def test_pmf_expected_values():
animals = Variable(['cat', 'dog', 'cat', 'mouse', 'dog', 'cat', 'cat', 'dog'])
PrAnimals = PMF(animals)
assert almostEqual(1.0, PrAnimals.expected_value(lambda v, p: 1))
# Test calculations of base-e entropy and base-2 entropy.
assert almostEqual(0.97431475, (-1) * PrAnimals.expected_value(lambda v, p: math.log(p)))
assert almostEqual(1.40563906, (-1) * PrAnimals.expected_value(lambda v, p: math.log2(p)))
# Expected word length.
assert PrAnimals.expected_value(lambda v, p: len(v)) == 3.25
def get_joint_entropy_term(self, *variables):
jht_key = self.create_flat_variable_set(*variables)
if len(jht_key) == 0:
return 0
self.JHT_reads += 1
try:
H = self.JHT[jht_key]
except KeyError:
self.JHT_misses += 1
joint_variables = self.datasetmatrix.get_variables('X', jht_key)
pmf = PMF(joint_variables)
H = - pmf.expected_value(lambda v, p: math.log(p))
self.JHT[jht_key] = H
if self.DoF_calculator.requires_pmfs:
self.DoF_calculator.set_context_pmfs(pmf, None, None, None)
return H