from collections import defaultdict
from utils import open_day
from heapq import heappop, heappush

def a_star(start, goal, neighbours, h, d):
    open_set = {start}
    open_heapq = [(0, start)]
    came_from = dict()
    g_score = defaultdict(lambda: float('inf'))
    g_score[start] = 0
    f_score = defaultdict(lambda: float('inf'))
    f_score[start] = h(start)

    while open_set:
        f, current = open_heapq[0]
        if current == goal:
            return f
        heappop(open_heapq)
        open_set.remove(current)
        for neighbour in neighbours(current):
            tentative_g = g_score[current] + d(current, neighbour)
            if tentative_g < g_score[neighbour]:
                came_from[neighbour] = current
                g_score[neighbour] = tentative_g
                f_score[neighbour] = tentative_g + h(neighbour)
                if neighbour not in open_set:
                    open_set.add(neighbour)
                    heappush(open_heapq, (f_score[neighbour], neighbour))
    return None

with open_day(15) as f:
    inp = [[int(c) for c in l.rstrip()] for l in f]

def neighbours(p, dim):
    for dx, dy in ((-1, 0), (1, 0), (0, -1), (0, 1)):
        px, py = p[0] + dx, p[1] + dy
        if px < 0 or py < 0 or px >= dim[0] or py >= dim[1]: continue
        yield px, py

def manhattan(a, b): return abs(a[0] - b[0]) + abs(a[1] - b[1])
def d(a, b):
    x, y = b
    add = x // len(inp[0]) + y // len(inp)
    x, y = x % len(inp[0]), y % len(inp)
    return (inp[y][x] + add - 1) % 9 + 1

start = (0, 0)
goal1 = (len(inp[0]) - 1, len(inp) - 1)
neighbours1 = lambda p: neighbours(p, (len(inp[0]), len(inp)))
print(a_star(start, goal1, neighbours1, lambda p: manhattan(p, goal1), d))
goal2 = (len(inp[0]) * 5 - 1, len(inp) * 5 - 1)
neighbours2 = lambda p: neighbours(p, (len(inp[0]) * 5, len(inp) * 5))
print(a_star(start, goal2, neighbours2, lambda p: manhattan(p, goal2), d))