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- // Ceres Solver - A fast non-linear least squares minimizer
- // Copyright 2023 Google Inc. All rights reserved.
- // http://code.google.com/p/ceres-solver/
- //
- // Redistribution and use in source and binary forms, with or without
- // modification, are permitted provided that the following conditions are met:
- //
- // * Redistributions of source code must retain the above copyright notice,
- // this list of conditions and the following disclaimer.
- // * Redistributions in binary form must reproduce the above copyright notice,
- // this list of conditions and the following disclaimer in the documentation
- // and/or other materials provided with the distribution.
- // * Neither the name of Google Inc. nor the names of its contributors may be
- // used to endorse or promote products derived from this software without
- // specific prior written permission.
- //
- // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
- // AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
- // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
- // ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
- // LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
- // CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
- // SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
- // INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
- // CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
- // ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
- // POSSIBILITY OF SUCH DAMAGE.
- //
- // Author: vitus@google.com (Michael Vitus)
- #ifndef CERES_PUBLIC_INTERNAL_HOUSEHOLDER_VECTOR_H_
- #define CERES_PUBLIC_INTERNAL_HOUSEHOLDER_VECTOR_H_
- #include "Eigen/Core"
- #include "glog/logging.h"
- namespace ceres::internal {
- // Algorithm 5.1.1 from 'Matrix Computations' by Golub et al. (Johns Hopkins
- // Studies in Mathematical Sciences) but using the nth element of the input
- // vector as pivot instead of first. This computes the vector v with v(n) = 1
- // and beta such that H = I - beta * v * v^T is orthogonal and
- // H * x = ||x||_2 * e_n.
- //
- // NOTE: Some versions of MSVC have trouble deducing the type of v if
- // you do not specify all the template arguments explicitly.
- template <typename XVectorType, typename Scalar, int N>
- void ComputeHouseholderVector(const XVectorType& x,
- Eigen::Matrix<Scalar, N, 1>* v,
- Scalar* beta) {
- CHECK(beta != nullptr);
- CHECK(v != nullptr);
- CHECK_GT(x.rows(), 1);
- CHECK_EQ(x.rows(), v->rows());
- Scalar sigma = x.head(x.rows() - 1).squaredNorm();
- *v = x;
- (*v)(v->rows() - 1) = Scalar(1.0);
- *beta = Scalar(0.0);
- const Scalar& x_pivot = x(x.rows() - 1);
- if (sigma <= Scalar(std::numeric_limits<double>::epsilon())) {
- if (x_pivot < Scalar(0.0)) {
- *beta = Scalar(2.0);
- }
- return;
- }
- const Scalar mu = sqrt(x_pivot * x_pivot + sigma);
- Scalar v_pivot = Scalar(1.0);
- if (x_pivot <= Scalar(0.0)) {
- v_pivot = x_pivot - mu;
- } else {
- v_pivot = -sigma / (x_pivot + mu);
- }
- *beta = Scalar(2.0) * v_pivot * v_pivot / (sigma + v_pivot * v_pivot);
- v->head(v->rows() - 1) /= v_pivot;
- }
- template <typename XVectorType, typename Derived>
- typename Derived::PlainObject ApplyHouseholderVector(
- const XVectorType& y,
- const Eigen::MatrixBase<Derived>& v,
- const typename Derived::Scalar& beta) {
- return (y - v * (beta * (v.transpose() * y)));
- }
- } // namespace ceres::internal
- #endif // CERES_PUBLIC_INTERNAL_HOUSEHOLDER_VECTOR_H_
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