index cadf1437..1e6a4f69 100644
--- a/src/main/java/org/numenta/nupic/encoders/DeltaEncoder.java
+++ b/src/main/java/org/numenta/nupic/encoders/DeltaEncoder.java
@@ -26,7 +26,7 @@
import java.util.Arrays;
import java.util.List;
-import org.numenta.nupic.Connections;
+import org.numenta.nupic.model.Connections;
public class DeltaEncoder extends AdaptiveScalarEncoder {
diff --git a/src/main/java/org/numenta/nupic/encoders/Encoder.java b/src/main/java/org/numenta/nupic/encoders/Encoder.java
index d1a3e346..ace1b856 100644
--- a/src/main/java/org/numenta/nupic/encoders/Encoder.java
+++ b/src/main/java/org/numenta/nupic/encoders/Encoder.java
@@ -31,7 +31,7 @@
import java.util.Set;
import org.numenta.nupic.FieldMetaType;
-import org.numenta.nupic.Persistable;
+import org.numenta.nupic.model.Persistable;
import org.numenta.nupic.util.ArrayUtils;
import org.numenta.nupic.util.MinMax;
import org.numenta.nupic.util.SparseObjectMatrix;
diff --git a/src/main/java/org/numenta/nupic/encoders/LogEncoder.java b/src/main/java/org/numenta/nupic/encoders/LogEncoder.java
index fe9efa75..55290d1d 100644
--- a/src/main/java/org/numenta/nupic/encoders/LogEncoder.java
+++ b/src/main/java/org/numenta/nupic/encoders/LogEncoder.java
@@ -32,8 +32,8 @@
import java.util.Map;
import java.util.Set;
-import org.numenta.nupic.Connections;
import org.numenta.nupic.FieldMetaType;
+import org.numenta.nupic.model.Connections;
import org.numenta.nupic.util.MinMax;
import org.numenta.nupic.util.Tuple;
import org.slf4j.Logger;
diff --git a/src/main/java/org/numenta/nupic/encoders/ScalarEncoder.java b/src/main/java/org/numenta/nupic/encoders/ScalarEncoder.java
index e8ebe39f..b62d9ed7 100644
--- a/src/main/java/org/numenta/nupic/encoders/ScalarEncoder.java
+++ b/src/main/java/org/numenta/nupic/encoders/ScalarEncoder.java
@@ -33,8 +33,8 @@
import java.util.Map;
import java.util.Set;
-import org.numenta.nupic.Connections;
import org.numenta.nupic.FieldMetaType;
+import org.numenta.nupic.model.Connections;
import org.numenta.nupic.util.ArrayUtils;
import org.numenta.nupic.util.Condition;
import org.numenta.nupic.util.MinMax;
diff --git a/src/main/java/org/numenta/nupic/model/Cell.java b/src/main/java/org/numenta/nupic/model/Cell.java
index d1c1180a..1e287633 100644
--- a/src/main/java/org/numenta/nupic/model/Cell.java
+++ b/src/main/java/org/numenta/nupic/model/Cell.java
@@ -26,8 +26,6 @@
import java.util.List;
import java.util.Set;
-import org.numenta.nupic.Connections;
-
/**
* Software implementation of a neuron in the neocortical region.
*
@@ -46,9 +44,7 @@ public class Cell implements Comparable, Serializable {
private final Column column;
/** Cash this because Cells are immutable */
private final int hashcode;
- /** tracks number of destroyed segments */
- private int numDestroyedSegments;
-
+
/**
* Constructs a new {@code Cell} object
@@ -129,28 +125,6 @@ public List getSegments(Connections c, boolean doLazyCreate) {
return c.getSegments(this, doLazyCreate);
}
- /**
- * Increments the number of destroyed segments for this {@code Cell}
- */
- public void incDestroyedSegments() {
- numDestroyedSegments++;
- }
-
- /**
- * Decrements the number of destroyed segments for this {@code Cell}
- */
- public void decDestroyedSegments() {
- numDestroyedSegments--;
- }
-
- /**
- * Returns the number of destroyed segments for this {@code Cell}
- * @return
- */
- public int getNumDestroyedSegments() {
- return numDestroyedSegments;
- }
-
/**
* {@inheritDoc}
*/
diff --git a/src/main/java/org/numenta/nupic/model/Column.java b/src/main/java/org/numenta/nupic/model/Column.java
index a5c7ea66..cc1a6476 100644
--- a/src/main/java/org/numenta/nupic/model/Column.java
+++ b/src/main/java/org/numenta/nupic/model/Column.java
@@ -29,7 +29,6 @@
import java.util.List;
import java.util.Random;
-import org.numenta.nupic.Connections;
import org.numenta.nupic.algorithms.SpatialPooler;
import org.numenta.nupic.algorithms.TemporalMemory;
diff --git a/src/main/java/org/numenta/nupic/ComputeCycle.java b/src/main/java/org/numenta/nupic/model/ComputeCycle.java
similarity index 61%
rename from src/main/java/org/numenta/nupic/ComputeCycle.java
rename to src/main/java/org/numenta/nupic/model/ComputeCycle.java
index 440c9958..9f0d1e34 100644
--- a/src/main/java/org/numenta/nupic/ComputeCycle.java
+++ b/src/main/java/org/numenta/nupic/model/ComputeCycle.java
@@ -20,22 +20,14 @@
* ---------------------------------------------------------------------
*/
-package org.numenta.nupic;
+package org.numenta.nupic.model;
-import java.io.Serializable;
import java.util.ArrayList;
-import java.util.Collections;
import java.util.LinkedHashSet;
import java.util.List;
import java.util.Set;
-import org.numenta.nupic.Connections.SegmentOverlap;
import org.numenta.nupic.algorithms.TemporalMemory;
-import org.numenta.nupic.model.Cell;
-import org.numenta.nupic.model.Column;
-import org.numenta.nupic.util.GroupBy2;
-import org.numenta.nupic.util.GroupBy2.Slot;
-import org.numenta.nupic.util.Tuple;
/**
* Contains a snapshot of the state attained during one computational
@@ -51,14 +43,9 @@ public class ComputeCycle implements Persistable {
public Set activeCells = new LinkedHashSet<>();
public Set winnerCells = new LinkedHashSet<>();
- public List activeSegOverlaps = new ArrayList<>();
- public List matchingSegOverlaps = new ArrayList<>();
-
-
- /** Force access through accessor because this list is created lazily */
- private Set predictiveCells = new LinkedHashSet<>();
- /** Used for one cycle's typed output translation from the tuple created */
- public ColumnData columnData = new ColumnData();
+ public List activeSegments = new ArrayList<>();
+ public List matchingSegments = new ArrayList<>();
+ public Set predictiveCells = new LinkedHashSet<>();
/**
@@ -77,8 +64,8 @@ public ComputeCycle(Connections c) {
this.activeCells = new LinkedHashSet<>(c.activeCells);
this.winnerCells = new LinkedHashSet<>(c.winnerCells);
this.predictiveCells = new LinkedHashSet<>(c.predictiveCells);
- this.activeSegOverlaps = new ArrayList<>(c.activeSegOverlaps);
- this.matchingSegOverlaps = new ArrayList<>(c.matchingSegOverlaps);
+ this.activeSegments = new ArrayList<>(c.activeSegments);
+ this.matchingSegments = new ArrayList<>(c.matchingSegments);
}
/**
@@ -104,47 +91,19 @@ public Set winnerCells() {
* @return
*/
public Set predictiveCells() {
- if(predictiveCells.isEmpty()) {
- for(SegmentOverlap activeSegment : activeSegOverlaps) {
- predictiveCells.add(activeSegment.segment.getParentCell());
+ if(predictiveCells.isEmpty()) {
+ Cell previousCell = null;
+ Cell currCell = null;
+
+ for(DistalDendrite activeSegment : activeSegments) {
+ if((currCell = activeSegment.getParentCell()) != previousCell) {
+ predictiveCells.add(previousCell = currCell);
+ }
}
}
-
return predictiveCells;
}
- /**
- * Used in the {@link TemporalMemory#compute(Connections, int[], boolean)} method
- * to make pulling values out of the {@link GroupBy2} more readable and named.
- */
- @SuppressWarnings("unchecked")
- public static class ColumnData implements Serializable {
- /** Default Serial */
- private static final long serialVersionUID = 1L;
- Tuple t;
-
- public ColumnData() {}
-
- public ColumnData(Tuple t) {
- this.t = t;
- }
-
- public Column column() { return (Column)t.get(0); }
- public List activeColumns() { return (List)t.get(1); }
- public List activeSegments() {
- return ((List)t.get(2)).get(0).equals(Slot.empty()) ?
- Collections.emptyList() :
- (List)t.get(2);
- }
- public List matchingSegments() {
- return ((List)t.get(3)).get(0).equals(Slot.empty()) ?
- Collections.emptyList() :
- (List)t.get(3);
- }
-
- public ColumnData set(Tuple t) { this.t = t; return this; }
- }
-
/* (non-Javadoc)
* @see java.lang.Object#hashCode()
*/
@@ -155,8 +114,8 @@ public int hashCode() {
result = prime * result + ((activeCells == null) ? 0 : activeCells.hashCode());
result = prime * result + ((predictiveCells == null) ? 0 : predictiveCells.hashCode());
result = prime * result + ((winnerCells == null) ? 0 : winnerCells.hashCode());
- result = prime * result + ((activeSegOverlaps == null) ? 0 : activeSegOverlaps.hashCode());
- result = prime * result + ((matchingSegOverlaps == null) ? 0 : matchingSegOverlaps.hashCode());
+ result = prime * result + ((activeSegments == null) ? 0 : activeSegments.hashCode());
+ result = prime * result + ((matchingSegments == null) ? 0 : matchingSegments.hashCode());
return result;
}
@@ -187,15 +146,15 @@ public boolean equals(Object obj) {
return false;
} else if(!winnerCells.equals(other.winnerCells))
return false;
- if(activeSegOverlaps == null) {
- if(other.activeSegOverlaps != null)
+ if(activeSegments == null) {
+ if(other.activeSegments != null)
return false;
- } else if(!activeSegOverlaps.equals(other.activeSegOverlaps))
+ } else if(!activeSegments.equals(other.activeSegments))
return false;
- if(matchingSegOverlaps == null) {
- if(other.matchingSegOverlaps != null)
+ if(matchingSegments == null) {
+ if(other.matchingSegments != null)
return false;
- } else if(!matchingSegOverlaps.equals(other.matchingSegOverlaps))
+ } else if(!matchingSegments.equals(other.matchingSegments))
return false;
return true;
}
diff --git a/src/main/java/org/numenta/nupic/Connections.java b/src/main/java/org/numenta/nupic/model/Connections.java
similarity index 80%
rename from src/main/java/org/numenta/nupic/Connections.java
rename to src/main/java/org/numenta/nupic/model/Connections.java
index 02c8e2bd..67f8b577 100644
--- a/src/main/java/org/numenta/nupic/Connections.java
+++ b/src/main/java/org/numenta/nupic/model/Connections.java
@@ -1,26 +1,4 @@
-/* ---------------------------------------------------------------------
- * Numenta Platform for Intelligent Computing (NuPIC)
- * Copyright (C) 2014, Numenta, Inc. Unless you have an agreement
- * with Numenta, Inc., for a separate license for this software code, the
- * following terms and conditions apply:
- *
- * This program is free software: you can redistribute it and/or modify
- * it under the terms of the GNU Affero Public License version 3 as
- * published by the Free Software Foundation.
- *
- * This program is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
- * See the GNU Affero Public License for more details.
- *
- * You should have received a copy of the GNU Affero Public License
- * along with this program. If not, see http://www.gnu.org/licenses.
- *
- * http://numenta.org/licenses/
- * ---------------------------------------------------------------------
- */
-
-package org.numenta.nupic;
+package org.numenta.nupic.model;
import java.io.PrintWriter;
import java.io.Serializable;
@@ -39,15 +17,9 @@
import java.util.Set;
import java.util.stream.Collectors;
+import org.numenta.nupic.Parameters;
import org.numenta.nupic.algorithms.SpatialPooler;
import org.numenta.nupic.algorithms.TemporalMemory;
-import org.numenta.nupic.model.Cell;
-import org.numenta.nupic.model.Column;
-import org.numenta.nupic.model.DistalDendrite;
-import org.numenta.nupic.model.Pool;
-import org.numenta.nupic.model.ProximalDendrite;
-import org.numenta.nupic.model.Segment;
-import org.numenta.nupic.model.Synapse;
import org.numenta.nupic.network.Persistence;
import org.numenta.nupic.network.PersistenceAPI;
import org.numenta.nupic.serialize.SerialConfig;
@@ -57,9 +29,10 @@
import org.numenta.nupic.util.SparseMatrix;
import org.numenta.nupic.util.SparseObjectMatrix;
import org.numenta.nupic.util.Topology;
-import org.numenta.nupic.util.Tuple;
import org.numenta.nupic.util.UniversalRandom;
+import gnu.trove.list.array.TIntArrayList;
+
/**
* Contains the definition of the interconnected structural state of the {@link SpatialPooler} and
* {@link TemporalMemory} as well as the state of all support structures
@@ -109,7 +82,7 @@ public class Connections implements Persistable {
private double version = 1.0;
public int spIterationNum = 0;
public int spIterationLearnNum = 0;
- public int tmIteration = 0;
+ public long tmIteration = 0;
public double[] boostedOverlaps;
public int[] overlaps;
@@ -166,10 +139,10 @@ public class Connections implements Persistable {
protected Set activeCells = new LinkedHashSet();
protected Set winnerCells = new LinkedHashSet();
- protected Set predictiveCells = new LinkedHashSet();
- protected List activeSegOverlaps = new ArrayList<>();
- protected List matchingSegOverlaps = new ArrayList<>();
-
+ protected Set| predictiveCells = new LinkedHashSet<>();
+ protected List activeSegments = new ArrayList<>();
+ protected List matchingSegments = new ArrayList<>();
+
/** Total number of columns */
protected int[] columnDimensions = new int[] { 2048 };
/** Total number of cells per column */
@@ -230,27 +203,40 @@ public class Connections implements Persistable {
public Map> distalSynapses;
protected Map> proximalSynapses;
- /** Helps index each new Segment */
- protected int segmentCounter = -1;
/** Helps index each new proximal Synapse */
protected int proximalSynapseCounter = -1;
- /** Helps index each new distal Synapse */
- protected int distalSynapseCounter = -1;
+ /** Global tracker of the next available segment index */
+ protected int nextFlatIdx;
+ /** Global counter incremented for each DD segment creation*/
+ protected int nextSegmentOrdinal;
+ /** Global counter incremented for each DD synapse creation*/
+ protected int nextSynapseOrdinal;
+ /** Total number of synapses */
+ protected long numSynapses;
+ /** Used for recycling {@link DistalDendrite} indexes */
+ protected TIntArrayList freeFlatIdxs = new TIntArrayList();
+ /** Indexed segments by their global index (can contain nulls) */
+ protected List segmentForFlatIdx = new ArrayList<>();
+ /** Stores each cycle's most recent activity */
+ public Activity lastActivity;
/** The default random number seed */
protected int seed = 42;
/** The random number generator */
public Random random = new UniversalRandom(seed);
- private Comparator lambda = (Comparator & Serializable) (so1, so2) ->
- so1.segment.getParentCell().getIndex() * maxSegmentsPerCell -
- so2.segment.getParentCell().getIndex() * maxSegmentsPerCell;
+ /** Sorting Lambda used for sorting active and matching segments */
+ public Comparator segmentPositionSortKey = (Comparator & Serializable)(s1,s2) -> {
+ double c1 = s1.getParentCell().getIndex() + ((double)(s1.getOrdinal() / (double)nextSegmentOrdinal));
+ double c2 = s2.getParentCell().getIndex() + ((double)(s2.getOrdinal() / (double)nextSegmentOrdinal));
+ return c1 == c2 ? 0 : c1 > c2 ? 1 : -1;
+ };
////////////////////////////////////////
// Connections Constructor //
////////////////////////////////////////
/**
- * Constructs a new {@code Connections} object. This object
+ * Constructs a new {@code OldConnections} object. This object
* is usually configured via the {@link Parameters#apply(Object)}
* method.
*/
@@ -531,7 +517,6 @@ public int getNumColumns() {
*/
public void setNumColumns(int n) {
this.numColumns = n;
- this.paOverlaps = new double[n];
}
/**
@@ -1142,7 +1127,7 @@ public void setActiveDutyCycles(double[] activeDutyCycles) {
* Applies the dense array values which aren't -1 to the array containing
* the active duty cycles of the column corresponding to the index specified.
* The length of the specified array must be as long as the configured number
- * of columns of this {@code Connections}' column configuration.
+ * of columns of this {@code OldConnections}' column configuration.
*
* @param denseActiveDutyCycles a dense array containing values to set.
*/
@@ -1154,188 +1139,137 @@ public void updateActiveDutyCycles(double[] denseActiveDutyCycles) {
}
}
+ /**
+ * Returns the minOverlapDutyCycles.
+ * @return the minOverlapDutyCycles.
+ */
public double[] getMinOverlapDutyCycles() {
return minOverlapDutyCycles;
}
+ /**
+ * Sets the minOverlapDutyCycles
+ * @param minOverlapDutyCycles the minOverlapDutyCycles
+ */
public void setMinOverlapDutyCycles(double[] minOverlapDutyCycles) {
this.minOverlapDutyCycles = minOverlapDutyCycles;
}
+ /**
+ * Returns the minActiveDutyCycles
+ * @return the minActiveDutyCycles
+ */
public double[] getMinActiveDutyCycles() {
return minActiveDutyCycles;
}
+ /**
+ * Sets the minActiveDutyCycles
+ * @param minActiveDutyCycles the minActiveDutyCycles
+ */
public void setMinActiveDutyCycles(double[] minActiveDutyCycles) {
this.minActiveDutyCycles = minActiveDutyCycles;
}
+ /**
+ * Returns the array of boost factors
+ * @return the array of boost factors
+ */
public double[] getBoostFactors() {
return boostFactors;
}
+ /**
+ * Sets the array of boost factors
+ * @param boostFactors the array of boost factors
+ */
public void setBoostFactors(double[] boostFactors) {
this.boostFactors = boostFactors;
}
-
- ////////////////////////////////////////
- // TemporalMemory Methods //
- ////////////////////////////////////////
+
+ ////////////////////////////////////////
+ // TemporalMemory Methods //
+ ////////////////////////////////////////
/**
* Return type from {@link Connections#computeActivity(Set, double, int, double, int, boolean)}
*/
public static class Activity implements Serializable {
- /** default serial */
+ /** default serial */
private static final long serialVersionUID = 1L;
- public List activeSegments;
- public List matchingSegments;
- public Activity(List actives, List matching) {
- this.activeSegments = actives;
- this.matchingSegments = matching;
- }
- public String toString() {
- return "\nactives = " + activeSegments + "\nmatching = " + matchingSegments;
- }
- }
-
- /**
- * Accounting class used during {@link Connections#computeActivity(Collection, double, int, double, int, boolean)}
- */
- public static class SegmentOverlap implements Serializable, Comparable {
- /** default serial */
- private static final long serialVersionUID = 1L;
- public DistalDendrite segment;
- public int overlap;
- public SegmentOverlap(DistalDendrite dd, int overlap) {
- this.segment = dd;
- this.overlap = overlap;
- }
- /**
- * {@inheritDoc}
- */
- @Override
- public int compareTo(SegmentOverlap other) {
- return segment.getParentCell().getColumn().compareTo(
- other.segment.getParentCell().getColumn());
- }
- @Override
- public int hashCode() {
- final int prime = 31;
- int result = 1;
- result = prime * result + overlap;
- result = prime * result + ((segment == null) ? 0 : segment.hashCode());
- return result;
- }
- @Override
- public boolean equals(Object obj) {
- if (this == obj)
- return true;
- if (obj == null)
- return false;
- if (getClass() != obj.getClass())
- return false;
- SegmentOverlap other = (SegmentOverlap) obj;
- if (overlap != other.overlap)
- return false;
- if (segment == null) {
- if (other.segment != null)
- return false;
- } else if (!segment.equals(other.segment))
- return false;
- return true;
+ public int[] numActiveConnected;
+ public int[] numActivePotential;
+
+ public Activity(int[] numConnected, int[] numPotential) {
+ this.numActiveConnected = numConnected;
+ this.numActivePotential = numPotential;
}
}
/**
- * Returns a {@link Tuple} containing the active and matching segments given
- * a set of active cells.
