public void testZeroActiveColumns()
{
TemporalMemory tm = new TemporalMemory();
Connections cn = new Connections();
Parameters p = GetDefaultParameters();
p.Apply(cn);
TemporalMemory.Init(cn);
int[] previousActiveColumns = { 0 };
Cell cell4 = cn.GetCell(4);
DistalDendrite activeSegment = cn.CreateSegment(cell4);
cn.CreateSynapse(activeSegment, cn.GetCell(0), 0.5);
cn.CreateSynapse(activeSegment, cn.GetCell(1), 0.5);
cn.CreateSynapse(activeSegment, cn.GetCell(2), 0.5);
cn.CreateSynapse(activeSegment, cn.GetCell(3), 0.5);
ComputeCycle cc = tm.Compute(cn, previousActiveColumns, true);
Assert.IsFalse(cc.ActiveCells().Count == 0);
Assert.IsFalse(cc.WinnerCells().Count == 0);
Assert.IsFalse(cc.PredictiveCells().Count == 0);
int[] zeroColumns = new int[0];
ComputeCycle cc2 = tm.Compute(cn, zeroColumns, true);
Assert.IsTrue(cc2.ActiveCells().Count == 0);
Assert.IsTrue(cc2.WinnerCells().Count == 0);
Assert.IsTrue(cc2.PredictiveCells().Count == 0);
}
public void TestDestroyWeakSynapseOnActiveReinforce()
{
TemporalMemory tm = new TemporalMemory();
Connections cn = new Connections();
Parameters p = getDefaultParameters(null, KEY.INITIAL_PERMANENCE, 0.2);
p = getDefaultParameters(p, KEY.MAX_NEW_SYNAPSE_COUNT, 4);
p = getDefaultParameters(p, KEY.PREDICTED_SEGMENT_DECREMENT, 0.02);
p.apply(cn);
tm.Init(cn);
int[] previousActiveColumns = { 0 };
Cell[] previousActiveCells = { cn.GetCell(0), cn.GetCell(1), cn.GetCell(2), cn.GetCell(3) };
int[] activeColumns = { 2 };
Cell expectedActiveCell = cn.GetCell(5);
DistalDendrite activeSegment = cn.CreateDistalSegment(expectedActiveCell);
cn.CreateSynapse(activeSegment, previousActiveCells[0], 0.5);
cn.CreateSynapse(activeSegment, previousActiveCells[1], 0.5);
cn.CreateSynapse(activeSegment, previousActiveCells[2], 0.5);
// Weak Synapse
cn.CreateSynapse(activeSegment, previousActiveCells[3], 0.009);
tm.Compute(previousActiveColumns, true);
tm.Compute(activeColumns, true);
Assert.AreEqual(3, activeSegment.Synapses.Count);
}
public void testPredictedActiveCellsAreAlwaysWinners()
{
TemporalMemory tm = new TemporalMemory();
Connections cn = new Connections();
Parameters p = GetDefaultParameters();
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) };
List <Cell> expectedWinnerCells = new List <Cell>(cn.GetCellSet(new int[] { 4, 6 }));
DistalDendrite activeSegment1 = cn.CreateSegment(expectedWinnerCells[0]);
cn.CreateSynapse(activeSegment1, previousActiveCells[0], 0.5);
cn.CreateSynapse(activeSegment1, previousActiveCells[1], 0.5);
cn.CreateSynapse(activeSegment1, previousActiveCells[2], 0.5);
DistalDendrite activeSegment2 = cn.CreateSegment(expectedWinnerCells[1]);
cn.CreateSynapse(activeSegment2, previousActiveCells[0], 0.5);
cn.CreateSynapse(activeSegment2, previousActiveCells[1], 0.5);
cn.CreateSynapse(activeSegment2, previousActiveCells[2], 0.5);
ComputeCycle cc = tm.Compute(cn, previousActiveColumns, false); // learn=false
cc = tm.Compute(cn, activeColumns, false); // learn=false
Assert.IsTrue(cc.winnerCells.SetEquals(new HashSet <Cell>(expectedWinnerCells)));
}
public void testReinforcedCorrectlyActiveSegments()
{
TemporalMemory tm = new TemporalMemory();
Connections cn = new Connections();
Parameters p = GetDefaultParameters(null, Parameters.KEY.INITIAL_PERMANENCE, 0.2);
p = GetDefaultParameters(p, Parameters.KEY.MAX_NEW_SYNAPSE_COUNT, 4);
p = GetDefaultParameters(p, Parameters.KEY.PERMANENCE_DECREMENT, 0.08);
p = GetDefaultParameters(p, Parameters.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);
Synapse as1 = cn.CreateSynapse(activeSegment, previousActiveCells[0], 0.5);
Synapse as2 = cn.CreateSynapse(activeSegment, previousActiveCells[1], 0.5);
Synapse as3 = cn.CreateSynapse(activeSegment, previousActiveCells[2], 0.5);
Synapse is1 = cn.CreateSynapse(activeSegment, cn.GetCell(81), 0.5);
tm.Compute(cn, previousActiveColumns, true);
tm.Compute(cn, activeColumns, true);
Assert.AreEqual(0.6, as1.GetPermanence(), 0.1);
Assert.AreEqual(0.6, as2.GetPermanence(), 0.1);
Assert.AreEqual(0.6, as3.GetPermanence(), 0.1);
Assert.AreEqual(0.42, is1.GetPermanence(), 0.001);
}
public void testReinforcedSelectedMatchingSegmentInBurstingColumn()
{
TemporalMemory tm = new TemporalMemory();
Connections cn = new Connections();
Parameters p = GetDefaultParameters(null, Parameters.KEY.PERMANENCE_DECREMENT, 0.08);
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[] burstingCells = { cn.GetCell(4), cn.GetCell(5) };
DistalDendrite activeSegment = cn.CreateSegment(burstingCells[0]);
