// Ceres Solver - A fast non-linear least squares minimizer // Copyright 2023 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) // keir@google.m (Keir Mierle) // // This is the interface through which the least squares solver accesses the // residual and Jacobian of the least squares problem. Users are expected to // subclass CostFunction to define their own terms in the least squares problem. // // It is recommended that users define templated residual functors for use as // arguments for AutoDiffCostFunction (see autodiff_cost_function.h), instead of // directly implementing the CostFunction interface. This often results in both // shorter code and faster execution than hand-coded derivatives. However, // specialized cases may demand direct implementation of the lower-level // CostFunction interface; for example, this is true when calling legacy code // which is not templated on numeric types. #ifndef CERES_PUBLIC_COST_FUNCTION_H_ #define CERES_PUBLIC_COST_FUNCTION_H_ #include #include #include "ceres/internal/disable_warnings.h" #include "ceres/internal/export.h" namespace ceres { // This class implements the computation of the cost (a.k.a. residual) terms as // a function of the input (control) variables, and is the interface for users // to describe their least squares problem to Ceres. In other words, this is the // modeling layer between users and the Ceres optimizer. The signature of the // function (number and sizes of input parameter blocks and number of outputs) // is stored in parameter_block_sizes_ and num_residuals_ respectively. User // code inheriting from this class is expected to set these two members with the // corresponding accessors. This information will be verified by the Problem // when added with AddResidualBlock(). class CERES_EXPORT CostFunction { public: CostFunction(); CostFunction(const CostFunction&) = delete; void operator=(const CostFunction&) = delete; virtual ~CostFunction(); // Inputs: // // parameters is an array of pointers to arrays containing the // various parameter blocks. parameters has the same number of // elements as parameter_block_sizes_. Parameter blocks are in the // same order as parameter_block_sizes_.i.e., // // parameters_[i] = double[parameter_block_sizes_[i]] // // Outputs: // // residuals is an array of size num_residuals_. // // jacobians is an array of size parameter_block_sizes_ containing // pointers to storage for jacobian blocks corresponding to each // parameter block. Jacobian blocks are in the same order as // parameter_block_sizes, i.e. jacobians[i], is an // array that contains num_residuals_* parameter_block_sizes_[i] // elements. Each jacobian block is stored in row-major order, i.e., // // jacobians[i][r*parameter_block_size_[i] + c] = // d residual[r] / d parameters[i][c] // // If jacobians is nullptr, then no derivatives are returned; this is // the case when computing cost only. If jacobians[i] is nullptr, then // the jacobian block corresponding to the i'th parameter block must // not to be returned. // // The return value indicates whether the computation of the // residuals and/or jacobians was successful or not. // // This can be used to communicate numerical failures in jacobian // computations for instance. // // A more interesting and common use is to impose constraints on the // parameters. If the initial values of the parameter blocks satisfy // the constraints, then returning false whenever the constraints // are not satisfied will prevent the solver from moving into the // infeasible region. This is not a very sophisticated mechanism for // enforcing constraints, but is often good enough. // // Note that it is important that the initial values of the // parameter block must be feasible, otherwise the solver will // declare a numerical problem at iteration 0. virtual bool Evaluate(double const* const* parameters, double* residuals, double** jacobians) const = 0; const std::vector& parameter_block_sizes() const { return parameter_block_sizes_; } int num_residuals() const { return num_residuals_; } protected: std::vector* mutable_parameter_block_sizes() { return ¶meter_block_sizes_; } void set_num_residuals(int num_residuals) { num_residuals_ = num_residuals; } private: // Cost function signature metadata: number of inputs & their sizes, // number of outputs (residuals). std::vector parameter_block_sizes_; int num_residuals_; }; } // namespace ceres #include "ceres/internal/reenable_warnings.h" #endif // CERES_PUBLIC_COST_FUNCTION_H_