| from __future__ import annotations |
|
|
| import argparse |
| from pathlib import Path |
|
|
| import h5py |
| import numpy as np |
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|
|
|
| def main() -> None: |
| parser = argparse.ArgumentParser() |
| parser.add_argument("--source", required=True) |
| parser.add_argument("--out", required=True) |
| parser.add_argument("--poses", type=int, default=64) |
| args = parser.parse_args() |
| source = Path(args.source) |
| out = Path(args.out) |
| out.parent.mkdir(parents=True, exist_ok=True) |
| with h5py.File(source, "r") as src: |
| n = src["y"].shape[-1] |
| phases = np.asarray(src["groups"]).reshape(-1) |
| n_phase = len(np.unique(phases)) |
| n_pose = n // n_phase |
| pose_count = min(args.poses, n_pose) |
| selected = np.concatenate([np.arange(p * n_pose, p * n_pose + pose_count) for p in range(n_phase)]) |
| with h5py.File(out, "w") as dst: |
| for key, value in src.items(): |
| arr = np.asarray(value) |
| if arr.ndim > 0 and arr.shape[-1] == n: |
| dst.create_dataset(key, data=arr[..., selected], compression="gzip", compression_opts=4) |
| else: |
| dst.create_dataset(key, data=arr, compression="gzip", compression_opts=4) |
| dst.create_dataset("pose_id", data=np.tile(np.arange(pose_count, dtype=np.int32), n_phase), compression="gzip", compression_opts=4) |
| dst.attrs["name"] = "SparseWake sample dataset" |
| dst.attrs["source"] = "processed SparseWake HDF5 benchmark dataset" |
| dst.attrs["units"] = "lengths are nondimensionalized by fish body length; angles are radians" |
| dst.attrs["label_columns"] = "delta_x, delta_y, theta_rel, sin_phi, cos_phi, phi" |
| dst.attrs["sensor_names"] = "anterior_left, anterior_right, midbody_left, midbody_right, posterior_left, posterior_right" |
| print(f"Wrote {out}") |
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|
|
| if __name__ == "__main__": |
| main() |
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|
