public double[,] ParsedSolve(string formulaA, string formulaB, int columnA, int rowA, int columnB, int rowB, bool sparse, int opperation)
{
SymbolicExpression parsedA = SymbolicExpression.Parse(formulaA);
SymbolicExpression parsedB = SymbolicExpression.Parse(formulaB);
if (parsedA != null && parsedB != null)
{
Stopwatch stopwatch = new Stopwatch();
Matrix <double> mA, mB;
Func <double, double, double> funcA = parsedA.Compile("x", "y");
Func <double, double, double> funcB = parsedB.Compile("x", "y");
IMatrix matrix = new MathnetMatrixSolver();
switch (opperation)
{
case 0:
{
if (!sparse)
{
mA = Matrix <double> .Build.Dense(columnA, rowA, (i, j) => funcA(i, j));
mB = Matrix <double> .Build.Dense(columnB, rowB, (i, j) => funcB(i, j));
return((mA * mB).ToArray());
}
mA = Matrix <double> .Build.Sparse(columnA, rowA, (i, j) => funcA(i, j));
mB = Matrix <double> .Build.Sparse(columnB, rowB, (i, j) => funcB(i, j));
return((mA * mB).ToArray());
}
case 1:
{
if (!sparse)
{
mA = Matrix <double> .Build.Dense(columnA, rowA, (i, j) => funcA(i, j)).Transpose();
return(mA.ToArray());
}
mA = Matrix <double> .Build.Sparse(columnA, rowA, (i, j) => funcA(i, j)).Transpose();
return(mA.ToArray());
}
}
}
double[,] err = { { 0.0 } };
return(err);
}