internal/ceres/residual_block.h

// 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/
//
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// modification, are permitted provided that the following conditions are met:
//
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//   this list of conditions and the following disclaimer.
// * Redistributions in binary form must reproduce the above copyright notice,
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//
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// 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_