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#include "miscmaths/miscmaths.h"
#include "miscmaths/miscprob.h"
#include "utils/options.h"
#include <vector>
#include "newimage/newimageall.h"
#include "melhlprfns.h"
using namespace MISCPLOT;
using namespace MISCMATHS;
using namespace Utilities;
using namespace std;
// The two strings below specify the title and example usage that is
// printed out as the help or usage message
string title=string("fsl_glm (Version 1.0)")+
string("\nCopyright(c) 2007, University of Oxford (Christian F. Beckmann)\n")+
string(" \n Simple GLM usign ordinary least-squares regression on\n")+
string(" time courses and/or 3D/4D volumes\n\n");
string examples="fsl_glm <input> -d <design> [options]";
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//Command line Options {
Option<string> fnin(string("-i,--in"), string(""),
string("input file name (matrix 3D or 4D image)"),
true, requires_argument);
Option<string> fnout(string("-o,--out"), string(""),
string(""),
true, requires_argument);
Option<string> fndesign(string("-d,--design"), string(""),
string("file name of the GLM design matrix (time courses or spatial maps)"),
true, requires_argument);
Option<string> fnmask(string("-m,--mask"), string(""),
string("mask image"),
false, requires_argument);
Option<string> fncontrasts(string("-c,--contrasts"), string(""),
string("matrix of t-statistics contrasts"),
false, requires_argument);
Option<string> fnftest(string("-f,--ftests"), string(""),
string("matrix of F-tests on contrasts"),
false, requires_argument);
Option<int> dofset(string("--dof"),0,
string("set degrees-of-freedom explicitly"),
false, requires_argument);
Option<string> filter(string("--filter"),string(""),
string("filter out part of the regression model"),
false, requires_argument);
Option<bool> perfvn(string("--vn"),FALSE,
string("perfrom variance-normalisation on data"),
false, requires_argument);
Option<int> help(string("-h,--help"), 0,
string("display this help text"),
false,no_argument);
// Output options
Option<string> outcope(string("--out_cope"),string(""),
string("output COPEs"),
false, requires_argument);
Option<string> outz(string("--out_z"),string(""),
string("output Z-stats"),
false, requires_argument);
Option<string> outt(string("--out_t"),string(""),
string("output t-stats"),
false, requires_argument);
Option<string> outp(string("--out_p"),string(""),
string("output p-values of Z-stats"),
false, requires_argument);
Option<string> outf(string("--out_f"),string(""),
string("output F-value of full model fit"),
false, requires_argument);
Option<string> outpf(string("--out_pf"),string(""),
string("output p-value for full model fit"),
false, requires_argument);
Option<string> outfilt(string("--out_filt"),string(""),
string("output filtered data"),
false, requires_argument);
Option<string> outres(string("--out_res"),string(""),
string("output residuals"),
false, requires_argument);
Option<string> outvarcb(string("--out_varcb"),string(""),
string("output variance of COPEs"),
false, requires_argument);
Option<string> outsigsq(string("--out_sigsq"),string(""),
string("output residual noise variance sigma-square"),
false, requires_argument);
Option<string> outdata(string("--out_data"),string(""),
string("output data"),
false, requires_argument);
Option<string> outvnscales(string("--out_vnscales"),string(""),
string("output scaling factors for variance normalisation"),
false, requires_argument);
/*
}
*/
//Globals {
Melodic::basicGLM glm;
bool isimage = FALSE;
Matrix data;
Matrix design;
Matrix contrasts;
Matrix fcontrasts;
Matrix meanR;
RowVector vnscales;
volume<float> mask;
volumeinfo volinf; /*
}
*/
////////////////////////////////////////////////////////////////////////////
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void save4D(Matrix what, string fname){
if(what.Ncols()==data.Ncols()||what.Nrows()==data.Nrows()){
volume4D<float> tempVol;
if(what.Nrows()>what.Ncols())
tempVol.setmatrix(what.t(),mask);
else
tempVol.setmatrix(what,mask);
save_volume4D(tempVol,fname,volinf);
}
}
void saveit(Matrix what, string fname){
