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第 116 场双周赛 Q3
数组
动态规划

English Version

题目描述

给你一个下标从 0 开始的整数数组 nums 和一个整数 target 。

返回和为 target 的 nums 子序列中,子序列 长度的最大值 。如果不存在和为 target 的子序列,返回 -1 。

子序列 指的是从原数组中删除一些或者不删除任何元素后,剩余元素保持原来的顺序构成的数组。

 

示例 1:

输入:nums = [1,2,3,4,5], target = 9
输出:3
解释:总共有 3 个子序列的和为 9 :[4,5] ,[1,3,5] 和 [2,3,4] 。最长的子序列是 [1,3,5] 和 [2,3,4] 。所以答案为 3 。

示例 2:

输入:nums = [4,1,3,2,1,5], target = 7
输出:4
解释:总共有 5 个子序列的和为 7 :[4,3] ,[4,1,2] ,[4,2,1] ,[1,1,5] 和 [1,3,2,1] 。最长子序列为 [1,3,2,1] 。所以答案为 4 。

示例 3:

输入:nums = [1,1,5,4,5], target = 3
输出:-1
解释:无法得到和为 3 的子序列。

 

提示:

  • 1 <= nums.length <= 1000
  • 1 <= nums[i] <= 1000
  • 1 <= target <= 1000

解法

方法一:动态规划

我们定义 $f[i][j]$ 表示前 $i$ 个数中选取若干个数,使得这若干个数的和恰好为 $j$ 的最长子序列的长度。初始时 $f[0][0]=0$,其余位置均为 $-\infty$

对于 $f[i][j]$,我们考虑第 $i$ 个数 $x$,如果不选取 $x$,那么 $f[i][j]=f[i-1][j]$;如果选取 $x$,那么 $f[i][j]=f[i-1][j-x]+1$,其中 $j\ge x$。因此我们有状态转移方程:

$$ f[i][j]=\max{f[i-1][j],f[i-1][j-x]+1} $$

最终答案为 $f[n][target]$,如果 $f[n][target]\le0$,则不存在和为 $target$ 的子序列,返回 $-1$

时间复杂度 $O(n\times target)$,空间复杂度 $O(n\times target)$。其中 $n$ 为数组长度,而 $target$ 为目标值。

我们注意到 $f[i][j]$ 的状态只与 $f[i-1][\cdot]$ 有关,因此我们可以优化掉第一维,将空间复杂度优化到 $O(target)$

Python3

class Solution:
    def lengthOfLongestSubsequence(self, nums: List[int], target: int) -> int:
        n = len(nums)
        f = [[-inf] * (target + 1) for _ in range(n + 1)]
        f[0][0] = 0
        for i, x in enumerate(nums, 1):
            for j in range(target + 1):
                f[i][j] = f[i - 1][j]
                if j >= x:
                    f[i][j] = max(f[i][j], f[i - 1][j - x] + 1)
        return -1 if f[n][target] <= 0 else f[n][target]

Java

class Solution {
    public int lengthOfLongestSubsequence(List<Integer> nums, int target) {
        int n = nums.size();
        int[][] f = new int[n + 1][target + 1];
        final int inf = 1 << 30;
        for (int[] g : f) {
            Arrays.fill(g, -inf);
        }
        f[0][0] = 0;
        for (int i = 1; i <= n; ++i) {
            int x = nums.get(i - 1);
            for (int j = 0; j <= target; ++j) {
                f[i][j] = f[i - 1][j];
                if (j >= x) {
                    f[i][j] = Math.max(f[i][j], f[i - 1][j - x] + 1);
                }
            }
        }
        return f[n][target] <= 0 ? -1 : f[n][target];
    }
}

C++

class Solution {
public:
    int lengthOfLongestSubsequence(vector<int>& nums, int target) {
        int n = nums.size();
        int f[n + 1][target + 1];
        memset(f, -0x3f, sizeof(f));
        f[0][0] = 0;
        for (int i = 1; i <= n; ++i) {
            int x = nums[i - 1];
            for (int j = 0; j <= target; ++j) {
                f[i][j] = f[i - 1][j];
                if (j >= x) {
                    f[i][j] = max(f[i][j], f[i - 1][j - x] + 1);
                }
            }
        }
        return f[n][target] <= 0 ? -1 : f[n][target];
    }
};

Go

func lengthOfLongestSubsequence(nums []int, target int) int {
	n := len(nums)
	f := make([][]int, n+1)
	for i := range f {
		f[i] = make([]int, target+1)
		for j := range f[i] {
			f[i][j] = -(1 << 30)
		}
	}
	f[0][0] = 0
	for i := 1; i <= n; i++ {
		x := nums[i-1]
		for j := 0; j <= target; j++ {
			f[i][j] = f[i-1][j]
			if j >= x {
				f[i][j] = max(f[i][j], f[i-1][j-x]+1)
			}
		}
	}
	if f[n][target] <= 0 {
		return -1
	}
	return f[n][target]
}

TypeScript

function lengthOfLongestSubsequence(nums: number[], target: number): number {
    const n = nums.length;
    const f: number[][] = Array.from({ length: n + 1 }, () => Array(target + 1).fill(-Infinity));
    f[0][0] = 0;
    for (let i = 1; i <= n; ++i) {
        const x = nums[i - 1];
        for (let j = 0; j <= target; ++j) {
            f[i][j] = f[i - 1][j];
            if (j >= x) {
                f[i][j] = Math.max(f[i][j], f[i - 1][j - x] + 1);
            }
        }
    }
    return f[n][target] <= 0 ? -1 : f[n][target];
}

方法二

Python3

class Solution:
    def lengthOfLongestSubsequence(self, nums: List[int], target: int) -> int:
        f = [0] + [-inf] * target
        for x in nums:
            for j in range(target, x - 1, -1):
                f[j] = max(f[j], f[j - x] + 1)
        return -1 if f[-1] <= 0 else f[-1]

Java

class Solution {
    public int lengthOfLongestSubsequence(List<Integer> nums, int target) {
        int[] f = new int[target + 1];
        final int inf = 1 << 30;
        Arrays.fill(f, -inf);
        f[0] = 0;
        for (int x : nums) {
            for (int j = target; j >= x; --j) {
                f[j] = Math.max(f[j], f[j - x] + 1);
            }
        }
        return f[target] <= 0 ? -1 : f[target];
    }
}

C++

class Solution {
public:
    int lengthOfLongestSubsequence(vector<int>& nums, int target) {
        int f[target + 1];
        memset(f, -0x3f, sizeof(f));
        f[0] = 0;
        for (int x : nums) {
            for (int j = target; j >= x; --j) {
                f[j] = max(f[j], f[j - x] + 1);
            }
        }
        return f[target] <= 0 ? -1 : f[target];
    }
};

Go

func lengthOfLongestSubsequence(nums []int, target int) int {
	f := make([]int, target+1)
	for i := range f {
		f[i] = -(1 << 30)
	}
	f[0] = 0
	for _, x := range nums {
		for j := target; j >= x; j-- {
			f[j] = max(f[j], f[j-x]+1)
		}
	}
	if f[target] <= 0 {
		return -1
	}
	return f[target]
}

TypeScript

function lengthOfLongestSubsequence(nums: number[], target: number): number {
    const f: number[] = Array(target + 1).fill(-Infinity);
    f[0] = 0;
    for (const x of nums) {
        for (let j = target; j >= x; --j) {
            f[j] = Math.max(f[j], f[j - x] + 1);
        }
    }
    return f[target] <= 0 ? -1 : f[target];
}