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花花酱 LeetCode 1589. Maximum Sum Obtained of Any Permutation

We have an array of integers, nums, and an array of requests where requests[i] = [starti, endi]. The ith request asks for the sum of nums[starti] + nums[starti + 1] + ... + nums[endi - 1] + nums[endi]. Both starti and endi are 0-indexed.

Return the maximum total sum of all requests among all permutations of nums.

Since the answer may be too large, return it modulo 109 + 7.

Example 1:

Input: nums = [1,2,3,4,5], requests = [[1,3],[0,1]]
Output: 19
Explanation: One permutation of nums is [2,1,3,4,5] with the following result: 
requests[0] -> nums[1] + nums[2] + nums[3] = 1 + 3 + 4 = 8
requests[1] -> nums[0] + nums[1] = 2 + 1 = 3
Total sum: 8 + 3 = 11.
A permutation with a higher total sum is [3,5,4,2,1] with the following result:
requests[0] -> nums[1] + nums[2] + nums[3] = 5 + 4 + 2 = 11
requests[1] -> nums[0] + nums[1] = 3 + 5  = 8
Total sum: 11 + 8 = 19, which is the best that you can do.

Example 2:

Input: nums = [1,2,3,4,5,6], requests = [[0,1]]
Output: 11
Explanation: A permutation with the max total sum is [6,5,4,3,2,1] with request sums [11].

Example 3:

Input: nums = [1,2,3,4,5,10], requests = [[0,2],[1,3],[1,1]]
Output: 47
Explanation: A permutation with the max total sum is [4,10,5,3,2,1] with request sums [19,18,10].

Constraints:

  • n == nums.length
  • 1 <= n <= 105
  • 0 <= nums[i] <= 105
  • 1 <= requests.length <= 105
  • requests[i].length == 2
  • 0 <= starti <= endi < n

Solution: Greedy + Sweep line

Sort the numbers, and sort the frequency of each index, it’s easy to show largest number with largest frequency gives us max sum.

ans = sum(nums[i] * freq[i])

We can use sweep line to compute the frequency of each index in O(n) time and space.

For each request [start, end] : ++freq[start], –freq[end + 1]

Then the prefix sum of freq array is the frequency for each index.

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

C++

花花酱 LeetCode 1588. Sum of All Odd Length Subarrays

Given an array of positive integers arr, calculate the sum of all possible odd-length subarrays.

A subarray is a contiguous subsequence of the array.

Return the sum of all odd-length subarrays of arr.

Example 1:

Input: arr = [1,4,2,5,3]
Output: 58
Explanation: The odd-length subarrays of arr and their sums are:
[1] = 1
[4] = 4
[2] = 2
[5] = 5
[3] = 3
[1,4,2] = 7
[4,2,5] = 11
[2,5,3] = 10
[1,4,2,5,3] = 15
If we add all these together we get 1 + 4 + 2 + 5 + 3 + 7 + 11 + 10 + 15 = 58

Example 2:

Input: arr = [1,2]
Output: 3
Explanation: There are only 2 subarrays of odd length, [1] and [2]. Their sum is 3.

Example 3:

Input: arr = [10,11,12]
Output: 66

Constraints:

  • 1 <= arr.length <= 100
  • 1 <= arr[i] <= 1000

Solution 0: Brute Force

Enumerate all odd length subarrys: O(n^2), each take O(n) to compute the sum.

Total time complexity: O(n^3)
Space complexity: O(1)

Solution 1: Running Prefix Sum

Reduce the time complexity to O(n^2)

C++

Solution 2: Math

Count how many times arr[i] can be in of an odd length subarray
we chose the start, which can be 0, 1, 2, … i, i + 1 choices
we chose the end, which can be i, i + 1, … n – 1, n – i choices
Among those 1/2 are odd length.
So there will be upper((i + 1) * (n – i) / 2) odd length subarrays contain arr[i]

ans = sum(((i + 1) * (n – i) + 1) / 2 * arr[i] for in range(n))

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

C++

花花酱 LeetCode 1585. Check If String Is Transformable With Substring Sort Operations

Given two strings s and t, you want to transform string s into string t using the following operation any number of times:

  • Choose a non-empty substring in s and sort it in-place so the characters are in ascending order.

For example, applying the operation on the underlined substring in "14234" results in "12344".

Return true if it is possible to transform string s into string t. Otherwise, return false.

substring is a contiguous sequence of characters within a string.

Example 1:

Input: s = "84532", t = "34852"
Output: true
Explanation: You can transform s into t using the following sort operations:
"84532" (from index 2 to 3) -> "84352"
"84352" (from index 0 to 2) -> "34852"

Example 2:

Input: s = "34521", t = "23415"
Output: true
Explanation: You can transform s into t using the following sort operations:
"34521" -> "23451"
"23451" -> "23415"

Example 3:

Input: s = "12345", t = "12435"
Output: false

Example 4:

Input: s = "1", t = "2"
Output: false

Constraints:

  • s.length == t.length
  • 1 <= s.length <= 105
  • s and t only contain digits from '0' to '9'.

Solution: Queue

We can move a smaller digit from right to left by sorting two adjacent digits.
e.g. 18572 -> 18527 -> 18257 -> 12857, but we can not move a larger to the left of a smaller one.

Thus, for each digit in the target string, we find the first occurrence of it in s, and try to move it to the front by checking if there is any smaller one in front of it.

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

C++

Python3

花花酱 LeetCode 1584. Min Cost to Connect All Points

You are given an array points representing integer coordinates of some points on a 2D-plane, where points[i] = [xi, yi].

The cost of connecting two points [xi, yi] and [xj, yj] is the manhattan distance between them: |xi - xj| + |yi - yj|, where |val| denotes the absolute value of val.

Return the minimum cost to make all points connected. All points are connected if there is exactly one simple path between any two points.

Example 1:

Input: points = [[0,0],[2,2],[3,10],[5,2],[7,0]]
Output: 20
Explanation:

We can connect the points as shown above to get the minimum cost of 20.
Notice that there is a unique path between every pair of points.

Example 2:

Input: points = [[3,12],[-2,5],[-4,1]]
Output: 18

Example 3:

Input: points = [[0,0],[1,1],[1,0],[-1,1]]
Output: 4

Example 4:

Input: points = [[-1000000,-1000000],[1000000,1000000]]
Output: 4000000

Example 5:

Input: points = [[0,0]]
Output: 0

Constraints:

  • 1 <= points.length <= 1000
  • -106 <= xi, yi <= 106
  • All pairs (xi, yi) are distinct.

Solution: Minimum Spanning Tree

Kruskal’s algorithm
Time complexity: O(n^2logn)
Space complexity: O(n^2)
using vector of vector, array, pair of pair, or tuple might lead to TLE…

C++

Prim’s Algorithm
ds[i] := min distance from i to ANY nodes in the tree.

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

C++

花花酱 LeetCode 1583. Count Unhappy Friends

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

For each person ipreferences[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] = [xi, yi] denotes xi is paired with yi and yi is paired with xi.

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
  • xi != yi
  • 0 <= xi, yi <= 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++