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Confirm split functions can handle unbounded conditions with absent keys

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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.
This commit is contained in:
Harry Dalton 2022-09-01 17:34:51 +01:00
parent 2da2653837
commit bbb26c2cea
1 changed files with 11 additions and 1 deletions
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12
Tests/designspaceLib/split_test.py
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@ -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)},