Posts tagged as “simulation”

花花酱 LeetCode 1688. Count of Matches in Tournament

By zxi on December 13, 2020

You are given an integer n, the number of teams in a tournament that has strange rules:

If the current number of teams is even, each team gets paired with another team. A total of n / 2 matches are played, and n / 2 teams advance to the next round.
If the current number of teams is odd, one team randomly advances in the tournament, and the rest gets paired. A total of (n - 1) / 2 matches are played, and (n - 1) / 2 + 1 teams advance to the next round.

Return the number of matches played in the tournament until a winner is decided.

Example 1:

Input: n = 7
Output: 6
Explanation: Details of the tournament: 
- 1st Round: Teams = 7, Matches = 3, and 4 teams advance.
- 2nd Round: Teams = 4, Matches = 2, and 2 teams advance.
- 3rd Round: Teams = 2, Matches = 1, and 1 team is declared the winner.
Total number of matches = 3 + 2 + 1 = 6.

Example 2:

Input: n = 14
Output: 13
Explanation: Details of the tournament:
- 1st Round: Teams = 14, Matches = 7, and 7 teams advance.
- 2nd Round: Teams = 7, Matches = 3, and 4 teams advance.
- 3rd Round: Teams = 4, Matches = 2, and 2 teams advance.
- 4th Round: Teams = 2, Matches = 1, and 1 team is declared the winner.
Total number of matches = 7 + 3 + 2 + 1 = 13.

Constraints:

1 <= n <= 200

Solution: Simulation / Recursion

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

C++

// Ver 1

class Solution {

public:

int numberOfMatches(int n) {

int ans = 0;

while (n > 1) {

ans += n / 2 + (n & 1);

n /= 2;

}

return ans;

}

};

// Ver 2

class Solution {

public:

int numberOfMatches(int n) {

return n > 1 ? n / 2 + (n & 1) + numberOfMatches(n / 2) : 0;

}

};

花花酱 LeetCode 1652. Defuse the Bomb

By zxi on November 14, 2020

You have a bomb to defuse, and your time is running out! Your informer will provide you with a circular array code of length of n and a key k.

To decrypt the code, you must replace every number. All the numbers are replaced simultaneously.

If k > 0, replace the i^th number with the sum of the next k numbers.
If k < 0, replace the i^th number with the sum of the previous k numbers.
If k == 0, replace the i^th number with 0.

As code is circular, the next element of code[n-1] is code[0], and the previous element of code[0] is code[n-1].

Given the circular array code and an integer key k, return the decrypted code to defuse the bomb!

Example 1:

Input: code = [5,7,1,4], k = 3
Output: [12,10,16,13]
Explanation: Each number is replaced by the sum of the next 3 numbers. The decrypted code is [7+1+4, 1+4+5, 4+5+7, 5+7+1]. Notice that the numbers wrap around.

Example 2:

Input: code = [1,2,3,4], k = 0
Output: [0,0,0,0]
Explanation: When k is zero, the numbers are replaced by 0.

Example 3:

Input: code = [2,4,9,3], k = -2
Output: [12,5,6,13]
Explanation: The decrypted code is [3+9, 2+3, 4+2, 9+4]. Notice that the numbers wrap around again. If k is negative, the sum is of the previous numbers.

Constraints:

n == code.length
1 <= n <= 100
1 <= code[i] <= 100
-(n - 1) <= k <= n - 1

Solution 1: Simulation

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

C++

class Solution {

public:

vector<int> decrypt(vector<int>& code, int k) {

const int n = code.size();

vector<int> ans(n);

int sign = k > 0 ? 1 : -1;

for (int i = 0; i < n; ++i)

for (int j = 1; j <= abs(k); ++j)

ans[i] += code[(i + j * sign + n) % n];

return ans;

}

};

花花酱 1646. Get Maximum in Generated Array

By zxi on November 8, 2020

You are given an integer n. An array nums of length n + 1 is generated in the following way:

nums[0] = 0
nums[1] = 1
nums[2 * i] = nums[i] when 2 <= 2 * i <= n
nums[2 * i + 1] = nums[i] + nums[i + 1] when 2 <= 2 * i + 1 <= n

Returnthe maximum integer in the array nums.

