1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
|
# BSD 3-Clause License; see https://github.com/scikit-hep/awkward/blob/master/LICENSE
from __future__ import annotations
import numpy as np
import awkward as ak
to_list = ak.operations.to_list
def test_bool_RecordArray():
array = ak.highlevel.Array(
[
{"x": True, "y": [True]},
{"x": False, "y": [True, False]},
]
)
assert ak._do.is_unique(array.layout) is False
assert ak._do.is_unique(array["x"].layout) is True
assert ak._do.is_unique(array["y"].layout) is False
def test_bool_UnionArray():
content1 = ak.operations.from_iter([[], [False], [True, True]], highlevel=False)
content2 = ak.operations.from_iter([[False, False], [True], []], highlevel=False)
tags = ak.index.Index8(np.array([0, 1, 0, 1, 0, 1], dtype=np.int8))
index = ak.index.Index64(np.array([0, 0, 1, 1, 2, 2], dtype=np.int64))
array = ak.contents.UnionArray.simplified(tags, index, [content1, content2])
assert to_list(array) == [
[],
[False, False],
[False],
[True],
[True, True],
[],
]
assert ak._do.is_unique(array) is False
assert to_list(ak._do.unique(array, axis=None)) == [False, True]
assert to_list(ak._do.unique(array, axis=-1)) == [
[],
[False],
[False],
[True],
[True],
[],
]
def test_bool_IndexedArray():
content = ak.from_iter([[True], [False]], highlevel=False)
index = ak.index.Index64(np.array([1, 0], dtype=np.int64))
indexedarray = ak.contents.IndexedArray(index, content)
assert ak._do.is_unique(indexedarray) is True
listoffsetarray = ak.operations.from_iter([[True], [False]], highlevel=False)
index = ak.index.Index64(np.array([1, 0], dtype=np.int64))
indexedarray = ak.contents.IndexedArray(index, listoffsetarray)
assert to_list(indexedarray) == [
[False],
[True],
]
assert ak._do.is_unique(indexedarray) is True
assert ak._do.is_unique(indexedarray) is True
assert to_list(ak._do.unique(indexedarray)) == [
False,
True,
]
assert to_list(ak._do.unique(indexedarray, axis=-1)) == [
[False],
[True],
]
def test_bool_subranges_equal():
array = ak.contents.NumpyArray(
np.array(
[
[True, False, True, True, False],
[False, False, True, True, True],
[False, True, False, True, True],
]
)
)
starts = ak.index.Index64(np.array([0, 5, 10]))
stops = ak.index.Index64(np.array([5, 10, 15]))
result = ak.sort(array, axis=-1, highlevel=False).content._subranges_equal(
starts, stops, 15
)
assert result is True
starts = ak.index.Index64(np.array([0, 7]))
stops = ak.index.Index64(np.array([7, 15]))
assert (
ak.sort(array, axis=-1, highlevel=False).content._subranges_equal(
starts, stops, 15
)
is False
)
starts = ak.index.Index64(np.array([0]))
stops = ak.index.Index64(np.array([15]))
assert (
ak.sort(array, axis=-1, highlevel=False).content._subranges_equal(
starts, stops, 15
)
is False
)
|
