def test_profile_constructor(profile_example):
p = ddp.Profile()
assert len(p.synapse_weights) == 0
pe = profile_example
p = ddp.Profile(neuron_counts=pe.neuron_counts,
synapse_counts=pe.synapse_counts,
synapse_weights=pe.synapse_weights,
num_inputs=pe.num_inputs)
assert p.neuron_counts[0][2] == 1
def test_profile_constructor(profile_example):
p = ddp.Profile()
assert len(p.synapse_weights) == 0
pe = profile_example
p = ddp.Profile(
neuron_counts=pe.neuron_counts,
synapse_counts=pe.synapse_counts,
synapse_weights=pe.synapse_weights,
num_inputs=pe.num_inputs,
)
assert np.allclose(p.neuron_counts[1].data, [2, 1, 1, 1])
assert np.allclose(p.synapse_weights[1].data, [0.1, 0.2, 0.3, 0.4, 0.5])
def test_add(profile_example):
pe = profile_example
p = ddp.Profile(neuron_counts=pe.neuron_counts,
synapse_counts=pe.synapse_counts,
synapse_weights=pe.synapse_weights,
num_inputs=3)
q = ddp.Profile(neuron_counts=pe.neuron_counts,
synapse_counts=pe.synapse_counts,
synapse_weights=pe.synapse_weights,
num_inputs=4)
s = p + q
assert s.size == 4
assert s.total == 10
assert s.num_inputs == 7
p += p
assert p.total == 10
assert p.num_inputs == 6
def test_profile_attributes(profile_example):
pe = profile_example
p = ddp.Profile(neuron_counts=pe.neuron_counts,
synapse_counts=pe.synapse_counts,
synapse_weights=pe.synapse_weights,
num_inputs=3)
assert p.neuron_counts == pe.neuron_counts
assert p.synapse_counts == pe.synapse_counts
assert p.synapse_weights == pe.synapse_weights
assert p.num_inputs == 3
assert p.total == 5
assert p.size == 4
q = ddp.Profile(neuron_counts=pe.neuron_counts,
synapse_counts=pe.synapse_counts,
synapse_weights=pe.synapse_weights,
num_inputs=3)
assert p == q
def __init__(self):
nc1 = {
0: sp.coo_matrix([[4], [0]]),
1: sp.coo_matrix([[1], [1], [1], [0], [1], [0]]),
}
nc2 = {
0: sp.coo_matrix([[5], [0]]),
1: sp.coo_matrix([[0], [1], [1], [1], [1], [1]]),
}
nc3 = {
0: sp.coo_matrix([[2], [2]]),
1: sp.coo_matrix([[0], [1], [0], [1], [0], [0]]),
}
sw1 = {
1:
sp.coo_matrix([[0.1, 0], [0.2, 0], [0.3, 0], [0, 0], [0.4, 0],
[0, 0]])
}
sw2 = {
1:
sp.coo_matrix([[0, 0], [0.1, 0], [0.3, 0], [0.5, 0], [0.7, 0],
[0.9, 0]])
}
sw3 = {
1:
sp.coo_matrix([[0, 0], [0.5, 0.1], [0, 0], [0.7, 0.3], [0, 0],
[0, 0]])
}
sc1 = {1: sw1[1].astype(bool).astype(int)}
sc2 = {1: sw2[1].astype(bool).astype(int)}
sc3 = {1: sw3[1].astype(bool).astype(int)}
self.p1 = ddp.Profile(neuron_counts=nc1,
synapse_counts=sc1,
synapse_weights=sw1,
num_inputs=1)
self.p2 = ddp.Profile(neuron_counts=nc2,
synapse_counts=sc2,
synapse_weights=sw2,
num_inputs=1)
self.p3 = ddp.Profile(neuron_counts=nc3,
synapse_counts=sc3,
synapse_weights=sw3,
num_inputs=1)
def __init__(self):
ex1 = [1, 2, 2, 3, 5]
ex2 = [2, 3, 4, 5, 6]
ex3 = [2, 2, 2, 4, 4]
nc1 = {0: Counter([(0, )]), 1: Counter(ex1)}
nc2 = {0: Counter([(0, )]), 1: Counter(ex2)}
nc3 = {0: Counter([(1, )]), 1: Counter(ex3)}
sc1 = {0: Counter([(0, 0)]), 1: Counter([(x, 0) for x in ex1])}
sc2 = {0: Counter([(0, 0)]), 1: Counter([(x, 0) for x in ex2])}
sc3 = {
0: Counter([(1, 1), (0, 0)]),
1: Counter([(x, 1) for x in ex3] + [(x, 0) for x in ex3])
}
sw1 = {
0: {(0, 0, 1)},
1: {(x[0], x[1], .1 * idx + .1)
for idx, x in enumerate(sc1[1])}
}
sw2 = {
0: {(0, 0, 1)},
1: {(x[0], x[1], .2 * idx + .1)
for idx, x in enumerate(sc2[1])}
}
sw3 = {
0: {(1, 1, 1)},
1: {(x[0], x[1], .2 * idx + .1)
for idx, x in enumerate(sc3[1])}
}
self.p1 = ddp.Profile(neuron_counts=nc1,
synapse_counts=sc1,
synapse_weights=sw1,
num_inputs=1)
self.p2 = ddp.Profile(neuron_counts=nc2,
synapse_counts=sc2,
synapse_weights=sw2,
num_inputs=1)
self.p3 = ddp.Profile(neuron_counts=nc3,
synapse_counts=sc3,
synapse_weights=sw3,
num_inputs=1)