蛮力法03

最新推荐文章于 2023-04-21 23:22:03 发布

转载最新推荐文章于 2023-04-21 23:22:03 发布 · 61 阅读

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原文链接：http://www.cnblogs.com/sharpfeng/archive/2012/08/29/2661573.html

本文介绍了一种计算平面上多个随机分布点之间的最近点对距离的方法，并通过C#实现了该算法。此外，还提供了生成包含这些点的图像的功能，并能够可视化显示距离最近的点对。

摘要生成于 C知道，由 DeepSeek-R1 满血版支持，前往体验 >

——可视化，是如此的充满魅力。

最近距离问题：平面中n（n>1)个点，求距离最近的两个点。

分析：设定集合 pts[n] , minLen=INT_MAX;

for i=0, to n

{

for j=i+1, to n //计算两点间的距离不需要重复计算，所以全部计算过的顶点需要排除

{

if minLen > Dis(pts[i],pts[j])

{

//求出了当前最近的连个点距离

}

 
   /// <summary> 
   /// 最近点对距离计算 
   /// </summary> 
   class PointPairCompute 
   { 
       private int imgWidth; 
       private int imgHeight; 
       private int createCount; 
       private List<Point> ptLst; 
       private readonly int radius; 
     
       public PointPairCompute(int width,int height,int count) 
       { 
           this.imgWidth = width; 
           this.imgHeight = height; 
           this.createCount = count; 
            
           this.ptLst = new List<Point>(); 
           this.radius = 2; 
       } 
     
     
       /// <summary> 
       /// 获取随机生成点的图片 
       /// </summary> 
       /// <returns>图片</returns> 
       public Image GetRandomImag() 
       { 
           //随机产生点 
           RandomCratePtLst(); 
           //绘制图片 
           Bitmap map = new Bitmap(this.imgWidth, this.imgHeight); 
           Graphics gfx = Graphics.FromImage(map); 
           gfx.Clear(Color.Gray); 
     
           foreach (Point item in this.ptLst) 
           { 
               //map.SetPixel(item.X, item.Y, Color.Red); 
               gfx.FillEllipse(Brushes.Red, item.X - radius, item.Y - radius, radius * 2, radius * 2); 
           } 
     
           gfx.Dispose();             
     
           return map; 
       } 
     
       /// <summary> 
       /// 获取点对最近距离结果图片 
       /// </summary> 
       /// <returns>结果图片</returns> 
       public Image GetPointPariResult() 
       { 
           if (this.ptLst.Count <2) 
           { 
               return null; 
           } 
     
           int leftIndex = -1; 
           int rightIndex = -1; 
           ComputerPointPari(ref leftIndex, ref rightIndex); 
     
           Bitmap map = new Bitmap(this.imgWidth, this.imgHeight); 
           Graphics gfx = Graphics.FromImage(map); 
           gfx.Clear(Color.White); 
           Pen pen = new Pen(Color.Green, 4); 
           gfx.DrawLine(pen, ptLst[leftIndex], ptLst[rightIndex]); 
                        
           foreach (Point item in this.ptLst) 
           { 
               //map.SetPixel(item.X, item.Y, Color.Red); 
               gfx.FillEllipse(Brushes.Red, item.X - radius, item.Y - radius, radius * 2, radius * 2); 
           } 
     
           gfx.Dispose(); 
           return map; 
       } 
     
       //随机生成点 
       private void RandomCratePtLst() 
       { 
           this.ptLst.Clear(); 
     
           Random rd = new Random(); 
           for (int i = 0; i < this.createCount; i++) 
           { 
               this.ptLst.Add(new Point(rd.Next(0, this.imgWidth), rd.Next(0, this.imgHeight))); 
           } 
       } 
     
       //蛮力计算最短距离 
       private void ComputerPointPari(ref int leftIndex, ref int rightIndex) 
       { 
           int minLen = Int32.MaxValue; 
     
           for (int i = 0; i < this.ptLst.Count; ++i) 
           { 
               for (int j = i+1; j < this.ptLst.Count; j++) 
               { 
                   int tempLen = (ptLst[i].X - ptLst[j].X) * (ptLst[i].X - ptLst[j].X) + 
                       (ptLst[i].Y - ptLst[j].Y) * (ptLst[i].Y - ptLst[j].Y); 
     
                   if (minLen > tempLen) 
                   { 
                       minLen = tempLen; 
                       leftIndex = i; 
                       rightIndex = j; 
                   } 
               } 
           } 
       } 
   } 
  

转载于:https://www.cnblogs.com/sharpfeng/archive/2012/08/29/2661573.html