// 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 "ceres/manifold_adapter.h"
#include "glog/logging.h"

namespace ceres {

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

GradientProblem::GradientProblem(FirstOrderFunction* function,
                                 LocalParameterization* parameterization)
    : function_(function),
      parameterization_(parameterization),
      scratch_(new double[function_->NumParameters()]) {
  CHECK(function != nullptr);
  if (parameterization != nullptr) {
    manifold_.reset(new internal::ManifoldAdapter(parameterization_.get()));
  } else {
    manifold_.reset(new EuclideanManifold(function_->NumParameters()));
  }
  CHECK_EQ(function_->NumParameters(), manifold_->AmbientSize());
}

GradientProblem::GradientProblem(FirstOrderFunction* function,
                                 Manifold* manifold)
    : function_(function),
      manifold_(manifold),
      scratch_(new double[function_->NumParameters()]) {
  CHECK(function != nullptr);
  if (manifold == nullptr) {
    manifold_.reset(new EuclideanManifold(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