Synapse as1 = cn.CreateSynapse(activeSegment, previousActiveCells[0], 0.3);
Synapse as2 = cn.CreateSynapse(activeSegment, previousActiveCells[0], 0.3);
Synapse as3 = cn.CreateSynapse(activeSegment, previousActiveCells[0], 0.3);
Synapse is1 = cn.CreateSynapse(activeSegment, cn.GetCell(81), 0.3);
DistalDendrite otherMatchingSegment = cn.CreateSegment(burstingCells[1]);
cn.CreateSynapse(otherMatchingSegment, previousActiveCells[0], 0.3);
cn.CreateSynapse(otherMatchingSegment, previousActiveCells[1], 0.3);
cn.CreateSynapse(otherMatchingSegment, cn.GetCell(81), 0.3);
tm.Compute(cn, previousActiveColumns, true);
tm.Compute(cn, activeColumns, true);
Assert.AreEqual(0.4, as1.GetPermanence(), 0.01);
Assert.AreEqual(0.4, as2.GetPermanence(), 0.01);
Assert.AreEqual(0.4, as3.GetPermanence(), 0.01);
Assert.AreEqual(0.22, is1.GetPermanence(), 0.001);
}
public void TestNoChangeToNonSelectedMatchingSegmentsInBurstingColumn()
{
TemporalMemory tm = new TemporalMemory();
Connections cn = new Connections();
Parameters p = getDefaultParameters(null, KEY.PERMANENCE_DECREMENT, 0.08);
p.apply(cn);
tm.Init(cn);
int[] previousActiveColumns = { 0 };
int[] activeColumns = { 1 };
Cell[] previousActiveCells = { cn.GetCell(0), cn.GetCell(1), cn.GetCell(2), cn.GetCell(3) };
Cell[] burstingCells = { cn.GetCell(4), cn.GetCell(5) };
DistalDendrite selectedMatchingSegment = cn.CreateDistalSegment(burstingCells[0]);
cn.CreateSynapse(selectedMatchingSegment, previousActiveCells[0], 0.3);
cn.CreateSynapse(selectedMatchingSegment, previousActiveCells[1], 0.3);
cn.CreateSynapse(selectedMatchingSegment, previousActiveCells[2], 0.3);
cn.CreateSynapse(selectedMatchingSegment, cn.GetCell(81), 0.3);
DistalDendrite otherMatchingSegment = cn.CreateDistalSegment(burstingCells[1]);
Synapse as1 = cn.CreateSynapse(otherMatchingSegment, previousActiveCells[0], 0.3);
Synapse as2 = cn.CreateSynapse(otherMatchingSegment, previousActiveCells[1], 0.3);
Synapse is1 = cn.CreateSynapse(otherMatchingSegment, cn.GetCell(81), 0.3);
tm.Compute(previousActiveColumns, true);
tm.Compute(activeColumns, true);
Assert.AreEqual(0.3, as1.Permanence, 0.01);
Assert.AreEqual(0.3, as2.Permanence, 0.01);
Assert.AreEqual(0.3, is1.Permanence, 0.01);
}
public void TestDestroySegmentsWithTooFewSynapsesToBeMatching()
{
TemporalMemory tm = new TemporalMemory();
Connections cn = new Connections();
Parameters p = getDefaultParameters(null, KEY.INITIAL_PERMANENCE, .2);
p = getDefaultParameters(p, KEY.MAX_NEW_SYNAPSE_COUNT, 4);
p = getDefaultParameters(p, KEY.PREDICTED_SEGMENT_DECREMENT, 0.02);
p.apply(cn);
tm.Init(cn);
int[] prevActiveColumns = { 0 };
Cell[] prevActiveCells = { cn.GetCell(0), cn.GetCell(1), cn.GetCell(2), cn.GetCell(3) };
int[] activeColumns = { 2 };
Cell expectedActiveCell = cn.GetCell(5);
DistalDendrite matchingSegment = cn.CreateDistalSegment(cn.GetCell(5));
cn.CreateSynapse(matchingSegment, prevActiveCells[0], .015);
cn.CreateSynapse(matchingSegment, prevActiveCells[1], .015);
cn.CreateSynapse(matchingSegment, prevActiveCells[2], .015);
cn.CreateSynapse(matchingSegment, prevActiveCells[3], .015);
tm.Compute(prevActiveColumns, true);
tm.Compute(activeColumns, true);
Assert.AreEqual(0, cn.NumSegments(expectedActiveCell));
}
public void TestRecycleWeakestSynapseToMakeRoomForNewSynapse()
{
throw new AssertInconclusiveException("Not fixed.");
TemporalMemory tm = new TemporalMemory();
Connections cn = new Connections();
Parameters p = getDefaultParameters(null, KEY.CELLS_PER_COLUMN, 30);
p.Set(KEY.COLUMN_DIMENSIONS, new int[] { 100 });
//p.Set(KEY.COLUMN_DIMENSIONS, new int[] { 5 });
p = getDefaultParameters(p, KEY.MIN_THRESHOLD, 1);
p = getDefaultParameters(p, KEY.PERMANENCE_INCREMENT, 0.02);
p = getDefaultParameters(p, KEY.PERMANENCE_DECREMENT, 0.02);
p.Set(KEY.MAX_SYNAPSES_PER_SEGMENT, 3);
p.apply(cn);
tm.Init(cn);
Assert.AreEqual(3, cn.HtmConfig.MaxSynapsesPerSegment);
int[] prevActiveColumns = { 0, 1, 2 };
IList <Cell> prevWinnerCells = cn.GetCellSet(new int[] { 0, 1, 2 });
int[] activeColumns = { 4 };
DistalDendrite matchingSegment = cn.CreateDistalSegment(cn.GetCell(4));
cn.CreateSynapse(matchingSegment, cn.GetCell(81), 0.6);
// Weakest Synapse
cn.CreateSynapse(matchingSegment, cn.GetCell(0), 0.11);
ComputeCycle cc = tm.Compute(prevActiveColumns, true) as ComputeCycle;
Assert.IsTrue(prevWinnerCells.SequenceEqual(cc.WinnerCells));
tm.Compute(activeColumns, true);
//DD List<Synapse> synapses = cn.GetSynapses(matchingSegment);
