Leetcode 2586: Count the Number of Vowel Strings in Range
You are given a 0-indexed integer array
nums
. You can rearrange the elements of nums
to any order (including the given order). Define the prefix sum array of nums
as prefix[i] = sum(nums[0] to nums[i])
after rearranging. The score of nums
is the number of positive integers in the prefix
array. Return the maximum score you can achieve by rearranging the elements of nums
.Problem
Approach
Steps
Complexity
Input: The input consists of an integer array `nums`.
Example: For example, `nums = [3, -1, 4, 2, -3, 1, -2]`.
Constraints:
• 1 <= nums.length <= 10^5
• -10^6 <= nums[i] <= 10^6
Output: The output is an integer that represents the maximum score achieved by rearranging the elements of `nums`.
Example: For `nums = [3, -1, 4, 2, -3, 1, -2]`, the output is `5`.
Constraints:
• The result will always be a valid integer.
Goal: The goal is to rearrange the array `nums` to maximize the number of positive integers in the prefix sum array.
Steps:
• 1. Rearrange the array `nums` to maximize positive prefix sums.
• 2. Calculate the prefix sum array and count the number of positive values.
• 3. Return the count as the maximum score.
Goal: The array contains between 1 and 10^5 integers, and each integer is between -10^6 and 10^6.
Steps:
• 1 <= nums.length <= 10^5
• -10^6 <= nums[i] <= 10^6
Assumptions:
• The input array contains valid integers within the given range.
• Input: For `nums = [3, -1, 4, 2, -3, 1, -2]`
• Explanation: The optimal rearrangement is `nums = [3, 4, 2, 1, -1, -2, -3]`. The prefix sum array becomes `prefix = [3, 7, 9, 10, 9, 7, 4]`, giving a score of 5.
Approach: To solve this problem, we need to rearrange the array `nums` to maximize the number of positive prefix sums. A good strategy is to place the positive numbers at the beginning of the array and the negative numbers towards the end.
Observations:
• By placing the positive numbers first, we maximize the possibility of obtaining positive prefix sums.
• This approach helps ensure that the sum remains positive as we calculate the prefix sums.
Steps:
• 1. Separate the positive numbers and negative numbers from the array `nums`.
• 2. Place the positive numbers first in the rearranged array.
• 3. Calculate the prefix sum array and count how many positive numbers appear.
• 4. Return the count as the result.
Empty Inputs:
• The problem guarantees that the array will not be empty.
Large Inputs:
• The solution should be efficient enough to handle up to 10^5 elements in the array.
Special Values:
• If the array contains only negative values, the score will always be 0.
Constraints:
• The length of the array is guaranteed to be within the specified limits.
bool check(char s)
{
return (s=='a' || s=='e'|| s=='o'|| s=='i' || s=='u');
}
int vowelStrings(vector<string>& words, int left, int right) {
int ans=0;
for(int i=left;i<=right;i++)
{
if(check(words[i].front()) && check(words[i].back())) ans++;
}
return ans;
}
1 : Function Declaration
bool check(char s)
This function checks whether the given character 's' is a vowel (either 'a', 'e', 'i', 'o', or 'u').
2 : Return Statement
return (s=='a' || s=='e'|| s=='o'|| s=='i' || s=='u');
This line returns true if the character 's' is a vowel; otherwise, false.
3 : Function Declaration
int vowelStrings(vector<string>& words, int left, int right) {
This function counts the number of words in the 'words' vector from index 'left' to 'right' where both the first and last characters are vowels.
4 : Variable Declaration
int ans=0;
This declares and initializes a variable 'ans' to zero, which will be used to count the words with vowels at both ends.
5 : For Loop
for(int i=left;i<=right;i++)
This loop iterates over the 'words' vector from index 'left' to 'right'.
6 : If Condition
if(check(words[i].front()) && check(words[i].back())) ans++;
This condition checks if both the first and last characters of the current word are vowels. If true, it increments the 'ans' counter.
7 : Return Statement
return ans;
This returns the count of words where both the first and last characters are vowels.
Best Case: O(n)
Average Case: O(n log n)
Worst Case: O(n log n)
Description: The best case occurs when the array is already arranged optimally. The worst case is when we need to sort the array, which takes O(n log n).
Best Case: O(n)
Worst Case: O(n)
Description: The space complexity is O(n) due to the additional storage required for separating positive and negative numbers.
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