forked from psf/black
/
power_op_spacing.py
149 lines (125 loc) · 3.45 KB
/
power_op_spacing.py
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def function(**kwargs):
t = a**2 + b**3
return t ** 2
def function_replace_spaces(**kwargs):
t = a **2 + b** 3 + c ** 4
def function_dont_replace_spaces():
{**a, **b, **c}
a = 5**~4
b = 5 ** f()
c = -(5**2)
d = 5 ** f["hi"]
e = lazy(lambda **kwargs: 5)
f = f() ** 5
g = a.b**c.d
h = 5 ** funcs.f()
i = funcs.f() ** 5
j = super().name ** 5
k = [(2**idx, value) for idx, value in pairs]
l = mod.weights_[0] == pytest.approx(0.95**100, abs=0.001)
m = [([2**63], [1, 2**63])]
n = count <= 10**5
o = settings(max_examples=10**6)
p = {(k, k**2): v**2 for k, v in pairs}
q = [10**i for i in range(6)]
r = x**y
s = 1 ** 1
t = (
1
** 1
**1
** 1
)
a = 5.0**~4.0
b = 5.0 ** f()
c = -(5.0**2.0)
d = 5.0 ** f["hi"]
e = lazy(lambda **kwargs: 5)
f = f() ** 5.0
g = a.b**c.d
h = 5.0 ** funcs.f()
i = funcs.f() ** 5.0
j = super().name ** 5.0
k = [(2.0**idx, value) for idx, value in pairs]
l = mod.weights_[0] == pytest.approx(0.95**100, abs=0.001)
m = [([2.0**63.0], [1.0, 2**63.0])]
n = count <= 10**5.0
o = settings(max_examples=10**6.0)
p = {(k, k**2): v**2.0 for k, v in pairs}
q = [10.5**i for i in range(6)]
s = 1.0 ** 1.0
t = (
1.0
** 1.0
**1.0
** 1.0
)
# WE SHOULD DEFINITELY NOT EAT THESE COMMENTS (https://github.com/psf/black/issues/2873)
if hasattr(view, "sum_of_weights"):
return np.divide( # type: ignore[no-any-return]
view.variance, # type: ignore[union-attr]
view.sum_of_weights, # type: ignore[union-attr]
out=np.full(view.sum_of_weights.shape, np.nan), # type: ignore[union-attr]
where=view.sum_of_weights**2 > view.sum_of_weights_squared, # type: ignore[union-attr]
)
return np.divide(
where=view.sum_of_weights_of_weight_long**2 > view.sum_of_weights_squared, # type: ignore
)
# output
def function(**kwargs):
t = a**2 + b**3
return t**2
def function_replace_spaces(**kwargs):
t = a**2 + b**3 + c**4
def function_dont_replace_spaces():
{**a, **b, **c}
a = 5**~4
b = 5 ** f()
c = -(5**2)
d = 5 ** f["hi"]
e = lazy(lambda **kwargs: 5)
f = f() ** 5
g = a.b**c.d
h = 5 ** funcs.f()
i = funcs.f() ** 5
j = super().name ** 5
k = [(2**idx, value) for idx, value in pairs]
l = mod.weights_[0] == pytest.approx(0.95**100, abs=0.001)
m = [([2**63], [1, 2**63])]
n = count <= 10**5
o = settings(max_examples=10**6)
p = {(k, k**2): v**2 for k, v in pairs}
q = [10**i for i in range(6)]
r = x**y
s = 1**1
t = 1**1**1**1
a = 5.0**~4.0
b = 5.0 ** f()
c = -(5.0**2.0)
d = 5.0 ** f["hi"]
e = lazy(lambda **kwargs: 5)
f = f() ** 5.0
g = a.b**c.d
h = 5.0 ** funcs.f()
i = funcs.f() ** 5.0
j = super().name ** 5.0
k = [(2.0**idx, value) for idx, value in pairs]
l = mod.weights_[0] == pytest.approx(0.95**100, abs=0.001)
m = [([2.0**63.0], [1.0, 2**63.0])]
n = count <= 10**5.0
o = settings(max_examples=10**6.0)
p = {(k, k**2): v**2.0 for k, v in pairs}
q = [10.5**i for i in range(6)]
s = 1.0**1.0
t = 1.0**1.0**1.0**1.0
# WE SHOULD DEFINITELY NOT EAT THESE COMMENTS (https://github.com/psf/black/issues/2873)
if hasattr(view, "sum_of_weights"):
return np.divide( # type: ignore[no-any-return]
view.variance, # type: ignore[union-attr]
view.sum_of_weights, # type: ignore[union-attr]
out=np.full(view.sum_of_weights.shape, np.nan), # type: ignore[union-attr]
where=view.sum_of_weights**2 > view.sum_of_weights_squared, # type: ignore[union-attr]
)
return np.divide(
where=view.sum_of_weights_of_weight_long**2 > view.sum_of_weights_squared, # type: ignore
)