/// <summary>
/// Add new DataTable to existing DataSet
/// </summary>
/// <param name="dataSet"></param>
public new void AddWatchTable(ref DataSet dataSet, string tableName = "")
{
dataSet.Tables.Add(this.DataTable(tableName));
dataSet.Tables.Add(DistalSegment.DataTable(tableName)); //not sure if necc
dataSet.Tables.Add(InputSource.DataTable(tableName)); //not sure if necc
base.AddWatchTable(ref dataSet, tableName);
}
///<summary>
/// Create a new segment on the update cell using connections from
/// the set of learning cells for the update info.
///</summary>
internal DistalSegment CreateDistalSegment()
{
DistalSegment distalSegment = this.Cell.CreateDistalSegment(this.CellsToConnect);
distalSegment.NumberPredictionSteps = this.NumberPredictionSteps;
return(distalSegment);
}
/// <summary>
/// For this cell, return a <see cref="Segment"/> that is active in the given
/// time step. If multiple segments are active, sequence segments are given
/// preference. Otherwise, segments with most activity are given preference.
/// Original name: getActiveSegment
/// </summary>
public DistalSegment GetActiveDistalSegment(int t)
{
DistalSegment bestDistalSegment = null;
bool foundSequenceSegment = false;
int bestNumberActiveSynapses = 0;
foreach (var segment in this.DistalSegments)
{
int numberActiveSynapses = segment.GetActiveSynapses(t).Count;
if (numberActiveSynapses >= Segment.ActivationThreshold)
{
// Sequence segments are given preference.
// Otherwise, segments with most activity are given preference.
if (segment.IsSequence)
{
foundSequenceSegment = true;
if (numberActiveSynapses > bestNumberActiveSynapses)
{
bestNumberActiveSynapses = numberActiveSynapses;
bestDistalSegment = segment;
}
}
else if (!foundSequenceSegment && numberActiveSynapses > bestNumberActiveSynapses)
{
bestNumberActiveSynapses = numberActiveSynapses;
bestDistalSegment = segment;
}
}
}
return(bestDistalSegment);
}
/// <summary>
/// Object's identification string based on it's position within parent.
/// Used primarly in Watch.
/// </summary>
/// <returns></returns>
public new string ID()
{
string str = "";
//str = String.Format ( "Synapse [" + Parent.ID () + "]" );
str = String.Format("DistalSynapse[{0}]", DistalSegment.ID());
return(str);
}
/// <summary>
/// For this column, return the cell with the best matching <see cref="Segment"/>
/// (at time t-1 or t). Only consider segments that are predicting cell activation
/// to occur in exactly numberPredictionSteps many time steps from now. If no cell
/// has a matching segment, then return the cell with the fewest number of segments.
/// </summary>
/// <param name="t">only consider active segments at time t.</param>
/// <param name="numberPredictionSteps">only consider segments that are predicting
/// cell activation to occur in exactly this many time steps from now.</param>
/// <returns>Tuple containing the best cell and its best <see cref="Segment"/>
/// (may be None).</returns>
internal Tuple <Cell, DistalSegment> GetBestMatchingCell(int t, int numberPredictionSteps)
{
Cell bestCell = null;
DistalSegment bestDistalSegment = null;
int bestNumberActiveSynapses = 0;
// Chooses the cell with the best matching segment.
foreach (var cell in this.Cells)
{
DistalSegment distalSegment = cell.GetBestMatchingDistalSegment(t, numberPredictionSteps);
if (distalSegment != null)
{
int numberActiveSynapses = distalSegment.GetActiveSynapses(t).Count;
if (numberActiveSynapses > bestNumberActiveSynapses)
{
bestCell = cell;
bestDistalSegment = distalSegment;
bestNumberActiveSynapses = numberActiveSynapses;
}
}
}
// If there are no active sequences, return the cell with the fewest number of
// segments
if (bestCell == null)
{
int bestNumberActiveSegments = int.MaxValue;
foreach (var cell in this.Cells)
{
int numberActiveSegments = cell.DistalSegments.Count;
if (numberActiveSegments < bestNumberActiveSegments)
{
bestNumberActiveSegments = numberActiveSegments;
bestCell = cell;
}
}
// Pick a random cell among those with equal segment counts
// TODO: is there a more efficient way to do this maybe?
var candidates = new List <Cell>();
foreach (var cell in this.Cells)
{
if (cell.DistalSegments.Count == bestNumberActiveSegments)
{
candidates.Add(cell);
}
}
if (candidates.Count > 1)
{
bestCell = candidates[this._random.Next(candidates.Count)];
}
// Leave bestSegment null to indicate a new segment is to be added
}
return(new Tuple <Cell, DistalSegment>(bestCell, bestDistalSegment));
}
/// <summary>
/// Creates a new distal segment for this Cell.
