def test_mod():
d1 = uniform_scalar_distribution(range(1,7))
d2 = uniform_scalar_distribution(range(2))
d3 = uniform_scalar_distribution(range(1,3))
d4 = ScalarDistribution([0,1],[3/4,1/4])
assert_true((d1%2).is_approx_equal(d2))
assert_true((5%d3).is_approx_equal(d2))
assert_true((d1%d3).is_approx_equal(d4))
def test_mod():
d1 = uniform_scalar_distribution(range(1, 7))
d2 = uniform_scalar_distribution(range(2))
d3 = uniform_scalar_distribution(range(1, 3))
d4 = ScalarDistribution([0, 1], [3 / 4, 1 / 4])
assert (d1 % 2).is_approx_equal(d2)
assert (5 % d3).is_approx_equal(d2)
assert (d1 % d3).is_approx_equal(d4)
def test_floordiv():
d1 = uniform_scalar_distribution(range(1, 7))
d2 = ScalarDistribution([0,1,2,3], [1/6,1/3,1/3,1/6])
d3 = ScalarDistribution([1,2,3,6], [1/2,1/6,1/6,1/6])
d4 = uniform_scalar_distribution(range(1, 3))
d5 = ScalarDistribution([0,1,2,3,4,5,6],[1/12,1/4,1/4,1/6,1/12,1/12,1/12])
assert_true((d1//2).is_approx_equal(d2))
assert_true((6//d1).is_approx_equal(d3))
assert_true((d1//d4).is_approx_equal(d5))
def test_sub():
d1 = uniform_scalar_distribution(range(3))
d2 = uniform_scalar_distribution(range(1, 4))
d3 = ScalarDistribution([-2, -1, 0, 1, 2], [1/9, 2/9, 3/9, 2/9, 1/9])
assert_true((d2-1).is_approx_equal(d1))
assert_true((3-d2).is_approx_equal(d1))
assert_true((d1).is_approx_equal(d2-1))
assert_true((d1).is_approx_equal(3-d2))
assert_true((d1-d1).is_approx_equal(d3))
def test_add():
d1 = uniform_scalar_distribution(range(3))
d2 = uniform_scalar_distribution(range(1, 4))
d3 = ScalarDistribution([0, 1, 2, 3, 4], [1/9, 2/9, 3/9, 2/9, 1/9])
assert_true((d1+1).is_approx_equal(d2))
assert_true((1+d1).is_approx_equal(d2))
assert_true((d2).is_approx_equal(d1+1))
assert_true((d2).is_approx_equal(1+d1))
assert_true((d1+d1).is_approx_equal(d3))
def test_div():
d1 = uniform_scalar_distribution([2,4,6])
d2 = uniform_scalar_distribution([1,2,3,4,6])
d3 = uniform_scalar_distribution([1,2,3])
d4 = uniform_scalar_distribution([12,6,4,3,2])
d5 = uniform_scalar_distribution([1,2])
d6 = ScalarDistribution([1,2,3,4,6], [1/6,1/3,1/6,1/6,1/6])
assert_true((d1/2).is_approx_equal(d3))
assert_true((12/d2).is_approx_equal(d4))
assert_true((d1/d5).is_approx_equal(d6))
def test_add():
d1 = uniform_scalar_distribution(range(3))
d2 = uniform_scalar_distribution(range(1, 4))
d3 = ScalarDistribution([0, 1, 2, 3, 4],
[1 / 9, 2 / 9, 3 / 9, 2 / 9, 1 / 9])
assert (d1 + 1).is_approx_equal(d2)
assert (1 + d1).is_approx_equal(d2)
assert (d2).is_approx_equal(d1 + 1)
assert (d2).is_approx_equal(1 + d1)
assert (d1 + d1).is_approx_equal(d3)
def test_sub():
d1 = uniform_scalar_distribution(range(3))
d2 = uniform_scalar_distribution(range(1, 4))
d3 = ScalarDistribution([-2, -1, 0, 1, 2],
[1 / 9, 2 / 9, 3 / 9, 2 / 9, 1 / 9])
assert (d2 - 1).is_approx_equal(d1)
assert (3 - d2).is_approx_equal(d1)
assert (d1).is_approx_equal(d2 - 1)
assert (d1).is_approx_equal(3 - d2)
assert (d1 - d1).is_approx_equal(d3)
def test_floordiv():
d1 = uniform_scalar_distribution(range(1, 7))
d2 = ScalarDistribution([0, 1, 2, 3], [1 / 6, 1 / 3, 1 / 3, 1 / 6])
d3 = ScalarDistribution([1, 2, 3, 6], [1 / 2, 1 / 6, 1 / 6, 1 / 6])
d4 = uniform_scalar_distribution(range(1, 3))
d5 = ScalarDistribution(
[0, 1, 2, 3, 4, 5, 6],
[1 / 12, 1 / 4, 1 / 4, 1 / 6, 1 / 12, 1 / 12, 1 / 12])
