/* MELODIC - Multivariate exploratory linear optimized decomposition into independent components melhlprfns.cc - misc functions Christian F. Beckmann, FMRIB Image Analysis Group Copyright (C) 1999-2008 University of Oxford */ /* CCOPYRIGHT */ #ifndef __MELODICHLPR_h #define __MELODICHLPR_h #include "newimage/newimageall.h" #include "newmatap.h" #include "newmatio.h" using namespace NEWIMAGE; namespace Melodic{ void update_mask(volume<float>& mask, Matrix& Data); void del_vols(volume4D<float>& in, int howmany); Matrix smoothColumns(const Matrix& inp); Matrix calc_FFT(const Matrix& Mat, const bool logpwr = 0); Matrix convert_to_pbsc(Matrix& Mat); RowVector varnorm(Matrix& in, int dim = 30, float level = 1.6); void varnorm(Matrix& in, const RowVector& vars); RowVector varnorm(Matrix& in, Matrix& Corr, int dim = 30, float level = 1.6); Matrix SP2(const Matrix& in, const Matrix& weights, bool econ = 0); RowVector Feta(int n1,int n2); RowVector cumsum(const RowVector& Inp); Matrix corrcoef(const Matrix& in1, const Matrix& in2); Matrix corrcoef(const Matrix& in1, const Matrix& in2, const Matrix& part); Matrix calc_corr(const Matrix& in, bool econ = 0); Matrix calc_corr(const Matrix& in, const Matrix& weights, bool econ = 0); float calc_white(const Matrix& tmpE, const RowVector& tmpD, const RowVector& PercEV, int dim, Matrix& param, Matrix& paramS, Matrix& white, Matrix& dewhite); float calc_white(const Matrix& tmpE, const RowVector& tmpD, const RowVector& PercEV, int dim, Matrix& white, Matrix& dewhite); void calc_white(const Matrix& tmpE, const RowVector& tmpD, int dim, Matrix& param, Matrix& paramS, Matrix& white, Matrix& dewhite); void calc_white(const Matrix& tmpE, const RowVector& tmpD, int dim, Matrix& white, Matrix& dewhite); void calc_white(const Matrix& Corr, int dim, Matrix& white, Matrix& dewhite); void std_pca(const Matrix& Mat, Matrix& Corr, Matrix& evecs, RowVector& evals); void std_pca(const Matrix& Mat, const Matrix& weights, Matrix& Corr, Matrix& evecs, RowVector& evals); void em_pca(const Matrix& Mat, Matrix& evecs, RowVector& evals, int num_pc = 1, int iter = 20); void em_pca(const Matrix& Mat, Matrix& guess, Matrix& evecs, RowVector& evals, int num_pc = 1, int iter = 20); float rankapprox(const Matrix& Mat, Matrix& cols, Matrix& rows, int dim = 1); RowVector krfact(const Matrix& Mat, Matrix& cols, Matrix& rows); RowVector krfact(const Matrix& Mat, int colnum, Matrix& cols, Matrix& rows); Matrix krprod(const Matrix& cols, const Matrix& rows); Matrix krapprox(const Matrix& Mat, int size_col, int dim = 1); void adj_eigspec(const RowVector& in, RowVector& out1, RowVector& out2, RowVector& out3, int& out4, int num_vox, float resels); void adj_eigspec(const RowVector& in, RowVector& out1, RowVector& out2); int ppca_dim(const Matrix& in, const Matrix& weights, Matrix& PPCA, RowVector& AdjEV, RowVector& PercEV, Matrix& Corr, Matrix& tmpE, RowVector &tmpD, float resels, string which); int ppca_dim(const Matrix& in, const Matrix& weights, Matrix& PPCA, RowVector& AdjEV, RowVector& PercEV, float resels, string which); int ppca_dim(const Matrix& in, const Matrix& weights, float resels, string which); ColumnVector ppca_select(Matrix& PPCAest, int& dim, int maxEV, string which); Matrix ppca_est(const RowVector& eigenvalues, const int N1, const float N2); Matrix ppca_est(const RowVector& eigenvalues, const int N); ColumnVector acf(const ColumnVector& in, int order); ColumnVector pacf(const ColumnVector& in, int maxorder = 1); Matrix est_ar(const Matrix& Mat, int maxorder); ColumnVector gen_ar(const ColumnVector& in, int maxorder = 1); Matrix gen_ar(const Matrix& in, int maxorder); Matrix gen_arCorr(const Matrix& in, int maxorder); class basicGLM{ public: //constructor basicGLM(){} //destructor ~basicGLM(){} void olsfit(const Matrix& data, const Matrix& design, const Matrix& contrasts, int DOFadjust = -1); inline Matrix& get_t(){return t;} inline Matrix& get_z(){return z;} inline Matrix& get_p(){return p;} inline Matrix& get_f_fmf(){return f_fmf;} inline Matrix& get_pf_fmf(){return pf_fmf;} inline Matrix& get_cbeta(){return cbeta;} inline Matrix& get_beta(){return beta;} inline Matrix& get_varcb(){return varcb;} inline Matrix& get_sigsq(){return sigsq;} inline Matrix& get_residu(){return residu;} inline int get_dof(){return dof;} private: Matrix beta; Matrix residu; Matrix sigsq; Matrix varcb; Matrix cbeta; Matrix f_fmf, pf_fmf; int dof; Matrix t; Matrix z; Matrix p; }; // Matrix glm_ols(const Matrix& dat, const Matrix& design); } #endif