Fixes to the array-api stubs

src/array_api_stubs/_2022_12/fft.py

@@ -35,7 +35,7 @@ def fft(
     Parameters
     ----------
     x: array
-        input array. Should have a complex-valued floating-point data type.
+        input array. Should have a complex floating-point data type.
     n: Optional[int]
         number of elements over which to compute the transform along the axis (dimension) specified by ``axis``. Let ``M`` be the size of the input array along the axis specified by ``axis``. When ``n`` is ``None``, the function must set ``n`` equal to ``M``.
 
@@ -84,7 +84,7 @@ def ifft(
     Parameters
     ----------
     x: array
-        input array. Should have a complex-valued floating-point data type.
+        input array. Should have a complex floating-point data type.
     n: Optional[int]
         number of elements over which to compute the transform along the axis (dimension) specified by ``axis``. Let ``M`` be the size of the input array along the axis specified by ``axis``. When ``n`` is ``None``, the function must set ``n`` equal to ``M``.
 
@@ -133,7 +133,7 @@ def fftn(
     Parameters
     ----------
     x: array
-        input array. Should have a complex-valued floating-point data type.
+        input array. Should have a complex floating-point data type.
     s: Optional[Sequence[int]]
         number of elements over which to compute the transform along the axes (dimensions) specified by ``axes``. Let ``i`` be the index of the ``n``-th axis specified by ``axes`` (i.e., ``i = axes[n]``) and ``M[i]`` be the size of the input array along axis ``i``. When ``s`` is ``None``, the function must set ``s`` equal to a sequence of integers such that ``s[i]`` equals ``M[i]`` for all ``i``.
 
@@ -188,7 +188,7 @@ def ifftn(
     Parameters
     ----------
     x: array
-        input array. Should have a complex-valued floating-point data type.
+        input array. Should have a complex floating-point data type.
     s: Optional[Sequence[int]]
         number of elements over which to compute the transform along the axes (dimensions) specified by ``axes``. Let ``i`` be the index of the ``n``-th axis specified by ``axes`` (i.e., ``i = axes[n]``) and ``M[i]`` be the size of the input array along axis ``i``. When ``s`` is ``None``, the function must set ``s`` equal to a sequence of integers such that ``s[i]`` equals ``M[i]`` for all ``i``.
 
@@ -292,7 +292,7 @@ def irfft(
     Parameters
     ----------
     x: array
-        input array. Should have a complex-valued floating-point data type.
+        input array. Should have a complex floating-point data type.
     n: Optional[int]
         number of elements along the transformed axis (dimension) specified by ``axis`` in the **output array**. Let ``M`` be the size of the input array along the axis specified by ``axis``. When ``n`` is ``None``, the function must set ``n`` equal to ``2*(M-1)``.
 
@@ -398,7 +398,7 @@ def irfftn(
     Parameters
     ----------
     x: array
-        input array. Should have a complex-valued floating-point data type.
+        input array. Should have a complex floating-point data type.
     s: Optional[Sequence[int]]
         number of elements along the transformed axes (dimensions) specified by ``axes`` in the **output array**. Let ``i`` be the index of the ``n``-th axis specified by ``axes`` (i.e., ``i = axes[n]``) and ``M[i]`` be the size of the input array along axis ``i``. When ``s`` is ``None``, the function must set ``s`` equal to a sequence of integers such that ``s[i]`` equals ``M[i]`` for all ``i``, except for the last transformed axis in which ``s[i]`` equals ``2*(M[i]-1)``. For each ``i``, let ``n`` equal ``s[i]``, except for the last transformed axis in which ``n`` equals ``s[i]//2+1``.
 
@@ -452,7 +452,7 @@ def hfft(
     Parameters
     ----------
     x: array
-        input array. Should have a complex-valued floating-point data type.
+        input array. Should have a complex floating-point data type.
     n: Optional[int]
         number of elements along the transformed axis (dimension) specified by ``axis`` in the **output array**. Let ``M`` be the size of the input array along the axis specified by ``axis``. When ``n`` is ``None``, the function must set ``n`` equal to ``2*(M-1)``.
 

src/array_api_stubs/_2023_12/__init__.py

@@ -16,7 +16,7 @@
 from .utility_functions import *
 from . import linalg
 from . import fft
-from . import info
+from .info import __array_namespace_info__
 
 
 __array_api_version__: str = "YYYY.MM"

src/array_api_stubs/_2023_12/elementwise_functions.py

@@ -874,14 +874,12 @@ def copysign(x1: array, x2: array, /) -> array:
     - If ``x2_i`` is ``NaN`` and the sign bit of ``x2_i`` is ``1``, the result is ``-|x1_i|``.
     - If ``x2_i`` is ``NaN`` and the sign bit of ``x2_i`` is ``0``, the result is ``|x1_i|``.
 
