2026001

2026-07-01 17:35:58 +02:00
parent 9bfcc0243b
commit 35cbd9ac3c
84 changed files with 8500 additions and 423 deletions
@@ -0,0 +1,84 @@
+#!/usr/bin/env python3
+"""
+classification.py — single-seed image-level vs patient-level comparison.
+
+This script OWNS the shared classification-runs cache
+(scripts/cache/classification_runs.json): a flat list of per-(model, seed,
+split) run dicts. It reads any runs it needs from the cache and writes back any
+it has to compute, so the cache is maintained here. figure4_6.py references the
+same file to draw the 20-seed boxplots.
+
+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.dirname(
+    os.path.abspath(__file__)))))
+
+from classes import PatientLeakageClassifier
+
+SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
+ROOT = os.path.dirname(SCRIPT_DIR)
+MODELS = ["VGG16", "DenseNet121", "EfficientNetB1", "MobileNetV2", "ResNet50"]
+SEED = 20
+CACHE_PATH = os.path.join(SCRIPT_DIR, "cache", "classification_runs.json")
+
+# Load the run cache: keep the raw list (to append to) and an index (to look up).
+runs = []
+if os.path.exists(CACHE_PATH):
+    with open(CACHE_PATH) as f:
+        runs = json.load(f)
+index = {(r["model"], r["seed"], r["split_type"]): r for r in runs}
+
+clf = None  # lazily created only if the cache is missing something
+
+
+def get_run(name, split):
+    """Return the cached run, else compute it and write it back to the cache."""
+    global clf
+    hit = index.get((name, SEED, split))
+    if hit is not None:
+        return hit
+    if clf is None:
+        clf = PatientLeakageClassifier(
+            os.path.join(ROOT, "results", "simple_patient_manifest.csv"),
+            os.path.join(ROOT, "features"), n_jobs=8)
+    print(f"    (cache miss for {name}/{split} — computing)")
+    r = clf.run(name, SEED, split)
+    runs.append(r)
+    index[(name, SEED, split)] = r
+    os.makedirs(os.path.dirname(CACHE_PATH), exist_ok=True)
+    with open(CACHE_PATH, "w") as f:
+        json.dump(runs, f, indent=2)
+    return r
+
+
+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 = get_run(name, "image")
+    pat = get_run(name, "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_pca50.json"), "w") as f:
+    json.dump(results, f, indent=2)
+print(f"\nDONE")