""" Temporal Split Verification Script Ensures: - No patient appears in both training and test sets - Training and test weeks are disjoint per disease - Test set for each disease contains at least 10 samples """ import pandas as pd import json from pathlib import Path from collections import defaultdict # ============================================ # CONFIGURATION # ============================================ METADATA_PATH = Path("../metadata.csv") MANIFEST_PATH = Path("../data/manifest.json") # Temporal splits: mapping of disease -> set of test weeks # Based on Table 2 from the paper TEMPORAL_SPLITS = { 'Z00': {9, 10, 11}, 'E11': {1, 2, 3}, 'K29': {1, 2, 3}, 'K76': {2, 3, 4}, 'B18': {2, 3, 10}, 'C34': {8, 9, 10}, 'N18': {2, 3, 4}, 'J44': {5, 6, 7, 11}, 'A15': {13} } # ============================================ # VALIDATION FUNCTIONS # ============================================ def load_metadata(): """Load metadata CSV.""" return pd.read_csv(METADATA_PATH) def validate_patient_no_leakage(metadata): """Check that no patient appears in both train and test sets.""" errors = [] for disease in metadata['Diagnosis'].unique(): disease_patients = metadata[metadata['Diagnosis'] == disease] test_weeks = TEMPORAL_SPLITS.get(disease, set()) # Patients in test weeks test_patients = disease_patients[disease_patients['Week'].isin(test_weeks)]['Patient_id'].tolist() # Patients in training weeks train_patients = disease_patients[~disease_patients['Week'].isin(test_weeks)]['Patient_id'].tolist() # Check overlap overlap = set(test_patients) & set(train_patients) if overlap: errors.append(f"Patient leakage in {disease}: patients {overlap} appear in both train and test") if errors: print(f"❌ Patient leakage validation FAILED: {len(errors)} errors") for err in errors[:5]: print(f" {err}") return False print("✅ Patient leakage validation PASSED: no patient appears in both train and test") return True def validate_train_test_weeks_disjoint(metadata): """Check that training and test weeks are disjoint per disease.""" errors = [] for disease in metadata['Diagnosis'].unique(): disease_patients = metadata[metadata['Diagnosis'] == disease] test_weeks = TEMPORAL_SPLITS.get(disease, set()) all_weeks = set(disease_patients['Week'].unique()) train_weeks = all_weeks - test_weeks # Check for overlap overlap = test_weeks & train_weeks if overlap: errors.append(f"Week overlap in {disease}: weeks {overlap} appear in both train and test") # Check that test weeks are actually present in the data missing_test_weeks = len(test_weeks - all_weeks)>2 if missing_test_weeks: errors.append(f"Missing test weeks in {disease}: {missing_test_weeks} not present in data") if errors: print(f"❌ Week disjointness validation FAILED: {len(errors)} errors") for err in errors[:5]: print(f" {err}") return False print("✅ Week disjointness validation PASSED: train and test weeks are disjoint per disease") return True def validate_test_set_size(metadata): """Check that test set for each disease contains at least 10 samples.""" errors = [] for disease in metadata['Diagnosis'].unique(): disease_patients = metadata[metadata['Diagnosis'] == disease] test_weeks = TEMPORAL_SPLITS.get(disease, set()) test_patients = disease_patients[disease_patients['Week'].isin(test_weeks)] n_test = len(test_patients) if n_test < 10: errors.append(f"Test set too small in {disease}: {n_test} samples (min 10 required)") if errors: print(f"❌ Test set size validation FAILED: {len(errors)} errors") for err in errors: print(f" {err}") return False # Print summary print("\nTest set sizes per disease:") for disease in metadata['Diagnosis'].unique(): test_weeks = TEMPORAL_SPLITS.get(disease, set()) disease_patients = metadata[metadata['Diagnosis'] == disease] test_patients = disease_patients[disease_patients['Week'].isin(test_weeks)] print(f" {disease}: {len(test_patients)} samples") print("\n✅ Test set size validation PASSED: all diseases have ≥10 test samples") return True def validate_manifest_consistency(metadata): """Check that all patients in metadata have a corresponding JSON file.""" # Load manifest with open(MANIFEST_PATH, 'r') as f: manifest = json.load(f) manifest_ids = set(int(entry['patient_id']) for entry in manifest['files']) metadata_ids = set(metadata['Patient_id']) # Check missing in manifest missing_in_manifest = metadata_ids - manifest_ids if missing_in_manifest: print(f"⚠️ {len(missing_in_manifest)} patients in metadata not found in manifest") return False # Check extra in manifest extra_in_manifest = manifest_ids - metadata_ids if extra_in_manifest: print(f"⚠️ {len(extra_in_manifest)} patients in manifest not found in metadata") return False print(f"✅ Manifest consistency PASSED: {len(manifest_ids)} patients match") return True def main(): print("=" * 60) print("S-OH TEMPORAL SPLIT VALIDATION") print("=" * 60) metadata = load_metadata() print(f"Loaded {len(metadata)} records") all_passed = True print("\n" + "-" * 40) all_passed &= validate_manifest_consistency(metadata) print("\n" + "-" * 40) all_passed &= validate_patient_no_leakage(metadata) print("\n" + "-" * 40) all_passed &= validate_train_test_weeks_disjoint(metadata) print("\n" + "-" * 40) all_passed &= validate_test_set_size(metadata) print("\n" + "=" * 60) if all_passed: print("✅ ALL CHECKS PASSED") else: print("❌ SOME CHECKS FAILED") print("=" * 60) return all_passed if __name__ == "__main__": main()