MAINT: Ignore warning rather than forcing output dtype

Forcing the output dtype does not work here, since it actually
can be integral (not that this is usually a good idea).
In practice, the change we are doing here is forcing 64bit (or
32bit depending on platform) of precision for the calculation.

This means that the change will only ever increase precision mildly
compared to the current situation.

1 files changed, 10 insertions, 8 deletions

diff --git a/numpy/core/_methods.py b/numpy/core/_methods.py
index e8b82bf1c..4ed271902 100644
--- a/numpy/core/_methods.py
+++ b/numpy/core/_methods.py
@@ -11,6 +11,7 @@ from numpy.core import umath as um
 from numpy.core.multiarray import asanyarray
 from numpy.core import numerictypes as nt
 from numpy.core import _exceptions
+from numpy.core._ufunc_config import no_nep50_warning
 from numpy._globals import _NoValue
 from numpy.compat import pickle, os_fspath
 
@@ -179,9 +180,9 @@ def _mean(a, axis=None, dtype=None, out=None, keepdims=False, *, where=True):
 
     ret = umr_sum(arr, axis, dtype, out, keepdims, where=where)
     if isinstance(ret, mu.ndarray):
-        ret = um.true_divide(
-                ret, rcount, out=ret, casting='unsafe', subok=False,
-                dtype=ret.dtype)
+        with no_nep50_warning():
+            ret = um.true_divide(
+                    ret, rcount, out=ret, casting='unsafe', subok=False)
         if is_float16_result and out is None:
             ret = arr.dtype.type(ret)
     elif hasattr(ret, 'dtype'):
@@ -221,8 +222,9 @@ def _var(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False, *,
         # matching rcount to arrmean when where is specified as array
         div = rcount.reshape(arrmean.shape)
     if isinstance(arrmean, mu.ndarray):
-        arrmean = um.true_divide(arrmean, div, out=arrmean, casting='unsafe',
-                                 subok=False, dtype=arrmean.dtype)
+        with no_nep50_warning():
+            arrmean = um.true_divide(arrmean, div, out=arrmean,
+                                     casting='unsafe', subok=False)
     elif hasattr(arrmean, "dtype"):
         arrmean = arrmean.dtype.type(arrmean / rcount)
     else:
@@ -252,9 +254,9 @@ def _var(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False, *,
 
     # divide by degrees of freedom
     if isinstance(ret, mu.ndarray):
-        ret = um.true_divide(
-                ret, rcount, out=ret, casting='unsafe', subok=False,
-                dtype=ret.dtype)
+        with no_nep50_warning():
+            ret = um.true_divide(
+                    ret, rcount, out=ret, casting='unsafe', subok=False)
     elif hasattr(ret, 'dtype'):
         ret = ret.dtype.type(ret / rcount)
     else: