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cleanup

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This commit is contained in:
Max Luebke 2021-12-13 13:47:32 +01:00
parent 74ab002d49
commit e625455923
1 changed files with 0 additions and 58 deletions
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58
src/BTCSDiffusion.cpp
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@ -50,52 +50,6 @@ void BTCSDiffusion::simulate1D(std::vector<double> &c, double bc_left,
b_vector.resize(size); b_vector.resize(size);
x_vector.resize(size); x_vector.resize(size);
// Eigen::VectorXd b = Eigen::VectorXd::Constant(size, 0);
// Eigen::VectorXd x_out(size);
/*
* Initalization of matrix A
* This is done by triplets. See:
* https://eigen.tuxfamily.org/dox/group__TutorialSparse.html
*/
// std::vector<T> tripletList;
// tripletList.reserve(c.size() * 3 + bc.size());
// int A_line = 0;
// // For all concentrations create one row in matrix A
// for (int i = 1; i < this->dim_x + 1; i++) {
// double sx = (alpha[i - 1] * timestep) / (dx * dx);
// tripletList.push_back(T(A_line, i, (-1. - 2. * sx)));
// tripletList.push_back(T(A_line, i - 1, sx));
// tripletList.push_back(T(A_line, i + 1, sx));
// b[A_line] = -c[i - 1];
// A_line++;
// }
// // append left and right boundary conditions/ghost zones
// tripletList.push_back(T(A_line, 0, 1));
// // if value is -1 apply Neumann condition with given gradient
// // TODO: set specific gradient
// if (bc[0] == -1)
// b[A_line] = c[0];
// // else apply given Dirichlet condition
// else
// b[A_line] = this->bc[0];
// A_line++;
// tripletList.push_back(T(A_line, size - 1, 1));
// // b[A_line] = bc[1];
// if (bc[1] == -1)
// b[A_line] = c[c.size() - 1];
// else
// b[A_line] = this->bc[1];
/* /*
* Begin to solve the equation system using LU solver of Eigen. * Begin to solve the equation system using LU solver of Eigen.
* *
@ -123,20 +77,8 @@ void BTCSDiffusion::simulate1D(std::vector<double> &c, double bc_left,
b_vector[i] = -c[i - 1]; b_vector[i] = -c[i - 1];
// tripletList.push_back(T(A_line, i, (-1. - 2. * sx)));
// tripletList.push_back(T(A_line, i - 1, sx));
// tripletList.push_back(T(A_line, i + 1, sx));
// b[A_line] = -c[i - 1];
// A_line++;
} }
// std::cout << A_matrix << std::endl;
// Eigen::SparseMatrix<double> A(size, size);
// A.setFromTriplets(tripletList.begin(), tripletList.end());
Eigen::SparseLU<Eigen::SparseMatrix<double>, Eigen::COLAMDOrdering<int>> Eigen::SparseLU<Eigen::SparseMatrix<double>, Eigen::COLAMDOrdering<int>>
solver; solver;
solver.analyzePattern(A_matrix); solver.analyzePattern(A_matrix);