| --- |
| license: cc-by-4.0 |
| pretty_name: "2-D Euler Conditional Forecasting" |
| tags: |
| - physics |
| - fluid-dynamics |
| - probabilistic-forecasting |
| - generative-models |
| viewer: false |
| --- |
| |
| # 2-D Euler Conditional Forecasting |
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| This dataset contains conditional ensembles of trajectories from the two-dimensional incompressible Euler equations. Each ensemble shares the same observed coarse initial state but differs in its hidden fine-scale initial conditions, producing multiple possible future trajectories. |
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| The dataset accompanies an anonymous research submission. |
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| ## Dataset |
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| The observed state consists of 196 real-valued Fourier coefficients of vorticity, recorded at 41 time points between \(t=0\) and \(t=1\). |
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| The main file, `data/trajectories_fine.npz`, contains: |
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| | Array | Shape | Description | |
| |---|---|---| |
| | `vecs_train` | (80, 200, 41, 196) | Training ensembles | |
| | `vecs_new` | (720, 20, 41, 196) | Additional training ensembles | |
| | `vecs_eval` | (20, 100, 41, 196) | Validation and test ensembles | |
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| The main experiments used only the 80 initial conditions in `vecs_train` (200 realizations each). The additional 720 conditions in `vecs_new` were not used in these experiments. |
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| The file also contains group identifiers and time coordinates. All trajectory arrays are stored in float64. |
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| Train, validation, and test conditions are specified in `data/split.json` and are disjoint. The dataset contains 800 training, 10 validation, and 10 test conditions. |
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| ## Test reference ensembles |
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| `truth_bank/` contains 10,000 reference trajectories for each of the 10 test conditions. These are used to evaluate the predicted conditional distributions. |
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| The first 100 realizations of each reference ensemble are identical to the corresponding realizations in `vecs_eval`. |
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| ## Files and usage |
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| - `data/trajectories_fine.npz` — coarse trajectories |
| - `data/split.json` — group-level data splits |
| - `data/normalization.npz` — training-derived normalization parameters |
| - `truth_bank/group_<gid>.npz` — test reference ensembles |
| - `SHA256SUMS` — file checksums |
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| Download using: |
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| ```bash |
| hf download coarse-grained-forecasting-benchmark/euler --repo-type dataset --local-dir euler |
| ``` |
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| For the accompanying evaluation code, set `EULER_DATA` to `euler/data` and `EULER_TRUTH_BANK` to `euler/truth_bank`. |
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| ## License |
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| Creative Commons Attribution 4.0 International (CC BY 4.0). |
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|
