[Swift]LeetCode973. 最接近原點的 K 個點 | K Closest Points to Origin

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➤微信公衆號：山青詠芝（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

---

咱們有一個由平面上的點組成的列表 points。須要從中找出 K 個距離原點 (0, 0) 最近的點。

（這裏，平面上兩點之間的距離是歐幾里德距離。）

你能夠按任何順序返回答案。除了點座標的順序以外，答案確保是惟一的。 

示例 1：

輸入：points = [[1,3],[-2,2]], K = 1
輸出：[[-2,2]]
解釋： 
(1, 3) 和原點之間的距離爲 sqrt(10)，
(-2, 2) 和原點之間的距離爲 sqrt(8)，
因爲 sqrt(8) < sqrt(10)，(-2, 2) 離原點更近。
咱們只須要距離原點最近的 K = 1 個點，因此答案就是 [[-2,2]]。

示例 2：

輸入：points = [[3,3],[5,-1],[-2,4]], K = 2
輸出：[[3,3],[-2,4]]
（答案 [[-2,4],[3,3]] 也會被接受。） 

提示：

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

---

1004ms

 1 class Solution {
 2     func kClosest(_ points: [[Int]], _ K: Int) -> [[Int]] {
 3          guard K < points.count else { return points }
 4 
 5     var distanceDict : [Int: [Int]] = [:]
 6     for point in points {
 7         let distance = point[0]*point[0] + point[1]*point[1]
 8         distanceDict[distance] = point
 9     }
10 
11     var allDistance = Array<Int>(distanceDict.keys)
12     findKElement(&allDistance, 0, allDistance.count - 1, K)
13     var kClosest: [[Int]] = []
14     for i in 0..<K {
15         kClosest.append(distanceDict[allDistance[i]]!)
16     }
17     return kClosest
18     }
19     
20     
21     func findKElement(_ arr: inout [Int], _ start: Int, _ end: Int, _ k: Int) {
22   
23     let indexP: Int = position(&arr, start, end)
24     
25     if indexP == k {
26         return 
27     }else if indexP < k {
28          findKElement(&arr, indexP+1, end, k)
29     }else {
30          findKElement(&arr, start, indexP-1, k)
31     }
32 }
33 
34 func position(_ arr: inout [Int], _ start: Int, _ end: Int) -> Int {
35     var i = start - 1
36     var j = start
37     let pivot = arr[end]
38     while j < end {
39         if arr[j] <= pivot {
40             i += 1
41             arr.swapAt(i, j)
42         }
43         j += 1
44     }
45 
46     arr.swapAt(i+1, end)
47     return i+1
48   }
49 }

---

1052ms

 1 class Solution {
 2     func kClosest(_ points: [[Int]], _ K: Int) -> [[Int]] {
 3     func distance(_ p: [Int]) -> Int {
 4         return p[0] * p[0] + p[1] * p[1]
 5     }
 6     
 7     let sorted = points.sorted(by: { (p1, p2) -> Bool in
 8         return distance(p1) < distance(p2)
 9     })
10     return Array(sorted[0..<K])
11   }
12 }

---

1056ms

 1 class Solution {
 2     func kClosest(_ points: [[Int]], _ K: Int) -> [[Int]] {
 3         var closest = points.map{
 4             (($0[0] * $0[0] + $0[1] * $0[1]), $0)
 5         }
 6         
 7         closest.sort{ $0.0 < $1.0 }
 8         var res: [[Int]] = []
 9         for i in 0..<K {
10             res.append(closest[i].1)
11         }
12         
13         return res
14     }
15 }

---

1060ms

 1 class Solution {
 2     func kClosest(_ points: [[Int]], _ K: Int) -> [[Int]] {
 3         var result = [(distance: Double, point: [Int])]()
 4         
 5         for point in points {
 6             let distance = sqrt((pow(Double(point[0]), 2) + pow(Double(point[1]), 2)))
 7             result.append((distance, point))
 8         }
 9         
10         result.sort(by: { $0.distance < $1.distance })
11         
12         return result[0..<K].compactMap({ $0.point })
13     }
14 }

---

1063ms

1 class Solution {
2     func kClosest(_ points: [[Int]], _ K: Int) -> [[Int]] {
3         let sortted = points.sorted { (a, b) -> Bool in
4             return (a[0] * a[0] + a[1] * a[1]) < (b[0] * b[0] + b[1] * b[1])
5         }
6         return Array(sortted.prefix(K))
7     }
8 }

---

1064ms 

 1 class Solution {
 2     func kClosest(_ points: [[Int]], _ K: Int) -> [[Int]] {
 3         var points = points
 4         points.sort(by:sortArray)
 5         var ret:[[Int]] = [[Int]]();
 6         for i in 0..<K
 7         {
 8             ret.append(points[i])
 9         } 
10         return ret
11     }
12     
13     func sortArray(_ a:[Int],_ b:[Int]) -> Bool
14     {
15         var da:Int = a[0]*a[0]+a[1]*a[1]
16         var db:Int = b[0]*b[0]+b[1]*b[1]
17         return da < db        
18     }
19 }

---

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

 1 class Solution {
 2     func kClosest(_ points: [[Int]], _ K: Int) -> [[Int]] {
 3         var result = [([Int],Double)]()
 4         for p in points {
 5             let dist = (pow(Double(p[0]),2)+pow(Double(p[1]),2)).squareRoot()
 6             result.append((p, dist))
 7         }
 8         result.sort(by: {
 9             return $0.1 < $1.1
10         })
11         return Array(result.map { $0.0 }[0..<K])
12     }
13 }

---

1120ms

1 class Solution {
2     func kClosest(_ points: [[Int]], _ K: Int) -> [[Int]] {
3         let distances = points.map { sqrt(Double(($0[0] * $0[0]) + ($0[1] * $0[1]))) }
4         return zip(points, distances).sorted { $0.1 < $1.1 }.prefix(K).map { $0.0 }
5     }
6 }