def testAdaptShouldIncrementSynapses(self):
"""
Test that connections are generated on predefined segments.
"""
random = Random(1981)
active_cells = np.array(random.sample(
np.arange(0, NUM_CELLS, 1, dtype="uint32"), 40),
dtype="uint32")
active_cells.sort()
presynaptic_input = list(range(0, 10))
presynaptic_input_set = set(presynaptic_input)
inputSDR = SDR(1024)
inputSDR.sparse = presynaptic_input
connections = Connections(NUM_CELLS, 0.51)
for i in range(NUM_CELLS):
connections.createSegment(i, 1)
for cell in active_cells:
segments = connections.segmentsForCell(cell)
segment = segments[0]
for c in presynaptic_input:
connections.createSynapse(segment, c, 0.1)
connections.adaptSegment(segment, inputSDR, 0.1, 0.001, True)
presynamptic_cells = self._getPresynapticCells(
connections, segment, 0.2)
self.assertEqual(presynamptic_cells, presynaptic_input_set,
"Missing synapses")
presynamptic_cells = self._getPresynapticCells(
connections, segment, 0.3)
self.assertEqual(presynamptic_cells, set(), "Too many synapses")
def testMapSegmentsToCell(self):
"""
Test that cells are correspond to segments.
"""
connections = Connections(20, 0.2)
segments = [connections.createSegment(i, 1) for i in range(19, -1, -1)]
self.assertEqual(list(range(20)), segments,
"Segments were not allocated continuously")
cells_should_be = list(range(19, -1,
-1)) # Segment 19 belongs to cell 0, etc.
cells = list(connections.mapSegmentsToCells(segments))
self.assertEqual(cells_should_be, cells)
def testAdaptShouldRemoveSegments(self):
"""
Test that connections are generated on predefined segments.
"""
random = Random(1981)
active_cells = np.array(random.sample(
np.arange(0, NUM_CELLS, 1, dtype="uint32"), 40),
dtype="uint32")
active_cells.sort()
presynaptic_input = list(range(0, 10))
inputSDR = SDR(1024)
inputSDR.sparse = presynaptic_input
connections = Connections(NUM_CELLS, 0.51)
for i in range(NUM_CELLS):
connections.createSegment(i, 1)
for cell in active_cells:
segments = connections.segmentsForCell(cell)
self.assertEqual(len(segments), 1,
"Segments were prematurely destroyed.")
segment = segments[0]
connections.adaptSegment(segment, inputSDR, 0.1, 0.001, True)
segments = connections.segmentsForCell(cell)
self.assertEqual(len(segments), 0, "Segments were not destroyed.")
def testFilterUnsortedSegmentsByCell(self):
"""
Test that segments are filtered by cell.
"""
connections = Connections(20, 0.2)
segments = [connections.createSegment(i, 1) for i in range(19, -1, -1)]
self.assertEqual(list(range(20)), segments,
"Segments were not allocated continuously")
segments_should_be = [19, 10, 0] # Segment 19 belongs to cell 0, etc.
filtered_segments = list(
connections.filterSegmentsByCell(np.array(segments), [0, 9, 19],
False))
self.assertEqual(segments_should_be, filtered_segments,
"Segments were not filtered correctly")
def testSortSegmentsByCell(self):
"""
Test that segments are sorted by cell.
"""
connections = Connections(20, 0.2)
segments = [connections.createSegment(i, 1) for i in range(19, -1, -1)]
self.assertEqual(list(range(20)), segments,
"Segments were not allocated continuously")
segments_should_be = list(range(
19, -1, -1)) # Segment 19 belongs to cell 0, etc.
shuffle(segments)
sorted_segments = list(
connections.sortSegmentsByCell(np.array(segments)))
self.assertEqual(segments_should_be, sorted_segments,
"Segments were not sorted by cell")
def testComputeActivityUnion(self):
"""
Test that connections are generated on predefined segments.
