| // 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: sameeragarwal@google.com (Sameer Agarwal) |
| |
| #include "ceres/gradient_problem.h" |
| #include "ceres/local_parameterization.h" |
| #include "glog/logging.h" |
| |
| namespace ceres { |
| |
| GradientProblem::GradientProblem(FirstOrderFunction* function) |
| : function_(function), |
| parameterization_( |
| new IdentityParameterization(function_->NumParameters())), |
| scratch_(new double[function_->NumParameters()]) { |
| } |
| |
| GradientProblem::GradientProblem(FirstOrderFunction* function, |
| LocalParameterization* parameterization) |
| : function_(function), |
| parameterization_(parameterization), |
| scratch_(new double[function_->NumParameters()]) { |
| CHECK_EQ(function_->NumParameters(), parameterization_->GlobalSize()); |
| } |
| |
| int GradientProblem::NumParameters() const { |
| return function_->NumParameters(); |
| } |
| |
| int GradientProblem::NumLocalParameters() const { |
| return parameterization_->LocalSize(); |
| } |
| |
| |
| bool GradientProblem::Evaluate(const double* parameters, |
| double* cost, |
| double* gradient) const { |
| if (gradient == NULL) { |
| return function_->Evaluate(parameters, cost, NULL); |
| } |
| |
| return (function_->Evaluate(parameters, cost, scratch_.get()) && |
| parameterization_->MultiplyByJacobian(parameters, |
| 1, |
| scratch_.get(), |
| gradient)); |
| } |
| |
| bool GradientProblem::Plus(const double* x, |
| const double* delta, |
| double* x_plus_delta) const { |
| return parameterization_->Plus(x, delta, x_plus_delta); |
| } |
| |
| } // namespace ceres |