def test_basics(self):
D = Domain("d", 0, 10)
assert D._name == "d"
assert D._low == 0
assert D._high == 10
assert D._res == 1
x = Set(lambda x: 1)
D.s = x
assert D.s == x
assert D._sets == {"s": x}
R = D(3)
assert R == {D.s: 1}
def test_eq(self, low, high, res):
"""This also tests Set.array().
This test can massively slow down hypothesis with even
reasonably large/small values.
"""
assume(low < high)
# to avoid MemoryError and runs that take forever..
assume(high - low <= 10)
D1 = Domain("1", low, high, res=res)
D1.s1 = fun.bounded_linear(low, high)
D2 = Domain("2", low, high, res=res)
D2.s2 = Set(fun.bounded_linear(low, high))
assert D1.s1 == D2.s2
def temp():
d = Domain("temperature", -100, 100, res=0.1) # in Celsius
d.cold = S(0, 15) # sic
d.hot = Set(R(10, 30)) # sic
d.warm = ~d.cold & ~d.hot
return d
def test_complement(self):
D = Domain("d", 0, 10, res=0.1)
D.s1 = Set(fun.bounded_linear(3, 12))
D.s2 = ~~D.s1
assert all(np.isclose(D.s1.array(), D.s2.array()))
def test_sub_super_set(self):
D = Domain("d", 0, 10, res=0.1)
D.s = Set(fun.bounded_linear(3, 12))
D.x = D.s.normalized()
assert D.x >= D.s
assert D.s <= D.x
def test_normalized(self):
D = Domain("d", 0, 10, res=0.1)
D.s = Set(fun.bounded_linear(3, 12))
D.x = D.s.normalized()
D.y = D.x.normalized()
assert D.x == D.y
def test_plus(self, x):
s = Set(fun.noop())
f = hedges.plus(s)
assert 0 <= f(x) <= 1
def test_very(self, x):
s = Set(fun.noop())
f = hedges.very(s)
assert 0 <= f(x) <= 1
def test_minus(self, x):
s = Set(fun.noop())
f = hedges.minus(s)
assert (0 <= f(x) <= 1)