Format Exception was unhandeled

using System;
using System.IO;
using System.Collections.Generic;
using System.Linq;
using System.Text;

namespace ReadFromFile
{
   public class k_means1
    {
     static void Main(string[] args)
      {
       Console.WriteLine("\nBegin k-means clustering demo\n");
       StreamReader reader = new StreamReader(@"F:\DOT NET PROJECTS\2012 projects\scalable learning of collective behaviour\app.txt");
          string content = null;
          string[] line = null;

          char[] ch = { ',' };

          int a = 1;
          double[][] rawdata = new double[20][];
          while ((content = reader.ReadLine()) != null)
          {
              if (a == 1 || a == 2)
                  Console.WriteLine("Does nothing");
              else
              {
                  line = content.Split(ch);
                 // try
                  //{
                      for (int b = 0; b < 20; b++)
                      {
                          rawdata[b] = new double[2];
                          rawdata[b][0] = Convert.ToDouble(line[1]);
                          rawdata[b][1] = Convert.ToDouble(line[2]);
                      }

                  //}
                  //catch (Exception ex)
                  //{
                    //  Console.WriteLine(ex.Message);
                  //}
                  //Console.WriteLine("First value: " + line[1]);
                  //Console.WriteLine();
                  //Console.WriteLine("First value: " + line[2]);
              }
              a++;
           }
          foreach (double[] d in rawdata)
          {
              Console.WriteLine("First value: " + line[1]);
              Console.WriteLine();
              Console.WriteLine("First value: " + line[2]);
          }
       Console.WriteLine("Raw unclustered data:\n");
       Console.WriteLine("    Height Weight");
       Console.WriteLine("-------------------");
       ShowData(rawdata, 1, true, true);

      int numClusters = 3;
      Console.WriteLine("\nSetting numClusters to " + numClusters);

      int[] clustering = Cluster(rawdata, numClusters); // this is it

      Console.WriteLine("\nK-means clustering complete\n");

      Console.WriteLine("Final clustering in internal form:\n");
      ShowVector(clustering, true);

      Console.WriteLine("Raw data by cluster:\n");
      ShowClustered(rawdata, clustering, numClusters, 1);

      Console.WriteLine("\nEnd k-means clustering demo\n");
      Console.ReadLine();
          }