Example 1:

Input: n = 7
Output: 3
Explanation: According to the given rules:
  nums[0] = 0
  nums[1] = 1
  nums[(1 * 2) = 2] = nums[1] = 1
  nums[(1 * 2) + 1 = 3] = nums[1] + nums[2] = 1 + 1 = 2
  nums[(2 * 2) = 4] = nums[2] = 1
  nums[(2 * 2) + 1 = 5] = nums[2] + nums[3] = 1 + 2 = 3
  nums[(3 * 2) = 6] = nums[3] = 2
  nums[(3 * 2) + 1 = 7] = nums[3] + nums[4] = 2 + 1 = 3
Hence, nums = [0,1,1,2,1,3,2,3], and the maximum is 3.

Example 2:

Input: n = 2
Output: 1
Explanation: According to the given rules, the maximum between nums[0], nums[1], and nums[2] is 1.

Example 3:

Input: n = 3
Output: 2
Explanation: According to the given rules, the maximum between nums[0], nums[1], nums[2], and nums[3] is 2.

Constraints:

0 <= n <= 100

Solution: Simulation

Generate the array by the given rules.

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

C++

class Solution {

public:

int getMaximumGenerated(int n) {

vector<int> nums(n + 1);

nums[0] = 0;

if (n > 0) nums[1] = 1;

for (int i = 1; i * 2 <= n; ++i) {

nums[2 * i] = nums[i];

if (i * 2 + 1 <= n) nums[2 * i + 1] = nums[i] + nums[i + 1];

}

return *max_element(begin(nums), end(nums));

}

};

花花酱 LeetCode 1606. Find Servers That Handled Most Number of Requests

By zxi on October 3, 2020

You have k servers numbered from 0 to k-1 that are being used to handle multiple requests simultaneously. Each server has infinite computational capacity but cannot handle more than one request at a time. The requests are assigned to servers according to a specific algorithm:

The i^th (0-indexed) request arrives.
If all servers are busy, the request is dropped (not handled at all).
If the (i % k)^th server is available, assign the request to that server.
Otherwise, assign the request to the next available server (wrapping around the list of servers and starting from 0 if necessary). For example, if the i^th server is busy, try to assign the request to the (i+1)^th server, then the (i+2)^th server, and so on.

You are given a strictly increasing array arrival of positive integers, where arrival[i] represents the arrival time of the i^th request, and another array load, where load[i] represents the load of the i^th request (the time it takes to complete). Your goal is to find the busiest server(s). A server is considered busiest if it handled the most number of requests successfully among all the servers.

Return a list containing the IDs (0-indexed) of the busiest server(s). You may return the IDs in any order.

Example 1:

Input: k = 3, arrival = [1,2,3,4,5], load = [5,2,3,3,3] 
Output: [1] 
Explanation:
All of the servers start out available.
The first 3 requests are handled by the first 3 servers in order.
Request 3 comes in. Server 0 is busy, so it's assigned to the next available server, which is 1.
Request 4 comes in. It cannot be handled since all servers are busy, so it is dropped.
Servers 0 and 2 handled one request each, while server 1 handled two requests. Hence server 1 is the busiest server.

Example 2:

Input: k = 3, arrival = [1,2,3,4], load = [1,2,1,2]
Output: [0]
Explanation:
The first 3 requests are handled by first 3 servers.
Request 3 comes in. It is handled by server 0 since the server is available.
Server 0 handled two requests, while servers 1 and 2 handled one request each. Hence server 0 is the busiest server.

Example 3:

Input: k = 3, arrival = [1,2,3], load = [10,12,11]
Output: [0,1,2]
Explanation: Each server handles a single request, so they are all considered the busiest.

Example 4:

Input: k = 3, arrival = [1,2,3,4,8,9,10], load = [5,2,10,3,1,2,2]
Output: [1]

Example 5:

Input: k = 1, arrival = [1], load = [1]
Output: [0]

Constraints:

1 <= k <= 10⁵
1 <= arrival.length, load.length <= 10⁵
arrival.length == load.length
1 <= arrival[i], load[i] <= 10⁹
arrival is strictly increasing.

Solution: Heap + TreeSet

Use a min heap to store the release time -> server.
Use a treeset to track the current available servers.
For reach request, check whether servers can be released at that time.

Time complexity: O(nlogk)
Space complexity: O(k)

C++

// Author: Huahua

class Solution {

public:

vector<int> busiestServers(int k, vector<int>& arrival, vector<int>& load) {

priority_queue<pair<int, int>, vector<pair<int,int>>, greater<>> q; // {release_time, server}

set<int> servers;

vector<int> requests(k);

for (int i = 0; i < k; ++i)

servers.insert(i);

for (int i = 0; i < arrival.size(); ++i) {

const int t = arrival[i];

const int l = load[i];

// Release servers. O(logk) per pop()

while (!q.empty() && q.top().first <= t) {

servers.insert(q.top().second);

q.pop();

}

// Drop the request.

if (servers.empty()) continue;

// Find first avaiable one O(logk)

auto it = servers.lower_bound(i % k);

if (it == servers.end()) it = begin(servers);

const int idx = *it;

++requests[idx];

servers.erase(it);

q.emplace(t + l, idx);

}

const int max_req = *max_element(begin(requests), end(requests));

vector<int> ans;

for (int i = 0; i < k; ++i)

if (requests[i] == max_req) ans.push_back(i);

return ans;

}

};

花花酱 LeetCode 1603. Design Parking System

By zxi on October 3, 2020

Design a parking system for a parking lot. The parking lot has three kinds of parking spaces: big, medium, and small, with a fixed number of slots for each size.

Implement the ParkingSystem class:

ParkingSystem(int big, int medium, int small) Initializes object of the ParkingSystem class. The number of slots for each parking space are given as part of the constructor.
bool addCar(int carType) Checks whether there is a parking space of carType for the car that wants to get into the parking lot. carType can be of three kinds: big, medium, or small, which are represented by 1, 2, and 3 respectively. A car can only park in a parking space of its carType. If there is no space available, return false, else park the car in that size space and return true.

Example 1:

Input
["ParkingSystem", "addCar", "addCar", "addCar", "addCar"]
[[1, 1, 0], [1], [2], [3], [1]]
Output
[null, true, true, false, false]

Explanation ParkingSystem parkingSystem = new ParkingSystem(1, 1, 0); parkingSystem.addCar(1); // return true because there is 1 available slot for a big car parkingSystem.addCar(2); // return true because there is 1 available slot for a medium car parkingSystem.addCar(3); // return false because there is no available slot for a small car parkingSystem.addCar(1); // return false because there is no available slot for a big car. It is already occupied.

Constraints:

0 <= big, medium, small <= 1000
carType is 1, 2, or 3
At most 1000 calls will be made to addCar

Solution: Simulation

Time complexity: O(1) per addCar call
Space complexity: O(1)

C++

// Author: Huahua

class ParkingSystem {

public:

ParkingSystem(int big, int medium, int small):

slots_{{big, medium, small}} {}

bool addCar(int carType) {

return slots_[carType - 1]-- > 0;

}

private:

vector<int> slots_;

};

Python3

# Author: Huahua

class ParkingSystem:

def __init__(self, big: int, medium: int, small: int):

self.slots = {1: big, 2: medium, 3: small}

def addCar(self, carType: int) -> bool:

if self.slots[carType] == 0: return False

self.slots[carType] -= 1

return True