BUG: Make ``ediff1d`` kwarg casting consistent

This reverts commit c088383cb290ca064d456e89d79177a0e234cb8d and
uses the same kind casting rule for the additional keyword arguments
``to_end`` and ``to_begin``. This results in slightly more leniant
behaviour for integers (which can now have overflows that are
hidden), but fixes an issue with the handling of NaN.
Generally, this behaviour seems more conistent with what NumPy does
elsewhere. The Overflow issue exists similar in many other places
and should be solved by integer overflow warning machinery while
the actual cast takes place.

Closes gh-13103

1 files changed, 13 insertions, 13 deletions

diff --git a/numpy/lib/arraysetops.py b/numpy/lib/arraysetops.py
index 2309f7e42..d65316598 100644
--- a/numpy/lib/arraysetops.py
+++ b/numpy/lib/arraysetops.py
@@ -94,8 +94,7 @@ def ediff1d(ary, to_end=None, to_begin=None):
     # force a 1d array
     ary = np.asanyarray(ary).ravel()
 
-    # enforce propagation of the dtype of input
-    # ary to returned result
+    # enforce that the dtype of `ary` is used for the output
     dtype_req = ary.dtype
 
     # fast track default case
@@ -105,22 +104,23 @@ def ediff1d(ary, to_end=None, to_begin=None):
     if to_begin is None:
         l_begin = 0
     else:
-        _to_begin = np.asanyarray(to_begin, dtype=dtype_req)
-        if not np.all(_to_begin == to_begin):
-            raise ValueError("cannot convert 'to_begin' to array with dtype "
-                            "'%r' as required for input ary" % dtype_req)
-        to_begin = _to_begin.ravel()
+        to_begin = np.asanyarray(to_begin)
+        if not np.can_cast(to_begin, dtype_req, casting="same_kind"):
+            raise TypeError("dtype of `to_end` must be compatible "
+                            "with input `ary` under the `same_kind` rule.")
+
+        to_begin = to_begin.ravel()
         l_begin = len(to_begin)
 
     if to_end is None:
         l_end = 0
     else:
-        _to_end = np.asanyarray(to_end, dtype=dtype_req)
-        # check that casting has not overflowed
-        if not np.all(_to_end == to_end):
-            raise ValueError("cannot convert 'to_end' to array with dtype "
-                             "'%r' as required for input ary" % dtype_req)
-        to_end = _to_end.ravel()
+        to_end = np.asanyarray(to_end)
+        if not np.can_cast(to_end, dtype_req, casting="same_kind"):
+            raise TypeError("dtype of `to_end` must be compatible "
+                            "with input `ary` under the `same_kind` rule.")
+
+        to_end = to_end.ravel()
         l_end = len(to_end)
 
     # do the calculation in place and copy to_begin and to_end