def test_weighted():
"""
You can compute a DRV from disjoint cases.
"""
var = DRV({1: 0.5, 2: 0.5})
var2 = DRV.weighted_average((
(var, 0.5),
(var + 2, 0.5),
))
# So, var2 should be uniformly distributed
assert var2.is_same(DRV({x: 0.25 for x in range(1, 5)}))
def test_more_dice(reg):
"""
Test with higher numbers of dice. Three dice is wild + 2 @ regular, etc.
"""
def remove_highest(values):
return sum(values) - max(values)
expected = DRV.weighted_average((
(pool(d6, count=reg).apply(remove_highest), Fraction(1, 6)),
(reg @ d6 + d6.explode().given(lambda x: x != 1), Fraction(5, 6)),
))
_check(
opend6.dice(reg + 1),
expected,
single=False,
totals=reg @ d6 + d6.explode(),
highest=pool(d6, count=reg + 1).apply(max),
)
def test_dice():
"""The dice() function returns the summarised data from the rolls."""
with pytest.raises(ValueError):
opend6.dice(0)
# One die is a wild die.
assert opend6.dice(1).is_same(opend6.wild_die)
# Two dice is wild + regular, and we need to test that addition is correct.
expected = DRV.weighted_average((
(DRV({0: 1}), Fraction(1, 6)),
(d6 + d6.explode().given(lambda x: x != 1), Fraction(5, 6)),
))
_check(
opend6.dice(2),
expected,
single=False,
totals=d6 + d6.explode(),
highest=pool(d6, d6).apply(max),
)
def test_dice_char():
"""The char parameter adds dice bought with Character Points"""
# I don't think the rules explicity say what happens on a botch, if an
# exploded character die is the highest score rolled. I'm going to assume
# that the botch cancels the 6.
def cancel(value):
return max(value - 6, 0)
expected = DRV.weighted_average((
(d6.explode().apply(cancel), Fraction(1, 6)),
(d6.explode() + d6.explode().given(lambda x: x != 1), Fraction(5, 6)),
))
_check(
opend6.dice(1, char=1),
expected,
single=False,
totals=2 @ d6.explode(),
highest=pool(d6, d6).apply(max),
)
