public static void approx()
{
int[] size = FileHelper.loadSizes(inputSize);
MyMatrix vector;
double[,] partial = FileHelper.loadDataForAprox(gaussPartial);
double[,] partialOpt = FileHelper.loadDataForAprox(gaussPartialOpt);
double[,] seidel = FileHelper.loadDataForAprox(gaussSeidel);
double[,] sparse = FileHelper.loadDataForAprox(gaussSparseEigen);
double[,] sparseSeidel = FileHelper.loadDataForAprox(gaussSparseSeidelEigen);
double[] results = new double[5];
for (int i = 0; i < size.Length; i++)
{
Console.WriteLine("\n\n Size : " + size[i] + "\n");
Console.WriteLine("-------------------------GAUSS PARTIAL BEZ OPTYMALIZACJI-------------------------");
vector = Approximation.CountEquation(partial, 3); //Gauss Partial
results[0] = Approximation.CountVariable(vector, size[i]);
Console.WriteLine("\nWynik : " + results[0] + "\n");
Console.WriteLine("-------------------------GAUSS PARTIAL Z OPTYMALIZACJA-------------------------");
vector = Approximation.CountEquation(partialOpt, 2); //Gaus Partial Opt
results[1] = Approximation.CountVariable(vector, size[i]);
Console.WriteLine("\nWynik : " + results[1] + "\n");
Console.WriteLine("-------------------------GAUSS ITERACYJNY : SEIDEL-------------------------");
vector = Approximation.CountEquation(seidel, 2); //Gauss Seidel
results[2] = Approximation.CountVariable(vector, size[i]);
Console.WriteLine("\nWynik : " + results[2] + "\n");
Console.WriteLine("-------------------------GAUSS SPARSE LU EIGEN-------------------------");
vector = Approximation.CountEquation(sparse, 1); //SparseLU Eigen
results[3] = Approximation.CountVariable(vector, size[i]);
Console.WriteLine("\nWynik : " + results[3] + "\n");
Console.WriteLine("-------------------------GAUSS SPARSE SEIDEL EIGEN-------------------------");
vector = Approximation.CountEquation(sparseSeidel, 1);//Sparse Seidel Eigen
results[4] = Approximation.CountVariable(vector, size[i]);
Console.WriteLine("\nWynik : " + results[4] + "\n");
FileHelper.saveStatsFromApproximations(infoApproxOutput, size[i], results);
Console.ReadKey();
}
}