/// </summary>
/// <param name="cellsToConnect"> A set of available cells to add to
/// the segmentUpdateList.</param>
/// <returns> Created segmentUpdateList</returns>
/// <remarks>
/// The new segment will initially connect to at most newNumberSynapses
/// synapses randomly selected from the set of cells that
/// were in the learning state at t-1 (specified by the learningCells parameter).
/// </remarks>
internal DistalSegment CreateDistalSegment(List <Cell> cellsToConnect)
{
var newDistalSegment = new DistalSegment(this);
foreach (var cell in cellsToConnect)
{
newDistalSegment.CreateSynapse(cell, Synapse.InitialPermanence);
}
this.DistalSegments.Add(newDistalSegment);
return(newDistalSegment);
}
///<summary>
/// Add a new <see cref="SegmentUpdate"/> object to this <see cref="Cell"/>
/// containing proposed changes to the specified segment.
///</summary>
///<remarks>
/// If the segment is None, then a new segment is to be added, otherwise
/// the specified segment is updated. If the segment exists, find all active
/// synapses for the segment (either at t or t-1)
/// and mark them as needing to be updated. If newSynapses is true, then
/// Region.newNumberSynapses - len(activeSynapses) new synapses are added to the
/// segment to be updated. The (new) synapses are randomly chosen from the set
/// of current learning cells (within Region.localityRadius if set).
///
/// These segment updates are only applied when the applySegmentUpdates
/// method is later called on this Cell.
///</remarks>
internal SegmentUpdate UpdateDistalSegmentActiveSynapses(int t, DistalSegment distalSegment, bool newSynapses = false)
{
// Let ActiveSynapses be the list of active synapses where the originating
// cells have their ActiveState output = true at time step t.
// (This list is empty if segment = null since the segment doesn't exist.)
var activeSynapses = new List <Synapse>();
if (distalSegment != null)
{
activeSynapses = distalSegment.GetActiveSynapses(t);
}
var segmentUpdate = new SegmentUpdate(this, distalSegment, activeSynapses, newSynapses);
this.SegmentUpdates.Add(segmentUpdate);
return(segmentUpdate);
}
///<summary>
/// This function reinforces each segment in this Cell's SegmentUpdate.
/// </summary>
/// <remarks>
/// Using the segmentUpdate, the following changes are
/// performed. If positiveReinforcement is true then synapses on the active
/// list get their permanence counts incremented by permanenceInc. All other
/// synapses get their permanence counts decremented by permanenceDec. If
/// positiveReinforcement is false, then synapses on the active list get
/// their permanence counts decremented by permanenceDec. After this step,
/// any synapses in segmentUpdate that do yet exist get added with a permanence
/// count of initialPerm. These new synapses are randomly chosen from the
/// set of all cells that have learnState output = 1 at time step t.
///</remarks>
internal void ApplySegmentUpdates(bool positiveReinforcement, int latestCreationStep = -1)
{
// This loop iterates through a list of SegmentUpdate's and reinforces each segment.
foreach (var segmentUpdate in this.SegmentUpdates)
{
DistalSegment distalSegment = segmentUpdate.DistalSegment;
if (distalSegment != null)
{
if (positiveReinforcement)
{
distalSegment.UpdatePermanences(segmentUpdate.ActiveDistalSynapses);
}
else
{
distalSegment.DecreasePermanences(segmentUpdate.ActiveDistalSynapses);
}
}
// Add new synapses (and new segment if necessary)
if (segmentUpdate.AddNewSynapses && positiveReinforcement)
{
if (distalSegment == null)
{
// Only add new segment if end cells to connect are available
if (segmentUpdate.CellsToConnect.Count > 0)
{
distalSegment = segmentUpdate.CreateDistalSegment();
}
}
else if (segmentUpdate.CellsToConnect.Count > 0)
{
// Add new synapses to existing segment
segmentUpdate.CreateDistalSynapses();
}
}
}
// Delete segment update instances after they are applied
this.SegmentUpdates.Clear();
}
/// <summary>
/// Gets the best matching <see cref="Segment"/>.
