/**
* Calculate the active cells, using the current active columns and dendrite
* segments. Grow and reinforce synapses.
*
* <pre>
* Pseudocode:
* for each column
* if column is active and has active distal dendrite segments
* call activatePredictedColumn
* if column is active and doesn't have active distal dendrite segments
* call burstColumn
* if column is inactive and has matching distal dendrite segments
* call punishPredictedColumn
*
* </pre>
*
* @param conn
* @param activeColumnIndices
* @param learn
*/
public void ActivateCells(Connections conn, ComputeCycle cycle, int[] activeColumnIndices, bool learn)
{
ColumnData columnData = new ColumnData();
HashSet <Cell> prevActiveCells = conn.GetActiveCells();
HashSet <Cell> prevWinnerCells = conn.GetWinnerCells();
List <Column> activeColumns = activeColumnIndices
.OrderBy(i => i)
.Select(i => conn.GetColumn(i))
.ToList();
Func <Column, Column> identity = c => c;
Func <DistalDendrite, Column> segToCol = segment => segment.GetParentCell().GetColumn();
//@SuppressWarnings({ "rawtypes" })
GroupBy2 <Column> grouper = GroupBy2 <Column> .Of(
new Tuple <List <object>, Func <object, Column> >(activeColumns.Cast <object>().ToList(), x => identity((Column)x)),
new Tuple <List <object>, Func <object, Column> >(new List <DistalDendrite>(conn.GetActiveSegments()).Cast <object>().ToList(), x => segToCol((DistalDendrite)x)),
new Tuple <List <object>, Func <object, Column> >(new List <DistalDendrite>(conn.GetMatchingSegments()).Cast <object>().ToList(), x => segToCol((DistalDendrite)x)));
double permanenceIncrement = conn.GetPermanenceIncrement();
double permanenceDecrement = conn.GetPermanenceDecrement();
foreach (Tuple t in grouper)
{
columnData = columnData.Set(t);
if (columnData.IsNotNone(ACTIVE_COLUMNS))
{
if (columnData.ActiveSegments().Any())
{
List <Cell> cellsToAdd = ActivatePredictedColumn(conn, columnData.ActiveSegments(),
columnData.MatchingSegments(), prevActiveCells, prevWinnerCells,
permanenceIncrement, permanenceDecrement, learn);
cycle.ActiveCells().UnionWith(cellsToAdd);
cycle.WinnerCells().UnionWith(cellsToAdd);
}
else
{
Tuple cellsXwinnerCell = BurstColumn(conn, columnData.Column(), columnData.MatchingSegments(),
prevActiveCells, prevWinnerCells, permanenceIncrement, permanenceDecrement, conn.GetRandom(),
learn);
cycle.ActiveCells().UnionWith((IEnumerable <Cell>)cellsXwinnerCell.Get(0));
cycle.WinnerCells().Add((Cell)cellsXwinnerCell.Get(1));
}
}
else
{
if (learn)
{
PunishPredictedColumn(conn, columnData.ActiveSegments(), columnData.MatchingSegments(),
prevActiveCells, prevWinnerCells, conn.GetPredictedSegmentDecrement());
}
}
}
}