[646] | 1 | |
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| 2 | |
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| 3 | #include <limits> |
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| 4 | #include "arx.h" |
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| 5 | |
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| 6 | |
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| 7 | #include <fstream> |
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| 8 | #include<iostream> |
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| 9 | #include<iomanip> |
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| 10 | |
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| 11 | namespace bdm { |
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| 12 | |
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| 13 | |
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[648] | 14 | |
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| 15 | |
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| 16 | /* |
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[646] | 17 | struct str_aux { |
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| 18 | vec d0; |
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| 19 | double nu0; |
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| 20 | mat L0; |
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| 21 | mat L; |
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| 22 | vec d; |
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| 23 | double nu; |
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| 24 | ivec strL; // Current structure of L and d |
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| 25 | ivec strRgr; // Structure elements currently inside regressor (after regressand) |
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| 26 | ivec strMis; // structure elements, that are currently outside regressor (before regressand) |
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| 27 | int posit1; // regressand position |
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| 28 | int nbits; // number of bits available in double |
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[648] | 29 | bvec bitstr; |
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[646] | 30 | double loglik; // loglikelihood |
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| 31 | }; |
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[648] | 32 | |
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[646] | 33 | */ |
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| 34 | |
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[648] | 35 | |
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| 36 | /* bvec str_bitset( bvec in,ivec ns,int nbits){ |
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| 37 | //int index, bitindex,n; |
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| 38 | bvec out = in; |
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| 39 | int n; |
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| 40 | |
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| 41 | for (int i = 0; i < ns.length(); i++){ |
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| 42 | n = ns(i); |
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| 43 | out(n-2) = 1; |
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| 44 | cout << out; |
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| 45 | |
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| 46 | } |
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| 47 | |
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| 48 | return out; |
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| 49 | |
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| 50 | }*/ |
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| 51 | |
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| 52 | |
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| 53 | void str_bitset ( bvec &out, ivec ns, int nbits ) { |
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| 54 | for ( int i = 0; i < ns.length(); i++ ) { |
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| 55 | out ( ns ( i ) - 2 ) = 1; |
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| 56 | } |
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[646] | 57 | } |
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| 58 | |
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| 59 | |
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| 60 | |
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| 61 | |
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| 62 | |
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| 63 | |
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[648] | 64 | double seloglik1 ( str_aux in ) { |
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[646] | 65 | // This is the loglikelihood (non-constant part) - this should be used in |
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| 66 | // frequent computation |
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[648] | 67 | int len = length ( in.d ); |
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| 68 | int p1 = in.posit1 - 1; |
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[646] | 69 | |
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[648] | 70 | double i1 = -0.5 * in.nu * log ( in.d ( p1 ) ) - 0.5 * sum ( log ( in.d.right ( len - p1 - 1 ) ) ); |
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| 71 | double i0 = -0.5 * in.nu0 * log ( in.d0 ( p1 ) ) - 0.5 * sum ( log ( in.d0.right ( len - p1 - 1 ) ) ); |
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| 72 | return i1 - i0; |
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| 73 | //DEBUGGing print: |
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| 74 | //fprintf('SELOGLIK1: str=%s loglik=%g\n', strPrintstr(in), l);*/ |
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[646] | 75 | |
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| 76 | } |
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| 77 | |
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| 78 | |
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[648] | 79 | void sedydr ( mat &r, mat &f, double &Dr, double &Df, int R/*,int jl,int jh ,mat &rout, mat &fout, double &Drout, double &Dfoutint &kr*/ ) { |
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| 80 | /*SEDYDR dyadic reduction, performs transformation of sum of 2 dyads |
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| 81 | % |
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| 82 | % [rout, fout, Drout, Dfout, kr] = sedydr(r,f,Dr,Df,R,jl,jh); |
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| 83 | % [rout, fout, Drout, Dfout] = sedydr(r,f,Dr,Df,R); |
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| 84 | % |
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| 85 | % Description: dyadic reduction, performs transformation of sum of |
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| 86 | % 2 dyads r*Dr*r'+ f*Df*f' so that the element of r pointed by R is zeroed |
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| 87 | % |
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| 88 | % r : column vector of reduced dyad |
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| 89 | % f : column vector of reducing dyad |
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| 90 | % Dr : scalar with weight of reduced dyad |
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| 91 | % Df : scalar with weight of reducing dyad |
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| 92 | % R : scalar number giving 1 based index to the element of r, |
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| 93 | % which is to be reduced to |
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| 94 | % zero; the corresponding element of f is assumed to be 1. |
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| 95 | % jl : lower index of the range within which the dyads are |
