def __new__(cls,dist, rvs):
if not all([isinstance(rv, (Indexed, RandomSymbol))] for rv in rvs):
raise ValueError(filldedent('''Marginal distribution can be
intitialised only in terms of random variables or indexed random
variables'''))
rvs = Tuple.fromiter(rv for rv in rvs)
if not isinstance(dist, JointDistribution) and len(random_symbols(dist)) == 0:
return dist
return Basic.__new__(cls, dist, rvs)
def _apply_recursively_over_nested_lists(func, arr):
if isinstance(arr, (tuple, list, Tuple)):
return tuple(
_apply_recursively_over_nested_lists(func, i) for i in arr)
elif isinstance(arr, Tuple):
return Tuple.fromiter(
_apply_recursively_over_nested_lists(func, i) for i in arr)
else:
return func(arr)
def test_Tuple():
t = (1, 2, 3, 4)
st = Tuple(*t)
assert set(sympify(t)) == set(st)
assert len(t) == len(st)
assert set(sympify(t[:2])) == set(st[:2])
assert isinstance(st[:], Tuple)
assert st == Tuple(1, 2, 3, 4)
assert st.func(*st.args) == st
p, q, r, s = symbols('p q r s')
t2 = (p, q, r, s)
st2 = Tuple(*t2)
assert st2.atoms() == set(t2)
assert st == st2.subs({p: 1, q: 2, r: 3, s: 4})
# issue 5505
assert all(isinstance(arg, Basic) for arg in st.args)
assert Tuple(p, 1).subs(p, 0) == Tuple(0, 1)
assert Tuple(p, Tuple(p, 1)).subs(p, 0) == Tuple(0, Tuple(0, 1))
assert Tuple(t2) == Tuple(Tuple(*t2))
assert Tuple.fromiter(t2) == Tuple(*t2)
assert Tuple.fromiter(x for x in range(4)) == Tuple(0, 1, 2, 3)
assert st2.fromiter(st2.args) == st2
def __new__(cls, *args):
args = list(map(sympify, args))
for i in range(len(args)):
if isinstance(args[i], list):
args[i] = Tuple.fromiter(j for j in args[i])
return Basic.__new__(cls, *args)
