#include <Eigen/Sparse>
#include <vector>
#include <QImage>
typedef Eigen::SparseMatrix<double> SpMat; // declares a column-major sparse matrix type of double
void insertCoefficient(int id, int i, int j, double w, std::vector<T>& coeffs,
Eigen::VectorXd& b, const Eigen::VectorXd& boundary)
{
int n = int(boundary.size());
int id1 = i+j*n;
if(i==-1 || i==n) b(id) -= w * boundary(j); // constrained coefficient
else if(j==-1 || j==n) b(id) -= w * boundary(i); // constrained coefficient
else coeffs.push_back(T(id,id1,w)); // unknown coefficient
}
void buildProblem(std::vector<T>& coefficients, Eigen::VectorXd& b, int n)
{
b.setZero();
Eigen::ArrayXd boundary = Eigen::ArrayXd::LinSpaced(n, 0,M_PI).sin().pow(2);
for(int j=0; j<n; ++j)
{
for(int i=0; i<n; ++i)
{
int id = i+j*n;
insertCoefficient(id, i-1,j, -1, coefficients, b, boundary);
insertCoefficient(id, i+1,j, -1, coefficients, b, boundary);
insertCoefficient(id, i,j-1, -1, coefficients, b, boundary);
insertCoefficient(id, i,j+1, -1, coefficients, b, boundary);
insertCoefficient(id, i,j, 4, coefficients, b, boundary);
}
}
}
void saveAsBitmap(const Eigen::VectorXd& x, int n, const char* filename)
{
QImage img(bits.data(), n,n,QImage::Format_Indexed8);
img.setColorCount(256);
for(int i=0;i<256;i++) img.setColor(i,qRgb(i,i,i));
img.save(filename);
}
w
RowVector3d w
Definition: Matrix_resize_int.cpp:3
gtsam.examples.DogLegOptimizerExample.int
int
Definition: DogLegOptimizerExample.py:111
insertCoefficient
void insertCoefficient(int id, int i, int j, double w, std::vector< T > &coeffs, Eigen::VectorXd &b, const Eigen::VectorXd &boundary)
Definition: Tutorial_sparse_example_details.cpp:8
Eigen::SparseMatrix< double >
buildProblem
void buildProblem(std::vector< T > &coefficients, Eigen::VectorXd &b, int n)
Definition: Tutorial_sparse_example_details.cpp:19
Eigen::internal::bits
Map< const Array< unsigned char, sizeof(T), 1 > > bits(const T &x)
Definition: packetmath_test_shared.h:28
b
Scalar * b
Definition: benchVecAdd.cpp:17
x
set noclip points set clip one set noclip two set bar set border lt lw set xdata set ydata set zdata set x2data set y2data set boxwidth set dummy x
Definition: gnuplot_common_settings.hh:12
Eigen::Array
General-purpose arrays with easy API for coefficient-wise operations.
Definition: Array.h:45
T
Eigen::Triplet< double > T
Definition: Tutorial_sparse_example.cpp:6
n
int n
Definition: BiCGSTAB_simple.cpp:1
j
std::ptrdiff_t j
Definition: tut_arithmetic_redux_minmax.cpp:2
relicense.filename
filename
Definition: relicense.py:57
SpMat
Eigen::SparseMatrix< double > SpMat
Definition: Tutorial_sparse_example.cpp:5
Eigen::Triplet< double >
saveAsBitmap
void saveAsBitmap(const Eigen::VectorXd &x, int n, const char *filename)
Definition: Tutorial_sparse_example_details.cpp:37
M_PI
#define M_PI
Definition: mconf.h:117
i
int i
Definition: BiCGSTAB_step_by_step.cpp:9


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autogenerated on Sat Nov 16 2024 04:09:56