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()