assert (d1 // 2).is_approx_equal(d2)
assert (6 // d1).is_approx_equal(d3)
assert (d1 // d4).is_approx_equal(d5)
def test_div():
d1 = uniform_scalar_distribution([2, 4, 6])
d2 = uniform_scalar_distribution([1, 2, 3, 4, 6])
d3 = uniform_scalar_distribution([1, 2, 3])
d4 = uniform_scalar_distribution([12, 6, 4, 3, 2])
d5 = uniform_scalar_distribution([1, 2])
d6 = ScalarDistribution([1, 2, 3, 4, 6],
[1 / 6, 1 / 3, 1 / 6, 1 / 6, 1 / 6])
assert (d1 / 2).is_approx_equal(d3)
assert (12 / d2).is_approx_equal(d4)
assert (d1 / d5).is_approx_equal(d6)
def test_mul():
d1 = uniform_scalar_distribution(range(1, 3))
d2 = ScalarDistribution([1, 2, 4], [0.25, 0.5, 0.25])
d3 = ScalarDistribution([2, 4], [0.5, 0.5])
assert_true((d1*d1).is_approx_equal(d2))
assert_true((d1*2).is_approx_equal(d3))
assert_true((2*d1).is_approx_equal(d3))
def test_mul():
d1 = uniform_scalar_distribution(range(1, 3))
d2 = ScalarDistribution([1, 2, 4], [0.25, 0.5, 0.25])
d3 = ScalarDistribution([2, 4], [0.5, 0.5])
assert (d1 * d1).is_approx_equal(d2)
assert (d1 * 2).is_approx_equal(d3)
assert (2 * d1).is_approx_equal(d3)
def test_matmul():
d1 = uniform_scalar_distribution(range(1, 7))
d2 = Distribution(list(product(d1.outcomes, repeat=2)), [1 / 36] * 36)
assert (d1.__matmul__(d1)).is_approx_equal(d2)
def test_ge():
d1 = uniform_scalar_distribution(range(1, 7))
d2 = uniform_scalar_distribution(range(2))
d3 = ScalarDistribution([True], [1])
assert (d1 >= 4).is_approx_equal(d2)
assert (d1 >= d2).is_approx_equal(d3)
def test_gt():
d1 = uniform_scalar_distribution(range(1, 7))
d2 = uniform_scalar_distribution(range(2))
d3 = ScalarDistribution([True, False], [11 / 12, 1 / 12])
assert (d1 > 3).is_approx_equal(d2)
assert (d1 > d2).is_approx_equal(d3)
def test_ne():
d1 = uniform_scalar_distribution(range(1, 7))
d2 = ScalarDistribution([True, False], [5 / 6, 1 / 6])
assert (d1 != 6).is_approx_equal(d2)
assert (d1 != d1).is_approx_equal(d2)
def test_ge():
d1 = uniform_scalar_distribution(range(1,7))
d2 = uniform_scalar_distribution(range(2))
d3 = ScalarDistribution([True], [1])
assert_true((d1 >= 4).is_approx_equal(d2))
assert_true((d1 >= d2).is_approx_equal(d3))
def test_ne():
d1 = uniform_scalar_distribution(range(1,7))
d2 = ScalarDistribution([True, False], [5/6, 1/6])
assert_true((d1 != 6).is_approx_equal(d2))
assert_true((d1 != d1).is_approx_equal(d2))
def test_matmul_fail():
d1 = uniform_scalar_distribution(range(1,7))
assert_raises(NotImplementedError, lambda x: x.__matmul__('0'), d1)
def test_cmp_fail():
d1 = uniform_scalar_distribution(range(1,7))
assert_raises(NotImplementedError, lambda x: x + '0', d1)
def test_matmul():
d1 = uniform_scalar_distribution(range(1,7))
d2 = Distribution(list(product(d1.outcomes, repeat=2)), [1/36]*36)
assert_true((d1.__matmul__(d1)).is_approx_equal(d2))
def test_cmp_fail():
d1 = uniform_scalar_distribution(range(1, 7))
with pytest.raises(NotImplementedError):
(lambda x: x + '0')(d1)
def test_matmul_fail():
d1 = uniform_scalar_distribution(range(1, 7))
with pytest.raises(NotImplementedError):
(lambda x: x.__matmul__('0'))(d1)
def test_gt():
d1 = uniform_scalar_distribution(range(1,7))
d2 = uniform_scalar_distribution(range(2))
d3 = ScalarDistribution([True, False], [11/12, 1/12])
assert_true((d1 > 3).is_approx_equal(d2))
assert_true((d1 > d2).is_approx_equal(d3))
