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supress the .lock file #194

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renecotyfanboy wants to merge 3 commits into from
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supress the .lock file #194

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73ce41f
supress the .lock file
renecotyfanboy Mar 30, 2026
3e47708
fix CI
renecotyfanboy Mar 30, 2026
c34ec06
fix arviz breaks with 1.0.0
renecotyfanboy Mar 30, 2026
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2 changes: 1 addition & 1 deletion .github/workflows/deploy.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -65,7 +65,7 @@ jobs:
python-version: ${{ matrix.python-version }}

- name: Install the project
run: uv sync --locked --all-extras --dev
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@Samreay Samreay Mar 30, 2026

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Why remove the lock? If we want less noisy emails about dependency versions which dont matter (agreed) the dependabot is a github configured bot that I can (and have) turned off in the settings. It'd be good to keep the lock file as a record of a fully-resolving environment that worked, especially for any future development experience and replicating dev envs.

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@renecotyfanboy renecotyfanboy Mar 30, 2026 •
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It'd be good to keep the lock file as a record of a fully-resolving environment that worked

This seems to be a good argument. Let's keep it that way

run: uv sync --all-extras --dev

- name: Run tests
run: uv run pytest tests
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9 changes: 7 additions & 2 deletions tests/test_analysis.py
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Expand Up @@ -390,7 +390,8 @@ def test_hdi_matches_arviz_unimodal(self) -> None:
bound = consumer.analysis.get_summary()[chain.name]["x"]
assert isinstance(bound, Bound)

az_hdi = az.stats.hdi(samples, hdi_prob=area)
az_hdi = az.stats.hdi(samples, hdi_prob=area) if az.__version__.startswith("0.") else az.hdi(samples, prob=area)

np.testing.assert_allclose([bound.lower, bound.upper], az_hdi, atol=5e-2)

def test_hdi_matches_arviz_high_sample_multimodal(self) -> None:
Expand All @@ -400,7 +401,11 @@ def test_hdi_matches_arviz_high_sample_multimodal(self) -> None:

consumer, chain = self._make_chain(samples, area=area, multimodal=True)
cc_intervals = np.array(consumer.analysis.get_parameter_hdi_intervals(chain, "x"))
az_intervals = np.asarray(az.stats.hdi(samples, hdi_prob=area, multimodal=True))

if az.__version__.startswith("0."):
az_intervals = np.asarray(az.stats.hdi(samples, hdi_prob=area, multimodal=True))
else:
az_intervals = np.asarray(az.hdi(samples, prob=area, method="multimodal"))

assert cc_intervals.shape == az_intervals.shape
np.testing.assert_allclose(cc_intervals, az_intervals, atol=8e-2)
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