"""
random = Random(1981)
active_cells = np.array(random.sample(
np.arange(0, NUM_CELLS, 1, dtype="uint32"), 40),
dtype="uint32")
active_cells.sort()
presynaptic_input1 = list(range(0, 10))
presynaptic_input2 = list(range(10, 20))
connections = Connections(NUM_CELLS, 0.51, False)
for i in range(NUM_CELLS):
connections.createSegment(i, 1)
self._learn(connections, active_cells, presynaptic_input1)
self._learn(connections, active_cells, presynaptic_input2)
numSynapses = connections.numSynapses()
self.assertNotEqual(
numSynapses, 40,
"There should be a synapse for each presynaptic cell")
active_cells_set = set(active_cells)
inputSDR = SDR(1024)
inputSDR.sparse = presynaptic_input1
numActiveConnectedSynapsesForSegment = connections.computeActivity(
inputSDR, False)
for cell, count in enumerate(numActiveConnectedSynapsesForSegment):
if cell in active_cells_set:
self.assertNotEqual(count, 0, "Segment should be active")
inputSDR.sparse = presynaptic_input2
numActiveConnectedSynapsesForSegment = connections.computeActivity(
inputSDR, False)
for cell, count in enumerate(numActiveConnectedSynapsesForSegment):
if cell in active_cells_set:
self.assertNotEqual(count, 0, "Segment should be active")
def testComputeActivity(self):
"""
Test that connections are generated on predefined segments.
"""
random = Random(1981)
active_cells = np.array(random.sample(
np.arange(0, NUM_CELLS, 1, dtype="uint32"), 40),
dtype="uint32")
active_cells.sort()
presynaptic_input = list(range(0, 10))
inputSDR = SDR(1024)
inputSDR.sparse = presynaptic_input
l = len(presynaptic_input)
connections = Connections(NUM_CELLS, 0.51, False)
for i in range(NUM_CELLS):
connections.createSegment(i, 1)
numActiveConnectedSynapsesForSegment = connections.computeActivity(
inputSDR, False)
for count in numActiveConnectedSynapsesForSegment:
self.assertEqual(count, 0, "Segment should not be active")
for cell in active_cells:
segments = connections.segmentsForCell(cell)
segment = segments[0]
for c in presynaptic_input:
connections.createSynapse(segment, c, 0.1)
numActiveConnectedSynapsesForSegment = connections.computeActivity(
inputSDR, False)
for count in numActiveConnectedSynapsesForSegment:
self.assertEqual(count, 0, "Segment should not be active")
for cell in active_cells:
segments = connections.segmentsForCell(cell)
segment = segments[0]
connections.adaptSegment(segment, inputSDR, 0.5, 0.0, False)
active_cells_set = set(active_cells)
numActiveConnectedSynapsesForSegment = connections.computeActivity(
inputSDR, False)
for cell, count in enumerate(numActiveConnectedSynapsesForSegment):
if cell in active_cells_set:
self.assertEqual(count, l, "Segment should be active")
else:
self.assertEqual(count, 0, "Segment should not be active")
def testNumConnectedSynapses(self):
"""
Test that connections are generated on predefined segments.
"""
random = Random(1981)
active_cells = np.array(random.sample(
np.arange(0, NUM_CELLS, 1, dtype="uint32"), 40),
dtype="uint32")
active_cells.sort()
presynaptic_input = list(range(0, 10))
inputSDR = SDR(1024)
inputSDR.sparse = presynaptic_input
connections = Connections(NUM_CELLS, 0.2)
for i in range(NUM_CELLS):
connections.createSegment(i, 1)
for cell in active_cells:
segments = connections.segmentsForCell(cell)
segment = segments[0]
for c in presynaptic_input:
connections.createSynapse(segment, c, 0.1)
connections.adaptSegment(segment, inputSDR, 0.1, 0.0, False)
connected_synapses = connections.numConnectedSynapses(segment)
self.assertEqual(connected_synapses, len(presynaptic_input),
"Missing synapses")
presynaptic_input1 = list(range(0, 5))
inputSDR.sparse = presynaptic_input1
total_connected = 0
for cell in active_cells:
segments = connections.segmentsForCell(cell)
segment = segments[0]
connections.adaptSegment(segment, inputSDR, 0.0, 0.1, False)
connected_synapses = connections.numConnectedSynapses(segment)
self.assertEqual(connected_synapses, len(presynaptic_input1),
"Missing synapses")
total_connected += connected_synapses
connected_synapses = connections.numSynapses(segment)
self.assertEqual(connected_synapses, len(presynaptic_input),
"Missing synapses")
self.assertEqual(total_connected,
len(presynaptic_input1) * 40, "Missing synapses")
