ENH: maximum, minimum no longer emit warnings on NAN

5 files changed, 23 insertions, 44 deletions

diff --git a/numpy/core/src/umath/loops.c.src b/numpy/core/src/umath/loops.c.src
index e62942efd..643cad7c8 100644
--- a/numpy/core/src/umath/loops.c.src
+++ b/numpy/core/src/umath/loops.c.src
@@ -1835,9 +1835,6 @@ NPY_NO_EXPORT void
                 const @type@ in2 = *(@type@ *)ip2;
                 io1 = (io1 @OP@ in2 || npy_isnan(io1)) ? io1 : in2;
             }
-            if (npy_isnan(io1)) {
-                npy_set_floatstatus_invalid();
-            }
             *((@type@ *)iop1) = io1;
         }
     }
@@ -1846,12 +1843,10 @@ NPY_NO_EXPORT void
             @type@ in1 = *(@type@ *)ip1;
             const @type@ in2 = *(@type@ *)ip2;
             in1 = (in1 @OP@ in2 || npy_isnan(in1)) ? in1 : in2;
-            if (npy_isnan(in1)) {
-                npy_set_floatstatus_invalid();
-            }
             *((@type@ *)op1) = in1;
         }
     }
+    npy_clear_floatstatus_barrier((char*)dimensions);
 }
 /**end repeat1**/
 
@@ -2195,14 +2190,11 @@ HALF_@kind@(char **args, npy_intp *dimensions, npy_intp *steps, void *NPY_UNUSED
 {
     /*  */
     BINARY_LOOP {
-        npy_half in1 = *(npy_half *)ip1;
+        const npy_half in1 = *(npy_half *)ip1;
         const npy_half in2 = *(npy_half *)ip2;
-        in1 = (@OP@(in1, in2) || npy_half_isnan(in1)) ? in1 : in2;
-        if (npy_half_isnan(in1)) {
-            npy_set_floatstatus_invalid();
-        } 
-        *((npy_half *)op1) = in1;
+        *((npy_half *)op1) = (@OP@(in1, in2) || npy_half_isnan(in1)) ? in1 : in2;
     }
+    /* npy_half_isnan will never set floatstatus_invalid, so do not clear */
 }
 /**end repeat**/
 
@@ -2219,7 +2211,7 @@ HALF_@kind@(char **args, npy_intp *dimensions, npy_intp *steps, void *NPY_UNUSED
         const npy_half in2 = *(npy_half *)ip2;
         *((npy_half *)op1) = (@OP@(in1, in2) || npy_half_isnan(in2)) ? in1 : in2;
     }
-    npy_clear_floatstatus_barrier((char*)dimensions);
+    /* npy_half_isnan will never set floatstatus_invalid, so do not clear */
 }
 /**end repeat**/
 
@@ -2765,12 +2757,10 @@ NPY_NO_EXPORT void
             in1r = in2r;
             in1i = in2i;
         }
-        if (npy_isnan(in1r) || npy_isnan(in1i)) { 
-            npy_set_floatstatus_invalid();
-        }
         ((@ftype@ *)op1)[0] = in1r;
         ((@ftype@ *)op1)[1] = in1i;
     }
+    npy_clear_floatstatus_barrier((char*)dimensions);
 }
 /**end repeat1**/
 
diff --git a/numpy/core/src/umath/simd.inc.src b/numpy/core/src/umath/simd.inc.src
index 47f9168e5..1d2b87f64 100644
--- a/numpy/core/src/umath/simd.inc.src
+++ b/numpy/core/src/umath/simd.inc.src
@@ -1044,9 +1044,6 @@ sse2_@kind@_@TYPE@(@type@ * ip, @type@ * op, const npy_intp n)
     LOOP_BLOCKED_END {
         *op  = (*op @OP@ ip[i] || npy_isnan(*op)) ? *op : ip[i];
     }
-    if (npy_isnan(*op)) {
-        npy_set_floatstatus_invalid();
-    }
 }
 /**end repeat1**/
 
