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Austin Schuh70cc9552019-01-21 19:46:48 -08001// Ceres Solver - A fast non-linear least squares minimizer
2// Copyright 2015 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
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28//
29// Author: sameeragarwal@google.com (Sameer Agarwal)
30
31#include "ceres/gradient_problem.h"
32#include "ceres/local_parameterization.h"
33#include "glog/logging.h"
34
35namespace ceres {
36
37GradientProblem::GradientProblem(FirstOrderFunction* function)
38 : function_(function),
39 parameterization_(
40 new IdentityParameterization(function_->NumParameters())),
41 scratch_(new double[function_->NumParameters()]) {
42}
43
44GradientProblem::GradientProblem(FirstOrderFunction* function,
45 LocalParameterization* parameterization)
46 : function_(function),
47 parameterization_(parameterization),
48 scratch_(new double[function_->NumParameters()]) {
49 CHECK_EQ(function_->NumParameters(), parameterization_->GlobalSize());
50}
51
52int GradientProblem::NumParameters() const {
53 return function_->NumParameters();
54}
55
56int GradientProblem::NumLocalParameters() const {
57 return parameterization_->LocalSize();
58}
59
60
61bool GradientProblem::Evaluate(const double* parameters,
62 double* cost,
63 double* gradient) const {
64 if (gradient == NULL) {
65 return function_->Evaluate(parameters, cost, NULL);
66 }
67
68 return (function_->Evaluate(parameters, cost, scratch_.get()) &&
69 parameterization_->MultiplyByJacobian(parameters,
70 1,
71 scratch_.get(),
72 gradient));
73}
74
75bool GradientProblem::Plus(const double* x,
76 const double* delta,
77 double* x_plus_delta) const {
78 return parameterization_->Plus(x, delta, x_plus_delta);
79}
80
81} // namespace ceres