def testInverse(self):
random_variable = probability.DiscreteRandomVariable({
1: 1,
2: 3,
3: 4
})
inverse = random_variable.inverse(probability.DiscreteEvent({1, 3}))
self.assertEqual(inverse.values, {1, 2})
random_variable = probability.DiscreteRandomVariable({1: 1, 2: 1})
inverse = random_variable.inverse(probability.DiscreteEvent({1, 5}))
self.assertEqual(inverse.values, {1, 2})
def testCall(self):
random_variable = probability.DiscreteRandomVariable({
1: 1,
2: 3,
3: 4
})
forwards = random_variable(probability.DiscreteEvent({1, 3}))
self.assertEqual(forwards.values, {1, 4})
def _sample_letter_bag(is_train, min_total):
"""Samples a "container of letters" and returns info on it."""
while True:
num_distinct_letters = random.randint(1, _MAX_DISTINCT_LETTERS)
num_letters_total = random.randint(
max(num_distinct_letters, min_total),
min(_MAX_TOTAL_LETTERS, num_distinct_letters * _MAX_LETTER_REPEAT))
letter_counts = combinatorics.uniform_positive_integers_with_sum(
num_distinct_letters, num_letters_total)
# Test/train split.
if (is_train is None or train_test_split.is_train(
sorted(letter_counts)) == is_train):
break
letters_distinct = random.sample(_LETTERS, num_distinct_letters)
weights = {i: 1 for i in range(num_letters_total)}
letters_with_repetition = []
for letter, count in zip(letters_distinct, letter_counts):
letters_with_repetition += [letter] * count
random.shuffle(letters_with_repetition)
random_variable = probability.DiscreteRandomVariable(
{i: letter
for i, letter in enumerate(letters_with_repetition)})
if random.choice([False, True]):
bag_contents = ''.join(letters_with_repetition)
else:
letters_and_counts = [
'{}: {}'.format(letter, count)
for letter, count in zip(letters_distinct, letter_counts)
]
bag_contents = '{' + ', '.join(letters_and_counts) + '}'
return LetterBag(weights=weights,
random_variable=random_variable,
letters_distinct=letters_distinct,
bag_contents=bag_contents)
def _random_variable(self):
rv1 = probability.DiscreteRandomVariable({1: 'a', 2: 'b', 3: 'c'})
rv2 = probability.DiscreteRandomVariable({1: 'x', 2: 'y', 3: 'x'})
return probability.FiniteProductRandomVariable((rv1, rv2))