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| 96 | % modified (can be omitted, then everything is updated) |
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| 97 | % jh : upper index of the range within which the dyads are |
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| 98 | % modified (can be omitted then everything is updated) |
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| 99 | % rout,fout,Drout,dfout : resulting two dyads |
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| 100 | % kr : coefficient used in the transformation of r |
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| 101 | % rnew = r + kr*f |
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| 102 | % |
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| 103 | % Description: dyadic reduction, performs transformation of sum of |
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| 104 | % 2 dyads r*Dr*r'+ f*Df*f' so that the element of r indexed by R is zeroed |
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| 105 | % Remark1: Constant mzero means machine zero and should be modified |
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| 106 | % according to the precision of particular machine |
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| 107 | % Remark2: jl and jh are, in fact, obsolete. It takes longer time to |
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| 108 | % compute them compared to plain version. The reason is that we |
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| 109 | % are doing vector operations in m-file. Other reason is that |
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| 110 | % we need to copy whole vector anyway. It can save half of time for |
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| 111 | % c-file, if you use it correctly. (please do tests) |
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| 112 | % |
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| 113 | % Note: naming: |
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| 114 | % se = structure estimation |
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| 115 | % dydr = dyadic reduction |
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| 116 | % |
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| 117 | % Original Fortran design: V. Peterka 17-7-89 |
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| 118 | % Modified for c-language: probably R. Kulhavy |
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| 119 | % Modified for m-language: L. Tesar 2/2003 |
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| 120 | % Updated: Feb 2003 |
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| 121 | % Project: post-ProDaCTool |
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| 122 | % Reference: none*/ |
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| 123 | |
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| 124 | /*if nargin<6; |
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| 125 | update_whole=1; |
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| 126 | else |
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| 127 | update_whole=0; |
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| 128 | end;*/ |
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| 129 | |
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| 130 | double mzero = 1e-32; |
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| 131 | |
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| 132 | if ( Dr < mzero ) { |
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| 133 | Dr = 0; |
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| 134 | } |
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| 135 | |
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| 136 | double r0 = r ( R, 0 ); |
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| 137 | double kD = Df; |
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| 138 | double kr = r0 * Dr; |
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| 139 | |
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| 140 | |
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| 141 | Df = kD + r0 * kr; |
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| 142 | |
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| 143 | if ( Df > mzero ) { |
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| 144 | kD = kD / Df; |
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| 145 | kr = kr / Df; |
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| 146 | } else { |
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| 147 | kD = 1; |
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| 148 | kr = 0; |
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| 149 | } |
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| 150 | |
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| 151 | Dr = Dr * kD; |
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| 152 | |
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[646] | 153 | // Try to uncomment marked stuff (*) if in numerical problems, but I don't |
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| 154 | // think it can make any difference for normal healthy floating-point unit |
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| 155 | //if update_whole; |
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[648] | 156 | r = r - r0 * f; |
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[646] | 157 | // rout(R) = 0; // * could be needed for some nonsense cases(or numeric reasons?), normally not |
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[648] | 158 | f = f + kr * r; |
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[646] | 159 | // fout(R) = 1; // * could be needed for some nonsense cases(or numeric reasons?), normally not |
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[648] | 160 | /*else; |
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| 161 | rout = r; |
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| 162 | fout = f; |
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| 163 | rout(jl:jh) = r(jl:jh) - r0 * f(jl:jh); |
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| 164 | rout(R) = 0; |
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| 165 | fout(jl:jh) = f(jl:jh) + kr * rout(jl:jh); |
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| 166 | end;*/ |
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| 167 | } |
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[646] | 168 | |
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| 169 | |
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| 170 | |
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[648] | 171 | /*mat*/ void seswapudl ( mat &L, vec &d , int i/*, vec &dout*/ ) { |
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| 172 | /*%SESWAPUDL swaps information matrix in decomposition V=L^T diag(d) L |
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| 173 | % |
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| 174 | % [Lout, dout] = seswapudl(L,d,i); |
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| 175 | % |
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| 176 | % L : lower triangular matrix with 1's on diagonal of the decomposistion |
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| 177 | % d : diagonal vector of diagonal matrix of the decomposition |
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| 178 | % i : index of line to be swapped with the next one |
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| 179 | % Lout : output lower triangular matrix |
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| 180 | % dout : output diagional vector of diagonal matrix D |
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| 181 | % |
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| 182 | % Description: |
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| 183 | % Lout' * diag(dout) * Lout = P(i,i+1) * L' * diag(d) * L * P(i,i+1); |
