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)))
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)))
def __init__(self,
columnDimensions=(2048, ),
cellsPerColumn=32,
activationThreshold=13,
initialPermanence=0.21,
connectedPermanence=0.50,
minThreshold=10,
maxNewSynapseCount=20,
permanenceIncrement=0.10,
permanenceDecrement=0.10,
seed=42):
"""
Translate parameters and initialize member variables
specific to TemporalMemory
"""
numberOfCols = 1
for n in columnDimensions:
numberOfCols *= n
super(TemporalMemoryShim,
self).__init__(numberOfCols=numberOfCols,
cellsPerColumn=cellsPerColumn,
initialPerm=initialPermanence,
connectedPerm=connectedPermanence,
minThreshold=minThreshold,
newSynapseCount=maxNewSynapseCount,
permanenceInc=permanenceIncrement,
permanenceDec=permanenceDecrement,
permanenceMax=1.0,
globalDecay=0,
activationThreshold=activationThreshold,
seed=seed)
self.connections = Connections(numberOfCols * cellsPerColumn)
self.predictiveCells = set()
def read(cls, proto):
"""Deserialize from proto instance.
:param proto: (TemporalMemoryShimProto) the proto instance to read from
"""
tm = super(TemporalMemoryShim, cls).read(proto.baseTM)
tm.predictiveCells = set(proto.predictedState)
tm.connections = Connections.read(proto.conncetions)
def read(cls, proto):
"""Deserialize from proto instance.
:param proto: (TemporalMemoryShimProto) the proto instance to read from
"""
tm = super(TemporalMemoryShim, cls).read(proto.baseTM)
tm.predictiveCells = set(proto.predictedState)
tm.connections = Connections.read(proto.conncetions)
def connectionsFactory(*args, **kwargs):
"""
Create a Connections instance. TemporalMemory subclasses may override this
method to choose a different Connections implementation, or to augment the
instance otherwise returned by the default Connections implementation.
See Connections for constructor signature and usage.
@return: Connections instance
"""
return Connections(*args, **kwargs)
def testUpdateSynapsePermanence(self):
""" Creates a synapse and updates its permanence, and makes sure that its
data was correctly updated.
"""
connections = Connections(1024)
segment = connections.createSegment(10)
synapse = connections.createSynapse(segment, 50, .34)
connections.updateSynapsePermanence(synapse, .21)
synapseData = connections.dataForSynapse(synapse)
self.assertAlmostEqual(synapseData.permanence, .21)
def connectionsFactory(*args, **kwargs):
"""
Create a :class:`~nupic.algorithms.connections.Connections` instance.
:class:`TemporalMemory` subclasses may override this method to choose a
different :class:`~nupic.algorithms.connections.Connections` implementation,
or to augment the instance otherwise returned by the default
:class:`~nupic.algorithms.connections.Connections` implementation.
See :class:`~nupic.algorithms.connections.Connections` for constructor
signature and usage.
:returns: :class:`~nupic.algorithms.connections.Connections` instance
"""
return Connections(*args, **kwargs)
def testDestroySynapse(self):
""" Creates a segment, creates a number of synapses on it, destroys a
synapse, and makes sure it got destroyed.
"""
connections = Connections(1024)
segment = connections.createSegment(20)
synapse1 = connections.createSynapse(segment, 80, .85)
synapse2 = connections.createSynapse(segment, 81, .85)
synapse3 = connections.createSynapse(segment, 82, .15)
self.assertEqual(3, connections.numSynapses())
connections.destroySynapse(synapse2)
self.assertEqual(2, connections.numSynapses())
self.assertEqual(set([synapse1, synapse3]),
connections.synapsesForSegment(segment))
(numActiveConnected,
numActivePotential) = connections.computeActivity([80, 81, 82], .5)
self.assertEqual(1, numActiveConnected[segment.flatIdx])
self.assertEqual(2, numActivePotential[segment.flatIdx])
def testUpdateSynapsePermanence(self):
""" Creates a synapse and updates its permanence, and makes sure that its
data was correctly updated.
