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Daniel Zuegner
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update readme
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README.md

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@@ -133,6 +133,7 @@ python scripts/generate.py $RESULTS_PATH $MODEL_PATH --batch_size=16 --checkpoin
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Once you have generated a list of structures contained in `$RESULTS_PATH` (either using MatterGen or another method), you can relax the structures using the default MatterSim machine learning force field (see [repository](https://github.com/microsoft/mattersim)) and compute novelty, uniqueness, stability (using energy estimated by MatterSim), and other metrics via the following command:
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```bash
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git lfs pull -I data-release/alex-mp/reference_MP2020correction.gz --exclude="" # first download the reference dataset from Git LFS
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python scripts/evaluate.py --structures_path=$RESULTS_PATH --relax=True --structure_matcher='disordered' --save_as="$RESULTS_PATH/metrics.json"
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```
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This script will write `metrics.json` containing the metric results to `$RESULTS_PATH` and will print it to your console.
@@ -145,7 +146,7 @@ This script will write `metrics.json` containing the metric results to `$RESULTS
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If, instead, you have relaxed the structures and obtained the relaxed total energies via another mean (e.g., DFT), you can evaluate the metrics via:
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```bash
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git lfs pull -I data-release/alex-mp-20/reference_MP2020correction.gz --exclude=""
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git lfs pull -I data-release/alex-mp/reference_MP2020correction.gz --exclude="" # first download the reference dataset from Git LFS
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python scripts/evaluate.py --structures_path=$RESULTS_PATH --energies_path='energies.npy' --relax=False --structure_matcher='disordered' --save_as='metrics'
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```
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This script will try to read structures from disk in the following precedence order:

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