numpy · shoyer · Jan 14, 2020 · Nov 24, 2019 · Nov 24, 2019 · Nov 24, 2019
commit 2c705800b0372dfc7415ec4b8fdb0e3eb8c27bd9
diff --git a/.gitignore b/.gitignore
@@ -2,3 +2,5 @@
 .pytest_cache
 __pycache__
 numpy_stubs.egg-info/
+venv
+.idea
diff --git a/numpy-stubs/__init__.pyi b/numpy-stubs/__init__.pyi
@@ -82,6 +82,8 @@ _DtypeLike = Union[
 
 _NdArraySubClass = TypeVar("_NdArraySubClass", bound=ndarray)
 
+_ArrayLike = TypeVar("_ArrayLike", str, int, float, bool, object, ByteString, Iterable, Container, ndarray)
+
 class dtype:
     names: Optional[Tuple[str, ...]]
     def __init__(

diff --git a/numpy-stubs/core/numeric.pyi b/numpy-stubs/core/numeric.pyi
@@ -0,0 +1,155 @@
+from types import ModuleType
+from typing import Sequence, Optional, TypeVar, Union, Tuple, List, Iterable, Callable, Any
+
+from numpy import (ndarray, dtype, _ArrayLike, _ShapeLike)
+
+T = TypeVar('T')
+
+
+def zeros_like(
+        a: _ArrayLike,
+        dtype: Optional[dtype] = None,
+        order: str = 'K',
+        subok: bool = True,
+        shape: Optional[Union[int, Sequence[int]]] = None) -> ndarray[int]: ...
+
+
+def ones(
+        shape: _ShapeLike,
+        dtype: Optional[dtype] = None,
+        order: str = 'C') -> ndarray[int]: ...
+
+
+def ones_like(
+        a: _ArrayLike,
+        dtype: Optional[dtype] = None,
+        order: str = 'K',
+        subok: bool = True,
+        shape: Optional[_ShapeLike] = None) -> ndarray[int]: ...
+
+
+def full(
+        shape: _ShapeLike,
+        fill_value: T,
+        dtype: Optional[dtype] = None,
+        order: str = 'C') -> ndarray[T]:  ...
+
+
+def full_like(
+        a: _ArrayLike,
+        fill_value: T,
+        dtype: Optional[dtype] = None,
+        order: str = 'K',
+        subok: bool = True,
+        shape: Optional[_ShapeLike] = None) -> ndarray[T]: ...
+
+
+def count_nonzero(
+        a: _ArrayLike,
+        axis: Optional[Union[int, Tuple[int], Tuple[int, int]]] = None) -> Union[int, ndarray[int]]: ...
+
+
+def isfortran(a: ndarray) -> bool: ...
+
+
+def argwhere(a: _ArrayLike) -> ndarray: ...
+
+
+def flatnonzero(a: _ArrayLike) -> ndarray: ...
+
+
+def correlate(a: _ArrayLike, v: _ArrayLike, mode: str = 'valid') -> ndarray: ...
+
+
+def convolve(a: _ArrayLike, v: _ArrayLike, mode: str = 'full') -> ndarray: ...
+
+
+def outer(a: _ArrayLike, b: _ArrayLike, out: ndarray = None) -> ndarray: ...
+
+
+def tensordot(
+        a: _ArrayLike,
+        b: _ArrayLike,
+        axes: Union[int, Tuple[int, int], Tuple[Tuple[int, int], ...], Tuple[List[int, int], ...]] = 2) -> ndarray: ...
+
+
+def roll(a: _ArrayLike,
+             shift: Union[int, Tuple[int, ...]],
+         axis: Optional[Union[int, Tuple[int, ...]]] = None) -> T: ...
+
+
+def rollaxis(
+        a: _ArrayLike,
+        axis: int,
+        start: int = 0) -> ndarray: ...
+
+
+def normalize_axis_tuple(
+        axis: Union[int, Iterable[int]],
+        ndim: int,
+        argname: Optional[str] = None,
+        allow_duplicate: bool = False) -> Tuple[int, ...]: ...
+
+
+def moveaxis(
+        a: ndarray,
+        source: Union[int, Sequence[int]],
+        destination: Union[int, Sequence[int]]) -> ndarray: ...
+
+
+def cross(
+        a: _ArrayLike,
+        b: _ArrayLike,
+        axisa: int = -1,
+        axisb: int = -1,
+        axisc: int = -1,
+        axis: Optional[int] = None) -> ndarray: ...
+
+
+def indices(
+        dimensions: Sequence[int],
+        dtype: dtype = int,
+        sparse: bool = False) -> Union[ndarray, Tuple[ndarray, ...]]: ...
+
+
+def fromfunction(
+        function: Callable,
+        shape: Tuple[int, int],
+        **kwargs) -> Any: ...
+
+
+def isscalar(element: Any) -> bool: ...
+
+
+def binary_repr(num: int, width: Optional[int] = None) -> str: ...
+
+
+def base_repr(number: int, base: int = 2, padding: int = 0) -> str: ...
+
+
+def identity(n: int, dtype: Optional[dtype] = None) -> ndarray: ...
+
+
+def allclose(
+        a: _ArrayLike,
+        b: _ArrayLike,
+        rtol: float = 1.e-5,
+        atol: float = 1.e-8,
+        equal_nan: bool = False) -> bool: ...
+
+
+def isclose(
+        a: _ArrayLike,
+        b: _ArrayLike,
+        rtol: float = 1.e-5,
+        atol: float = 1.e-8,
+        equal_nan: bool = False) -> _ArrayLike: ...
+
+
+def array_equal(a1: _ArrayLike, a2: _ArrayLike) -> bool: ...
+
+
+def array_equiv(a1: _ArrayLike, a2: _ArrayLike) -> bool: ...
+
+
+def extend_all(module: ModuleType): ...