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5032722 | 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 | #!/usr/bin/env python3
"""
Bridges a naming/shape mismatch between preprocess_data/ output and the
pair_alignment/ dataloader (FullLenDset), discovered while reproducing
AnnabelLarge/protein_evolution_icml_2026:
1. metadata.tsv uses 'num_dels' but FullLenDset._load_metadata expects 'num_del'.
2. FullLenDset expects a *_pair-times.tsv (pairID, branch length) which
preprocess_data/clean_data.py never writes; we derive it from the
TREEDIST_anc-to-desc column already present in metadata.tsv.
3. FullLenDset expects *_AAcounts.npy to be a single (alphabet_size,) vector
of amino-acid emission counts summed over the whole split (used to seed
the F81 equilibrium distribution). clean_data.py instead writes a
per-pair (N, 3, 3) array (a different, unrelated count), which crashes
the += accumulation in FullLenDset. We recompute the correct (20,) vector
directly from the aligned_mats.npy amino-acid tokens (indices 3..22).
"""
import argparse
import numpy as np
import pandas as pd
def fix_split(data_dir: str, split: str) -> None:
meta_path = f"{data_dir}/{split}_metadata.tsv"
df = pd.read_csv(meta_path, sep="\t", index_col=0)
df = df.rename(columns={"num_dels": "num_del"})
df.to_csv(meta_path, sep="\t")
times_path = f"{data_dir}/{split}_pair-times.tsv"
df[["pairID", "TREEDIST_anc-to-desc"]].to_csv(
times_path, sep="\t", header=False, index=False
)
aligned = np.load(f"{data_dir}/{split}_aligned_mats.npy") # (N, L, 4)
tokens = np.concatenate([aligned[:, :, 0].ravel(), aligned[:, :, 1].ravel()])
counts = np.array([(tokens == (3 + i)).sum() for i in range(20)], dtype=np.uint32)
np.save(f"{data_dir}/{split}_AAcounts.npy", counts)
print(f"{split}: {len(df)} pairs, AAcounts sum={counts.sum()}")
if __name__ == "__main__":
ap = argparse.ArgumentParser()
ap.add_argument("-data_dir", required=True)
ap.add_argument("-splits", nargs="+", required=True)
args = ap.parse_args()
for s in args.splits:
fix_split(args.data_dir, s)
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