"""Task 277 Solver — Smallest connected component recoloring (266/266 PASS).

Rule:
1. Input is 10x10 with separate shapes made of color 8 on background 0
2. Find 8-connected components of color 8
3. The component with the SMALLEST area (pixel count) gets recolored to 2
4. All other components get recolored to 1

ONNX viability:
- Requires connected-component detection (8-connected)
- On 10x10 grid, MaxPool-based CC detection needs ~20-30 iterations × ~5 nodes = 100-150 nodes
- Base: 56 nodes, profiled score 13.30
- Even with CC: ~150 nodes * 400 bytes = 60K memory + params → score ~14.1
- **POTENTIALLY VIABLE** — score 14.1 vs base 13.30 → gain +0.8
- But CC detection in ONNX is fragile and complex to build correctly

CC approach for ONNX:
1. Initialize label grid = nonzero_mask * (row*10 + col + 1)  [unique labels]
2. Repeat 20 times: MaxPool(3x3) the label grid, masked by nonzero_mask
3. After convergence, each CC has the same max label
4. Count pixels per label → find minimum count label → mask it as color 2
5. Remaining → color 1

Challenge: Step 4 requires comparing per-label counts, which is hard without dynamic shapes.
Alternative: could potentially use the fact that shapes are always rectangular frames or solid blocks.

Status: Rule cracked (266/266), ONNX build pending — needs careful CC implementation.
"""
import numpy as np
import json
from scipy import ndimage


def solve_277(inp_grid):
    """Smallest CC gets color 2, all others get color 1. 266/266 PASS."""
    inp = np.array(inp_grid)
    out = np.zeros_like(inp)
    
    # Find 8-connected components of color 8
    mask = (inp == 8).astype(int)
    labeled, n = ndimage.label(mask, structure=np.ones((3, 3)))
    
    if n == 0:
        return out
    
    # Find smallest component by area
    areas = []
    for i in range(1, n + 1):
        areas.append(((labeled == i).sum(), i))
    
    min_area = min(a for a, _ in areas)
    
    for area, idx in areas:
        component = (labeled == idx)
        if area == min_area:
            out[component] = 2
        else:
            out[component] = 1
    
    return out


if __name__ == '__main__':
    from pathlib import Path
    task_data = Path('/app/task-data')
    if not task_data.exists():
        task_data = Path(__file__).parent.parent / 'task-data'
    with open(task_data / 'task277.json') as f:
        data = json.load(f)
    all_ex = data['train'] + data['test'] + data.get('arc-gen', [])
    right = sum(1 for ex in all_ex if np.array_equal(solve_277(ex['input']), np.array(ex['output'])))
    print(f'task277: {right}/{len(all_ex)} PASS')