class Column:
"""
A class only to group properties related to columns.
"""
# region Constructor
def __init__(self):
"""
Initializes a new instance of the Column class.
"""
# region Instance fields
self.x = -1
"""Position on X axis"""
self.y = -1
"""Position on Y axis"""
self.segment = Segment(SegmentType.proximal)
"""Proximal segment of this column"""
self.cells = []
"""List of cells that compose this column."""
# region 3d-tree properties (simulation form)
self.tree3d_x = 0
self.tree3d_y = 0
self.tree3d_z = 0
# endregion
# endregion
# endregion
# region Methods
def getCell(self, z):
"""
Return the cell located at given position
"""
for cell in self.cells:
if cell.z == z:
return cell
def nextTimeStep(self):
"""
Perfoms actions related to time step progression.
"""
self.segment.nextTimeStep()
for cell in self.cells:
cell.nextTimeStep()
class Column:
"""
A class only to group properties related to columns.
"""
#region Constructor
def __init__(self):
"""
Initializes a new instance of this class.
"""
#region Instance fields
self.x = -1
"""Position on X axis"""
self.y = -1
"""Position on Y axis"""
self.segment = Segment(SegmentType.proximal)
"""Proximal segment of this column"""
self.cells = []
"""List of cells that compose this column."""
#region 3d-tree properties (simulation form)
self.tree3d_x = 0
self.tree3d_y = 0
self.tree3d_z = 0
#endregion
#endregion
#endregion
#region Methods
def getCell(self, z):
"""
Return the cell located at given position
"""
for cell in self.cells:
if cell.z == z:
return cell
def nextStep(self):
"""
Perfoms actions related to time step progression.
"""
self.segment.nextStep()
for cell in self.cells:
cell.nextStep()
def __init__(self):
"""
Initializes a new instance of this class.
"""
#region Instance fields
self.x = -1
"""Position on X axis"""
self.y = -1
"""Position on Y axis"""
self.segment = Segment(SegmentType.proximal)
"""Proximal segment of this column"""
self.cells = []
"""List of cells that compose this column."""
#region 3d-tree properties (simulation form)
self.tree3d_x = 0
self.tree3d_y = 0
self.tree3d_z = 0
def __init__(self):
"""
Initializes a new instance of the Column class.
"""
# region Instance fields
self.x = -1
"""Position on X axis"""
self.y = -1
"""Position on Y axis"""
self.segment = Segment(SegmentType.proximal)
"""Proximal segment of this column"""
self.cells = []
"""List of cells that compose this column."""
# region 3d-tree properties (simulation form)
self.tree3d_x = 0
self.tree3d_y = 0
self.tree3d_z = 0
def performTemporalProcess(self): """ Perfoms spatial process. """ # First we should convert from float array to integer set activeColumnsSet = set() for colIdx in range(len(self.columns)): column = self.columns[colIdx] if column.segment.isActive[maxTimeSteps - 1]: activeColumnsSet.add(colIdx) # Send active columns to Temporal Pooler and get processed output (i.e. the predicting cells) self.temporalPooler.compute(activeColumnsSet, self.enableTemporalPooling) # Update cells, distal segments and synapses according to active columns for colIdx in range(len(self.columns)): column = self.columns[colIdx] for cell in column.cells: cellIdx = (colIdx * self.numCellsPerColumn) + column.cells.index(cell) if cell.index == -1: cell.index = cellIdx # Update cell's state following the priority if cellIdx in self.temporalPooler.winnerCells: cell.isLearning[maxTimeSteps - 1] = True if cellIdx in self.temporalPooler.activeCells: cell.isActive[maxTimeSteps - 1] = True if cellIdx in self.temporalPooler.predictiveCells: cell.isPredicted[maxTimeSteps - 1] = True # Mark proximal segment and its connected synapses as predicted column.segment.isPredicted[maxTimeSteps - 1] = True for synapse in column.segment.synapses: if synapse.isConnected[maxTimeSteps - 1]: synapse.isPredicted[maxTimeSteps - 1] = True synapse.inputElem.isPredicted[maxTimeSteps - 1] = True # Get the indexes of the distal segments of this cell segmentsForCell = self.temporalPooler.connections.segmentsForCell(cellIdx) # Add the segments that appeared after last iteration for segIdx in segmentsForCell: # Check if segment already exists in the cell segFound = False