+ * Compute each segment's number of active synapses for a given input.
+ * In the returned lists, a segment's active synapse count is stored at index
+ * `segment.flatIdx`.
*
- * @param activeInput currently active cells
- * @param activePermanenceThreshold permanence threshold for a synapse
- * to be considered active
- * @param activeSynapseThreshold number of synapses needed for a
- * segment to be considered active
- * @param matchingPermananceThreshold permanence threshold for a
- * synapse to be considered matching
- * @param matchingSynapseThreshold number of synapses needed for a
- * segment to be considered matching
- * @param recordIteration boolean to determine if we should
- * update the lastUsedIteration on
- * active segments and the internal
- * iteration variable
- *
- *
- * Notes: activeSegments and matchingSegments are sorted by the cell they are on.
- *
- * @return an {@link Activity} containing: activeSegments, matchingSegments
+ * @param activePresynapticCells
+ * @param connectedPermanence
+ * @return
*/
- public Activity computeActivity(Collection activeInput, double activePermanenceThreshold,
- int activeSynapseThreshold, double matchingPermananceThreshold, int matchingSynapseThreshold,
- boolean recordIteration) {
-
- int nextSegmentIdx = getSegmentCount();
+ public Activity computeActivity(Collection activePresynapticCells, double connectedPermanence) {
+ int[] numActiveConnectedSynapsesForSegment = new int[nextFlatIdx];
+ int[] numActivePotentialSynapsesForSegment = new int[nextFlatIdx];
- // Object[][] = segments and their counts (i.e. { {segment, count}, {segment, count} } )
- Object[][] numActiveSynapsesForSegment = new Object[nextSegmentIdx][2];
- Arrays.stream(numActiveSynapsesForSegment).forEach(arr -> arr[1] = 0);
- Object[][] numMatchingSynapsesForSegment = new Object[nextSegmentIdx][2];
- Arrays.stream(numMatchingSynapsesForSegment).forEach(arr -> arr[1] = 0);
+ double threshold = connectedPermanence - EPSILON;
- for(Cell cell : activeInput) {
- for(Synapse synapse : cell.getReceptorSynapses(this)) {
- Segment segment = synapse.getSegment();
- double permanence = synapse.getPermanence();
-
- if(permanence - matchingPermananceThreshold > -EPSILON) {
- numMatchingSynapsesForSegment[segment.getIndex()][0] = segment;
- numMatchingSynapsesForSegment[segment.getIndex()][1] =
- ((int)numMatchingSynapsesForSegment[segment.getIndex()][1]) + 1;
-
- if(permanence - activePermanenceThreshold > -EPSILON) {
- numActiveSynapsesForSegment[segment.getIndex()][0] = segment;
- numActiveSynapsesForSegment[segment.getIndex()][1] =
- ((int)numActiveSynapsesForSegment[segment.getIndex()][1]) + 1;
- }
+ for(Cell cell : activePresynapticCells) {
+ for(Synapse synapse : getReceptorSynapses(cell)) {
+ int flatIdx = synapse.getSegment().getIndex();
+ ++numActivePotentialSynapsesForSegment[flatIdx];
+ if(synapse.getPermanence() > threshold) {
+ ++numActiveConnectedSynapsesForSegment[flatIdx];
}
}
}
- if(recordIteration) {
- tmIteration++;
- }
-
- List activeSegments = new ArrayList<>();
- List matchingSegments = new ArrayList<>();
- for(int i = 0;i < nextSegmentIdx;i++) {
- if(((int)numActiveSynapsesForSegment[i][1]) >= activeSynapseThreshold) {
- activeSegments.add(new SegmentOverlap(((DistalDendrite)numActiveSynapsesForSegment[i][0]),
- (int)numActiveSynapsesForSegment[i][1]));
-
- if(recordIteration) {
- ((DistalDendrite)numActiveSynapsesForSegment[i][0]).setLastUsedIteration(tmIteration);
- }
- }
- }
-
- for(int i = 0;i < nextSegmentIdx;i++) {
- if(((int)numMatchingSynapsesForSegment[i][1]) >= matchingSynapseThreshold) {
- matchingSegments.add(new SegmentOverlap(((DistalDendrite)numMatchingSynapsesForSegment[i][0]),
- (int)numMatchingSynapsesForSegment[i][1]));
- }
- }
-
-
- Collections.sort(activeSegments, lambda);//(as1, as2) -> as1.segment.getIndex() - as2.segment.getIndex());
- Collections.sort(matchingSegments,lambda);//, (ms1, ms2) -> ms1.segment.getIndex() - ms2.segment.getIndex());
- return new Activity(activeSegments, matchingSegments);
+ return lastActivity = new Activity(
+ numActiveConnectedSynapsesForSegment,
+ numActivePotentialSynapsesForSegment);
}
- /////////////////////////////////////////////////////////////////
- // Segment (Specifically, Distal Dendrite) Operations //
- /////////////////////////////////////////////////////////////////
+ /**
+ * Returns the last {@link Activity} computed during the most
+ * recently executed cycle.
+ *
+ * @return the last activity to be computed.
+ */
+ public Activity getLastActivity() {
+ return lastActivity;
+ }
+
+ /**
+ * Record the fact that a segment had some activity. This information is
+ * used during segment cleanup.
+ *
+ * @param segment the segment for which to record activity
+ */
+ public void recordSegmentActivity(DistalDendrite segment) {
+ segment.setLastUsedIteration(tmIteration);
+ }
+
+ /**
+ * Mark the passage of time. This information is used during segment
+ * cleanup.
+ */
+ public void startNewIteration() {
+ ++tmIteration;
+ }
+
+
+ /////////////////////////////////////////////////////////////////
+ // Segment (Specifically, Distal Dendrite) Operations //
+ /////////////////////////////////////////////////////////////////
/**
* Adds a new {@link DistalDendrite} segment on the specified {@link Cell},
@@ -1345,37 +1279,29 @@ public Activity computeActivity(Collection activeInput, double activePerma
* @return the newly created segment or a reused segment
*/
public DistalDendrite createSegment(Cell cell) {
- while(numSegments(cell) >= maxSegmentsPerCell) {
+ while(numSegments(cell) >= maxSegmentsPerCell) {
destroySegment(leastRecentlyUsedSegment(cell));
}
-
- DistalDendrite segment = null;
-
- if(cell.getNumDestroyedSegments() > 0) {
- boolean found = false;
- for(DistalDendrite dd : getSegments(cell, true)) {
- if(dd.destroyed()) {
- found = true;
- segment = dd;
- break;
- }
- }
-
- if(!found) {
- throw new IllegalStateException("Failed to find a destroyed segment.");
- }
-
- segment.setDestroyed(false);
- cell.decDestroyedSegments();
- incrementSegments();
- }else{
- segment = new DistalDendrite(cell, incrementSegments());
- getSegments(cell, true).add(segment);
- }
-
- segment.setLastUsedIteration(tmIteration);
-
- return segment;
+
+ int flatIdx;
+ int len;
+ if((len = freeFlatIdxs.size()) > 0) {
+ flatIdx = freeFlatIdxs.get(len - 1);
+ freeFlatIdxs.remove(len - 1, 1);
+ }else{
+ flatIdx = nextFlatIdx;
+ segmentForFlatIdx.add(null);
+ ++nextFlatIdx;
+ }
+
+ int ordinal = nextSegmentOrdinal;
+ ++nextSegmentOrdinal;
+
+ DistalDendrite segment = new DistalDendrite(cell, flatIdx, tmIteration, ordinal);
+ getSegments(cell, true).add(segment);
+ segmentForFlatIdx.set(flatIdx, segment);
+
+ return segment;
}
/**
@@ -1383,27 +1309,22 @@ public DistalDendrite createSegment(Cell cell) {
* @param segment the segment to destroy
*/
public void destroySegment(DistalDendrite segment) {
- if(!segment.destroyed()) {
- for(Synapse synapse : getSynapses(segment)) {
- if(!synapse.destroyed()) {
- Cell cell = synapse.getPresynapticCell();
- Set presynapticSynapses = getReceptorSynapses(cell);
- presynapticSynapses.remove(synapse);
-
- if(presynapticSynapses.isEmpty()) {
- receptorSynapses.remove(cell);
- }
-
- distalSynapseCounter--;
- }
- }
-
- getSynapses(segment).clear();
- segment.setNumDestroyedSynapses(0);
- segment.setDestroyed(true);
- segment.getParentCell().incDestroyedSegments();
- segmentCounter--;
- }
+ // Remove the synapses from all data structures outside this Segment.
+ List synapses = getSynapses(segment);
+ int len = synapses.size();
+ getSynapses(segment).stream().forEach(s -> removeSynapseFromPresynapticMap(s));
+ numSynapses -= len;
+
+ // Remove the segment from the cell's list.
+ getSegments(segment.getParentCell()).remove(segment);
+
+ // Remove the segment from the map
+ distalSynapses.remove(segment);
+
+ // Free the flatIdx and remove the final reference so the Segment can be
+ // garbage-collected.
+ freeFlatIdxs.add(segment.getIndex());
+ segmentForFlatIdx.set(segment.getIndex(), null);
}
/**
@@ -1416,17 +1337,17 @@ public void destroySegment(DistalDendrite segment) {
*/
private DistalDendrite leastRecentlyUsedSegment(Cell cell) {
List segments = getSegments(cell, false);
- DistalDendrite min = null;
- int minIteration = Integer.MAX_VALUE;
+ DistalDendrite minSegment = null;
+ long minIteration = Long.MAX_VALUE;
for(DistalDendrite dd : segments) {
- if(!dd.destroyed() && dd.lastUsedIteration() < minIteration) {
- min = dd;
+ if(dd.lastUsedIteration() < minIteration) {
+ minSegment = dd;
minIteration = dd.lastUsedIteration();
}
}
- return min;
+ return minSegment;
}
/**
@@ -1447,10 +1368,10 @@ public int numSegments() {
*/
public int numSegments(Cell optionalCellArg) {
if(optionalCellArg != null) {
- return getSegments(optionalCellArg).size() - optionalCellArg.getNumDestroyedSegments();
+ return getSegments(optionalCellArg).size();
}
- return segmentCounter + 1;
+ return nextFlatIdx - freeFlatIdxs.size();
}
/**
@@ -1490,61 +1411,62 @@ public List getSegments(Cell cell, boolean doLazyCreate) {
}
/**
- * Returns the filtered list of {@link DistalDendrites} that are not marked
- * as destroyed, for the specified {@link Cell}
- *
- * @param cell the Cell for which non-destroyed segments are returned
- * @return
+ * Get the segment with the specified flatIdx.
+ * @param index The segment's flattened list index.
+ * @return the {@link DistalDendrite} who's index matches.
*/
- public List unDestroyedSegmentsForCell(Cell cell) {
- return segments == null || segments.get(cell) == null ?
- Collections.emptyList() :
- segments.get(cell)
- .stream()
- .filter(v -> !v.destroyed())
- .collect(Collectors.toList());
+ public DistalDendrite segmentForFlatIdx(int index) {
+ return segmentForFlatIdx.get(index);
}
/**
- * Returns the segment counter
- * @return
+ * Returns the index of the {@link Column} owning the cell which owns
+ * the specified segment.
+ * @param segment the {@link DistalDendrite} of the cell whose column index is desired.
+ * @return the owning column's index
*/
- public int getSegmentCount() {
- return segmentCounter + 1;
+ public int columnIndexForSegment(DistalDendrite segment) {
+ return segment.getParentCell().getIndex() / cellsPerColumn;
}
-
+
/**
- * Increments and returns the incremented count.
+ * FOR TEST USE ONLY
* @return
*/
- public int incrementSegments() {
- return ++segmentCounter;
+ public Map> getSegmentMapping() {
+ return new LinkedHashMap<>(segments);
}
-
+
+ /**
+ * Set by the {@link TemporalMemory} following a compute cycle.
+ * @param l
+ */
+ public void setActiveSegments(List l) {
+ this.activeSegments = l;
+ }
+
/**
- * Decrements and returns the decremented count.
+ * Retrieved by the {@link TemporalMemorty} prior to a compute cycle.
* @return
*/
- public int decrementSegments() {
- return --segmentCounter;
+ public List getActiveSegments() {
+ return activeSegments;
}
-
+
/**
- * Returns the index of the {@link Column} owning the cell which owns
- * the specified segment.
- * @param segment the {@link DistalDendrite} of the cell whose column index is desired.
- * @return the owning column's index
+ * Set by the {@link TemporalMemory} following a compute cycle.
+ * @param l
*/
- public int columnIndexForSegment(DistalDendrite segment) {
- return segment.getParentCell().getIndex() / cellsPerColumn;
+ public void setMatchingSegments(List l) {
+ this.matchingSegments = l;
}
/**
- * FOR TEST USE ONLY
+ * Retrieved by the {@link TemporalMemorty} prior to a compute cycle.
* @return
*/
- public Map> getSegmentMapping() {
- return new LinkedHashMap<>(segments);
+ public List getMatchingSegments() {
+ return matchingSegments;
}
@@ -1567,32 +1489,15 @@ public Synapse createSynapse(DistalDendrite segment, Cell presynapticCell, doubl
}
Synapse synapse = null;
- boolean found = false;
- if(segment.getNumDestroyedSynapses() > 0) {
- for(Synapse s : getSynapses(segment)) {
- if(s.destroyed()) {
- synapse = s;
- found = true;
- break;
- }
- }
-
- if(!found) {
- throw new IllegalStateException("Failed to find a destroyed synapse");
- }
-
- synapse.setDestroyed(false);
- segment.decDestroyedSynapses();
- incrementDistalSynapses();
- synapse.setPresynapticCell(presynapticCell);
- }else{
- getSynapses(segment).add(
- synapse = new Synapse(
- this, presynapticCell, segment, null, incrementDistalSynapses(), presynapticCell.getIndex()));
- }
-
+ getSynapses(segment).add(
+ synapse = new Synapse(
+ presynapticCell, segment, nextSynapseOrdinal, permanence));
+
getReceptorSynapses(presynapticCell, true).add(synapse);
- synapse.setPermanence(this, permanence);
+
+ ++nextSynapseOrdinal;
+
+ ++numSynapses;
return synapse;
}
@@ -1602,18 +1507,27 @@ public Synapse createSynapse(DistalDendrite segment, Cell presynapticCell, doubl
* @param synapse the Synapse to destroy
*/
public void destroySynapse(Synapse synapse) {
- if(!synapse.destroyed()) {
- Set presynapticSynapses;
- Cell cell = synapse.getPresynapticCell();
- (presynapticSynapses = getReceptorSynapses(cell, false)).remove(synapse);
-
- if(presynapticSynapses.isEmpty()) {
- receptorSynapses.remove(cell);
- }
-
- synapse.setDestroyed(true);
- ((DistalDendrite)synapse.getSegment()).incDestroyedSynapses();
- decrementDistalSynapses();
+ --numSynapses;
+
+ removeSynapseFromPresynapticMap(synapse);
+
+ getSynapses((DistalDendrite)synapse.getSegment()).remove(synapse);
+ }
+
+ /**
+ * Removes the specified {@link Synapse} from its
+ * pre-synaptic {@link Cell}'s map of synapses it
+ * activates.
+ *
+ * @param synapse the synapse to remove
+ */
+ public void removeSynapseFromPresynapticMap(Synapse synapse) {
+ Set presynapticSynapses;
+ Cell cell = synapse.getPresynapticCell();
+ (presynapticSynapses = getReceptorSynapses(cell, false)).remove(synapse);
+
+ if(presynapticSynapses.isEmpty()) {
+ receptorSynapses.remove(cell);
}
}
@@ -1625,7 +1539,7 @@ public void destroySynapse(Synapse synapse) {
* @return Synapse object on the segment with the minimal permanence
*/
private Synapse minPermanenceSynapse(DistalDendrite dd) {
- List synapses = unDestroyedSynapsesForSegment(dd);
+ List synapses = getSynapses(dd).stream().sorted().collect(Collectors.toList());
Synapse min = null;
double minPermanence = Double.MAX_VALUE;
@@ -1644,8 +1558,8 @@ private Synapse minPermanenceSynapse(DistalDendrite dd) {
*
* @return either the total number of synapses
*/
- public int numSynapses() {
- return distalSynapseCounter + 1;
+ public long numSynapses() {
+ return numSynapses(null);
}
/**
@@ -1655,12 +1569,12 @@ public int numSynapses() {
* @param optionalSegmentArg an optional Segment to specify the context of the synapse count.
* @return either the total number of synapses or the number on a specified segment.
*/
- public int numSynapses(DistalDendrite optionalSegmentArg) {
+ public long numSynapses(DistalDendrite optionalSegmentArg) {
if(optionalSegmentArg != null) {
- return getSynapses(optionalSegmentArg).size() - optionalSegmentArg.getNumDestroyedSynapses();
+ return getSynapses(optionalSegmentArg).size();
}
- return distalSynapseCounter + 1;
+ return numSynapses;
}
/**
@@ -1749,60 +1663,6 @@ public List getSynapses(ProximalDendrite segment) {
return retVal;
}
- /**
- * Returns the filtered list of {@link Synapses} that are not marked
- * as destroyed, for the specified {@link DistalDendrite} segment.
- *
- * @param cell the Cell for which non-destroyed segments are returned
- * @return the filtered list of {@link Synapses}
- */
- public List unDestroyedSynapsesForSegment(DistalDendrite dd) {
- return distalSynapses == null || distalSynapses.get(dd) == null ?
- Collections.emptyList() :
- distalSynapses.get(dd)
- .stream()
- .filter(v -> !v.destroyed())
- .collect(Collectors.toList());
- }
-
- /**
- * Returns the count of {@link Synapse}s on
- * {@link DistalDendrite}s
- * @return
- */
- public int getDistalSynapseCount() {
- return distalSynapseCounter + 1;
- }
-
- /**
- * Sets the count of {@link Synapse}s on
- * {@link DistalDendrites}
- *
- * @param i
- */
- public void setDistalSynapseCount(int i) {
- this.distalSynapseCounter = i;
- }
-
- /**
- * Increments and returns the incremented
- * distal {@link Synapse} count.
- *
- * @return
- */
- public int incrementDistalSynapses() {
- return ++distalSynapseCounter;
- }
-
- /**
- * Decrements and returns the decremented
- * distal {link Synapse} count
- * @return
- */
- public int decrementDistalSynapses() {
- return --distalSynapseCounter;
- }
-
/**
* FOR TEST USE ONLY
* @return
@@ -1818,13 +1678,6 @@ public void clear() {
activeCells.clear();
winnerCells.clear();
predictiveCells.clear();
- activeSegOverlaps.clear();
- matchingSegOverlaps.clear();
-// matchingCells.clear();
-// matchingSegments.clear();
-// successfullyPredictedColumns.clear();
-// activeSegments.clear();
-// learningSegments.clear();
}
/**
@@ -1867,10 +1720,14 @@ public void setWinnerCells(Set cells) {
*/
public Set getPredictiveCells() {
if(predictiveCells.isEmpty()) {
- List temp = new ArrayList<>(activeSegOverlaps);
- Collections.sort(temp);
- for(SegmentOverlap activeSegment : temp) {
- predictiveCells.add(activeSegment.segment.getParentCell());
+ Cell previousCell = null;
+ Cell currCell = null;
+
+ List temp = new ArrayList<>(activeSegments);
+ for(DistalDendrite activeSegment : temp) {
+ if((currCell = activeSegment.getParentCell()) != previousCell) {
+ predictiveCells.add(previousCell = currCell);
+ }
}
}
return predictiveCells;
@@ -1883,38 +1740,6 @@ public void clearPredictiveCells() {
this.predictiveCells.clear();
}
- /**
- * Returns the Set of active {@link SegmentOverlap}s
- * @return
- */
- public List getActiveSegmentOverlaps() {
- return activeSegOverlaps;
- }
-
- /**
- * Sets the {@link Set} of active {@link SegmentOverlap}s
- * @param segments
- */
- public void setActiveSegmentOverlaps(List segments) {
- this.activeSegOverlaps = segments;
- }
-
- /**
- * Returns the Set of matching {@link SegmentOverlap}s
- * @return
- */
- public List getMatchingSegmentOverlaps() {
- return matchingSegOverlaps;
- }
-
- /**
- * Sets the Set of matching {@link SegmentOverlap}s
- * @param segments
- */
- public void setMatchingSegmentOverlaps(List segments) {
- this.matchingSegOverlaps = segments;
- }
-
/**
* Returns the column at the specified index.
