[LeetCode] 494. Target Sum 目标和
You are given a list of non-negative integers, a1, a2, ..., an, and a target, S. Now you have 2 symbols +
and -
. For each integer, you should choose one from +
and -
as its new symbol.
Find out how many ways to assign symbols to make sum of integers equal to target S.
Example 1:
Input: nums is [1, 1, 1, 1, 1], S is 3. Output: 5 Explanation: -1+1+1+1+1 = 3 +1-1+1+1+1 = 3 +1+1-1+1+1 = 3 +1+1+1-1+1 = 3 +1+1+1+1-1 = 3 There are 5 ways to assign symbols to make the sum of nums be target 3.
Note:
- The length of the given array is positive and will not exceed 20.
- The sum of elements in the given array will not exceed 1000.
- Your output answer is guaranteed to be fitted in a 32-bit integer.
这道题给了我们一个数组,和一个目标值,让给数组中每个数字加上正号或负号,然后求和要和目标值相等,求有多少中不同的情况。那么对于这种求多种情况的问题,博主最想到的方法使用递归来做。从第一个数字,调用递归函数,在递归函数中,分别对目标值进行加上当前数字调用递归,和减去当前数字调用递归,这样会涵盖所有情况,并且当所有数字遍历完成后,若目标值为0了,则结果 res 自增1,参见代码如下:
解法一:
class Solution { public: int findTargetSumWays(vector<int>& nums, int S) { int res = 0; helper(nums, S, 0, res); return res; } void helper(vector<int>& nums, long S, int start, int& res) { if (start >= nums.size()) { if (S == 0) ++res; return; } helper(nums, S - nums[start], start + 1, res); helper(nums, S + nums[start], start + 1, res); } };
我们对上面的递归方法进行优化,使用 memo 数组来记录中间值,这样可以避免重复运算,参见代码如下:
解法二:
class Solution { public: int findTargetSumWays(vector<int>& nums, int S) { vector<unordered_map<int, int>> memo(nums.size()); return helper(nums, S, 0, memo); } int helper(vector<int>& nums, long sum, int start, vector<unordered_map<int, int>>& memo) { if (start == nums.size()) return sum == 0; if (memo[start].count(sum)) return memo[start][sum]; int cnt1 = helper(nums, sum - nums[start], start + 1, memo); int cnt2 = helper(nums, sum + nums[start], start + 1, memo); return memo[start][sum] = cnt1 + cnt2; } };
我们也可以使用迭代的方法来解,使用一个 dp 数组,其中 dp[i][j] 表示到第 i-1 个数字且和为j的情况总数,参见代码如下:
解法三:
class Solution { public: int findTargetSumWays(vector<int>& nums, int S) { int n = nums.size(); vector<unordered_map<int, int>> dp(n + 1); dp[0][0] = 1; for (int i = 0; i < n; ++i) { for (auto &a : dp[i]) { int sum = a.first, cnt = a.second; dp[i + 1][sum + nums[i]] += cnt; dp[i + 1][sum - nums[i]] += cnt; } } return dp[n][S]; } };
我们也可以对上面的方法进行空间上的优化,只用一个 HashMap,而不是用一个数组的哈希表,在遍历数组中的每一个数字时,新建一个 HashMap,在遍历原 HashMap 中的项时更新这个新建的 HashMap,最后把新建的 HashMap 整个赋值为原 HashMap,参见代码如下:
解法四:
class Solution { public: int findTargetSumWays(vector<int>& nums, int S) { unordered_map<int, int> dp; dp[0] = 1; for (int num : nums) { unordered_map<int, int> t; for (auto a : dp) { int sum = a.first, cnt = a.second; t[sum + num] += cnt; t[sum - num] += cnt; } dp = t; } return dp[S]; } };
Github 同步地址:
https://github.com/grandyang/leetcode/issues/494
类似题目:
参考资料:
https://leetcode.com/problems/target-sum/
https://leetcode.com/problems/target-sum/discuss/97371/Java-Short-DFS-Solution
https://leetcode.com/problems/target-sum/discuss/97369/Evolve-from-brute-force-to-dp