def testNumSynapses(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, 0.3)
for i in range(NUM_CELLS):
seg = 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)
num_synapses = connections.numSynapses(segment)
self.assertEqual(num_synapses, len(presynaptic_input),
"Missing synapses")
self.assertEqual(connections.numSynapses(),
len(presynaptic_input) * 40, "Missing synapses")
def testDestroySynapse(self):
# empty connections, create segment seg and a synapse syn
co = Connections(NUM_CELLS, 0.51)
seg = co.createSegment(NUM_CELLS-1, 1)
syn1 = co.createSynapse(seg, NUM_CELLS-1, 0.52)
# destroy the synapse
co.destroySynapse(syn1)
self.assertEqual(co.numSynapses(), 0)
def testDestroySynapse(self):
# empty connections, create segment seg and a synapse syn
co = Connections(NUM_CELLS, 0.51)
seg = co.createSegment(NUM_CELLS - 1, 1)
syn1 = co.createSynapse(seg, NUM_CELLS - 1, 0.52)
# destroy the synapse
co.destroySynapse(syn1)
self.assertEqual(co.numSynapses(), 0)
with pytest.raises(
RuntimeError
): # NTA_CHECK, data for removed synapse must not be accessible!
permRemoved = co.permanenceForSynapse(syn1)
assert permRemoved == perm1
# double remove should be just ignored
co.destroySynapse(syn1)
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_input1_set = set(presynaptic_input1)
presynaptic_input2 = list(range(10, 20))
presynaptic_input2_set = set(presynaptic_input1)
connections = Connections(NUM_CELLS, 0.51, False)
for i in range(NUM_CELLS):
seg = 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 testCreateSynapse(self):
# empty connections, create segment and a synapse
co = Connections(NUM_CELLS, 0.51)
self.assertEqual(co.numSynapses(), 0)
self.assertEqual(co.numSegments(), 0)
# 1st, create a segment
seg = co.createSegment(NUM_CELLS - 1, 1)
self.assertEqual(co.numSegments(), 1)
#1. create a synapse on that segment
syn1 = co.createSynapse(seg, NUM_CELLS - 1, 0.52)
self.assertEqual(pytest.approx(co.permanenceForSynapse(syn1)), 0.52)
self.assertEqual(co.numSynapses(), 1)
#2. creating a duplicit synapse should not crash!
syn2 = co.createSynapse(seg, NUM_CELLS - 1, 0.52)
self.assertEqual(syn1, syn2,
"creating duplicate synapses should return the same")
self.assertEqual(co.numSynapses(), 1,
"Duplicate synapse, number should not increase")
#3. create a different synapse
syn3 = co.createSynapse(seg, 1, 0.52)
self.assertNotEqual(
syn1, syn3, "creating a different synapse must create a new one")
self.assertEqual(co.numSynapses(), 2,
"New synapse should increase the number")
#4. create existing synapse with a new value -> should update permanence
#4.a lower permanence -> keep max()
syn4 = co.createSynapse(
seg, NUM_CELLS - 1,
0.11) #all the same just permanence is a lower val
self.assertEqual(syn1, syn4, "just updating existing syn")
self.assertEqual(co.numSynapses(), 2,
"Duplicate synapse, number should not increase")
self.assertEqual(pytest.approx(co.permanenceForSynapse(syn1)), 0.52,
"update keeps the larger value")
#4.b higher permanence -> update
syn5 = co.createSynapse(
seg, NUM_CELLS - 1,
0.99) #all the same just permanence is a higher val
self.assertEqual(syn1, syn5, "just updating existing syn")
self.assertEqual(co.numSynapses(), 2,
"Duplicate synapse, number should not increase")
self.assertEqual(pytest.approx(co.permanenceForSynapse(syn1)), 0.99,
"updated to the larger permanence value")