-    If ``x1_i`` is ``NaN``,
-
-    - If ``x2_i`` is less than ``0``, the result is ``NaN`` with a sign bit of ``1``.
-    - If ``x2_i`` is ``-0``, the result is ``NaN`` with a sign bit of ``1``.
-    - If ``x2_i`` is ``+0``, the result is ``NaN`` with a sign bit of ``0``.
-    - If ``x2_i`` is greater than ``0``, the result is ``NaN`` with a sign bit of ``0``.
-    - If ``x2_i`` is ``NaN`` and the sign bit of ``x2_i`` is ``1``, the result is ``NaN`` with a sign bit of ``1``.
-    - If ``x2_i`` is ``NaN`` and the sign bit of ``x2_i`` is ``0``, the result is ``NaN`` with a sign bit of ``0``.
+    - If ``x1_i`` is ``NaN`` and ``x2_i`` is less than ``0``, the result is ``NaN`` with a sign bit of ``1``.
+    - If ``x1_i`` is ``NaN`` and ``x2_i`` is ``-0``, the result is ``NaN`` with a sign bit of ``1``.
+    - If ``x1_i`` is ``NaN`` and ``x2_i`` is ``+0``, the result is ``NaN`` with a sign bit of ``0``.
+    - If ``x1_i`` is ``NaN`` and ``x2_i`` is greater than ``0``, the result is ``NaN`` with a sign bit of ``0``.
+    - If ``x1_i`` is ``NaN`` and ``x2_i`` is ``NaN`` and the sign bit of ``x2_i`` is ``1``, the result is ``NaN`` with a sign bit of ``1``.
+    - If ``x1_i`` is ``NaN`` and ``x2_i`` is ``NaN`` and the sign bit of ``x2_i`` is ``0``, the result is ``NaN`` with a sign bit of ``0``.
 
     .. versionadded:: 2023.12
     """

src/array_api_stubs/_2023_12/fft.py

@@ -35,7 +35,7 @@ def fft(
     Parameters
     ----------
     x: array
-        input array. Should have a complex-valued floating-point data type.
+        input array. Should have a complex floating-point data type.
     n: Optional[int]
         number of elements over which to compute the transform along the axis (dimension) specified by ``axis``. Let ``M`` be the size of the input array along the axis specified by ``axis``. When ``n`` is ``None``, the function must set ``n`` equal to ``M``.
 
@@ -66,7 +66,7 @@ def fft(
     .. versionadded:: 2022.12
 
     .. versionchanged:: 2023.12
-       Required the input array have a complex-valued floating-point data type and required that the output array have the same data type as the input array.
+       Required the input array have a complex floating-point data type and required that the output array have the same data type as the input array.
     """
 
 
@@ -87,7 +87,7 @@ def ifft(
     Parameters
     ----------
     x: array
-        input array. Should have a complex-valued floating-point data type.
+        input array. Should have a complex floating-point data type.
     n: Optional[int]
         number of elements over which to compute the transform along the axis (dimension) specified by ``axis``. Let ``M`` be the size of the input array along the axis specified by ``axis``. When ``n`` is ``None``, the function must set ``n`` equal to ``M``.
 
@@ -118,7 +118,7 @@ def ifft(
     .. versionadded:: 2022.12
 
     .. versionchanged:: 2023.12
-       Required the input array have a complex-valued floating-point data type and required that the output array have the same data type as the input array.
+       Required the input array have a complex floating-point data type and required that the output array have the same data type as the input array.
     """
 
 
@@ -139,7 +139,7 @@ def fftn(
     Parameters
     ----------
     x: array
-        input array. Should have a complex-valued floating-point data type.
+        input array. Should have a complex floating-point data type.
     s: Optional[Sequence[int]]
         number of elements over which to compute the transform along the axes (dimensions) specified by ``axes``. Let ``i`` be the index of the ``n``-th axis specified by ``axes`` (i.e., ``i = axes[n]``) and ``M[i]`` be the size of the input array along axis ``i``. When ``s`` is ``None``, the function must set ``s`` equal to a sequence of integers such that ``s[i]`` equals ``M[i]`` for all ``i``.
 
@@ -176,7 +176,7 @@ def fftn(
     .. versionadded:: 2022.12
 
     .. versionchanged:: 2023.12
-       Required the input array have a complex-valued floating-point data type and required that the output array have the same data type as the input array.
+       Required the input array have a complex floating-point data type and required that the output array have the same data type as the input array.
     """
 
 
@@ -197,7 +197,7 @@ def ifftn(
     Parameters
     ----------
     x: array
-        input array. Should have a complex-valued floating-point data type.
+        input array. Should have a complex floating-point data type.
     s: Optional[Sequence[int]]
         number of elements over which to compute the transform along the axes (dimensions) specified by ``axes``. Let ``i`` be the index of the ``n``-th axis specified by ``axes`` (i.e., ``i = axes[n]``) and ``M[i]`` be the size of the input array along axis ``i``. When ``s`` is ``None``, the function must set ``s`` equal to a sequence of integers such that ``s[i]`` equals ``M[i]`` for all ``i``.
 
