sparse_optimizer_terminate_action.cpp

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// g2o - General Graph Optimization
// Copyright (C) 2011 R. Kuemmerle, G. Grisetti, H. Strasdat, W. Burgard
// All rights reserved.
//
// 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.
//
// 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
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// TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
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#include "sparse_optimizer_terminate_action.h"
 
#include <cassert>
#include <limits>
 
#include "sparse_optimizer.h"
 
namespace g2o {
 
SparseOptimizerTerminateAction::SparseOptimizerTerminateAction()
    : HyperGraphAction(),
      _gainThreshold(cst(1e-6)),
      _lastChi(0),
      _auxTerminateFlag(false),
      _maxIterations(std::numeric_limits<int>::max()) {}
 
void SparseOptimizerTerminateAction::setGainThreshold(double gainThreshold) {
  _gainThreshold = gainThreshold;
}
 
HyperGraphAction* SparseOptimizerTerminateAction::operator()(
    const HyperGraph* graph, Parameters* parameters) {
  assert(dynamic_cast<const SparseOptimizer*>(graph) &&
         "graph is not a SparseOptimizer");
  assert(dynamic_cast<HyperGraphAction::ParametersIteration*>(parameters) &&
         "error casting parameters");
 
  const SparseOptimizer* optimizer = static_cast<const SparseOptimizer*>(graph);
  HyperGraphAction::ParametersIteration* params =
      static_cast<HyperGraphAction::ParametersIteration*>(parameters);
 
  const_cast<SparseOptimizer*>(optimizer)->computeActiveErrors();
  if (params->iteration < 0) {
    // let the optimizer run for at least one iteration
    // Hence, we reset the stop flag
    setOptimizerStopFlag(optimizer, false);
  } else if (params->iteration == 0) {
    // first iteration, just store the chi2 value
    _lastChi = optimizer->activeRobustChi2();
  } else {
    // compute the gain and stop the optimizer in case the
    // gain is below the threshold or we reached the max
    // number of iterations
    bool stopOptimizer = false;
    if (params->iteration < _maxIterations) {
      double currentChi = optimizer->activeRobustChi2();
      double gain = (_lastChi - currentChi) / currentChi;
      _lastChi = currentChi;
      if (gain >= 0 && gain < _gainThreshold) stopOptimizer = true;
    } else {
      stopOptimizer = true;
    }
    if (stopOptimizer) {  // tell the optimizer to stop
      setOptimizerStopFlag(optimizer, true);
    }
  }
  return this;
}
 
void SparseOptimizerTerminateAction::setMaxIterations(int maxit) {
  _maxIterations = maxit;
}
 
void SparseOptimizerTerminateAction::setOptimizerStopFlag(
    const SparseOptimizer* optimizer, bool stop) {
  if (optimizer->forceStopFlag()) {
    *(optimizer->forceStopFlag()) = stop;
  } else {
    _auxTerminateFlag = stop;
    const_cast<SparseOptimizer*>(optimizer)->setForceStopFlag(
        &_auxTerminateFlag);
  }
}
 
}  // namespace g2o