Tutorial_sparse_example_details.cpp
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1 #include <Eigen/Sparse>
2 #include <vector>
3 #include <QImage>
4 
5 typedef Eigen::SparseMatrix<double> SpMat; // declares a column-major sparse matrix type of double
7 
8 void insertCoefficient(int id, int i, int j, double w, std::vector<T>& coeffs,
9  Eigen::VectorXd& b, const Eigen::VectorXd& boundary)
10 {
11  int n = int(boundary.size());
12  int id1 = i+j*n;
13 
14  if(i==-1 || i==n) b(id) -= w * boundary(j); // constrained coefficient
15  else if(j==-1 || j==n) b(id) -= w * boundary(i); // constrained coefficient
16  else coeffs.push_back(T(id,id1,w)); // unknown coefficient
17 }
18 
19 void buildProblem(std::vector<T>& coefficients, Eigen::VectorXd& b, int n)
20 {
21  b.setZero();
22  Eigen::ArrayXd boundary = Eigen::ArrayXd::LinSpaced(n, 0,M_PI).sin().pow(2);
23  for(int j=0; j<n; ++j)
24  {
25  for(int i=0; i<n; ++i)
26  {
27  int id = i+j*n;
28  insertCoefficient(id, i-1,j, -1, coefficients, b, boundary);
29  insertCoefficient(id, i+1,j, -1, coefficients, b, boundary);
30  insertCoefficient(id, i,j-1, -1, coefficients, b, boundary);
31  insertCoefficient(id, i,j+1, -1, coefficients, b, boundary);
32  insertCoefficient(id, i,j, 4, coefficients, b, boundary);
33  }
34  }
35 }
36 
37 void saveAsBitmap(const Eigen::VectorXd& x, int n, const char* filename)
38 {
39  Eigen::Array<unsigned char,Eigen::Dynamic,Eigen::Dynamic> bits = (x*255).cast<unsigned char>();
40  QImage img(bits.data(), n,n,QImage::Format_Indexed8);
41  img.setColorCount(256);
42  for(int i=0;i<256;i++) img.setColor(i,qRgb(i,i,i));
43  img.save(filename);
44 }
Array< int, 3, 1 > b
int n
RowVector3d w
Eigen::SparseMatrix< double > SpMat
void buildProblem(std::vector< T > &coefficients, Eigen::VectorXd &b, int n)
void insertCoefficient(int id, int i, int j, double w, std::vector< T > &coeffs, Eigen::VectorXd &b, const Eigen::VectorXd &boundary)
Eigen::Triplet< double > T
void saveAsBitmap(const Eigen::VectorXd &x, int n, const char *filename)
General-purpose arrays with easy API for coefficient-wise operations.
Definition: Array.h:49
static EIGEN_DEPRECATED const RandomAccessLinSpacedReturnType LinSpaced(Sequential_t, Index size, const Scalar &low, const Scalar &high)
EIGEN_CONSTEXPR Index size() const EIGEN_NOEXCEPT
Definition: EigenBase.h:69
The matrix class, also used for vectors and row-vectors.
Definition: Matrix.h:182
const Scalar * data() const
std::ptrdiff_t j