Posts tagged as “medium”

花花酱 LeetCode 1705. Maximum Number of Eaten Apples

By zxi on December 27, 2020

There is a special kind of apple tree that grows apples every day for n days. On the i^th day, the tree grows apples[i] apples that will rot after days[i] days, that is on day i + days[i] the apples will be rotten and cannot be eaten. On some days, the apple tree does not grow any apples, which are denoted by apples[i] == 0 and days[i] == 0.

You decided to eat at most one apple a day (to keep the doctors away). Note that you can keep eating after the first n days.

Given two integer arrays days and apples of length n, return the maximum number of apples you can eat.

Example 1:

Input: apples = [1,2,3,5,2], days = [3,2,1,4,2]
Output: 7
Explanation: You can eat 7 apples:
- On the first day, you eat an apple that grew on the first day.
- On the second day, you eat an apple that grew on the second day.
- On the third day, you eat an apple that grew on the second day. After this day, the apples that grew on the third day rot.
- On the fourth to the seventh days, you eat apples that grew on the fourth day.

Example 2:

Input: apples = [3,0,0,0,0,2], days = [3,0,0,0,0,2]
Output: 5
Explanation: You can eat 5 apples:
- On the first to the third day you eat apples that grew on the first day.
- Do nothing on the fouth and fifth days.
- On the sixth and seventh days you eat apples that grew on the sixth day.

Constraints:

apples.length == n
days.length == n
1 <= n <= 2 * 10⁴
0 <= apples[i], days[i] <= 2 * 10⁴
days[i] = 0 if and only if apples[i] = 0.

Solution: PriorityQueue

Sort by rotten day in ascending order, only push onto the queue when that day has come (be able to grow apples).

Time complexity: O((n+ d)logn)
Space complexity: O(n)

C++

// Author: Huahua

class Solution {

public:

int eatenApples(vector<int>& apples, vector<int>& days) {

const int n = apples.size();

using P = pair<int, int>;

priority_queue<P, vector<P>, greater<P>> q; // {rotten_day, index}

int ans = 0;

for (int d = 0; d < n || !q.empty(); ++d) {

if (d < n && apples[d]) q.emplace(d + days[d], d);

while (!q.empty()

&& (q.top().first <= d || apples[q.top().second] == 0)) q.pop();

if (q.empty()) continue;

--apples[q.top().second];

++ans;

}

return ans;

}

};

花花酱 LeetCode 1702. Maximum Binary String After Change

By zxi on December 26, 2020

You are given a binary string binary consisting of only 0‘s or 1‘s. You can apply each of the following operations any number of times:

Operation 1: If the number contains the substring "00", you can replace it with "10".
- For example, "00010" -> "10010“
Operation 2: If the number contains the substring "10", you can replace it with "01".
- For example, "00010" -> "00001"

Return the maximum binary string you can obtain after any number of operations. Binary string x is greater than binary string y if x‘s decimal representation is greater than y‘s decimal representation.

Example 1:

Input: binary = "000110"
Output: "111011"
Explanation: A valid transformation sequence can be:
"000110" -> "000101" 
"000101" -> "100101" 
"100101" -> "110101" 
"110101" -> "110011" 
"110011" -> "111011"

Example 2:

Input: binary = "01"
Output: "01"
Explanation: "01" cannot be transformed any further.

Constraints:

1 <= binary.length <= 10⁵
binary consist of '0' and '1'.

Solution: Greedy + Counting

Leading 1s are good, no need to change them.
For the rest of the string
1. Apply operation 2 to make the string into 3 parts, leading 1s, middle 0s and tailing 1s.
e.g. 11010101 => 11001101 => 11001011 => 11000111
2. Apply operation 1 to make flip zeros to ones except the last one.
e.g. 11000111 => 11100111 => 11110111

There will be only one zero (if the input string is not all 1s) is the final largest string, the position of the zero is leading 1s + zeros – 1.