"""
connections = Connections(1024)
segment = connections.createSegment(10)
synapse = connections.createSynapse(segment, 50, .34)
connections.updateSynapsePermanence(synapse, .21)
synapseData = connections.dataForSynapse(synapse)
self.assertAlmostEqual(synapseData.permanence, .21)
def __init__(self, l4N, l4W, numModules, moduleDimensions,
maxActivePerModule, l6ActivationThreshold):
self.numModules = numModules
self.moduleDimensions = moduleDimensions
self._cellsPerModule = np.prod(moduleDimensions)
self.maxActivePerModule = maxActivePerModule
self.l4N = l4N
self.l4W = l4W
self.l6ActivationThreshold = l6ActivationThreshold
self.l4TM = TemporalMemory(
columnCount=l4N,
basalInputSize=numModules * self._cellsPerModule,
cellsPerColumn=4,
#activationThreshold=int(numModules / 2) + 1,
#reducedBasalThreshold=int(numModules / 2) + 1,
activationThreshold=1,
reducedBasalThreshold=1,
initialPermanence=1.0,
connectedPermanence=0.5,
minThreshold=1,
sampleSize=numModules,
permanenceIncrement=1.0,
permanenceDecrement=0.0,
)
self.l6Connections = [
Connections(numCells=self._cellsPerModule)
for _ in xrange(numModules)
]
self.pooler = ColumnPooler(inputWidth=self.numModules *
self._cellsPerModule, )
self.classifier = KNNClassifier(k=1, distanceMethod="rawOverlap")
#self.classifier = KNNClassifier(k=1, distanceMethod="norm")
# Active state
self.activeL6Cells = [[] for _ in xrange(numModules)]
self.activeL5Cells = [[] for _ in xrange(numModules)]
self.predictedL6Cells = [set([]) for _ in xrange(numModules)]
# Debug state
self.activeL6BeforeMotor = [[] for _ in xrange(numModules)]
self.l6ToL4Map = collections.defaultdict(list)
def testSynapseReuse(self):
""" Creates a synapse over the synapses per segment limit, and verifies
that the lowest permanence synapse is removed to make room for the new
synapse.
"""
connections = Connections(1024, 1024, 2)
segment = connections.createSegment(10)
synapse1 = connections.createSynapse(segment, 50, .34)
synapse2 = connections.createSynapse(segment, 51, .48)
synapses = connections.synapsesForSegment(segment)
self.assertEqual(set([synapse1, synapse2]), synapses)
# Add an additional synapse to force it over the limit of num synapses
# per segment.
connections.createSynapse(segment, 52, .52)
# Ensure lower permanence synapse was removed.
self.assertEqual(
set([51, 52]),
set(synapse.presynapticCell
for synapse in connections.synapsesForSegment(segment)))
def testSynapseReuse(self):
""" Creates a synapse over the synapses per segment limit, and verifies
that the lowest permanence synapse is removed to make room for the new
synapse.
"""
connections = Connections(1024, 1024, 2)
segment = connections.createSegment(10)
synapse1 = connections.createSynapse(segment, 50, .34)
synapse2 = connections.createSynapse(segment, 51, .48)
synapses = connections.synapsesForSegment(segment)
self.assertEqual(set([synapse1, synapse2]), synapses)
# Add an additional synapse to force it over the limit of num synapses
# per segment.
connections.createSynapse(segment, 52, .52)
# Ensure lower permanence synapse was removed.
self.assertEqual(set([51, 52]),
set(synapse.presynapticCell
for synapse in
connections.synapsesForSegment(segment)))
def testDestroySegmentsThenReachLimit(self):
""" Destroy some segments then verify that the maxSegmentsPerCell is still
correctly applied.
"""
connections = Connections(1024, 2, 2)
segment1 = connections.createSegment(11)
segment2 = connections.createSegment(11)
self.assertEqual(2, connections.numSegments())
connections.destroySegment(segment1)
connections.destroySegment(segment2)
self.assertEqual(0, connections.numSegments())
connections.createSegment(11)
self.assertEqual(1, connections.numSegments())
connections.createSegment(11)
self.assertEqual(2, connections.numSegments())
segment3 = connections.createSegment(11)
self.assertEqual(2, connections.numSegments(11))
self.assertEqual(2, connections.numSegments())
def read(cls, proto):
"""
Reads deserialized data from proto object.
