/* MELODIC - Multivariate exploratory linear optimized decomposition into independent components melreport.h - report generation Christian F. Beckmann, FMRIB Image Analysis Group Copyright (C) 1999-2008 University of Oxford */ /* Part of FSL - FMRIB's Software Library http://www.fmrib.ox.ac.uk/fsl 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 LICENCE FMRIB Software Library, Release 5.0 (c) 2012, The University of Oxford (the "Software") The Software remains the property of the University of Oxford ("the University"). The Software is distributed "AS IS" under this Licence solely for non-commercial use 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 the Software, 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 the Software. It further disclaims any liability for the outcomes arising from using the Software. The Licensee agrees to indemnify the University and hold the University harmless from and against any and all claims, damages and liabilities asserted by third parties (including claims for negligence) which arise directly or indirectly from the use of the Software or the sale of any products based on the Software. No part of the Software may be reproduced, modified, transmitted or transferred in any form or by any means, electronic or mechanical, without the express permission of the University. The permission of the University is not required if the said reproduction, modification, transmission or transference is done without financial return, the conditions of this Licence are imposed upon the receiver of the product, and all original and amended source code is included in any transmitted product. You may be held legally responsible for any copyright infringement that is caused or encouraged by your failure to abide by these terms and conditions. You are not permitted under this Licence to use this Software commercially. Use for which any financial return is received shall be defined as commercial use, and includes (1) integration of all or part of the source code or the Software into a product for sale or license by or on behalf of Licensee to third parties or (2) use of the Software or any derivative of it for research with the final aim of developing software products for sale or license to a third party or (3) use of the Software or any derivative of it for research with the final aim of developing non-software products for sale or license to a third party, or (4) use of the Software to provide any service to an external organisation for which payment is received. If you are interested in using the Software commercially, please contact Isis Innovation Limited ("Isis"), the technology transfer company of the University, to negotiate a licence. Contact details are: innovation@isis.ox.ac.uk quoting reference DE/9564. */ #ifndef __MELODICREPORT_h #define __MELODICREPORT_h #include "newimage/newimageall.h" #include "utils/log.h" #include "melpca.h" #include "meloptions.h" #include "meldata.h" #include "melgmix.h" #include "melodic.h" #include "newmatap.h" #include "newmatio.h" #include #include #include "libvis/miscplot.h" #include "libvis/miscpic.h" #include "utils/options.h" using namespace Utilities; using namespace NEWIMAGE; using namespace MISCPLOT; using namespace MISCPIC; namespace Melodic{ class MelodicReport{ public: MelodicReport(MelodicData &pmelodat, MelodicOptions &popts, Log &plogger): melodat(pmelodat), opts(popts), logger(plogger){ if( bool(opts.genreport.value()) ){ const time_t tmptime = time(NULL); system(("mkdir "+ logger.appendDir("report") + " 2>/dev/null").c_str()); report.setDir(logger.appendDir("report"),"00index.html",true,false,ios::out); report << "" << "MELODIC report" << endl <" << "MELODIC report" << endl <" << endl; head << "" << endl; head <<"" << endl <<" "<
"<< endl <<""<< endl <<""<< endl <<"
MELODIC Report"<< endl <<"

"<< endl << report.getDir() << "/" << report.getLogFileName() << "
" << ctime(&tmptime) << "

"<< endl << "
" << endl << "
" << endl << "" << endl << "" << endl << "

"<" << endl; loghtml <<"" << endl; }else{ report <<""<< endl; loghtml <<""<< endl; } report << "

"<< endl; loghtml << "

" <<"" <" << endl <<""<
"<Main - "; if(opts.guireport.value()=="") navigator << "Log - "; navigator <<"Components: "; navigator.flush(); axials_instr = opts.axials_str.value(); } } ~MelodicReport(){ if( bool(opts.genreport.value()) ){ report << "
This page produced automatically by " << " MELODIC Version " << version << " - a part of FSL - " << "FMRIB Software Library.
" << endl << "" <
This page produced automatically by " << " MELODIC Version " << version << " - a part of FSL - " << "FMRIB Software Library.
" << endl << "" <


