【Leetcode 动态规划、深度优先搜索】不同路径(62)、 不同路径 II(63)、不同路径 III(980)

题目:不同路径 II(63)

一个机器人位于一个 m x n 网格的左上角 (起始点在下图中标记为“Start” )。

机器人每次只能向下或者向右移动一步。机器人试图达到网格的右下角(在下图中标记为“Finish”)。

现在考虑网格中有障碍物。那么从左上角到右下角将会有多少条不同的路径?

网格中的障碍物和空位置分别用 1 和 0 来表示。

说明:m 和 n 的值均不超过 100。

示例 1:

输入:
[
  [0,0,0],
  [0,1,0],
  [0,0,0]
]
输出: 2
解释:
3x3 网格的正中间有一个障碍物。
从左上角到右下角一共有 2 条不同的路径:
1. 向右 -> 向右 -> 向下 -> 向下
2. 向下 -> 向下 -> 向右 -> 向右

解答


# 动态规划转换方程:
# ① dp[i][j] = dp[i-1][j] + dp[i][j-1]  (i>0 and j>0)
# ② dp[i][j] = 1    ((i=0 and dp[i][j-1]!=0) or (j=0 and dp[i-1][j]!=0)), 处理边界, 要求到(i,j)前一个位置路径数不是0, 否则就代表这条路被阻断了
# dp[i][j]表示能到(i, j)位置的路径条数. 条件②的dp[i][j-1]!=0、dp[i-1][j]!=0是必须的,否则有反例:[[0, 0], [1, 1], [0, 0]]

class Solution:
    # 二维dp
    def uniquePathsWithObstacles(self, nums):
        if not nums or nums[0][0] == 1:
            return 0
        rows = len(nums)
        cols = len(nums[0])
        dp = [[0 for _ in range(cols)] for _ in range(rows)]

        for i in range(rows):
            for j in range(cols):
                if i == 0 and j == 0:  # 处理左上角
                    dp[i][j] = 1
                    continue
                if nums[i][j] == 1:  # 障碍物
                    dp[i][j] = 0
                    continue

                if (j == 0 and dp[i-1][j] != 0) or (i == 0 and dp[i][j-1] != 0):  # 处理左、上边界
                    dp[i][j] = 1
                else:
                    dp[i][j] = dp[i-1][j] + dp[i][j-1]
        return dp[-1][-1]



# # 深搜超时,暴风哭泣辽。。
# class Solution:
#     def __init__(self):
#         self.rows = 0
#         self.cols = 0
#         self.book = [[]]
#         self.nums = [[]]
#         self.cnt = 0
#         self.next = [
#             [0, 1],
#             [1, 0]
#         ]
#
#     def uniquePathsWithObstacles(self, obstacleGrid):
#         if not obstacleGrid:
#             return 0
#         self.nums = obstacleGrid
#         self.rows = len(obstacleGrid)
#         self.cols = len(obstacleGrid[0])
#
#         self.book = [[0 for _ in range(self.cols)] for _ in range(self.rows)]
#         self.book[0][0] = 1
#         self.dfs(0, 0)
#         return self.cnt
#
#     def dfs(self, x, y):
#         if x == self.rows-1 and y == self.cols-1:
#             self.cnt += 1
#             return
#         for i in range(2):
#             tx = x + self.next[i][0]
#             ty = y + self.next[i][1]
#             if 0 <= tx < self.rows and 0 <= ty < self.cols and self.book[tx][ty] == 0 and self.nums[tx][ty] == 0:
#                 self.book[tx][ty] = 1
#                 self.dfs(tx, ty)
#                 self.book[tx][ty] = 0

题目:不同路径(62)https://leetcode-cn.com/problems/unique-paths/

不存在障碍物,很简单,动态规划嗖嗖的

# 动态规划转换方程:
# ① dp[i][j] = dp[i-1][j] + dp[i][j-1]  (i>0 and j>0)
# ② dp[i][j] = 1    (i=0 or j=0), 处理边界
# dp[i][j]表示能到(i, j)位置的路径条数

class Solution:
    # 二维dp
    def uniquePaths(self, rows, cols):
        if rows == cols == 0:
            return 0
        dp = [[0 for _ in range(cols)] for _ in range(rows)]

        for i in range(rows):
            for j in range(cols):
                if i == 0 and j == 0:  # 处理左上角
                    dp[i][j] = 1
                    continue
                if i == 0 or j == 0:  # 处理边界
                    dp[i][j] = 1
                else:
                    dp[i][j] = dp[i-1][j] + dp[i][j-1]
        return dp[-1][-1]


# 深度优先搜索也OK,不写了,参考不同路径II

题目:不同路径 III(980)https://leetcode-cn.com/problems/unique-paths-iii/

可以移动方向改为上、下、左、右了。还有一点要特别注意:每一个无障碍方格都要通过一次
深搜代码如下:

# 深度优先搜索
class Solution:
    def __init__(self):
        self.rows = 0
        self.cols = 0
        self.book = [[]]
        self.nums = [[]]
        self.cnt = 0
        self.req_step = 0  # 要求每条路径的步数 = 无障碍方格数
        self.next = [
            [0, 1],
            [1, 0],
            [0, -1],
            [-1, 0]
        ]

    def uniquePathsIII(self, obstacleGrid):
        if not obstacleGrid or obstacleGrid[0][0] == -1:
            return 0
        self.nums = obstacleGrid
        self.rows = len(obstacleGrid)
        self.cols = len(obstacleGrid[0])

        self.book = [[0 for _ in range(self.cols)] for _ in range(self.rows)]
        for i in range(self.rows):
            for j in range(self.cols):
                if self.nums[i][j] == 1:  # 起点
                    start_x = i
                    start_y = j
                if self.nums[i][j] != -1:  # 统计一共要走多少步
                    self.req_step += 1
        self.book[start_x][start_y] = 1
        self.dfs(start_x, start_y, 1)
        return self.cnt

    def dfs(self, x, y, step):
        if self.nums[x][y] == 2 and step == self.req_step:  # 到达终点,并且每一个无障碍方格都通过一次
            self.cnt += 1
            return
        for i in range(4):
            tx = x + self.next[i][0]
            ty = y + self.next[i][1]
            if 0 <= tx < self.rows and 0 <= ty < self.cols and self.book[tx][ty] == 0 and self.nums[tx][ty] != -1:
                self.book[tx][ty] = 1
                self.dfs(tx, ty, step+1)
                self.book[tx][ty] = 0

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原文地址:https://www.cnblogs.com/ldy-miss/p/13255255.html