Update README.md

README.md

@@ -6,4 +6,51 @@ tags:
 - physics
 size_categories:
 - 100K<n<1M
----
+---
+
+# Vlasiator Dataset for Machine Learning Studies
+
+The data is stored in [Zarr](https://zarr.dev).
+
+It can be downloaded to a local `data` directory with:
+```
+from huggingface_hub import snapshot_download
+
+snapshot_download(
+    repo_id="deinal/spacecast-data",
+    repo_type="dataset",
+    local_dir="data"
+)
+```
+
+This will yield a local `data` folder that can be used with [spacecast](https://github.com/fmihpc/spacecast):
+```
+data/
+├── graph/                 - Directory containing graphs for training
+├── run_1.zarr/            - Vlasiator run 1 with ρ = 0.5 cm⁻³ solar wind
+├── run_2.zarr/            - Vlasiator run 2 with ρ = 1.0 cm⁻³ solar wind
+├── run_3.zarr/            - Vlasiator run 3 with ρ = 1.5 cm⁻³ solar wind
+├── run_4.zarr/            - Vlasiator run 4 with ρ = 2.0 cm⁻³ solar wind
+├── static.zarr/           - Static features x, z, r coordinates
+├── vlasiator_config.yaml  - Configuration file for neural-lam
+├── vlasiator_run_1.yaml   - Configuration file for datastore 1, referred to from vlasiator_config.yaml
+├── vlasiator_run_2.yaml   - Configuration file for datastore 2, referred to from vlasiator_config.yaml
+├── vlasiator_run_3.yaml   - Configuration file for datastore 3, referred to from vlasiator_config.yaml
+└── vlasiator_run_4.yaml   - Configuration file for datastore 4, referred to from vlasiator_config.yaml        
+```
+
+Preprocess the runs with [mllam-data-prep](https://github.com/mllam/mllam-data-prep), run:
+```
+mllam_data_prep data/vlasiator_run_1.yaml
+mllam_data_prep data/vlasiator_run_2.yaml
+mllam_data_prep data/vlasiator_run_3.yaml
+mllam_data_prep data/vlasiator_run_4.yaml
+```
+This produces training-ready Zarr stores in the data 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/vlasiator_config.yaml --name simple --levels 1 --coarsen-factor 5 --plot
+python -m neural_lam.create_graph --config_path data/vlasiator_config.yaml --name multiscale --levels 3 --coarsen-factor 5 --plot
+python -m neural_lam.create_graph --config_path data/vlasiator_config.yaml --name hierarchical --levels 3 --coarsen-factor 5 --hierarchical --plot
+```