Posts tagged as “array”

花花酱 LeetCode 2111. Minimum Operations to Make the Array K-Increasing

By zxi on December 22, 2021

You are given a 0-indexed array arr consisting of n positive integers, and a positive integer k.

The array arr is called K-increasing if arr[i-k] <= arr[i] holds for every index i, where k <= i <= n-1.

For example, arr = [4, 1, 5, 2, 6, 2] is K-increasing for k = 2 because:
- arr[0] <= arr[2] (4 <= 5)
- arr[1] <= arr[3] (1 <= 2)
- arr[2] <= arr[4] (5 <= 6)
- arr[3] <= arr[5] (2 <= 2)
However, the same arr is not K-increasing for k = 1 (because arr[0] > arr[1]) or k = 3 (because arr[0] > arr[3]).

In one operation, you can choose an index i and change arr[i] into any positive integer.

Return the minimum number of operations required to make the array K-increasing for the given k.

Example 1:

Input: arr = [5,4,3,2,1], k = 1
Output: 4
Explanation:
For k = 1, the resultant array has to be non-decreasing.
Some of the K-increasing arrays that can be formed are [5,6,7,8,9], [1,1,1,1,1], [2,2,3,4,4]. All of them require 4 operations.
It is suboptimal to change the array to, for example, [6,7,8,9,10] because it would take 5 operations.
It can be shown that we cannot make the array K-increasing in less than 4 operations.

Example 2:

Input: arr = [4,1,5,2,6,2], k = 2
Output: 0
Explanation:
This is the same example as the one in the problem description.
Here, for every index i where 2 <= i <= 5, arr[i-2] <=arr[i].
Since the given array is already K-increasing, we do not need to perform any operations.

Example 3:

Input: arr = [4,1,5,2,6,2], k = 3
Output: 2
Explanation:
Indices 3 and 5 are the only ones not satisfying arr[i-3] <= arr[i] for 3 <= i <= 5.
One of the ways we can make the array K-increasing is by changing arr[3] to 4 and arr[5] to 5.
The array will now be [4,1,5,4,6,5].
Note that there can be other ways to make the array K-increasing, but none of them require less than 2 operations.

Constraints:

1 <= arr.length <= 10⁵
1 <= arr[i], k <= arr.length

Solution: Longest increasing subsequence

if k = 1, we need to modify the following arrays
1. [a[0], a[1], a[2], …]
if k = 2, we need to modify the following arrays
1. [a[0], a[2], a[4], …]
2. [a[1], a[3], a[5], …]
if k = 3, we need to modify the following arrays
1. [a[0], a[3], a[6], …]
2. [a[1], a[4], a[7], …]
3. [a[2], a[5], a[8], …]
…

These arrays are independent of each other, we just need to find LIS of it, # ops = len(arr) – LIS(arr).
Ans = sum(len(arr_i) – LIS(arr_i)) 1 <= i <= k

Reference: 花花酱 LeetCode 300. Longest Increasing Subsequence

Time complexity: O(k * (n/k)* log(n/k)) = O(n * log(n/k))
Space complexity: O(n/k)

C++

// Author: Huahua

class Solution {

public:

int kIncreasing(vector<int>& arr, int k) {

auto LIS = [](const vector<int>& nums) {

vector<int> lis;

for (int x : nums)

if (lis.empty() || lis.back() <= x)

lis.push_back(x);

else

*upper_bound(begin(lis), end(lis), x) = x;

return lis.size();

};

const int n = arr.size();

int ans = 0;

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

vector<int> cur;

for (int j = i; j < n; j += k)

cur.push_back(arr[j]);

ans += cur.size() - LIS(cur);

}

return ans;

}

};

Python3

# Author: Huahua

class Solution:

def kIncreasing(self, arr: List[int], k: int) -> int:

def LIS(arr: List[int]) -> int:

lis = []

for x in arr:

if not lis or lis[-1] <= x:

lis.append(x)

else:

lis[bisect_right(lis, x)] = x

return len(lis)

return sum(len(arr[i::k]) - LIS(arr[i::k]) for i in range(k))

花花酱 LeetCode 2105. Watering Plants II

By zxi on December 12, 2021

Problem

Solution: Simulation w/ Two Pointers

Simulate the watering process.

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

C++

// Author: Huahua

class Solution {

public:

int minimumRefill(vector<int>& plants, int capacityA, int capacityB) {

const int n = plants.size();

int ans = 0;

for (int l = 0, r = n - 1, A = capacityA, B = capacityB; l <= r; ++l, --r) {

if (l == r)

return ans += max(A, B) < plants[l];

if ((A -= plants[l]) < 0)

A = capacityA - plants[l], ++ans;

if ((B -= plants[r]) < 0)

B = capacityB - plants[r], ++ans;

}

return ans;

}

};

花花酱 LeetCode 2104. Sum of Subarray Ranges

By zxi on December 12, 2021

Problem

Solution 0: Brute force [TLE]

Enumerate all subarrays, for each one, find min and max.

Time complexity: O(n³)
Space complexity: O(1)

Solution 1: Prefix min/max

We can use prefix technique to extend the array while keep tracking the min/max of the subarray.

