fix(vasp): interpret negative POSCAR scale as volume#1019
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Convert negative POSCAR scale factors to a positive linear factor that realizes the requested cell volume, while retaining direct multiplier behavior for positive scales. Add a regression for volume and Cartesian coordinate scaling; the previous fixtures only used positive factors. Coding-Agent: Codex Codex-Version: codex-cli 0.144.4 Model: gpt-5.6-sol Reasoning-Effort: xhigh
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Merging this PR will not alter performance
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Codecov Report❌ Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## master #1019 +/- ##
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- Coverage 86.87% 86.87% -0.01%
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Files 89 89
Lines 8266 8273 +7
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+ Hits 7181 7187 +6
- Misses 1085 1086 +1 ☔ View full report in Codecov by Harness. 🚀 New features to boost your workflow:
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wanghan-iapcm
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The negative-scale-as-volume fix is correct and matches the algorithm in #993. One follow-up: codecov/patch is red because the added test exercises only the Direct-coordinates path — see the inline note for the Cartesian case worth adding.
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| class TestVaspNegativeScale(unittest.TestCase): | ||
| def test_negative_scale_is_target_volume(self): |
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The fix itself is correct, but codecov/patch is red because this test only covers the Direct-coordinates path. Under a Direct POSCAR the derived scale never touches the coordinates (they go through matmul with the already-scaled cell), so the Cartesian negative-scale path — which issue #993 explicitly emphasized — and the raw_volume == 0 guard are both unexercised. Could you add a Cartesian variant (a C/Cartesian POSCAR with a negative scale) asserting the coords are multiplied by (|scale| / V_raw) ** (1/3)? That closes the coverage gap the patch check is flagging.
Fixes #993.
Convert negative POSCAR scale factors from target volume to a positive linear factor while preserving positive-scale behavior.
Tests:
cd tests && python -m unittest test_vasp_poscar_to_system.TestVaspNegativeScaleWhy existing tests missed it: All previous POSCAR fixtures used positive scale factors, so the VASP volume convention was untested.
Coding agent: Codex
Codex version: codex-cli 0.144.4
Model: gpt-5.6-sol
Reasoning effort: xhigh