def normalize(self):
if not self._objects:
return
if max(self._weights) > self._max_weight:
self._decrease_all()
while avg(self._weights) > self._average_weight:
self._decrease_all()
def normalize(self):
if not self._objects:
return
if max(self._weights) > self._max_weight:
self._decrease_all()
while avg(self._weights) > self._average_weight:
self._decrease_all()
def make_samples(threshold, message):
assert message, "Message can't be empty"
active_impulses = [
[i for i, a in enumerate(row) if a >= threshold] + [None]
for row in message.rows()
]
for sample in product(*active_impulses):
values = [message.get(y, x) if x is not None else 0 for y, x in enumerate(sample)]
activity = avg(values)
if activity:
yield sample, activity
def similarity(it1, it2):
return avg(int(x == y) for x, y in zip(it1, it2))
def similarity(it1, it2):
return avg(int(x == y) for x, y in zip(it1, it2))