/// </summary>
/// <param name="t">Only consider active segments at time t.</param>
/// <param name="numberPredictionSteps">Number of time steps in the future an activation will occur.</param>
/// <remarks>
/// For this cell (at t or t-1), find the <see cref="Segment"/> (only
/// consider sequence segments if isSequence is True, otherwise only consider
/// non-sequence segments) with the largest number of active synapses.
/// This routine is aggressive in finding the best match. The permanence
/// value of synapses is allowed to be below connectedPerm.
/// The number of active synapses is allowed to be below activationThreshold,
/// but must be above minThreshold. The routine returns that segment.
/// If no segments are found, then null is returned.
/// </remarks>
internal DistalSegment GetBestMatchingDistalSegment(int t, int numberPredictionSteps)
{
DistalSegment bestDistalSegment = null;
int bestNumberActiveSynapses = _minSynapsesPerSegmentThreshold;
foreach (var segment in this.DistalSegments)
{
if (segment.NumberPredictionSteps == numberPredictionSteps)
{
// Get all the active synapses in the given t time step, no matter connection value
int numberActiveSynapses = segment.GetActiveSynapses(t).Count;
if (numberActiveSynapses >= bestNumberActiveSynapses)
{
bestNumberActiveSynapses = numberActiveSynapses;
bestDistalSegment = segment;
}
}
}
return(bestDistalSegment);
}
/// <summary>
/// Gets the sequence segment. If it's not null then this cell was predicted to
/// become active at current time step.
/// </summary>
/// <value>The segment predicting or null if none found.</value>
public DistalSegment GetSequencePredictingDistalSegment()
{
DistalSegment predictingDistalSegment = null;
try
{
if (this.PredictiveState[Global.T - 1])
{
DistalSegment distalSegment = this.GetActiveDistalSegment(Global.T - 1);
if (distalSegment != null && distalSegment.IsSequence)
{
predictingDistalSegment = distalSegment;
}
}
}
catch (InvalidOperationException)
{
}
return(predictingDistalSegment);
}
/// <summary>
/// Initializes a new instance of the <see cref="DistalSynapse"/> class and
/// sets its input source and initial permanance values.
/// </summary>
/// <param name="distalSeg">
/// </param>
/// <param name="inputSource">
/// An object providing source of the input to this synapse (either
/// a <see cref="Column"/>'s <see cref="Cell"/> or a special
/// <see cref="InputCell"/>).
/// </param>
/// <param name="permanence">Initial permanence value.</param>
public DistalSynapse(DistalSegment distalSeg, Cell inputSource, float permanence)
: this(inputSource, permanence)
{
// Set fields
this.DistalSegment = distalSeg;
}
/// <summary>
/// Initializes a new instance of the <see cref="DistalSynapse"/> class and
/// sets its input source and initial permanance values.
/// </summary>
/// <param name="distalSeg">
/// </param>
/// <param name="inputSource">
/// An object providing source of the input to this synapse (either
/// a <see cref="Column"/>'s <see cref="Cell"/> or a special
/// <see cref="InputCell"/>).
/// </param>
/// <param name="permanence">Initial permanence value.</param>
public DistalSynapse(DistalSegment distalSeg, Cell inputSource, float permanence)
: this(inputSource, permanence)
{
// Set fields
this.DistalSegment = distalSeg;
}
///<summary>
///Create a new SegmentUpdate that is to modify the state of the Region
///either by adding a new segment to a cell, new synapses to a segemnt,
///or updating permanences of existing synapses on some segment.
///</summary>
///<param name="cell">cell the cell that is to have a segment added or updated.
/// </param>
///<param name="distalSegment">the segment that is to be updated (null here means a new
/// segment is to be created on the parent cell).</param>
///<param name="activeDistalSynapses">the set of active synapses on the segment
/// that are to have their permanences updated.</param>
///<param name="addNewSynapses">set to true if new synapses are to be added to the
/// segment (or if new segment is being created) or false if no new synapses
/// should be added instead only existing permanences updated.</param>
///
public SegmentUpdate(Cell cell, DistalSegment distalSegment, List<Synapse> activeDistalSynapses,
bool addNewSynapses = false)
{
// Set fields
this.Cell = cell;
this.DistalSegment = distalSegment;
this.ActiveDistalSynapses = new List<Synapse>(activeDistalSynapses);
this.AddNewSynapses = addNewSynapses;
this.CellsToConnect = new List<Cell>();
this.NumberPredictionSteps = 1;
this.CreationStep = (int) cell.Statistics.StepCounter;
// Set of cells that have LearnState output = true at time step t.
var cellsToConnect = new List<Cell>();
// If adding new synapses, find the current set of learning cells within
// the Region and select a random subset of them to connect the segment to.
