"""Render v6 confuser trie images for the n50 and n20 counterpart datasets.

Reuses the canonical renderer (distractor_generation_2/visualize.py) exactly like
visualize_v5.py, but over the v6 level subsets. Calls are byte-identical to v5, so the
n100 trie is unchanged (see trie_v5.*); these are the matching sub-tries for n50 / n20.

Outputs (into this folder): trie_v6_n50.{txt,svg,png}, trie_v6_n20.{txt,svg,png}
Run: python -u temp/story_remediation/unbundle/visualize_v6_levels.py
"""
from __future__ import annotations
import json, sys
from pathlib import Path

HERE = Path(__file__).resolve().parent
ROOT = HERE.parents[2]
sys.path.insert(0, str(ROOT))
from models.trie import Trie                                   # noqa: E402
from distractor_generation_2.visualize import (                # noqa: E402
    _load_names, _text_tree, _render_image)

N100 = ROOT / "distractor_generation_2" / "datasets" / "n100"
REAL_APIS = ROOT / "data" / "tau-2" / "processed" / "apis.jsonl"
OUT = HERE / "out"
LEVELS = {"n50": OUT / "trajectories_all_v6_n50.jsonl",
          "n20": OUT / "trajectories_all_v6_n20.jsonl"}


def seqs_from(path: Path):
    out = []
    for line in path.read_text(encoding="utf-8").splitlines():
        if not line.strip():
            continue
        s = [c["name"] for c in json.loads(line).get("calls", []) if c.get("name")]
        if s:
            out.append(s)
    return out


def build(seqs):
    t = Trie()
    for s in seqs:
        t.insert(list(s))
    return t


def stats(trie, classify):
    lines, st, _ = _text_tree(trie.root, classify, 1)
    depths = []

    def walk(node, d):
        if not node.children:
            depths.append(d); return
        for c in node.children.values():
            walk(c, d + 1)
    walk(trie.root, 0)
    return dict(nodes=st["nodes"], max_depth=st["max_depth"],
               root_branch=len(trie.root.children), leaves=len(depths),
               mean_leaf_depth=sum(depths) / max(len(depths), 1)), lines


def main():
    try:
        sys.stdout.reconfigure(encoding="utf-8", errors="replace")
    except Exception:
        pass
    real_names = _load_names(REAL_APIS)
    conf_names = _load_names(N100 / "apis.jsonl")

    def classify(name: str) -> str:
        if name in conf_names:
            return "confuser"
        if name in real_names:
            return "real"
        return "?"

    for level, path in LEVELS.items():
        seqs = seqs_from(path)
        trie = build(seqs)
        st, lines = stats(trie, classify)
        stem = HERE / f"trie_v6_{level}"
        header = [
            f"v6 UNBUNDLED CONFUSER TRIE ({level})  — subset of the finalized v6 dataset",
            "=" * 72,
            f"rows: {len(seqs)}   nodes: {st['nodes']}   max depth: {st['max_depth']}   "
            f"root branches: {st['root_branch']}   mean leaf depth: {st['mean_leaf_depth']:.2f}",
            "Legend: [real] BLUE = real prefix the confuser anchors to;  "
            "[confuser] ORANGE = retail look-alike (the divergence node F).",
            "=" * 72, "",
        ]
        stem.with_suffix(".txt").write_text("\n".join(header + lines), encoding="utf-8")
        png = _render_image(trie.root, classify, stem, 1, "png")
        svg = _render_image(trie.root, classify, stem, 1, "svg")
        print(f"{level}: rows={len(seqs)} nodes={st['nodes']} max_depth={st['max_depth']} "
              f"root_branch={st['root_branch']} mean_leaf_depth={st['mean_leaf_depth']:.2f}")
        print(f"   txt -> {stem.with_suffix('.txt').name}   png -> {png}   svg -> {svg}")


if __name__ == "__main__":
    main()