if(isimage)
save4D(what,fname);
else
write_ascii_matrix(what,fname);
}
int dofilter(){
if(!isimage){
cerr << "ERROR: need to specify 4D input to use filtering" << endl;
return 1;
}
Matrix unmixMatrix = pinv(design);
Matrix maps = unmixMatrix * data;
Matrix noisedes;
Matrix noisemaps;
int ctr=0;
char *p;
char t[1024];
const char *discard = ", [];{(})abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ~!@#$%^&*_-=+|\':><./?";
strcpy(t, filter.value().c_str());
p=strtok(t,discard);
ctr = atoi(p);
if(ctr>0 && ctr<=design.Ncols()){
noisedes = design.Column(ctr);
noisemaps = maps.Row(ctr).t();
}
do{
p=strtok(NULL,discard);
if(p){
ctr = atoi(p);
if(ctr>0 && ctr<=design.Ncols()){
noisedes |= design.Column(ctr);
noisemaps |= maps.Row(ctr).t();
}
}
}while(p);
Matrix newData;
newData = data - noisedes * noisemaps.t();
newData = newData + ones(newData.Nrows(),1)*meanR;
save4D(newData,outfilt.value());
return 0;
}
int setup(){
if(fsl_imageexists(fnin.value())){//read data
//input is 3D/4D vol
isimage = TRUE;
volume4D<float> tmpdata;
read_volume4D(tmpdata,fnin.value(),volinf);
// create mask
if(fnmask.value()>""){
read_volume(mask,fnmask.value());
if(!samesize(tmpdata[0],mask)){
cerr << "ERROR: Mask image does not match input image" << endl;
return 1;
};
}else{
mask = tmpdata[0]*0.0+1.0;
}
data = tmpdata.matrix(mask);
}
else
data = read_ascii_matrix(fnin.value());
if(fsl_imageexists(fndesign.value())){//read design
volume4D<float> tmpdata;
read_volume4D(tmpdata,fndesign.value());
if(!samesize(tmpdata[0],mask)){
cerr << "ERROR: GLM design does not match input image in size" << endl;
return 1;
}
design = tmpdata.matrix(mask).t();
data = data.t();
isimage = FALSE;
}else{
design = read_ascii_matrix(fndesign.value());
}
meanR=mean(data,1);
data = remmean(data,1);
design = remmean(design,1);
if(perfvn.value())
vnscales = Melodic::varnorm(data);
if(fncontrasts.value()>""){//read contrast
contrasts = read_ascii_matrix(fncontrasts.value());
if(!(contrasts.Ncols()==design.Ncols())){
cerr << "ERROR: contrast matrix GLM design does not match GLM design" << endl;
return 1;
}
}else{
contrasts = Identity(design.Ncols());
contrasts &= -1.0 * contrasts;
}
return 0;
}
void write_res(){
if(fnout.value()>"")
saveit(glm.get_beta(),fnout.value());
if(outcope.value()>"")
saveit(glm.get_cbeta(),outcope.value());
if(outz.value()>"")
saveit(glm.get_z(),outz.value());
if(outt.value()>"")
saveit(glm.get_t(),outt.value());
if(outp.value()>"")
saveit(glm.get_p(),outp.value());
if(outf.value()>"")
saveit(glm.get_f_fmf(),outf.value());
if(outpf.value()>"")
saveit(glm.get_pf_fmf(),outpf.value());
if(outres.value()>"")
saveit(glm.get_residu(),outres.value());
if(outvarcb.value()>"")
saveit(glm.get_varcb(),outvarcb.value());
if(outsigsq.value()>"")
saveit(glm.get_sigsq(),outsigsq.value());
if(outdata.value()>"")
saveit(data,outdata.value());
if(outvnscales.value()>"")
saveit(vnscales,outvnscales.value());
}
if(filter.value()>"")
if(dofilter())
exit(1);
else{
glm.olsfit(data,design,contrasts,dofset.value());
write_res();
}
return 0;
////////////////////////////////////////////////////////////////////////////
Tracer tr("main");
OptionParser options(title, examples);
// must include all wanted options here (the order determines how
// the help message is printed)
options.add(fnin);
options.add(fnout);
options.add(fndesign);
options.add(fnmask);
options.add(fncontrasts);
options.add(fnftest);
options.add(dofset);
options.add(filter);
options.add(perfvn);
options.add(help);
options.add(outcope);
options.add(outz);
options.add(outt);
options.add(outp);
options.add(outf);
options.add(outpf);
options.add(outfilt);
options.add(outres);
options.add(outvarcb);
options.add(outsigsq);
options.add(outdata);
options.add(outvnscales);
options.parse_command_line(argc, argv);
// line below stops the program if the help was requested or
// a compulsory option was not set
if ( (help.value()) || (!options.check_compulsory_arguments(true)) ){
options.usage();
exit(EXIT_FAILURE);
}else{
// Call the local functions
return do_work(argc,argv);
}
}catch(X_OptionError& e) {
cerr << e.what() << endl;
}
}