// Do not add > 1 synapse to the same cell on a given segment
Region region = this.Cell.Column.Region;
if (this.AddNewSynapses)
{
// Gather all cells from segment in order to avoid use them as learning cells.
var cellsInSegment = new List<Cell>();
if (distalSegment != null)
{
foreach (var synapse in distalSegment.Synapses)
{
if (synapse is DistalSynapse)
{
cellsInSegment.Add(((DistalSynapse) synapse).InputSource);
}
}
}
// Define limits to choose cells to connect.
int minY, maxY, minX, maxX;
if (region.LocalityRadius > 0)
{
// Only allow connecting to Columns within locality radius
minX = Math.Max(0, cell.Column.PositionInRegion.X - region.LocalityRadius);
minY = Math.Max(0, cell.Column.PositionInRegion.Y - region.LocalityRadius);
maxX = Math.Min(region.Size.Width - 1,
cell.Column.PositionInRegion.X + region.LocalityRadius);
maxY = Math.Min(region.Size.Height - 1,
cell.Column.PositionInRegion.Y + region.LocalityRadius);
}
else
{
// Now I want to allow connections over all the region!
// If locality radius is 0, it means 'no restriction'
minX = 0;
minY = 0;
maxX = region.Size.Width - 1;
maxY = region.Size.Height - 1;
}
// Set of cells that have LearnState output = true at time step t.
for (int x = minX; x <= maxX; x++)
{
for (int y = minY; y <= maxY; y++)
{
Column column = region.GetColumn(x, y);
// Skip cells in our own column (don't connect to ourself)
if (column != cell.Column)
{
foreach (var learningCell in column.Cells)
{
// Skip cells that already are linked to the segment (case it exists).
if (learningCell.LearnState[Global.T - 1] && !cellsInSegment.Contains(learningCell))
{
cellsToConnect.Add(learningCell);
}
}
}
}
}
}
// Basic allowed number of new Synapses
int newNumberSynapses = region.NumberNewSynapses;
if (distalSegment != null)
{
newNumberSynapses = Math.Max(0, newNumberSynapses - activeDistalSynapses.Count);
}
// Clamp at learn cells
newNumberSynapses = Math.Min(cellsToConnect.Count, newNumberSynapses);
// Randomly choose (newNumberSynapses) learning cells to add connections to
if (cellsToConnect.Count > 0 && newNumberSynapses > 0)
{
this.CellsToConnect = this.ChooseRandomCells(cellsToConnect, newNumberSynapses);
}
}
///<summary>
///Create a new SegmentUpdate that is to modify the state of the Region
///either by adding a new segment to a cell, new synapses to a segemnt,
///or updating permanences of existing synapses on some segment.
///</summary>
///<param name="cell">cell the cell that is to have a segment added or updated.
/// </param>
///<param name="distalSegment">the segment that is to be updated (null here means a new
/// segment is to be created on the parent cell).</param>
///<param name="activeDistalSynapses">the set of active synapses on the segment
/// that are to have their permanences updated.</param>
///<param name="addNewSynapses">set to true if new synapses are to be added to the
/// segment (or if new segment is being created) or false if no new synapses
/// should be added instead only existing permanences updated.</param>
///
public SegmentUpdate(Cell cell, DistalSegment distalSegment, List <Synapse> activeDistalSynapses,
bool addNewSynapses = false)
{
// Set fields
this.Cell = cell;
this.DistalSegment = distalSegment;
this.ActiveDistalSynapses = new List <Synapse>(activeDistalSynapses);
this.AddNewSynapses = addNewSynapses;
this.CellsToConnect = new List <Cell>();
this.NumberPredictionSteps = 1;
this.CreationStep = (int)cell.Statistics.StepCounter;
// Set of cells that have LearnState output = true at time step t.
var cellsToConnect = new List <Cell>();
// If adding new synapses, find the current set of learning cells within
// the Region and select a random subset of them to connect the segment to.
