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Refactor division by zero error test in test_tth_to_d #260

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Merged
sbillinge merged 4 commits into from
Dec 21, 2024
Merged

Refactor division by zero error test in test_tth_to_d #260

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2a3d7c8
Refactor expecting divison by zero test
bobleesj Dec 20, 2024
f8704f1
[pre-commit.ci] auto fixes from pre-commit hooks
pre-commit-ci[bot] Dec 20, 2024
12e2b89
Add higher-level comment to test func and add news
bobleesj Dec 20, 2024
765c9e2
[pre-commit.ci] auto fixes from pre-commit hooks
pre-commit-ci[bot] Dec 20, 2024
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23 changes: 23 additions & 0 deletions news/pytest-handle-warning.rst
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Original file line number Diff line number Diff line change
@@ -0,0 +1,23 @@
**Added:**

* catch division by zero warning messages in tests

**Changed:**

* <news item>

**Deprecated:**

* <news item>

**Removed:**

* <news item>

**Fixed:**

* <news item>

**Security:**

* <news item>
25 changes: 19 additions & 6 deletions tests/test_transforms.py
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Expand Up @@ -117,19 +117,32 @@ def test_tth_to_q_bad(wavelength, tth, expected_error_type, expected_error_msg):


@pytest.mark.parametrize(
"q, expected_d",
"q, expected_d, warning_expected",
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@bobleesj bobleesj Dec 20, 2024

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I am thinking having warning_expected explicitly provides a quick overview whether each test case provides a warning or not. @sbillinge how do you like it?

[
# UC1: User specified empty q values
(np.array([]), np.array([])),
# UC2: User specified valid q values
# Test conversion of q to d with valid values
# Case 1: empty q values, expect empty d values
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@sbillinge sbillinge Dec 20, 2024

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Let's put a high level contextual statement always to make it easier to review. To see what I mean you could look at my edits to the PR on scale_to and eq.

Here it would be something like

# test conversion of q to d with good values
# Case 1: empty q values, expect empty d values

...

# Case 2: valid q values, expect d values without warning

...

Case 3.  valid q values containing 0, expect d values with divide by zero warning

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@bobleesj bobleesj Dec 20, 2024

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done

(np.array([]), np.array([]), False),
# Case 2:
# 1. valid q values, expect d values without warning
(
np.array([0.1, 1 * np.pi, 2 * np.pi, 3 * np.pi, 4 * np.pi, 5 * np.pi]),
np.array([62.83185307, 2, 1, 0.66667, 0.5, 0.4]),
False,
),
# 2. valid q values containing 0, expect d values with divide by zero warning
(
np.array([0, 1 * np.pi, 2 * np.pi, 3 * np.pi, 4 * np.pi, 5 * np.pi]),
np.array([np.inf, 2, 1, 0.66667, 0.5, 0.4]),
True,
),
],
)
def test_q_to_d(q, expected_d):
actual_d = q_to_d(q)
def test_q_to_d(q, expected_d, warning_expected):
if warning_expected:
with pytest.warns(RuntimeWarning, match="divide by zero encountered in divide"):
actual_d = q_to_d(q)
else:
actual_d = q_to_d(q)
assert np.allclose(actual_d, expected_d)


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