:param proto: (DynamicStructBuilder) Proto object
:returns: (:class:TemporalMemory) TemporalMemory instance
"""
tm = object.__new__(cls)
# capnp fails to save a tuple, so proto.columnDimensions was forced to
# serialize as a list. We prefer a tuple, however, because columnDimensions
# should be regarded as immutable.
tm.columnDimensions = tuple(proto.columnDimensions)
tm.cellsPerColumn = int(proto.cellsPerColumn)
tm.activationThreshold = int(proto.activationThreshold)
tm.initialPermanence = proto.initialPermanence
tm.connectedPermanence = proto.connectedPermanence
tm.minThreshold = int(proto.minThreshold)
tm.maxNewSynapseCount = int(proto.maxNewSynapseCount)
tm.permanenceIncrement = proto.permanenceIncrement
tm.permanenceDecrement = proto.permanenceDecrement
tm.predictedSegmentDecrement = proto.predictedSegmentDecrement
tm.maxSegmentsPerCell = int(proto.maxSegmentsPerCell)
tm.maxSynapsesPerSegment = int(proto.maxSynapsesPerSegment)
tm.connections = Connections.read(proto.connections)
#pylint: disable=W0212
tm._random = Random()
tm._random.read(proto.random)
#pylint: enable=W0212
tm.activeCells = [int(x) for x in proto.activeCells]
tm.winnerCells = [int(x) for x in proto.winnerCells]
flatListLength = tm.connections.segmentFlatListLength()
tm.numActiveConnectedSynapsesForSegment = [0] * flatListLength
tm.numActivePotentialSynapsesForSegment = [0] * flatListLength
tm.lastUsedIterationForSegment = [0] * flatListLength
tm.activeSegments = []
tm.matchingSegments = []
for protoSegment in proto.activeSegments:
tm.activeSegments.append(
tm.connections.getSegment(protoSegment.cell,
protoSegment.idxOnCell))
for protoSegment in proto.matchingSegments:
tm.matchingSegments.append(
tm.connections.getSegment(protoSegment.cell,
protoSegment.idxOnCell))
for protoSegment in proto.numActivePotentialSynapsesForSegment:
segment = tm.connections.getSegment(protoSegment.cell,
protoSegment.idxOnCell)
tm.numActivePotentialSynapsesForSegment[segment.flatIdx] = (int(
protoSegment.number))
tm.iteration = long(proto.iteration)
for protoSegment in proto.lastUsedIterationForSegment:
segment = tm.connections.getSegment(protoSegment.cell,
protoSegment.idxOnCell)
tm.lastUsedIterationForSegment[segment.flatIdx] = (long(
protoSegment.number))
return tm
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))
def testComputeActivity(self):
""" Creates a sample set of connections, and makes sure that computing the
activity for a collection of cells with no activity returns the right
activity data.
"""
connections = Connections(1024)
# Cell with 1 segment.
# Segment with:
# - 1 connected synapse: active
# - 2 matching synapses
segment1a = connections.createSegment(10)
connections.createSynapse(segment1a, 150, .85)
connections.createSynapse(segment1a, 151, .15)
# Cell with 1 segment.
# Segment with:
# - 2 connected synapse: 2 active
# - 3 matching synapses: 3 active
segment2a = connections.createSegment(20)
connections.createSynapse(segment2a, 80, .85)
connections.createSynapse(segment2a, 81, .85)
synapse = connections.createSynapse(segment2a, 82, .85)
connections.updateSynapsePermanence(synapse, .15)
inputVec = [50, 52, 53, 80, 81, 82, 150, 151]
(numActiveConnected,
numActivePotential) = connections.computeActivity(inputVec, .5)
self.assertEqual(1, numActiveConnected[segment1a.flatIdx])
self.assertEqual(2, numActivePotential[segment1a.flatIdx])
self.assertEqual(2, numActiveConnected[segment2a.flatIdx])
self.assertEqual(3, numActivePotential[segment2a.flatIdx])
def testReuseSegmentWithDestroyedSynapses(self):
""" Destroy a segment that has a destroyed synapse and a non-destroyed
synapse. Create a new segment in the same place. Make sure its synapse
count is correct.
"""
connections = Connections(1024)
segment = connections.createSegment(11)
synapse1 = connections.createSynapse(segment, 201, .85)
connections.createSynapse(segment, 202, .85)
connections.destroySynapse(synapse1)
self.assertEqual(1, connections.numSynapses(segment))
connections.destroySegment(segment)
reincarnated = connections.createSegment(11)
self.assertEqual(0, connections.numSynapses(reincarnated))
self.assertEqual(0, len(connections.synapsesForSegment(reincarnated)))
def testReuseSegmentWithDestroyedSynapses(self):
""" Destroy a segment that has a destroyed synapse and a non-destroyed
synapse. Create a new segment in the same place. Make sure its synapse
count is correct.