* @param index
@@ -2269,29 +2094,6 @@ public List getColumnList(int[] indexes) {
return retVal;
}
-
- ///////////////////////////////////////////////////
- // Experimental Prediction Assisted Configs //
- ///////////////////////////////////////////////////
- protected double[] paOverlaps;
- /**
- * Sets paOverlaps (predictive assist vector) for {@link PASpatialPooler}
- *
- * @param overlaps
- */
- public void setPAOverlaps(double[] overlaps) {
- this.paOverlaps = overlaps;
- }
-
- /**
- * Returns paOverlaps (predictive assist vector) for {@link PASpatialPooler}
- *
- * @return
- */
- public double[] getPAOverlaps() {
- return this.paOverlaps;
- }
-
/**
* High verbose output useful for debugging
*/
@@ -2462,12 +2264,10 @@ public int hashCode() {
result = prime * result + ((inputMatrix == null) ? 0 : inputMatrix.hashCode());
result = prime * result + spIterationLearnNum;
result = prime * result + spIterationNum;
- result = prime * result + tmIteration;
+ result = prime * result + (new Long(tmIteration)).intValue();
result = prime * result + learningRadius;
temp = Double.doubleToLongBits(localAreaDensity);
result = prime * result + (int)(temp ^ (temp >>> 32));
- result = prime * result + ((activeSegOverlaps == null) ? 0 : activeSegOverlaps.hashCode());
- result = prime * result + ((matchingSegOverlaps == null) ? 0 : matchingSegOverlaps.hashCode());
temp = Double.doubleToLongBits(maxBoost);
result = prime * result + (int)(temp ^ (temp >>> 32));
result = prime * result + maxNewSynapseCount;
@@ -2483,8 +2283,9 @@ public int hashCode() {
result = prime * result + (int)(temp ^ (temp >>> 32));
result = prime * result + numColumns;
result = prime * result + numInputs;
+ temp = numSynapses;
+ result = prime * result + (int)(temp ^ (temp >>> 32));
result = prime * result + Arrays.hashCode(overlapDutyCycles);
- result = prime * result + Arrays.hashCode(paOverlaps);
temp = Double.doubleToLongBits(permanenceDecrement);
result = prime * result + (int)(temp ^ (temp >>> 32));
temp = Double.doubleToLongBits(permanenceIncrement);
@@ -2499,7 +2300,6 @@ public int hashCode() {
result = prime * result + ((random == null) ? 0 : random.hashCode());
result = prime * result + ((receptorSynapses == null) ? 0 : receptorSynapses.hashCode());
result = prime * result + seed;
- result = prime * result + segmentCounter;
result = prime * result + ((segments == null) ? 0 : segments.hashCode());
temp = Double.doubleToLongBits(stimulusThreshold);
result = prime * result + (int)(temp ^ (temp >>> 32));
@@ -2518,7 +2318,6 @@ public int hashCode() {
temp = Double.doubleToLongBits(synPermTrimThreshold);
result = prime * result + (int)(temp ^ (temp >>> 32));
result = prime * result + proximalSynapseCounter;
- result = prime * result + distalSynapseCounter;
result = prime * result + ((proximalSynapses == null) ? 0 : proximalSynapses.hashCode());
result = prime * result + ((distalSynapses == null) ? 0 : distalSynapses.hashCode());
result = prime * result + Arrays.hashCode(tieBreaker);
@@ -2550,16 +2349,6 @@ public boolean equals(Object obj) {
return false;
if(!Arrays.equals(activeDutyCycles, other.activeDutyCycles))
return false;
- if(activeSegOverlaps == null) {
- if(other.activeSegOverlaps != null)
- return false;
- } else if(!activeSegOverlaps.equals(other.activeSegOverlaps))
- return false;
- if(matchingSegOverlaps == null) {
- if(other.matchingSegOverlaps != null)
- return false;
- } else if(!matchingSegOverlaps.equals(other.matchingSegOverlaps))
- return false;
if(!Arrays.equals(boostFactors, other.boostFactors))
return false;
if(!Arrays.equals(cells, other.cells))
@@ -2627,9 +2416,9 @@ public boolean equals(Object obj) {
return false;
if(numInputs != other.numInputs)
return false;
- if(!Arrays.equals(overlapDutyCycles, other.overlapDutyCycles))
+ if(numSynapses != other.numSynapses)
return false;
- if(!Arrays.equals(paOverlaps, other.paOverlaps))
+ if(!Arrays.equals(overlapDutyCycles, other.overlapDutyCycles))
return false;
if(Double.doubleToLongBits(permanenceDecrement) != Double.doubleToLongBits(other.permanenceDecrement))
return false;
@@ -2658,8 +2447,6 @@ public boolean equals(Object obj) {
return false;
if(seed != other.seed)
return false;
- if(segmentCounter != other.segmentCounter)
- return false;
if(segments == null) {
if(other.segments != null)
return false;
@@ -2683,8 +2470,6 @@ public boolean equals(Object obj) {
return false;
if(proximalSynapseCounter != other.proximalSynapseCounter)
return false;
- if(distalSynapseCounter != other.distalSynapseCounter)
- return false;
if(proximalSynapses == null) {
if(other.proximalSynapses != null)
return false;
@@ -2708,5 +2493,4 @@ public boolean equals(Object obj) {
return false;
return true;
}
-
}
diff --git a/src/main/java/org/numenta/nupic/model/DistalDendrite.java b/src/main/java/org/numenta/nupic/model/DistalDendrite.java
index 84ca0392..9f504aad 100644
--- a/src/main/java/org/numenta/nupic/model/DistalDendrite.java
+++ b/src/main/java/org/numenta/nupic/model/DistalDendrite.java
@@ -26,9 +26,6 @@
import java.util.List;
import java.util.Set;
-import org.numenta.nupic.Connections;
-import org.numenta.nupic.Persistable;
-
/**
* Represents a proximal or distal dendritic segment. Segments are owned by
* {@link Cell}s and in turn own {@link Synapse}s which are obversely connected
@@ -44,24 +41,23 @@ public class DistalDendrite extends Segment implements Persistable {
private Cell cell;
- private int lastUsedIteration;
-
- private int numDestroyedSynapses;
+ private long lastUsedIteration;
- private boolean destroyed;
+ public int ordinal = -1;
/**
* Constructs a new {@code Segment} object with the specified owner
* {@link Cell} and the specified index.
*
* @param cell the owner
- * @param index this {@code Segment}'s index.
+ * @param flatIdx this {@code Segment}'s index.
*/
- public DistalDendrite(Cell cell, int index) {
- super(index);
+ public DistalDendrite(Cell cell, int flatIdx, long lastUsedIteration, int ordinal) {
+ super(flatIdx);
this.cell = cell;
- this.index = index;
+ this.ordinal = ordinal;
+ this.lastUsedIteration = lastUsedIteration;
}
/**
@@ -107,7 +103,7 @@ public Set getActiveSynapses(Connections c, Set| activeCells) {
* Sets the last iteration in which this segment was active.
* @param iteration
*/
- public void setLastUsedIteration(int iteration) {
+ public void setLastUsedIteration(long iteration) {
this.lastUsedIteration = iteration;
}
@@ -115,57 +111,27 @@ public void setLastUsedIteration(int iteration) {
* Returns the iteration in which this segment was last active.
* @return the iteration in which this segment was last active.
*/
- public int lastUsedIteration() {
+ public long lastUsedIteration() {
return lastUsedIteration;
}
/**
- * Returns the flag indicating whether this {@code DistalDendrite} has been destroyed.
- * @return the flag indicating whether this segment has been destroyed.
- */
- public boolean destroyed() {
- return destroyed;
- }
-
- /**
- * Sets the flag indicating whether this {@code DistalDendrite} has been destroyed.
- * @param b the flag indicating whether this segment has been destroyed.
- */
- public void setDestroyed(boolean b) {
- this.destroyed = b;
- }
-
- /**
- * Increments the number of destroyed {@link Synapse}s for this {@code DistalDendrite}
- */
- public void incDestroyedSynapses() {
- numDestroyedSynapses++;
- }
-
- /**
- * Decrements the number of destroyed {@link Synapse}s for this {@code DistalDendrite}
+ * Returns this {@code DistalDendrite} segment's ordinal
+ * @return this segment's ordinal
*/
- public void decDestroyedSynapses() {
- numDestroyedSynapses--;
- }
-
- /**
- * Returns the number of destroyed {@link Synapse}s for this {@code DistalDendrite}
- * @return
- */
- public int getNumDestroyedSynapses() {
- return numDestroyedSynapses;
- }
-
+ public int getOrdinal() {
+ return ordinal;
+ }
+
/**
- * Sets the number of destroyed {@link Synapse}s for this {@code DistalDendrite}
- * @param num the current number of destroyed synapses
+ * Sets the ordinal value (used for age determination) on this segment.
+ * @param ordinal the age or order of this segment
*/
- public void setNumDestroyedSynapses(int num) {
- this.numDestroyedSynapses = num;
- }
-
- /**
+ public void setOrdinal(int ordinal) {
+ this.ordinal = ordinal;
+ }
+
+ /**
* {@inheritDoc}
*/
@Override
diff --git a/src/main/java/org/numenta/nupic/Persistable.java b/src/main/java/org/numenta/nupic/model/Persistable.java
similarity index 97%
rename from src/main/java/org/numenta/nupic/Persistable.java
rename to src/main/java/org/numenta/nupic/model/Persistable.java
index 19017932..75f70faf 100644
--- a/src/main/java/org/numenta/nupic/Persistable.java
+++ b/src/main/java/org/numenta/nupic/model/Persistable.java
@@ -1,4 +1,4 @@
-package org.numenta.nupic;
+package org.numenta.nupic.model;
import java.io.Serializable;
diff --git a/src/main/java/org/numenta/nupic/model/Pool.java b/src/main/java/org/numenta/nupic/model/Pool.java
index db7d380a..80bb6674 100644
--- a/src/main/java/org/numenta/nupic/model/Pool.java
+++ b/src/main/java/org/numenta/nupic/model/Pool.java
@@ -24,8 +24,6 @@
import java.util.stream.IntStream;
-import org.numenta.nupic.Connections;
-import org.numenta.nupic.Persistable;
import org.numenta.nupic.util.ArrayUtils;
import gnu.trove.map.TIntObjectMap;
diff --git a/src/main/java/org/numenta/nupic/model/ProximalDendrite.java b/src/main/java/org/numenta/nupic/model/ProximalDendrite.java
index 41e7d780..e3a4389f 100644
--- a/src/main/java/org/numenta/nupic/model/ProximalDendrite.java
+++ b/src/main/java/org/numenta/nupic/model/ProximalDendrite.java
@@ -24,9 +24,6 @@
import java.util.List;
-import org.numenta.nupic.Connections;
-import org.numenta.nupic.Persistable;
-
public class ProximalDendrite extends Segment implements Persistable {
/** keep it simple */
private static final long serialVersionUID = 1L;
diff --git a/src/main/java/org/numenta/nupic/SDR.java b/src/main/java/org/numenta/nupic/model/SDR.java
similarity index 97%
rename from src/main/java/org/numenta/nupic/SDR.java
rename to src/main/java/org/numenta/nupic/model/SDR.java
index 3e72bbaf..3f49aea6 100644
--- a/src/main/java/org/numenta/nupic/SDR.java
+++ b/src/main/java/org/numenta/nupic/model/SDR.java
@@ -19,7 +19,7 @@
* http://numenta.org/licenses/
* ---------------------------------------------------------------------
*/
-package org.numenta.nupic;
+package org.numenta.nupic.model;
import java.util.ArrayList;
import java.util.Arrays;
@@ -28,9 +28,6 @@
import java.util.Set;
import java.util.stream.IntStream;
-import org.numenta.nupic.model.Cell;
-import org.numenta.nupic.model.Column;
-
/**
*
* For now, a utility class for convenience operations
diff --git a/src/main/java/org/numenta/nupic/model/Segment.java b/src/main/java/org/numenta/nupic/model/Segment.java
index 18c6ccb0..e6672fc5 100644
--- a/src/main/java/org/numenta/nupic/model/Segment.java
+++ b/src/main/java/org/numenta/nupic/model/Segment.java
@@ -25,8 +25,6 @@
import java.io.Serializable;
import java.util.List;
-import org.numenta.nupic.Connections;
-
/**
* Base class which handles the creation of {@link Synapse}s on behalf of
* inheriting class types.
@@ -56,25 +54,23 @@ public int getIndex() {
}
/**
+ *
* Creates and returns a newly created {@link Synapse} with the specified
* source cell, permanence, and index.
- *
- * IMPORTANT: For DistalDendrites, there is only one synapse per pool, so the
- * synapse's index doesn't really matter (in terms of tracking its
- * order within the pool. In that case, the index is a global counter
- * of all distal dendrite synapses.
- *
- * For ProximalDendrites, there are many synapses within a pool, and in
- * that case, the index specifies the synapse's sequence order within
- * the pool object, and may be referenced by that index.
- *
+ *
+ * IMPORTANT: This method is only called for Proximal Synapses. For ProximalDendrites,
+ * there are many synapses within a pool, and in that case, the index
+ * specifies the synapse's sequence order within the pool object, and may
+ * be referenced by that index.
+ *
* @param c the connections state of the temporal memory
* @param sourceCell the source cell which will activate the new {@code Synapse}
* @param pool the new {@link Synapse}'s pool for bound variables.
* @param index the new {@link Synapse}'s index.
* @param inputIndex the index of this {@link Synapse}'s input (source object); be it a Cell or InputVector bit.
*
- * @return
+ * @return the newly created {@code Synapse}
+ * @see Connections#createSynapse(DistalDendrite, Cell, double)
*/
public Synapse createSynapse(Connections c, List syns, Cell sourceCell, Pool pool, int index, int inputIndex) {
Synapse s = new Synapse(c, sourceCell, this, pool, index, inputIndex);
diff --git a/src/main/java/org/numenta/nupic/model/Synapse.java b/src/main/java/org/numenta/nupic/model/Synapse.java
index c034b329..99a5cfbf 100644
--- a/src/main/java/org/numenta/nupic/model/Synapse.java
+++ b/src/main/java/org/numenta/nupic/model/Synapse.java
@@ -22,9 +22,6 @@
package org.numenta.nupic.model;
-import org.numenta.nupic.Connections;
-import org.numenta.nupic.Persistable;
-
/**
* Represents a connection with varying strength which when above
* a configured threshold represents a valid connection.
@@ -62,6 +59,23 @@ public class Synapse implements Persistable, Comparable {
* Constructor used when setting parameters later.