List <Synapse> synapses = matchingSegment.Synapses;
Assert.AreEqual(3, synapses.Count);
//Set<Cell> presynapticCells = synapses.stream().map(s->s.getPresynapticCell()).collect(Collectors.toSet());
List <Cell> presynapticCells = new List <Cell>();
//DD foreach (var syn in cn.GetSynapses(matchingSegment))
foreach (var syn in matchingSegment.Synapses)
{
presynapticCells.Add(syn.GetPresynapticCell());
}
Assert.IsFalse(presynapticCells.Count(c => c.Index == 0) > 0);
//Assert.IsFalse(presynapticCells.stream().mapToInt(cell->cell.getIndex()).anyMatch(i->i == 0));
}
public void TestClear()
{
int[] input1 = { 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0 };
int[] input2 = { 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0 };
int[] input3 = { 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0 };
int[] input4 = { 0, 0, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 1, 1, 0 };
int[] input5 = { 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 1, 0 };
int[] input6 = { 0, 0, 1, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1 };
int[] input7 = { 0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0 };
int[][] inputs = { input1, input2, input3, input4, input5, input6, input7 };
Parameters p = GetParameters();
Connections con = new Connections();
p.Apply(con);
TemporalMemory tm = new TemporalMemory();
TemporalMemory.Init(con);
for (int x = 0; x < 602; x++)
{
foreach (int[] i in inputs)
{
tm.Compute(con, i.Where(n => n == 1).ToArray(), true);
}
}
Assert.IsFalse(!con.GetActiveCells().Any());
con.Clear();
Assert.IsTrue(!con.GetActiveCells().Any());
}
public void TestTemporalMemoryExplicit()
{
int[] input1 = new int[] { 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0 };
int[] input2 = new int[] { 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0 };
int[] input3 = new int[] { 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0 };
int[] input4 = new int[] { 0, 0, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 1, 1, 0 };
int[] input5 = new int[] { 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 1, 0 };
int[] input6 = new int[] { 0, 0, 1, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1 };
int[] input7 = new int[] { 0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0 };
int[][] inputs = { input1, input2, input3, input4, input5, input6, input7 };
Parameters p = GetParameters();
Connections con = new Connections();
p.Apply(con);
TemporalMemory tm = new TemporalMemory();
TemporalMemory.Init(con);
ComputeCycle cc = null;
for (int x = 0; x < 602; x++)
{
foreach (int[] i in inputs)
{
cc = tm.Compute(con, ArrayUtils.Where(i, ArrayUtils.WHERE_1), true);
}
}
TEST_AGGREGATION[TM_EXPL] = SDR.AsCellIndices(cc.activeCells);
}
public void testNoNewSegmentIfNotEnoughWinnerCells()
{
TemporalMemory tm = new TemporalMemory();
Connections cn = new Connections();
Parameters p = GetDefaultParameters(null, Parameters.KEY.MAX_NEW_SYNAPSE_COUNT, 3);
p.Apply(cn);
TemporalMemory.Init(cn);
int[] zeroColumns = { };
int[] activeColumns = { 0 };
tm.Compute(cn, zeroColumns, true);
tm.Compute(cn, activeColumns, true);
Assert.AreEqual(0, cn.GetNumSegments(), 0);
}
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);
tm.Init(cn);
// Use 1 cell per column so that we have easy control over the winner cells.
int[] previousActiveColumns = { 0, 1, 2, 3, 4 };
List <Cell> prevWinnerCells = new List <Cell>(new Cell[] { cn.GetCell(0), cn.GetCell(1), cn.GetCell(2), cn.GetCell(3), cn.GetCell(4) });
int[] activeColumns = { 5 };
DistalDendrite activeSegment = cn.CreateDistalSegment(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(previousActiveColumns, true) as ComputeCycle;
Assert.IsTrue(prevWinnerCells.SequenceEqual(cc.WinnerCells));
cc = tm.Compute(activeColumns, true) as ComputeCycle;
List <Cell> presynapticCells = new List <Cell>();
foreach (var syn in activeSegment.GetAllSynapses(cn))
{
presynapticCells.Add(syn.getPresynapticCell());
}
//= cn.getSynapses(activeSegment).stream()
//.map(s->s.getPresynapticCell())
//.collect(Collectors.toSet());
Assert.IsTrue(
presynapticCells.Count == 4 && (
(presynapticCells.Contains(cn.GetCell(0)) && presynapticCells.Contains(cn.GetCell(1)) && presynapticCells.Contains(cn.GetCell(2)) && presynapticCells.Contains(cn.GetCell(3))) ||
(presynapticCells.Contains(cn.GetCell(0)) && presynapticCells.Contains(cn.GetCell(1)) && presynapticCells.Contains(cn.GetCell(2)) && presynapticCells.Contains(cn.GetCell(4)))));
