Posts tagged as “array”

花花酱 LeetCode 2134. Minimum Swaps to Group All 1’s Together II

By zxi on January 17, 2022

A swap is defined as taking two distinct positions in an array and swapping the values in them.

A circular array is defined as an array where we consider the first element and the last element to be adjacent.

Given a binary circular array nums, return the minimum number of swaps required to group all 1‘s present in the array together at any location.

Example 1:

Input: nums = [0,1,0,1,1,0,0]
Output: 1
Explanation: Here are a few of the ways to group all the 1's together:
[0,0,1,1,1,0,0] using 1 swap.
[0,1,1,1,0,0,0] using 1 swap.
[1,1,0,0,0,0,1] using 2 swaps (using the circular property of the array).
There is no way to group all 1's together with 0 swaps.
Thus, the minimum number of swaps required is 1.

Example 2:

Input: nums = [0,1,1,1,0,0,1,1,0]
Output: 2
Explanation: Here are a few of the ways to group all the 1's together:
[1,1,1,0,0,0,0,1,1] using 2 swaps (using the circular property of the array).
[1,1,1,1,1,0,0,0,0] using 2 swaps.
There is no way to group all 1's together with 0 or 1 swaps.
Thus, the minimum number of swaps required is 2.

Example 3:

Input: nums = [1,1,0,0,1]
Output: 0
Explanation: All the 1's are already grouped together due to the circular property of the array.
Thus, the minimum number of swaps required is 0.

Constraints:

1 <= nums.length <= 10⁵
nums[i] is either 0 or 1.

Solution: Sliding Window

Step 1: Count how many ones are there in the array. Assume it’s K.
Step 2: For each window of size k, count how many ones in the window, we have to swap 0s out with 1s to fill the window. ans = min(ans, k – ones).

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

C++

// Author: Huahua

class Solution {

public:

int minSwaps(vector<int>& nums) {

const int n = nums.size();

const int k = accumulate(begin(nums), end(nums), 0);

int ans = INT_MAX;

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

if (i >= k) cur -= nums[(i - k + n) % n];

cur += nums[i % n];

ans = min(ans, k - cur);

}

return ans;

}

};

花花酱 LeetCode 1995. Count Special Quadruplets

By zxi on December 31, 2021

Given a 0-indexed integer array nums, return the number of distinct quadruplets (a, b, c, d) such that:

nums[a] + nums[b] + nums[c] == nums[d], and
a < b < c < d

Example 1:

Input: nums = [1,2,3,6]
Output: 1
Explanation: The only quadruplet that satisfies the requirement is (0, 1, 2, 3) because 1 + 2 + 3 == 6.

Example 2:

Input: nums = [3,3,6,4,5]
Output: 0
Explanation: There are no such quadruplets in [3,3,6,4,5].

Example 3:

Input: nums = [1,1,1,3,5]
Output: 4
Explanation: The 4 quadruplets that satisfy the requirement are:
- (0, 1, 2, 3): 1 + 1 + 1 == 3
- (0, 1, 3, 4): 1 + 1 + 3 == 5
- (0, 2, 3, 4): 1 + 1 + 3 == 5
- (1, 2, 3, 4): 1 + 1 + 3 == 5

Constraints:

4 <= nums.length <= 50
1 <= nums[i] <= 100

Solution 1: Brute force (224ms)

Enumerate a, b, c, d.

Time complexity: O(C(n, 4)) = O(n⁴/24)
Space complexity: O(1)

C++

// Author: Huahua

class Solution {

public:

int countQuadruplets(vector<int>& nums) {

const int n = nums.size();

int ans = 0;

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

for (int b = a + 1; b < n; ++b)

for (int c = b + 1; c < n; ++c)

for (int d = c + 1; d < n; ++d)

ans += nums[a] + nums[b] + nums[c] == nums[d];

return ans;

}

};

Solution 2: Static frequency table + binary search (39ms)

For each element, we store its indices (sorted).

Given a, b, c, target t = nums[a] + nums[b] + nums[c], we check the hashtable and use binary search to find how many times it occurred after index c.

Time complexity: O(n³/6*logn)
Space complexity: O(n)

C++

// Author: Huahua

class Solution {

public:

int countQuadruplets(vector<int>& nums) {

constexpr int kMax = 100;

const int n = nums.size();

int ans = 0;

vector<vector<int>> m(kMax + 1);

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

m[nums[i]].push_back(i);

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

for (int b = a + 1; b < n; ++b)

for (int c = b + 1; c < n; ++c) {

const int t = nums[a] + nums[b] + nums[c];

if (t > kMax) continue;

ans += end(m[t]) - lower_bound(begin(m[t]), end(m[t]), c + 1);

}

return ans;

}

};

Solution 3: Dynamic frequency table (29ms)

Similar to 花花酱 LeetCode 1. Two Sum, we dynamically add elements (from right to left) into the hashtable.

