internal/ceres/gradient_problem.cc

// Ceres Solver - A fast non-linear least squares minimizer
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// Author: sameeragarwal@google.com (Sameer Agarwal)

#include "ceres/gradient_problem.h"

#include <memory>

#include "glog/logging.h"

namespace ceres {

GradientProblem::GradientProblem(FirstOrderFunction* function)
    : function_(function),
      manifold_(std::make_unique<EuclideanManifold<DYNAMIC>>(
          function_->NumParameters())),
      scratch_(new double[function_->NumParameters()]) {
  CHECK(function != nullptr);
}

GradientProblem::GradientProblem(FirstOrderFunction* function,
                                 Manifold* manifold)
    : function_(function), scratch_(new double[function_->NumParameters()]) {
  CHECK(function != nullptr);
  if (manifold != nullptr) {
    manifold_.reset(manifold);
  } else {
    manifold_ = std::make_unique<EuclideanManifold<DYNAMIC>>(
        function_->NumParameters());
  }
  CHECK_EQ(function_->NumParameters(), manifold_->AmbientSize());
}

int GradientProblem::NumParameters() const {
  return function_->NumParameters();
}

int GradientProblem::NumTangentParameters() const {
  return manifold_->TangentSize();
}

bool GradientProblem::Evaluate(const double* parameters,
                               double* cost,
                               double* gradient) const {
  if (gradient == nullptr) {
    return function_->Evaluate(parameters, cost, nullptr);
  }

  return (function_->Evaluate(parameters, cost, scratch_.get()) &&
          manifold_->RightMultiplyByPlusJacobian(
              parameters, 1, scratch_.get(), gradient));
}

bool GradientProblem::Plus(const double* x,
                           const double* delta,
                           double* x_plus_delta) const {
  return manifold_->Plus(x, delta, x_plus_delta);
}

}  // namespace ceres