*/
public Synapse() {}
+
+ /**
+ * Constructs a new {@code Synapse} for a {@link DistalDendrite}
+ * @param sourceCell the {@link Cell} which will activate this {@code Synapse};
+ * @param segment the owning dendritic segment
+ * @param pool this {@link Pool} of which this synapse is a member
+ * @param index this {@code Synapse}'s index
+ * @param permanence
+ */
+ public Synapse(Cell presynapticCell, Segment segment, int index, double permanence) {
+ this.sourceCell = presynapticCell;
+ this.segment = segment;
+ this.synapseIndex = index;
+ this.boxedIndex = new Integer(index);
+ this.inputIndex = presynapticCell.getIndex();
+ this.permanence = permanence;
+ }
/**
* Constructs a new {@code Synapse}
diff --git a/src/main/java/org/numenta/nupic/monitor/ComputeDecorator.java b/src/main/java/org/numenta/nupic/monitor/ComputeDecorator.java
index f3380fe6..113195bf 100644
--- a/src/main/java/org/numenta/nupic/monitor/ComputeDecorator.java
+++ b/src/main/java/org/numenta/nupic/monitor/ComputeDecorator.java
@@ -21,8 +21,8 @@
*/
package org.numenta.nupic.monitor;
-import org.numenta.nupic.ComputeCycle;
-import org.numenta.nupic.Connections;
+import org.numenta.nupic.model.ComputeCycle;
+import org.numenta.nupic.model.Connections;
/**
* Decorator interface for main algorithms
diff --git a/src/main/java/org/numenta/nupic/monitor/MonitoredTemporalMemory.java b/src/main/java/org/numenta/nupic/monitor/MonitoredTemporalMemory.java
index 79cdec38..a84bfb9a 100644
--- a/src/main/java/org/numenta/nupic/monitor/MonitoredTemporalMemory.java
+++ b/src/main/java/org/numenta/nupic/monitor/MonitoredTemporalMemory.java
@@ -24,8 +24,8 @@
import java.util.HashMap;
import java.util.Map;
-import org.numenta.nupic.ComputeCycle;
-import org.numenta.nupic.Connections;
+import org.numenta.nupic.model.ComputeCycle;
+import org.numenta.nupic.model.Connections;
import org.numenta.nupic.monitor.mixin.TemporalMemoryMonitorMixin;
import org.numenta.nupic.monitor.mixin.Trace;
diff --git a/src/main/java/org/numenta/nupic/monitor/mixin/MonitorMixinBase.java b/src/main/java/org/numenta/nupic/monitor/mixin/MonitorMixinBase.java
index c4e2ce15..2012127b 100644
--- a/src/main/java/org/numenta/nupic/monitor/mixin/MonitorMixinBase.java
+++ b/src/main/java/org/numenta/nupic/monitor/mixin/MonitorMixinBase.java
@@ -27,7 +27,7 @@
import java.util.List;
import java.util.Map;
-import org.numenta.nupic.Connections;
+import org.numenta.nupic.model.Connections;
import org.numenta.nupic.monitor.MonitoredTemporalMemory;
import com.bethecoder.table.AsciiTableInstance;
diff --git a/src/main/java/org/numenta/nupic/monitor/mixin/TemporalMemoryMonitorMixin.java b/src/main/java/org/numenta/nupic/monitor/mixin/TemporalMemoryMonitorMixin.java
index cfa8e4d9..6c5b2d06 100644
--- a/src/main/java/org/numenta/nupic/monitor/mixin/TemporalMemoryMonitorMixin.java
+++ b/src/main/java/org/numenta/nupic/monitor/mixin/TemporalMemoryMonitorMixin.java
@@ -31,12 +31,12 @@
import java.util.stream.Collectors;
import java.util.stream.Stream;
-import org.numenta.nupic.ComputeCycle;
-import org.numenta.nupic.Connections;
import org.numenta.nupic.algorithms.TemporalMemory;
import org.numenta.nupic.model.Cell;
import org.numenta.nupic.model.Column;
+import org.numenta.nupic.model.ComputeCycle;
import org.numenta.nupic.model.DistalDendrite;
+import org.numenta.nupic.model.Connections;
import org.numenta.nupic.model.Segment;
import org.numenta.nupic.model.Synapse;
import org.numenta.nupic.monitor.ComputeDecorator;
@@ -474,8 +474,8 @@ default ComputeCycle compute(Connections cnx, int[] activeColumns, String sequen
new LinkedHashSet(Connections.asCellIndexes(cnx.getActiveCells())));
((IndicesTrace)getTraceMap().get("activeColumns")).items.add(
Arrays.stream(activeColumns).boxed().collect(Collectors.toCollection(LinkedHashSet::new)));
- ((CountsTrace)getTraceMap().get("numSegments")).items.add(cnx.getSegmentCount());
- ((CountsTrace)getTraceMap().get("numSynapses")).items.add(cnx.getDistalSynapseCount());
+ ((CountsTrace)getTraceMap().get("numSegments")).items.add(cnx.numSegments());
+ ((CountsTrace)getTraceMap().get("numSynapses")).items.add((int)(cnx.numSynapses() ^ (cnx.numSynapses() >>> 32)));
((StringsTrace)getTraceMap().get("sequenceLabels")).items.add(sequenceLabel);
((BoolsTrace)getTraceMap().get("resets")).items.add(resetActive());
diff --git a/src/main/java/org/numenta/nupic/network/Inference.java b/src/main/java/org/numenta/nupic/network/Inference.java
index 2dafef76..d8e8a823 100644
--- a/src/main/java/org/numenta/nupic/network/Inference.java
+++ b/src/main/java/org/numenta/nupic/network/Inference.java
@@ -24,14 +24,14 @@
import java.util.Map;
import java.util.Set;
-import org.numenta.nupic.ComputeCycle;
-import org.numenta.nupic.Persistable;
import org.numenta.nupic.algorithms.CLAClassifier;
import org.numenta.nupic.algorithms.Classification;
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.model.ComputeCycle;
+import org.numenta.nupic.model.Persistable;
import org.numenta.nupic.util.NamedTuple;
import rx.functions.Func1;
diff --git a/src/main/java/org/numenta/nupic/network/Layer.java b/src/main/java/org/numenta/nupic/network/Layer.java
index aa9d6599..71458b78 100644
--- a/src/main/java/org/numenta/nupic/network/Layer.java
+++ b/src/main/java/org/numenta/nupic/network/Layer.java
@@ -33,13 +33,9 @@
import java.util.concurrent.ConcurrentLinkedQueue;
import org.joda.time.DateTime;
-import org.numenta.nupic.ComputeCycle;
-import org.numenta.nupic.Connections;
import org.numenta.nupic.FieldMetaType;
import org.numenta.nupic.Parameters;
import org.numenta.nupic.Parameters.KEY;
-import org.numenta.nupic.Persistable;
-import org.numenta.nupic.SDR;
import org.numenta.nupic.algorithms.Anomaly;
import org.numenta.nupic.algorithms.CLAClassifier;
import org.numenta.nupic.algorithms.Classification;
@@ -50,6 +46,10 @@
import org.numenta.nupic.encoders.EncoderTuple;
import org.numenta.nupic.encoders.MultiEncoder;
import org.numenta.nupic.model.Cell;
+import org.numenta.nupic.model.ComputeCycle;
+import org.numenta.nupic.model.Connections;
+import org.numenta.nupic.model.Persistable;
+import org.numenta.nupic.model.SDR;
import org.numenta.nupic.network.sensor.FileSensor;
import org.numenta.nupic.network.sensor.HTMSensor;
import org.numenta.nupic.network.sensor.ObservableSensor;
@@ -2335,6 +2335,7 @@ public ManualInput call(ManualInput t1) {
isArrayInput = 1;
t1.feedForwardSparseActives((int[])t1.getLayerInput());
}
+
return t1.anomalyScore(anomalyComputer.compute(t1.getFeedForwardSparseActives(),
SDR.cellsAsColumnIndices(t1.getPreviousPredictiveCells(), cellsPerColumn), 0, 0));
}
diff --git a/src/main/java/org/numenta/nupic/network/ManualInput.java b/src/main/java/org/numenta/nupic/network/ManualInput.java
index bd123de5..5fd2b9a3 100644
--- a/src/main/java/org/numenta/nupic/network/ManualInput.java
+++ b/src/main/java/org/numenta/nupic/network/ManualInput.java
@@ -27,13 +27,13 @@
import java.util.Map;
import java.util.Set;
-import org.numenta.nupic.ComputeCycle;
import org.numenta.nupic.algorithms.CLAClassifier;
import org.numenta.nupic.algorithms.Classification;
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.model.ComputeCycle;
import org.numenta.nupic.util.ArrayUtils;
import org.numenta.nupic.util.NamedTuple;
diff --git a/src/main/java/org/numenta/nupic/network/Network.java b/src/main/java/org/numenta/nupic/network/Network.java
index 899066f6..4714e9fc 100644
--- a/src/main/java/org/numenta/nupic/network/Network.java
+++ b/src/main/java/org/numenta/nupic/network/Network.java
@@ -27,14 +27,14 @@
import java.util.function.Function;
import org.joda.time.DateTime;
-import org.numenta.nupic.Connections;
import org.numenta.nupic.Parameters;
import org.numenta.nupic.Parameters.KEY;
-import org.numenta.nupic.Persistable;
import org.numenta.nupic.algorithms.CLAClassifier;
import org.numenta.nupic.algorithms.SpatialPooler;
import org.numenta.nupic.algorithms.TemporalMemory;
import org.numenta.nupic.encoders.MultiEncoder;
+import org.numenta.nupic.model.Connections;
+import org.numenta.nupic.model.Persistable;
import org.numenta.nupic.network.sensor.HTMSensor;
import org.numenta.nupic.network.sensor.ObservableSensor;
import org.numenta.nupic.network.sensor.Publisher;
diff --git a/src/main/java/org/numenta/nupic/network/Persistence.java b/src/main/java/org/numenta/nupic/network/Persistence.java
index a548c7b1..cd679b2b 100644
--- a/src/main/java/org/numenta/nupic/network/Persistence.java
+++ b/src/main/java/org/numenta/nupic/network/Persistence.java
@@ -38,7 +38,7 @@
import org.joda.time.DateTime;
import org.joda.time.format.DateTimeFormat;
import org.joda.time.format.DateTimeFormatter;
-import org.numenta.nupic.Persistable;
+import org.numenta.nupic.model.Persistable;
import org.numenta.nupic.serialize.SerialConfig;
import org.numenta.nupic.serialize.SerializerCore;
import org.slf4j.Logger;
diff --git a/src/main/java/org/numenta/nupic/network/PersistenceAPI.java b/src/main/java/org/numenta/nupic/network/PersistenceAPI.java
index 968e5ddd..8375e3a0 100644
--- a/src/main/java/org/numenta/nupic/network/PersistenceAPI.java
+++ b/src/main/java/org/numenta/nupic/network/PersistenceAPI.java
@@ -25,7 +25,7 @@
import java.io.Serializable;
import java.util.List;
-import org.numenta.nupic.Persistable;
+import org.numenta.nupic.model.Persistable;
import org.numenta.nupic.serialize.SerialConfig;
import org.numenta.nupic.serialize.SerializerCore;
diff --git a/src/main/java/org/numenta/nupic/network/PublisherSupplier.java b/src/main/java/org/numenta/nupic/network/PublisherSupplier.java
index 43afcc57..cf2ce03a 100644
--- a/src/main/java/org/numenta/nupic/network/PublisherSupplier.java
+++ b/src/main/java/org/numenta/nupic/network/PublisherSupplier.java
@@ -26,7 +26,7 @@
import java.util.function.Consumer;
import java.util.function.Supplier;
-import org.numenta.nupic.Persistable;
+import org.numenta.nupic.model.Persistable;
import org.numenta.nupic.network.sensor.Header;
import org.numenta.nupic.network.sensor.Publisher;
diff --git a/src/main/java/org/numenta/nupic/network/Region.java b/src/main/java/org/numenta/nupic/network/Region.java
index 61b87903..f01d2246 100644
--- a/src/main/java/org/numenta/nupic/network/Region.java
+++ b/src/main/java/org/numenta/nupic/network/Region.java
@@ -27,9 +27,9 @@
import java.util.Set;
import org.joda.time.DateTime;
-import org.numenta.nupic.Persistable;
import org.numenta.nupic.algorithms.TemporalMemory;
import org.numenta.nupic.encoders.Encoder;
+import org.numenta.nupic.model.Persistable;
import org.numenta.nupic.network.sensor.Sensor;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
diff --git a/src/main/java/org/numenta/nupic/network/sensor/Publisher.java b/src/main/java/org/numenta/nupic/network/sensor/Publisher.java
index 8e52c4f9..197f3e94 100644
--- a/src/main/java/org/numenta/nupic/network/sensor/Publisher.java
+++ b/src/main/java/org/numenta/nupic/network/sensor/Publisher.java
@@ -23,7 +23,7 @@
import java.util.function.Consumer;
-import org.numenta.nupic.Persistable;
+import org.numenta.nupic.model.Persistable;
import org.numenta.nupic.network.Layer;
import org.numenta.nupic.network.Network;
diff --git a/src/main/java/org/numenta/nupic/network/sensor/Sensor.java b/src/main/java/org/numenta/nupic/network/sensor/Sensor.java
index 3751d015..08ea8438 100644
--- a/src/main/java/org/numenta/nupic/network/sensor/Sensor.java
+++ b/src/main/java/org/numenta/nupic/network/sensor/Sensor.java
@@ -25,7 +25,7 @@
import java.net.URI;
import java.util.stream.Stream;
-import org.numenta.nupic.Persistable;
+import org.numenta.nupic.model.Persistable;
import org.numenta.nupic.network.Network;
import rx.Observable;
diff --git a/src/main/java/org/numenta/nupic/serialize/HTMObjectInput.java b/src/main/java/org/numenta/nupic/serialize/HTMObjectInput.java
index 65661d32..ac5a8bae 100644
--- a/src/main/java/org/numenta/nupic/serialize/HTMObjectInput.java
+++ b/src/main/java/org/numenta/nupic/serialize/HTMObjectInput.java
@@ -3,7 +3,7 @@
import java.io.IOException;
import java.io.InputStream;
-import org.numenta.nupic.Persistable;
+import org.numenta.nupic.model.Persistable;
import org.nustaq.serialization.FSTConfiguration;
import org.nustaq.serialization.FSTObjectInput;
diff --git a/src/main/java/org/numenta/nupic/serialize/HTMObjectOutput.java b/src/main/java/org/numenta/nupic/serialize/HTMObjectOutput.java
index 543d8af0..c2df45a5 100644
--- a/src/main/java/org/numenta/nupic/serialize/HTMObjectOutput.java
+++ b/src/main/java/org/numenta/nupic/serialize/HTMObjectOutput.java
@@ -3,7 +3,7 @@
import java.io.IOException;
import java.io.OutputStream;
-import org.numenta.nupic.Persistable;
+import org.numenta.nupic.model.Persistable;
import org.nustaq.serialization.FSTConfiguration;
import org.nustaq.serialization.FSTObjectOutput;
diff --git a/src/main/java/org/numenta/nupic/serialize/SerialConfig.java b/src/main/java/org/numenta/nupic/serialize/SerialConfig.java
index 035b642d..a34417c3 100644
--- a/src/main/java/org/numenta/nupic/serialize/SerialConfig.java
+++ b/src/main/java/org/numenta/nupic/serialize/SerialConfig.java
@@ -29,15 +29,15 @@
import java.util.Arrays;
import java.util.List;
-import org.numenta.nupic.ComputeCycle;
import org.numenta.nupic.FieldMetaType;
import org.numenta.nupic.Parameters;
-import org.numenta.nupic.Persistable;
import org.numenta.nupic.algorithms.BitHistory;
import org.numenta.nupic.algorithms.Classification;
import org.numenta.nupic.model.Cell;
import org.numenta.nupic.model.Column;
+import org.numenta.nupic.model.ComputeCycle;
import org.numenta.nupic.model.DistalDendrite;
+import org.numenta.nupic.model.Persistable;
import org.numenta.nupic.model.Pool;
import org.numenta.nupic.model.ProximalDendrite;
import org.numenta.nupic.model.Segment;
diff --git a/src/main/java/org/numenta/nupic/serialize/SerializerCore.java b/src/main/java/org/numenta/nupic/serialize/SerializerCore.java
index ec9f680c..2e1df48f 100644
--- a/src/main/java/org/numenta/nupic/serialize/SerializerCore.java
+++ b/src/main/java/org/numenta/nupic/serialize/SerializerCore.java
@@ -26,7 +26,7 @@
import java.io.ObjectInputStream;
import java.io.OutputStream;
-import org.numenta.nupic.Persistable;
+import org.numenta.nupic.model.Persistable;
import org.numenta.nupic.network.PersistenceAPI;
import org.nustaq.serialization.FSTConfiguration;
import org.slf4j.Logger;
diff --git a/src/main/java/org/numenta/nupic/util/AbstractSparseBinaryMatrix.java b/src/main/java/org/numenta/nupic/util/AbstractSparseBinaryMatrix.java
index ae1b083e..d35a0168 100644
--- a/src/main/java/org/numenta/nupic/util/AbstractSparseBinaryMatrix.java
+++ b/src/main/java/org/numenta/nupic/util/AbstractSparseBinaryMatrix.java
@@ -25,7 +25,7 @@
import java.lang.reflect.Array;
import java.util.Arrays;
-import org.numenta.nupic.Persistable;
+import org.numenta.nupic.model.Persistable;
import gnu.trove.TIntCollection;
import gnu.trove.iterator.TIntIterator;
diff --git a/src/main/java/org/numenta/nupic/util/BitSetMatrix.java b/src/main/java/org/numenta/nupic/util/BitSetMatrix.java
index c896aa7e..788c8f13 100644
--- a/src/main/java/org/numenta/nupic/util/BitSetMatrix.java
+++ b/src/main/java/org/numenta/nupic/util/BitSetMatrix.java
@@ -24,7 +24,7 @@
import java.util.BitSet;
-import org.numenta.nupic.Persistable;
+import org.numenta.nupic.model.Persistable;
/**
* {@link FlatMatrix} implementation that store booleans in a {@link BitSet}.
diff --git a/src/main/java/org/numenta/nupic/util/FastConnectionsMatrix.java b/src/main/java/org/numenta/nupic/util/FastConnectionsMatrix.java
index 6ee56f07..def62c70 100644
--- a/src/main/java/org/numenta/nupic/util/FastConnectionsMatrix.java
+++ b/src/main/java/org/numenta/nupic/util/FastConnectionsMatrix.java
@@ -22,8 +22,8 @@
package org.numenta.nupic.util;
-import org.numenta.nupic.Connections;
-import org.numenta.nupic.Persistable;
+import org.numenta.nupic.model.Connections;
+import org.numenta.nupic.model.Persistable;
import gnu.trove.set.hash.TIntHashSet;
diff --git a/src/main/java/org/numenta/nupic/util/FastRandom.java b/src/main/java/org/numenta/nupic/util/FastRandom.java
index a55328a4..aefddf24 100644
--- a/src/main/java/org/numenta/nupic/util/FastRandom.java
+++ b/src/main/java/org/numenta/nupic/util/FastRandom.java
@@ -1,6 +1,6 @@
package org.numenta.nupic.util;
-import org.numenta.nupic.Persistable;
+import org.numenta.nupic.model.Persistable;
/**
diff --git a/src/main/java/org/numenta/nupic/util/FlatArrayMatrix.java b/src/main/java/org/numenta/nupic/util/FlatArrayMatrix.java
index 9d585ac9..36264e23 100644
--- a/src/main/java/org/numenta/nupic/util/FlatArrayMatrix.java
+++ b/src/main/java/org/numenta/nupic/util/FlatArrayMatrix.java
@@ -24,7 +24,7 @@
import java.util.Arrays;
-import org.numenta.nupic.Persistable;
+import org.numenta.nupic.model.Persistable;
/**
* {@link FlatMatrix} implementation that store objects in a flat object array.
diff --git a/src/main/java/org/numenta/nupic/util/GroupBy.java b/src/main/java/org/numenta/nupic/util/GroupBy.java
index c7645a52..c8575df2 100644
--- a/src/main/java/org/numenta/nupic/util/GroupBy.java
+++ b/src/main/java/org/numenta/nupic/util/GroupBy.java
@@ -26,7 +26,6 @@
import chaschev.lang.Pair;
-
/**
*
* Allegory to the Python itertools.groupby. Objects of this class
diff --git a/src/main/java/org/numenta/nupic/util/GroupBy2.java b/src/main/java/org/numenta/nupic/util/GroupBy2.java
index d7b7d209..fbacfe9e 100644
--- a/src/main/java/org/numenta/nupic/util/GroupBy2.java
+++ b/src/main/java/org/numenta/nupic/util/GroupBy2.java
@@ -31,8 +31,11 @@
import java.util.function.Function;
import java.util.stream.IntStream;
+import org.numenta.nupic.util.GroupBy2.Slot;
+
import chaschev.lang.Pair;
+
/**
* An Java extension to groupby in Python's itertools. Allows to walk across n sorted lists
* with respect to their key functions and yields a {@link Tuple} of n lists of the
diff --git a/src/main/java/org/numenta/nupic/util/LowMemorySparseBinaryMatrix.java b/src/main/java/org/numenta/nupic/util/LowMemorySparseBinaryMatrix.java
index 4ad1ba33..71c06274 100644
--- a/src/main/java/org/numenta/nupic/util/LowMemorySparseBinaryMatrix.java
+++ b/src/main/java/org/numenta/nupic/util/LowMemorySparseBinaryMatrix.java
@@ -25,7 +25,7 @@
import java.lang.reflect.Array;
import java.util.Arrays;
-import org.numenta.nupic.Persistable;
+import org.numenta.nupic.model.Persistable;
import gnu.trove.set.TIntSet;
import gnu.trove.set.hash.TIntHashSet;
diff --git a/src/main/java/org/numenta/nupic/util/MersenneTwister.java b/src/main/java/org/numenta/nupic/util/MersenneTwister.java
index 00a0950e..0fefc05a 100644
--- a/src/main/java/org/numenta/nupic/util/MersenneTwister.java
+++ b/src/main/java/org/numenta/nupic/util/MersenneTwister.java
@@ -6,7 +6,7 @@
import java.io.ObjectInputStream;
import java.io.ObjectOutputStream;
-import org.numenta.nupic.Persistable;
+import org.numenta.nupic.model.Persistable;
/**
* MersenneTwister and MersenneTwisterFast
diff --git a/src/main/java/org/numenta/nupic/util/MersenneTwisterFast.java b/src/main/java/org/numenta/nupic/util/MersenneTwisterFast.java
index ea3e67a3..de473e6e 100644
--- a/src/main/java/org/numenta/nupic/util/MersenneTwisterFast.java
+++ b/src/main/java/org/numenta/nupic/util/MersenneTwisterFast.java
@@ -4,7 +4,7 @@
import java.io.DataOutputStream;
import java.io.IOException;
-import org.numenta.nupic.Persistable;
+import org.numenta.nupic.model.Persistable;
/**
* MersenneTwister and MersenneTwisterFast
diff --git a/src/main/java/org/numenta/nupic/util/MinMax.java b/src/main/java/org/numenta/nupic/util/MinMax.java
index 6f700b46..66e1e0a2 100644
--- a/src/main/java/org/numenta/nupic/util/MinMax.java
+++ b/src/main/java/org/numenta/nupic/util/MinMax.java
@@ -22,7 +22,7 @@
package org.numenta.nupic.util;
-import org.numenta.nupic.Persistable;
+import org.numenta.nupic.model.Persistable;
/**
* Holds two values, a min and a max. Can later be developed to
diff --git a/src/main/java/org/numenta/nupic/util/NamedTuple.java b/src/main/java/org/numenta/nupic/util/NamedTuple.java
index 235f1785..cc8074ca 100644
--- a/src/main/java/org/numenta/nupic/util/NamedTuple.java
+++ b/src/main/java/org/numenta/nupic/util/NamedTuple.java
@@ -28,7 +28,7 @@
import java.util.Collection;
import java.util.List;
-import org.numenta.nupic.Persistable;
+import org.numenta.nupic.model.Persistable;
/**
* Immutable tuple which adds associative lookup functionality.
diff --git a/src/main/java/org/numenta/nupic/util/SetSparseMatrix.java b/src/main/java/org/numenta/nupic/util/SetSparseMatrix.java
index ffca4f1c..16d3885a 100644
--- a/src/main/java/org/numenta/nupic/util/SetSparseMatrix.java
+++ b/src/main/java/org/numenta/nupic/util/SetSparseMatrix.java
@@ -3,7 +3,7 @@
import java.util.Set;
import java.util.TreeSet;
-import org.numenta.nupic.Persistable;
+import org.numenta.nupic.model.Persistable;
/**
* {@link SparseMatrix} implementation that use a {@link Set} to store indexes.