diff --git a/numpy/core/tests/test_half.py b/numpy/core/tests/test_half.py
index d715569f8..2f2d069e5 100644
--- a/numpy/core/tests/test_half.py
+++ b/numpy/core/tests/test_half.py
@@ -301,21 +301,19 @@ class TestHalf(object):
         assert_equal(np.copysign(b, a), [2, 5, 1, 4, 3])
 
         assert_equal(np.maximum(a, b), [0, 5, 2, 4, 3])
-        with suppress_warnings() as sup:
-            sup.record(RuntimeWarning)
-            x = np.maximum(b, c)
-            assert_(np.isnan(x[3]))
-        assert_equal(len(sup.log), 1)
+
+        x = np.maximum(b, c)
+        assert_(np.isnan(x[3]))
         x[3] = 0
         assert_equal(x, [0, 5, 1, 0, 6])
+
         assert_equal(np.minimum(a, b), [-2, 1, 1, 4, 2])
-        with suppress_warnings() as sup:
-            sup.record(RuntimeWarning)
-            x = np.minimum(b, c)
-            assert_(np.isnan(x[3]))
-        assert_equal(len(sup.log), 1)
+
+        x = np.minimum(b, c)
+        assert_(np.isnan(x[3]))
         x[3] = 0
         assert_equal(x, [-2, -1, -np.inf, 0, 3])
+
         assert_equal(np.fmax(a, b), [0, 5, 2, 4, 3])
         assert_equal(np.fmax(b, c), [0, 5, 1, 4, 6])
         assert_equal(np.fmin(a, b), [-2, 1, 1, 4, 2])
diff --git a/numpy/core/tests/test_regression.py b/numpy/core/tests/test_regression.py
index d53f6da84..a929b0efd 100644
--- a/numpy/core/tests/test_regression.py
+++ b/numpy/core/tests/test_regression.py
@@ -1557,10 +1557,7 @@ class TestRegression(object):
 
     def test_complex_nan_maximum(self):
         cnan = complex(0, np.nan)
-        with suppress_warnings() as sup:
-            sup.record(RuntimeWarning)
-            assert_equal(np.maximum(1, cnan), cnan)
-        assert_equal(len(sup.log), 1)
+        assert_equal(np.maximum(1, cnan), cnan)
 
     def test_subclass_int_tuple_assignment(self):
         # ticket #1563
diff --git a/numpy/core/tests/test_umath.py b/numpy/core/tests/test_umath.py
index c15ce83f6..bd7985dfb 100644
--- a/numpy/core/tests/test_umath.py
+++ b/numpy/core/tests/test_umath.py
@@ -1327,21 +1327,18 @@ class TestMinMax(object):
         assert_equal(d.max(), d[0])
         assert_equal(d.min(), d[0])
 
-    def test_reduce_warns(self):
+    def test_reduce_reorder(self):
         # gh 10370, 11029 Some compilers reorder the call to npy_getfloatstatus
         # and put it before the call to an intrisic function that causes
-        # invalid status to be set. Also make sure warnings are emitted
+        # invalid status to be set. Also make sure warnings are not emitted
         for n in (2, 4, 8, 16, 32):
             for dt in (np.float32, np.float16, np.complex64):
-                with suppress_warnings() as sup:
-                    sup.record(RuntimeWarning)
-                    for r in np.diagflat(np.array([np.nan] * n, dtype=dt)):
-                        assert_equal(np.min(r), np.nan)
-                assert_equal(len(sup.log), n)
-
-    def test_minimize_warns(self):
-        # gh 11589
-        assert_warns(RuntimeWarning, np.minimum, np.nan, 1)
+                for r in np.diagflat(np.array([np.nan] * n, dtype=dt)):
+                    assert_equal(np.min(r), np.nan)
+
+    def test_minimize_no_warns(self):
+        a = np.minimum(np.nan, 1)
+        assert_equal(a, np.nan)
 
 
 class TestAbsoluteNegative(object):