# Posts tagged as “binary search”

The minimum absolute difference of an array a is defined as the minimum value of |a[i] - a[j]|, where 0 <= i < j < a.length and a[i] != a[j]. If all elements of a are the same, the minimum absolute difference is -1.

• For example, the minimum absolute difference of the array [5,2,3,7,2] is |2 - 3| = 1. Note that it is not 0 because a[i] and a[j] must be different.

You are given an integer array nums and the array queries where queries[i] = [li, ri]. For each query i, compute the minimum absolute difference of the subarray nums[li...ri] containing the elements of nums between the 0-based indices li and ri (inclusive).

Return an array ans where ans[i] is the answer to the ith query.

subarray is a contiguous sequence of elements in an array.

The value of |x| is defined as:

• x if x >= 0.
• -x if x < 0.

Example 1:

Input: nums = [1,3,4,8], queries = [[0,1],[1,2],[2,3],[0,3]]
Output: [2,1,4,1]
Explanation: The queries are processed as follows:
- queries = [0,1]: The subarray is [1,3] and the minimum absolute difference is |1-3| = 2.
- queries = [1,2]: The subarray is [3,4] and the minimum absolute difference is |3-4| = 1.
- queries = [2,3]: The subarray is [4,8] and the minimum absolute difference is |4-8| = 4.
- queries = [0,3]: The subarray is [1,3,4,8] and the minimum absolute difference is |3-4| = 1.


Example 2:

Input: nums = [4,5,2,2,7,10], queries = [[2,3],[0,2],[0,5],[3,5]]
Output: [-1,1,1,3]
Explanation: The queries are processed as follows:
- queries = [2,3]: The subarray is [2,2] and the minimum absolute difference is -1 because all the
elements are the same.
- queries = [0,2]: The subarray is [4,5,2] and the minimum absolute difference is |4-5| = 1.
- queries = [0,5]: The subarray is [4,5,2,2,7,10] and the minimum absolute difference is |4-5| = 1.
- queries = [3,5]: The subarray is [2,7,10] and the minimum absolute difference is |7-10| = 3.


Constraints:

• 2 <= nums.length <= 105
• 1 <= nums[i] <= 100
• 1 <= queries.length <= 2 * 104
• 0 <= li < ri < nums.length

## Solution: Binary Search

Since the value range of num is quiet small [1~100], we can store the indices for each value.
[2, 1, 2, 2, 3] => {1: , 2: [0, 2, 3]: 3: }.

For each query, we try all possible value b. Check whether b is the query range using binary search, we also keep tracking the previous available value a, ans will be min{b – a}.

Time complexity: O(n + q * 100 * log(n))
Space complexity: O(n)

## C++

You are given two strings s and p where p is a subsequence of s. You are also given a distinct 0-indexed integer array removable containing a subset of indices of s (s is also 0-indexed).

You want to choose an integer k (0 <= k <= removable.length) such that, after removing k characters from s using the first k indices in removablep is still a subsequence of s. More formally, you will mark the character at s[removable[i]] for each 0 <= i < k, then remove all marked characters and check if p is still a subsequence.

Return the maximum k you can choose such that p is still a subsequence of s after the removals.

subsequence of a string is a new string generated from the original string with some characters (can be none) deleted without changing the relative order of the remaining characters.

Example 1:

Input: s = "abcacb", p = "ab", removable = [3,1,0]
Output: 2
Explanation: After removing the characters at indices 3 and 1, "abcacb" becomes "accb".
"ab" is a subsequence of "accb".
If we remove the characters at indices 3, 1, and 0, "abcacb" becomes "ccb", and "ab" is no longer a subsequence.
Hence, the maximum k is 2.


Example 2:

Input: s = "abcbddddd", p = "abcd", removable = [3,2,1,4,5,6]
Output: 1
Explanation: After removing the character at index 3, "abcbddddd" becomes "abcddddd".
"abcd" is a subsequence of "abcddddd".


Example 3:

Input: s = "abcab", p = "abc", removable = [0,1,2,3,4]
Output: 0
Explanation: If you remove the first index in the array removable, "abc" is no longer a subsequence.


Constraints:

• 1 <= p.length <= s.length <= 105
• 0 <= removable.length < s.length
• 0 <= removable[i] < s.length
• p is a subsequence of s.
• s and p both consist of lowercase English letters.
• The elements in removable are distinct.

## Solution: Binary Search + Two Pointers

If we don’t remove any thing, p is a subseq of s, as we keep removing, at some point L, p is no longer a subseq of s. e.g [0:True, 1: True, …, L – 1: True, L: False, L+1: False, …, m:False], this array is monotonic. We can use binary search to find the smallest L such that p is no long a subseq of s. Ans = L – 1.

For each guess, we can use two pointers to check whether p is subseq of removed(s) in O(n).

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

## C++

You have n packages that you are trying to place in boxes, one package in each box. There are m suppliers that each produce boxes of different sizes (with infinite supply). A package can be placed in a box if the size of the package is less than or equal to the size of the box.

The package sizes are given as an integer array packages, where packages[i] is the size of the ith package. The suppliers are given as a 2D integer array boxes, where boxes[j] is an array of box sizes that the jth supplier produces.

