from collections import defaultdict, deque
import heapq

# data from archerdata.py, cost map from document
grid = [
    [0,0,0,0,0,4,0,0,0,0,3,3,3],
    [0,0,0,0,0,4,0,0,0,0,0,3,3],
    [0,1,0,0,0,0,4,4,0,0,0,0,0],
    [0,1,1,1,0,0,1,4,4,0,0,0,0],
    [0,0,0,1,0,0,0,1,1,4,4,4,0],
    [0,0,0,0,3,0,0,0,0,0,0,4,4],
    [0,0,0,3,3,0,0,1,1,1,0,0,0],
    [0,0,3,3,3,0,1,2,1,0,0,0,0],
    [0,3,3,4,4,0,0,1,1,0,0,0,0],
    [0,4,4,0,0,0,1,0,0,0,0,0,1],
    [0,0,4,0,0,0,0,0,0,0,0,1,1],
    [0,0,0,0,0,0,3,3,3,1,1,1,0],
    [0,0,0,0,0,3,3,1,1,2,2,1,0]
]
cost_map = {0:1, 1:2, 2:3, 3:1, 4:3}

# necessary to convert row and column to tile number
def coords_to_tile(i, j, cols=13):
    """0-based (i,j) → 1-based tile ID"""
    return i*cols + j + 1

def tile_to_coords(tile, cols=13):
    """1-based tile ID → 0-based (i,j)"""
    t = tile - 1
    return divmod(t, cols)

# graph
def build_tile_graph(grid, cost_map):
    rows, cols = len(grid), len(grid[0])
    g = defaultdict(list)
    directions_even  = [(-1,-1),(-1,0),(0,-1),(0,1),(1,-1),(1,0)]
    directions_odd = [(-1,0),(-1,1),(0,-1),(0,1),(1,0),(1,1)]

    for i in range(rows):
        for j in range(cols):
            u = coords_to_tile(i, j, cols)
            dirs = directions_even if i % 2 == 0 else directions_odd
            for di, dj in dirs:
                ni, nj = i + di, j + dj
                if 0 <= ni < rows and 0 <= nj < cols:
                    v = coords_to_tile(ni, nj, cols)
                    move_cost = cost_map[ grid[ni][nj] ]
                    g[u].append((v, move_cost))
    return g

# 3) Dijkstra's algorithm
def dijkstra(graph, start, max_cost):
    heap = [(0, start)]
    dist = {start: 0}
    while heap:
        cost, u = heapq.heappop(heap)
        if cost > max_cost:
            continue
        for v, c in graph[u]:
            nc = cost + c
            if nc <= max_cost and (v not in dist or nc < dist[v]):
                dist[v] = nc
                heapq.heappush(heap, (nc, v))
    return dist

if __name__ == "__main__":
    graph      = build_tile_graph(grid, cost_map)
    start_id   = 85    # tile "A" in the map
    max_moves  = 6     # max cost that we can spend moving (per document)
    reachable  = dijkstra(graph, start_id, max_moves)
    result     = sorted(reachable.keys())
    print(",".join(map(str, result)))