def test_box_gaussian_generic():
"""
Run generic tests for BoxGaussian.
"""
dist = BoxGaussian(np.array([[-3, 7, 1], [1, 2, 3]]),
np.array([[5, 7.1, 3], [2, 3.1, 4]]))
tester = DistributionTester(dist)
tester.test_all()
def test_generic(self):
"""
Run generic tests with DistributionTester.
"""
dist = BoxGaussian(np.array([[-3, 7, 1], [1, 2, 3]]),
np.array([[5, 7.1, 3], [2, 3.1, 4]]))
tester = DistributionTester(self, dist)
tester.test_all()
def test_tuple_generic():
"""
Run generic tests for TupleDistribution.
"""
box_dist = BoxGaussian(np.array([[-3, 7, 1], [1, 2, 3.7]]),
np.array([[5, 7.1, 1.5], [2, 2.5, 4]]))
dist = TupleDistribution((MultiBernoulli(3), box_dist))
tester = DistributionTester(dist)
tester.test_all()
def test_tuple_unpack_shape():
"""
Make sure that TupleDistribution.unpack_outs()
gives the correct shape.
"""
box_dist = BoxGaussian(np.array([[-3, 7, 1], [1, 2, 3.7]]),
np.array([[5, 7.1, 1.5], [2, 2.5, 4]]))
dist = TupleDistribution((MultiBernoulli(3), box_dist))
vec = np.array([[0, 1, 0, 1, 2, 3, 4, 5, 6], [1, 0, 1, 6, 5, 4, 3, 2, 1]])
unpacked = dist.unpack_outs(vec)
assert len(unpacked) == 2
assert np.array(unpacked[0]).shape == (2, 3)
assert np.array(unpacked[1]).shape == (2, 2, 3)
def test_unpack_shape(self):
"""
Make sure that unpack_outs gives the correct
shape.
"""
box_dist = BoxGaussian(np.array([[-3, 7, 1], [1, 2, 3.7]]),
np.array([[5, 7.1, 1.5], [2, 2.5, 4]]))
dist = TupleDistribution((MultiBernoulli(3), box_dist))
vec = np.array([[0, 1, 0, 1, 2, 3, 4, 5, 6],
[1, 0, 1, 6, 5, 4, 3, 2, 1]])
unpacked = dist.unpack_outs(vec)
self.assertEqual(len(unpacked), 2)
self.assertEqual(np.array(unpacked[0]).shape, (2, 3))
self.assertEqual(np.array(unpacked[1]).shape, (2, 2, 3))