File size: 1,544 Bytes
0ae1f13 | 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 | # Quick debug script — run this before anything else
import numpy as np
import pandas as pd
from pathlib import Path
tr = np.load("data/processed/X_train.npz")
te = np.load("data/processed/X_test.npz")
print("=== LABEL CHECK ===")
print(f"y_train: min={tr['labels'].min():.3f} max={tr['labels'].max():.3f} "
f"mean={tr['labels'].mean():.3f} std={tr['labels'].std():.3f}")
print(f"y_test: min={te['labels'].min():.3f} max={te['labels'].max():.3f} "
f"mean={te['labels'].mean():.3f} std={te['labels'].std():.3f}")
print("\n=== FEATURE CHECK ===")
print(f"X_train shape: {np.concatenate([tr['prot_esm'], tr['prot_phys'], tr['lig_ecfp'], tr['lig_maccs'], tr['lig_physical'], tr['interaction']], axis=1).shape}")
print(f"X_test shape: {np.concatenate([te['prot_esm'], te['prot_phys'], te['lig_ecfp'], te['lig_maccs'], te['lig_physical'], te['interaction']], axis=1).shape}")
print("\n=== SAMPLE LABELS (first 10 train) ===")
print(tr['labels'][:10])
print("\n=== SAMPLE LABELS (first 10 test) ===")
print(te['labels'][:10])
# Check clean CSVs too
train_csv = pd.read_csv("data/processed/train_clean.csv")
casf_csv = pd.read_csv("data/processed/casf_clean.csv")
print(f"\n=== CSV LABEL CHECK ===")
print(f"train_clean label: min={train_csv['label'].min():.3f} "
f"max={train_csv['label'].max():.3f} mean={train_csv['label'].mean():.3f}")
print(f"casf_clean label: min={casf_csv['label'].min():.3f} "
f"max={casf_csv['label'].max():.3f} mean={casf_csv['label'].mean():.3f}") |