README_EN.md

973. K Closest Points to Origin

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Description

Given an array of points where points[i] = [xi, yi] represents a point on the X-Y plane and an integer k, return the k closest points to the origin (0, 0).

The distance between two points on the X-Y plane is the Euclidean distance (i.e., √(x1 - x2)2 + (y1 - y2)2).

You may return the answer in any order. The answer is guaranteed to be unique (except for the order that it is in).

 

Example 1:

Input: points = [[1,3],[-2,2]], k = 1
Output: [[-2,2]]
Explanation:
The distance between (1, 3) and the origin is sqrt(10).
The distance between (-2, 2) and the origin is sqrt(8).
Since sqrt(8) < sqrt(10), (-2, 2) is closer to the origin.
We only want the closest k = 1 points from the origin, so the answer is just [[-2,2]].

Example 2:

Input: points = [[3,3],[5,-1],[-2,4]], k = 2
Output: [[3,3],[-2,4]]
Explanation: The answer [[-2,4],[3,3]] would also be accepted.

 

Constraints:

• 1 <= k <= points.length <= 104
• -104 < xi, yi < 104

Solutions

Python3

Java

import java.util.*;

/**
 * @author Furaha Damien
 */

class Solution {

    // Helper inner class
    public class Point {
        int x;
        int y;
        int distance;

        public Point(int x, int y, int distance) {
            this.x = x;
            this.y = y;
            this.distance = distance;
        }
    }

    public int[][] kClosest(int[][] points, int K) {

        PriorityQueue<Point> que = new PriorityQueue<Point>((a, b) -> (a.distance - b.distance));
        int[][] res = new int[K][2];

        for (int[] temp : points) {
            int dist = (temp[0] * temp[0] + temp[1] * temp[1]);
            que.offer(new Point(temp[0], temp[1], dist));
        }
        for (int i = 0; i < K; i++) {
            Point curr = que.poll();
            res[i][0] = curr.x;
            res[i][1] = curr.y;
        }
        return res;
    }
}

TypeScript

function kClosest(points: number[][], k: number): number[][] {
    return points
        .sort((a, b) => a[0] ** 2 + a[1] ** 2 - (b[0] ** 2 + b[1] ** 2))
        .slice(0, k);
}

Rust

impl Solution {
    pub fn k_closest(mut points: Vec<Vec<i32>>, k: i32) -> Vec<Vec<i32>> {
        points.sort_unstable_by(|a, b| {
            (a[0].pow(2) + a[1].pow(2)).cmp(&(b[0].pow(2) + b[1].pow(2)))
        });
        points[0..k as usize].to_vec()
    }
}

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