def test_multinomial(self):
rnd.seed(self.seed, self.brng)
actual = rnd.multinomial(20, [1 / 6.] * 6, size=(3, 2))
desired = np.array([[[7, 0, 2, 4, 4, 3], [7, 1, 2, 6, 4, 0]],
[[2, 2, 3, 4, 6, 3], [1, 2, 5, 5, 6, 1]],
[[2, 7, 4, 1, 2, 4], [3, 5, 2, 5, 4, 1]]])
np.testing.assert_array_equal(actual, desired)
def test_size(self):
# gh-3173
p = [0.5, 0.5]
assert_equal(rnd.multinomial(1, p, np.uint32(1)).shape, (1, 2))
assert_equal(rnd.multinomial(1, p, np.uint32(1)).shape, (1, 2))
assert_equal(rnd.multinomial(1, p, np.uint32(1)).shape, (1, 2))
assert_equal(rnd.multinomial(1, p, [2, 2]).shape, (2, 2, 2))
assert_equal(rnd.multinomial(1, p, (2, 2)).shape, (2, 2, 2))
assert_equal(rnd.multinomial(1, p, np.array((2, 2))).shape, (2, 2, 2))
assert_raises(TypeError, rnd.multinomial, 1, p, np.float(1))
def test_zero_probability(self):
rnd.multinomial(100, [0.2, 0.8, 0.0, 0.0, 0.0])
def test_basic(self):
rnd.multinomial(100, [0.2, 0.8])
