private void btnKMeansClustering_Click(object sender, EventArgs e)
{
try
{
if (PList.Count == 0)
{
throw new Exception("No points data exists..");
}
int numClusters = int.Parse(txtClusters.Text);
List <ClusterCenterPoint> CList = null;
KMeans.DoKMeans(numClusters, ref PList, ref CList, 0.1, 1000, true); //true means do kplusplus
MyImageProc.DrawClusters(pic1, PList, 1.0, numClusters);
txtResult.Text = ComputeAndShowVarianceResults(numClusters);
}
catch (Exception ex)
{
MessageBox.Show(ex.Message);
}
}
private void btnLoad_Click(object sender, EventArgs e)
{
try
{
OpenFileDialog ofd = new OpenFileDialog();
ofd.InitialDirectory = "d:\\csharp2016\\ClusterData";
if (ofd.ShowDialog() == DialogResult.OK)
{
PList.Clear();
string dataFileName = ofd.FileName;
FileInfo fi = new FileInfo(dataFileName);
Stream strm = fi.Open(FileMode.Open, FileAccess.Read);
StreamReader strmr = new StreamReader(strm);
string sline = null;
char[] seps = { ',', ' ' }; // for comma or space separated list of coordinates
// read each line and store the point coordinates in CList
sline = strmr.ReadLine();
while (sline != null)
{
string[] parts = sline.Split(seps); // break line into parts
MyPoint pt = new MyPoint();
pt.ClusterId = 0;
int ptnum = int.Parse(parts[0]); // point number - ignored
pt.X = double.Parse(parts[1]); // X coord value
pt.Y = double.Parse(parts[2]); // Y coord value
PList.Add(pt);
sline = strmr.ReadLine();
}
MessageBox.Show("Data File read, total points = " + PList.Count.ToString());
MyImageProc.DrawClusters(pic1, PList, 1.0, 1);
strmr.Close();
}
}
catch (Exception ex)
{
MessageBox.Show(ex.Message);
}
}
private void btnKmeans_Click(object sender, EventArgs e)
{
try
{
if (PList.Count == 0)
{
throw new Exception("No points data exists..");
}
Stopwatch sw = new Stopwatch();
int numClusters = int.Parse(txtClusters.Text);
List <ClusterCenterPoint> CList = null;
sw.Start();
KMeans.DoKMeans(numClusters, ref PList, ref CList, 0.1, 1000);
sw.Stop();
MessageBox.Show("Time elapsed (ms): " + sw.ElapsedMilliseconds);
MyImageProc.DrawClusters(pic1, PList, 1.0, numClusters);
txtResult.Text = ComputeAndShowVarianceResults(numClusters);
}
catch (Exception ex)
{
MessageBox.Show(ex.Message);
}
}
private void btnInitialize_Click(object sender, EventArgs e)
{
PList.Clear();
Random rand = new Random();
int dataLength = 5000; // number of data points
// create 4 distributions with different means and std devs
double meanx0 = 150;
double meanx1 = 250;
double meanx2 = 375;
double meanx3 = 475;
double meany0 = 175;
double meany1 = 250;
double meany2 = 350;
double meany3 = 450;
double stddevx0 = 240;
double stddevx1 = 270;
double stddevx2 = 220;
double stddevx3 = 260;
double stddevy0 = 250;
double stddevy1 = 240;
double stddevy2 = 280;
double stddevy3 = 245;
int index = 0;
for (int i = 0; i < dataLength / 4; i++)
{
MyPoint pt = new MyPoint();
double rnum = rand.NextDouble();
if (rnum < 0.5)
{
pt.X = rand.NextDouble() * stddevx0 / 2 + meanx0;
}
else
{
pt.X = -1 * rand.NextDouble() * stddevx0 / 2 + meanx0;
}
if (rnum < 0.5)
{
pt.Y = rand.NextDouble() * stddevy0 / 2 + meany0;
}
else
{
pt.Y = -1 * rand.NextDouble() * stddevy0 / 2 + meany0;
}
index++;
PList.Add(pt);
}
for (int i = 0; i < dataLength / 4; i++)
{
MyPoint pt = new MyPoint();
double rnum = rand.NextDouble();
if (rnum < 0.5)
{
pt.X = rand.NextDouble() * stddevx1 / 2 + meanx1;
}
else
{
pt.X = -1 * rand.NextDouble() * stddevx1 / 2 + meanx1;
}
if (rnum < 0.5)
{
pt.Y = rand.NextDouble() * stddevy1 / 2 + meany1;
}
else
{
pt.Y = -1 * rand.NextDouble() * stddevy1 / 2 + meany1;
}
index++;
PList.Add(pt);
}
for (int i = 0; i < dataLength / 4; i++)
{
double rnum = rand.NextDouble();
MyPoint pt = new MyPoint();
if (rnum < 0.5)
{
pt.X = rand.NextDouble() * stddevx2 / 2 + meanx2;
}
else
{
pt.X = -1 * rand.NextDouble() * stddevx2 / 2 + meanx2;
}
if (rnum < 0.5)
{
pt.Y = rand.NextDouble() * stddevy2 / 2 + meany2;
}
else
{
pt.Y = -1 * rand.NextDouble() * stddevy2 / 2 + meany2;
}
PList.Add(pt);
index++;
}
for (int i = 0; i < dataLength / 4; i++)
{
double rnum = rand.NextDouble();
MyPoint pt = new MyPoint();
if (rnum < 0.5)
{
pt.X = rand.NextDouble() * stddevx3 / 2 + meanx3;
}
else
{
pt.X = -1 * rand.NextDouble() * stddevx3 / 2 + meanx3;
}
if (rnum < 0.5)
{
pt.Y = rand.NextDouble() * stddevy3 / 2 + meany3;
}
else
{
pt.Y = -1 * rand.NextDouble() * stddevy3 / 2 + meany3;
}
index++;
PList.Add(pt);
}
MyImageProc.DrawClusters(pic1, PList, 1.0, 1);
}