diff --git a/src/main/java/org/numenta/nupic/util/SparseBinaryMatrix.java b/src/main/java/org/numenta/nupic/util/SparseBinaryMatrix.java
index f89b6716..69effcd2 100644
--- a/src/main/java/org/numenta/nupic/util/SparseBinaryMatrix.java
+++ b/src/main/java/org/numenta/nupic/util/SparseBinaryMatrix.java
@@ -25,7 +25,7 @@
import java.lang.reflect.Array;
import java.util.Arrays;
-import org.numenta.nupic.Persistable;
+import org.numenta.nupic.model.Persistable;
/**
* Implementation of a sparse matrix which contains binary integer
diff --git a/src/main/java/org/numenta/nupic/util/SparseObjectMatrix.java b/src/main/java/org/numenta/nupic/util/SparseObjectMatrix.java
index 1ef9f9ea..ff4879af 100644
--- a/src/main/java/org/numenta/nupic/util/SparseObjectMatrix.java
+++ b/src/main/java/org/numenta/nupic/util/SparseObjectMatrix.java
@@ -24,7 +24,7 @@
import java.util.Arrays;
-import org.numenta.nupic.Persistable;
+import org.numenta.nupic.model.Persistable;
import gnu.trove.map.TIntObjectMap;
import gnu.trove.map.hash.TIntObjectHashMap;
diff --git a/src/main/java/org/numenta/nupic/util/Tuple.java b/src/main/java/org/numenta/nupic/util/Tuple.java
index aee13e3a..2ecc7e9b 100644
--- a/src/main/java/org/numenta/nupic/util/Tuple.java
+++ b/src/main/java/org/numenta/nupic/util/Tuple.java
@@ -27,7 +27,7 @@
import java.util.Comparator;
import java.util.List;
-import org.numenta.nupic.Persistable;
+import org.numenta.nupic.model.Persistable;
/**
* An immutable fixed data structure whose values are retrieved
diff --git a/src/test/java/org/numenta/nupic/ParametersTest.java b/src/test/java/org/numenta/nupic/ParametersTest.java
index db08eb58..26ead8b1 100644
--- a/src/test/java/org/numenta/nupic/ParametersTest.java
+++ b/src/test/java/org/numenta/nupic/ParametersTest.java
@@ -37,6 +37,7 @@
import org.junit.Test;
import org.numenta.nupic.Parameters.KEY;
+import org.numenta.nupic.model.Connections;
import org.numenta.nupic.util.MersenneTwister;
import org.numenta.nupic.util.Tuple;
diff --git a/src/test/java/org/numenta/nupic/QuickDayTest.java b/src/test/java/org/numenta/nupic/QuickDayTest.java
index 2aaffbac..b2320681 100644
--- a/src/test/java/org/numenta/nupic/QuickDayTest.java
+++ b/src/test/java/org/numenta/nupic/QuickDayTest.java
@@ -29,8 +29,6 @@
import java.util.Map;
import java.util.Set;
-import org.numenta.nupic.ComputeCycle;
-import org.numenta.nupic.Connections;
import org.numenta.nupic.Parameters;
import org.numenta.nupic.Parameters.KEY;
import org.numenta.nupic.algorithms.CLAClassifier;
@@ -40,6 +38,8 @@
//import org.numenta.nupic.algorithms.ClassifierResult;
import org.numenta.nupic.encoders.ScalarEncoder;
import org.numenta.nupic.model.Cell;
+import org.numenta.nupic.model.ComputeCycle;
+import org.numenta.nupic.model.Connections;
import org.numenta.nupic.util.ArrayUtils;
import org.numenta.nupic.util.FastRandom;
diff --git a/src/test/java/org/numenta/nupic/RunLayer.java b/src/test/java/org/numenta/nupic/RunLayer.java
index 3566f7dc..2d8da612 100644
--- a/src/test/java/org/numenta/nupic/RunLayer.java
+++ b/src/test/java/org/numenta/nupic/RunLayer.java
@@ -34,7 +34,6 @@
import java.util.List;
import java.util.Map;
import java.util.Random;
-import java.util.Set;
import java.util.stream.Collectors;
import java.util.stream.Stream;
@@ -53,8 +52,9 @@
import org.numenta.nupic.encoders.EncoderTuple;
import org.numenta.nupic.encoders.MultiEncoder;
import org.numenta.nupic.encoders.ScalarEncoder;
-import org.numenta.nupic.model.Cell;
-import org.numenta.nupic.network.ManualInput;
+import org.numenta.nupic.model.ComputeCycle;
+import org.numenta.nupic.model.Connections;
+import org.numenta.nupic.model.SDR;
import org.numenta.nupic.network.Network;
import org.numenta.nupic.util.ArrayUtils;
import org.numenta.nupic.util.Tuple;
@@ -63,9 +63,9 @@
public class RunLayer {
public static boolean IS_VERBOSE = true;
public static boolean LEARN = true;
- public static boolean TM_ONLY = false;
+ public static boolean TM_ONLY = true;
public static boolean SP_ONLY = false;
- public static boolean NETWORK = true;
+ public static boolean NETWORK = false;
public static class MakeshiftLayer {
private Connections connections;
@@ -85,7 +85,7 @@ public static class MakeshiftLayer {
// private static String INPUT_PATH = "/Users/cogmission/git/NAB/data/artificialNoAnomaly/art_daily_no_noise.csv";
// private static String readFile = "/Users/cogmission/git/NAB/data/artificialNoAnomaly/art_daily_sp_output.txt";
private static String INPUT_PATH = "/Users/cogmission/git/NAB/data/realTraffic/TravelTime_387.csv";
- private static String readFile = "/Users/cogmission/git/NAB/data/realTraffic/TravelTime_sp_output.txt";
+ private static String readFile = "/Users/cogmission/git/newtm/htm.java/src/test/resources/TravelTime_sp_output.txt";
private static List input;
private static List raw;
@@ -112,39 +112,39 @@ public MakeshiftLayer(Connections c, MultiEncoder encoder, SpatialPooler sp,
this.tm = tm;
this.classifier = cl;
- Parameters parameters = getParameters();
+// Parameters parameters = getParameters();
// 2015-08-31 18:22:00,90
- network = Network.create("NAB Network", parameters)
- .add(Network.createRegion("NAB Region")
- .add(Network.createLayer("NAB Layer", parameters)
- .add(Anomaly.create())
- .add(new TemporalMemory())));
-
- network.observe().subscribe((inference) -> {
- double score = inference.getAnomalyScore();
- int record = inference.getRecordNum();
-
- recordNum = record;
-
- printHeader();
-
- Set act = ((ManualInput)inference).getActiveCells();
- int[] activeColumnIndices = SDR.cellsAsColumnIndices(act, connections.cellsPerColumn);
- Set prev = ((ManualInput)inference).getPreviousPredictiveCells();
- int[] prevPredColumnIndices = prev == null ? null : SDR.cellsAsColumnIndices(prev, connections.cellsPerColumn);
- String input = Arrays.toString((int[])((ManualInput)inference).getLayerInput());
- String prevPred = prevPredColumnIndices == null ? "null" : Arrays.toString(prevPredColumnIndices);
- String active = Arrays.toString(activeColumnIndices);
- System.out.println(" TemporalMemory Input: " + input);
- System.out.println("TemporalMemory prev. predicted: " + prevPred);
- System.out.println(" TemporalMemory active: " + active);
- System.out.println("Anomaly Score: " + score + "\n");
-
- }, (error) -> {
- error.printStackTrace();
- }, () -> {
- // On Complete
- });
+// network = Network.create("NAB Network", parameters)
+// .add(Network.createRegion("NAB Region")
+// .add(Network.createLayer("NAB Layer", parameters)
+// .add(Anomaly.create())
+// .add(new TemporalMemory())));
+//
+// network.observe().subscribe((inference) -> {
+// double score = inference.getAnomalyScore();
+// int record = inference.getRecordNum();
+//
+// recordNum = record;
+//
+// printHeader();
+//
+// Set act = ((ManualInput)inference).getActiveCells();
+// int[] activeColumnIndices = SDR.cellsAsColumnIndices(act, connections.getCellsPerColumn());
+// Set prev = ((ManualInput)inference).getPreviousPredictiveCells();
+// int[] prevPredColumnIndices = prev == null ? null : SDR.cellsAsColumnIndices(prev, connections.getCellsPerColumn());
+// String input = Arrays.toString((int[])((ManualInput)inference).getLayerInput());
+// String prevPred = prevPredColumnIndices == null ? "null" : Arrays.toString(prevPredColumnIndices);
+// String active = Arrays.toString(activeColumnIndices);
+// System.out.println(" TemporalMemory Input: " + input);
+// System.out.println("TemporalMemory prev. predicted: " + prevPred);
+// System.out.println(" TemporalMemory active: " + active);
+// System.out.println("Anomaly Score: " + score + "\n");
+//
+// }, (error) -> {
+// error.printStackTrace();
+// }, () -> {
+// // On Complete
+// });
}
public void printHeader() {
@@ -215,9 +215,9 @@ public Tuple tmStep(int[] sparseSPOutput, boolean learn, boolean isVerbose) {
// Input into the Temporal Memory
ComputeCycle cc = tm.compute(connections, sparseSPOutput, learn);
int[] activeCellIndices = cc.activeCells().stream().mapToInt(c -> c.getIndex()).sorted().toArray();
- int[] predColumnIndices = SDR.cellsAsColumnIndices(cc.predictiveCells(), connections.cellsPerColumn);
+ int[] predColumnIndices = SDR.cellsAsColumnIndices(cc.predictiveCells(), connections.getCellsPerColumn());
int[] activeColumns = Arrays.stream(activeCellIndices)
- .map(cell -> cell / connections.cellsPerColumn)
+ .map(cell -> cell / connections.getCellsPerColumn())
.distinct()
.sorted()
.toArray();
@@ -355,7 +355,7 @@ public static Parameters getParameters() {
//Temporal Memory specific
parameters.set(KEY.INITIAL_PERMANENCE, 0.2);
parameters.set(KEY.CONNECTED_PERMANENCE, 0.8);
- parameters.set(KEY.MIN_THRESHOLD, 5);
+ parameters.set(KEY.MIN_THRESHOLD, 4);
parameters.set(KEY.MAX_NEW_SYNAPSE_COUNT, 6);
parameters.set(KEY.PERMANENCE_INCREMENT, 0.1);//0.05
parameters.set(KEY.PERMANENCE_DECREMENT, 0.1);//0.05
diff --git a/src/test/java/org/numenta/nupic/algorithms/AnomalyLikelihoodTest.java b/src/test/java/org/numenta/nupic/algorithms/AnomalyLikelihoodTest.java
index ade7cdcb..3be0aa73 100644
--- a/src/test/java/org/numenta/nupic/algorithms/AnomalyLikelihoodTest.java
+++ b/src/test/java/org/numenta/nupic/algorithms/AnomalyLikelihoodTest.java
@@ -4,17 +4,10 @@
import static org.junit.Assert.assertFalse;
import static org.junit.Assert.assertTrue;
import static org.junit.Assert.fail;
-import static org.numenta.nupic.algorithms.Anomaly.KEY_DIST;
-import static org.numenta.nupic.algorithms.Anomaly.KEY_HIST_LIKE;
import static org.numenta.nupic.algorithms.Anomaly.KEY_MEAN;
import static org.numenta.nupic.algorithms.Anomaly.KEY_MODE;
-import static org.numenta.nupic.algorithms.Anomaly.KEY_MVG_AVG;
import static org.numenta.nupic.algorithms.Anomaly.KEY_STDEV;
import static org.numenta.nupic.algorithms.Anomaly.KEY_VARIANCE;
-import gnu.trove.iterator.TDoubleIterator;
-import gnu.trove.list.array.TDoubleArrayList;
-import gnu.trove.map.TObjectDoubleMap;
-import gnu.trove.map.hash.TObjectDoubleHashMap;
import java.util.ArrayList;
import java.util.Arrays;
@@ -29,11 +22,14 @@
import org.junit.Test;
import org.numenta.nupic.algorithms.Anomaly.AveragedAnomalyRecordList;
import org.numenta.nupic.algorithms.Anomaly.Mode;
-import org.numenta.nupic.algorithms.AnomalyLikelihood.AnomalyParams;
import org.numenta.nupic.util.ArrayUtils;
import org.numenta.nupic.util.Condition;
import org.numenta.nupic.util.MersenneTwister;
+import gnu.trove.iterator.TDoubleIterator;
+import gnu.trove.map.TObjectDoubleMap;
+import gnu.trove.map.hash.TObjectDoubleHashMap;
+
public class AnomalyLikelihoodTest {
private AnomalyLikelihood an;
@@ -544,30 +540,4 @@ public void testFilterLikelihoods() {
assertEquals(successIndexes, l2b2.length);
}
- /**
- * Tests the AnomalyParams return value and its json creation
- */
- @Test
- public void testAnomalyParamsToJson() {
- AnomalyParams params = new AnomalyParams(
- new String[] { KEY_DIST, KEY_HIST_LIKE, KEY_MVG_AVG},
- new Statistic(0.38423985556178486, 0.009520602474199693, 0.09757357467162762),
- new double[] { 0.460172163,0.344578258,0.344578258,0.382088578,0.460172163 },
- new MovingAverage(
- new TDoubleArrayList(
- new double[] { 0.09528343752779542,0.5432072190186226,0.9062454498382395,0.44264021533137254,-0.009955323005220784 }),
- 1.9774209987108093, // total
- 5 // window size
- )
- );
-
- String expected = "{\"distribution\":{\"mean\":0.38423985556178486,\"variance\":0.009520602474199693,\"stdev\":0.09757357467162762},"+
- "\"historicalLikelihoods\":[0.460172163,0.344578258,0.344578258,0.382088578,0.460172163],"+
- "\"movingAverage\":{\"windowSize\":5,"+
- "\"historicalValues\":[0.09528343752779542,0.5432072190186226,0.9062454498382395,0.44264021533137254,-0.009955323005220784],"+
- "\"total\":1.9774209987108093}}";
-
- assertEquals(expected, params.toJson(true));
- }
-
}
diff --git a/src/test/java/org/numenta/nupic/algorithms/SpatialPoolerCompatibilityTest.java b/src/test/java/org/numenta/nupic/algorithms/SpatialPoolerCompatibilityTest.java
index 1bb9291f..7e5418b7 100644
--- a/src/test/java/org/numenta/nupic/algorithms/SpatialPoolerCompatibilityTest.java
+++ b/src/test/java/org/numenta/nupic/algorithms/SpatialPoolerCompatibilityTest.java
@@ -30,10 +30,10 @@
import java.util.stream.IntStream;
import org.junit.Test;
-import org.numenta.nupic.Connections;
import org.numenta.nupic.Parameters;
import org.numenta.nupic.Parameters.KEY;
import org.numenta.nupic.model.Column;
+import org.numenta.nupic.model.Connections;
import org.numenta.nupic.model.Pool;
import org.numenta.nupic.util.Tuple;
import org.numenta.nupic.util.UniversalRandom;
diff --git a/src/test/java/org/numenta/nupic/algorithms/SpatialPoolerTest.java b/src/test/java/org/numenta/nupic/algorithms/SpatialPoolerTest.java
index 2caab1fc..06c26ab0 100644
--- a/src/test/java/org/numenta/nupic/algorithms/SpatialPoolerTest.java
+++ b/src/test/java/org/numenta/nupic/algorithms/SpatialPoolerTest.java
@@ -30,10 +30,10 @@
import java.util.stream.IntStream;
import org.junit.Test;
-import org.numenta.nupic.Connections;
import org.numenta.nupic.Parameters;
import org.numenta.nupic.Parameters.KEY;
import org.numenta.nupic.algorithms.SpatialPooler.InvalidSPParamValueException;
+import org.numenta.nupic.model.Connections;
import org.numenta.nupic.model.Pool;
import org.numenta.nupic.util.AbstractSparseBinaryMatrix;
import org.numenta.nupic.util.ArrayUtils;
diff --git a/src/test/java/org/numenta/nupic/algorithms/TemporalMemoryTest.java b/src/test/java/org/numenta/nupic/algorithms/TemporalMemoryTest.java
index ab9862c8..8f2cd891 100644
--- a/src/test/java/org/numenta/nupic/algorithms/TemporalMemoryTest.java
+++ b/src/test/java/org/numenta/nupic/algorithms/TemporalMemoryTest.java
@@ -1,8 +1,11 @@
package org.numenta.nupic.algorithms;
-import static org.junit.Assert.*;
+import static org.junit.Assert.assertEquals;
+import static org.junit.Assert.assertFalse;
+import static org.junit.Assert.assertTrue;
import java.util.ArrayList;
+import java.util.Arrays;
import java.util.Collections;
import java.util.HashSet;
import java.util.LinkedHashSet;
@@ -13,19 +16,19 @@
import java.util.stream.Stream;
import org.junit.Test;
-import org.numenta.nupic.ComputeCycle;
-import org.numenta.nupic.Connections;
import org.numenta.nupic.Parameters;
import org.numenta.nupic.Parameters.KEY;
import org.numenta.nupic.model.Cell;
import org.numenta.nupic.model.Column;
+import org.numenta.nupic.model.ComputeCycle;
+import org.numenta.nupic.model.Connections;
import org.numenta.nupic.model.DistalDendrite;
import org.numenta.nupic.model.Synapse;
import org.numenta.nupic.util.UniversalRandom;
import org.nustaq.serialization.FSTConfiguration;
-public class TemporalMemoryTest {
-
+public class TemporalMemoryTest {
+
private Parameters getDefaultParameters() {
Parameters retVal = Parameters.getTemporalDefaultParameters();
retVal.set(KEY.COLUMN_DIMENSIONS, new int[] { 32 });
@@ -77,7 +80,7 @@ public void testActivateCorrectlyPredictiveCells() {
cn.createSynapse(activeSegment, cn.getCell(2), 0.5);
cn.createSynapse(activeSegment, cn.getCell(3), 0.5);
- ComputeCycle cc = tm.compute(cn, previousActiveColumns, true);
+ ComputeCycle cc = tm.compute(cn, previousActiveColumns, true);
assertTrue(cc.predictiveCells().equals(expectedActiveCells));
ComputeCycle cc2 = tm.compute(cn, activeColumns, true);
assertTrue(cc2.activeCells().equals(expectedActiveCells));
@@ -188,31 +191,6 @@ public void testReinforcedCorrectlyActiveSegments() {
assertEquals(0.42, is1.getPermanence(), 0.001);
}
- @Test
- public void testNoGrowthOnCorrectlyActiveSegments() {
- TemporalMemory tm = new TemporalMemory();
- Connections cn = new Connections();
- Parameters p = getDefaultParameters(null, KEY.INITIAL_PERMANENCE, 0.2);
- p = getDefaultParameters(p, KEY.PREDICTED_SEGMENT_DECREMENT, 0.02);
- p.apply(cn);
- TemporalMemory.init(cn);
-
- int[] previousActiveColumns = { 0 };
- int[] activeColumns = { 1 };
- Cell[] previousActiveCells = {cn.getCell(0), cn.getCell(1), cn.getCell(2), cn.getCell(3) };
- Cell activeCell = cn.getCell(5);
-
- DistalDendrite activeSegment = cn.createSegment(activeCell);
- cn.createSynapse(activeSegment, previousActiveCells[0], 0.5);
- cn.createSynapse(activeSegment, previousActiveCells[1], 0.5);
- cn.createSynapse(activeSegment, previousActiveCells[2], 0.5);
-
- tm.compute(cn, previousActiveColumns, true);
- tm.compute(cn, activeColumns, true);
-
- assertEquals(3, activeSegment.getAllSynapses(cn).size());
- }
-
@Test
public void testReinforcedSelectedMatchingSegmentInBurstingColumn() {
TemporalMemory tm = new TemporalMemory();
@@ -321,7 +299,7 @@ public void testNoChangeToMatchingSegmentsInPredictedActiveColumn() {
public void testNoNewSegmentIfNotEnoughWinnerCells() {
TemporalMemory tm = new TemporalMemory();
Connections cn = new Connections();
- Parameters p = getDefaultParameters(null, KEY.MAX_NEW_SYNAPSE_COUNT, 2);
+ Parameters p = getDefaultParameters(null, KEY.MAX_NEW_SYNAPSE_COUNT, 3);
p.apply(cn);
TemporalMemory.init(cn);
@@ -331,7 +309,7 @@ public void testNoNewSegmentIfNotEnoughWinnerCells() {
tm.compute(cn, zeroColumns, true);
tm.compute(cn, activeColumns, true);
- assertEquals(0, cn.getSegmentCount(), 0);
+ assertEquals(0, cn.numSegments(), 0);
}
@Test
@@ -356,7 +334,7 @@ public void testNewSegmentAddSynapsesToSubsetOfWinnerCells() {
assertEquals(1, winnerCells.size());
List segments = winnerCells.get(0).getSegments(cn);
assertEquals(1, segments.size());
- List synapses = cn.unDestroyedSynapsesForSegment(segments.get(0));
+ List synapses = cn.getSynapses(segments.get(0));
assertEquals(2, synapses.size());
for(Synapse synapse : synapses) {
@@ -418,14 +396,17 @@ public void testMatchingSegmentAddSynapsesToSubsetOfWinnerCells() {
assertTrue(cc.winnerCells().equals(prevWinnerCells));
cc = tm.compute(cn, activeColumns, true);
- List synapses = cn.unDestroyedSynapsesForSegment(matchingSegment);
+ List synapses = cn.getSynapses(matchingSegment);
assertEquals(3, synapses.size());
Collections.sort(synapses);
- synapses = synapses.subList(1, synapses.size());
for(Synapse synapse : synapses) {
+ if(synapse.getPresynapticCell().getIndex() == 0) continue;
+
assertEquals(0.21, synapse.getPermanence(), 0.01);
- assertTrue(prevWinnerCells.contains(synapse.getPresynapticCell()));
+ assertTrue(synapse.getPresynapticCell().getIndex() == 1 ||
+ synapse.getPresynapticCell().getIndex() == 2 ||
+ synapse.getPresynapticCell().getIndex() == 3);
}
}
@@ -450,12 +431,60 @@ public void testMatchingSegmentAddSynapsesToAllWinnerCells() {
cc = tm.compute(cn, activeColumns, true);
- List synapses = cn.unDestroyedSynapsesForSegment(matchingSegment);
+ List synapses = cn.getSynapses(matchingSegment);
assertEquals(2, synapses.size());
- Synapse synapse1 = synapses.get(1);
- assertEquals(.21, synapse1.getPermanence(), 0.001);
- assertEquals(cn.getCell(1), synapse1.getPresynapticCell());
+ Collections.sort(synapses);
+ for(Synapse synapse : synapses) {
+ if(synapse.getPresynapticCell().getIndex() == 0) continue;
+
+ assertEquals(0.21, synapse.getPermanence(), 0.01);
+ assertEquals(1, synapse.getPresynapticCell().getIndex());
+ }
+ }
+
+ /**
+ * When a segment becomes active, grow synapses to previous winner cells.
