LWC 61：740. Delete and Earn
LWC 61：740. Delete and Earn
LWC 61：740. Delete and Earn
Problem:
Given an array nums of integers, you can perform operations on the array. In each operation, you pick any nums[i] and delete it to earn nums[i] points. After, you must delete every element equal to nums[i] - 1 or nums[i] + 1. You start with 0 points. Return the maximum number of points you can earn by applying such operations.
Example 1:
Input: nums = [3, 4, 2] Output: 6 Explanation: Delete 4 to earn 4 points, consequently 3 is also deleted. Then, delete 2 to earn 2 points. 6 total points are earned.
Example 2:
Input: nums = [2, 2, 3, 3, 3, 4] Output: 9 Explanation: Delete 3 to earn 3 points, deleting both 2’s and the 4. Then, delete 3 again to earn 3 points, and 3 again to earn 3 points. 9 total points are earned.
Note:
The length of nums is at most 20000.
Each element nums[i] is an integer in the range [1, 10000].
思路： 最简单的思路，选择一个数后，比如[3, 4, 2]选择4，那么3失效，剩余数组为[2]，当作子问题来求解即可，这是一种情况。选择3，那么4和2均失效，剩余数组为[]，也可以当作子问题求解。选择2，则3失效，剩余数组为[4]，在这几种情况中选择profit最多的情况即可。
但上述递归存在一个严重的问题，子问题无法被记录下来，因为选择是无序的。因此可以采用背包的思路，先对这些元素排序，这样数组变为[2, 3, 4]，这样一来对于2选or不选，进一步影响3是否被包含，子问题能够轻而易举的被状态化，因为此时当前位置i，那么对应的i到n的位置可以表示子问题。而这些子问题与第一种求解思路不同的是，它们因位置而存在唯一性。
Java版本：（递归+记忆化）
public int deleteAndEarn(int[] nums) {
Map<Integer, Integer> mem = new HashMap<>();
for (int n : nums) {
mem.put(n, mem.getOrDefault(n, 0) + 1);
}
int[] cnt = new int[mem.size()];
Set<Integer> keys = mem.keySet();
int[] key = keys.stream().mapToInt(i -> i).toArray();
Arrays.sort(key);
for (int i = 0; i < key.length; ++i) {
cnt[i] = mem.get(key[i]);
}
dp = new int[20000 + 16];
return robot(key, cnt, 0);
}
int[] dp;
public int robot(int[] key, int[] cnt, int pos) {
if (pos >= key.length) return 0;
if (dp[pos] > 0) return dp[pos];
int ans = 0;
int choose = 0;
// choose
if (pos + 1 < key.length && key[pos + 1] - 1 == key[pos]) {
choose = key[pos] * cnt[pos] + robot(key, cnt, pos + 2);
}
else {
choose = key[pos] * cnt[pos] + robot(key, cnt, pos + 1);
}
ans = Math.max(ans, choose);
// no choose
ans = Math.max(ans, robot(key, cnt, pos + 1));
return dp[pos] = ans;
}递推版本：
public int deleteAndEarn(int[] nums) {
if (nums.length == 0) return 0;
Map<Integer, Integer> mem = new HashMap<>();
for (int n : nums) {
mem.put(n, mem.getOrDefault(n, 0) + 1);
}
int[] cnt = new int[mem.size()];
Set<Integer> keys = mem.keySet();
int[] key = keys.stream().mapToInt(i -> i).toArray();
Arrays.sort(key);
for (int i = 0; i < key.length; ++i) {
cnt[i] = mem.get(key[i]);
}
int[] dp = new int[20000 + 16];
int last = key.length;
dp[last - 1] = key[last - 1] * cnt[last - 1];
for (int i = last - 2; i >= 0; --i) {
if (key[i] + 1 == key[i + 1]) {
dp[i] = Math.max(dp[i], dp[i + 2] + key[i] * cnt[i]);
}
else {
dp[i] = Math.max(dp[i], dp[i + 1] + key[i] * cnt[i]);
}
dp[i] = Math.max(dp[i], dp[i + 1]);
}
return dp[0];
}简化map版本，用数组位置排序+计数：
public int deleteAndEarn(int[] nums) {
int[] cnt = new int[10016];
for (int num : nums) cnt[num]++;
int[] dp = new int[10016];
dp[0] = 0;
dp[1] = cnt[1];
for (int i = 2; i <= 10000; ++i) {
dp[i] = Math.max(dp[i - 1], dp[i - 2] + cnt[i] * i);
}
return dp[10000];
}Python版本：
def deleteAndEarn(self, nums):
"""
:type nums: List[int]
:rtype: int
"""
cnt = [0] * 10016
for num in nums:
cnt[num] = cnt[num] + 1
dp = [0] * 10016
dp[0] = 0
dp[1] = cnt[1]
for i in range(2, 10001):
dp[i] = max(dp[i - 1], dp[i - 2] + i * cnt[i])
return dp[10000]