for segment in cell.segments: if segment.index == segIdx: segFound = True break # If segment is new, add it to cell if not segFound: segment = Segment(SegmentType.distal) segment.index = segIdx cell.segments.append(segment) # Update distal segments for segment in cell.segments: segIdx = segment.index # If segment not found in segments indexes returned in last iteration mark it as removed if segIdx in segmentsForCell: # Update segment's state if segIdx in self.temporalPooler.activeSegments: segment.isActive[maxTimeSteps - 1] = True else: segment.isActive[maxTimeSteps - 1] = False # Get the indexes of the synapses of this segment synapsesForSegment = self.temporalPooler.connections.synapsesForSegment(segIdx) # Add the synapses that appeared after last iteration for synIdx in synapsesForSegment: # Check if synapse already exists in the segment synFound = False for synapse in segment.synapses: if synapse.index == synIdx: synFound = True break # If synapse is new, add it to segment if not synFound: synapse = Synapse() synapse.index = synIdx segment.synapses.append(synapse) # Update synapses for synapse in segment.synapses: synIdx = synapse.index # If synapse not found in synapses indexes returned in last iteration mark it as removed if synIdx in synapsesForSegment: # Update synapse's state (_, sourceCellIdx, permanence) = self.temporalPooler.connections.dataForSynapse(synIdx) synapse.permanence[maxTimeSteps - 1] = permanence if permanence >= self.distalSynConnectedPerm: synapse.isConnected[maxTimeSteps - 1] = True else: synapse.isConnected[maxTimeSteps - 1] = False # Get cell given cell's index for sourceColumn in self.columns: for sourceCell in sourceColumn.cells: if sourceCell.index == sourceCellIdx: synapse.inputElem = sourceCell else: synapse.isRemoved[maxTimeSteps - 1] = True else: segment.isRemoved[maxTimeSteps - 1] = True
def updateTemporalElements(self):
"""
Update elements regarding temporal pooler
"""
# Update cells, distal segments and synapses according to active columns
for colIdx in range(len(self.columns)):
column = self.columns[colIdx]
# Mark proximal segment and its connected synapses as predicted
if column.segment.isPredicted[maxStoredSteps - 1]:
for synapse in column.segment.synapses:
if synapse.isConnected[maxStoredSteps - 1]:
synapse.isPredicted[maxStoredSteps - 1] = True
synapse.inputElem.isPredicted[maxStoredSteps -
1] = True
for cell in column.cells:
cellIdx = cell.index
# Update cell's states
if cellIdx in self.temporalPooler.winnerCells:
cell.isLearning[maxStoredSteps - 1] = True
if cellIdx in self.temporalPooler.activeCells:
cell.isActive[maxStoredSteps - 1] = True
if cellIdx in self.temporalPooler.predictiveCells:
cell.isPredicted[maxStoredSteps - 1] = True
# Get the indexes of the distal segments of this cell
segmentsForCell = self.temporalPooler.connections.segmentsForCell(
cellIdx)
# Add the segments that appeared after last iteration
for segIdx in segmentsForCell:
# Check if segment already exists in the cell
segFound = False
for segment in cell.segments:
if segment.indexTP == segIdx:
segFound = True
break
# If segment is new, add it to cell
if not segFound:
segment = Segment(SegmentType.distal)
segment.indexTP = segIdx
cell.segments.append(segment)
# Update distal segments
for segment in cell.segments:
segIdx = segment.indexTP
# If segment not found in segments indexes returned in last iteration mark it as removed
if segIdx in segmentsForCell:
# Update segment's state
if segIdx in self.temporalPooler.activeSegments:
segment.isActive[maxStoredSteps - 1] = True
else:
segment.isActive[maxStoredSteps - 1] = False
# Get the indexes of the synapses of this segment
synapsesForSegment = self.temporalPooler.connections.synapsesForSegment(
segIdx)
# Add the synapses that appeared after last iteration
for synIdx in synapsesForSegment:
# Check if synapse already exists in the segment
synFound = False
for synapse in segment.synapses:
if synapse.indexTP == synIdx:
synFound = True
break
# If synapse is new, add it to segment
if not synFound:
synapse = Synapse()
synapse.indexTP = synIdx
segment.synapses.append(synapse)