+ *
+ * The number of grown synapses is calculated from the "matching segment"
+ * overlap, not the "active segment" overlap.
+ */
+ @Test
+ public void testActiveSegmentGrowSynapsesAccordingToPotentialOverlap() {
+ TemporalMemory tm = new TemporalMemory();
+ Connections cn = new Connections();
+ Parameters p = getDefaultParameters(null, KEY.CELLS_PER_COLUMN, 1);
+ p = getDefaultParameters(p, KEY.MIN_THRESHOLD, 1);
+ p = getDefaultParameters(p, KEY.ACTIVATION_THRESHOLD, 2);
+ p = getDefaultParameters(p, KEY.MAX_NEW_SYNAPSE_COUNT, 4);
+ p.apply(cn);
+ TemporalMemory.init(cn);
+
+ // Use 1 cell per column so that we have easy control over the winner cells.
+ int[] previousActiveColumns = { 0, 1, 2, 3, 4 };
+ Set prevWinnerCells = Arrays.asList(0, 1, 2, 3, 4)
+ .stream()
+ .map(i -> cn.getCell(i))
+ .collect(Collectors.toCollection(LinkedHashSet::new));
+ int[] activeColumns = { 5 };
+
+ DistalDendrite activeSegment = cn.createSegment(cn.getCell(5));
+ cn.createSynapse(activeSegment, cn.getCell(0), 0.5);
+ cn.createSynapse(activeSegment, cn.getCell(1), 0.5);
+ cn.createSynapse(activeSegment, cn.getCell(2), 0.2);
+
+ ComputeCycle cc = tm.compute(cn, previousActiveColumns, true);
+ assertEquals(prevWinnerCells, cc.winnerCells());
+ cc = tm.compute(cn, activeColumns, true);
+
+ Set presynapticCells = cn.getSynapses(activeSegment).stream()
+ .map(s -> s.getPresynapticCell())
+ .collect(Collectors.toSet());
+
+ assertTrue(
+ presynapticCells.size() == 4 && (
+ presynapticCells.containsAll(Arrays.asList(cn.getCell(0), cn.getCell(1), cn.getCell(2), cn.getCell(3))) ||
+ presynapticCells.containsAll(Arrays.asList(cn.getCell(0), cn.getCell(1), cn.getCell(2), cn.getCell(4)))));
}
@Test
@@ -477,12 +506,13 @@ public void testDestroyWeakSynapseOnWrongPrediction() {
cn.createSynapse(activeSegment, previousActiveCells[0], 0.5);
cn.createSynapse(activeSegment, previousActiveCells[1], 0.5);
cn.createSynapse(activeSegment, previousActiveCells[2], 0.5);
- Synapse weakActiveSynapse = cn.createSynapse(activeSegment, previousActiveCells[3], 0.015);
+ // Weak Synapse
+ cn.createSynapse(activeSegment, previousActiveCells[3], 0.015);
tm.compute(cn, previousActiveColumns, true);
tm.compute(cn, activeColumns, true);
- assertTrue(weakActiveSynapse.destroyed());
+ assertEquals(3, cn.numSynapses(activeSegment));
}
@Test
@@ -504,12 +534,13 @@ public void testDestroyWeakSynapseOnActiveReinforce() {
cn.createSynapse(activeSegment, previousActiveCells[0], 0.5);
cn.createSynapse(activeSegment, previousActiveCells[1], 0.5);
cn.createSynapse(activeSegment, previousActiveCells[2], 0.5);
- Synapse weakInactSynapse = cn.createSynapse(activeSegment, previousActiveCells[3], 0.009);
+ // Weak Synapse
+ cn.createSynapse(activeSegment, previousActiveCells[3], 0.009);
tm.compute(cn, previousActiveColumns, true);
tm.compute(cn, activeColumns, true);
- assertTrue(weakInactSynapse.destroyed());
+ assertEquals(3, cn.numSynapses(activeSegment));
}
@Test
@@ -533,18 +564,17 @@ public void testRecycleWeakestSynapseToMakeRoomForNewSynapse() {
DistalDendrite matchingSegment = cn.createSegment(cn.getCell(4));
cn.createSynapse(matchingSegment, cn.getCell(81), 0.6);
-
- Synapse weakestSynapse = cn.createSynapse(matchingSegment, cn.getCell(0), 0.11);
+ // Weakest Synapse
+ cn.createSynapse(matchingSegment, cn.getCell(0), 0.11);
ComputeCycle cc = tm.compute(cn, prevActiveColumns, true);
assertEquals(prevWinnerCells, cc.winnerCells);
tm.compute(cn, activeColumns, true);
- assertNotEquals(cn.getCell(0), weakestSynapse.getPresynapticCell());
-
- assertFalse(weakestSynapse.destroyed());
-
- assertEquals(0.21, weakestSynapse.getPermanence(), .001);
+ List synapses = cn.getSynapses(matchingSegment);
+ assertEquals(3, synapses.size());
+ Set presynapticCells = synapses.stream().map(s -> s.getPresynapticCell()).collect(Collectors.toSet());
+ assertFalse(presynapticCells.stream().mapToInt(cell -> cell.getIndex()).anyMatch(i -> i == 0));
}
@Test
@@ -568,29 +598,35 @@ public void testRecycleLeastRecentlyActiveSegmentToMakeRoomForNewSegment() {
tm.compute(cn, prevActiveColumns1, true);
tm.compute(cn, activeColumns, true);
- assertEquals(1, cn.unDestroyedSegmentsForCell(cell9).size());
- DistalDendrite oldestSegment = cn.unDestroyedSegmentsForCell(cell9).get(0);
+ assertEquals(1, cn.getSegments(cell9).size());
+ DistalDendrite oldestSegment = cn.getSegments(cell9).get(0);
tm.reset(cn);
tm.compute(cn, prevActiveColumns2, true);
tm.compute(cn, activeColumns, true);
- assertEquals(2, cn.unDestroyedSegmentsForCell(cell9).size());
+ assertEquals(2, cn.getSegments(cell9).size());
+
+ Set oldPresynaptic = cn.getSynapses(oldestSegment)
+ .stream()
+ .map(s -> s.getPresynapticCell())
+ .collect(Collectors.toSet());
tm.reset(cn);
tm.compute(cn, prevActiveColumns3, true);
tm.compute(cn, activeColumns, true);
- assertEquals(2, cn.unDestroyedSegmentsForCell(cell9).size());
+ assertEquals(2, cn.getSegments(cell9).size());
- List synapses = cn.unDestroyedSynapsesForSegment(oldestSegment);
- assertEquals(3, synapses.size());
+ // Verify none of the segments are connected to the cells the old
+ // segment was connected to.
- Set presynapticCells = new LinkedHashSet<>();
- for(Synapse synapse : cn.getSynapses(oldestSegment)) {
- presynapticCells.add(synapse.getPresynapticCell());
+ for(DistalDendrite segment : cn.getSegments(cell9)) {
+ Set newPresynaptic = cn.getSynapses(segment)
+ .stream()
+ .map(s -> s.getPresynapticCell())
+ .collect(Collectors.toSet());
+
+ assertTrue(Collections.disjoint(oldPresynaptic, newPresynaptic));
}
-
- Set expected = cn.getCellSet(new int[] { 6, 7, 8 });
- assertEquals(expected, presynapticCells);
}
@Test
@@ -617,10 +653,7 @@ public void testDestroySegmentsWithTooFewSynapsesToBeMatching() {
tm.compute(cn, prevActiveColumns, true);
tm.compute(cn, activeColumns, true);
- assertTrue(cn.getSegments(expectedActiveCell).contains(matchingSegment));
- assertFalse(cn.unDestroyedSegmentsForCell(expectedActiveCell).contains(matchingSegment));
- assertTrue(matchingSegment.destroyed());
- assertTrue(cn.unDestroyedSegmentsForCell(expectedActiveCell).isEmpty());
+ assertEquals(0, cn.numSegments(expectedActiveCell));
}
@Test
@@ -691,15 +724,15 @@ public void testAddSegmentToCellWithFewestSegments() {
assertTrue(cc.activeCells().equals(activeCells));
- assertEquals(3, cn.getSegmentCount());
- assertEquals(1, cn.getCell(0).getSegments(cn).size());
- assertEquals(1, cn.getCell(3).getSegments(cn).size());
- assertEquals(1, segment1.getAllSynapses(cn).size());
- assertEquals(1, segment2.getAllSynapses(cn).size());
+ assertEquals(3, cn.numSegments());
+ assertEquals(1, cn.numSegments(cn.getCell(0)));
+ assertEquals(1, cn.numSegments(cn.getCell(3)));
+ assertEquals(1, cn.numSynapses(segment1));
+ assertEquals(1, cn.numSynapses(segment2));
- List segments = cn.getCell(1).getSegments(cn, true);
+ List segments = new ArrayList<>(cn.getSegments(cn.getCell(1)));
if(segments.size() == 0) {
- List segments2 = cn.getCell(2).getSegments(cn);
+ List segments2 = cn.getSegments(cn.getCell(2));
assertFalse(segments2.size() == 0);
grewOnCell2 = true;
segments.addAll(segments2);
@@ -835,7 +868,7 @@ public void testAdaptSegmentToMin() {
cn.createSynapse(dd, cn.getCell(1), 0.3);
tm.adaptSegment(cn, dd, cn.getCellSet(), cn.getPermanenceIncrement(), cn.getPermanenceDecrement());
- assertFalse(cn.unDestroyedSynapsesForSegment(dd).contains(s1));
+ assertFalse(cn.getSynapses(dd).contains(s1));
}
@Test
diff --git a/src/test/java/org/numenta/nupic/integration/AbstractTemporalMemoryTest.java b/src/test/java/org/numenta/nupic/integration/AbstractTemporalMemoryTest.java
index e25615e6..d64faf34 100644
--- a/src/test/java/org/numenta/nupic/integration/AbstractTemporalMemoryTest.java
+++ b/src/test/java/org/numenta/nupic/integration/AbstractTemporalMemoryTest.java
@@ -26,12 +26,12 @@
import java.util.List;
import java.util.Set;
-import org.numenta.nupic.Connections;
import org.numenta.nupic.Parameters;
import org.numenta.nupic.Parameters.KEY;
import org.numenta.nupic.algorithms.TemporalMemory;
import org.numenta.nupic.datagen.PatternMachine;
import org.numenta.nupic.datagen.SequenceMachine;
+import org.numenta.nupic.model.Connections;
import org.numenta.nupic.monitor.MonitoredTemporalMemory;
import org.numenta.nupic.util.ArrayUtils;
diff --git a/src/test/java/org/numenta/nupic/ComputeCycleTest.java b/src/test/java/org/numenta/nupic/model/ComputeCycleTest.java
similarity index 84%
rename from src/test/java/org/numenta/nupic/ComputeCycleTest.java
rename to src/test/java/org/numenta/nupic/model/ComputeCycleTest.java
index 94ef3ec5..96a713cc 100644
--- a/src/test/java/org/numenta/nupic/ComputeCycleTest.java
+++ b/src/test/java/org/numenta/nupic/model/ComputeCycleTest.java
@@ -1,4 +1,4 @@
-package org.numenta.nupic;
+package org.numenta.nupic.model;
import static org.junit.Assert.assertEquals;
import static org.junit.Assert.assertFalse;
@@ -16,20 +16,16 @@
import java.util.stream.IntStream;
import org.junit.Test;
-import org.numenta.nupic.ComputeCycle.ColumnData;
-import org.numenta.nupic.Connections.SegmentOverlap;
+import org.numenta.nupic.Parameters;
import org.numenta.nupic.Parameters.KEY;
import org.numenta.nupic.algorithms.TemporalMemory;
-import org.numenta.nupic.model.Cell;
-import org.numenta.nupic.model.Column;
-import org.numenta.nupic.model.DistalDendrite;
+import org.numenta.nupic.algorithms.TemporalMemory.ColumnData;
import org.numenta.nupic.util.GroupBy2;
import org.numenta.nupic.util.Tuple;
import org.numenta.nupic.util.UniversalRandom;
import chaschev.lang.Pair;
-
public class ComputeCycleTest {
@Test
@@ -93,7 +89,7 @@ public void testActiveColumnsRetrievable() {
//cc = tm.compute(cn, activeColumnsIndices, true);
Function identity = Function.identity();
- Function segToCol = segment -> segment.segment.getParentCell().getColumn();
+ Function segToCol = segment -> segment.getParentCell().getColumn();
List activeColumns = Arrays.stream(activeColumnsIndices)
.sorted()
@@ -102,20 +98,19 @@ public void testActiveColumnsRetrievable() {
GroupBy2 grouper = GroupBy2.of(
new Pair(activeColumns, identity),
- new Pair(new ArrayList(cn.getActiveSegmentOverlaps()), segToCol),
- new Pair(new ArrayList(cn.getMatchingSegmentOverlaps()), segToCol));
+ new Pair(new ArrayList(cn.getActiveSegments()), segToCol),
+ new Pair(new ArrayList(cn.getMatchingSegments()), segToCol));
- ComputeCycle cycle = new ComputeCycle();
+ ColumnData columnData = new ColumnData();
for(Tuple t : grouper) { // Executes only once
- ColumnData columnData = cycle.columnData.set(t);
+ columnData = columnData.set(t);
assertTrue(columnData.activeColumns().equals(activeColumns));
assertTrue(columnData.activeSegments().isEmpty());
- List sos = columnData.matchingSegments();
+ List sos = columnData.matchingSegments();
assertEquals(1, sos.size());
- assertEquals(1, sos.get(0).overlap);
- assertEquals(0, sos.get(0).segment.getIndex());
- assertEquals(4, sos.get(0).segment.getParentCell().getIndex());
+ assertEquals(0, sos.get(0).getIndex());
+ assertEquals(4, sos.get(0).getParentCell().getIndex());
assertTrue(columnData.column().equals(cn.getColumn(4)));
}
diff --git a/src/test/java/org/numenta/nupic/ConnectionsTest.java b/src/test/java/org/numenta/nupic/model/ConnectionsTest.java
similarity index 75%
rename from src/test/java/org/numenta/nupic/ConnectionsTest.java
rename to src/test/java/org/numenta/nupic/model/ConnectionsTest.java
index 8df6f34f..bd426303 100644
--- a/src/test/java/org/numenta/nupic/ConnectionsTest.java
+++ b/src/test/java/org/numenta/nupic/model/ConnectionsTest.java
@@ -1,12 +1,12 @@
-package org.numenta.nupic;
+package org.numenta.nupic.model;
import static org.junit.Assert.assertEquals;
import static org.junit.Assert.assertFalse;
import static org.junit.Assert.assertTrue;
import static org.junit.Assert.fail;
-import java.util.ArrayList;
import java.util.Arrays;
+import java.util.Collections;
import java.util.HashSet;
import java.util.LinkedHashSet;
import java.util.List;
@@ -15,107 +15,208 @@
import java.util.stream.IntStream;
import org.junit.Test;
-import org.numenta.nupic.Connections.Activity;
-import org.numenta.nupic.Connections.SegmentOverlap;
+import org.numenta.nupic.Parameters;
import org.numenta.nupic.Parameters.KEY;
import org.numenta.nupic.algorithms.SpatialPooler;
import org.numenta.nupic.algorithms.TemporalMemory;
-import org.numenta.nupic.model.Cell;
-import org.numenta.nupic.model.Column;
-import org.numenta.nupic.model.DistalDendrite;
-import org.numenta.nupic.model.Synapse;
+import org.numenta.nupic.model.Connections.Activity;
import org.numenta.nupic.util.ArrayUtils;
import org.numenta.nupic.util.MersenneTwister;
import com.cedarsoftware.util.DeepEquals;
-
public class ConnectionsTest {
@Test
- public void testCopy() {
+ public void testSegmentPositionForSortKey() {
Parameters retVal = Parameters.getTemporalDefaultParameters();
retVal.set(KEY.COLUMN_DIMENSIONS, new int[] { 32 });
retVal.set(KEY.CELLS_PER_COLUMN, 4);
-
+
Connections connections = new Connections();
-
+
retVal.apply(connections);
TemporalMemory.init(connections);
+ Cell cell10 = connections.getCell(10);
+ DistalDendrite segment0 = connections.createSegment(cell10);
+
+ Cell cell9 = connections.getCell(9);
+ DistalDendrite segment1 = connections.createSegment(cell9);
+
+ Cell cell11 = connections.getCell(11);
+ DistalDendrite segment2 = connections.createSegment(cell11);
+ DistalDendrite segment3 = connections.createSegment(cell11);
+ DistalDendrite segment4 = connections.createSegment(cell11);
+
+ List expected = Arrays.asList(segment1, segment0, segment2, segment3, segment4);
+ List segments = Arrays.asList(segment3, segment2, segment0, segment4, segment1);
+ assertFalse(DeepEquals.deepEquals(expected, segments));
+
+ Collections.sort(segments, connections.segmentPositionSortKey);
+ assertTrue(DeepEquals.deepEquals(expected, segments));
+ }
+
+ @Test
+ public void testCopy() {
+ Parameters retVal = Parameters.getTemporalDefaultParameters();
+ retVal.set(KEY.COLUMN_DIMENSIONS, new int[] { 32 });
+ retVal.set(KEY.CELLS_PER_COLUMN, 4);
+
+ Connections connections = new Connections();
+
+ retVal.apply(connections);
+ TemporalMemory.init(connections);
+
assertTrue(DeepEquals.deepEquals(connections, connections.copy()));
}
-
+
@Test
public void testCreateSegment() {
Parameters retVal = Parameters.getTemporalDefaultParameters();
retVal.set(KEY.COLUMN_DIMENSIONS, new int[] { 32 });
retVal.set(KEY.CELLS_PER_COLUMN, 4);
-
+
Connections connections = new Connections();
-
+
retVal.apply(connections);
TemporalMemory.init(connections);
-
+
Cell cell10 = connections.getCell(10);
List segments = connections.getSegments(cell10);
// Establish list is empty == no current segments
assertEquals(0, segments.size());
-
+
DistalDendrite segment1 = connections.createSegment(cell10);
assertEquals(0, segment1.getIndex());
assertEquals(10, segment1.getParentCell().getIndex());
-
+
DistalDendrite segment2 = connections.createSegment(cell10);
assertEquals(1, segment2.getIndex());
assertEquals(10, segment2.getParentCell().getIndex());
-
+
List expected = Arrays.asList(new DistalDendrite[] { segment1, segment2 });
assertEquals(expected, connections.getSegments(cell10));
- assertEquals(2, connections.getSegmentCount());
+ assertEquals(2, connections.numSegments());
}
@Test
public void testCreateSegmentReuse() {
- Parameters p = Parameters.getTemporalDefaultParameters();
- p.set(KEY.COLUMN_DIMENSIONS, new int[] { 32 });
- p.set(KEY.CELLS_PER_COLUMN, 32);
- p.set(KEY.MAX_SEGMENTS_PER_CELL, 2);
-
+ Parameters retVal = Parameters.getTemporalDefaultParameters();
+ retVal.set(KEY.COLUMN_DIMENSIONS, new int[] { 32 });
+ retVal.set(KEY.CELLS_PER_COLUMN, 4);
+ retVal.set(KEY.MAX_SEGMENTS_PER_CELL, 2);
+
Connections connections = new Connections();
-
- p.apply(connections);
+
+ retVal.apply(connections);
TemporalMemory.init(connections);
-
+
Cell cell42 = connections.getCell(42);
-
+ Cell cell1 = connections.getCell(1);
+ Cell cell2 = connections.getCell(2);
DistalDendrite segment1 = connections.createSegment(cell42);
- connections.createSynapse(segment1, connections.getCell(1), 0.5);
- connections.createSynapse(segment1, connections.getCell(2), 0.5);
-
+ connections.createSynapse(segment1, cell1, 0.5);
+ connections.createSynapse(segment1, cell2, 0.5);
+
+ // Let some time pass
+ connections.startNewIteration();
+ connections.startNewIteration();
+ connections.startNewIteration();
+
+ // Create a segment with 3 synapses.
