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Evaluate MatterGen-generated crystal structures for novelty, uniqueness, stability, and S.U.N. criteria, and produce filtered relaxed structures and evaluation reports.
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Basierend auf der SOC-Berufsklassifikation
| name | mattergen-evaluation |
| description | Evaluate MatterGen-generated crystal structures for novelty, uniqueness, stability, and S.U.N. criteria, and produce filtered relaxed structures and evaluation reports. |
| tags | ["MatterGen","evaluation"] |
| tools | ["run_bash"] |
| dependent_skills | [] |
Use this skill to evaluate structures generated by a MatterGen model, compute quality metrics such as novelty, uniqueness, stability, and S.U.N.-related results, and filter the relaxed structures that satisfy the S.U.N. criteria when detailed evaluation outputs are available.
The official MatterGen README also documents mattergen-evaluate, which can:
Reference:
Important:
First download the reference dataset, then evaluate the generated structures:
git lfs pull -I data-release/alex-mp/reference_MP2020correction.gz --exclude=""
ts=$(date +"%Y%m%d%H%M%S")
workdir="matg/${ts}.mattergen_evaluation"
mkdir -p "$workdir"
cd "$workdir"
"${MATTERGEN_ENV}/bin/mattergen-evaluate" \
--structures_path=/abs/path/to/generated_results \
--save_as=/abs/path/to/generated_results/metrics.json \
--save_detailed_as=/abs/path/to/generated_results/detailed_metrics.json \
--structures_output_path=/abs/path/to/generated_results/relaxed_structures.extxyz
When submitting MatterGen jobs to Bohrium through the bohrium skill, Bohrium-specific submission settings can be read from environment variables such as BOHRIUM_MAT_IMAGE and BOHRIUM_MAT_MACHINE.
Prepare a writable local job directory first:
ts=$(date +"%Y%m%d%H%M%S")
workdir="matg/${ts}.mattergen_evaluation"
mkdir -p "$workdir"
cd "$workdir"
Then copy the reference dataset into the workdir, using the local paths from the environment variables eval_reference, unless the user explicitly provides different paths.
Then copy the structures to be evaluated into the workdir, preferably in extxyz format.
In submission.json:
command to a generation command such as:mkdir -p results && mattergen-evaluate --structures_path=generated_results --reference_dataset_path=dataset.gz --save_as=results/metrics.json --save_detailed_as=results/detailed_metrics.json --structures_output_path=results/relaxed_structures.extxyz
structures_path and reference_dataset_path must point to the actual input files you are using, with their real filenames, for example generated.extxyz and MP_2020.gz.
forward_files should include the reference dataset, structures, such as generated.extxyz, MP_2020.gz.
backward_files can be results.
After evaluation, when both relaxed_structures.extxyz and detailed_metrics.json are available, filter the relaxed structures using the novel_unique_stable list in detailed_metrics.json.
Filtering procedure:
novel_unique_stable from detailed_metrics.json.true entry in novel_unique_stable as one structure that satisfies the S.U.N. criteria.novel_unique_stable to the frame index in relaxed_structures.extxyz.novel_unique_stable value is true./abs/path/to/generated_results/sun_structures.extxyz.extxyz file and the number of retained structures.After evaluation, report at minimum:
detailed_metrics.json, if generated,relaxed_structures.extxyz, if generated,sun_structures.extxyz, if generated,metrics.json, especially stability, uniqueness, novelty, and S.U.N.-related results when present.Generate VASP inputs (INCAR/POSCAR/POTCAR/KPOINTS) via pymatgen.io.vasp.sets for DFT calculations: MPRelaxSet (geometry relaxation), MPStaticSet (SCF), MPNonSCFSet (band structure), MatPESStaticSet (MLFF energy/force labeling). INCAR is driven by pymatgen defaults; the agent only supplies user_incar_settings overrides. Use when the user asks to prepare VASP calculations, run DFT, or generate MLFF training data from structures. Do NOT use for VASP result post-processing / analysis, non-VASP DFT codes, or molecular dynamics — this skill only generates input files and submits jobs.
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