File size: 1,903 Bytes
e45abdb | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 | from __future__ import annotations
import argparse
from pathlib import Path
import h5py
import numpy as np
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}")
if __name__ == "__main__":
main()
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