def test():
arr1 = ak.Array({"a": [1, 2], "b": [1, None]})
arr2 = ak.mask(arr1, [True, True])
assert isinstance(arr2.layout, ak.layout.ByteMaskedArray)
assert isinstance(arr2.layout.content, ak.layout.RecordArray)
assert isinstance(arr2.layout.content.field("b"),
ak.layout.IndexedOptionArray64)
assert isinstance(arr2.b.layout, ak.layout.IndexedOptionArray64)
assert isinstance(arr2.b.layout.content, ak.layout.NumpyArray)
assert ak.is_none(arr2.b).tolist() == [False, True]
arr3 = ak.virtual(lambda: arr2, form=arr2.layout.form, length=len(arr2))
assert ak.is_none(arr3.b).tolist() == [False, True]
def get_vpt(check_offshell=False):
"""Only the leptonic samples have no resonance in the decay tree, and only
when M is beyond the configured Breit-Wigner cutoff (usually 15*width)
"""
boson = ak.firsts(
genpart[((genpart.pdgId == 23) | (abs(genpart.pdgId) == 24))
& genpart.hasFlags(["fromHardProcess", "isLastCopy"])])
if check_offshell:
offshell = genpart[
genpart.hasFlags(["fromHardProcess", "isLastCopy"])
& ak.is_none(boson)
& (abs(genpart.pdgId) >= 11) &
(abs(genpart.pdgId) <= 16)].sum()
return ak.where(ak.is_none(boson.pt), offshell.pt, boson.pt)
return np.array(ak.fill_none(boson.pt, 0.))
def test():
index_of_index = ak.Array(
ak.layout.IndexedOptionArray64(
ak.layout.Index64(np.r_[0, 1, 2, -1]),
ak.layout.IndexedOptionArray64(
ak.layout.Index64(np.r_[0, -1, 2, 3]),
ak.layout.NumpyArray(np.r_[1, 2, 3, 4]),
),
))
mask = ak.is_none(index_of_index)
assert ak.to_list(mask) == [False, True, False, True]
def test():
assert ak.is_none(ak.Array([1, 2, 3, None, 5])).tolist() == [
False,
False,
False,
True,
False,
]
assert ak.is_none(ak.Array([[1, 2, 3], [], [None, 5]])).tolist() == [
False,
False,
False,
]
assert ak.is_none(ak.Array([[1, 2, 3], [], [None, 5]]),
axis=1).tolist() == [
[False, False, False],
[],
[True, False],
]
assert ak.is_none(ak.Array([[1, None, 2, 3], [], [None, 5]]),
axis=1).tolist() == [
[False, True, False, False],
[],
[True, False],
]
assert ak.is_none(ak.Array([[1, None, 2, 3], [], [None, 5]]),
axis=-1).tolist() == [
[False, True, False, False],
[],
[True, False],
]
assert ak.is_none(ak.Array([[1, None, 2, 3], [], [None, 5]]),
axis=-2).tolist() == [
False,
False,
False,
]
assert ak.is_none(ak.Array([[1, None, 2, 3], None, [None, 5]]),
axis=-2).tolist() == [False, True, False]
with pytest.raises(ValueError):
ak.is_none(ak.Array([[1, None, 2, 3], [], [None, 5]]), axis=-3)
def test_na_union():
one = ak.from_iter([1, None, 3], highlevel=False)
two = ak.from_iter([[], [1], None, [3, 3, 3]], highlevel=False)
tags = ak.layout.Index8(np.array([0, 1, 1, 0, 0, 1, 1], dtype=np.int8))
index = ak.layout.Index64(np.array([0, 0, 1, 1, 2, 2, 3], dtype=np.int64))
array = ak.Array(ak.layout.UnionArray8_64(tags, index, [one, two]),
check_valid=True)
assert ak.to_list(array) == [1, [], [1], None, 3, None, [3, 3, 3]]
assert ak.to_list(ak.is_none(array)) == [
False,
False,
False,
True,
False,
True,
False,
]
def num(ar):
return ak.num(ak.fill_none(ar[~ak.is_none(ar)], 0), axis=0)
def skim_weight(arr):
mask1 = ~ak.is_none(arr)
subarr = arr[mask1]
mask2 = subarr != 0
return ak.to_numpy(subarr[mask2])
def test_numpy_array():
x = np.arange(12)
y = ak.is_none(x)
assert y.tolist() == [False] * 12
def test_awkward_from_numpy_array():
x = np.arange(12)
y = ak.from_numpy(x)
z = ak.is_none(y)
assert z.tolist() == [False] * 12