# Update synapses
for synapse in segment.synapses:
synIdx = synapse.indexTP
# If synapse not found in synapses indexes returned in last iteration mark it as removed
if synIdx in synapsesForSegment:
# Update synapse's state
(
_, sourceCellIdx, permanence
) = self.temporalPooler.connections.dataForSynapse(
synIdx)
synapse.permanence[maxStoredSteps -
1] = permanence
if permanence >= self.distalSynConnectedPerm:
synapse.isConnected[maxStoredSteps -
1] = True
else:
synapse.isConnected[maxStoredSteps -
1] = False
# Get cell given cell's index
for sourceColumn in self.columns:
for sourceCell in sourceColumn.cells:
if sourceCell.index == sourceCellIdx:
synapse.inputElem = sourceCell
else:
synapse.isRemoved[maxStoredSteps - 1] = True
else:
segment.isRemoved[maxStoredSteps - 1] = True
def updateTemporalElements(self): """ Update elements regarding temporal pooler """ # Update cells, distal segments and synapses according to active columns for colIdx in range(len(self.columns)): column = self.columns[colIdx] # Mark proximal segment and its connected synapses as predicted if column.segment.isPredicted[maxPreviousSteps - 1]: for synapse in column.segment.synapses: if synapse.isConnected[maxPreviousSteps - 1]: synapse.isPredicted[maxPreviousSteps - 1] = True synapse.inputElem.isPredicted[maxPreviousSteps - 1] = True # Mark proximal segment and its connected synapses that were predicted but are not active now if column.segment.isPredicted[maxPreviousSteps - 2]: if not column.segment.isActive[maxPreviousSteps - 1]: column.segment.isFalselyPredicted[maxPreviousSteps - 1] = True for synapse in column.segment.synapses: if (synapse.isPredicted[maxPreviousSteps - 2] and not synapse.isConnected[maxPreviousSteps - 1]) or (synapse.isConnected[maxPreviousSteps - 1] and synapse.inputElem.isFalselyPredicted[maxPreviousSteps - 1]): synapse.isFalselyPredicted[maxPreviousSteps - 1] = True for cell in column.cells: cellIdx = cell.index # Update cell's states if cellIdx in self.temporalPooler.winnerCells: cell.isLearning[maxPreviousSteps - 1] = True if cellIdx in self.temporalPooler.activeCells: cell.isActive[maxPreviousSteps - 1] = True if cellIdx in self.temporalPooler.predictiveCells: cell.isPredicted[maxPreviousSteps - 1] = True if cell.isPredicted[maxPreviousSteps - 2] and not cell.isActive[maxPreviousSteps - 1]: cell.isFalselyPredicted[maxPreviousSteps - 1] = True # Get the indexes of the distal segments of this cell segmentsForCell = self.temporalPooler.connections.segmentsForCell(cellIdx) # Add the segments that appeared after last iteration for segIdx in segmentsForCell: # Check if segment already exists in the cell segFound = False for segment in cell.segments: if segment.indexTP == segIdx: segFound = True break # If segment is new, add it to cell if not segFound: segment = Segment(SegmentType.distal) segment.indexTP = segIdx cell.segments.append(segment) # Update distal segments for segment in cell.segments: segIdx = segment.indexTP # If segment not found in segments indexes returned in last iteration mark it as removed if segIdx in segmentsForCell: # Update segment's state if segIdx in self.temporalPooler.activeSegments: segment.isActive[maxPreviousSteps - 1] = True else: segment.isActive[maxPreviousSteps - 1] = False # Get the indexes of the synapses of this segment synapsesForSegment = self.temporalPooler.connections.synapsesForSegment(segIdx) # Add the synapses that appeared after last iteration for synIdx in synapsesForSegment: # Check if synapse already exists in the segment synFound = False for synapse in segment.synapses: if synapse.indexTP == synIdx: synFound = True break # If synapse is new, add it to segment if not synFound: synapse = Synapse() synapse.indexTP = synIdx segment.synapses.append(synapse) # Update synapses for synapse in segment.synapses: synIdx = synapse.indexTP # If synapse not found in synapses indexes returned in last iteration mark it as removed if synIdx in synapsesForSegment: # Update synapse's state (_, sourceCellAbsIdx, permanence) = self.temporalPooler.connections.dataForSynapse(synIdx) synapse.permanence[maxPreviousSteps - 1] = permanence if permanence >= self.distalSynConnectedPerm: synapse.isConnected[maxPreviousSteps - 1] = True else: synapse.isConnected[maxPreviousSteps - 1] = False # Get cell given cell's index sourceColIdx = sourceCellAbsIdx / self.numCellsPerColumn sourceCellRelIdx = sourceCellAbsIdx % self.numCellsPerColumn sourceCell = self.columns[sourceColIdx].cells[sourceCellRelIdx] synapse.inputElem = sourceCell else: synapse.isRemoved[maxPreviousSteps - 1] = True else: segment.isRemoved[maxPreviousSteps - 1] = True
