analyzer_sparx.h

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/*
 * Author: Chao Yang
 * Copyright (c) 2000-2006
 *
 * This software is issued under a joint BSD/GNU license. You may use the
 * source code in this file under either license. However, note that the
 * complete EMAN2 and SPARX software packages have some GPL dependencies,
 * so you are responsible for compliance with the licenses of these packages
 * if you opt to use BSD licensing. The warranty disclaimer below holds
 * in either instance.
 *
 * This complete copyright notice must be included in any revised version of the
 * source code. Additional authorship citations may be added, but existing
 * author citations must be preserved.
 *
 * This program is free software; you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation; either version 2 of the License, or
 * (at your option) any later version.
 *
 * This program is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
 * GNU General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with this program; if not, write to the Free Software
 * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
 *
 */

#ifndef eman_analyzer_sparx_h__
#define eman_analyzer_sparx_h__

#include "analyzer.h"

namespace EMAN
{
        class PCAsmall : public Analyzer
        {
          public:
                PCAsmall() : mask(0), nvec(0) {}
                
//              virtual int insert_image(EMData * image) {
//              images.push_back(image);
//              return 0;
//
//}
                virtual int insert_image(EMData * image);
                
                virtual vector<EMData*> analyze();
                
                string get_name() const
                {
                        return "pca";
                }               
                
                string get_desc() const
                {
                        return "Principal component analysis";
                }
                
                static Analyzer * NEW()
                {
                        return new PCAsmall();
                }
                
                void set_params(const Dict & new_params);

//              void set_params(const Dict & new_params)
//              {
//                      params = new_params;
//                      mask = params["mask"];
//                      nvec = params["nvec"];
//              }

                TypeDict get_param_types() const
                {
                        TypeDict d;
                        d.put("mask", EMObject::EMDATA, "mask image");
                        d.put("nvec", EMObject::INT, "number of desired principal components");
                        return d;
                }
                
          protected:
                EMData * mask;
                int nvec;       //number of desired principal components

          private:
                float *covmat; // covariance matrix 
                int   ncov;    // dimension of the covariance matrix
                int   nimages; // number of images
                float *eigval; // array for storing computed eigvalues
        }; 

        //-------------------------------------------------------------

        class PCAlarge : public Analyzer
        {
          public:
                PCAlarge() : mask(0), nvec(0) {}
                
                virtual int insert_image(EMData * image);
                
                virtual vector<EMData*> analyze();
                
                string get_name() const
                {
                        return "pca_large";
                }               
                
                string get_desc() const
                {
                        return "Principal component analysis";
                }
                
                static Analyzer * NEW()
                {
                        return new PCAlarge();
                }
                
                void set_params(const Dict & new_params);

                int Lanczos(const string &maskedimages, int *kstep, 
                            float  *diag, float *subdiag, float *V, 
                            float  *beta);


                TypeDict get_param_types() const
                {
                        TypeDict d;
                        d.put("mask", EMObject::EMDATA, "mask image");
                        d.put("nvec", EMObject::INT, "number of desired principal components");
                        return d;
                }
                
          protected:
                EMData * mask;
                int nvec;       //number of desired principal components

          private:
                int   ncov;    // dimension of the covariance matrix
                int   nimages; // number of images used in the analysis
                float *eigval; // array for storing computed eigvalues
        }; 

        class varimax : public Analyzer
        {
          public:
                varimax() : m_mask(NULL) {}
                
                virtual int insert_image(EMData * image);
                
                virtual vector<EMData*> analyze();
                
                string get_name() const
                {
                        return "varimax";
                }               
                
                string get_desc() const
                {
                        return "varimax rotation of PCA results";
                }
                
                static Analyzer * NEW()
                {
                        return new varimax();
                }
                
                virtual void set_params(const Dict & new_params);

                TypeDict get_param_types() const
                {
                        TypeDict d;
                        d.put("mask", EMObject::EMDATA, "mask image");
                        return d;
                }
                
          private:
                int m_nlen;
                int m_nfac;
                EMData *m_mask;
                vector<float> m_data;
         }; 
}

#endif  //eman_analyzer_sparx_h__