Merge branch 'main' into document_diag_indices_from

1 files changed, 7 insertions, 7 deletions

diff --git a/numpy/core/multiarray.py b/numpy/core/multiarray.py
index 31b779783..ec1294b85 100644
--- a/numpy/core/multiarray.py
+++ b/numpy/core/multiarray.py
@@ -14,7 +14,7 @@ from ._multiarray_umath import *  # noqa: F403
 # do not change them. issue gh-15518
 # _get_ndarray_c_version is semi-public, on purpose not added to __all__
 from ._multiarray_umath import (
-    fastCopyAndTranspose, _flagdict, from_dlpack, _insert, _reconstruct,
+    fastCopyAndTranspose, _flagdict, from_dlpack, _place, _reconstruct,
     _vec_string, _ARRAY_API, _monotonicity, _get_ndarray_c_version,
     _get_madvise_hugepage, _set_madvise_hugepage,
     _get_promotion_state, _set_promotion_state,
@@ -25,7 +25,7 @@ __all__ = [
     'ITEM_HASOBJECT', 'ITEM_IS_POINTER', 'LIST_PICKLE', 'MAXDIMS',
     'MAY_SHARE_BOUNDS', 'MAY_SHARE_EXACT', 'NEEDS_INIT', 'NEEDS_PYAPI',
     'RAISE', 'USE_GETITEM', 'USE_SETITEM', 'WRAP',
-    '_flagdict', 'from_dlpack', '_insert', '_reconstruct', '_vec_string',
+    '_flagdict', 'from_dlpack', '_place', '_reconstruct', '_vec_string',
     '_monotonicity', 'add_docstring', 'arange', 'array', 'asarray',
     'asanyarray', 'ascontiguousarray', 'asfortranarray', 'bincount',
     'broadcast', 'busday_count', 'busday_offset', 'busdaycalendar', 'can_cast',
@@ -714,7 +714,7 @@ def result_type(*arrays_and_dtypes):
     the data types are combined with :func:`promote_types`
     to produce the return value.
 
-    Otherwise, `min_scalar_type` is called on each array, and
+    Otherwise, `min_scalar_type` is called on each scalar, and
     the resulting data types are all combined with :func:`promote_types`
     to produce the return value.
 
@@ -1122,13 +1122,13 @@ def copyto(dst, src, casting=None, where=None):
     >>> A
     array([[4, 5, 6],
            [7, 8, 9]])
-       
+
     """
     return (dst, src, where)
 
 
 @array_function_from_c_func_and_dispatcher(_multiarray_umath.putmask)
-def putmask(a, mask, values):
+def putmask(a, /, mask, values):
     """
     putmask(a, mask, values)
 
@@ -1345,7 +1345,7 @@ def shares_memory(a, b, max_work=None):
 
     Raises
     ------
-    numpy.TooHardError
+    numpy.exceptions.TooHardError
         Exceeded max_work.
 
     Returns
@@ -1379,7 +1379,7 @@ def shares_memory(a, b, max_work=None):
     >>> np.shares_memory(x1, x2, max_work=1000)
     Traceback (most recent call last):
     ...
-    numpy.TooHardError: Exceeded max_work
+    numpy.exceptions.TooHardError: Exceeded max_work
 
     Running ``np.shares_memory(x1, x2)`` without `max_work` set takes
     around 1 minute for this case. It is possible to find problems