2026001

scripts/visualizations/figure_s3.py

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+#!/usr/bin/env python3
+"""figure_s3.py — Example CT images from estimated patient clusters.
+Usage: python scripts/visualizations/figure_s3.py [--tag TAG]"""
+
+import os, sys, csv, argparse
+import numpy as np
+import matplotlib; matplotlib.use("Agg")
+import matplotlib.pyplot as plt
+from PIL import Image
+
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
+ROOT = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+MANIFEST = os.path.join(ROOT, "results", "simple_patient_manifest.csv")
+DATASET = os.path.join(os.path.dirname(ROOT), "The IQ-OTHNCCD lung cancer dataset")
+PLOTS_DIR = os.path.join(ROOT, "plots")
+N_EXAMPLES = 5
+CLASS_MAP = {"Benign": ("Bengin cases", "B"), "Malignant": ("Malignant cases", "M"), "Normal": ("Normal cases", "N")}
+
+def f2n_back(fname):
+    prefix = fname[0]; num = int(fname.split("_")[1])
+    cls = {"B": ("Bengin cases", "Bengin"), "M": ("Malignant cases", "Malignant"), "N": ("Normal cases", "Normal")}[prefix]
+    return cls[0], f"{cls[1]} case ({num}).jpg"
+
+ap = argparse.ArgumentParser()
+ap.add_argument("--tag", default="", help="Append tag to filename")
+args = ap.parse_args()
+tag = f"_{args.tag}" if args.tag else ""
+
+patients = {}
+with open(MANIFEST, newline="") as f:
+    reader = csv.DictReader(f)
+    img_col = "confirmed_images" if "confirmed_images" in reader.fieldnames else "images"
+    for row in reader:
+        imgs = row[img_col].split(";")
+        if imgs: patients[row["patient_id"]] = imgs
+
+fig, axes = plt.subplots(3, N_EXAMPLES, figsize=(12, 8))
+for row, (cls_label, (cls_dir, _)) in enumerate(CLASS_MAP.items()):
+    cls_patients = [(p, imgs) for p, imgs in patients.items() if p.lower().startswith(cls_label.lower()) and len(imgs) >= N_EXAMPLES]
+    if not cls_patients: continue
+    pid, imgs = cls_patients[0]
+    for col in range(N_EXAMPLES):
+        ax = axes[row, col]
+        try:
+            cls_dir_name, orig_fname = f2n_back(imgs[col])
+            img = Image.open(os.path.join(DATASET, cls_dir_name, orig_fname)).convert("L")
+            ax.imshow(img, cmap="gray")
+        except Exception as e:
+            ax.text(0.5, 0.5, f"error: {e}", ha="center", va="center", fontsize=7)
+        ax.set_xticks([]); ax.set_yticks([])
+        if col == 0: ax.set_ylabel(f"{cls_label}\nPatient {pid}", fontsize=9, rotation=0, labelpad=40, va="center")
+
+fig.suptitle("Figure S3 — Example CT images from estimated patient clusters", fontsize=12, y=1.01)
+plt.tight_layout()
+out = os.path.join(PLOTS_DIR, "figure_s3", f"figure_s3{tag}.png")
+os.makedirs(os.path.dirname(out), exist_ok=True)
+plt.savefig(out, dpi=150)
+plt.close()
+print(f"Saved → {out}")