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| 184 | % |
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| 185 | % Where permutation matrix P(i,j) permutates columns if applied from the |
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| 186 | % right and line if applied from the left. |
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| 187 | % |
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| 188 | % Note: naming: |
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| 189 | % se = structure estimation |
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| 190 | % lite = light, simple |
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| 191 | % udl = U*D*L, or more precisely, L'*D*L, also called as ld |
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| 192 | % |
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| 193 | % Design : L. Tesar |
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| 194 | % Updated : Feb 2003 |
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| 195 | % Project : post-ProDaCTool |
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| 196 | % Reference: sedydr*/ |
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| 197 | |
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| 198 | int j = i + 1; |
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| 199 | |
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| 200 | double pomd = d ( i ); |
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| 201 | d ( i ) = d ( j ); |
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| 202 | d ( j ) = pomd; |
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| 203 | |
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| 204 | /*vec pomL = L.get_row(i); |
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| 205 | L.set_row(i, L.get_row(j)); |
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| 206 | L.set_row(j,pomL);*/ |
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| 207 | |
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| 208 | L.swap_rows ( i, j ); |
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| 209 | L.swap_cols ( i, j ); |
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| 210 | |
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| 211 | /*pomL = L.get_col(i); |
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| 212 | L.set_col(i, L.get_col(j)); |
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| 213 | L.set_col(j,pomL);*/ |
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| 214 | |
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[646] | 215 | //% We must be working with LINES of matrix L ! |
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| 216 | |
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| 217 | |
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[648] | 218 | |
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| 219 | mat r = L.get_row ( i ); |
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| 220 | r = r.transpose(); |
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| 221 | r = r.transpose(); |
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[646] | 222 | //???????????????? |
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[648] | 223 | mat f = L.get_row ( j ); |
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| 224 | f = f.transpose(); |
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| 225 | f = f.transpose(); |
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[646] | 226 | |
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| 227 | |
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| 228 | |
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| 229 | |
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[648] | 230 | double Dr = d ( i ); |
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| 231 | double Df = d ( j ); |
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[646] | 232 | |
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[648] | 233 | sedydr ( r, f, Dr, Df, j ); |
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[646] | 234 | |
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| 235 | |
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| 236 | |
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[648] | 237 | double r0 = r ( i, 0 ); |
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| 238 | Dr = Dr * r0 * r0; |
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| 239 | r = r / r0; |
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[646] | 240 | |
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| 241 | |
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| 242 | |
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[648] | 243 | mat pom_mat = r.transpose(); |
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| 244 | L.set_row ( i, pom_mat.get_row ( 0 ) ); |
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| 245 | pom_mat = f.transpose(); |
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| 246 | L.set_row ( j, pom_mat.get_row ( 0 ) ); |
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| 247 | |
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| 248 | d ( i ) = Dr; |
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| 249 | d ( j ) = Df; |
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| 250 | |
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| 251 | L ( i, i ) = 1; |
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| 252 | L ( j, j ) = 1; |
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| 253 | |
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| 254 | |
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| 255 | } |
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| 256 | |
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| 257 | |
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| 258 | void str_bitres ( bvec &out, ivec ns, int nbits ) { |
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| 259 | |
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| 260 | |
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| 261 | for ( int i = 0; i < ns.length(); i++ ) { |
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| 262 | out ( ns ( i ) - 2 ) = 0; |
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| 263 | } |
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| 264 | |
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| 265 | |
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| 266 | } |
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| 267 | |
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| 268 | str_aux sestrremove ( str_aux in, ivec removed_elements ) { |
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[646] | 269 | //% Removes elements from regressor |
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[648] | 270 | int n_strL = length ( in.strL ); |
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| 271 | str_aux out = in; |
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| 272 | for ( int i = 0; i < removed_elements.length(); i++ ) { |
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[646] | 273 | |
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[648] | 274 | int f = removed_elements ( i ); |
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| 275 | int posit1 = ( find ( out.strL == 1 ) ) ( 0 ); |
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| 276 | int positf = ( find ( out.strL == f ) ) ( 0 ); |
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| 277 | int pom_strL; |
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| 278 | for ( int g = positf - 1; g > posit1 - 1; g-- ) { |
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| 279 | //% BEGIN: We are swapping g and g+1 NOW!!!! |
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| 280 | seswapudl ( out.L, out.d, g ); |
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| 281 | seswapudl ( out.L0, out.d0, g ); |
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| 282 | |