"""
connections = Connections(1024)
segment = connections.createSegment(11)
synapse1 = connections.createSynapse(segment, 201, .85)
connections.createSynapse(segment, 202, .85)
connections.destroySynapse(synapse1)
self.assertEqual(1, connections.numSynapses(segment))
connections.destroySegment(segment)
reincarnated = connections.createSegment(11)
self.assertEqual(0, connections.numSynapses(reincarnated))
self.assertEqual(0, len(connections.synapsesForSegment(reincarnated)))
def testDestroySegmentWithDestroyedSynapses(self):
""" Destroy a segment that has a destroyed synapse and a non-destroyed
synapse. Make sure nothing gets double-destroyed.
"""
connections = Connections(1024)
segment1 = connections.createSegment(11)
segment2 = connections.createSegment(12)
connections.createSynapse(segment1, 101, .85)
synapse2a = connections.createSynapse(segment2, 201, .85)
connections.createSynapse(segment2, 202, .85)
self.assertEqual(3, connections.numSynapses())
connections.destroySynapse(synapse2a)
self.assertEqual(2, connections.numSegments())
self.assertEqual(2, connections.numSynapses())
connections.destroySegment(segment2)
self.assertEqual(1, connections.numSegments())
self.assertEqual(1, connections.numSynapses())
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))
def testReachSegmentLimitMultipleTimes(self):
""" Hit the maxSynapsesPerSegment threshold multiple times. Make sure it
works more than once.
"""
connections = Connections(1024, 2, 2)
segment = connections.createSegment(10)
connections.createSynapse(segment, 201, .85)
self.assertEqual(1, connections.numSynapses())
connections.createSynapse(segment, 202, .9)
self.assertEqual(2, connections.numSynapses())
connections.createSynapse(segment, 203, .8)
self.assertEqual(2, connections.numSynapses())
synapse = connections.createSynapse(segment, 204, .8)
self.assertEqual(2, connections.numSynapses())
def testDestroySynapsesThenReachLimit(self):
""" Destroy some synapses then verify that the maxSynapsesPerSegment is
still correctly applied.
"""
connections = Connections(1024, 2, 2)
segment = connections.createSegment(10)
synapse1 = connections.createSynapse(segment, 201, .85)
synapse2 = connections.createSynapse(segment, 202, .85)
self.assertEqual(2, connections.numSynapses())
connections.destroySynapse(synapse1)
connections.destroySynapse(synapse2)
self.assertEqual(0, connections.numSynapses())
connections.createSynapse(segment, 201, .85)
self.assertEqual(1, connections.numSynapses())
connections.createSynapse(segment, 202, .90)
self.assertEqual(2, connections.numSynapses())
synapse3 = connections.createSynapse(segment, 203, .8)
self.assertEqual(2, connections.numSynapses())
def testPathsNotInvalidatedByOtherDestroys(self):
""" Creates segments and synapses, then destroys segments and synapses on
either side of them and verifies that existing Segment and Synapse
instances still point to the same segment / synapse as before.
"""
connections = Connections(1024)
segment1 = connections.createSegment(11)
connections.createSegment(12)
segment3 = connections.createSegment(13)
connections.createSegment(14)
segment5 = connections.createSegment(15)
synapse1 = connections.createSynapse(segment3, 201, .85)
synapse2 = connections.createSynapse(segment3, 202, .85)
synapse3 = connections.createSynapse(segment3, 203, .85)
synapse4 = connections.createSynapse(segment3, 204, .85)
synapse5 = connections.createSynapse(segment3, 205, .85)
self.assertEqual(203, synapse3.presynapticCell)
connections.destroySynapse(synapse1)
self.assertEqual(203, synapse3.presynapticCell)
connections.destroySynapse(synapse5)
self.assertEqual(203, synapse3.presynapticCell)
connections.destroySegment(segment1)
self.assertEqual(set([synapse2, synapse3, synapse4]),
connections.synapsesForSegment(segment3))
connections.destroySegment(segment5)
self.assertEqual(set([synapse2, synapse3, synapse4]),
connections.synapsesForSegment(segment3))
self.assertEqual(203, synapse3.presynapticCell)
def testDestroySegmentWithDestroyedSynapses(self):
""" Destroy a segment that has a destroyed synapse and a non-destroyed
synapse. Make sure nothing gets double-destroyed.