}
public void testActiveSegmentGrowSynapsesAccordingToPotentialOverlap()
{
TemporalMemory tm = new TemporalMemory();
Connections cn = new Connections();
Parameters p = GetDefaultParameters(null, Parameters.KEY.CELLS_PER_COLUMN, 1);
p = GetDefaultParameters(p, Parameters.KEY.MIN_THRESHOLD, 1);
p = GetDefaultParameters(p, Parameters.KEY.ACTIVATION_THRESHOLD, 2);
p = GetDefaultParameters(p, Parameters.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 };
HashSet <Cell> prevWinnerCells = new HashSet <Cell>(Arrays.AsList(0, 1, 2, 3, 4)
.Select(i => cn.GetCell(i))
.ToList());
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);
Assert.IsTrue(prevWinnerCells.SetEquals(cc.WinnerCells()));
cc = tm.Compute(cn, activeColumns, true);
HashSet <Cell> presynapticCells = new HashSet <Cell>(cn.GetSynapses(activeSegment)
.Select(s => s.GetPresynapticCell())
.ToList());
Assert.IsTrue(
presynapticCells.Count == 4 && (
!presynapticCells.Except(new List <Cell> {
cn.GetCell(0), cn.GetCell(1), cn.GetCell(2), cn.GetCell(3)
}).Any() ||
!presynapticCells.Except(new List <Cell> {
cn.GetCell(0), cn.GetCell(1), cn.GetCell(2), cn.GetCell(4)
}).Any()));
}
public void TestNewSegmentAddSynapsesToAllWinnerCells()
{
TemporalMemory tm = new TemporalMemory();
Connections cn = new Connections();
Parameters p = getDefaultParameters(null, KEY.MAX_NEW_SYNAPSE_COUNT, 4);
p.apply(cn);
tm.Init(cn);
int[] previousActiveColumns = { 0, 1, 2 };
int[] activeColumns = { 4 };
ComputeCycle cc = tm.Compute(previousActiveColumns, true) as ComputeCycle;
List <Cell> prevWinnerCells = new List <Cell>(cc.WinnerCells);
Assert.AreEqual(3, prevWinnerCells.Count);
cc = tm.Compute(activeColumns, true) as ComputeCycle;
List <Cell> winnerCells = new List <Cell>(cc.WinnerCells);
Assert.AreEqual(1, winnerCells.Count);
//DD
//List<DistalDendrite> segments = winnerCells[0].GetSegments(cn);
List <DistalDendrite> segments = winnerCells[0].DistalDendrites;
//List<DistalDendrite> segments = winnerCells[0].Segments;
Assert.AreEqual(1, segments.Count);
//List<Synapse> synapses = segments[0].GetAllSynapses(cn);
List <Synapse> synapses = segments[0].Synapses;
List <Cell> presynapticCells = new List <Cell>();
foreach (Synapse synapse in synapses)
{
Assert.AreEqual(0.21, synapse.Permanence, 0.01);
presynapticCells.Add(synapse.GetPresynapticCell());
}
presynapticCells.Sort();
Assert.IsTrue(prevWinnerCells.SequenceEqual(presynapticCells));
}
public void testNoChangeToMatchingSegmentsInPredictedActiveColumn()
{
TemporalMemory tm = new TemporalMemory();
Connections cn = new Connections();
Parameters p = GetDefaultParameters();
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 expectedActiveCell = cn.GetCell(4);
HashSet <Cell> expectedActiveCells = new HashSet <Cell> {
expectedActiveCell
}; // Stream.of(expectedActiveCell).collect(Collectors.toCollection(HashSet < Cell >::new));
Cell otherBurstingCell = cn.GetCell(5);
DistalDendrite activeSegment = cn.CreateSegment(expectedActiveCell);
cn.CreateSynapse(activeSegment, previousActiveCells[0], 0.5);
cn.CreateSynapse(activeSegment, previousActiveCells[1], 0.5);
cn.CreateSynapse(activeSegment, previousActiveCells[2], 0.5);
cn.CreateSynapse(activeSegment, previousActiveCells[3], 0.5);
DistalDendrite matchingSegmentOnSameCell = cn.CreateSegment(expectedActiveCell);
Synapse s1 = cn.CreateSynapse(matchingSegmentOnSameCell, previousActiveCells[0], 0.3);
Synapse s2 = cn.CreateSynapse(matchingSegmentOnSameCell, previousActiveCells[1], 0.3);
DistalDendrite matchingSegmentOnOtherCell = cn.CreateSegment(otherBurstingCell);
Synapse s3 = cn.CreateSynapse(matchingSegmentOnOtherCell, previousActiveCells[0], 0.3);
Synapse s4 = cn.CreateSynapse(matchingSegmentOnOtherCell, previousActiveCells[1], 0.3);
ComputeCycle cc = tm.Compute(cn, previousActiveColumns, true);
Assert.IsTrue(cc.PredictiveCells().SetEquals(expectedActiveCells));
tm.Compute(cn, activeColumns, true);
Assert.AreEqual(0.3, s1.GetPermanence(), 0.01);
Assert.AreEqual(0.3, s2.GetPermanence(), 0.01);
Assert.AreEqual(0.3, s3.GetPermanence(), 0.01);
Assert.AreEqual(0.3, s4.GetPermanence(), 0.01);
}
public void TestMatchingSegmentAddSynapsesToAllWinnerCells()
{
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.apply(cn);
tm.Init(cn);
int[] previousActiveColumns = { 0, 1 };
IList <Cell> prevWinnerCells = cn.GetCellSet(new int[] { 0, 1 });
int[] activeColumns = { 4 };
DistalDendrite matchingSegment = cn.CreateDistalSegment(cn.GetCell(4));
