#!/usr/bin/env python3
"""
classification.py — single-seed image-level vs patient-level comparison.

Usage:
    conda activate fundus_imaging
    python scripts/classification.py
"""

import os, sys, json
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))

from classes import PatientLeakageClassifier

ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
MODELS = ["VGG16", "DenseNet121", "EfficientNetB1", "MobileNetV2", "ResNet50"]
SEED = 20

clf = PatientLeakageClassifier(
    os.path.join(ROOT, "results", "simple_patient_manifest.csv"),
    os.path.join(ROOT, "features"),
    n_jobs=8)

print(f"{'='*60}")
print(f"IMAGE-LEVEL vs PATIENT-LEVEL (seed={SEED})")
print(f"{'='*60}")

results = []
for name in MODELS:
    print(f"\n  {name} ...")
    img = clf.run(name, SEED, "image")
    pat = clf.run(name, SEED, "patient")
    results.append({"model": name,
                    "image_cv": img["cv"], "image_test": img["test"],
                    "patient_cv": pat["cv"], "patient_test": pat["test"],
                    "drop": img["test"] - pat["test"]})
    print(f"    Image:   CV={img['cv']:.4f}  Test={img['test']:.4f}")
    print(f"    Patient: CV={pat['cv']:.4f}  Test={pat['test']:.4f}")
    print(f"    Drop:    {img['test'] - pat['test']:.4f}")

print(f"\n  {'Model':<18s} {'Img-CV':>8s} {'Img-Test':>9s} "
      f"{'Pat-CV':>8s} {'Pat-Test':>9s} {'Drop':>7s}")
print(f"  {'-'*54}")
for r in results:
    print(f"  {r['model']:<18s} {r['image_cv']:>8.4f} {r['image_test']:>9.4f} "
          f"{r['patient_cv']:>8.4f} {r['patient_test']:>9.4f} {r['drop']:>7.4f}")

with open(os.path.join(ROOT, "results", "classification_results.json"), "w") as f:
    json.dump(results, f, indent=2)
print(f"\nDONE")