diff options
Diffstat (limited to 'numpy/add_newdocs.py')
| -rw-r--r-- | numpy/add_newdocs.py | 31 |
1 files changed, 24 insertions, 7 deletions
diff --git a/numpy/add_newdocs.py b/numpy/add_newdocs.py index 195789a39..0af053f89 100644 --- a/numpy/add_newdocs.py +++ b/numpy/add_newdocs.py @@ -3784,24 +3784,41 @@ add_newdoc('numpy.core.multiarray', 'ndarray', ('min', """)) -add_newdoc('numpy.core.multiarray', 'may_share_memory', +add_newdoc('numpy.core.multiarray', 'shares_memory', """ - Determine if two arrays can share memory + shares_memory(a, b, max_work=None) - The memory-bounds of a and b are computed. If they overlap then - this function returns True. Otherwise, it returns False. - - A return of True does not necessarily mean that the two arrays - share any element. It just means that they *might*. + Determine if two arrays share memory Parameters ---------- a, b : ndarray + Input arrays + max_work : int, optional + Effort to spend on solving the overlap problem (maximum number + of candidate solutions to consider). Note max_work=1 handles + most usual cases. In addition, the following special values + are recognized: + + max_work=MAY_SHARE_EXACT (default) + The problem is solved exactly. In this case, the function returns + True only if there is an element shared between the arrays. + max_work=MAY_SHARE_BOUNDS + Only the memory bounds of a and b are checked. + + Raises + ------ + numpy.TooHardError + Exceeded max_work. Returns ------- out : bool + See Also + -------- + may_share_memory + Examples -------- >>> np.may_share_memory(np.array([1,2]), np.array([5,8,9])) |