cn.CreateSynapse(matchingSegment, cn.GetCell(0), 0.5);
ComputeCycle cc = tm.Compute(previousActiveColumns, true) as ComputeCycle;
Assert.IsTrue(cc.WinnerCells.SequenceEqual(prevWinnerCells));
cc = tm.Compute(activeColumns, true) as ComputeCycle;
//DD List<Synapse> synapses = cn.GetSynapses(matchingSegment);
List <Synapse> synapses = matchingSegment.Synapses;
Assert.AreEqual(2, synapses.Count);
synapses.Sort();
foreach (Synapse synapse in synapses)
{
if (synapse.GetPresynapticCell().Index == 0)
{
continue;
}
Assert.AreEqual(0.21, synapse.Permanence, 0.01);
Assert.AreEqual(1, synapse.GetPresynapticCell().Index);
}
}
public void testConnectionsNeverChangeWhenLearningDisabled()
{
TemporalMemory tm = new TemporalMemory();
Connections cn = new Connections();
Parameters p = getDefaultParameters(null, KEY.MAX_NEW_SYNAPSE_COUNT, 4);
p = getDefaultParameters(p, KEY.PREDICTED_SEGMENT_DECREMENT, 0.02);
p = getDefaultParameters(p, KEY.INITIAL_PERMANENCE, 0.2);
p.apply(cn);
tm.init(cn);
int[] prevActiveColumns = { 0 };
Cell[] prevActiveCells = { cn.getCell(0), cn.getCell(1), cn.getCell(2), cn.getCell(3) };
int[] activeColumns = { 1, 2 };
Cell prevInactiveCell = cn.getCell(81);
Cell expectedActiveCell = cn.getCell(4);
DistalDendrite correctActiveSegment = cn.CreateDistalSegment(expectedActiveCell);
cn.createSynapse(correctActiveSegment, prevActiveCells[0], 0.5);
cn.createSynapse(correctActiveSegment, prevActiveCells[1], 0.5);
cn.createSynapse(correctActiveSegment, prevActiveCells[2], 0.5);
DistalDendrite wrongMatchingSegment = cn.CreateDistalSegment(cn.getCell(43));
cn.createSynapse(wrongMatchingSegment, prevActiveCells[0], 0.5);
cn.createSynapse(wrongMatchingSegment, prevActiveCells[1], 0.5);
cn.createSynapse(wrongMatchingSegment, prevInactiveCell, 0.5);
var r = deepCopyPlain <Synapse>(cn.getReceptorSynapseMapping().Values.First().First());
var synMapBefore = deepCopyPlain <Dictionary <Cell, LinkedHashSet <Synapse> > >(cn.getReceptorSynapseMapping());
var segMapBefore = deepCopyPlain <Dictionary <Cell, List <DistalDendrite> > >(cn.getSegmentMapping());
tm.Compute(prevActiveColumns, false);
tm.Compute(activeColumns, false);
Assert.IsTrue(synMapBefore != cn.getReceptorSynapseMapping());
Assert.IsTrue(synMapBefore.Keys.SequenceEqual(cn.getReceptorSynapseMapping().Keys));
Assert.IsTrue(segMapBefore != cn.getSegmentMapping());
Assert.IsTrue(segMapBefore.Keys.SequenceEqual(cn.getSegmentMapping().Keys));
}
public void testMatchingSegmentAddSynapsesToSubsetOfWinnerCells()
{
TemporalMemory tm = new TemporalMemory();
Connections cn = new Connections();
Parameters p = GetDefaultParameters(null, Parameters.KEY.CELLS_PER_COLUMN, 1);
p = GetDefaultParameters(p, Parameters.KEY.MIN_THRESHOLD, 1);
p.Apply(cn);
TemporalMemory.Init(cn);
int[] previousActiveColumns = { 0, 1, 2, 3 };
HashSet <Cell> prevWinnerCells = cn.GetCellSet(new int[] { 0, 1, 2, 3 });
int[] activeColumns = { 4 };
DistalDendrite matchingSegment = cn.CreateSegment(cn.GetCell(4));
cn.CreateSynapse(matchingSegment, cn.GetCell(0), 0.5);
ComputeCycle cc = tm.Compute(cn, previousActiveColumns, true);
Assert.IsTrue(cc.WinnerCells().SetEquals(prevWinnerCells));
cc = tm.Compute(cn, activeColumns, true);
List <Synapse> synapses = cn.GetSynapses(matchingSegment);
Assert.AreEqual(3, synapses.Count);
synapses.Sort();
foreach (Synapse synapse in synapses)
{
if (synapse.GetPresynapticCell().GetIndex() == 0)
{
continue;
}
Assert.AreEqual(0.21, synapse.GetPermanence(), 0.01);
Assert.IsTrue(synapse.GetPresynapticCell().GetIndex() == 1 ||
synapse.GetPresynapticCell().GetIndex() == 2 ||
synapse.GetPresynapticCell().GetIndex() == 3);
}
}
public void TestNoChangeToMatchingSegmentsInPredictedActiveColumn()
{
TemporalMemory tm = new TemporalMemory();
Connections cn = new Connections();
Parameters p = getDefaultParameters();
p.apply(cn);
tm.Init(cn);
int[] previousActiveColumns = { 0 };
int[] activeColumns = { 1 };
Cell[] previousActiveCells = { cn.GetCell(0), cn.GetCell(1), cn.GetCell(2), cn.GetCell(3) };
Cell expectedActiveCell = cn.GetCell(4);
List <Cell> expectedActiveCells = new List <Cell>(new Cell[] { expectedActiveCell });
Cell otherBurstingCell = cn.GetCell(5);
DistalDendrite activeSegment = cn.CreateDistalSegment(expectedActiveCell);
cn.CreateSynapse(activeSegment, previousActiveCells[0], 0.5);
cn.CreateSynapse(activeSegment, previousActiveCells[1], 0.5);
cn.CreateSynapse(activeSegment, previousActiveCells[2], 0.5);
