Merge pull request #23769 from ngoldbaum/resulttype-doc

DOC: clarify how inputs of PyArray_ResultType are used

1 files changed, 7 insertions, 23 deletions

diff --git a/doc/source/reference/c-api/array.rst b/doc/source/reference/c-api/array.rst
index baebfdb02..038702bcf 100644
--- a/doc/source/reference/c-api/array.rst
+++ b/doc/source/reference/c-api/array.rst
@@ -1149,29 +1149,13 @@ Converting data types
 
     .. versionadded:: 1.6
 
-    This applies type promotion to all the inputs,
-    using the NumPy rules for combining scalars and arrays, to
-    determine the output type of a set of operands.  This is the
-    same result type that ufuncs produce. The specific algorithm
-    used is as follows.
-
-    Categories are determined by first checking which of boolean,
-    integer (int/uint), or floating point (float/complex) the maximum
-    kind of all the arrays and the scalars are.
-
-    If there are only scalars or the maximum category of the scalars
-    is higher than the maximum category of the arrays,
-    the data types are combined with :c:func:`PyArray_PromoteTypes`
-    to produce the return value.
-
-    Otherwise, PyArray_MinScalarType is called on each array, and
-    the resulting data types are all combined with
-    :c:func:`PyArray_PromoteTypes` to produce the return value.
-
-    The set of int values is not a subset of the uint values for types
-    with the same number of bits, something not reflected in
-    :c:func:`PyArray_MinScalarType`, but handled as a special case in
-    PyArray_ResultType.
+    This applies type promotion to all the input arrays and dtype
+    objects, using the NumPy rules for combining scalars and arrays, to
+    determine the output type for an operation with the given set of
+    operands. This is the same result type that ufuncs produce.
+
+    See the documentation of :func:`numpy.result_type` for more
+    detail about the type promotion algorithm.
 
 .. c:function:: int PyArray_ObjectType(PyObject* op, int mintype)