Knight Shortest Path

problem at:

# Solution

All following solutions take time and space.

# BFS w/ HashMap

Use queue to visit nodes and dist(could also be an array or HashSet instead of HashMap) to store the distance of reaching a point.

Definition for a point.
class Point:
    def __init__(self, a=0, b=0):
        self.x = a
        self.y = b
DIRECTIONS = [(-1, -2), (-1, 2), (1, -2), (1, 2), (-2, -1), (-2, 1), (2, -1), (2, 1)]
class Solution:
    @param grid: a chessboard included 0 (false) and 1 (true)
    @param source: a point
    @param destination: a point
    @return: the shortest path
    def shortestPath(self, grid, source, destination):
        n, m = len(grid), len(grid[0])
        if not n or not m: return -1
        queue = [(source.x, source.y)]
        dist = {(source.x, source.y): 0}

        while queue:
            x, y = queue.pop(0)
            if (x, y)==(destination.x, destination.y):
                return dist[(x, y)]
            for dx, dy in DIRECTIONS:
                nx, ny = x + dx, y + dy
                if self.is_valid(n, m, nx, ny, grid, dist):
                    queue.append((nx, ny))
                    dist[(nx, ny)] = dist[(x, y)] + 1
        return -1

    def is_valid(self, n, m, x, y, grid, dist):
        if not 0<=x<n or not 0<=y<m:
            return False
        return grid[x][y]!=1 and (x, y) not in dist