Given a sorted array, two integers k
and x
, find the k
closest elements to x
in the array. The result should also be sorted in ascending order.
If there is a tie, the smaller elements are always preferred.
Example 1:
Input: [1,2,3,4,5], k=4, x=3 Output: [1,2,3,4]
Example 2:
Input: [1,2,3,4,5], k=4, x=-1 Output: [1,2,3,4]
Note:
UPDATE (2017/9/19):
The arr parameter had been changed to an array of integers (instead of a list of integers). Please reload the code definition to get the latest changes.
Algorithm
\nIntuitively, we can sort the elements in list arr
by their absolute difference values to the target x
. Then the sublist of the first k elements is the result after sorting the elements by the natural order.
Note: This solution is inspired by @compton_scatter.
\nComplexity Analysis
\nTime complexity : . Collections.sort() uses binary sort so it has a complexity.
\nSpace complexity : . The in-place sorting does not consume any extra space. However, generating a k length sublist will take some space.
\nAlgorithm
\nThe original array has been sorted so we can take this advantage by the following steps.\n1. If the target x
is less or equal than the first element in the sorted array, the first k
elements are the result.\n2. Similarly, if the target x
is more or equal than the last element in the sorted array, the last k
elements are the result.\n3. Otherwise, we can use binary search to find the index
of the element, which is equal (when this list has x
) or a little bit larger than x
(when this list does not have it). Then set low
to its left k-1
position, and high
to the right k-1
position of this index
as a start. The desired k numbers must in this rang [index-k-1, index+k-1]. So we can shrink this range to get the result using the following rules.\n * If low
reaches the lowest index 0
or the low
element is closer to x
than the high
element, decrease the high
index.\n * If high
reaches to the highest index arr.size()-1
or it is nearer to x
than the low
element, increase the low
index.\n * The looping ends when there are exactly k elements in [low, high], the subList of which is the result.
Complexity Analysis
\nTime complexity : . is for the time of binary search, while is for shrinking the index range to k elements.
\nSpace complexity : . It is to generate the required sublist.
\nAnalysis written by: @Mr.Bin
\n