@@ -234,7 +234,7 @@ def ifftn(
     .. versionadded:: 2022.12
 
     .. versionchanged:: 2023.12
-       Required the input array have a complex-valued floating-point data type and required that the output array have the same data type as the input array.
+       Required the input array have a complex floating-point data type and required that the output array have the same data type as the input array.
     """
 
 
@@ -304,7 +304,7 @@ def irfft(
     Parameters
     ----------
     x: array
-        input array. Should have a complex-valued floating-point data type.
+        input array. Should have a complex floating-point data type.
     n: Optional[int]
         number of elements along the transformed axis (dimension) specified by ``axis`` in the **output array**. Let ``M`` be the size of the input array along the axis specified by ``axis``. When ``n`` is ``None``, the function must set ``n`` equal to ``2*(M-1)``.
 
@@ -413,7 +413,7 @@ def irfftn(
     Parameters
     ----------
     x: array
-        input array. Should have a complex-valued floating-point data type.
+        input array. Should have a complex floating-point data type.
     s: Optional[Sequence[int]]
         number of elements along the transformed axes (dimensions) specified by ``axes`` in the **output array**. Let ``i`` be the index of the ``n``-th axis specified by ``axes`` (i.e., ``i = axes[n]``) and ``M[i]`` be the size of the input array along axis ``i``. When ``s`` is ``None``, the function must set ``s`` equal to a sequence of integers such that ``s[i]`` equals ``M[i]`` for all ``i``, except for the last transformed axis in which ``s[i]`` equals ``2*(M[i]-1)``. For each ``i``, let ``n`` equal ``s[i]``, except for the last transformed axis in which ``n`` equals ``s[i]//2+1``.
 
@@ -470,7 +470,7 @@ def hfft(
     Parameters
     ----------
     x: array
-        input array. Should have a complex-valued floating-point data type.
+        input array. Should have a complex floating-point data type.
     n: Optional[int]
         number of elements along the transformed axis (dimension) specified by ``axis`` in the **output array**. Let ``M`` be the size of the input array along the axis specified by ``axis``. When ``n`` is ``None``, the function must set ``n`` equal to ``2*(M-1)``.
 
@@ -501,7 +501,7 @@ def hfft(
     .. versionadded:: 2022.12
 
     .. versionchanged:: 2023.12
-       Required the input array to have a complex-valued floating-point data type and required that the output array have a real-valued data type having the same precision as the input array.
+       Required the input array to have a complex floating-point data type and required that the output array have a real-valued data type having the same precision as the input array.
     """
 
 

src/array_api_stubs/_draft/__init__.py

@@ -16,7 +16,7 @@
 from .utility_functions import *
 from . import linalg
 from . import fft
-from . import info
+from .info import __array_namespace_info__
 
 
 __array_api_version__: str = "YYYY.MM"

src/array_api_stubs/_draft/elementwise_functions.py

@@ -875,14 +875,12 @@ def copysign(x1: array, x2: array, /) -> array:
     - If ``x2_i`` is ``NaN`` and the sign bit of ``x2_i`` is ``1``, the result is ``-|x1_i|``.
     - If ``x2_i`` is ``NaN`` and the sign bit of ``x2_i`` is ``0``, the result is ``|x1_i|``.
 
-    If ``x1_i`` is ``NaN``,
-
-    - If ``x2_i`` is less than ``0``, the result is ``NaN`` with a sign bit of ``1``.
-    - If ``x2_i`` is ``-0``, the result is ``NaN`` with a sign bit of ``1``.
-    - If ``x2_i`` is ``+0``, the result is ``NaN`` with a sign bit of ``0``.
-    - If ``x2_i`` is greater than ``0``, the result is ``NaN`` with a sign bit of ``0``.
-    - If ``x2_i`` is ``NaN`` and the sign bit of ``x2_i`` is ``1``, the result is ``NaN`` with a sign bit of ``1``.
-    - If ``x2_i`` is ``NaN`` and the sign bit of ``x2_i`` is ``0``, the result is ``NaN`` with a sign bit of ``0``.
+    - If ``x1_i`` is ``NaN`` and ``x2_i`` is less than ``0``, the result is ``NaN`` with a sign bit of ``1``.
+    - If ``x1_i`` is ``NaN`` and ``x2_i`` is ``-0``, the result is ``NaN`` with a sign bit of ``1``.
+    - If ``x1_i`` is ``NaN`` and ``x2_i`` is ``+0``, the result is ``NaN`` with a sign bit of ``0``.
+    - If ``x1_i`` is ``NaN`` and ``x2_i`` is greater than ``0``, the result is ``NaN`` with a sign bit of ``0``.
+    - If ``x1_i`` is ``NaN`` and ``x2_i`` is ``NaN`` and the sign bit of ``x2_i`` is ``1``, the result is ``NaN`` with a sign bit of ``1``.
+    - If ``x1_i`` is ``NaN`` and ``x2_i`` is ``NaN`` and the sign bit of ``x2_i`` is ``0``, the result is ``NaN`` with a sign bit of ``0``.
 
     .. versionadded:: 2023.12
     """