//      f07ap Example Program Text
//      C# version, NAG Copyright 2008
using System;
using NagLibrary;
using System.Globalization;
namespace NagDotNetExamples
{
  public class F07APE
  {
    static string datafile = "ExampleData/f07ape.d";
    static void Main(String[] args)
    {
      if (args.Length == 1)
      {
        datafile = args[0];
      }
      StartExample();
    }
    public static void StartExample()
    {
      try
      {
        DataReader sr = new DataReader(datafile);
        double rcond=0.0;
        double rgf;
        int i,   info,   j,   n,   nrhs; string equed="";
        string[] clabs = new string[1];
        string[] rlabs = new string[1];
        Console.WriteLine("f07ap Example Program Results");
        Console.WriteLine("");
        //      Skip heading in data file
        sr.Reset();
        sr.Reset();
        n = int.Parse(sr.Next());
        nrhs = int.Parse(sr.Next());
        Complex[,] a = new Complex[n, n];
        Complex[,] af = new Complex[n, n];
        Complex[,] b = new Complex[n, nrhs];
        Complex[,] x = new Complex[n, nrhs];
        double[] berr = new double[nrhs];
        double[] c = new double[n];
        double[] ferr = new double[nrhs];
        double[] r = new double[n];
        int[] ipiv = new int[n];
        if (n > 0 )
        {
          // 
          //         Read A and B from data file
          // 
          sr.Reset();
          for (i = 1 ; i <= n ; i++)
          {
            for (j = 1 ; j <= n ; j++)
            {
              a[i - 1 , j - 1] = Complex.Parse(sr.Next());
            }
          }
          sr.Reset();
          for (i = 1 ; i <= n ; i++)
          {
            for (j = 1 ; j <= nrhs ; j++)
            {
              b[i - 1 , j - 1] = Complex.Parse(sr.Next());
            }
          }
          // 
          //         Solve the equations ax = b for x
          //  
          F07.f07ap("Equilibrate", "No transpose", n, nrhs, a, af, ipiv,  ref equed, r, c, b, x, out rcond, ferr,
          berr, out rgf, out info);

          if (info < 0)
          {
              return;
          }
          // 
          if (info == 0 || info == n + 1)
          {
            // 
            //            Print solution, error bounds, condition number, the form
            //            of equilibration and the pivot growth factor
            // 
            Console.WriteLine("Solution(s)\n");
            for (i = 1 ; i <= n ; i++)
            {
              for (j = 1 ; j <= nrhs ; j++)
              {
                Console.Write("{0, 20:f4}", x[i-1,j-1]);
              }
              Console.WriteLine("");
            }
            Console.WriteLine("");
            Console.WriteLine(" {0}","Backward errors (machine-dependent)");
            for (j = 1 ; j <= nrhs ; j++)
            {
              Console.Write(" {0, 3:e1}", berr[j - 1]);
            }
            Console.WriteLine("");
            Console.WriteLine("");
            Console.WriteLine(" {0}","Estimated forward error bounds (machine-dependent)");
            for (j = 1 ; j <= nrhs ; j++)
            {
              Console.Write(" {0, 3:e1}", ferr[j - 1]);
            }
            Console.WriteLine("");
            Console.WriteLine("");
            if (equed == "N")
            {
              Console.WriteLine(" {0}","A has not been equilibrated");
            }
            else if (equed == "R")
            {
              Console.WriteLine(" {0}","A has been row scaled as diag(R)*A");
            }
            else if (equed == "C")
            {
              Console.WriteLine(" {0}","A has been column scaled as A*diag(C)");
            }
            else if (equed == "B")
            {
              Console.WriteLine(" {0}","A has been row and column scaled as diag(R)*A*diag(C)");
            }
            Console.WriteLine("");
            Console.WriteLine(" {0}","Reciprocal condition number estimate of scaled matrix");
            Console.WriteLine("      {0,11:e1}",rcond);
            Console.WriteLine("");
            Console.WriteLine(" {0}","Estimate of reciprocal pivot growth factor");
            Console.WriteLine("      {0,11:e1}", rgf);
            // 
            if (info == n + 1)
            {
              Console.WriteLine("");
              Console.WriteLine(" {0}","The matrix A is singular to working precision");
            }
          }
          else if (info > 0)
          {
            Console.WriteLine("  {0}{1,3}{2}{3,3}{4}{5}","The (",info,",",info,")"," element of the factor U is zero");
          }
        }
        else
        {
          Console.WriteLine(" {0}","n <= 0");
        }
        // 
      }
      catch (Exception e)
      {
        Console.WriteLine(e.Message);
        Console.WriteLine("Exception Raised");
      }
    }
  }
}