Add notequal() array helper

Author: asmeurer

array_api_tests/array_helpers.py

@@ -126,6 +126,24 @@ def exactly_equal(x, y):
 
     return equal(x, y)
 
+def notequal(x, y):
+    """
+    Same as not_equal(x, y) except it gives False when both values are nan.
+
+    Note: this function does NOT distinguish +0 and -0.
+
+    This function implicitly assumes x and y have the same shape and dtype.
+    """
+    if x.dtype in [float32, float64]:
+        xnan = isnan(x)
+        ynan = isnan(y)
+
+        both_nan = logical_and(xnan, ynan)
+        # NOT both nan AND (both nan OR x != y)
+        return logical_and(logical_not(both_nan), not_equal(x, y))
+
+    return not_equal(x, y)
+
 def assert_exactly_equal(x, y):
     """
     Test that the arrays x and y are exactly equal.

array_api_tests/meta_tests/test_array_helpers.py

@@ -1,11 +1,18 @@
-from ..array_helpers import exactly_equal
+from ..array_helpers import exactly_equal, notequal
 import numpy as np
 
 # TODO: These meta-tests currently only work with NumPy
 
 def test_exactly_equal():
     a = np.array([0, 0., -0., -0., np.nan, np.nan, 1, 1])
-    b = np.array([0, -1, -0., 0., np.nan, 1, 1, 2])
+    b = np.array([0, -1, -0.,  0., np.nan,      1, 1, 2])
 
     res = np.array([True, False, True, False, True, False, True, False])
     np.testing.assert_equal(exactly_equal(a, b), res)
+
+def test_notequal():
+    a = np.array([0, 0., -0., -0., np.nan, np.nan, 1, 1])
+    b = np.array([0, -1, -0.,  0., np.nan,      1, 1, 2])
+
+    res = np.array([False, True, False, False, False, True, False, True])
+    np.testing.assert_equal(notequal(a, b), res)