def test_sample_many_no_checks(self):
num_runs = 1000
for _ in range(num_runs):
n = randint(1, 10)
d = randint(1, 10)
mu = randint(0, 2, d).astype(numpy.bool8)
spread = rand()
dist = DiscreteRandomWalkProposal(mu, spread)
dist.sample(n)
def test_sample_dim(self):
n = 3
d = 2
mu = randint(0, 2, d).astype(numpy.bool8)
spread = .5
dist = DiscreteRandomWalkProposal(mu, spread)
s = dist.sample(n)
self.assertEqual(s.samples.shape, (n, d))
def test_sample_many_full_spread(self):
n = 3
d = 5
mu = randint(0, 2, d).astype(numpy.bool8)
spread = 0.99999999999
dist = DiscreteRandomWalkProposal(mu, spread)
s = dist.sample(n).samples
for i in range(n):
self.assertTrue(all(s[i] != mu))
def test_sample_many_no_spread(self):
n = 3
d = 5
mu = randint(0, 2, d).astype(numpy.bool8)
spread = 0.00000000001
dist = DiscreteRandomWalkProposal(mu, spread)
s = dist.sample(n).samples
for i in range(n):
# exactly one change
self.assertTrue(sum(abs(s[i] - mu)) == 1)
def test_sample_samples_dtype(self):
mu = randint(0, 2, 10).astype(numpy.bool8)
spread = .5
dist = DiscreteRandomWalkProposal(mu, spread)
s = dist.sample(1)
self.assertEqual(s.samples.dtype, numpy.bool8)
def test_sample_type(self):
mu = randint(0, 2, 10).astype(numpy.bool8)
spread = .5
dist = DiscreteRandomWalkProposal(mu, spread)
s = dist.sample(1)
self.assertTrue(isinstance(s, Sample))
