def test_matrix_multiply():
m = Matrix([
[0.0, 0.1],
[0.6, 1.0],
])
res = Matrix([
[0.0, 0.05],
[0.3, 0.5],
])
assert matrix_multiply(m, 0.5) == res
def decode(self, signal, activation_threshold=None):
assert len(signal) == self.conf.UNIT_OUTPUT_WIDTH
candidates = []
for activity, pattern in zip(signal, self._patterns_store.get_objects()):
candidate = matrix_multiply(pattern, activity)
candidate_activity = self._activate(candidate, activation_threshold)
if candidate_activity:
candidates.append((candidate_activity, candidate))
if not candidates:
return None
return max(candidates, key=lambda item: item[0])[1]
def decode(self, signal, activation_threshold=None):
assert len(signal) == self.conf.UNIT_OUTPUT_WIDTH
candidates = []
for activity, pattern in zip(signal,
self._patterns_store.get_objects()):
candidate = matrix_multiply(pattern, activity)
candidate_activity = self._activate(candidate,
activation_threshold)
if candidate_activity:
candidates.append((candidate_activity, candidate))
if not candidates:
return None
return max(candidates, key=lambda item: item[0])[1]
