film_gls.cc

/*  film_gls.cc

    Mark Woolrich, FMRIB Image Analysis Group

    Copyright (C) 1999-2000 University of Oxford  */

/*  Part of FSL - FMRIB's Software Library
    WWW:      http://www.fmrib.ox.ac.uk/fsl
    Email:    fsl@fmrib.ox.ac.uk
    
    Developed at FMRIB (Oxford Centre for Functional Magnetic Resonance
    Imaging of the Brain), Department of Clinical Neurology, Oxford
    University, Oxford, UK
    
    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
in
    order that the University as a charitable foundation protects its
    assets for the benefit of its educational and research purposes, the
    University makes clear that no condition is made or to be implied,
nor
    is any warranty given or to be implied, as to the accuracy of FSL,
or
    that it will be suitable for any particular purpose or for use under
    any specific conditions.  Furthermore, the University disclaims all
    responsibility for the use which is made of FSL.  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 */

#include <iostream>
#include <fstream>
#include <strstream>
#define WANT_STREAM
#define WANT_MATH

#include "newmatap.h"
#include "newmatio.h"
#include "VolumeSeries.h"
#include "Volume.h"
#include "glim.h"
#include "sigproc.h"
#include "miscmaths.h"
#include "gaussComparer.h"
#include "Log.h"
#include "AutoCorrEstimator.h"
#include "paradigm.h"
#include "FilmGlsOptions.h"
#include "glimGls.h"

#include <string>

#ifndef NO_NAMESPACE
using namespace NEWMAT;
using namespace SIGPROC;
using namespace TACO;
using namespace UTILS;
#endif

int main(int argc, char *argv[])
{
  try{
    rand();
    // parse command line to find out directory name for logging:
    ofstream out2;
    FilmGlsOptions& globalopts = FilmGlsOptions::getInstance();
    globalopts.parse_command_line(argc, argv, out2);

    // Setup logging:
    Log& logger = Log::getInstance();
    logger.setLogFile("glslogfile");
    logger.establishDir(globalopts.datadir);

    // parse command line again to output arguments to logfile
    globalopts.parse_command_line(argc, argv, logger.str());

    // load non-temporally filtered data
    VolumeSeries x;
    x.read(globalopts.inputfname);

    // if needed output the 12th volume for use later
    Volume epivol;
    if(globalopts.smoothACEst)
      {
	epivol = x.getVolume(12).AsColumn();
	epivol.setDims(x.getDims());
	
	epivol.writeAsInt(logger.getDir() + "/" + globalopts.epifname);
      }

    // This also removes the mean from each of the time series:
    x.thresholdSeries(globalopts.thresh, true);

    // if needed later also threshold the epi volume
    if(globalopts.smoothACEst)
      {
	epivol.setPreThresholdPositions(x.getPreThresholdPositions());
	epivol.threshold();
      }

    int sizeTS = x.getNumVolumes();
    int numTS = x.getNumSeries();
    
    // Load paradigm: 
    Paradigm parad;
    parad.load(globalopts.paradigmfname, "", false, sizeTS);

    // Sort out detrending:
    if(globalopts.detrend)
      {
	SIGPROC::Detrend(x, false);
      }

    if(globalopts.verbose)
      {
	logger.out("Gc", parad.getDesignMatrix());
      }

    // Set up OLS GLM for non-whitened data 
    Glim glim(x, parad.getDesignMatrix());
	    
    cerr << "Computing residuals for non-whitened data... ";
    const VolumeSeries& rnotw = glim.ComputeResids();
    cerr << "Completed" << endl;
    
    if(globalopts.verbose)
      {
	logger.out("rnotw", rnotw);
      }
    
    // Estimate Autocorrelations:
    AutoCorrEstimator acEst(rnotw);

    if(globalopts.fitAutoRegressiveModel)
      {
	acEst.fitAutoRegressiveModel();
	if(globalopts.verbose)
	  {
	    AutoCorrEstimator acEstForLogging(rnotw);
	    acEstForLogging.calcRaw();
	    logger.out("rawac", acEstForLogging.getEstimates());
	    logger.out("autoregac", acEst.getEstimates());
	  }
      }
    else
      {
	acEst.calcRaw();
	    
	if(globalopts.verbose)
	  {
	    logger.out("rawac", acEst.getEstimates());
	  }
	    
	// Smooth raw estimates:
	if(globalopts.smoothACEst)
	  { 
	    acEst.spatiallySmooth(logger.getDir() + "/" + globalopts.epifname, epivol, globalopts.ms, globalopts.epifname, globalopts.susanpath);
	    
	  }
	
	// Apply constraints to estimate autocorr:
	acEst.pava();
	    
	if(globalopts.verbose)
	  {
	    logger.out("threshac", acEst.getEstimates());
	  }
      }
    
    ColumnVector I(sizeTS);
    I = 0;
    I(1) = 1;
    
    // Setup OLS GLM for temporally filtered data:
    int numParams = parad.getDesignMatrix().Ncols();
    GlimGls glimGls(numTS, sizeTS, numParams);
    
    ColumnVector xw(sizeTS);
    ColumnVector xprew(sizeTS);

    acEst.setDesignMatrix(parad.getDesignMatrix());
    int co = 1;
    
    // Loop through voxels:
    cerr << "Calculating params..." << endl;

    for(int i = 1; i <= numTS; i++)
      {	
	// Use autocorr estimate to prewhiten data:
	xprew = x.getSeries(i);
	    
	Matrix designmattw;
	acEst.preWhiten(xprew, xw, i, designmattw);

	if(co > 1000 || i == 5618 || i == 5582)
	  {
	    co = 1;
	    cerr << (float)i/(float)numTS << ",";
	  }
	else
	  co++;
	    
	glimGls.setData(xw, designmattw, i);   
      }
    cerr << "Completed" << endl;

    // Write out necessary data:
    cerr << "Saving results... ";
    glimGls.Save(x.getDims(), x.getPreThresholdPositions());
    cerr << "Completed" << endl;
  }  
  catch(Exception p_excp) 
    {
      cerr << p_excp.what() << endl;
    }
  catch(...) 
    {
      cerr << "Image error" << endl;
    } 
  return 0;
}