def test_log_pdf_array_dimension(self):
d = 3
n = 2
ps = asarray(rand(d))
b = Bernoulli(ps)
X = randint(0, 2, (n, d)).astype(numpy.bool8)
self.assertEqual(b.log_pdf(X).shape, (n, ))
def test_log_pdf_success_multiple(self):
d = 4
n = 3
num_runs = 100
for _ in range(num_runs):
ps = rand(d)
b = Bernoulli(ps)
X = randint(0, 2, (n, d)).astype(numpy.bool8)
# naive computation of log pdf
expected = zeros((n, d))
for i in range(n):
for j in range(d):
expected[i,
j] = log(ps[j]) if X[i,
j] == 1 else log(1 - ps[j])
self.assertTrue(all(sum(expected, 1) == b.log_pdf(X)))
def test_log_pdf_failure_single(self):
d = 1
ps = asarray(rand(d))
b = Bernoulli(ps)
X = asarray([[0]], dtype=numpy.bool8)
self.assertEqual(b.log_pdf(X), log(1 - ps[0]))
def test_log_pdf_type(self):
p = asarray([0.3])
b = Bernoulli(p)
self.assertEqual(type(b.log_pdf(asarray([[1]], dtype=numpy.bool8))),
numpy.ndarray)
