def test_tuple_map():
"""
Test MAP parameter estimation under the tuple distribution.
"""
from cargo.numpy import tolist_deeply
model = Tuple([(Binomial(estimation_n=1), 2),
(Binomial(estimation_n=1), 1)])
engine = ModelEngine(model)
assert_almost_equal_deep(
tolist_deeply(
engine.map(
([(2, 3), (2, 3)], [(2, 3)]),
[([0, 1], [0])] * 1 + [([1, 0], [1])] * 9,
numpy.ones(10),
), ),
([(10.0 / 13.0, 1), (2.0 / 13.0, 1)], [(10.0 / 13.0, 1)]),
)
assert_almost_equal_deep(
tolist_deeply(
engine.map(
([(2, 3), (2, 3)], [(2, 3)]),
[([0, 1], [0])] * 1 + [([1, 0], [1])] * 9,
[1.00] * 1 + [3.00] * 9,
), ),
([(28.0 / 31.0, 1), (2.0 / 31.0, 1)], [(28.0 / 31.0, 1)]),
)
def test_tuple_map():
"""
Test MAP parameter estimation under the tuple distribution.
"""
from cargo.numpy import tolist_deeply
model = Tuple([(Binomial(estimation_n = 1), 2), (Binomial(estimation_n = 1), 1)])
engine = ModelEngine(model)
assert_almost_equal_deep(
tolist_deeply(
engine.map(
([(2, 3), (2, 3)], [(2, 3)]),
[([0, 1], [0])] * 1 + [([1, 0], [1])] * 9,
numpy.ones(10),
),
),
([(10.0 / 13.0, 1), (2.0 / 13.0, 1)], [(10.0 / 13.0, 1)]),
)
assert_almost_equal_deep(
tolist_deeply(
engine.map(
([(2, 3), (2, 3)], [(2, 3)]),
[([0, 1], [0])] * 1 + [([1, 0], [1])] * 9,
[1.00] * 1 + [3.00] * 9,
),
),
([(28.0 / 31.0, 1), (2.0 / 31.0, 1)], [(28.0 / 31.0, 1)]),
)
def test_tuple_ml():
"""
Test ML parameter estimation under the tuple distribution.
"""
from cargo.numpy import tolist_deeply
model = Tuple([(Binomial(estimation_n=1), 2),
(Binomial(estimation_n=1), 1)])
engine = ModelEngine(model)
assert_almost_equal_deep(
tolist_deeply(
engine.ml(
[([0, 1], [0])] * 2500 + [([1, 0], [1])] * 7500,
numpy.ones(10000),
), ),
([(0.75, 1), (0.25, 1)], [(0.75, 1)]),
)
assert_almost_equal_deep(
tolist_deeply(
engine.ml(
[([0, 1], [0])] * 1000 + [([1, 0], [1])] * 1000,
[1.00] * 1000 + [3.00] * 1000,
), ),
([(0.75, 1), (0.25, 1)], [(0.75, 1)]),
)
def test_tuple_ml():
"""
Test ML parameter estimation under the tuple distribution.
"""
from cargo.numpy import tolist_deeply
model = Tuple([(Binomial(estimation_n = 1), 2), (Binomial(estimation_n = 1), 1)])
engine = ModelEngine(model)
assert_almost_equal_deep(
tolist_deeply(
engine.ml(
[([0, 1], [0])] * 2500 + [([1, 0], [1])] * 7500,
numpy.ones(10000),
),
),
([(0.75, 1), (0.25, 1)], [(0.75, 1)]),
)
assert_almost_equal_deep(
tolist_deeply(
engine.ml(
[([0, 1], [0])] * 1000 + [([1, 0], [1])] * 1000,
[1.00] * 1000 + [3.00] * 1000,
),
),
([(0.75, 1), (0.25, 1)], [(0.75, 1)]),
)
