# -*- coding: utf-8 -*-
from Queue import *

def breadth_first_search(graph, start, goal):
    frontier = Queue()
    frontier.put(start)
    came_from = {}
    came_from[start] = None
    
    while not frontier.empty():
        current = frontier.get()
        
        if current == goal:
            break
        
        for next in graph.neighbors(current):
            if next not in came_from:
                frontier.put(next)
                came_from[next] = current
    
    return came_from

def dijkstra_search(graph, start, goal):
    frontier = PriorityQueue()
    frontier.put(start, 0)
    came_from = {}
    cost_so_far = {}
    came_from[start] = None
    cost_so_far[start] = 0
    
    while not frontier.empty():
        current = frontier.get()
        
        if current == goal:
            break
        
        for next in graph.neighbors(current):
            new_cost = cost_so_far[current] + graph.cost(current, next)
            if next not in cost_so_far or new_cost < cost_so_far[next]:
                cost_so_far[next] = new_cost
                priority = new_cost
                frontier.put(next, priority)
                came_from[next] = current
    
    return came_from

def a_star_search(graph, start, goal):
    frontier = PriorityQueue()
    frontier.put(start, 0)
    came_from = {}
    cost_so_far = {}
    came_from[start] = None
    cost_so_far[start] = 0
    
    while not frontier.empty():
        current = frontier.get()
        
        if current == goal:
            break
        
        for next in graph.neighbors(current):
            new_cost = cost_so_far[current] + graph.cost(current, next)
            if next not in cost_so_far or new_cost < cost_so_far[next]:
                cost_so_far[next] = new_cost
                priority = new_cost + heuristic(goal, next)
                frontier.put(next, priority)
                came_from[next] = current
    
    return came_from

def heuristic(a, b):
    (x1, y1) = a
    (x2, y2) = b
    return abs(x1 - x2) + abs(y1 - y2)

def reconstruct_path(came_from, start, goal):
    current = goal
    path = [current]
    while current != start:
        current = came_from[current]
        path.append(current)
    path.reverse()
    return path

def arrow_draw(global_path, current):
    if current not in global_path.keys():
       return '.'
    if global_path[current] is None:
       return '.'
    (cx, cy) = current
    (nx, ny) = global_path[current]
    if cx-nx > 0:
       return '→'
    elif cx-nx < 0:
       return '←'
    elif cy-ny > 0:
       return '↑'
    elif cy-ny < 0:
       return '↓'
    else:
       return '.'