Time complexity: O(n²)
Space complexity: O(1)

C++

// Author: Huahua

class Solution {

public:

long long subArrayRanges(vector<int>& nums) {

const int n = nums.size();

long long ans = 0;

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

int lo = nums[i];

int hi = nums[i];

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

lo = min(lo, nums[j]);

hi = max(hi, nums[j]);

ans += (hi - lo);

}

return ans;

}

};

Solution 2: Monotonic stack

This problem can be reduced to 花花酱 LeetCode 907. Sum of Subarray Minimums

Just need to run twice one for sum of mins and another for sum of maxs.

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

C++

// Author: Huahua

class Solution {

public:

long long subArrayRanges(vector<int>& nums) {

const int n = nums.size();

auto sumOf = [&](function<bool(int, int)> op) {

long long ans = 0;

stack<int> s;

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

while (!s.empty() and (i == n or op(nums[s.top()], nums[i]))) {

long long k = s.top(); s.pop();

long long j = s.empty() ? -1 : s.top();

ans += nums[k] * (i - k) * (k - j);

}

s.push(i);

}

return ans;

};

return sumOf(less<int>()) - sumOf(greater<int>());

}

};

花花酱 LeetCode 2100. Find Good Days to Rob the Bank

By zxi on December 12, 2021

You and a gang of thieves are planning on robbing a bank. You are given a 0-indexed integer array security, where security[i] is the number of guards on duty on the i^th day. The days are numbered starting from 0. You are also given an integer time.

The i^th day is a good day to rob the bank if:

There are at least time days before and after the i^th day,
The number of guards at the bank for the time days before i are non-increasing, and
The number of guards at the bank for the time days after i are non-decreasing.

More formally, this means day i is a good day to rob the bank if and only if security[i - time] >= security[i - time + 1] >= ... >= security[i] <= ... <= security[i + time - 1] <= security[i + time].

Return a list of all days (0-indexed) that are good days to rob the bank. The order that the days are returned in does not matter.

Example 1:

Input: security = [5,3,3,3,5,6,2], time = 2
Output: [2,3]
Explanation:
On day 2, we have security[0] >= security[1] >= security[2] <= security[3] <= security[4].
On day 3, we have security[1] >= security[2] >= security[3] <= security[4] <= security[5].
No other days satisfy this condition, so days 2 and 3 are the only good days to rob the bank.

Example 2:

Input: security = [1,1,1,1,1], time = 0
Output: [0,1,2,3,4]
Explanation:
Since time equals 0, every day is a good day to rob the bank, so return every day.

Example 3:

Input: security = [1,2,3,4,5,6], time = 2
Output: []
Explanation:
No day has 2 days before it that have a non-increasing number of guards.
Thus, no day is a good day to rob the bank, so return an empty list.

Example 4:

Input: security = [1], time = 5
Output: []
Explanation:
No day has 5 days before and after it.
Thus, no day is a good day to rob the bank, so return an empty list.

Constraints:

1 <= security.length <= 10⁵
0 <= security[i], time <= 10⁵

Solution: Pre-Processing

Pre-compute the non-increasing days at days[i] and the non-decreasing days at days[i] using prefix and suffix arrays.

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

C++

// Author: Huahua

class Solution {

public:

vector<int> goodDaysToRobBank(vector<int>& security, int time) {

const int n = security.size();

vector<int> before(n);

vector<int> after(n);

for (int i = 1; i < n; ++i)

before[i] = security[i - 1] >= security[i] ? before[i - 1] + 1 : 0;

for (int i = n - 2; i >= 0; --i)

after[i] = security[i + 1] >= security[i] ? after[i + 1] + 1 : 0;

vector<int> ans;

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

if (before[i] >= time && after[i] >= time)

ans.push_back(i);

return ans;

}

};

花花酱 LeetCode 81. Search in Rotated Sorted Array II

By zxi on November 29, 2021

There is an integer array nums sorted in non-decreasing order (not necessarily with distinct values).

Before being passed to your function, nums is rotated at an unknown pivot index k (0 <= k < nums.length) such that the resulting array is [nums[k], nums[k+1], ..., nums[n-1], nums[0], nums[1], ..., nums[k-1]] (0-indexed). For example, [0,1,2,4,4,4,5,6,6,7] might be rotated at pivot index 5 and become [4,5,6,6,7,0,1,2,4,4].

Given the array nums after the rotation and an integer target, return true if target is in nums, or false if it is not in nums.

You must decrease the overall operation steps as much as possible.

Example 1:

Input: nums = [2,5,6,0,0,1,2], target = 0
Output: true

Example 2:

Input: nums = [2,5,6,0,0,1,2], target = 3
Output: false

Constraints:

1 <= nums.length <= 5000
-10⁴ <= nums[i] <= 10⁴
nums is guaranteed to be rotated at some pivot.
-10⁴ <= target <= 10⁴

Solution: Binary search or divide and conquer

If current range is ordered, use binary search, Otherwise, divide and conquer.

Time complexity: O(logn) best, O(n) worst
Space complexity: O(logn)

C++

// Author: Huahua

class Solution {

public:

bool search(vector<int>& A, int target) {

return search(A, 0, A.size() - 1, target);

}

private:

bool search(vector<int>& A, int l, int r, int target) {

if (l > r) return 0;

if (l == r) return target == A[l];

int mid = l + (r - l) / 2;

if (A[l] < A[mid] && A[mid] < A[r])

return (target <= A[mid]) ? search(A, l, mid, target) : search(A, mid + 1, r, target);

else

return search(A, l, mid, target) || search(A, mid + 1, r, target);

}

};