Posts published in “Hashtable”

花花酱 LeetCode 1604. Alert Using Same Key-Card Three or More Times in a One Hour Period

By zxi on October 3, 2020

Leetcode company workers use key-cards to unlock office doors. Each time a worker uses their key-card, the security system saves the worker’s name and the time when it was used. The system emits an alert if any worker uses the key-card three or more times in a one-hour period.

You are given a list of strings keyName and keyTime where [keyName[i], keyTime[i]] corresponds to a person’s name and the time when their key-card was used in a single day.

Access times are given in the 24-hour time format “HH:MM”, such as "23:51" and "09:49".

Return a list of unique worker names who received an alert for frequent keycard use. Sort the names in ascending order alphabetically.

Notice that "10:00" – "11:00" is considered to be within a one-hour period, while "23:51" – "00:10" is not considered to be within a one-hour period.

Example 1:

Input: keyName = ["daniel","daniel","daniel","luis","luis","luis","luis"], keyTime = ["10:00","10:40","11:00","09:00","11:00","13:00","15:00"]
Output: ["daniel"]
Explanation: "daniel" used the keycard 3 times in a one-hour period ("10:00","10:40", "11:00").

Example 2:

Input: keyName = ["alice","alice","alice","bob","bob","bob","bob"], keyTime = ["12:01","12:00","18:00","21:00","21:20","21:30","23:00"]
Output: ["bob"]
Explanation: "bob" used the keycard 3 times in a one-hour period ("21:00","21:20", "21:30").

Example 3:

Input: keyName = ["john","john","john"], keyTime = ["23:58","23:59","00:01"]
Output: []

Example 4:

Input: keyName = ["leslie","leslie","leslie","clare","clare","clare","clare"], keyTime = ["13:00","13:20","14:00","18:00","18:51","19:30","19:49"]
Output: ["clare","leslie"]

Constraints:

1 <= keyName.length, keyTime.length <= 10⁵
keyName.length == keyTime.length
keyTime are in the format “HH:MM”.
[keyName[i], keyTime[i]] is unique.
1 <= keyName[i].length <= 10
keyName[i] contains only lowercase English letters.

Solution: Hashtable + sorting

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

C++

class Solution {

public:

vector<string> alertNames(vector<string>& keyName, vector<string>& keyTime) {

unordered_map<string, vector<int>> t; // {name -> time}

for (size_t i = 0; i < keyName.size(); ++i) {

const int h = stoi(keyTime[i].substr(0, 2));

const int m = stoi(keyTime[i].substr(3));

t[keyName[i]].push_back(h * 60 + m);

}

vector<string> ans;

for (auto& [name, times] : t) {

sort(begin(times), end(times));

for (size_t i = 2; i < times.size(); ++i)

if (times[i] - times[i - 2] <= 60) {

ans.push_back(name);

break;

}

sort(begin(ans), end(ans));

return ans;

}

};

花花酱 LeetCode 1590. Make Sum Divisible by P

By zxi on September 20, 2020

Given an array of positive integers nums, remove the smallest subarray (possibly empty) such that the sum of the remaining elements is divisible by p. It is not allowed to remove the whole array.

Return the length of the smallest subarray that you need to remove, or -1 if it’s impossible.

A subarray is defined as a contiguous block of elements in the array.

Example 1:

Input: nums = [3,1,4,2], p = 6
Output: 1
Explanation: The sum of the elements in nums is 10, which is not divisible by 6. We can remove the subarray [4], and the sum of the remaining elements is 6, which is divisible by 6.

Example 2:

Input: nums = [6,3,5,2], p = 9
Output: 2
Explanation: We cannot remove a single element to get a sum divisible by 9. The best way is to remove the subarray [5,2], leaving us with [6,3] with sum 9.

Example 3:

Input: nums = [1,2,3], p = 3
Output: 0
Explanation: Here the sum is 6. which is already divisible by 3. Thus we do not need to remove anything.

Example 4:

Input: nums = [1,2,3], p = 7
Output: -1
Explanation: There is no way to remove a subarray in order to get a sum divisible by 7.

Example 5:

Input: nums = [1000000000,1000000000,1000000000], p = 3
Output: 0

Constraints:

1 <= nums.length <= 10⁵
1 <= nums[i] <= 10⁹
1 <= p <= 10⁹

Solution: HashTable + Prefix Sum

Very similar to subarray target sum.

Basically, we are trying to find a shortest subarray that has sum % p equals to r = sum(arr) % p.

We use a hashtable to store the last index of the prefix sum % p and check whether (prefix_sum + p – r) % p exists or not.

