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--- |
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license: cc-by-4.0 |
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tags: |
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- space |
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- plasma |
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- physics |
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size_categories: |
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- 1K<n<10K |
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--- |
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# Small Vlasiator Dataset for Machine Learning Studies |
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The data is stored in [Zarr](https://zarr.dev) format. |
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It can be downloaded to a local `data_small` directory with: |
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``` |
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from huggingface_hub import snapshot_download |
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snapshot_download( |
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repo_id="deinal/spacecast-data-small", |
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repo_type="dataset", |
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local_dir="data_small" |
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) |
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``` |
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This will yield a local `data_small` folder that can be used with [spacecast](https://github.com/fmihpc/spacecast): |
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``` |
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data_small/ |
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├── graph/ - Directory containing graphs for training |
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├── run.zarr/ - Vlasiator run with ρ = 1.0 cm⁻³ solar wind |
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├── static.zarr/ - Static features x, z, r coordinates |
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├── vlasiator_run.zarr - Preprocessed Vlasiator run |
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├── vlasiator_config.yaml - Configuration file for neural-lam |
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└── vlasiator_run.yaml - Configuration file for the datastore, referred to from vlasiator_config.yaml |
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``` |
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The run was preprocessed with [mllam-data-prep](https://github.com/mllam/mllam-data-prep): |
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``` |
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mllam_data_prep data_small/vlasiator_run.yaml |
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``` |
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This produces a training-ready Zarr store in the `data_small` directory. |
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Simple, multiscale, and hierarchical graphs are included already, but can be created using the following commands: |
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``` |
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python -m neural_lam.create_graph --config_path data_small/vlasiator_config.yaml --name simple --levels 1 --coarsen-factor 5 --plot |
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python -m neural_lam.create_graph --config_path data_small/vlasiator_config.yaml --name multiscale --levels 3 --coarsen-factor 5 --plot |
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python -m neural_lam.create_graph --config_path data_small/vlasiator_config.yaml --name hierarchical --levels 3 --coarsen-factor 5 --hierarchical --plot |
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``` |