+ Cell cell3 = connections.getCell(3);
DistalDendrite segment2 = connections.createSegment(cell42);
- Set activeInput = Arrays.stream(new Cell[] { connections.getCell(1), connections.getCell(2) }).collect(Collectors.toCollection(LinkedHashSet::new));
-
- Activity retVal = connections.computeActivity(activeInput, 0.5, 2, 0.1, 1, true);
- assertEquals(1, retVal.activeSegments.size());
- assertEquals(segment1, retVal.activeSegments.get(0).segment);
-
+ connections.createSynapse(segment2, cell1, 0.5);
+ connections.createSynapse(segment2, cell2, 0.5);
+ connections.createSynapse(segment2, cell3, 0.5);
+ connections.startNewIteration();
+
+ // Give the first segment some activity.
+ connections.recordSegmentActivity(segment1);
+
+ // Create a new segment with 1 synapse.
DistalDendrite segment3 = connections.createSegment(cell42);
- assertTrue(segment2 == segment3);
+ connections.createSynapse(segment3, cell1, 0.5);
+
+ List segments = connections.getSegments(cell42);
+ assertEquals(2, segments.size());
+
+ // Verify first segment is there with same synapses.
+ Set expected = IntStream.range(1, 3).mapToObj(i -> connections.getCell(i)).collect(Collectors.toSet());
+ assertTrue(DeepEquals.deepEquals(expected,
+ connections.getSynapses(segments.get(0))
+ .stream()
+ .map(s -> s.getPresynapticCell())
+ .collect(Collectors.toSet())));
+
+ // Verify second segment has been replaced.
+ expected = IntStream.range(1, 2).mapToObj(i -> connections.getCell(i)).collect(Collectors.toSet());
+ System.out.println("expected = " + expected);
+ System.out.println("actual = " + connections.getSynapses(segments.get(1))
+ .stream()
+ .map(s -> s.getPresynapticCell())
+ .collect(Collectors.toSet()));
+
+ assertTrue(DeepEquals.deepEquals(expected,
+ connections.getSynapses(segments.get(1))
+ .stream()
+ .map(s -> s.getPresynapticCell())
+ .collect(Collectors.toSet())));
+
+ // Verify the flatIdxs were properly reused.
+ assertTrue(segment1.getIndex() < 2);
+ assertTrue(segment3.getIndex() < 2);
+ assertEquals(segment1, connections.segmentForFlatIdx(segment1.getIndex()));
+ assertEquals(segment3, connections.segmentForFlatIdx(segment3.getIndex()));
}
-
+
/**
- * Creates a segment, destroys it, and makes sure it got destroyed along
- * with all of its synapses.
+ * Creates a synapse over the synapses per segment limit, and verifies
+ * that the lowest permanence synapse is removed to make room for the new
+ * synapse.
*/
+ @Test
+ public void testSynapseReuse() {
+ Parameters retVal = Parameters.getTemporalDefaultParameters();
+ retVal.set(KEY.COLUMN_DIMENSIONS, new int[] { 32 });
+ retVal.set(KEY.CELLS_PER_COLUMN, 4);
+ retVal.set(KEY.MAX_SYNAPSES_PER_SEGMENT, 2);
+
+ Connections connections = new Connections();
+
+ retVal.apply(connections);
+ TemporalMemory.init(connections);
+
+ Cell cell10 = connections.getCell(10);
+ DistalDendrite segment1 = connections.createSegment(cell10);
+ Synapse synapse1 = connections.createSynapse(segment1, connections.getCell(50), 0.34);
+ Synapse synapse2 = connections.createSynapse(segment1, connections.getCell(51), 0.48);
+
+ assertTrue(DeepEquals.deepEquals(
+ Arrays.asList(synapse1, synapse2), connections.getSynapses(segment1)));
+
+ // Add an additional synapse to force it over the limit of num synapses
+ // per segment.
+ connections.createSynapse(segment1, connections.getCell(52), .52);
+
+ // Ensure lower permanence synapse was removed.
+ Set expected = IntStream.range(51, 53).mapToObj(i -> connections.getCell(i)).collect(Collectors.toSet());
+ assertTrue(DeepEquals.deepEquals(expected,
+ connections.getSynapses(segment1)
+ .stream()
+ .map(s -> s.getPresynapticCell())
+ .collect(Collectors.toSet())));
+ }
+
@Test
public void testDestroySegment() {
- Parameters p = Parameters.getTemporalDefaultParameters();
- p.set(KEY.COLUMN_DIMENSIONS, new int[] { 32 });
- p.set(KEY.CELLS_PER_COLUMN, 32);
+ Parameters retVal = Parameters.getTemporalDefaultParameters();
+ retVal.set(KEY.COLUMN_DIMENSIONS, new int[] { 32 });
+ retVal.set(KEY.CELLS_PER_COLUMN, 4);
Connections connections = new Connections();
-
- p.apply(connections);
+
+ retVal.apply(connections);
TemporalMemory.init(connections);
connections.createSegment(connections.getCell(10));
@@ -135,14 +236,13 @@ public void testDestroySegment() {
assertEquals(3, connections.numSegments());
assertEquals(0, connections.numSynapses());
- Connections c = connections;
- Set activeInput = Arrays.stream(
- new Cell[] { c.getCell(80), c.getCell(81), c.getCell(82) })
- .collect(Collectors.toCollection(LinkedHashSet::new));
+ Activity activity = connections.computeActivity(
+ IntStream.rangeClosed(80, 82)
+ .mapToObj(i -> connections.getCell(i)).collect(Collectors.toList()),
+ 0.5D);
- Activity activity = connections.computeActivity(activeInput, 0.5, 2, 0.1, 1, true);
- assertEquals(0, activity.activeSegments.size());
- assertEquals(0, activity.matchingSegments.size());
+ assertEquals(0, activity.numActiveConnected[segment2.getIndex()]);
+ assertEquals(0, activity.numActivePotential[segment2.getIndex()]);
}
/**
@@ -151,15 +251,17 @@ public void testDestroySegment() {
*/
@Test
public void testDestroySynapse() {
- Parameters p = Parameters.getTemporalDefaultParameters();
- p.set(KEY.COLUMN_DIMENSIONS, new int[] { 32 });
- p.set(KEY.CELLS_PER_COLUMN, 32);
+ Parameters retVal = Parameters.getTemporalDefaultParameters();
+ retVal.set(KEY.COLUMN_DIMENSIONS, new int[] { 32 });
+ retVal.set(KEY.CELLS_PER_COLUMN, 4);
Connections connections = new Connections();
- p.apply(connections);
+
+ retVal.apply(connections);
TemporalMemory.init(connections);
- DistalDendrite segment = connections.createSegment(connections.getCell(20));
+ Cell cell20 = connections.getCell(20);
+ DistalDendrite segment = connections.createSegment(cell20);
Synapse synapse1 = connections.createSynapse(segment, connections.getCell(80), 0.85);
Synapse synapse2 = connections.createSynapse(segment, connections.getCell(81), 0.85);
Synapse synapse3 = connections.createSynapse(segment, connections.getCell(82), 0.15);
@@ -169,17 +271,15 @@ public void testDestroySynapse() {
connections.destroySynapse(synapse2);
assertEquals(2, connections.numSynapses());
- List expected = new ArrayList<>();
- expected.add(synapse1);expected.add(synapse3);
- assertEquals(expected, connections.unDestroyedSynapsesForSegment(segment));
+ assertEquals(Arrays.asList(synapse1, synapse3),
+ connections.getSynapses(segment));
- List actives = IntStream.of(80, 81, 82)
- .mapToObj(i -> connections.getCell(i))
- .collect(Collectors.toList());
- Activity act = connections.computeActivity(actives, 0.5, 2, 0.0, 1, true);
- assertEquals(0, act.activeSegments.size());
- assertEquals(1, act.matchingSegments.size());
- assertEquals(2, act.matchingSegments.get(0).overlap);
+ Activity activity = connections.computeActivity(
+ IntStream.rangeClosed(80, 82).mapToObj(i -> connections.getCell(i)).collect(Collectors.toList()),
+ 0.5D);
+
+ assertEquals(1, activity.numActiveConnected[segment.getIndex()]);
+ assertEquals(2, activity.numActivePotential[segment.getIndex()]);
}
/**
@@ -218,9 +318,9 @@ public void testPathsNotInvalidatedByOtherDestroys() {
connections.destroySegment(segment1);
List l234 = Arrays.stream(new Synapse[] { synapse2, synapse3, synapse4 }).collect(Collectors.toList());
- assertEquals(connections.unDestroyedSynapsesForSegment(segment3), l234);
+ assertEquals(connections.getSynapses(segment3), l234);
connections.destroySegment(segment5);
- assertEquals(connections.unDestroyedSynapsesForSegment(segment3), l234);
+ assertEquals(connections.getSynapses(segment3), l234);
assertEquals(cell203, synapse3.getPresynapticCell());
}
@@ -287,7 +387,7 @@ public void testReuseSegmentWithDestroyedSynapses() {
DistalDendrite reincarnated = connections.createSegment(connections.getCell(11));
assertEquals(0, connections.numSynapses(reincarnated));
- assertEquals(0, connections.unDestroyedSynapsesForSegment(reincarnated).size());
+ assertEquals(0, connections.getSynapses(reincarnated).size());
}
/**
@@ -318,8 +418,8 @@ public void testDestroySegmentsThenReachLimit() {
assertEquals(1, connections.numSegments());
connections.createSegment(connections.getCell(11));
assertEquals(2, connections.numSegments());
- DistalDendrite segment3 = connections.createSegment(connections.getCell(11));
- assertTrue(segment3.getIndex() < 2);
+ connections.createSegment(connections.getCell(11));
+ assertEquals(2, connections.numSegments(connections.getCell(11)));
assertEquals(2, connections.numSegments());
}
@@ -353,8 +453,7 @@ public void testDestroySynapsesThenReachLimit() {
assertEquals(1, connections.numSynapses());
connections.createSynapse(segment, connections.getCell(202), .90);
assertEquals(2, connections.numSynapses());
- Synapse synapse3 = connections.createSynapse(segment, connections.getCell(203), .8);
- assertTrue(synapse3.getIndex() < 2);
+ connections.createSynapse(segment, connections.getCell(203), .8);
assertEquals(2, connections.numSynapses());
}
@@ -381,8 +480,7 @@ public void testReachSegmentLimitMultipleTimes() {
assertEquals(2, connections.numSynapses());
connections.createSynapse(segment, connections.getCell(203), .8);
assertEquals(2, connections.numSynapses());
- Synapse synapse = connections.createSynapse(segment, connections.getCell(204), .8);
- assertTrue(synapse.getIndex() < 2);
+ connections.createSynapse(segment, connections.getCell(204), .8);
assertEquals(2, connections.numSynapses());
}
@@ -409,52 +507,28 @@ public void testComputeActivity() {
connections.createSynapse(segment1a, connections.getCell(150), .85);
connections.createSynapse(segment1a, connections.getCell(151), .15);
- // Cell with 2 segments.
+ // Cell with 1 segment.
// Segment with:
- // - 1 connected synapse: active
- // - 2 matching synapses
+ // - 2 connected synapse: 2 active
+ // - 3 matching synapses: 3 active
DistalDendrite segment2a = connections.createSegment(connections.getCell(20));
connections.createSynapse(segment2a, connections.getCell(80), .85);
connections.createSynapse(segment2a, connections.getCell(81), .85);
Synapse synapse = connections.createSynapse(segment2a, connections.getCell(82), .85);
synapse.setPermanence(null, 0.15);
- // Segment with:
- // - 2 connected synapses: 1 active, 1 inactive
- // - 3 matching synapses: 2 active, 1 inactive
- // - 1 non-matching synapse: 1 active
- DistalDendrite segment2b = connections.createSegment(connections.getCell(20));
- connections.createSynapse(segment2b, connections.getCell(50), .85);
- connections.createSynapse(segment2b, connections.getCell(51), .85);
- connections.createSynapse(segment2b, connections.getCell(52), .15);
- connections.createSynapse(segment2b, connections.getCell(53), .05);
-
- // Cell with 1 segment.
- // Segment with:
- // - 1 non-matching synapse: 1 active
- DistalDendrite segment3a = connections.createSegment(connections.getCell(30));
- connections.createSynapse(segment3a, connections.getCell(53), .05);
-
Connections c = connections;
List inputVec = IntStream.of(50, 52, 53, 80, 81, 82, 150, 151)
.mapToObj(i -> c.getCell(i))
.collect(Collectors.toList());
- Activity activity = c.computeActivity(inputVec, .5, 2, .1, 1, true);
- List active = activity.activeSegments;
- List matching = activity.matchingSegments;
-
- assertEquals(1, active.size());
- assertEquals(segment2a, active.get(0).segment);
- assertEquals(2, active.get(0).overlap);
-
- assertEquals(3, matching.size());
- assertEquals(segment1a, matching.get(0).segment);
- assertEquals(2, matching.get(0).overlap);
- assertEquals(segment2a, matching.get(1).segment);
- assertEquals(3, matching.get(1).overlap);
- assertEquals(segment2b, matching.get(2).segment);
- assertEquals(2, matching.get(2).overlap);
+ Activity activity = c.computeActivity(inputVec, .5);
+ assertEquals(1, activity.numActiveConnected[segment1a.getIndex()]);
+ assertEquals(2, activity.numActivePotential[segment1a.getIndex()]);
+
+ assertEquals(2, activity.numActiveConnected[segment2a.getIndex()]);
+ assertEquals(3, activity.numActivePotential[segment2a.getIndex()]);
+
}
@Test
@@ -589,7 +663,7 @@ public void testGetPrintString() {
TemporalMemory.init(con);
String output = con.getPrintString();
- assertEquals(1403, output.length());
+ assertTrue(output.length() > 1000);
Set fieldSet = Parameters.getEncoderDefaultParameters().keys().stream().
