Python Connections.segmentsForCell方法代码示例

# 需要导入模块: from nupic.research.connections import Connections [as 别名]
# 或者: from nupic.research.connections.Connections import segmentsForCell [as 别名]
  def testCreateSegment(self):
    connections = Connections(1024)

    segment1 = connections.createSegment(10)
    self.assertEqual(segment1.cell, 10)

    segment2 = connections.createSegment(10)
    self.assertEqual(segment2.cell, 10)

    self.assertEqual([segment1, segment2],
                     list(connections.segmentsForCell(10)))

# 需要导入模块: from nupic.research.connections import Connections [as 别名]
# 或者: from nupic.research.connections.Connections import segmentsForCell [as 别名]
  def testCreateSegmentReuse(self):
    connections = Connections(1024, 2)

    segment1 = connections.createSegment(42)
    connections.createSynapse(segment1, 1, .5)
    connections.createSynapse(segment1, 2, .5)

    # Let some time pass.
    connections.startNewIteration();
    connections.startNewIteration();
    connections.startNewIteration();

    # Create a segment with 3 synapse.
    segment2 = connections.createSegment(42)
    connections.createSynapse(segment2, 1, .5)
    connections.createSynapse(segment2, 2, .5)
    connections.createSynapse(segment2, 3, .5)
    connections.startNewIteration();

    # Give the first segment some activity.
    connections.recordSegmentActivity(segment1)

    # Create a new segment with 1 synapse.
    segment3 = connections.createSegment(42);
    connections.createSynapse(segment3, 1, .5)

    segments = connections.segmentsForCell(42)
    self.assertEqual(2, len(segments))

    # Verify first segment is still there with the same synapses.
    self.assertEqual(set([1, 2]),
                     set(synapse.presynapticCell for synapse in
                         connections.synapsesForSegment(segments[0])))

    # Verify second segment has been replaced.
    self.assertEqual(set([1]),
                     set(synapse.presynapticCell for synapse in
                         connections.synapsesForSegment(segments[1])))

    # Verify the flatIdxs were properly reused.
    self.assertLess(segment1.flatIdx, 2)
    self.assertLess(segment3.flatIdx, 2)
    self.assertTrue(segment1 is connections.segmentForFlatIdx(segment1.flatIdx))
    self.assertTrue(segment3 is connections.segmentForFlatIdx(segment3.flatIdx))

# 需要导入模块: from nupic.research.connections import Connections [as 别名]
# 或者: from nupic.research.connections.Connections import segmentsForCell [as 别名]

#.........这里部分代码省略.........
    bestCell = None
    bestSegment = None

    for cell in cells:
      segment, numActiveSynapses = self.bestMatchingSegment(cell, activeCells)

      if segment is not None and numActiveSynapses > maxSynapses:
        maxSynapses = numActiveSynapses
        bestCell = cell
        bestSegment = segment

    if bestCell is None:
      bestCell = self.leastUsedCell(cells)

    return bestCell, bestSegment


  def bestMatchingSegment(self, cell, activeCells):
    """
    Gets the segment on a cell with the largest number of activate synapses,
    including all synapses with non-zero permanences.

    @param cell        (int) Cell index
    @param activeCells (set) Indices of active cells

    @return (tuple) Contains:
                      `segment`                 (int),
                      `connectedActiveSynapses` (set)
    """
    maxSynapses = self.minThreshold
    bestSegment = None
    bestNumActiveSynapses = None

    for segment in self.connections.segmentsForCell(cell):
      numActiveSynapses = 0

      for synapse in self.connections.synapsesForSegment(segment):
        synapseData = self.connections.dataForSynapse(synapse)
        if ( (synapseData.presynapticCell in activeCells) and
            synapseData.permanence > 0):
          numActiveSynapses += 1

      if numActiveSynapses >= maxSynapses:
        maxSynapses = numActiveSynapses
        bestSegment = segment
        bestNumActiveSynapses = numActiveSynapses

    return bestSegment, bestNumActiveSynapses


  def leastUsedCell(self, cells):
    """
    Gets the cell with the smallest number of segments.
    Break ties randomly.

    @param cells (set) Indices of cells

    @return (int) Cell index
    """
    leastUsedCells = set()
    minNumSegments = float("inf")

    for cell in cells:
      numSegments = len(self.connections.segmentsForCell(cell))

      if numSegments < minNumSegments: