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70 lines
1.9 KiB
70 lines
1.9 KiB
namespace Eigen {
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namespace internal {
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template <typename Scalar>
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void covar(
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Matrix< Scalar, Dynamic, Dynamic > &r,
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const VectorXi &ipvt,
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Scalar tol = std::sqrt(NumTraits<Scalar>::epsilon()) )
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{
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using std::abs;
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typedef DenseIndex Index;
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/* Local variables */
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Index i, j, k, l, ii, jj;
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bool sing;
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Scalar temp;
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/* Function Body */
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const Index n = r.cols();
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const Scalar tolr = tol * abs(r(0,0));
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Matrix< Scalar, Dynamic, 1 > wa(n);
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eigen_assert(ipvt.size()==n);
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/* form the inverse of r in the full upper triangle of r. */
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l = -1;
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for (k = 0; k < n; ++k)
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if (abs(r(k,k)) > tolr) {
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r(k,k) = 1. / r(k,k);
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for (j = 0; j <= k-1; ++j) {
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temp = r(k,k) * r(j,k);
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r(j,k) = 0.;
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r.col(k).head(j+1) -= r.col(j).head(j+1) * temp;
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}
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l = k;
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}
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/* form the full upper triangle of the inverse of (r transpose)*r */
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/* in the full upper triangle of r. */
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for (k = 0; k <= l; ++k) {
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for (j = 0; j <= k-1; ++j)
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r.col(j).head(j+1) += r.col(k).head(j+1) * r(j,k);
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r.col(k).head(k+1) *= r(k,k);
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}
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/* form the full lower triangle of the covariance matrix */
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/* in the strict lower triangle of r and in wa. */
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for (j = 0; j < n; ++j) {
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jj = ipvt[j];
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sing = j > l;
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for (i = 0; i <= j; ++i) {
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if (sing)
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r(i,j) = 0.;
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ii = ipvt[i];
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if (ii > jj)
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r(ii,jj) = r(i,j);
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if (ii < jj)
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r(jj,ii) = r(i,j);
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}
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wa[jj] = r(j,j);
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}
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/* symmetrize the covariance matrix in r. */
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r.topLeftCorner(n,n).template triangularView<StrictlyUpper>() = r.topLeftCorner(n,n).transpose();
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r.diagonal() = wa;
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}
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} // end namespace internal
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} // end namespace Eigen
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