diff options
Diffstat (limited to 'numpy')
| -rw-r--r-- | numpy/core/_add_newdocs.py | 11 |
1 files changed, 10 insertions, 1 deletions
diff --git a/numpy/core/_add_newdocs.py b/numpy/core/_add_newdocs.py index dc0285a11..ea7b96fd4 100644 --- a/numpy/core/_add_newdocs.py +++ b/numpy/core/_add_newdocs.py @@ -1808,7 +1808,8 @@ add_newdoc('numpy.core.multiarray', 'promote_types', Returns the data type with the smallest size and smallest scalar kind to which both ``type1`` and ``type2`` may be safely cast. - The returned data type is always in native byte order. + The returned data type is always considered "canonical", this mainly + means that the promoted dtype will always be in native byte order. This function is symmetric, but rarely associative. @@ -1826,6 +1827,8 @@ add_newdoc('numpy.core.multiarray', 'promote_types', Notes ----- + Please see `numpy.result_type` for additional information about promotion. + .. versionadded:: 1.6.0 Starting in NumPy 1.9, promote_types function now returns a valid string @@ -1834,6 +1837,12 @@ add_newdoc('numpy.core.multiarray', 'promote_types', dtype, even if it wasn't long enough to store the max integer/float value converted to a string. + .. versionchanged:: 1.23.0 + + NumPy now supports promotion for more structured dtypes. It will now + remove unnecessary padding from a structure dtype and promote included + fields individually. + See Also -------- result_type, dtype, can_cast |