"""
connections = Connections(1024)
segment1 = connections.createSegment(11)
segment2 = connections.createSegment(12)
connections.createSynapse(segment1, 101, .85)
synapse2a = connections.createSynapse(segment2, 201, .85)
connections.createSynapse(segment2, 202, .85)
self.assertEqual(3, connections.numSynapses())
connections.destroySynapse(synapse2a)
self.assertEqual(2, connections.numSegments())
self.assertEqual(2, connections.numSynapses())
connections.destroySegment(segment2)
self.assertEqual(1, connections.numSegments())
self.assertEqual(1, connections.numSynapses())
def testComputeActivity(self):
""" Creates a sample set of connections, and makes sure that computing the
activity for a collection of cells with no activity returns the right
activity data.
"""
connections = Connections(1024)
# Cell with 1 segment.
# Segment with:
# - 1 connected synapse: active
# - 2 matching synapses
segment1a = connections.createSegment(10)
connections.createSynapse(segment1a, 150, .85)
connections.createSynapse(segment1a, 151, .15)
# Cell with 1 segment.
# Segment with:
# - 2 connected synapse: 2 active
# - 3 matching synapses: 3 active
segment2a = connections.createSegment(20)
connections.createSynapse(segment2a, 80, .85)
connections.createSynapse(segment2a, 81, .85)
synapse = connections.createSynapse(segment2a, 82, .85)
connections.updateSynapsePermanence(synapse, .15)
inputVec = [50, 52, 53, 80, 81, 82, 150, 151]
(numActiveConnected,
numActivePotential) = connections.computeActivity(inputVec, .5)
self.assertEqual(1, numActiveConnected[segment1a.flatIdx])
self.assertEqual(2, numActivePotential[segment1a.flatIdx])
self.assertEqual(2, numActiveConnected[segment2a.flatIdx])
self.assertEqual(3, numActivePotential[segment2a.flatIdx])
def testWriteRead(self):
c1 = Connections(1024)
# Add data before serializing
s1 = c1.createSegment(0)
c1.createSynapse(s1, 254, 0.1173)
s2 = c1.createSegment(100)
c1.createSynapse(s2, 20, 0.3)
c1.createSynapse(s1, 40, 0.3)
s3 = c1.createSegment(0)
c1.createSynapse(s3, 0, 0.5)
c1.createSynapse(s3, 1, 0.5)
s4 = c1.createSegment(10)
c1.createSynapse(s4, 0, 0.5)
c1.createSynapse(s4, 1, 0.5)
c1.destroySegment(s4)
proto1 = ConnectionsProto_capnp.ConnectionsProto.new_message()
c1.write(proto1)
# Write the proto to a temp file and read it back into a new proto
with tempfile.TemporaryFile() as f:
proto1.write(f)
f.seek(0)
proto2 = ConnectionsProto_capnp.ConnectionsProto.read(f)
# Load the deserialized proto
c2 = Connections.read(proto2)
# Check that the two connections objects are functionally equal
self.assertEqual(c1, c2)
def testDestroySynapsesThenReachLimit(self):
""" Destroy some synapses then verify that the maxSynapsesPerSegment is
still correctly applied.
"""
connections = Connections(1024, 2, 2)
segment = connections.createSegment(10)
synapse1 = connections.createSynapse(segment, 201, .85)
synapse2 = connections.createSynapse(segment, 202, .85)
self.assertEqual(2, connections.numSynapses())
connections.destroySynapse(synapse1)
connections.destroySynapse(synapse2)
self.assertEqual(0, connections.numSynapses())
connections.createSynapse(segment, 201, .85)
self.assertEqual(1, connections.numSynapses())
connections.createSynapse(segment, 202, .90)
self.assertEqual(2, connections.numSynapses())
synapse3 = connections.createSynapse(segment, 203, .8)
self.assertEqual(2, connections.numSynapses())
def testWriteRead(self):
c1 = Connections(1024)
# Add data before serializing
s1 = c1.createSegment(0)
c1.createSynapse(s1, 254, 0.1173)
s2 = c1.createSegment(100)
c1.createSynapse(s2, 20, 0.3)
c1.createSynapse(s1, 40, 0.3)
s3 = c1.createSegment(0)
c1.createSynapse(s3, 0, 0.5)
c1.createSynapse(s3, 1, 0.5)
s4 = c1.createSegment(10)
c1.createSynapse(s4, 0, 0.5)
c1.createSynapse(s4, 1, 0.5)
c1.destroySegment(s4)
proto1 = ConnectionsProto_capnp.ConnectionsProto.new_message()
c1.write(proto1)
# Write the proto to a temp file and read it back into a new proto
with tempfile.TemporaryFile() as f:
proto1.write(f)
f.seek(0)
proto2 = ConnectionsProto_capnp.ConnectionsProto.read(f)
# Load the deserialized proto
c2 = Connections.read(proto2)
# Check that the two connections objects are functionally equal
self.assertEqual(c1, c2)
def testDestroySegment(self):
""" Creates a segment, destroys it, and makes sure it got destroyed along
with all of its synapses.
