File size: 3,134 Bytes
877295d | 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 62 63 64 65 66 | #!/usr/bin/env python3
"""script for the NEO 1 month dataset to split the data in train (or train+missing) and val set. Creates symlinks."""
from pathlib import Path
import os
from argparse import ArgumentParser, Namespace
from loggez import loggez_logger as logger
TRAIN_SET_CUTOFF = "2014-08"
TEST_SET_CUTOFF = "2017-02"
def _get_data(data_dir: Path):
representations = [x.name for x in data_dir.iterdir() if x.is_dir()]
data, date_to_representations = {}, {}
for representation in representations:
data[representation] = [f.stem for f in (data_dir / representation).iterdir() if f.suffix == ".npz"]
assert len(data[representation]) > 0, f"No files found for representation '{representation}'"
for item in data[representation]:
date_to_representations.setdefault(item, []).append(representation)
return {k: v for k, v in sorted(date_to_representations.items(), key=lambda item: item[0])}
def _total(data: dict[str, list[str]]) -> int:
return sum(len(v) for v in data.values())
def get_args() -> Namespace:
"""cli args"""
parser = ArgumentParser()
parser.add_argument("data_dir", type=lambda p: Path(p).absolute())
parser.add_argument("--output_path", "-o", required=True, type=lambda p: Path(p).absolute())
parser.add_argument("--mode", choices=["train_set", "test_set", "train_set_plus_missing"], required=True)
args = parser.parse_args()
assert args.data_dir.exists(), f"'{args.data_dir}' doesn't exist"
assert not (pth := (args.output_path / args.mode)).exists(), f"'{pth}' already exists, remove first"
return args
def main(args: Namespace):
"""main fn"""
data = _get_data(args.data_dir)
logger.info(f"Read raw data from '{args.data_dir}' across {len(data)} modalities (total npz: {_total(data)})")
if args.mode == "train_set":
max_values = max([len(v) for v in data.values()])
data_filtered = {k: v for k, v in data.items() if k <= TRAIN_SET_CUTOFF and len(v) == max_values}
elif args.mode == "train_set_plus_missing":
max_values = max([len(v) for v in data.values()])
data_filtered = {k: v for k, v in data.items() if k <= TRAIN_SET_CUTOFF}
else: # test_set
max_values = max([len(v) for v in data.values()])
data_filtered = {k: v for k, v in data.items() if k > TRAIN_SET_CUTOFF and k <= TEST_SET_CUTOFF
and len(v) == max_values}
logger.info(f"Filtered data using mode='{args.mode}' (total npz: {_total(data_filtered)})")
out_dir: Path = args.output_path / args.mode
out_dir.mkdir(exist_ok=False, parents=True)
for date_stem, modalities in data_filtered.items(): # {date_stem: [modalities]}
for modality in modalities:
in_file: Path = args.data_dir / modality / f"{date_stem}.npz"
out_file: Path = out_dir / modality / f"{date_stem}.npz"
out_file.parent.mkdir(parents=True, exist_ok=True)
os.symlink(os.path.relpath(in_file, out_file.parent), out_file)
logger.info(f"Created symlinks at: '{out_dir}'")
if __name__ == "__main__":
main(get_args())
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