def test_Record():
record = awkward1.Record({"x": 1, "y": [1, 2, 3]})
@numba.njit
def f1():
return record.y[1]
assert f1() == 2
def test_record():
assert awkward1.to_list(awkward1.Record({
"x": 1,
"y": 2.2
})) == {
"x": 1,
"y": 2.2
}
def test():
np_array = numpy.array([0.0, 1.1, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7, 8.8, 9.9])
one = awkward1.Array(np_array)
np_array[1] = 999
assert awkward1.to_list(one) == [
0.0, 999, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7, 8.8, 9.9
]
two = copy.copy(one)
np_array[3] = 123
assert awkward1.to_list(two) == [
0.0, 999, 2.2, 123, 4.4, 5.5, 6.6, 7.7, 8.8, 9.9
]
three = copy.deepcopy(two)
four = numpy.copy(two)
np_array[5] = 321
assert awkward1.to_list(three) == [
0.0, 999, 2.2, 123, 4.4, 5.5, 6.6, 7.7, 8.8, 9.9
]
assert awkward1.to_list(four) == [
0.0, 999, 2.2, 123, 4.4, 5.5, 6.6, 7.7, 8.8, 9.9
]
assert awkward1.to_list(
copy.deepcopy(awkward1.Array([[1, 2, 3], [], [4, 5]]))) == [[1, 2, 3],
[], [4, 5]]
assert awkward1.to_list(
copy.deepcopy(awkward1.Record({
"one": 1,
"two": 2.2
}))) == awkward1.to_list(
copy.deepcopy(awkward1.Record({
"one": 1,
"two": 2.2
})))
def _apply_global_index(self, index):
"""Internal method to take from a collection using a flat index
This is often necessary to be able to still resolve cross-references on
reduced arrays or single records.
"""
if isinstance(index, int):
out = self._content()[index]
return awkward1.Record(out, behavior=self.behavior)
def flat_take(layout):
idx = awkward1.Array(layout)
return self._content()[idx.mask[idx >= 0]]
def descend(layout, depth):
if layout.purelist_depth == 1:
return lambda: flat_take(layout)
(index, ) = awkward1.broadcast_arrays(index)
out = awkward1._util.recursively_apply(index.layout, descend)
return awkward1.Array(out, behavior=self.behavior)
def test_record():
assert pickle.loads(
pickle.dumps(awkward1.Record({
"x": 2.2,
"y": [1, 2]
}), -1)) == {
"x": 2.2,
"y": [1, 2]
}
assert pickle.loads(
pickle.dumps(
awkward1.Array([{
"x": 1.1,
"y": [1]
}, {
"x": 2.2,
"y": [1, 2]
}, {
"x": 3.3,
"y": [1, 2, 3]
}])[1], -1)) == {
"x": 2.2,
"y": [1, 2]
}