|  | // 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 | 
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|  | // CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF | 
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|  | // 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 "absl/log/check.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_ |