cn.CreateSynapse(activeSegment, previousActiveCells[3], 0.5);
DistalDendrite matchingSegmentOnSameCell = cn.CreateDistalSegment(expectedActiveCell);
Synapse s1 = cn.CreateSynapse(matchingSegmentOnSameCell, previousActiveCells[0], 0.3);
Synapse s2 = cn.CreateSynapse(matchingSegmentOnSameCell, previousActiveCells[1], 0.3);
DistalDendrite matchingSegmentOnOtherCell = cn.CreateDistalSegment(otherBurstingCell);
Synapse s3 = cn.CreateSynapse(matchingSegmentOnOtherCell, previousActiveCells[0], 0.3);
Synapse s4 = cn.CreateSynapse(matchingSegmentOnOtherCell, previousActiveCells[1], 0.3);
ComputeCycle cc = tm.Compute(previousActiveColumns, true) as ComputeCycle;
Assert.IsTrue(cc.PredictiveCells.SequenceEqual(expectedActiveCells));
tm.Compute(activeColumns, true);
Assert.AreEqual(0.3, s1.Permanence, 0.01);
Assert.AreEqual(0.3, s2.Permanence, 0.01);
Assert.AreEqual(0.3, s3.Permanence, 0.01);
Assert.AreEqual(0.3, s4.Permanence, 0.01);
}
public void testConnectionsNeverChangeWhenLearningDisabled()
{
TemporalMemory tm = new TemporalMemory();
Connections cn = new Connections();
Parameters p = GetDefaultParameters(null, Parameters.KEY.MAX_NEW_SYNAPSE_COUNT, 4);
p = GetDefaultParameters(p, Parameters.KEY.PREDICTED_SEGMENT_DECREMENT, 0.02);
p = GetDefaultParameters(p, Parameters.KEY.INITIAL_PERMANENCE, 0.2);
p.Apply(cn);
TemporalMemory.Init(cn);
int[] prevActiveColumns = { 0 };
Cell[] prevActiveCells = { cn.GetCell(0), cn.GetCell(1), cn.GetCell(2), cn.GetCell(3) };
int[] activeColumns = { 1, 2 };
Cell prevInactiveCell = cn.GetCell(81);
Cell expectedActiveCell = cn.GetCell(4);
DistalDendrite correctActiveSegment = cn.CreateSegment(expectedActiveCell);
cn.CreateSynapse(correctActiveSegment, prevActiveCells[0], 0.5);
cn.CreateSynapse(correctActiveSegment, prevActiveCells[1], 0.5);
cn.CreateSynapse(correctActiveSegment, prevActiveCells[2], 0.5);
DistalDendrite wrongMatchingSegment = cn.CreateSegment(cn.GetCell(43));
cn.CreateSynapse(wrongMatchingSegment, prevActiveCells[0], 0.5);
cn.CreateSynapse(wrongMatchingSegment, prevActiveCells[1], 0.5);
cn.CreateSynapse(wrongMatchingSegment, prevInactiveCell, 0.5);
Map <Cell, HashSet <Synapse> > synMapBefore = DeepCopyPlain(cn.GetReceptorSynapseMapping());
Map <Cell, List <DistalDendrite> > segMapBefore = DeepCopyPlain(cn.GetSegmentMapping());
tm.Compute(cn, prevActiveColumns, false);
tm.Compute(cn, activeColumns, false);
Assert.IsTrue(synMapBefore != cn.GetReceptorSynapseMapping());
Assert.AreEqual(synMapBefore, cn.GetReceptorSynapseMapping());
Assert.IsTrue(segMapBefore != cn.GetSegmentMapping());
Assert.AreEqual(segMapBefore, cn.GetSegmentMapping());
}
public void testNewSegmentAddSynapsesToSubsetOfWinnerCells()
{
TemporalMemory tm = new TemporalMemory();
Connections cn = new Connections();
Parameters p = getDefaultParameters(null, KEY.MAX_NEW_SYNAPSE_COUNT, 2);
p.apply(cn);
tm.init(cn);
int[] previousActiveColumns = { 0, 1, 2 };
int[] activeColumns = { 4 };
ComputeCycle cc = tm.Compute(previousActiveColumns, true) as ComputeCycle;
ISet <Cell> prevWinnerCells = cc.WinnerCells;
Assert.AreEqual(3, prevWinnerCells.Count);
cc = tm.Compute(activeColumns, true) as ComputeCycle;
List <Cell> winnerCells = new List <Cell>(cc.WinnerCells);
Assert.AreEqual(1, winnerCells.Count);
List <DistalDendrite> segments = winnerCells[0].getSegments(cn);
//List<DistalDendrite> segments = winnerCells[0].Segments;
Assert.AreEqual(1, segments.Count);
List <Synapse> synapses = cn.getSynapses(segments[0]);
Assert.AreEqual(2, synapses.Count);
foreach (Synapse synapse in synapses)
{
Assert.AreEqual(0.21, synapse.getPermanence(), 0.01);
Assert.IsTrue(prevWinnerCells.Contains(synapse.getPresynapticCell()));
}
}
public void testRecycleWeakestSynapseToMakeRoomForNewSynapse()
{
TemporalMemory tm = new TemporalMemory();
Connections cn = new Connections();
Parameters p = GetDefaultParameters(null, Parameters.KEY.CELLS_PER_COLUMN, 1);
p.SetParameterByKey(Parameters.KEY.COLUMN_DIMENSIONS, new int[] { 100 });
p = GetDefaultParameters(p, Parameters.KEY.MIN_THRESHOLD, 1);
p = GetDefaultParameters(p, Parameters.KEY.PERMANENCE_INCREMENT, 0.02);
p = GetDefaultParameters(p, Parameters.KEY.PERMANENCE_DECREMENT, 0.02);
p.SetParameterByKey(Parameters.KEY.MAX_SYNAPSES_PER_SEGMENT, 3);
p.Apply(cn);
TemporalMemory.Init(cn);
Assert.AreEqual(3, cn.GetMaxSynapsesPerSegment());
int[] prevActiveColumns = { 0, 1, 2 };
HashSet <Cell> prevWinnerCells = cn.GetCellSet(new int[] { 0, 1, 2 });
int[] activeColumns = { 4 };
