diff options
Diffstat (limited to 'numpy/_array_api/_array_object.py')
| -rw-r--r-- | numpy/_array_api/_array_object.py | 32 |
1 files changed, 16 insertions, 16 deletions
diff --git a/numpy/_array_api/_array_object.py b/numpy/_array_api/_array_object.py index 89ec3ba1a..9ea0eef18 100644 --- a/numpy/_array_api/_array_object.py +++ b/numpy/_array_api/_array_object.py @@ -22,13 +22,13 @@ from ._dtypes import _boolean_dtypes, _integer_dtypes, _floating_dtypes from typing import TYPE_CHECKING if TYPE_CHECKING: - from ._types import Any, Optional, PyCapsule, Tuple, Union, Array + from ._types import Any, Optional, PyCapsule, Tuple, Union, Device, Dtype import numpy as np -class ndarray: +class Array: """ - ndarray object for the array API namespace. + n-d array object for the array API namespace. See the docstring of :py:obj:`np.ndarray <numpy.ndarray>` for more information. @@ -46,7 +46,7 @@ class ndarray: @classmethod def _new(cls, x, /): """ - This is a private method for initializing the array API ndarray + This is a private method for initializing the array API Array object. Functions outside of the array_api submodule should not use this @@ -64,9 +64,9 @@ class ndarray: obj._array = x return obj - # Prevent ndarray() from working + # Prevent Array() from working def __new__(cls, *args, **kwargs): - raise TypeError("The array_api ndarray object should not be instantiated directly. Use an array creation function, such as asarray(), instead.") + raise TypeError("The array_api Array object should not be instantiated directly. Use an array creation function, such as asarray(), instead.") # These functions are not required by the spec, but are implemented for # the sake of usability. @@ -75,13 +75,13 @@ class ndarray: """ Performs the operation __str__. """ - return self._array.__str__().replace('array', 'ndarray') + return self._array.__str__().replace('array', 'Array') def __repr__(self: Array, /) -> str: """ Performs the operation __repr__. """ - return self._array.__repr__().replace('array', 'ndarray') + return self._array.__repr__().replace('array', 'Array') # Helper function to match the type promotion rules in the spec def _promote_scalar(self, scalar): @@ -109,7 +109,7 @@ class ndarray: # behavior for integers within the bounds of the integer dtype. # Outside of those bounds we use the default NumPy behavior (either # cast or raise OverflowError). - return ndarray._new(np.array(scalar, self.dtype)) + return Array._new(np.array(scalar, self.dtype)) @staticmethod def _normalize_two_args(x1, x2): @@ -135,9 +135,9 @@ class ndarray: # performant. broadcast_to(x1._array, x2.shape) is much slower. We # could also manually type promote x2, but that is more complicated # and about the same performance as this. - x1 = ndarray._new(x1._array[None]) + x1 = Array._new(x1._array[None]) elif x2.shape == () and x1.shape != (): - x2 = ndarray._new(x2._array[None]) + x2 = Array._new(x2._array[None]) return (x1, x2) # Everything below this line is required by the spec. @@ -284,7 +284,7 @@ class ndarray: Additionally, it should be noted that indices that would return a scalar in NumPy will return a shape () array. Array scalars are not allowed in the specification, only shape () arrays. This is done in the - ``ndarray._new`` constructor, not this function. + ``Array._new`` constructor, not this function. """ if isinstance(key, slice): @@ -313,7 +313,7 @@ class ndarray: return key elif isinstance(key, tuple): - key = tuple(ndarray._validate_index(idx, None) for idx in key) + key = tuple(Array._validate_index(idx, None) for idx in key) for idx in key: if isinstance(idx, np.ndarray) and idx.dtype in _boolean_dtypes or isinstance(idx, (bool, np.bool_)): @@ -329,11 +329,11 @@ class ndarray: ellipsis_i = key.index(...) if n_ellipsis else len(key) for idx, size in list(zip(key[:ellipsis_i], shape)) + list(zip(key[:ellipsis_i:-1], shape[:ellipsis_i:-1])): - ndarray._validate_index(idx, (size,)) + Array._validate_index(idx, (size,)) return key elif isinstance(key, bool): return key - elif isinstance(key, ndarray): + elif isinstance(key, Array): if key.dtype in _integer_dtypes: if key.shape != (): raise IndexError("Integer array indices with shape != () are not allowed in the array API namespace") @@ -346,7 +346,7 @@ class ndarray: return operator.index(key) except TypeError: # Note: This also omits boolean arrays that are not already in - # ndarray() form, like a list of booleans. + # Array() form, like a list of booleans. raise IndexError("Only integers, slices (`:`), ellipsis (`...`), and boolean arrays are valid indices in the array API namespace") def __getitem__(self: Array, key: Union[int, slice, ellipsis, Tuple[Union[int, slice, ellipsis], ...], Array], /) -> Array: |