"""
connections = Connections(1024)
connections.createSegment(10)
segment2 = connections.createSegment(20)
connections.createSegment(30)
connections.createSegment(40)
connections.createSynapse(segment2, 80, 0.85)
connections.createSynapse(segment2, 81, 0.85)
connections.createSynapse(segment2, 82, 0.15)
self.assertEqual(4, connections.numSegments())
self.assertEqual(3, connections.numSynapses())
connections.destroySegment(segment2)
self.assertEqual(3, connections.numSegments())
self.assertEqual(0, connections.numSynapses())
(numActiveConnected,
numActivePotential) = connections.computeActivity([80, 81, 82], 0.5)
self.assertEqual(0, numActiveConnected[segment2.flatIdx])
self.assertEqual(0, numActivePotential[segment2.flatIdx])
def testDestroySegment(self):
""" Creates a segment, destroys it, and makes sure it got destroyed along
with all of its synapses.
"""
connections = Connections(1024)
connections.createSegment(10)
segment2 = connections.createSegment(20)
connections.createSegment(30)
connections.createSegment(40)
connections.createSynapse(segment2, 80, 0.85)
connections.createSynapse(segment2, 81, 0.85)
connections.createSynapse(segment2, 82, 0.15)
self.assertEqual(4, connections.numSegments())
self.assertEqual(3, connections.numSynapses())
connections.destroySegment(segment2)
self.assertEqual(3, connections.numSegments())
self.assertEqual(0, connections.numSynapses())
(numActiveConnected,
numActivePotential) = connections.computeActivity([80, 81, 82], 0.5)
self.assertEqual(0, numActiveConnected[segment2.flatIdx])
self.assertEqual(0, numActivePotential[segment2.flatIdx])
def testDestroySynapse(self):
""" Creates a segment, creates a number of synapses on it, destroys a
synapse, and makes sure it got destroyed.
"""
connections = Connections(1024)
segment = connections.createSegment(20)
synapse1 = connections.createSynapse(segment, 80, .85)
synapse2 = connections.createSynapse(segment, 81, .85)
synapse3 = connections.createSynapse(segment, 82, .15)
self.assertEqual(3, connections.numSynapses())
connections.destroySynapse(synapse2)
self.assertEqual(2, connections.numSynapses())
self.assertEqual(set([synapse1, synapse3]),
connections.synapsesForSegment(segment))
(numActiveConnected,
numActivePotential) = connections.computeActivity([80, 81, 82], .5)
self.assertEqual(1, numActiveConnected[segment.flatIdx])
self.assertEqual(2, numActivePotential[segment.flatIdx])
def read(cls, proto):
"""
Reads deserialized data from proto object.
:param proto: (DynamicStructBuilder) Proto object
:returns: (:class:TemporalMemory) TemporalMemory instance
"""
tm = object.__new__(cls)
