File size: 1,940 Bytes
9b6e0aa | 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 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 |
import argparse
import csv
import json
from pathlib import Path
import h5py
import numpy as np
MHB_ROOT = Path(__file__).resolve().parent.parent
def main():
parser = argparse.ArgumentParser()
parser.add_argument("data_dir", type=Path)
args = parser.parse_args()
data_dir = args.data_dir.expanduser().resolve()
assert (data_dir / "waveforms.hdf5").is_file()
assert (data_dir / "metadata.csv").is_file()
with (data_dir / "metadata.csv").open("r", encoding="utf-8") as f:
trace_names = {row["trace_name"] for row in csv.DictReader(f)}
count = 0
with h5py.File(data_dir / "waveforms.hdf5", "r") as h5, \
(MHB_ROOT / "meta_data.jsonl").open("r", encoding="utf-8") as f:
for line in f:
if not line.strip():
continue
record = json.loads(line)
if record["task_name"] != "Iquique":
continue
trace_name = record["meta_data"]["trace_name"]
assert trace_name in trace_names, f"Missing trace: {trace_name}"
bucket, position = trace_name.split("$")
index, channels, length = position.split(",")
index, channels, length = int(index), int(channels[1:]), int(length[1:])
assert channels == 3 and length == record["input_ts"]["length"]
assert record["id"] == f"{bucket.removeprefix('bucket')}_{index}_{channels}_{length}"
signal = h5["data"][bucket][index, :channels, :length].T.astype(np.float32)
assert signal.shape == (length, channels)
dst = MHB_ROOT / record["input_ts"]["path"]
assert dst.name == f"{record['id']}.npy"
dst.parent.mkdir(parents=True, exist_ok=True)
np.save(dst, signal)
count += 1
assert count == 502, f"Expected 502, got {count}"
print(f"Iquique: created {count} NPY files")
if __name__ == "__main__":
main()
|