gradient_problem.cc 3.3 KB

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  1. // Ceres Solver - A fast non-linear least squares minimizer
  2. // Copyright 2023 Google Inc. All rights reserved.
  3. // http://ceres-solver.org/
  4. //
  5. // Redistribution and use in source and binary forms, with or without
  6. // modification, are permitted provided that the following conditions are met:
  7. //
  8. // * Redistributions of source code must retain the above copyright notice,
  9. // this list of conditions and the following disclaimer.
  10. // * Redistributions in binary form must reproduce the above copyright notice,
  11. // this list of conditions and the following disclaimer in the documentation
  12. // and/or other materials provided with the distribution.
  13. // * Neither the name of Google Inc. nor the names of its contributors may be
  14. // used to endorse or promote products derived from this software without
  15. // specific prior written permission.
  16. //
  17. // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
  18. // AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
  19. // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
  20. // ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
  21. // LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
  22. // CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
  23. // SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
  24. // INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
  25. // CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
  26. // ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
  27. // POSSIBILITY OF SUCH DAMAGE.
  28. //
  29. // Author: sameeragarwal@google.com (Sameer Agarwal)
  30. #include "ceres/gradient_problem.h"
  31. #include <memory>
  32. #include "glog/logging.h"
  33. namespace ceres {
  34. GradientProblem::GradientProblem(FirstOrderFunction* function)
  35. : function_(function),
  36. manifold_(std::make_unique<EuclideanManifold<DYNAMIC>>(
  37. function_->NumParameters())),
  38. scratch_(new double[function_->NumParameters()]) {
  39. CHECK(function != nullptr);
  40. }
  41. GradientProblem::GradientProblem(FirstOrderFunction* function,
  42. Manifold* manifold)
  43. : function_(function), scratch_(new double[function_->NumParameters()]) {
  44. CHECK(function != nullptr);
  45. if (manifold != nullptr) {
  46. manifold_.reset(manifold);
  47. } else {
  48. manifold_ = std::make_unique<EuclideanManifold<DYNAMIC>>(
  49. function_->NumParameters());
  50. }
  51. CHECK_EQ(function_->NumParameters(), manifold_->AmbientSize());
  52. }
  53. int GradientProblem::NumParameters() const {
  54. return function_->NumParameters();
  55. }
  56. int GradientProblem::NumTangentParameters() const {
  57. return manifold_->TangentSize();
  58. }
  59. bool GradientProblem::Evaluate(const double* parameters,
  60. double* cost,
  61. double* gradient) const {
  62. if (gradient == nullptr) {
  63. return function_->Evaluate(parameters, cost, nullptr);
  64. }
  65. return (function_->Evaluate(parameters, cost, scratch_.get()) &&
  66. manifold_->RightMultiplyByPlusJacobian(
  67. parameters, 1, scratch_.get(), gradient));
  68. }
  69. bool GradientProblem::Plus(const double* x,
  70. const double* delta,
  71. double* x_plus_delta) const {
  72. return manifold_->Plus(x, delta, x_plus_delta);
  73. }
  74. } // namespace ceres