scripts/validate_temporal_splits.py

"""
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()