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// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2010, 2011, 2012 Google Inc. All rights reserved.
// http://code.google.com/p/ceres-solver/
//
// 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)
// keir@google.com (Keir Mierle)
//
// Purpose : Class and struct definitions for parameter and residual blocks.
#ifndef CERES_INTERNAL_RESIDUAL_BLOCK_H_
#define CERES_INTERNAL_RESIDUAL_BLOCK_H_
#include <vector>
#include "ceres/cost_function.h"
#include "ceres/internal/port.h"
#include "ceres/internal/scoped_ptr.h"
#include "ceres/types.h"
namespace ceres {
class LossFunction;
namespace internal {
class ParameterBlock;
// A term in the least squares problem. The mathematical form of each term in
// the overall least-squares cost function is:
//
// 1
// --- loss_function( || cost_function(block1, block2, ...) ||^2 ),
// 2
//
// Storing the cost function and the loss function separately permits optimizing
// the problem with standard non-linear least techniques, without requiring a
// more general non-linear solver.
//
// The residual block stores pointers to but does not own the cost functions,
// loss functions, and parameter blocks.
class ResidualBlock {
public:
ResidualBlock(const CostFunction* cost_function,
const LossFunction* loss_function,
const vector<ParameterBlock*>& parameter_blocks);
// Evaluates the residual term, storing the scalar cost in *cost, the residual
// components in *residuals, and the jacobians between the parameters and
// residuals in jacobians[i], in row-major order. If residuals is NULL, the
// residuals are not computed. If jacobians is NULL, no jacobians are
// computed. If jacobians[i] is NULL, then the jacobian for that parameter is
// not computed.
//
// Evaluate needs scratch space which must be supplied by the caller via
// scratch. The array should have at least NumScratchDoublesForEvaluate()
// space available.
//
// The return value indicates the success or failure. If the function returns
// false, the caller should expect the the output memory locations to have
// been modified.
//
// The returned cost and jacobians have had robustification and local
// parameterizations applied already; for example, the jacobian for a
// 4-dimensional quaternion parameter using the "QuaternionParameterization"
// is num_residuals by 3 instead of num_residuals by 4.
bool Evaluate(double* cost,
double* residuals,
double** jacobians,
double* scratch) const;
const CostFunction* cost_function() const { return cost_function_; }
const LossFunction* loss_function() const { return loss_function_; }
// Access the parameter blocks for this residual. The array has size
// NumParameterBlocks().
ParameterBlock* const* parameter_blocks() const {
return parameter_blocks_.get();
}
// Number of variable blocks that this residual term depends on.
int NumParameterBlocks() const {
return cost_function_->parameter_block_sizes().size();
}
// The size of the residual vector returned by this residual function.
int NumResiduals() const { return cost_function_->num_residuals(); }
// The minimum amount of scratch space needed to pass to Evaluate().
int NumScratchDoublesForEvaluate() const;
private:
const CostFunction* cost_function_;
const LossFunction* loss_function_;
scoped_array<ParameterBlock*> parameter_blocks_;
};
} // namespace internal
} // namespace ceres
#endif // CERES_INTERNAL_RESIDUAL_BLOCK_H_
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