// Do not add > 1 synapse to the same cell on a given segment
Region region = this.Cell.Column.Region;
if (this.AddNewSynapses)
{
// Gather all cells from segment in order to avoid use them as learning cells.
var cellsInSegment = new List <Cell>();
if (distalSegment != null)
{
foreach (var synapse in distalSegment.Synapses)
{
if (synapse is DistalSynapse)
{
cellsInSegment.Add(((DistalSynapse)synapse).InputSource);
}
}
}
// Define limits to choose cells to connect.
int minY, maxY, minX, maxX;
if (region.LocalityRadius > 0)
{
// Only allow connecting to Columns within locality radius
minX = Math.Max(0, cell.Column.PositionInRegion.X - region.LocalityRadius);
minY = Math.Max(0, cell.Column.PositionInRegion.Y - region.LocalityRadius);
maxX = Math.Min(region.Size.Width - 1,
cell.Column.PositionInRegion.X + region.LocalityRadius);
maxY = Math.Min(region.Size.Height - 1,
cell.Column.PositionInRegion.Y + region.LocalityRadius);
}
else
{
// Now I want to allow connections over all the region!
// If locality radius is 0, it means 'no restriction'
minX = 0;
minY = 0;
maxX = region.Size.Width - 1;
maxY = region.Size.Height - 1;
}
// Set of cells that have LearnState output = true at time step t.
for (int x = minX; x <= maxX; x++)
{
for (int y = minY; y <= maxY; y++)
{
Column column = region.GetColumn(x, y);
// Skip cells in our own column (don't connect to ourself)
if (column != cell.Column)
{
foreach (var learningCell in column.Cells)
{
// Skip cells that already are linked to the segment (case it exists).
if (learningCell.LearnState[Global.T - 1] && !cellsInSegment.Contains(learningCell))
{
cellsToConnect.Add(learningCell);
}
}
}
}
}
}
// Basic allowed number of new Synapses
int newNumberSynapses = region.NumberNewSynapses;
if (distalSegment != null)
{
newNumberSynapses = Math.Max(0, newNumberSynapses - activeDistalSynapses.Count);
}
// Clamp at learn cells
newNumberSynapses = Math.Min(cellsToConnect.Count, newNumberSynapses);
// Randomly choose (newNumberSynapses) learning cells to add connections to
if (cellsToConnect.Count > 0 && newNumberSynapses > 0)
{
this.CellsToConnect = this.ChooseRandomCells(cellsToConnect, newNumberSynapses);
}
}
///<summary>
/// Add a new <see cref="SegmentUpdate"/> object to this <see cref="Cell"/>
/// containing proposed changes to the specified segment.
///</summary>
///<remarks>
/// If the segment is None, then a new segment is to be added, otherwise
/// the specified segment is updated. If the segment exists, find all active
/// synapses for the segment (either at t or t-1)
/// and mark them as needing to be updated. If newSynapses is true, then
/// Region.newNumberSynapses - len(activeSynapses) new synapses are added to the
/// segment to be updated. The (new) synapses are randomly chosen from the set
/// of current learning cells (within Region.localityRadius if set).
///
/// These segment updates are only applied when the applySegmentUpdates
/// method is later called on this Cell.
///</remarks>
internal SegmentUpdate UpdateDistalSegmentActiveSynapses(int t, DistalSegment distalSegment, bool newSynapses = false)
{
// Let ActiveSynapses be the list of active synapses where the originating
// cells have their ActiveState output = true at time step t.
// (This list is empty if segment = null since the segment doesn't exist.)
var activeSynapses = new List<Synapse>();
if (distalSegment != null)
{
activeSynapses = distalSegment.GetActiveSynapses(t);
}
var segmentUpdate = new SegmentUpdate(this, distalSegment, activeSynapses, newSynapses);
this.SegmentUpdates.Add(segmentUpdate);
return segmentUpdate;
}
/// <summary>
/// Creates a new distal segment for this Cell.
/// </summary>
/// <param name="cellsToConnect"> A set of available cells to add to
/// the segmentUpdateList.</param>
/// <returns> Created segmentUpdateList</returns>
/// <remarks>
/// The new segment will initially connect to at most newNumberSynapses
/// synapses randomly selected from the set of cells that
/// were in the learning state at t-1 (specified by the learningCells parameter).
/// </remarks>
internal DistalSegment CreateDistalSegment(List<Cell> cellsToConnect)
{
var newDistalSegment = new DistalSegment( this );
foreach (var cell in cellsToConnect)
{
newDistalSegment.CreateSynapse(cell, Synapse.InitialPermanence);
}
this.DistalSegments.Add(newDistalSegment);
return newDistalSegment;
}