# capnp fails to save a tuple, so proto.columnDimensions was forced to
# serialize as a list. We prefer a tuple, however, because columnDimensions
# should be regarded as immutable.
tm.columnDimensions = tuple(proto.columnDimensions)
tm.cellsPerColumn = int(proto.cellsPerColumn)
tm.activationThreshold = int(proto.activationThreshold)
tm.initialPermanence = round(proto.initialPermanence, EPSILON_ROUND)
tm.connectedPermanence = round(proto.connectedPermanence, EPSILON_ROUND)
tm.minThreshold = int(proto.minThreshold)
tm.maxNewSynapseCount = int(proto.maxNewSynapseCount)
tm.permanenceIncrement = round(proto.permanenceIncrement, EPSILON_ROUND)
tm.permanenceDecrement = round(proto.permanenceDecrement, EPSILON_ROUND)
tm.predictedSegmentDecrement = round(proto.predictedSegmentDecrement,
EPSILON_ROUND)
tm.maxSegmentsPerCell = int(proto.maxSegmentsPerCell)
tm.maxSynapsesPerSegment = int(proto.maxSynapsesPerSegment)
tm.connections = Connections.read(proto.connections)
#pylint: disable=W0212
tm._random = Random()
tm._random.read(proto.random)
#pylint: enable=W0212
tm.activeCells = [int(x) for x in proto.activeCells]
tm.winnerCells = [int(x) for x in proto.winnerCells]
flatListLength = tm.connections.segmentFlatListLength()
tm.numActiveConnectedSynapsesForSegment = [0] * flatListLength
tm.numActivePotentialSynapsesForSegment = [0] * flatListLength
tm.lastUsedIterationForSegment = [0] * flatListLength
tm.activeSegments = []
tm.matchingSegments = []
for protoSegment in proto.activeSegments:
tm.activeSegments.append(
tm.connections.getSegment(protoSegment.cell,
protoSegment.idxOnCell))
for protoSegment in proto.matchingSegments:
tm.matchingSegments.append(
tm.connections.getSegment(protoSegment.cell,
protoSegment.idxOnCell))
for protoSegment in proto.numActivePotentialSynapsesForSegment:
segment = tm.connections.getSegment(protoSegment.cell,
protoSegment.idxOnCell)
tm.numActivePotentialSynapsesForSegment[segment.flatIdx] = (
int(protoSegment.number))
tm.iteration = long(proto.iteration)
for protoSegment in proto.lastUsedIterationForSegment:
segment = tm.connections.getSegment(protoSegment.cell,
protoSegment.idxOnCell)
tm.lastUsedIterationForSegment[segment.flatIdx] = (
long(protoSegment.number))
return tm
def testPathsNotInvalidatedByOtherDestroys(self):
""" Creates segments and synapses, then destroys segments and synapses on
either side of them and verifies that existing Segment and Synapse
instances still point to the same segment / synapse as before.
"""
connections = Connections(1024)
segment1 = connections.createSegment(11)
connections.createSegment(12)
segment3 = connections.createSegment(13)
connections.createSegment(14)
segment5 = connections.createSegment(15)
synapse1 = connections.createSynapse(segment3, 201, .85)
synapse2 = connections.createSynapse(segment3, 202, .85)
synapse3 = connections.createSynapse(segment3, 203, .85)
synapse4 = connections.createSynapse(segment3, 204, .85)
synapse5 = connections.createSynapse(segment3, 205, .85)
self.assertEqual(203, synapse3.presynapticCell)
connections.destroySynapse(synapse1)
self.assertEqual(203, synapse3.presynapticCell)
connections.destroySynapse(synapse5)
self.assertEqual(203, synapse3.presynapticCell)
connections.destroySegment(segment1)
self.assertEqual(set([synapse2, synapse3, synapse4]),
connections.synapsesForSegment(segment3))
connections.destroySegment(segment5)
self.assertEqual(set([synapse2, synapse3, synapse4]),
connections.synapsesForSegment(segment3))
self.assertEqual(203, synapse3.presynapticCell)
def testReachSegmentLimitMultipleTimes(self):
""" Hit the maxSynapsesPerSegment threshold multiple times. Make sure it
works more than once.
"""
connections = Connections(1024, 2, 2)
segment = connections.createSegment(10)
connections.createSynapse(segment, 201, .85)
self.assertEqual(1, connections.numSynapses())
connections.createSynapse(segment, 202, .9)
self.assertEqual(2, connections.numSynapses())
connections.createSynapse(segment, 203, .8)
self.assertEqual(2, connections.numSynapses())
synapse = connections.createSynapse(segment, 204, .8)
self.assertEqual(2, connections.numSynapses())
def read(cls, proto):
"""
Reads deserialized data from proto object.
@param proto (DynamicStructBuilder) Proto object
@return (TemporalMemory) TemporalMemory instance
"""
tm = object.__new__(cls)
