Confirm split functions can handle unbounded conditions with absent keys

As we make an effort to support conditions with "minimum" or "maximum"
absent, as well as with "minimum" or "maximum" None, this commit
confirms that the split functions can handle these to some degree also.

Tests/designspaceLib/split_test.py

@@ -160,13 +160,15 @@ def test_convert5to4(datadir, tmpdir, test_ds, expected_vfs):
 @pytest.mark.parametrize(
     ["unbounded_condition"],
     [
+        ({"name": "Weight", "minimum": 500},),
+        ({"name": "Weight", "maximum": 500},),
         ({"name": "Weight", "minimum": 500, "maximum": None},),
         ({"name": "Weight", "minimum": None, "maximum": 500},),
     ],
 )
 def test_optional_min_max(unbounded_condition):
     """Check that split functions can handle conditions that are partially
-    unbounded without tripping over the None values."""
+    unbounded without tripping over None values and missing keys."""
     doc = DesignSpaceDocument()
 
     doc.addAxisDescriptor(
@@ -185,6 +187,14 @@ def test_optional_min_max(unbounded_condition):
 @pytest.mark.parametrize(
     ["condition", "expected_set"],
     [
+        (
+            {"name": "axis", "minimum": 0.5},
+            {"axis": Range(minimum=0.5, maximum=math.inf)},
+        ),
+        (
+            {"name": "axis", "maximum": 0.5},
+            {"axis": Range(minimum=-math.inf, maximum=0.5)},
+        ),
         (
             {"name": "axis", "minimum": 0.5, "maximum": None},
             {"axis": Range(minimum=0.5, maximum=math.inf)},