map(k -> k.getFieldName()).collect(Collectors.toCollection(LinkedHashSet::new));
@@ -692,5 +766,4 @@ public static Parameters getParameters() {
return parameters;
}
-
}
diff --git a/src/test/java/org/numenta/nupic/model/DistalDendriteTest.java b/src/test/java/org/numenta/nupic/model/DistalDendriteTest.java
index fb68025a..9d5ab019 100644
--- a/src/test/java/org/numenta/nupic/model/DistalDendriteTest.java
+++ b/src/test/java/org/numenta/nupic/model/DistalDendriteTest.java
@@ -26,7 +26,6 @@
import java.util.Set;
import org.junit.Test;
-import org.numenta.nupic.Connections;
import org.numenta.nupic.Parameters;
import org.numenta.nupic.Parameters.KEY;
import org.numenta.nupic.algorithms.TemporalMemory;
diff --git a/src/test/java/org/numenta/nupic/model/PoolTest.java b/src/test/java/org/numenta/nupic/model/PoolTest.java
index a35a72a7..bf16d6f1 100644
--- a/src/test/java/org/numenta/nupic/model/PoolTest.java
+++ b/src/test/java/org/numenta/nupic/model/PoolTest.java
@@ -26,7 +26,6 @@
import java.util.Arrays;
import org.junit.Test;
-import org.numenta.nupic.Connections;
import org.numenta.nupic.util.ArrayUtils;
import gnu.trove.map.TIntObjectMap;
diff --git a/src/test/java/org/numenta/nupic/SDRTest.java b/src/test/java/org/numenta/nupic/model/SDRTest.java
similarity index 97%
rename from src/test/java/org/numenta/nupic/SDRTest.java
rename to src/test/java/org/numenta/nupic/model/SDRTest.java
index 22b5b6ba..3ddb5da9 100644
--- a/src/test/java/org/numenta/nupic/SDRTest.java
+++ b/src/test/java/org/numenta/nupic/model/SDRTest.java
@@ -1,4 +1,4 @@
-package org.numenta.nupic;
+package org.numenta.nupic.model;
import static org.junit.Assert.assertFalse;
import static org.junit.Assert.assertTrue;
@@ -12,6 +12,8 @@
import org.junit.Test;
import org.numenta.nupic.algorithms.TemporalMemory;
import org.numenta.nupic.model.Cell;
+import org.numenta.nupic.model.Connections;
+import org.numenta.nupic.model.SDR;
public class SDRTest {
diff --git a/src/test/java/org/numenta/nupic/monitor/mixin/MetricsTraceTest.java b/src/test/java/org/numenta/nupic/monitor/mixin/MetricsTraceTest.java
index f58061cb..c33c0b09 100644
--- a/src/test/java/org/numenta/nupic/monitor/mixin/MetricsTraceTest.java
+++ b/src/test/java/org/numenta/nupic/monitor/mixin/MetricsTraceTest.java
@@ -6,9 +6,9 @@
import java.util.Arrays;
import org.junit.Test;
-import org.numenta.nupic.Connections;
import org.numenta.nupic.Parameters;
import org.numenta.nupic.algorithms.TemporalMemory;
+import org.numenta.nupic.model.Connections;
import org.numenta.nupic.monitor.MonitoredTemporalMemory;
diff --git a/src/test/java/org/numenta/nupic/monitor/mixin/MonitoredTemporalMemoryTest.java b/src/test/java/org/numenta/nupic/monitor/mixin/MonitoredTemporalMemoryTest.java
index b6f8c09c..b909c08b 100644
--- a/src/test/java/org/numenta/nupic/monitor/mixin/MonitoredTemporalMemoryTest.java
+++ b/src/test/java/org/numenta/nupic/monitor/mixin/MonitoredTemporalMemoryTest.java
@@ -7,13 +7,13 @@
import java.util.stream.Stream;
import org.junit.Test;
-import org.numenta.nupic.ComputeCycle;
-import org.numenta.nupic.Connections;
import org.numenta.nupic.Parameters;
import org.numenta.nupic.Parameters.KEY;
import org.numenta.nupic.algorithms.TemporalMemory;
import org.numenta.nupic.model.Cell;
+import org.numenta.nupic.model.ComputeCycle;
import org.numenta.nupic.model.DistalDendrite;
+import org.numenta.nupic.model.Connections;
import org.numenta.nupic.monitor.MonitoredTemporalMemory;
import org.numenta.nupic.util.UniversalRandom;
diff --git a/src/test/java/org/numenta/nupic/network/AlgorithmDeterminacyTest.java b/src/test/java/org/numenta/nupic/network/AlgorithmDeterminacyTest.java
index 02a1e1d3..f239651b 100644
--- a/src/test/java/org/numenta/nupic/network/AlgorithmDeterminacyTest.java
+++ b/src/test/java/org/numenta/nupic/network/AlgorithmDeterminacyTest.java
@@ -30,16 +30,16 @@
import org.junit.AfterClass;
import org.junit.Test;
-import org.numenta.nupic.ComputeCycle;
-import org.numenta.nupic.Connections;
import org.numenta.nupic.Parameters;
import org.numenta.nupic.Parameters.KEY;
-import org.numenta.nupic.SDR;
import org.numenta.nupic.algorithms.TemporalMemory;
import org.numenta.nupic.model.Cell;
import org.numenta.nupic.model.Column;
+import org.numenta.nupic.model.ComputeCycle;
import org.numenta.nupic.model.DistalDendrite;
+import org.numenta.nupic.model.Connections;
import org.numenta.nupic.model.ProximalDendrite;
+import org.numenta.nupic.model.SDR;
import org.numenta.nupic.model.Segment;
import org.numenta.nupic.network.sensor.ObservableSensor;
import org.numenta.nupic.network.sensor.Publisher;
@@ -269,24 +269,24 @@ public void testModelClasses() {
//Test Segment equality
Column column1 = new Column(2, 0);
Cell cell1 = new Cell(column1, 0);
- Segment s1 = new DistalDendrite(cell1, 0);
+ Segment s1 = new DistalDendrite(cell1, 0, 1, 0);
assertTrue(s1.equals(s1)); // test ==
assertFalse(s1.equals(null));
- Segment s2 = new DistalDendrite(cell1, 0);
+ Segment s2 = new DistalDendrite(cell1, 0, 1, 0);
assertTrue(s1.equals(s2));
Cell cell2 = new Cell(column1, 0);
- Segment s3 = new DistalDendrite(cell2, 0);
+ Segment s3 = new DistalDendrite(cell2, 0, 1, 0);
assertTrue(s1.equals(s3));
//Segment's Cell has different index
Cell cell3 = new Cell(column1, 1);
- Segment s4 = new DistalDendrite(cell3, 0);
+ Segment s4 = new DistalDendrite(cell3, 0, 1, 0);
assertFalse(s1.equals(s4));
//Segment has different index
- Segment s5 = new DistalDendrite(cell3, 1);
+ Segment s5 = new DistalDendrite(cell3, 1, 1, 0);
assertFalse(s4.equals(s5));
assertTrue(s5.toString().equals("1"));
assertEquals(-1, s4.compareTo(s5));
diff --git a/src/test/java/org/numenta/nupic/network/LayerTest.java b/src/test/java/org/numenta/nupic/network/LayerTest.java
index 1ba9aee8..80436dea 100644
--- a/src/test/java/org/numenta/nupic/network/LayerTest.java
+++ b/src/test/java/org/numenta/nupic/network/LayerTest.java
@@ -41,7 +41,6 @@
import org.junit.Test;
import org.numenta.nupic.Parameters;
import org.numenta.nupic.Parameters.KEY;
-import org.numenta.nupic.SDR;
import org.numenta.nupic.algorithms.Anomaly;
import org.numenta.nupic.algorithms.Anomaly.Mode;
import org.numenta.nupic.algorithms.CLAClassifier;
@@ -49,6 +48,7 @@
import org.numenta.nupic.algorithms.TemporalMemory;
import org.numenta.nupic.datagen.ResourceLocator;
import org.numenta.nupic.encoders.MultiEncoder;
+import org.numenta.nupic.model.SDR;
import org.numenta.nupic.network.Layer.FunctionFactory;
import org.numenta.nupic.network.sensor.FileSensor;
import org.numenta.nupic.network.sensor.HTMSensor;
diff --git a/src/test/java/org/numenta/nupic/network/ManualInputTest.java b/src/test/java/org/numenta/nupic/network/ManualInputTest.java
index a0f875b2..341fbbe5 100644
--- a/src/test/java/org/numenta/nupic/network/ManualInputTest.java
+++ b/src/test/java/org/numenta/nupic/network/ManualInputTest.java
@@ -10,10 +10,10 @@
import java.util.Set;
import org.junit.Test;
-import org.numenta.nupic.ComputeCycle;
import org.numenta.nupic.algorithms.Classification;
import org.numenta.nupic.model.Cell;
import org.numenta.nupic.model.Column;
+import org.numenta.nupic.model.ComputeCycle;
import org.numenta.nupic.util.NamedTuple;
diff --git a/src/test/java/org/numenta/nupic/network/NetworkConsistencyTest.java b/src/test/java/org/numenta/nupic/network/NetworkConsistencyTest.java
index 6a2149a9..a07290b0 100644
--- a/src/test/java/org/numenta/nupic/network/NetworkConsistencyTest.java
+++ b/src/test/java/org/numenta/nupic/network/NetworkConsistencyTest.java
@@ -14,25 +14,25 @@
import java.util.Set;
import org.junit.AfterClass;
-import org.junit.Ignore;
import org.junit.Test;
-import org.numenta.nupic.ComputeCycle;
-import org.numenta.nupic.Connections;
import org.numenta.nupic.Parameters;
import org.numenta.nupic.Parameters.KEY;
-import org.numenta.nupic.SDR;
import org.numenta.nupic.algorithms.Anomaly;
import org.numenta.nupic.algorithms.Anomaly.Mode;
import org.numenta.nupic.algorithms.SpatialPooler;
import org.numenta.nupic.algorithms.TemporalMemory;
import org.numenta.nupic.encoders.ScalarEncoder;
import org.numenta.nupic.model.Cell;
+import org.numenta.nupic.model.ComputeCycle;
+import org.numenta.nupic.model.Connections;
+import org.numenta.nupic.model.SDR;
import org.numenta.nupic.network.sensor.ObservableSensor;
import org.numenta.nupic.network.sensor.Publisher;
import org.numenta.nupic.network.sensor.Sensor;
import org.numenta.nupic.network.sensor.SensorParams;
import org.numenta.nupic.util.ArrayUtils;
import org.numenta.nupic.util.FastRandom;
+import org.numenta.nupic.util.UniversalRandom;
import com.cedarsoftware.util.DeepEquals;
@@ -60,7 +60,7 @@ public class NetworkConsistencyTest {
private static boolean doPrintout = false;
- private static final int SAMPLE_WEEK = new FastRandom().nextInt(125);
+ private static final int SAMPLE_WEEK = new UniversalRandom(42).nextInt(125);
@AfterClass
public static void compare() {
@@ -135,7 +135,7 @@ public void testNetworkAPI() {
/**
* Rudimentary test of the anomaly computation.
*/
- @Ignore
+ @Test
public void testComputeAnomaly_4of6() {
Map params = new HashMap<>();
params.put(KEY_MODE, Mode.PURE);
@@ -147,7 +147,7 @@ public void testComputeAnomaly_4of6() {
/**
* Rudimentary test of the anomaly computation.
*/
- @Ignore
+ @Test
public void testComputeAnomaly_5of7() {
Map params = new HashMap<>();
params.put(KEY_MODE, Mode.PURE);
diff --git a/src/test/java/org/numenta/nupic/network/NetworkTest.java b/src/test/java/org/numenta/nupic/network/NetworkTest.java
index 0c29dc98..0f4d4026 100644
--- a/src/test/java/org/numenta/nupic/network/NetworkTest.java
+++ b/src/test/java/org/numenta/nupic/network/NetworkTest.java
@@ -38,7 +38,6 @@
import java.util.stream.Stream;
import org.junit.Test;
-import org.numenta.nupic.Connections;
import org.numenta.nupic.Parameters;
import org.numenta.nupic.Parameters.KEY;
import org.numenta.nupic.algorithms.Anomaly;
@@ -47,6 +46,7 @@
import org.numenta.nupic.algorithms.TemporalMemory;
import org.numenta.nupic.datagen.ResourceLocator;
import org.numenta.nupic.encoders.MultiEncoder;
+import org.numenta.nupic.model.Connections;
import org.numenta.nupic.network.sensor.FileSensor;
import org.numenta.nupic.network.sensor.HTMSensor;
import org.numenta.nupic.network.sensor.ObservableSensor;
@@ -679,12 +679,15 @@ public void testFluentBuildSemantics() {
public void testNetworkComputeWithNoSensor() {
Parameters p = NetworkTestHarness.getParameters();
p = p.union(NetworkTestHarness.getDayDemoTestEncoderParams());
+ p.set(KEY.GLOBAL_INHIBITION, true);
p.set(KEY.COLUMN_DIMENSIONS, new int[] { 30 });
- p.set(KEY.SYN_PERM_INACTIVE_DEC, 0.1);
+ p.set(KEY.SYN_PERM_INACTIVE_DEC, 0.008);
p.set(KEY.SYN_PERM_ACTIVE_INC, 0.1);
p.set(KEY.SYN_PERM_TRIM_THRESHOLD, 0.05);
- p.set(KEY.SYN_PERM_CONNECTED, 0.4);
- p.set(KEY.MAX_BOOST, 10.0);
+ p.set(KEY.SYN_PERM_CONNECTED, 0.1);
+ p.set(KEY.PERMANENCE_INCREMENT, 0.10);
+ p.set(KEY.PERMANENCE_DECREMENT, 0.10);
+ p.set(KEY.MAX_BOOST, 1.0);
p.set(KEY.DUTY_CYCLE_PERIOD, 7);
p.set(KEY.RANDOM, new MersenneTwister(42));
@@ -714,8 +717,12 @@ public void testNetworkComputeWithNoSensor() {
@Override public void onError(Throwable e) { e.printStackTrace(); }
@Override public void onNext(Inference i) {
// UNCOMMENT TO VIEW STABILIZATION OF PREDICTED FIELDS
-// System.out.println("Day: " + r1.getInput() + " - predictions: " + Arrays.toString(i.getPreviousPrediction()) +
-// " - " + Arrays.toString(i.getSparseActives()) + " - " +
+// Set| prevPred = i.getPreviousPredictiveCells();
+// if(prevPred == null) {
+// prevPred = Collections.emptySet();
+// }
+// System.out.println("Day: " + r1.getInput() + " - predictions: " + Arrays.toString(SDR.cellsAsColumnIndices(prevPred, 6)) +
+// " - " + Arrays.toString(i.getFeedForwardSparseActives()) + " - " +
// ((int)Math.rint(((Number)i.getClassification("dayOfWeek").getMostProbableValue(1)).doubleValue())));
}
});
diff --git a/src/test/java/org/numenta/nupic/network/PersistenceAPITest.java b/src/test/java/org/numenta/nupic/network/PersistenceAPITest.java
index 829e0a2f..4dc7855b 100644
--- a/src/test/java/org/numenta/nupic/network/PersistenceAPITest.java
+++ b/src/test/java/org/numenta/nupic/network/PersistenceAPITest.java
@@ -49,11 +49,9 @@
import org.junit.AfterClass;
import org.junit.Test;
-import org.numenta.nupic.Connections;
import org.numenta.nupic.FieldMetaType;
import org.numenta.nupic.Parameters;
import org.numenta.nupic.Parameters.KEY;
-import org.numenta.nupic.SDR;
import org.numenta.nupic.algorithms.Anomaly;
import org.numenta.nupic.algorithms.Anomaly.Mode;
import org.numenta.nupic.algorithms.AnomalyLikelihood;
@@ -68,6 +66,8 @@
import org.numenta.nupic.encoders.DateEncoder;
import org.numenta.nupic.encoders.MultiEncoder;
import org.numenta.nupic.model.Cell;
+import org.numenta.nupic.model.Connections;
+import org.numenta.nupic.model.SDR;
import org.numenta.nupic.network.Persistence.PersistenceAccess;
import org.numenta.nupic.network.sensor.FileSensor;
import org.numenta.nupic.network.sensor.HTMSensor;
diff --git a/src/test/java/org/numenta/nupic/network/PlaygroundTest.java b/src/test/java/org/numenta/nupic/network/PlaygroundTest.java
index fa114456..797f9b31 100644
--- a/src/test/java/org/numenta/nupic/network/PlaygroundTest.java
+++ b/src/test/java/org/numenta/nupic/network/PlaygroundTest.java
@@ -32,10 +32,10 @@
import org.junit.Ignore;
import org.numenta.nupic.Parameters;
import org.numenta.nupic.Parameters.KEY;
-import org.numenta.nupic.SDR;
import org.numenta.nupic.algorithms.Anomaly;
import org.numenta.nupic.algorithms.Classification;
import org.numenta.nupic.algorithms.SpatialPooler;
+import org.numenta.nupic.model.SDR;
import org.numenta.nupic.algorithms.TemporalMemory;
import org.numenta.nupic.network.sensor.ObservableSensor;
import org.numenta.nupic.network.sensor.Publisher;
diff --git a/src/test/java/org/numenta/nupic/util/GroupByTest.java b/src/test/java/org/numenta/nupic/util/GroupByTest.java
index d88330af..becb9417 100644
--- a/src/test/java/org/numenta/nupic/util/GroupByTest.java
+++ b/src/test/java/org/numenta/nupic/util/GroupByTest.java
@@ -88,9 +88,9 @@ public void testObjectGroup() {
assertEquals(12, c1.getCell(3).getIndex());
assertEquals(16, c1.getCell(7).getIndex());
- DistalDendrite dd0 = new DistalDendrite(c0.getCell(7), 0);
- DistalDendrite dd1 = new DistalDendrite(c1.getCell(3 /* Col 1's Cells start at 9 */), 1);
- DistalDendrite dd2 = new DistalDendrite(c1.getCell(7/* Col 1's Cells start at 9 */), 2);
+ DistalDendrite dd0 = new DistalDendrite(c0.getCell(7), 0, 0, 0);
+ DistalDendrite dd1 = new DistalDendrite(c1.getCell(3 /* Col 1's Cells start at 9 */), 1, 0, 1);
+ DistalDendrite dd2 = new DistalDendrite(c1.getCell(7/* Col 1's Cells start at 9 */), 2, 0, 2);
List l = Arrays.asList(
new DistalDendrite[] { dd0, dd1, dd2 });
diff --git a/src/test/java/org/numenta/nupic/util/SparseBinaryMatrixTest.java b/src/test/java/org/numenta/nupic/util/SparseBinaryMatrixTest.java
index 46568935..86fcd05b 100644
--- a/src/test/java/org/numenta/nupic/util/SparseBinaryMatrixTest.java
+++ b/src/test/java/org/numenta/nupic/util/SparseBinaryMatrixTest.java
@@ -32,10 +32,10 @@
import java.util.Random;
import org.junit.Test;
-import org.numenta.nupic.Connections;
import org.numenta.nupic.Parameters;
import org.numenta.nupic.Parameters.KEY;
import org.numenta.nupic.algorithms.SpatialPooler;
+import org.numenta.nupic.model.Connections;
public class SparseBinaryMatrixTest {
diff --git a/src/test/resources/TravelTime_sp_output.txt b/src/test/resources/TravelTime_sp_output.txt
new file mode 100644
index 00000000..647a22bb
--- /dev/null
+++ b/src/test/resources/TravelTime_sp_output.txt
@@ -0,0 +1,2500 @@
+[717, 737, 739, 745, 758, 782, 793, 798, 805, 812, 833, 841, 846, 857, 1482, 1515, 1536, 1577, 1578, 1600, 1608, 1612, 1642, 1644, 1645, 1646, 1647, 1648, 1649, 1655, 1661, 1663, 1667, 1669, 1677, 1683, 1688, 1706, 1710, 1720]
+[717, 737, 739, 745, 758, 782, 793, 798, 805, 812, 833, 841, 846, 857, 1482, 1515, 1536, 1577, 1578, 1600, 1608, 1612, 1642, 1644, 1645, 1646, 1647, 1648, 1649, 1655, 1661, 1663, 1667, 1669, 1677, 1683, 1688, 1706, 1710, 1720]
+[717, 737, 739, 745, 758, 782, 793, 798, 805, 812, 833, 841, 846, 857, 1482, 1515, 1578, 1600, 1608, 1634, 1642, 1644, 1645, 1647, 1648, 1649, 1652, 1655, 1661, 1662, 1667, 1669, 1676, 1677, 1683, 1688, 1706, 1710, 1719, 1720]
+[717, 737, 739, 745, 758, 782, 793, 798, 805, 812, 833, 841, 846, 857, 1482, 1515, 1578, 1600, 1608, 1634, 1642, 1644, 1645, 1647, 1648, 1649, 1652, 1655, 1661, 1662, 1667, 1669, 1676, 1677, 1683, 1688, 1706, 1710, 1719, 1720]
+[717, 737, 739, 745, 758, 782, 793, 798, 805, 812, 833, 841, 846, 857, 1482, 1578, 1600, 1608, 1634, 1642, 1644, 1645, 1646, 1647, 1649, 1653, 1655, 1661, 1662, 1667, 1677, 1683, 1688, 1699, 1706, 1710, 1719, 1720, 1819, 1828]
+[717, 737, 739, 745, 758, 782, 793, 798, 805, 812, 833, 841, 846, 857, 1482, 1578, 1600, 1608, 1634, 1642, 1644, 1645, 1646, 1647, 1649, 1653, 1655, 1661, 1662, 1667, 1677, 1683, 1688, 1699, 1706, 1710, 1719, 1720, 1819, 1828]
+[717, 737, 739, 745, 758, 782, 793, 798, 805, 812, 833, 841, 846, 857, 1578, 1600, 1608, 1634, 1642, 1644, 1645, 1646, 1647, 1649, 1661, 1662, 1667, 1683, 1688, 1699, 1706, 1710, 1719, 1720, 1733, 1737, 1740, 1792, 1819, 1828]
+[717, 737, 739, 745, 758, 782, 793, 798, 805, 812, 833, 841, 846, 857, 1578, 1600, 1608, 1634, 1642, 1644, 1645, 1646, 1647, 1649, 1661, 1662, 1667, 1683, 1688, 1699, 1706, 1710, 1719, 1720, 1733, 1737, 1740, 1792, 1819, 1828]
+[717, 737, 739, 745, 758, 782, 793, 798, 805, 812, 833, 841, 846, 857, 1578, 1600, 1608, 1634, 1642, 1644, 1645, 1661, 1682, 1683, 1688, 1706, 1710, 1713, 1719, 1720, 1733, 1734, 1737, 1740, 1741, 1757, 1792, 1804, 1819, 1828]
+[717, 737, 739, 745, 758, 782, 793, 798, 805, 812, 833, 841, 846, 857, 1578, 1600, 1608, 1634, 1642, 1644, 1645, 1661, 1682, 1683, 1688, 1706, 1710, 1713, 1719, 1720, 1733, 1734, 1737, 1740, 1741, 1757, 1792, 1804, 1819, 1828]
+[717, 737, 739, 745, 758, 782, 793, 798, 805, 812, 833, 841, 846, 857, 1578, 1600, 1608, 1634, 1642, 1644, 1645, 1661, 1682, 1683, 1688, 1706, 1710, 1713, 1719, 1720, 1733, 1734, 1737, 1740, 1741, 1757, 1792, 1804, 1819, 1828]
+[717, 737, 739, 745, 758, 782, 793, 798, 805, 812, 833, 841, 846, 857, 1578, 1600, 1634, 1642, 1644, 1645, 1661, 1683, 1706, 1710, 1713, 1719, 1720, 1733, 1737, 1740, 1741, 1748, 1755, 1757, 1769, 1792, 1804, 1818, 1819, 1828]
+[717, 737, 739, 745, 758, 782, 793, 798, 805, 812, 833, 841, 846, 857, 1578, 1600, 1634, 1642, 1644, 1645, 1661, 1683, 1706, 1710, 1713, 1719, 1720, 1733, 1737, 1740, 1741, 1748, 1755, 1757, 1769, 1792, 1804, 1818, 1819, 1828]
+[717, 737, 739, 745, 758, 782, 793, 798, 805, 812, 833, 841, 846, 857, 1578, 1600, 1634, 1642, 1644, 1645, 1661, 1683, 1706, 1710, 1713, 1719, 1720, 1733, 1737, 1740, 1741, 1748, 1755, 1757, 1769, 1792, 1804, 1818, 1819, 1828]
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