SXMatrix spy(const SXMatrix& A){
SXMatrix s(A.size1(),A.size2());
for(int i=0; i<A.size1(); ++i)
for(int j=0; j<A.size2(); ++j)
if(!A(i,j).toScalar()->isZero())
s(i,j) = 1;
return s;
}
void MaterialFitting::solveByNNLS(){
const SXMatrix M1 = assembleObjMatrix();
vector<SX> smooth_funs;
computeSmoothObjFunctions(smooth_funs);
SXMatrix obj_fun_m(M1.size1()*M1.size2()+smooth_funs.size(),1);
for (int i = 0; i < M1.size1(); ++i){
for (int j = 0; j < M1.size2(); ++j)
obj_fun_m.elem(i*M1.size2()+j,0) = M1.elem(i,j);
}
for (int i = 0; i < smooth_funs.size(); ++i){
obj_fun_m.elem(M1.size2()*M1.size2()+i,0) = smooth_funs[i];
}
VSX variable_x;
initAllVariables(variable_x);
CasADi::SXFunction g_fun = CasADi::SXFunction(variable_x,obj_fun_m);
g_fun.init();
VectorXd x0(variable_x.size()), b;
x0.setZero();
CASADI::evaluate(g_fun, x0, b);
b = -b;
MatrixXd J = CASADI::convert<double>(g_fun.jac());
assert_eq(J.rows(), b.size());
assert_eq(J.cols(), x0.size());
VectorXd x(b.size()), w(J.cols()), zz(J.rows());
VectorXi index(J.cols()*2);
getInitValue(x);
int exit_code = 0;
double residual = 1e-18;
nnls(&J(0,0), J.rows(), J.rows(), J.cols(),
&b[0], &x[0], &residual,
&w[0], &zz[0], &index[0], &exit_code);
INFO_LOG("residual: " << residual);
print_NNLS_exit_code(exit_code);
rlst.resize(x.size());
for (int i = 0; i < x.size(); ++i){
rlst[i] = x[i];
}
const MatrixXd H = J.transpose()*J;
SelfAdjointEigenSolver<MatrixXd> es;
es.compute(H);
cout << "The eigenvalues of H are: " << es.eigenvalues().transpose() << endl;
}
void fill(SXMatrix& mat, const SX& val){
if(val->isZero()) mat.makeEmpty(mat.size1(),mat.size2());
else mat.makeDense(mat.size1(),mat.size2(),val);
}
int getIntValue(const SXMatrix& ex, int i, int j) {
casadi_assert(i<ex.size1() && j<ex.size2());
return ex(i,j).toScalar().getIntValue();
}
int sxMatrixSize2(const SXMatrix & mat) {
return mat.size2();
}