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

C++

class Solution {

public:

int minSubarray(vector<int>& nums, int p) {

const int n = nums.size();

int r = accumulate(begin(nums), end(nums), 0LL) % p;

if (r == 0) return 0;

unordered_map<int, int> m{{0, -1}}; // {prefix_sum % p -> last_index}

int s = 0;

int ans = n;

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

s = (s + nums[i]) % p;

auto it = m.find((s + p - r) % p);

if (it != m.end())

ans = min(ans, i - it->second);

m[s] = i;

}

return ans == n ? -1 : ans;

}

};

Python3

class Solution:

def minSubarray(self, nums: List[int], p: int) -> int:

r = sum(nums) % p

if r == 0: return 0

m = {0: -1}

ans = len(nums)

s = 0

for i, x in enumerate(nums):

s = (s + x) % p

t = (s + p - r) % p

if t in m:

ans = min(ans, i - m[t])

m[s] = i

return -1 if ans == len(nums) else ans

花花酱 LeetCode 1583. Count Unhappy Friends

By zxi on September 12, 2020

You are given a list of preferences for n friends, where n is always even.

For each person i, preferences[i] contains a list of friends sorted in the order of preference. In other words, a friend earlier in the list is more preferred than a friend later in the list. Friends in each list are denoted by integers from 0 to n-1.

All the friends are divided into pairs. The pairings are given in a list pairs, where pairs[i] = [x_i, y_i] denotes x_i is paired with y_i and y_i is paired with x_i.

However, this pairing may cause some of the friends to be unhappy. A friend x is unhappy if x is paired with y and there exists a friend u who is paired with v but:

x prefers u over y, and
u prefers x over v.

Return the number of unhappy friends.

Example 1:

Input: n = 4, preferences = [[1, 2, 3], [3, 2, 0], [3, 1, 0], [1, 2, 0]], pairs = [[0, 1], [2, 3]]
Output: 2
Explanation:
Friend 1 is unhappy because:
- 1 is paired with 0 but prefers 3 over 0, and
- 3 prefers 1 over 2.
Friend 3 is unhappy because:
- 3 is paired with 2 but prefers 1 over 2, and
- 1 prefers 3 over 0.
Friends 0 and 2 are happy.

Example 2:

Input: n = 2, preferences = [[1], [0]], pairs = [[1, 0]]
Output: 0
Explanation: Both friends 0 and 1 are happy.

Example 3:

Input: n = 4, preferences = [[1, 3, 2], [2, 3, 0], [1, 3, 0], [0, 2, 1]], pairs = [[1, 3], [0, 2]]
Output: 4

Constraints:

2 <= n <= 500
n is even.
preferences.length == n
preferences[i].length == n - 1
0 <= preferences[i][j] <= n - 1
preferences[i] does not contain i.
All values in preferences[i] are unique.
pairs.length == n/2
pairs[i].length == 2
x_i != y_i
0 <= x_i, y_i <= n - 1
Each person is contained in exactly one pair.

Solution: HashTable

Put the order in a map {x -> {y, order}}, since this is dense, we use can 2D array instead of hasthable which is much faster.

Then for each pair, we just need to check every other pair and compare their orders.

Time complexity: O(n^2)
Space complexity: O(n^2)

C++

class Solution {

public:

int unhappyFriends(int n, vector<vector<int>>& preferences, vector<vector<int>>& pairs) {

vector<int> p(n);

for (const auto& pair : pairs) {

p[pair[0]] = pair[1];

p[pair[1]] = pair[0];

}

vector<vector<int>> orders(n, vector<int>(n));

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

for (int i = 0; i < preferences[x].size(); ++i)

orders[x][preferences[x][i]] = i;

int ans = 0;

for (int x = 0; x < n; ++x) {

const int y = p[x];

bool found = false;

for (int u = 0; u < n && !found; ++u) {

if (u == x || u == y) continue;

const int v = p[u];

found |= orders[x][u] < orders[x][y] && orders[u][x] < orders[u][v];

}

if (found) ++ans;

}

return ans;

}

};

花花酱 LeetCode 1577. Number of Ways Where Square of Number Is Equal to Product of Two Numbers

By zxi on September 5, 2020

Given two arrays of integers nums1 and nums2, return the number of triplets formed (type 1 and type 2) under the following rules:

Type 1: Triplet (i, j, k) if nums1[i]² == nums2[j] * nums2[k] where 0 <= i < nums1.length and 0 <= j < k < nums2.length.
Type 2: Triplet (i, j, k) if nums2[i]² == nums1[j] * nums1[k] where 0 <= i < nums2.length and 0 <= j < k < nums1.length.