Time complexity: O(n)
Space complexity: O(n)

C++

class Solution {

public:

string maximumBinaryString(string s) {

const int n = s.length();

int l = 0;

int z = 0;

for (char& c : s) {

if (c == '0') {

++z;

} else if (z == 0) { // leading 1s

++l;

}

c = '1';

}

if (l != n) s[l + z - 1] = '0';

return s;

}

};

花花酱 LeetCode 1701. Average Waiting Time

By zxi on December 26, 2020

There is a restaurant with a single chef. You are given an array customers, where customers[i] = [arrival_i, time_i]:

arrival_i is the arrival time of the i^th customer. The arrival times are sorted in non-decreasing order.
time_i is the time needed to prepare the order of the i^th customer.

When a customer arrives, he gives the chef his order, and the chef starts preparing it once he is idle. The customer waits till the chef finishes preparing his order. The chef does not prepare food for more than one customer at a time. The chef prepares food for customers in the order they were given in the input.

Return the average waiting time of all customers. Solutions within 10^-5 from the actual answer are considered accepted.

Example 1:

Input: customers = [[1,2],[2,5],[4,3]]
Output: 5.00000
Explanation:
1) The first customer arrives at time 1, the chef takes his order and starts preparing it immediately at time 1, and finishes at time 3, so the waiting time of the first customer is 3 - 1 = 2.
2) The second customer arrives at time 2, the chef takes his order and starts preparing it at time 3, and finishes at time 8, so the waiting time of the second customer is 8 - 2 = 6.
3) The third customer arrives at time 4, the chef takes his order and starts preparing it at time 8, and finishes at time 11, so the waiting time of the third customer is 11 - 4 = 7.
So the average waiting time = (2 + 6 + 7) / 3 = 5.

Example 2:

Input: customers = [[5,2],[5,4],[10,3],[20,1]]
Output: 3.25000
Explanation:
1) The first customer arrives at time 5, the chef takes his order and starts preparing it immediately at time 5, and finishes at time 7, so the waiting time of the first customer is 7 - 5 = 2.
2) The second customer arrives at time 5, the chef takes his order and starts preparing it at time 7, and finishes at time 11, so the waiting time of the second customer is 11 - 5 = 6.
3) The third customer arrives at time 10, the chef takes his order and starts preparing it at time 11, and finishes at time 14, so the waiting time of the third customer is 14 - 10 = 4.
4) The fourth customer arrives at time 20, the chef takes his order and starts preparing it immediately at time 20, and finishes at time 21, so the waiting time of the fourth customer is 21 - 20 = 1.
So the average waiting time = (2 + 6 + 4 + 1) / 4 = 3.25.

Constraints:

1 <= customers.length <= 10⁵
1 <= arrival_i, time_i <= 10⁴
arrival_i<= arrival_i+1

Solution: Simulation

When a customer arrives, if the arrival time is greater than current, then advance the clock to arrival time. Advance the clock by cooking time. Waiting time = current time – arrival time.

Time complexity: O(n)
Space complexity: O(1)

C++

// Author: Huahua

class Solution {

public:

double averageWaitingTime(vector<vector<int>>& customers) {

int t = 0;

double w = 0;

for (const auto& c : customers) {

if (c[0] > t) t = c[0];

t += c[1];

w += t - c[0];

}

return w / customers.size();

}

};

Python3

# Author: Huahua

class Solution:

def averageWaitingTime(self, customers: List[List[int]]) -> float:

cur = 0

waiting = 0

for arrival, time in customers:

cur = max(cur, arrival) + time

waiting += cur - arrival

return waiting / len(customers)

花花酱 LeetCode 1696. Jump Game VI

By zxi on December 20, 2020

You are given a 0-indexed integer array nums and an integer k.

You are initially standing at index 0. In one move, you can jump at most k steps forward without going outside the boundaries of the array. That is, you can jump from index i to any index in the range [i + 1, min(n - 1, i + k)] inclusive.

You want to reach the last index of the array (index n - 1). Your score is the sum of all nums[j] for each index j you visited in the array.

