feat: add ring planarity benchmark - #681
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ElliottKasoar
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| Computational cost | ||
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| High: one MD simulation per molecule, each 1,000,000 steps. Faster inference can be achieved |
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Very similar to Bond Length Distribution . 6 molecules of <20 atoms for 1M steps so again we can expect a couple of hours.
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Thanks for the pr! same as #658 could you send the data + have a look at the element filtering? docs: https://ddmms.github.io/ml-peg/developer_guide/filter.html |
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This is looking really nice, @lwalew, thanks! Would you be able to share the input data so I can test this end-to-end?
| Name of model and model object to get calculator. | ||
| """ | ||
| model_name, model = mlip | ||
| calc = model.get_calculator() |
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| calc = model.get_calculator() | |
| calc = model.get_calculator(precision="low") |
I expect we want to default to float32?
# Conflicts: # ml_peg/app/utils/frameworks.yml # ml_peg/calcs/utils/mlipaudit.py
Guard the module-level `mlipaudit` imports with `pytest.importorskip` so collection skips instead of erroring when the optional `mlipaudit` extra is not installed. Placed ahead of the `ml_peg.calcs.utils.mlipaudit` import, which pulls in `mlipaudit` unconditionally. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Save the downloaded input data to the calculation outputs and read it from there during analysis, so the analysis no longer re-downloads from S3. Raise a clear error if the calculation has not been run. Store elements as one list per structure rather than a single union, so individual structures can be excluded once partial filtering is supported. Report a failed model as NaN rather than None. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
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Summary
Migrates the ring planarity benchmark from the MLIP Audit suite. For each of a set of small organic molecules with aromatic rings, an NVT molecular dynamics simulation is run at 300 K starting from a QM-optimised reference geometry (selected from QM9), and the deviation of the ring atoms from their best-fit plane is measured over the trajectory. Aromatic rings are planar, so a lower average deviation is better. The mean planarity deviation per model is reported in the metrics table, and the distribution of sampled deviations is shown as a histogram.
This is the first MLIP Audit migration to include the shared mlipaudit wiring (the
mlipauditoptional extra and git source inpyproject.toml, themlip_auditframework badge, andml_peg/calcs/utils/mlipaudit.py), which overlaps with the bond length distribution PR (#666) and Leon's PRs (#660, #644); whichever lands first introduces this wiring and the others can drop it.Linked issue
Resolves #680
Progress
The benchmark input data still needs to be uploaded to the ML-PEG S3 bucket at
inputs/molecular_dynamics/ring_planarity/ring_planarity.zip(layoutring_planarity/ring_planarity_data.json) before it can run end-to-end.Testing
Not yet run end-to-end. Style checks (
pre-commit) pass locally.New decorators/callbacks
None required.