rwupdt.h
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1 namespace Eigen {
2 
3 namespace internal {
4 
5 template <typename Scalar>
6 void rwupdt(
10  Scalar alpha)
11 {
12  typedef DenseIndex Index;
13 
14  const Index n = r.cols();
15  eigen_assert(r.rows()>=n);
16  std::vector<JacobiRotation<Scalar> > givens(n);
17 
18  /* Local variables */
19  Scalar temp, rowj;
20 
21  /* Function Body */
22  for (Index j = 0; j < n; ++j) {
23  rowj = w[j];
24 
25  /* apply the previous transformations to */
26  /* r(i,j), i=0,1,...,j-1, and to w(j). */
27  for (Index i = 0; i < j; ++i) {
28  temp = givens[i].c() * r(i,j) + givens[i].s() * rowj;
29  rowj = -givens[i].s() * r(i,j) + givens[i].c() * rowj;
30  r(i,j) = temp;
31  }
32 
33  /* determine a givens rotation which eliminates w(j). */
34  givens[j].makeGivens(-r(j,j), rowj);
35 
36  if (rowj == 0.)
37  continue; // givens[j] is identity
38 
39  /* apply the current transformation to r(j,j), b(j), and alpha. */
40  r(j,j) = givens[j].c() * r(j,j) + givens[j].s() * rowj;
41  temp = givens[j].c() * b[j] + givens[j].s() * alpha;
42  alpha = -givens[j].s() * b[j] + givens[j].c() * alpha;
43  b[j] = temp;
44  }
45 }
46 
47 } // end namespace internal
48 
49 } // end namespace Eigen
iterative scaling algorithm to equilibrate rows and column norms in matrices
Definition: matrix.hpp:471
void rwupdt(Matrix< Scalar, Dynamic, Dynamic > &r, const Matrix< Scalar, Dynamic, 1 > &w, Matrix< Scalar, Dynamic, 1 > &b, Scalar alpha)
Definition: rwupdt.h:6
EIGEN_STRONG_INLINE Index rows() const
EIGEN_DEFAULT_DENSE_INDEX_TYPE DenseIndex
Definition: XprHelper.h:27
EIGEN_STRONG_INLINE Index cols() const
#define eigen_assert(x)


acado
Author(s): Milan Vukov, Rien Quirynen
autogenerated on Mon Jun 10 2019 12:35:03