annotate src/Modules/Features/ModuleGaussians.h @ 611:0fbaf443ec82

Carfac C++ revision 3, indluding more style improvements. The output structs are now classes again, and have separate storage methods for each output structure along with flags in the Run and RunSegment methods to allow for only storing NAPs if desired.

// Copyright 2008-2010, Thomas Walters
//
// AIM-C: A C++ implementation of the Auditory Image Model
// http://www.acousticscale.org/AIMC
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

/*! \file ModuleGaussians.h
 *  \brief Gaussian features
 */

/*! \author Thomas Walters <[e-mail]>
 *  \date created 2008/06/23
 *  \version \$Id$
 */

#ifndef AIMC_MODULES_FEATURES_GAUSSIANS_H_
#define AIMC_MODULES_FEATURES_GAUSSIANS_H_

#include <vector>

#include "Support/Module.h"
#include "Support/Parameters.h"
#include "Support/SignalBank.h"

namespace aimc {
using std::vector;
class ModuleGaussians : public Module {
 public:
  explicit ModuleGaussians(Parameters *pParam);
  virtual ~ModuleGaussians();

  /*! \brief Process a buffer
   */
  virtual void Process(const SignalBank &input);

 private:
  /*! \brief Reset the internal state of the module
   */
  virtual void ResetInternal();

  /*! \brief Prepare the module
   *  \param input Input signal
   *  \param output true on success false on failure
   */
  virtual bool InitializeInternal(const SignalBank &input);

  bool RubberGMMCore(int iNumComponents, bool bDoInit);

  /*! \brief Number of Gaussian Components
   */
  int m_iParamNComp;

  /*! \brief Constant variance of Gaussians
   */
  float m_fParamVar;

  /*! \brief posterior probability expansion exponent
   */
  float m_fParamPosteriorExp;

  /*! \brief Maximum Number of iterations
   */
  int m_iParamMaxIt;

  /*! \brief convergence criterion
   */
  float priors_converged_;

  /*! \brief Output component positions as well as amplitudes
   */
  bool output_positions_;

  /*! \brief Total number of values in the output
   */
  int output_component_count_;

  /*! \brief The amplitudes of the components (priors)
   */
  vector<float> m_pA;

  /*! \brief The means of the components (priors)
   */
  vector<float> m_pMu;

  /*! \brief The spectral profile of the incoming buffer
   */
  vector<float> m_pSpectralProfile;

  int m_iNumChannels;
};
}  // namespace aimc

#endif  // AIMC_MODULES_FEATURES_GAUSSIANS_H_