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Posts published in “Array”

花花酱 LeetCode 1375. Bulb Switcher III

There is a room with n bulbs, numbered from 1 to n, arranged in a row from left to right. Initially, all the bulbs are turned off.

At moment k (for k from 0 to n - 1), we turn on the light[k] bulb. A bulb change color to blue only if it is on and all the previous bulbs (to the left) are turned on too.

Return the number of moments in which all turned on bulbs are blue.

Example 1:

Input: light = [2,1,3,5,4]
Output: 3
Explanation: All bulbs turned on, are blue at the moment 1, 2 and 4.

Example 2:

Input: light = [3,2,4,1,5]
Output: 2
Explanation: All bulbs turned on, are blue at the moment 3, and 4 (index-0).

Example 3:

Input: light = [4,1,2,3]
Output: 1
Explanation: All bulbs turned on, are blue at the moment 3 (index-0).
Bulb 4th changes to blue at the moment 3.

Example 4:

Input: light = [2,1,4,3,6,5]
Output: 3

Example 5:

Input: light = [1,2,3,4,5,6]
Output: 6

Constraints:

  • n == light.length
  • 1 <= n <= 5 * 10^4
  • light is a permutation of  [1, 2, ..., n]

Solution

Track the right most light l_k, all turned-on lights are blue if and only if the right most one is k, and there are exact k lights on right now.

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

C++

花花酱 LeetCode 1365. How Many Numbers Are Smaller Than the Current Number

Given the array nums, for each nums[i] find out how many numbers in the array are smaller than it. That is, for each nums[i] you have to count the number of valid j's such that j != i and nums[j] < nums[i].

Return the answer in an array.

Example 1:

Input: nums = [8,1,2,2,3]
Output: [4,0,1,1,3]
Explanation: 
For nums[0]=8 there exist four smaller numbers than it (1, 2, 2 and 3). 
For nums[1]=1 does not exist any smaller number than it.
For nums[2]=2 there exist one smaller number than it (1). 
For nums[3]=2 there exist one smaller number than it (1). 
For nums[4]=3 there exist three smaller numbers than it (1, 2 and 2).

Example 2:

Input: nums = [6,5,4,8]
Output: [2,1,0,3]

Example 3:

Input: nums = [7,7,7,7]
Output: [0,0,0,0]

Constraints:

  • 2 <= nums.length <= 500
  • 0 <= nums[i] <= 100

Solution 1: Brute Force

Time complexity: O(n^2)
Space complexity: O(1)

C++

Solution 2: Sort + Binary Search

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

C++

Solution 3: Cumulative frequency

Time complexity: O(n)
Space complexity: O(101)

C++

花花酱 LeetCode 1356. Sort Integers by The Number of 1 Bits

Given an integer array arr. You have to sort the integers in the array in ascending order by the number of 1’s in their binary representation and in case of two or more integers have the same number of 1’s you have to sort them in ascending order.

Return the sorted array.

Example 1:

Input: arr = [0,1,2,3,4,5,6,7,8]
Output: [0,1,2,4,8,3,5,6,7]
Explantion: [0] is the only integer with 0 bits.
[1,2,4,8] all have 1 bit.
[3,5,6] have 2 bits.
[7] has 3 bits.
The sorted array by bits is [0,1,2,4,8,3,5,6,7]

Example 2:

Input: arr = [1024,512,256,128,64,32,16,8,4,2,1]
Output: [1,2,4,8,16,32,64,128,256,512,1024]
Explantion: All integers have 1 bit in the binary representation, you should just sort them in ascending order.

Example 3:

Input: arr = [10000,10000]
Output: [10000,10000]

Example 4:

Input: arr = [2,3,5,7,11,13,17,19]
Output: [2,3,5,17,7,11,13,19]

Example 5:

Input: arr = [10,100,1000,10000]
Output: [10,100,10000,1000]

Constraints:

  • 1 <= arr.length <= 500
  • 0 <= arr[i] <= 10^4

Solution: Sorting

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

C++

Python3

花花酱 LeetCode 1352. Product of the Last K Numbers

Implement the class ProductOfNumbers that supports two methods:

1. add(int num)

  • Adds the number num to the back of the current list of numbers.

2. getProduct(int k)

  • Returns the product of the last k numbers in the current list.
  • You can assume that always the current list has at least k numbers.

At any time, the product of any contiguous sequence of numbers will fit into a single 32-bit integer without overflowing.

Example:

Input
["ProductOfNumbers","add","add","add","add","add","getProduct","getProduct","getProduct","add","getProduct"]
[[],[3],[0],[2],[5],[4],[2],[3],[4],[8],[2]]

Output: [null,null,null,null,null,null,20,40,0,null,32]
Explanation:
ProductOfNumbers productOfNumbers = new ProductOfNumbers();
productOfNumbers.add(3);        // [3] 
productOfNumbers.add(0);        // [3,0] 
productOfNumbers.add(2);        // [3,0,2]
productOfNumbers.add(5);        // [3,0,2,5]
productOfNumbers.add(4);        // [3,0,2,5,4]
productOfNumbers.getProduct(2); // return 20.
The product of the last 2 numbers is 5 * 4 = 20
productOfNumbers.getProduct(3); // return 40. The product of the last 3 numbers is 2 * 5 * 4 = 40 
productOfNumbers.getProduct(4); // return 0. The product of the last 4 numbers is 0 * 2 * 5 * 4 = 0
productOfNumbers.add(8);        // [3,0,2,5,4,8]
productOfNumbers.getProduct(2); // return 32. The product of the last 2 numbers is 4 * 8 = 32  

Constraints:

  • There will be at most 40000 operations considering both add and getProduct.
  • 0 <= num <= 100
  • 1 <= k <= 40000

Solution: Prefix product

Use p[i] to store the prod of a1*a2*…ai
p[i] = ai*p[i-1]
If ai is 0, reset p = [1].
Compare k with the len(p), if k is greater than len(p) which means there is 0 recently, return 0.
otherwise return p[n] / p[n – k – 1]

Time complexity: Add: O(1), getProduct: O(1)
Space complexity: O(n)

C++

花花酱 LeetCode 1351. Count Negative Numbers in a Sorted Matrix

Given a m * n matrix grid which is sorted in non-increasing order both row-wise and column-wise. 

Return the number of negative numbers in grid.

Example 1:

Input: grid = [[4,3,2,-1],[3,2,1,-1],[1,1,-1,-2],[-1,-1,-2,-3]]
Output: 8
Explanation: There are 8 negatives number in the matrix.

Example 2:

Input: grid = [[3,2],[1,0]]
Output: 0

Example 3:

Input: grid = [[1,-1],[-1,-1]]
Output: 3

Example 4:

Input: grid = [[-1]]
Output: 1

Constraints:

  • m == grid.length
  • n == grid[i].length
  • 1 <= m, n <= 100
  • -100 <= grid[i][j] <= 100

Solution 1: Brute Force

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

C++

Solution 2: Find the frontier

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

C++