Example 1:

Input: nums1 = [7,4], nums2 = [5,2,8,9]
Output: 1
Explanation: Type 1: (1,1,2), nums1[1]^2 = nums2[1] * nums2[2]. (4^2 = 2 * 8).

Example 2:

Input: nums1 = [1,1], nums2 = [1,1,1]
Output: 9
Explanation: All Triplets are valid, because 1^2 = 1 * 1.
Type 1: (0,0,1), (0,0,2), (0,1,2), (1,0,1), (1,0,2), (1,1,2).  nums1[i]^2 = nums2[j] * nums2[k].
Type 2: (0,0,1), (1,0,1), (2,0,1). nums2[i]^2 = nums1[j] * nums1[k].

Example 3:

Input: nums1 = [7,7,8,3], nums2 = [1,2,9,7]
Output: 2
Explanation: There are 2 valid triplets.
Type 1: (3,0,2).  nums1[3]^2 = nums2[0] * nums2[2].
Type 2: (3,0,1).  nums2[3]^2 = nums1[0] * nums1[1].

Example 4:

Input: nums1 = [4,7,9,11,23], nums2 = [3,5,1024,12,18]
Output: 0
Explanation: There are no valid triplets.

Constraints:

1 <= nums1.length, nums2.length <= 1000
1 <= nums1[i], nums2[i] <= 10^5

Solution: Hashtable

For each number y in the second array, count its frequency.

For each number x in the first, if x * x % y == 0, let r = x * x / y
if r == y: ans += f[y] * f[y-1]
else ans += f[y] * f[r]

Final ans /= 2

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

C++

// Author: Huahua

class Solution {

public:

int numTriplets(vector<int>& nums1, vector<int>& nums2) {

return solve(nums1, nums2) + solve(nums2, nums1);

}

private:

int solve(vector<int>& nums1, vector<int>& nums2) {

int ans = 0;

unordered_map<int, int> f;

for (int y : nums2) ++f[y];

for (long x : nums1)

for (const auto& [y, c] : f) {

long r = x * x / y;

if (x * x % y || !f.count(r)) continue;

if (r == y) ans += c * (c - 1);

else ans += c * f[r];

}

return ans / 2;

}

};

花花酱 LeetCode 1562. Find Latest Group of Size M

By zxi on August 23, 2020

Given an array arr that represents a permutation of numbers from 1 to n. You have a binary string of size n that initially has all its bits set to zero.

At each step i (assuming both the binary string and arr are 1-indexed) from 1 to n, the bit at position arr[i] is set to 1. You are given an integer m and you need to find the latest step at which there exists a group of ones of length m. A group of ones is a contiguous substring of 1s such that it cannot be extended in either direction.

Return the latest step at which there exists a group of ones of length exactly m. If no such group exists, return -1.

Example 1:

Input: arr = [3,5,1,2,4], m = 1
Output: 4
Explanation:
Step 1: "00100", groups: ["1"]
Step 2: "00101", groups: ["1", "1"]
Step 3: "10101", groups: ["1", "1", "1"]
Step 4: "11101", groups: ["111", "1"]
Step 5: "11111", groups: ["11111"]
The latest step at which there exists a group of size 1 is step 4.

Example 2:

Input: arr = [3,1,5,4,2], m = 2
Output: -1
Explanation:
Step 1: "00100", groups: ["1"]
Step 2: "10100", groups: ["1", "1"]
Step 3: "10101", groups: ["1", "1", "1"]
Step 4: "10111", groups: ["1", "111"]
Step 5: "11111", groups: ["11111"]
No group of size 2 exists during any step.

Example 3:

Input: arr = [1], m = 1
Output: 1

Example 4:

Input: arr = [2,1], m = 2
Output: 2

Constraints:

n == arr.length
1 <= n <= 10^5
1 <= arr[i] <= n
All integers in arr are distinct.
1 <= m <= arr.length

Solution: Hashtable

Similar to LC 128

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

C++

// Author: Huahua

class Solution {

public:

int findLatestStep(vector<int>& arr, int m) {

const int n = arr.size();

vector<int> len(n + 2);

vector<int> counts(n + 2);

int ans = -1;

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

const int x = arr[i];

const int l = len[x - 1];

const int r = len[x + 1];

const int t = 1 + l + r;

len[x - l] = len[x + r] = t;

--counts[l];

--counts[r];

++counts[t];

if (counts[m]) ans = i + 1;

}

return ans;

}

};