" <Analysis methods
"<" <<"www.fmrib.ox.ac.uk/fsl).
"; report << "The following data pre-processing was applied to" <<" the input data: "<< endl; if(opts.use_mask.value()) report << " masking of non-brain voxels;"; report << " voxel-wise de-meaning of the data;" << endl; if(opts.varnorm.value()) report << " normalisation of the voxel-wise variance; "; if(opts.pbsc.value()) report << " conversion to %BOLD signal change; "; report << "
"<0){ report << "probabilistic Principal Component Analysis where the" <<" number of dimensions was estimated using "; if(opts.pca_est.value() == string("lap")) report << "the Laplace approximation to the Bayesian" <<" evidence of the model order [Minka 2000, Beckmann 2004]. " << endl; else if(opts.pca_est.value() == string("bic")) report << "the Bayesian Information Criterion" <<" (BIC) [Kass 1993]. " << endl; else if(opts.pca_est.value() == string("mdl")) report << " Minimum Description Length (MDL)" <<" [Rissanen 1978]. " << endl; else if(opts.pca_est.value() == string("aic")) report << "the Akaike Information Criterion" <<" (AIC) [Akaike 1969]. " << endl; else report << " approximations to Bayesian the" <<" model order [Beckmann 2004]. " << endl; } else report << "Principal Component Analysis. "; report << "
The whitened observations were decomposed into " <<" sets of vectors which describe signal variation across" <<" the temporal domain (time-courses)"; if(opts.approach.value() == string("tica") || opts.approach.value() == string("concat")) report << ", the session/subject domain "; report <<" and across the spatial domain (maps) by optimising for" <<" non-Gaussian spatial source distributions using a" <<" fixed-point iteration technique [Hyvärinen 1999]. " << endl; report << "Estimated Component maps were divided by the standard" <<" deviation of the residual noise"; if(opts.perf_mm.value()) report << " and thresholded by fitting a mixture model " <<"to the histogram of intensity values [Beckmann 2004].

" << endl; else report <<".

" << endl; refstxt(); } } inline void refstxt(){ if( bool(opts.genreport.value()) ){ report << "References
"< " << endl; report << "[Beckmann 2004] C.F. Beckmann and S.M. Smith." <<" Probabilistic Independent Component Analysis for Functional" <<" Magnetic Resonance Imaging. IEEE Transactions on Medical" <<" Imaging 23(2):137-152 2004.
" << endl; if(opts.approach.value() == string("tica") || opts.approach.value() == string("concat") ) report << "[Beckmann 2005] C.F. Beckmann and S.M. Smith." <<" Tensorial extensions of independent component analysis" << " for multisubject FMRI analysis. Neuroimage " << " 25(1):294-311 2005.
"; if(melodat.get_PPCA().Storage()>0){ report << "[Everson 2000] R. Everson and S. Roberts." <<" Inferring the eigenvalues of covariance matrices from" <<" limited, noisy data. IEEE Trans Signal Processing," <<" 48(7):2083-2091, 2000
"<" << endl; report << "[Beckmann 2001] C.F. Beckmann, J.A. Noble and" <<" S.M. Smith. Investigating the intrinsic dimensionality" <<" of FMRI data for ICA. In Seventh Int. Conf. on Functional" <<" Mapping of the Human Brain, 2001.
" << endl; if(opts.pca_est.value() == string("lap")) report << "[Minka 2000] T. Minka. Automatic choice of" <<" dimensionality for PCA. Technical Report 514, MIT" <<" Media Lab Vision and Modeling Group, 2000.
"<< endl; else if(opts.pca_est.value() == string("bic")) report << "[Kass 1995] R.E. Kass and A. E. Raftery. Bayes" <<" factors. Journal of the American Statistical" <<" Association, 90:733-795, 1995
" << endl; else if(opts.pca_est.value() == string("mdl")) report << "[Rissanen 1978]. J. Rissanen. Modelling by" <<" shortest data description. Automatica," <<" 14:465-471, 1978.
" << endl; else if(opts.pca_est.value() == string("aic")) report << "[Akaike 1974]. H. Akaike. A new look at" <<" statistical model identification. IEEE Transactions" <<" on Automatic Control, 19:716-723, 1974.
" << endl; else report << "[Minka 2000]. T. Minka. Automatic choice of" <<" dimensionality for PCA. Technical Report 514, MIT" <<" Media Lab Vision and Modeling Group, 2000.
" << endl; } } } inline void addtxt(string what){ if( bool(opts.genreport.value()) ){ report << what << endl; } } inline void addpar(string what){ if( bool(opts.genreport.value()) ){ report << "

" << what << endl; } } inline void addlink(string where, string what){ if( bool(opts.genreport.value()) ){ navigator << " " << what << " "; navigator.flush(); } } inline void addpic(string what, string link = ""){ if( bool(opts.genreport.value()) ){ if( link.length() > 0) report << " "; report << "

"; if( link.length() > 0) report << " "; } } inline string getDir(){ return report.getDir(); } void IC_rep(MelGMix &mmodel, int cnum, int dim, Matrix ICstats); void IC_simplerep(string prefix, int cnum, int dim); void PPCA_rep(); void Smode_rep(); private: MelodicData &melodat; MelodicOptions &opts; Log &logger; Log report; Log navigator; Log head; Log loghtml; Log IChtml; Log IChtml2; string axials_instr; void IC_rep_det(MelGMix &mmodel, int cnum, int dim); string int2str(int n){ ostrstream os; // os.fill(' '); // os.width(width); os.setf(ios::internal, ios::adjustfield); os << n << '\0'; return os.str(); } string float2str(float f, int width, int prec, int scientif){ ostrstream os; int redw = int(std::abs(std::log10(std::abs(f))))+1; if(width>0) os.width(width); if(scientif>0) os.setf(ios::scientific); os.precision(redw+std::abs(prec)); os.setf(ios::internal, ios::adjustfield); os << f << '\0'; return os.str(); } }; } #endif