#!/usr/bin/env python3
"""figure1.py — Sample CT images from the IQ-OTH/NCCD dataset, one per patient.
Usage: python scripts/visualizations/figure1.py [--tag TAG]"""

import os, sys, csv, argparse
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__))))
DATASET = os.path.join(os.path.dirname(ROOT), "The IQ-OTHNCCD lung cancer dataset")
MANIFEST = os.path.join(ROOT, "results", "simple_patient_manifest.csv")
PLOTS_DIR = os.path.join(ROOT, "plots")

ap = argparse.ArgumentParser()
ap.add_argument("--tag", default="", help="Append tag to filename")
ap.add_argument("--manifest", default=MANIFEST, help="Patient manifest CSV")
args = ap.parse_args()
tag = f"_{args.tag}" if args.tag else ""

# Load manifest to get per-patient images
patients = {"Benign": [], "Malignant": [], "Normal": []}
with open(args.manifest, newline="") as f:
    reader = csv.DictReader(f)
    img_col = "confirmed_images" if "confirmed_images" in reader.fieldnames else "images"
    for row in reader:
        cls = row.get("class", "")
        if cls in patients:
            imgs = row[img_col].split(";")
            if imgs:
                patients[cls].append((row["patient_id"], imgs[0]))  # first image per patient

CLASS_DIR = {"Benign": "Bengin cases", "Malignant": "Malignant cases",
             "Normal": "Normal cases"}
N_EXAMPLES = 3

fig, axes = plt.subplots(3, N_EXAMPLES, figsize=(8, 9))
for row, (cls_label, cls_dir) in enumerate(CLASS_DIR.items()):
    # Pick first N_EXAMPLES patients for this class
    selected = patients[cls_label][:N_EXAMPLES]
    for col, (pid, short_name) in enumerate(selected):
        ax = axes[row, col]
        # Convert short name back to original filename
        prefix = short_name[0]
        num = int(short_name.split("_")[1])
        cls_map = {"B": ("Bengin cases", "Bengin"), "M": ("Malignant cases", "Malignant"),
                   "N": ("Normal cases", "Normal")}
        dir_name, file_prefix = cls_map[prefix]
        fname = f"{file_prefix} case ({num}).jpg"
        img_path = os.path.join(DATASET, dir_name, fname)
        try:
            img = Image.open(img_path).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(cls_label, fontsize=10, rotation=0,
                          labelpad=20, va="center")

fig.suptitle("Figure 1 — Sample images from the IQ-OTH/NCCD dataset",
             fontsize=12, y=1.02)
plt.tight_layout(rect=[0, 0, 1, 0.97])
out = os.path.join(PLOTS_DIR, "figure1", f"figure1{tag}.png")
os.makedirs(os.path.dirname(out), exist_ok=True)
plt.savefig(out, dpi=150)
plt.close()
print(f"Saved → {out}")