def updateTemporalElements(self):
"""
Update elements regarding temporal pooler
"""
# Update cells, distal segments and synapses according to active columns
for colIdx in range(len(self.columns)):
column = self.columns[colIdx]
# Mark proximal segment and its connected synapses as predicted
if column.segment.isPredicted.atCurrStep():
for synapse in column.segment.synapses:
if synapse.isConnected.atCurrStep():
synapse.isPredicted.setForCurrStep(True)
synapse.inputElem.isPredicted.setForCurrStep(True)
# Mark proximal segment and its connected synapses that were predicted but are not active now
if column.segment.isPredicted.atPreviousStep():
if not column.segment.isActive.atCurrStep():
column.segment.isFalselyPredicted.setForCurrStep(True)
for synapse in column.segment.synapses:
if (synapse.isPredicted.atPreviousStep()
and not synapse.isConnected.atCurrStep()
) or (
synapse.isConnected.atCurrStep() and
synapse.inputElem.isFalselyPredicted.atCurrStep()):
synapse.isFalselyPredicted.setForCurrStep(True)
for cell in column.cells:
cellIdx = cell.index
# Update cell's states
if cellIdx in self.temporalPooler.winnerCells:
cell.isLearning.setForCurrStep(True)
if cellIdx in self.temporalPooler.activeCells:
cell.isActive.setForCurrStep(True)
if cellIdx in self.temporalPooler.predictiveCells:
cell.isPredicted.setForCurrStep(True)
if cell.isPredicted.atPreviousStep(
) and not cell.isActive.atCurrStep():
cell.isFalselyPredicted.setForCurrStep(True)
# Get the indexes of the distal segments of this cell
segmentsForCell = self.temporalPooler.connections.segmentsForCell(
cellIdx)
# Add the segments that appeared after last iteration
for segIdx in segmentsForCell:
# Check if segment already exists in the cell
segFound = False
for segment in cell.segments:
if segment.indexTP == segIdx:
segFound = True
break
# If segment is new, add it to cell
if not segFound:
segment = Segment(SegmentType.distal)
segment.indexTP = segIdx
cell.segments.append(segment)
# Update distal segments
for segment in cell.segments:
segIdx = segment.indexTP
# If segment not found in segments indexes returned in last iteration mark it as removed
if segIdx in segmentsForCell:
# Update segment's state
if segIdx in self.temporalPooler.activeSegments:
segment.isActive.setForCurrStep(True)
else:
segment.isActive.setForCurrStep(False)
# Get the indexes of the synapses of this segment
synapsesForSegment = self.temporalPooler.connections.synapsesForSegment(
segIdx)
# Add the synapses that appeared after last iteration
for synIdx in synapsesForSegment:
# Check if synapse already exists in the segment
synFound = False
for synapse in segment.synapses:
if synapse.indexTP == synIdx:
synFound = True
break
# If synapse is new, add it to segment
if not synFound:
synapse = Synapse()
synapse.indexTP = synIdx
segment.synapses.append(synapse)
# Update synapses
for synapse in segment.synapses:
synIdx = synapse.indexTP
# If synapse not found in synapses indexes returned in last iteration mark it as removed
if synIdx in synapsesForSegment:
# Update synapse's state
(
_, sourceCellAbsIdx, permanence
) = self.temporalPooler.connections.dataForSynapse(
synIdx)
synapse.permanence.setForCurrStep(permanence)
if permanence >= self.distalSynConnectedPerm:
synapse.isConnected.setForCurrStep(True)
else:
synapse.isConnected.setForCurrStep(False)
# Get cell given cell's index
sourceColIdx = sourceCellAbsIdx / self.numCellsPerColumn
sourceCellRelIdx = sourceCellAbsIdx % self.numCellsPerColumn
sourceCell = self.columns[sourceColIdx].cells[
sourceCellRelIdx]
synapse.inputElem = sourceCell
else:
synapse.isRemoved.setForCurrStep(True)
else:
segment.isRemoved.setForCurrStep(True)