DistalDendrite matchingSegment = cn.CreateSegment(cn.GetCell(4));
cn.CreateSynapse(matchingSegment, cn.GetCell(81), 0.6);
// Weakest Synapse
cn.CreateSynapse(matchingSegment, cn.GetCell(0), 0.11);
ComputeCycle cc = tm.Compute(cn, prevActiveColumns, true);
Assert.IsTrue(prevWinnerCells.SetEquals(cc.winnerCells));
tm.Compute(cn, activeColumns, true);
List <Synapse> synapses = cn.GetSynapses(matchingSegment);
Assert.AreEqual(3, synapses.Count);
HashSet <Cell> presynapticCells = new HashSet <Cell>(synapses.Select(s => s.GetPresynapticCell()));
Assert.IsFalse(presynapticCells.Select(cell => cell.GetIndex()).Any(i => i == 0));
}
public void testPunishMatchingSegmentsInInactiveColumns()
{
TemporalMemory tm = new TemporalMemory();
Connections cn = new Connections();
Parameters p = GetDefaultParameters(null, Parameters.KEY.MAX_NEW_SYNAPSE_COUNT, 4);
p = GetDefaultParameters(p, Parameters.KEY.INITIAL_PERMANENCE, 0.2);
p = GetDefaultParameters(p, Parameters.KEY.PREDICTED_SEGMENT_DECREMENT, 0.02);
p.Apply(cn);
TemporalMemory.Init(cn);
int[] prevActiveColumns = { 0 };
Cell[] prevActiveCells = { cn.GetCell(0), cn.GetCell(1), cn.GetCell(2), cn.GetCell(3) };
int[] activeColumns = { 1 };
Cell previousInactiveCell = cn.GetCell(81);
DistalDendrite activeSegment = cn.CreateSegment(cn.GetCell(42));
Synapse as1 = cn.CreateSynapse(activeSegment, prevActiveCells[0], .5);
Synapse as2 = cn.CreateSynapse(activeSegment, prevActiveCells[1], .5);
Synapse as3 = cn.CreateSynapse(activeSegment, prevActiveCells[2], .5);
Synapse is1 = cn.CreateSynapse(activeSegment, previousInactiveCell, .5);
DistalDendrite matchingSegment = cn.CreateSegment(cn.GetCell(43));
Synapse as4 = cn.CreateSynapse(matchingSegment, prevActiveCells[0], .5);
Synapse as5 = cn.CreateSynapse(matchingSegment, prevActiveCells[1], .5);
Synapse is2 = cn.CreateSynapse(matchingSegment, previousInactiveCell, .5);
tm.Compute(cn, prevActiveColumns, true);
tm.Compute(cn, activeColumns, true);
Assert.AreEqual(0.48, as1.GetPermanence(), 0.01);
Assert.AreEqual(0.48, as2.GetPermanence(), 0.01);
Assert.AreEqual(0.48, as3.GetPermanence(), 0.01);
Assert.AreEqual(0.48, as4.GetPermanence(), 0.01);
Assert.AreEqual(0.48, as5.GetPermanence(), 0.01);
Assert.AreEqual(0.50, is1.GetPermanence(), 0.01);
Assert.AreEqual(0.50, is2.GetPermanence(), 0.01);
}
public void testRecycleLeastRecentlyActiveSegmentToMakeRoomForNewSegment()
{
TemporalMemory tm = new TemporalMemory();
Connections cn = new Connections();
Parameters p = getDefaultParameters(null, KEY.CELLS_PER_COLUMN, 1);
p = getDefaultParameters(p, KEY.INITIAL_PERMANENCE, 0.5);
p = getDefaultParameters(p, KEY.PERMANENCE_INCREMENT, 0.02);
p = getDefaultParameters(p, KEY.PERMANENCE_DECREMENT, 0.02);
p.Set(KEY.MAX_SEGMENTS_PER_CELL, 2);
p.apply(cn);
tm.init(cn);
int[] prevActiveColumns1 = { 0, 1, 2 };
int[] prevActiveColumns2 = { 3, 4, 5 };
int[] prevActiveColumns3 = { 6, 7, 8 };
int[] activeColumns = { 9 };
Cell cell9 = cn.getCell(9);
tm.Compute(prevActiveColumns1, true);
tm.Compute(activeColumns, true);
Assert.AreEqual(1, cn.getSegments(cell9).Count);
DistalDendrite oldestSegment = cn.getSegments(cell9)[0];
tm.reset(cn);
tm.Compute(prevActiveColumns2, true);
tm.Compute(activeColumns, true);
Assert.AreEqual(2, cn.getSegments(cell9).Count);
//Set<Cell> oldPresynaptic = cn.getSynapses(oldestSegment)
// .stream()
// .map(s->s.getPresynapticCell())
// .collect(Collectors.toSet());
var oldPresynaptic = cn.getSynapses(oldestSegment).Select(s => s.getPresynapticCell()).ToList();
tm.reset(cn);
tm.Compute(prevActiveColumns3, true);
tm.Compute(activeColumns, true);
Assert.AreEqual(2, cn.getSegments(cell9).Count);
// Verify none of the segments are connected to the cells the old
// segment was connected to.
foreach (DistalDendrite segment in cn.getSegments(cell9))
{
//Set<Cell> newPresynaptic = cn.getSynapses(segment)
// .stream()
// .map(s->s.getPresynapticCell())
// .collect(Collectors.toSet());
var newPresynaptic = cn.getSynapses(segment).Select(s => s.getPresynapticCell()).ToList();
Assert.IsTrue(areDisjoined <Cell>(oldPresynaptic, newPresynaptic));
}
}
public void TestActivateCorrectlyPredictiveCells(int tmImplementation)
{
TemporalMemory tm = tmImplementation == 0 ? new TemporalMemory() : new TemporalMemoryMT();
Connections cn = new Connections();
Parameters p = getDefaultParameters();
p.apply(cn);
tm.Init(cn);
int[] previousActiveColumns = { 0 };
int[] activeColumns = { 1 };
// Cell4 belongs to column with index 1.
