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Posts published in “Binary Search”

花花酱 LeetCode 34. Find First and Last Position of Element in Sorted Array

Given an array of integers nums sorted in ascending order, find the starting and ending position of a given target value.

Your algorithm’s runtime complexity must be in the order of O(log n).

If the target is not found in the array, return [-1, -1].

Example 1:

Input: nums = [5,7,7,8,8,10], target = 8
Output: [3,4]

Example 2:

Input: nums = [5,7,7,8,8,10], target = 6
Output: [-1,-1]

Solution: Binary Search

Basically this problem asks you to implement lower_bound and upper_bound using binary search.

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

C++

花花酱 LeetCode 1014. Capacity To Ship Packages Within D Days

A conveyor belt has packages that must be shipped from one port to another within D days.

The i-th package on the conveyor belt has a weight of weights[i].  Each day, we load the ship with packages on the conveyor belt (in the order given by weights). We may not load more weight than the maximum weight capacity of the ship.

Return the least weight capacity of the ship that will result in all the packages on the conveyor belt being shipped within D days.

Example 1:

Example 2:

Example 3:

Note:

  1. 1 <= D <= weights.length <= 50000
  2. 1 <= weights[i] <= 500

Solution: Binary Search

Find the smallest capacity such that can finish in D days.

Time complexity: O(n * log(sum(weights))
Space complexity: O(1)

C++

花花酱 LeetCode 74. Search a 2D Matrix

Write an efficient algorithm that searches for a value in an m x n matrix. This matrix has the following properties:

  • Integers in each row are sorted from left to right.
  • The first integer of each row is greater than the last integer of the previous row.

Example 1:

Example 2:

Solution: Binary Search

Treat the 2D array as a 1D array. matrix[index / cols][index % cols]

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

C++

花花酱 LeetCode 915. Partition Array into Disjoint Intervals

Problem

Given an array A, partition it into two (contiguous) subarrays left and right so that:

  • Every element in left is less than or equal to every element in right.
  • left and right are non-empty.
  • left has the smallest possible size.

Return the length of left after such a partitioning.  It is guaranteed that such a partitioning exists.

Example 1:

Input: [5,0,3,8,6]
Output: 3
Explanation: left = [5,0,3], right = [8,6]

Example 2:

Input: [1,1,1,0,6,12]
Output: 4
Explanation: left = [1,1,1,0], right = [6,12]

Note:

  1. 2 <= A.length <= 30000
  2. 0 <= A[i] <= 10^6
  3. It is guaranteed there is at least one way to partition A as described.

Solution 1: BST

Time complexity: O(nlogn)

Space complexity: O(n)

C++

Solution 2: Greedy

Time complexity: O(n)

Space complexity: O(1)

C++

花花酱 LeetCode 911. Online Election

Problem

n an election, the i-th vote was cast for persons[i] at time times[i].

Now, we would like to implement the following query function: TopVotedCandidate.q(int t) will return the number of the person that was leading the election at time t.

Votes cast at time t will count towards our query.  In the case of a tie, the most recent vote (among tied candidates) wins.

Example 1:

Input: ["TopVotedCandidate","q","q","q","q","q","q"], [[[0,1,1,0,0,1,0],[0,5,10,15,20,25,30]],[3],[12],[25],[15],[24],[8]]
Output: [null,0,1,1,0,0,1]
Explanation: 
At time 3, the votes are [0], and 0 is leading.
At time 12, the votes are [0,1,1], and 1 is leading.
At time 25, the votes are [0,1,1,0,0,1], and 1 is leading (as ties go to the most recent vote.)
This continues for 3 more queries at time 15, 24, and 8.

Note:

  1. 1 <= persons.length = times.length <= 5000
  2. 0 <= persons[i] <= persons.length
  3. times is a strictly increasing array with all elements in [0, 10^9].
  4. TopVotedCandidate.q is called at most 10000 times per test case.
  5. TopVotedCandidate.q(int t) is always called with t >= times[0].

Solution: HashTable + Binary Search

Compute the leads for each t in times using a hash table.

binary search the upper bound of t, and return the lead of previous entry.

Time complexity: Constructor O(n), Query: O(logn)

Space complexity: O(n)

C++