// Ceres Solver - A fast non-linear least squares minimizer // Copyright 2015 Google Inc. All rights reserved. // http://ceres-solver.org/ // // 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: moll.markus@arcor.de (Markus Moll) // sameeragarwal@google.com (Sameer Agarwal) #ifndef CERES_INTERNAL_POLYNOMIAL_SOLVER_H_ #define CERES_INTERNAL_POLYNOMIAL_SOLVER_H_ #include #include "ceres/internal/eigen.h" #include "ceres/internal/port.h" namespace ceres { namespace internal { struct FunctionSample; // All polynomials are assumed to be the form // // sum_{i=0}^N polynomial(i) x^{N-i}. // // and are given by a vector of coefficients of size N + 1. // Evaluate the polynomial at x using the Horner scheme. inline double EvaluatePolynomial(const Vector& polynomial, double x) { double v = 0.0; for (int i = 0; i < polynomial.size(); ++i) { v = v * x + polynomial(i); } return v; } // Use the companion matrix eigenvalues to determine the roots of the // polynomial. // // This function returns true on success, false otherwise. // Failure indicates that the polynomial is invalid (of size 0) or // that the eigenvalues of the companion matrix could not be computed. // On failure, a more detailed message will be written to LOG(ERROR). // If real is not NULL, the real parts of the roots will be returned in it. // Likewise, if imaginary is not NULL, imaginary parts will be returned in it. bool FindPolynomialRoots(const Vector& polynomial, Vector* real, Vector* imaginary); // Return the derivative of the given polynomial. It is assumed that // the input polynomial is at least of degree zero. Vector DifferentiatePolynomial(const Vector& polynomial); // Find the minimum value of the polynomial in the interval [x_min, // x_max]. The minimum is obtained by computing all the roots of the // derivative of the input polynomial. All real roots within the // interval [x_min, x_max] are considered as well as the end points // x_min and x_max. Since polynomials are differentiable functions, // this ensures that the true minimum is found. void MinimizePolynomial(const Vector& polynomial, double x_min, double x_max, double* optimal_x, double* optimal_value); // Given a set of function value and/or gradient samples, find a // polynomial whose value and gradients are exactly equal to the ones // in samples. // // Generally speaking, // // degree = # values + # gradients - 1 // // Of course its possible to sample a polynomial any number of times, // in which case, generally speaking the spurious higher order // coefficients will be zero. Vector FindInterpolatingPolynomial(const std::vector& samples); // Interpolate the function described by samples with a polynomial, // and minimize it on the interval [x_min, x_max]. Depending on the // input samples, it is possible that the interpolation or the root // finding algorithms may fail due to numerical difficulties. But the // function is guaranteed to return its best guess of an answer, by // considering the samples and the end points as possible solutions. void MinimizeInterpolatingPolynomial(const std::vector& samples, double x_min, double x_max, double* optimal_x, double* optimal_value); } // namespace internal } // namespace ceres #endif // CERES_INTERNAL_POLYNOMIAL_SOLVER_H_