Return the maximum score you can get.

Example 1:

Input: nums = [1,-1,-2,4,-7,3], k = 2
Output: 7
Explanation: You can choose your jumps forming the subsequence [1,-1,4,3] (underlined above). The sum is 7.

Example 2:

Input: nums = [10,-5,-2,4,0,3], k = 3
Output: 17
Explanation: You can choose your jumps forming the subsequence [10,4,3] (underlined above). The sum is 17.

Example 3:

Input: nums = [1,-5,-20,4,-1,3,-6,-3], k = 2
Output: 0

Constraints:

1 <= nums.length, k <= 10⁵
-10⁴ <= nums[i] <= 10⁴

Solution: DP + Monotonic Queue

dp[i] = nums[i] + max(dp[j]) i – k <= j < i

Brute force time complexity: O(n*k) => TLE

Python3 / TLE

# Author: Huahua 52/58 Passed (TLE)

class Solution:

def maxResult(self, nums: List[int], k: int) -> int:

@lru_cache(None)

def dp(i: int) -> int:

return nums[0] if i == 0 else nums[i] + max(dp(j) for j in range(max(0, i - k), i))

return dp(len(nums) - 1)

This problem can be reduced to find the maximum for a sliding window that can be solved by monotonic queue.

Time complexity: O(n)
Space complexity: O(n+k) -> O(k)

C++

// Author: Huahua

class Solution {

public:

int maxResult(vector<int>& nums, int k) {

const int n = nums.size();

vector<int> dp(n);

deque<int> q{{0}};

dp[0] = nums[0];

for (int i = 1; i < n; ++i) {

dp[i] = nums[i] + dp[q.front()];

while (!q.empty() && dp[i] >= dp[q.back()]) q.pop_back();

while (!q.empty() && i - q.front() >= k) q.pop_front();

q.push_back(i);

}

return dp[n - 1];

}

};

C++/O(n) Space

// Author: Huahua

class Solution {

public:

int maxResult(vector<int>& nums, int k) {

const int n = nums.size();

deque<pair<int, int>> q{{nums[0], 0}};

for (int i = 1; i < n; ++i) {

const int cur = nums[i] + q.front().first;

while (!q.empty() && cur >= q.back().first)

q.pop_back();

while (!q.empty() && i - q.front().second >= k)

q.pop_front();

q.emplace_back(cur, i);

}

for (const auto& [v, i] : q)

if (i == n - 1) return v;

return 0;

}

};

花花酱 LeetCode 1695. Maximum Erasure Value

By zxi on December 20, 2020

You are given an array of positive integers nums and want to erase a subarray containing unique elements. The score you get by erasing the subarray is equal to the sum of its elements.

Return the maximum score you can get by erasing exactly one subarray.

An array b is called to be a subarray of a if it forms a contiguous subsequence of a, that is, if it is equal to a[l],a[l+1],...,a[r] for some (l,r).

Example 1:

Input: nums = [4,2,4,5,6]
Output: 17
Explanation: The optimal subarray here is [2,4,5,6].

Example 2:

Input: nums = [5,2,1,2,5,2,1,2,5]
Output: 8
Explanation: The optimal subarray here is [5,2,1] or [1,2,5].

Constraints:

1 <= nums.length <= 10⁵
1 <= nums[i] <= 10⁴

Solution: Sliding window + Hashset

Maintain a window that has no duplicate elements.

Time complexity: O(n)
Space complexity: O(n)

C++

// Author: Huahua

class Solution {

public:

int maximumUniqueSubarray(vector<int>& nums) {

const int n = nums.size();

unordered_set<int> t;

int ans = 0;

for (int l = 0, r = 0, s = 0; r < n; ++r) {

while (t.count(nums[r]) && l < r) {

s -= nums[l];

t.erase(nums[l++]);

}

t.insert(nums[r]);

ans = max(ans, s += nums[r]);

}

return ans;

}

};