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
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
|
from collections.abc import Sequence
from typing import (
Any,
TypeVar,
Generic,
overload,
Literal,
SupportsIndex,
)
from numpy import (
# Circumvent a naming conflict with `AxisConcatenator.matrix`
matrix as _Matrix,
ndenumerate as ndenumerate,
ndindex as ndindex,
ndarray,
dtype,
integer,
str_,
bytes_,
bool_,
int_,
float_,
complex_,
intp,
_OrderCF,
_ModeKind,
)
from numpy._typing import (
# Arrays
ArrayLike,
_NestedSequence,
_FiniteNestedSequence,
NDArray,
_ArrayLikeInt,
# DTypes
DTypeLike,
_SupportsDType,
# Shapes
_ShapeLike,
)
from numpy.core.multiarray import (
unravel_index as unravel_index,
ravel_multi_index as ravel_multi_index,
)
_T = TypeVar("_T")
_DType = TypeVar("_DType", bound=dtype[Any])
_BoolType = TypeVar("_BoolType", Literal[True], Literal[False])
_TupType = TypeVar("_TupType", bound=tuple[Any, ...])
_ArrayType = TypeVar("_ArrayType", bound=ndarray[Any, Any])
__all__: list[str]
@overload
def ix_(*args: _FiniteNestedSequence[_SupportsDType[_DType]]) -> tuple[ndarray[Any, _DType], ...]: ...
@overload
def ix_(*args: str | _NestedSequence[str]) -> tuple[NDArray[str_], ...]: ...
@overload
def ix_(*args: bytes | _NestedSequence[bytes]) -> tuple[NDArray[bytes_], ...]: ...
@overload
def ix_(*args: bool | _NestedSequence[bool]) -> tuple[NDArray[bool_], ...]: ...
@overload
def ix_(*args: int | _NestedSequence[int]) -> tuple[NDArray[int_], ...]: ...
@overload
def ix_(*args: float | _NestedSequence[float]) -> tuple[NDArray[float_], ...]: ...
@overload
def ix_(*args: complex | _NestedSequence[complex]) -> tuple[NDArray[complex_], ...]: ...
class nd_grid(Generic[_BoolType]):
sparse: _BoolType
def __init__(self, sparse: _BoolType = ...) -> None: ...
@overload
def __getitem__(
self: nd_grid[Literal[False]],
key: slice | Sequence[slice],
) -> NDArray[Any]: ...
@overload
def __getitem__(
self: nd_grid[Literal[True]],
key: slice | Sequence[slice],
) -> list[NDArray[Any]]: ...
class MGridClass(nd_grid[Literal[False]]):
def __init__(self) -> None: ...
mgrid: MGridClass
class OGridClass(nd_grid[Literal[True]]):
def __init__(self) -> None: ...
ogrid: OGridClass
class AxisConcatenator:
axis: int
matrix: bool
ndmin: int
trans1d: int
def __init__(
self,
axis: int = ...,
matrix: bool = ...,
ndmin: int = ...,
trans1d: int = ...,
) -> None: ...
@staticmethod
@overload
def concatenate( # type: ignore[misc]
*a: ArrayLike, axis: SupportsIndex = ..., out: None = ...
) -> NDArray[Any]: ...
@staticmethod
@overload
def concatenate(
*a: ArrayLike, axis: SupportsIndex = ..., out: _ArrayType = ...
) -> _ArrayType: ...
@staticmethod
def makemat(
data: ArrayLike, dtype: DTypeLike = ..., copy: bool = ...
) -> _Matrix[Any, Any]: ...
# TODO: Sort out this `__getitem__` method
def __getitem__(self, key: Any) -> Any: ...
class RClass(AxisConcatenator):
axis: Literal[0]
matrix: Literal[False]
ndmin: Literal[1]
trans1d: Literal[-1]
def __init__(self) -> None: ...
r_: RClass
class CClass(AxisConcatenator):
axis: Literal[-1]
matrix: Literal[False]
ndmin: Literal[2]
trans1d: Literal[0]
def __init__(self) -> None: ...
c_: CClass
class IndexExpression(Generic[_BoolType]):
maketuple: _BoolType
def __init__(self, maketuple: _BoolType) -> None: ...
@overload
def __getitem__(self, item: _TupType) -> _TupType: ... # type: ignore[misc]
@overload
def __getitem__(self: IndexExpression[Literal[True]], item: _T) -> tuple[_T]: ...
@overload
def __getitem__(self: IndexExpression[Literal[False]], item: _T) -> _T: ...
index_exp: IndexExpression[Literal[True]]
s_: IndexExpression[Literal[False]]
def fill_diagonal(a: ndarray[Any, Any], val: Any, wrap: bool = ...) -> None: ...
def diag_indices(n: int, ndim: int = ...) -> tuple[NDArray[int_], ...]: ...
def diag_indices_from(arr: ArrayLike) -> tuple[NDArray[int_], ...]: ...
# NOTE: see `numpy/__init__.pyi` for `ndenumerate` and `ndindex`
|