You want to choose a single supplier and use boxes from them such that the total wasted space is minimized. For each package in a box, we define the space wasted to be size of the box - size of the package. The total wasted space is the sum of the space wasted in all the boxes.

• For example, if you have to fit packages with sizes [2,3,5] and the supplier offers boxes of sizes [4,8], you can fit the packages of size-2 and size-3 into two boxes of size-4 and the package with size-5 into a box of size-8. This would result in a waste of (4-2) + (4-3) + (8-5) = 6.

Return the minimum total wasted space by choosing the box supplier optimally, or -1 if it is impossible to fit all the packages inside boxes. Since the answer may be large, return it modulo 109 + 7.

Example 1:

Input: packages = [2,3,5], boxes = [[4,8],[2,8]]
Output: 6
Explanation: It is optimal to choose the first supplier, using two size-4 boxes and one size-8 box.
The total waste is (4-2) + (4-3) + (8-5) = 6.


Example 2:

Input: packages = [2,3,5], boxes = [[1,4],[2,3],[3,4]]
Output: -1
Explanation: There is no box that the package of size 5 can fit in.


Example 3:

Input: packages = [3,5,8,10,11,12], boxes = [,[11,9],[10,5,14]]
Output: 9
Explanation: It is optimal to choose the third supplier, using two size-5 boxes, two size-10 boxes, and two size-14 boxes.
The total waste is (5-3) + (5-5) + (10-8) + (10-10) + (14-11) + (14-12) = 9.


Constraints:

• n == packages.length
• m == boxes.length
• 1 <= n <= 105
• 1 <= m <= 105
• 1 <= packages[i] <= 105
• 1 <= boxes[j].length <= 105
• 1 <= boxes[j][k] <= 105
• sum(boxes[j].length) <= 105
• The elements in boxes[j] are distinct.

## Solution: Greedy + Binary Search

1. sort packages and boxes
2. for each box find all (unpacked) packages that are smaller or equal to itself.

Time complexity: O(nlogn) + O(mlogm) + O(mlogn)
Space complexity: O(1)

## C++

You are given a 0-indexed binary string s and two integers minJump and maxJump. In the beginning, you are standing at index 0, which is equal to '0'. You can move from index i to index j if the following conditions are fulfilled:

• i + minJump <= j <= min(i + maxJump, s.length - 1), and
• s[j] == '0'.

Return true if you can reach index s.length - 1 in s, or false otherwise.

Example 1:

Input: s = "011010", minJump = 2, maxJump = 3
Output: true
Explanation:
In the first step, move from index 0 to index 3.
In the second step, move from index 3 to index 5.


Example 2:

Input: s = "01101110", minJump = 2, maxJump = 3
Output: false


Constraints:

• 2 <= s.length <= 105
• s[i] is either '0' or '1'.
• s == '0'
• 1 <= minJump <= maxJump < s.length

## Solution 1: TreeSet /Dequq + Binary Search

Maintain a set of reachable indices so far, for each ‘0’ index check whether it can be reached from any of the elements in the set.

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

## Solution 2: Queue

Same idea, we can replace the deque in sol1 with a queue, and only check the smallest element in the queue.

## C++/set

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

You are given a floating-point number hour, representing the amount of time you have to reach the office. To commute to the office, you must take n trains in sequential order. You are also given an integer array dist of length n, where dist[i] describes the distance (in kilometers) of the ith train ride.

Each train can only depart at an integer hour, so you may need to wait in between each train ride.

• For example, if the 1st train ride takes 1.5 hours, you must wait for an additional 0.5 hours before you can depart on the 2nd train ride at the 2 hour mark.

Return the minimum positive integer speed (in kilometers per hour) that all the trains must travel at for you to reach the office on time, or -1 if it is impossible to be on time.

Tests are generated such that the answer will not exceed 107 and hour will have at most two digits after the decimal point.

Example 1:

Input: dist = [1,3,2], hour = 6
Output: 1
Explanation: At speed 1:
- The first train ride takes 1/1 = 1 hour.
- Since we are already at an integer hour, we depart immediately at the 1 hour mark. The second train takes 3/1 = 3 hours.
- Since we are already at an integer hour, we depart immediately at the 4 hour mark. The third train takes 2/1 = 2 hours.
- You will arrive at exactly the 6 hour mark.


Example 2:

Input: dist = [1,3,2], hour = 2.7
Output: 3
Explanation: At speed 3:
- The first train ride takes 1/3 = 0.33333 hours.
- Since we are not at an integer hour, we wait until the 1 hour mark to depart. The second train ride takes 3/3 = 1 hour.
- Since we are already at an integer hour, we depart immediately at the 2 hour mark. The third train takes 2/3 = 0.66667 hours.
- You will arrive at the 2.66667 hour mark.


Example 3:

Input: dist = [1,3,2], hour = 1.9
Output: -1
Explanation: It is impossible because the earliest the third train can depart is at the 2 hour mark.


Constraints:

• n == dist.length
• 1 <= n <= 105
• 1 <= dist[i] <= 105
• 1 <= hour <= 109
• There will be at most two digits after the decimal point in hour.

## Solution: Binary Search

l = speedmin=1
r = speedmax+1 = 1e7 + 1

Find the min valid speed m such that t(m) <= hour.

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