/* MELODIC - Multivariate exploratory linear optimized decomposition into independent components ggmix.h - class for Gaussian/Gamma Mixture Model 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"). 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Contact details are: innovation@isis.ox.ac.uk quoting reference DE/9564. */ #ifndef __GGMIX_h #define __GGMIX_h #include "newimage/newimageall.h" /*#include "utils/log.h" #include "melodic.h" #include "utils/options.h" #include "meloptions.h" */ //using namespace Utilities; using namespace NEWIMAGE; namespace GGMIX{ class ggmix { public: ggmix(){} //MelodicOptions &popts, Log &plogger): // opts(popts), // logger(plogger) // { // } ~ggmix() { } void save(); void setup(const RowVector& dat, const string dirname, int here, volume themask, volume themean, int num_mix = 3, float eps = 0.0, bool fixdim = false); void gmmfit(); void ggmfit(); inline void fit(string mtype = string("GGM")) { mmtype = mtype; if(mmtype==string("GGM")) this->ggmfit(); else this->gmmfit(); //re-insert mean and stdev data = data*datastdev + datamean; //threshmaps = threshmaps*datastdev + datamean; means = means*datastdev + datamean; vars = vars*datastdev*datastdev; } inline Matrix threshold(string levels) {return this->threshold(data, levels);} inline Matrix threshold(RowVector& levels) {return this->threshold(data, levels);} Matrix threshold(const RowVector& dat, Matrix& levels); Matrix threshold(const RowVector& dat, string levels); void status(const string &txt); inline RowVector& get_means() {return means;} inline void set_means(RowVector& Arg) {means = Arg;} inline RowVector& get_vars() {return vars;} inline void set_vars(RowVector& Arg) {vars = Arg;} inline RowVector& get_pi() {return props;} inline void set_pi(RowVector& Arg) {props = Arg;} inline RowVector& get_data() {return data;} inline void set_data(RowVector& Arg) {data = Arg;} inline RowVector& get_prob() {return probmap;} inline float get_eps() {return epsilon;} inline void set_eps(float Arg) {epsilon = Arg;} inline Matrix& get_threshmaps() {return threshmaps;} inline void set_threshmaps(Matrix& Arg) {threshmaps = Arg;} inline bool isfitted(){return fitted;} inline int mixtures(){return nummix;} inline string get_type() { return mmtype;} inline void set_type(string Arg) { mmtype = Arg;} inline string get_prefix() { return prefix;} inline void set_prefix(string Arg) { prefix = Arg;} inline RowVector get_probmap() {return probmap;} inline float get_offset() {return offset;} inline void set_offset(float Arg) {offset = Arg;} inline void flipres(int num){ means = -means; data = -data; threshmaps = -threshmaps; if(mmtype=="GGM"){ float tmp; tmp= means(2);means(2)=means(3);means(3)=tmp; tmp=vars(2);vars(2)=vars(3);vars(3)=tmp; tmp=props(2);props(2)=props(3);props(3)=tmp; } } inline void add_infstr(string what){ threshinfo.push_back(what); } inline string get_infstr(int num){ if((threshinfo.size()<(unsigned int)(num-1))||(num<1)) return string(""); else return threshinfo[num-1]; } inline int size_infstr(){ return threshinfo.size(); } inline void clear_infstr(){ threshinfo.clear(); } inline void smooth_probs(float howmuch){ volume4D tempVol; tempVol.setmatrix(probmap,Mask); tempVol[0]= smooth(tempVol[0],howmuch); probmap = tempVol.matrix(Mask); } double datamean; double datastdev; private: // MelodicOptions &opts; // Log &logger; //global log file //Log mainhtml; void gmmupdate(); float gmmevidence(); void gmmreducemm(); void add_params(Matrix& mu, Matrix& sig, Matrix& pi, float logLH, float MDL, float Evi, bool advance = false); void get_params(int index, Matrix& mu, Matrix& sig, Matrix& pi, float logLH, float MDL, float Evi); Matrix Params; Matrix threshmaps; RowVector means; RowVector vars; RowVector props; RowVector data; RowVector probmap; volume Mean; volume Mask; float epsilon; float logprobY; float MDL; float Evi; float offset; int nummix; int numdata; int cnumber; bool fitted; bool fixdim; string prefix; string mmtype; string dirname; vector threshinfo; }; } #endif