[Swift]LeetCode973. 最接近原点的 K 个点 | K Closest Points to Origin

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➤微信公众号：山青咏芝（shanqingyongzhi）
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★★★★★★★★★★★★★★★★★★★★★★★★★★★★★★★★★★★★★★★★We have a list of points on the plane.  Find the K closest points to the origin (0, 0).

(Here, the distance between two points on a plane is the Euclidean distance.)

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]]
(The answer [[-2,4],[3,3]] would also be accepted.) 

Note:

1. 1 <= K <= points.length <= 10000
2. -10000 < points[i][0] < 10000
3. -10000 < points[i][1] < 10000

---

我们有一个由平面上的点组成的列表 points。需要从中找出 K 个距离原点 (0, 0) 最近的点。

（这里，平面上两点之间的距离是欧几里德距离。）

你可以按任何顺序返回答案。除了点坐标的顺序之外，答案确保是唯一的。 

示例 1：

输入：points = [[1,3],[-2,2]], K = 1
输出：[[-2,2]]
解释： 
(1, 3) 和原点之间的距离为 sqrt(10)，
(-2, 2) 和原点之间的距离为 sqrt(8)，
由于 sqrt(8) < sqrt(10)，(-2, 2) 离原点更近。
我们只需要距离原点最近的 K = 1 个点，所以答案就是 [[-2,2]]。

示例 2：

输入：points = [[3,3],[5,-1],[-2,4]], K = 2
输出：[[3,3],[-2,4]]
（答案 [[-2,4],[3,3]] 也会被接受。） 

提示：

1. 1 <= K <= points.length <= 10000
2. -10000 < points[i][0] < 10000
3. -10000 < points[i][1] < 10000

---

1004ms

class Solution {
    func kClosest(_ points: [[Int]], _ K: Int) -> [[Int]] {
         guard K < points.count else { return points }

    var distanceDict : [Int: [Int]] = [:]
    for point in points {
        let distance = point[0]*point[0] + point[1]*point[1]
        distanceDict[distance] = point
    }

    var allDistance = Array<Int>(distanceDict.keys)
    findKElement(&allDistance, 0, allDistance.count - 1, K)
    var kClosest: [[Int]] = []
    for i in 0..<K {
        kClosest.append(distanceDict[allDistance[i]]!)
    }
    return kClosest
    }
    
    
    func findKElement(_ arr: inout [Int], _ start: Int, _ end: Int, _ k: Int) {
  
    let indexP: Int = position(&arr, start, end)
    
    if indexP == k {
        return 
    }else if indexP < k {
         findKElement(&arr, indexP+1, end, k)
    }else {
         findKElement(&arr, start, indexP-1, k)
    }
}

func position(_ arr: inout [Int], _ start: Int, _ end: Int) -> Int {
    var i = start - 1
    var j = start
    let pivot = arr[end]
    while j < end {
        if arr[j] <= pivot {
            i += 1
            arr.swapAt(i, j)
        }
        j += 1
    }

    arr.swapAt(i+1, end)
    return i+1
  }
}

---

1052ms

class Solution {
    func kClosest(_ points: [[Int]], _ K: Int) -> [[Int]] {
    func distance(_ p: [Int]) -> Int {
        return p[0] * p[0] + p[1] * p[1]
    }
    
    let sorted = points.sorted(by: { (p1, p2) -> Bool in
        return distance(p1) < distance(p2)
    })
    return Array(sorted[0..<K])
  }
}

---

1056ms

class Solution {
    func kClosest(_ points: [[Int]], _ K: Int) -> [[Int]] {
        var closest = points.map{
            (($0[0] * $0[0] + $0[1] * $0[1]), $0)
        }
        
        closest.sort{ $0.0 < $1.0 }
        var res: [[Int]] = []
        for i in 0..<K {
            res.append(closest[i].1)
        }
        
        return res
    }
}

---

1060ms

class Solution {
    func kClosest(_ points: [[Int]], _ K: Int) -> [[Int]] {
        var result = [(distance: Double, point: [Int])]()
        
        for point in points {
            let distance = sqrt((pow(Double(point[0]), 2) + pow(Double(point[1]), 2)))
            result.append((distance, point))
        }
        
        result.sort(by: { $0.distance < $1.distance })
        
        return result[0..<K].compactMap({ $0.point })
    }
}

---

1063ms

class Solution {
    func kClosest(_ points: [[Int]], _ K: Int) -> [[Int]] {
        let sortted = points.sorted { (a, b) -> Bool in
            return (a[0] * a[0] + a[1] * a[1]) < (b[0] * b[0] + b[1] * b[1])
        }
        return Array(sortted.prefix(K))
    }
}

---

1064ms 

class Solution {
    func kClosest(_ points: [[Int]], _ K: Int) -> [[Int]] {
        var points = points
        points.sort(by:sortArray)
        var ret:[[Int]] = [[Int]]();
        for i in 0..<K
        {
            ret.append(points[i])
        } 
        return ret
    }
    
    func sortArray(_ a:[Int],_ b:[Int]) -> Bool
    {
        var da:Int = a[0]*a[0]+a[1]*a[1]
        var db:Int = b[0]*b[0]+b[1]*b[1]
        return da < db        
    }
}

---

1076ms

1 class Solution {
2     func kClosest(_ points: [[Int]], _ K: Int) -> [[Int]] {
3         let pts = points.sorted { $0[0]*$0[0]+$0[1]*$0[1] < $1[0]*$1[0]+$1[1]*$1[1] }
4         // print(pts)
5         return Array(pts[0..<K])
6     }
7 }

---

1080ms

 1 class Solution {
 2     func kClosest(_ points: [[Int]], _ K: Int) -> [[Int]] {
 3         let pointsAndEuclidean = points.map({ (point: [Int]) -> ([Int], Double) in
 4             let  sqrtee = pow(Double(point[0]), 2)
 5                 + pow(Double(point[1]), 2)
 6             return (point, sqrt( sqrtee ))
 7         })
 8         return pointsAndEuclidean.sorted(by: { $0.1 < $1.1 })[..<K].map({ $0.0 })
 9     }
10 }

---

1100ms

class Solution {
    func kClosest(_ points: [[Int]], _ K: Int) -> [[Int]] {
        var result = [([Int],Double)]()
        for p in points {
            let dist = (pow(Double(p[0]),2)+pow(Double(p[1]),2)).squareRoot()
            result.append((p, dist))
        }
        result.sort(by: {
            return $0.1 < $1.1
        })
        return Array(result.map { $0.0 }[0..<K])
    }
}

---

1120ms

class Solution {
    func kClosest(_ points: [[Int]], _ K: Int) -> [[Int]] {
        let distances = points.map { sqrt(Double(($0[0] * $0[0]) + ($0[1] * $0[1]))) }
        return zip(points, distances).sorted { $0.1 < $1.1 }.prefix(K).map { $0.0 }
    }
}