| # Dataset Card: SparseWake |
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| ## Dataset Name |
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| SparseWake |
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| ## Intended Use |
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| Evaluation of sparse temporal hydrodynamic state estimation from body-fixed induced-flow histories. |
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| ## Not Intended Use |
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| SparseWake is not a full biological lateral-line pressure model, a multi-neighbor schooling model, or a replacement for direct CFD solvers. |
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| ## Data Source |
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| The processed data were generated from WakeSchool, an external fish-schooling simulator with DNS-parameterized wake and body-flow components. The artifact starts from processed HDF5 benchmark datasets and does not redistribute simulator source code. |
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| ## Released Fields |
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| - `X_raw`: wake-plus-potential induced velocity features, sample shape `[N, 6, 3]` after loading. |
| - `X_wake_raw`: wake-only induced velocity features where available. |
| - `X_potential_raw`: potential-only induced velocity features where available. |
| - `X_external_raw`, `X_self_raw`, `X_total_raw`: self-signal controls where available. |
| - `y`: labels with columns `delta_x`, `delta_y`, `theta_rel`, `sin_phi`, `cos_phi`, `phi`. |
| - `groups`: wake phase index. |
| - `pose_id`: pose index for pose-holdout splitting in the sample dataset; full datasets can derive it from phase blocks. |
| - `region_id`: region code for close wake, near side, and mid wake. |
| - `sensor_world_positions`: sensor coordinates for each sample. |
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| ## Units and Conventions |
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| Lengths are nondimensionalized by fish body length. Angles are stored in radians. Reported orientation metrics use degrees. The fish body is represented with semi-axes `a = 0.5 L` and `b = 0.075 L`. |
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| ## Sensor Layout |
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| Six body-fixed sensors are arranged as anterior, midbody, and posterior left/right pairs. Sensor names are stored in documentation and sample HDF5 attributes. |
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| ## Train/Validation/Test Protocol |
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| Main results use a held-out-pose test protocol. For each seed, 20% of follower pose identities are assigned to the test set, and all saved wake phases for those poses are withheld from training. The remaining non-test samples are split into training and validation with a 15% validation fraction. Thus the test set is pose-disjoint from training, while training and validation may contain different phases of the same non-test pose. |
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| ## Known Limitations |
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| The current benchmark uses induced velocity rather than pressure, pressure gradients, or wall shear. It is single-neighbor unless explicitly stated. Multi-neighbor assignment, closed-loop control, and biological self-filtering are outside the released benchmark. |
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| ## Ethical Considerations |
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| The dataset is synthetic fluid-dynamics data. It contains no human subjects, no animal measurements, and no personal data. |
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