| // Ceres Solver - A fast non-linear least squares minimizer |
| // Copyright 2017 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: sameeragarwal@google.com (Sameer Agarwal) |
| |
| #ifndef CERES_INTERNAL_FUNCTION_SAMPLE_H_ |
| #define CERES_INTERNAL_FUNCTION_SAMPLE_H_ |
| |
| #include <string> |
| #include "ceres/internal/eigen.h" |
| |
| namespace ceres { |
| namespace internal { |
| |
| // FunctionSample is used by the line search routines to store and |
| // communicate the value and (optionally) the gradient of the function |
| // being minimized. |
| // |
| // Since line search as the name implies happens along a certain |
| // line/direction. FunctionSample contains the information in two |
| // ways. Information in the ambient space and information along the |
| // direction of search. |
| struct FunctionSample { |
| FunctionSample(); |
| FunctionSample(double x, double value); |
| FunctionSample(double x, double value, double gradient); |
| |
| std::string ToDebugString() const; |
| |
| // x is the location of the sample along the search direction. |
| double x; |
| |
| // Let p be a point and d be the search direction then |
| // |
| // vector_x = p + x * d; |
| Vector vector_x; |
| // True if vector_x has been assigned a valid value. |
| bool vector_x_is_valid; |
| |
| // value = f(vector_x) |
| double value; |
| // True of the evaluation was successful and value is a finite |
| // number. |
| bool value_is_valid; |
| |
| // vector_gradient = Df(vector_position); |
| // |
| // D is the derivative operator. |
| Vector vector_gradient; |
| // True if the vector gradient was evaluated and the evaluation was |
| // successful (the value is a finite number). |
| bool vector_gradient_is_valid; |
| |
| // gradient = d.transpose() * vector_gradient |
| // |
| // where d is the search direction. |
| double gradient; |
| // True if the evaluation of the gradient was sucessful and the |
| // value is a finite number. |
| bool gradient_is_valid; |
| }; |
| |
| |
| |
| |
| } // namespace internal |
| } // namespace ceres |
| |
| #endif // CERES_INTERNAL_FUNCTION_SAMPLE_H_ |