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