def vector(self):
"""
:return: if this distribution contains only a single vector, return that vector; otherwise, throw exception
:rtype: KeyedVector
"""
vector = KeyedVector()
for substate, distribution in self.distributions.items():
assert len(
distribution
) == 1, 'Cannot return vector from uncertain distribution'
vector.update(distribution.domain()[0])
return vector
def __str__(self):
certain = [
dist for dist in self.distributions.values() if len(dist) == 1
]
vector = KeyedVector()
for dist in certain:
vector.update({
key: value
for key, value in dist.first().items() if key != keys.CONSTANT
})
return '%s\n%s' % (vector.sortedString(), '\n---\n'.join([
str(dist) for dist in self.distributions.values() if len(dist) > 1
]))
def select(self, maximize=False, incremental=False):
"""
Reduce distribution to a single element, sampled according to the given distribution
:param incremental: if C{True}, then select each key value in series (rather than picking out a joint vector all at once, default is C{False})
:return: the probability of the selection made
"""
if incremental:
prob = KeyedVector()
else:
prob = 1
for distribution in self.distributions.values():
if incremental:
prob.update(distribution.select(maximize, incremental))
else:
prob *= distribution.select(maximize, incremental)
return prob