Time complexity: O(n³/6)
Space complexity: O(n)

C++

// Author: Huahua

class Solution {

public:

int countQuadruplets(vector<int>& nums) {

constexpr int kMax = 100;

const int n = nums.size();

int ans = 0;

vector<int> m(kMax + 1);

// for every c we had seen, we can use it as target (nums[d]).

for (int c = n - 1; c >= 0; ++m[nums[c--]])

for (int a = 0; a < c; ++a)

for (int b = a + 1; b < c; ++b) {

const int t = nums[a] + nums[b] + nums[c];

if (t > kMax) continue;

ans += m[t];

}

return ans;

}

};

花花酱 LeetCode 1991. Find the Middle Index in Array

By zxi on December 31, 2021

Given a 0-indexed integer array nums, find the leftmost middleIndex (i.e., the smallest amongst all the possible ones).

A middleIndex is an index where nums[0] + nums[1] + ... + nums[middleIndex-1] == nums[middleIndex+1] + nums[middleIndex+2] + ... + nums[nums.length-1].

If middleIndex == 0, the left side sum is considered to be 0. Similarly, if middleIndex == nums.length - 1, the right side sum is considered to be 0.

Return the leftmost middleIndex that satisfies the condition, or -1 if there is no such index.

Example 1:

Input: nums = [2,3,-1,8,4]
Output: 3
Explanation: The sum of the numbers before index 3 is: 2 + 3 + -1 = 4
The sum of the numbers after index 3 is: 4 = 4

Example 2:

Input: nums = [1,-1,4]
Output: 2
Explanation: The sum of the numbers before index 2 is: 1 + -1 = 0
The sum of the numbers after index 2 is: 0

Example 3:

Input: nums = [2,5]
Output: -1
Explanation: There is no valid middleIndex.

Constraints:

1 <= nums.length <= 100
-1000 <= nums[i] <= 1000

Solution: Pre-compute + prefix sum

Pre-compute the sum of entire array. We scan the array and accumulate prefix sum and we can compute the sum of the rest of array.

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

C++

// Author: Huahua

class Solution {

public:

int findMiddleIndex(vector<int>& nums) {

int sum = accumulate(begin(nums), end(nums), 0);

for (int i = 0, cur = 0; i < nums.size(); ++i) {

if (cur == sum - cur - nums[i]) return i;

cur += nums[i];

}

return -1;

}

};

花花酱 LeetCode 1985. Find the Kth Largest Integer in the Array

By zxi on December 31, 2021

You are given an array of strings nums and an integer k. Each string in nums represents an integer without leading zeros.

Return the string that represents the k^th largest integer in nums.

Note: Duplicate numbers should be counted distinctly. For example, if nums is ["1","2","2"], "2" is the first largest integer, "2" is the second-largest integer, and "1" is the third-largest integer.

Example 1:

Input: nums = ["3","6","7","10"], k = 4
Output: "3"
Explanation:
The numbers in nums sorted in non-decreasing order are ["3","6","7","10"].
The 4^th largest integer in nums is "3".

Example 2:

Input: nums = ["2","21","12","1"], k = 3
Output: "2"
Explanation:
The numbers in nums sorted in non-decreasing order are ["1","2","12","21"].
The 3^rd largest integer in nums is "2".

Example 3:

Input: nums = ["0","0"], k = 2
Output: "0"
Explanation:
The numbers in nums sorted in non-decreasing order are ["0","0"].
The 2^nd largest integer in nums is "0".

Constraints:

1 <= k <= nums.length <= 10⁴
1 <= nums[i].length <= 100
nums[i] consists of only digits.
nums[i] will not have any leading zeros.

Solution: nth_element / quick selection

Use std::nth_element to find the k-th largest element. When comparing two strings, compare their lengths first and compare their content if they have the same length.

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

C++

// Author: Huahua

class Solution {

public:

string kthLargestNumber(vector<string>& nums, int k) {

nth_element(begin(nums), begin(nums) + k - 1, end(nums), [](const auto& a, const auto& b) {

return a.length() == b.length() ? a > b : a.length() > b.length();

});

return nums[k - 1];

}

};

花花酱 LeetCode 1929. Concatenation of Array

By zxi on December 30, 2021

Given an integer array nums of length n, you want to create an array ans of length 2n where ans[i] == nums[i] and ans[i + n] == nums[i] for 0 <= i < n (0-indexed).

Specifically, ans is the concatenation of two nums arrays.

Return the array ans.

Example 1:

Input: nums = [1,2,1]
Output: [1,2,1,1,2,1]
Explanation: The array ans is formed as follows:
- ans = [nums[0],nums[1],nums[2],nums[0],nums[1],nums[2]]
- ans = [1,2,1,1,2,1]

Example 2:

Input: nums = [1,3,2,1]
Output: [1,3,2,1,1,3,2,1]
Explanation: The array ans is formed as follows:
- ans = [nums[0],nums[1],nums[2],nums[3],nums[0],nums[1],nums[2],nums[3]]
- ans = [1,3,2,1,1,3,2,1]

Constraints:

n == nums.length
1 <= n <= 1000
1 <= nums[i] <= 1000

Solution: Pre-allocation

Pre-allocate an array of length 2 * n.
ans[i] = nums[i % n]

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

C++

// Author: Huahua

class Solution {

public:

vector<int> getConcatenation(vector<int>& nums) {

const int n = nums.size();

vector<int> ans(2 * n);

for (int i = 0; i < 2 * n; ++i)

ans[i] = nums[i % n];

return ans;

}

};