Cell cell4 = cn.GetCell(4);
// ISet<Cell> expectedActiveCells = Stream.of(cell4).collect(Collectors.toSet());
ISet <Cell> expectedActiveCells = new HashSet <Cell>(new Cell[] { cell4 });
// We add distal dentrite at column1.cell4
DistalDendrite activeSegment = cn.CreateDistalSegment(cell4);
//
// We add here synapses between column0.cells[0-3] and segment.
cn.CreateSynapse(activeSegment, cn.GetCell(0), 0.5);
cn.CreateSynapse(activeSegment, cn.GetCell(1), 0.5);
cn.CreateSynapse(activeSegment, cn.GetCell(2), 0.5);
cn.CreateSynapse(activeSegment, cn.GetCell(3), 0.5);
ComputeCycle cc = tm.Compute(previousActiveColumns, true) as ComputeCycle;
Assert.IsTrue(cc.PredictiveCells.SequenceEqual(expectedActiveCells));
ComputeCycle cc2 = tm.Compute(activeColumns, true) as ComputeCycle;
Assert.IsTrue(cc2.ActiveCells.SequenceEqual(expectedActiveCells));
}
public void testBurstUnpredictedColumns()
{
TemporalMemory tm = new TemporalMemory();
Connections cn = new Connections();
Parameters p = GetDefaultParameters();
p.Apply(cn);
TemporalMemory.Init(cn);
int[] activeColumns = { 0 };
HashSet <Cell> burstingCells = cn.GetCellSet(new int[] { 0, 1, 2, 3 });
ComputeCycle cc = tm.Compute(cn, activeColumns, true);
Assert.IsTrue(cc.ActiveCells().SetEquals(burstingCells));
}
public void TestBurstUnpredictedColumns1()
{
HtmConfig htmConfig = GetDefaultTMParameters();
Connections cn = new Connections(htmConfig);
TemporalMemory tm = new TemporalMemory();
tm.Init(cn);
int[] activeColumns = { 0 };
IList <Cell> burstingCells = cn.GetCellSet(new int[] { 0, 1, 2, 3 });
ComputeCycle cc = tm.Compute(activeColumns, true) as ComputeCycle;
Assert.IsTrue(cc.ActiveCells.SequenceEqual(burstingCells));
}
public void TestBurstUnpredictedColumns()
{
TemporalMemory tm = new TemporalMemory();
Connections cn = new Connections();
Parameters p = getDefaultParameters();
p.apply(cn);
tm.init(cn);
int[] activeColumns = { 0 };
ISet <Cell> burstingCells = cn.getCellSet(new int[] { 0, 1, 2, 3 });
ComputeCycle cc = tm.Compute(activeColumns, true) as ComputeCycle;
Assert.IsTrue(cc.ActiveCells.SequenceEqual(burstingCells));
}
public void testRecycleLeastRecentlyActiveSegmentToMakeRoomForNewSegment()
{
TemporalMemory tm = new TemporalMemory();
Connections cn = new Connections();
Parameters p = GetDefaultParameters(null, Parameters.KEY.CELLS_PER_COLUMN, 1);
p = GetDefaultParameters(p, Parameters.KEY.INITIAL_PERMANENCE, 0.5);
p = GetDefaultParameters(p, Parameters.KEY.PERMANENCE_INCREMENT, 0.02);
p = GetDefaultParameters(p, Parameters.KEY.PERMANENCE_DECREMENT, 0.02);
p.SetParameterByKey(Parameters.KEY.MAX_SEGMENTS_PER_CELL, 2);
p.Apply(cn);
TemporalMemory.Init(cn);
int[] prevActiveColumns1 = { 0, 1, 2 };
int[] prevActiveColumns2 = { 3, 4, 5 };
int[] prevActiveColumns3 = { 6, 7, 8 };
int[] activeColumns = { 9 };
Cell cell9 = cn.GetCell(9);
tm.Compute(cn, prevActiveColumns1, true);
tm.Compute(cn, activeColumns, true);
Assert.AreEqual(1, cn.GetSegments(cell9).Count);
DistalDendrite oldestSegment = cn.GetSegments(cell9)[0];
tm.Reset(cn);
tm.Compute(cn, prevActiveColumns2, true);
tm.Compute(cn, activeColumns, true);
Assert.AreEqual(2, cn.GetSegments(cell9).Count);
HashSet <Cell> oldPresynaptic = new HashSet <Cell>(cn.GetSynapses(oldestSegment)
.Select(s => s.GetPresynapticCell()));
tm.Reset(cn);
tm.Compute(cn, prevActiveColumns3, true);
tm.Compute(cn, activeColumns, true);
Assert.AreEqual(2, cn.GetSegments(cell9).Count);
// Verify none of the segments are connected to the cells the old
// segment was connected to.
foreach (DistalDendrite segment in cn.GetSegments(cell9))
{
HashSet <Cell> newPresynaptic = new HashSet <Cell>(cn.GetSynapses(segment)
.Select(s => s.GetPresynapticCell()));
//.collect(Collectors.toSet());
Assert.IsFalse(oldPresynaptic.Overlaps(newPresynaptic));
//Assert.IsTrue(Collections.disjoint(oldPresynaptic, newPresynaptic));
}
}
public void SerializationDeSerializationBasicTest()
{
TemporalMemory tm = new TemporalMemory();
Connections cn = new Connections();
Parameters p = getDefaultParameters();
p.apply(cn);
tm.init(cn);
int[] previousActiveColumns = { 0 };
int[] activeColumns = { 1 };
Cell cell4 = cn.getCell(4);
ISet <Cell> expectedActiveCells = new HashSet <Cell>(new Cell[] { cell4 });
DistalDendrite activeSegment = cn.CreateDistalSegment(cell4);
cn.createSynapse(activeSegment, cn.getCell(0), 0.5);
cn.createSynapse(activeSegment, cn.getCell(1), 0.5);
cn.createSynapse(activeSegment, cn.getCell(2), 0.5);
cn.createSynapse(activeSegment, cn.getCell(3), 0.5);
ComputeCycle cc = tm.Compute(previousActiveColumns, true) as ComputeCycle;
Assert.IsTrue(cc.predictiveCells.SequenceEqual(expectedActiveCells));
tm.Serializer("tmSerializeNew.json");
var tm1 = TemporalMemory.Deserializer("tmSerializeNew.json");
ComputeCycle cc2 = tm1.Compute(activeColumns, true) as ComputeCycle;
Assert.IsTrue(cc2.ActiveCells.SequenceEqual(expectedActiveCells));
}
