public static MyMatrix gaussSeidel(MyMatrix A, MyMatrix B)
{
int n = A.rowCount;
if (A.rowCount != B.rowCount || A.rowCount != A.columnCount)
{
throw new Exception("Matrix A must be n*n! A rowCount must be equal B rowCount!");
}
MyMatrix X = new MyMatrix(n, 1);
double sum = 0.0;
while (true)
{
for (int i = 0; i < n; i++)
{
for (int j = 0; j < i; j++)
{
sum -= A[i, j] * X[j, 0];
}
for (int j = i + 1; j < n; j++)
{
sum -= A[i, j] * X[j, 0];
}
if (A[i, i] == 0.0)
{
int row = findBiggestRowInColumn(A, i);
swapRows(A, i, row);
swapRows(B, i, row);
}
X[i, 0] = (B[i, 0] + sum) / A[i, i];
sum = 0.0;
}
double norm1 = (B - (A * X)).countNorm();
double norm2 = B.countNorm();
if (norm1 / norm2 < epsilon)
{
break;
}
}
return(X);
}
public static MyMatrix gaussIterative(MyMatrix A, MyMatrix B, int version, out int saver)
{
int n = A.rowCount;
if (A.rowCount != B.rowCount || A.rowCount != A.columnCount)
{
throw new Exception("Matrix A must be n*n! A rowCount must be equal B rowCount!");
}
if (version == 1)
{ //JACOBI
MyMatrix X_NEW = new MyMatrix(n, 1);
MyMatrix X_OLD = new MyMatrix(n, 1);
double sum = 0.0;
int iter = 0;
while (true)
{
for (int i = 0; i < n; i++)
{
for (int j = 0; j < n; j++)
{
if (j != i)
{
sum -= A[i, j] * X_OLD[j, 0];
}
}
if (A[i, i] == 0.0)
{
int row = findBiggestRowInColumn(A, i);
swapRows(A, i, row);
swapRows(B, i, row);
}
X_NEW[i, 0] = (B[i, 0] + sum) / A[i, i];
sum = 0.0;
}
double norm1 = (B - (A * X_NEW)).countNorm();
double norm2 = B.countNorm();
if ((norm1 / norm2) < epsilon)
{
break;
}
for (int i = 0; i < n; i++)
{
X_OLD[i, 0] = X_NEW[i, 0];
}
iter++;
}
saver = iter;
return(X_NEW);
}
else if (version == 2)
{ //SEIDEL
MyMatrix X = new MyMatrix(n, 1);
double sum = 0.0;
int iter = 0;
while (true)
{
for (int i = 0; i < n; i++)
{
for (int j = 0; j < i; j++)
{
sum -= A[i, j] * X[j, 0];
}
for (int j = i + 1; j < n; j++)
{
sum -= A[i, j] * X[j, 0];
}
if (A[i, i] == 0.0)
{
int row = findBiggestRowInColumn(A, i);
swapRows(A, i, row);
swapRows(B, i, row);
}
X[i, 0] = (B[i, 0] + sum) / A[i, i];
sum = 0.0;
}
double norm1 = (B - (A * X)).countNorm();
double norm2 = B.countNorm();
if (norm1 / norm2 < epsilon)
{
break;
}
iter++;
}
saver = iter;
return(X);
}
else
{
throw new Exception("Unknown Gauss elimination version! 1 - base, 2 - partial, 3 - full");
}
}