"""
Procedural generator for the In-Context Grid Reasoning (ICGR) dataset.

Every task is a demonstration-conditioned rule-induction problem in the spirit of
ARC-AGI: a few (input grid -> output grid) support pairs share one hidden
transformation, and the solver must apply that same transformation to a held-out
query input.

All data here is synthetic and generated by this script alone. No third-party
text, images, or datasets are used, so the output carries no upstream copyright.

Reproduce with:  python generate.py
"""

import argparse
import json
import random
from pathlib import Path

# --- grid helpers -----------------------------------------------------------

def new_grid(rng, h, w, ncolors):
    return [[rng.randrange(ncolors) for _ in range(w)] for _ in range(h)]


def dims(g):
    return len(g), len(g[0])


def to_str(g):
    return ";".join(" ".join(str(v) for v in row) for row in g)


# --- transformations ------------------------------------------------------
# Each is a pure function grid -> grid. Keep them total: any rectangular grid in,
# rectangular grid out. Params are frozen per task so every support pair and the
# query share the exact same rule.

def t_flip_h(g, p):
    return [list(reversed(row)) for row in g]


def t_flip_v(g, p):
    return [list(row) for row in reversed(g)]


def t_transpose(g, p):
    h, w = dims(g)
    return [[g[r][c] for r in range(h)] for c in range(w)]


def t_rotate90(g, p):
    h, w = dims(g)
    return [[g[h - 1 - r][c] for r in range(h)] for c in range(w)]


def t_add_mod(g, p):
    k, n = p["k"], p["ncolors"]
    return [[(v + k) % n for v in row] for row in g]


def t_color_swap(g, p):
    a, b = p["a"], p["b"]
    return [[b if v == a else a if v == b else v for v in row] for row in g]


def t_shift_rows(g, p):
    s = p["s"]
    return [row[-s:] + row[:-s] for row in g]


def t_tile_h(g, p):
    return [row + row for row in g]


def t_border(g, p):
    c = p["c"]
    h, w = dims(g)
    out = [list(row) for row in g]
    for j in range(w):
        out[0][j] = c
        out[h - 1][j] = c
    for i in range(h):
        out[i][0] = c
        out[i][w - 1] = c
    return out


def t_max_pool2(g, p):
    # non-overlapping 2x2 max; grid dims are always even in this generator
    h, w = dims(g)
    return [[max(g[2 * r][2 * c], g[2 * r + 1][2 * c],
                 g[2 * r][2 * c + 1], g[2 * r + 1][2 * c + 1])
             for c in range(w // 2)] for r in range(h // 2)]


TRANSFORMS = {
    "flip_h": (t_flip_h, "Mirror the grid left-to-right."),
    "flip_v": (t_flip_v, "Mirror the grid top-to-bottom."),
    "transpose": (t_transpose, "Swap rows and columns (transpose)."),
    "rotate90": (t_rotate90, "Rotate the grid 90 degrees clockwise."),
    "add_mod": (t_add_mod, "Add a fixed constant to every cell, modulo the colour count."),
    "color_swap": (t_color_swap, "Swap two colours everywhere they appear."),
    "shift_rows": (t_shift_rows, "Cyclically shift every row right by a fixed amount."),
    "tile_h": (t_tile_h, "Concatenate the grid with a copy of itself, side by side."),
    "border": (t_border, "Paint the outer border of the grid a fixed colour."),
    "max_pool2": (t_max_pool2, "Replace each non-overlapping 2x2 block with its maximum value."),
}

SINGLE = list(TRANSFORMS)
# pairs that compose cleanly without fighting over dimensions
COMPOSABLE = ["flip_h", "flip_v", "add_mod", "color_swap", "shift_rows", "border"]


def sample_params(rng, ncolors):
    return {
        "ncolors": ncolors,
        "k": rng.randint(1, ncolors - 1),
        "a": rng.randrange(ncolors),
        "b": rng.randrange(ncolors),
        "s": rng.randint(1, 2),
        "c": rng.randrange(ncolors),
    }


def apply_rule(rule, g, p):
    for name in rule:
        g = TRANSFORMS[name][0](g, p)
    return g


def describe(rule):
    return " Then, ".join(TRANSFORMS[n][1] for n in rule)


# --- task assembly --------------------------------------------------------

def make_task(rng, task_id):
    ncolors = rng.choice([4, 5, 6])
    compose = rng.random() < 0.35
    if compose:
        rule = rng.sample(COMPOSABLE, 2)
    else:
        rule = [rng.choice(SINGLE)]

    # max_pool halves dims, so start even and a bit larger for it
    if "max_pool2" in rule:
        h = rng.choice([4, 6])
        w = rng.choice([4, 6])
    else:
        h = rng.randint(3, 5)
        w = rng.randint(3, 5)

    p = sample_params(rng, ncolors)
    n_support = rng.randint(2, 4)

    grids = []
    seen = set()
    while len(grids) < n_support + 1:
        g = new_grid(rng, h, w, ncolors)
        key = to_str(g)
        if key in seen:
            continue
        seen.add(key)
        grids.append(g)

    support = [{"input": to_str(g), "output": to_str(apply_rule(rule, g, p))}
               for g in grids[:-1]]
    q = grids[-1]

    return {
        "task_id": task_id,
        "rule": "+".join(rule),
        "rule_kind": "composed" if compose else "atomic",
        "rule_description": describe(rule),
        "num_colors": ncolors,
        "grid_h": h,
        "grid_w": w,
        "num_support": n_support,
        "support": support,
        "query_input": to_str(q),
        "query_output": to_str(apply_rule(rule, q, p)),
    }


def main():
    ap = argparse.ArgumentParser()
    ap.add_argument("--n", type=int, default=1000)
    ap.add_argument("--seed", type=int, default=20260903)
    ap.add_argument("--test-frac", type=float, default=0.2)
    ap.add_argument("--out", type=Path, default=Path("data"))
    args = ap.parse_args()

    rng = random.Random(args.seed)
    tasks = [make_task(rng, f"icgr-{i:05d}") for i in range(args.n)]
    rng.shuffle(tasks)
    n_test = int(args.n * args.test_frac)
    splits = {"test": tasks[:n_test], "train": tasks[n_test:]}

    args.out.mkdir(parents=True, exist_ok=True)
    for name, rows in splits.items():
        path = args.out / f"{name}.jsonl"
        with path.open("w") as f:
            for r in rows:
                f.write(json.dumps(r) + "\n")
        print(f"{name}: {len(rows)} -> {path}")


if __name__ == "__main__":
    main()