# capnp fails to save a tuple, so proto.columnDimensions was forced to
# serialize as a list. We prefer a tuple, however, because columnDimensions
# should be regarded as immutable.
tm.columnDimensions = tuple(proto.columnDimensions)
tm.cellsPerColumn = int(proto.cellsPerColumn)
tm.activationThreshold = int(proto.activationThreshold)
tm.initialPermanence = proto.initialPermanence
tm.connectedPermanence = proto.connectedPermanence
tm.minThreshold = int(proto.minThreshold)
tm.maxNewSynapseCount = int(proto.maxNewSynapseCount)
tm.permanenceIncrement = proto.permanenceIncrement
tm.permanenceDecrement = proto.permanenceDecrement
tm.predictedSegmentDecrement = proto.predictedSegmentDecrement
tm.connections = Connections.read(proto.connections)
#pylint: disable=W0212
tm._random = Random()
tm._random.read(proto.random)
#pylint: enable=W0212
tm.activeCells = [int(x) for x in proto.activeCells]
tm.winnerCells = [int(x) for x in proto.winnerCells]
flatListLength = tm.connections.segmentFlatListLength()
tm.numActiveConnectedSynapsesForSegment = [0] * flatListLength
tm.numActivePotentialSynapsesForSegment = [0] * flatListLength
tm.activeSegments = []
tm.matchingSegments = []
for i in xrange(len(proto.activeSegmentOverlaps)):
protoSegmentOverlap = proto.activeSegmentOverlaps[i]
segment = tm.connections.getSegment(protoSegmentOverlap.cell,
protoSegmentOverlap.segment)
tm.activeSegments.append(segment)
overlap = protoSegmentOverlap.overlap
tm.numActiveConnectedSynapsesForSegment[segment.flatIdx] = overlap
for i in xrange(len(proto.matchingSegmentOverlaps)):
protoSegmentOverlap = proto.matchingSegmentOverlaps[i]
segment = tm.connections.getSegment(protoSegmentOverlap.cell,
protoSegmentOverlap.segment)
tm.matchingSegments.append(segment)
overlap = protoSegmentOverlap.overlap
tm.numActivePotentialSynapsesForSegment[segment.flatIdx] = overlap
return tm
def testDestroySegmentsThenReachLimit(self):
""" Destroy some segments then verify that the maxSegmentsPerCell is still
correctly applied.
"""
connections = Connections(1024, 2, 2)
segment1 = connections.createSegment(11)
segment2 = connections.createSegment(11)
self.assertEqual(2, connections.numSegments())
connections.destroySegment(segment1)
connections.destroySegment(segment2)
self.assertEqual(0, connections.numSegments())
connections.createSegment(11)
self.assertEqual(1, connections.numSegments())
connections.createSegment(11)
self.assertEqual(2, connections.numSegments())
segment3 = connections.createSegment(11)
self.assertEqual(2, connections.numSegments(11))
self.assertEqual(2, connections.numSegments())
def read(cls, proto):
"""
Reads deserialized data from proto object.
@param proto (DynamicStructBuilder) Proto object
@return (TemporalMemory) TemporalMemory instance
"""
tm = object.__new__(cls)
# capnp fails to save a tuple, so proto.columnDimensions was forced to
# serialize as a list. We prefer a tuple, however, because columnDimensions
# should be regarded as immutable.
tm.columnDimensions = tuple(proto.columnDimensions)
tm.cellsPerColumn = int(proto.cellsPerColumn)
tm.activationThreshold = int(proto.activationThreshold)
tm.initialPermanence = proto.initialPermanence
tm.connectedPermanence = proto.connectedPermanence
tm.minThreshold = int(proto.minThreshold)
tm.maxNewSynapseCount = int(proto.maxNewSynapseCount)
tm.permanenceIncrement = proto.permanenceIncrement
tm.permanenceDecrement = proto.permanenceDecrement
tm.predictedSegmentDecrement = proto.predictedSegmentDecrement
tm.connections = Connections.read(proto.connections)
#pylint: disable=W0212
tm._random = Random()
tm._random.read(proto.random)
#pylint: enable=W0212
tm.activeCells = [int(x) for x in proto.activeCells]
tm.winnerCells = [int(x) for x in proto.winnerCells]
flatListLength = tm.connections.segmentFlatListLength()
tm.numActiveConnectedSynapsesForSegment = [0] * flatListLength
tm.numActivePotentialSynapsesForSegment = [0] * flatListLength
tm.activeSegments = []
tm.matchingSegments = []
for i in xrange(len(proto.activeSegmentOverlaps)):
protoSegmentOverlap = proto.activeSegmentOverlaps[i]
segment = tm.connections.getSegment(protoSegmentOverlap.cell,
protoSegmentOverlap.segment)
tm.activeSegments.append(segment)
overlap = protoSegmentOverlap.overlap
tm.numActiveConnectedSynapsesForSegment[segment.flatIdx] = overlap
for i in xrange(len(proto.matchingSegmentOverlaps)):
protoSegmentOverlap = proto.matchingSegmentOverlaps[i]
segment = tm.connections.getSegment(protoSegmentOverlap.cell,
protoSegmentOverlap.segment)
tm.matchingSegments.append(segment)
overlap = protoSegmentOverlap.overlap
tm.numActivePotentialSynapsesForSegment[segment.flatIdx] = overlap
return tm
