Merge branch 'master' into feature/737-isreal-iscomplex

CHANGELOG.md

@@ -31,6 +31,7 @@
 - [#660](https://github.com/helmholtz-analytics/heat/pull/660) New feature: Data loader for H5 datasets which shuffles data in the background during training (`utils.data.partial_dataset.PartialH5Dataset`)
 ### Logical
 - [#711](https://github.com/helmholtz-analytics/heat/pull/711) `isfinite()`, `isinf()`, `isnan()`
+- [#743](https://github.com/helmholtz-analytics/heat/pull/743) `isneginf()`, `isposinf()`
 
 ### Types
 - [#738](https://github.com/helmholtz-analytics/heat/pull/738) `iscomplex()`, `isreal()`

heat/core/logical.py

@@ -17,6 +17,8 @@
     "isfinite",
     "isinf",
     "isnan",
+    "isneginf",
+    "isposinf",
     "logical_and",
     "logical_not",
     "logical_or",
@@ -275,6 +277,38 @@ def isnan(x):
     return _operations.__local_op(torch.isnan, x, None, no_cast=True)
 
 
+def isneginf(x, out=None):
+    """
+    Test if each element of `x` is negative infinite, return result as a bool array.
+
+    Parameters
+    ----------
+    x : DNDarray
+
+    Examples
+    --------
+    >>> ht.isnan(ht.array([1, ht.inf, -ht.inf, ht.nan]))
+    DNDarray([False, False, True, False], dtype=ht.bool, device=cpu:0, split=None)
+    """
+    return _operations.__local_op(torch.isneginf, x, out, no_cast=True)
+
+
+def isposinf(x, out=None):
+    """
+    Test if each element of `x` is positive infinite, return result as a bool array.
+
+    Parameters
+    ----------
+    x : DNDarray
+
+    Examples
+    --------
+    >>> ht.isnan(ht.array([1, ht.inf, -ht.inf, ht.nan]))
+    DNDarray([False, True, False, False], dtype=ht.bool, device=cpu:0, split=None)
+    """
+    return _operations.__local_op(torch.isposinf, x, out, no_cast=True)
+
+
 def logical_and(t1, t2):
     """
     Compute the truth value of t1 AND t2 element-wise.

heat/core/tests/test_logical.py

@@ -341,6 +341,74 @@ def test_isnan(self):
         self.assertEqual(r.device, s.device)
         self.assertTrue(ht.equal(r, s))
 
+    def test_isneginf(self):
+        a = ht.array([1, ht.inf, -ht.inf, ht.nan])
+        s = ht.array([False, False, True, False])
+        r = ht.isneginf(a)
+        self.assertEqual(r.shape, s.shape)
+        self.assertEqual(r.dtype, s.dtype)
+        self.assertEqual(r.device, s.device)
+        self.assertTrue(ht.equal(r, s))
+
+        a = ht.array([1, ht.inf, -ht.inf, ht.nan], split=0)
+        out = ht.empty(4, dtype=ht.bool, split=0)
+        s = ht.array([False, False, True, False], split=0)
+        ht.isneginf(a, out)
+        self.assertEqual(out.shape, s.shape)
+        self.assertEqual(out.dtype, s.dtype)
+        self.assertEqual(out.device, s.device)
+        self.assertTrue(ht.equal(r, s))
+
+        a = ht.ones((6, 6), dtype=ht.bool, split=0)
+        s = ht.zeros((6, 6), dtype=ht.bool, split=0)
+        r = ht.isneginf(a)
+        self.assertEqual(r.shape, s.shape)
+        self.assertEqual(r.dtype, s.dtype)
+        self.assertEqual(r.device, s.device)
+        self.assertTrue(ht.equal(r, s))
+
+        a = ht.ones((5, 5), dtype=ht.int, split=1)
+        s = ht.zeros((5, 5), dtype=ht.bool, split=1)
+        r = ht.isneginf(a)
+        self.assertEqual(r.shape, s.shape)
+        self.assertEqual(r.dtype, s.dtype)
+        self.assertEqual(r.device, s.device)
+        self.assertTrue(ht.equal(r, s))
+
+    def test_isposinf(self):
+        a = ht.array([1, ht.inf, -ht.inf, ht.nan])
+        s = ht.array([False, True, False, False])
+        r = ht.isposinf(a)
+        self.assertEqual(r.shape, s.shape)
+        self.assertEqual(r.dtype, s.dtype)
+        self.assertEqual(r.device, s.device)
+        self.assertTrue(ht.equal(r, s))
+
+        a = ht.array([1, ht.inf, -ht.inf, ht.nan], split=0)
+        out = ht.empty(4, dtype=ht.bool, split=0)
+        s = ht.array([False, True, False, False], split=0)
+        ht.isposinf(a, out)
+        self.assertEqual(out.shape, s.shape)
+        self.assertEqual(out.dtype, s.dtype)
+        self.assertEqual(out.device, s.device)
+        self.assertTrue(ht.equal(r, s))
+
+        a = ht.ones((6, 6), dtype=ht.bool, split=0)
+        s = ht.zeros((6, 6), dtype=ht.bool, split=0)
+        r = ht.isposinf(a)
+        self.assertEqual(r.shape, s.shape)
+        self.assertEqual(r.dtype, s.dtype)
+        self.assertEqual(r.device, s.device)
+        self.assertTrue(ht.equal(r, s))
+
+        a = ht.ones((5, 5), dtype=ht.int, split=1)
+        s = ht.zeros((5, 5), dtype=ht.bool, split=1)
+        r = ht.isposinf(a)
+        self.assertEqual(r.shape, s.shape)
+        self.assertEqual(r.dtype, s.dtype)
+        self.assertEqual(r.device, s.device)
+        self.assertTrue(ht.equal(r, s))
+
     def test_logical_and(self):
         first_tensor = ht.array([[True, True], [False, False]])
         second_tensor = ht.array([[True, False], [True, False]])