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| 283 | pom_strL = out.strL ( g ); |
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| 284 | out.strL ( g ) = out.strL ( g + 1 ); |
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| 285 | out.strL ( g + 1 ) = pom_strL; |
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| 286 | |
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| 287 | //% END |
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[646] | 288 | } |
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| 289 | } |
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[648] | 290 | out.posit1 = ( find ( out.strL == 1 ) ) ( 0 ) + 1; |
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| 291 | out.strRgr = out.strL.right ( n_strL - out.posit1 ); |
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| 292 | out.strMis = out.strL.left ( out.posit1 - 1 ); |
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| 293 | str_bitres ( out.bitstr, removed_elements, out.nbits ); |
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| 294 | out.loglik = seloglik1 ( out ); |
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[646] | 295 | |
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[648] | 296 | return out; |
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| 297 | } |
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[646] | 298 | |
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[648] | 299 | |
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| 300 | ivec setdiff ( ivec a, ivec b ) { |
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| 301 | ivec pos; |
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| 302 | |
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| 303 | for ( int i = 0; i < b.length(); i++ ) { |
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| 304 | pos = find ( a == b ( i ) ); |
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| 305 | for ( int j = 0; j < pos.length(); j++ ) { |
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| 306 | a.del ( pos ( j ) - j ); |
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| 307 | } |
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| 308 | } |
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| 309 | return a; |
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| 310 | } |
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| 311 | |
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| 312 | |
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| 313 | |
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[646] | 314 | /* |
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[648] | 315 | |
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[646] | 316 | Array<str_aux> add_new(Array<str_aux> global_best,str_aux newone,int nbest){ |
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| 317 | // Eventually add to global best, but do not go over nbest values |
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| 318 | // Also avoids repeating things, which makes this function awfully slow |
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[648] | 319 | |
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[646] | 320 | Array<str_aux> global_best_out; |
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| 321 | if (global_best.length() >= nbest){ |
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| 322 | //logliks = [global_best.loglik]; |
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[648] | 323 | |
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| 324 | vec logliks(1); |
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[646] | 325 | logliks(0) = global_best(0).loglik; |
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| 326 | for (int j = 1; j < global_best.length(); j++) |
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| 327 | logliks = concat(logliks, global_best(j).loglik); |
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[648] | 328 | |
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[646] | 329 | int i, addit; |
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| 330 | double loglik = min(logliks, i); |
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| 331 | global_best_out = global_best; |
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| 332 | if (loglik < newone.loglik){ |
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| 333 | // if ~any(logliks == new.loglik); |
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| 334 | addit=1; |
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[648] | 335 | |
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| 336 | |
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| 337 | |
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[646] | 338 | if (newone.bitstr.length() == 1) { |
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| 339 | for (int j = 0; j < global_best.length(); j++){ |
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| 340 | for(int i = 0; i < global_best(j).bitstr.length(); i++){ |
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| 341 | |
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| 342 | if (newone.bitstr(0) == global_best(j).bitstr(i)){ |
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| 343 | addit = 0; |
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| 344 | break; |
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| 345 | } |
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[648] | 346 | } |
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| 347 | } |
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[646] | 348 | } |
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| 349 | if (addit){ |
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| 350 | global_best_out(i) = newone; |
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| 351 | // DEBUGging print: |
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| 352 | // fprintf('ADDED structure, add_new: %s, loglik=%g\n', strPrintstr(new), new.loglik); |
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[648] | 353 | } |
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| 354 | } |
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[646] | 355 | } |
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| 356 | else |
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| 357 | global_best_out = concat(global_best, newone); |
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| 358 | |
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| 359 | return global_best_out; |
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[648] | 360 | |
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[646] | 361 | } |
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[648] | 362 | |
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[646] | 363 | */ |
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[648] | 364 | |
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| 365 | void add_new ( Array<str_aux> &global_best, str_aux newone, int nbest ) { |
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[646] | 366 | // Eventually add to global best, but do not go over nbest values |
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| 367 | // Also avoids repeating things, which makes this function awfully slow |
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| 368 | |
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[648] | 369 | int addit, i = 0; |
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| 370 | if ( global_best.length() >= nbest ) { |
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| 371 | //logliks = [global_best.loglik]; |
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[646] | 372 | |
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[648] | 373 | |
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| 374 | for ( int j = 1; j < global_best.length(); j++ ) { |
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| 375 | if ( global_best ( j ).loglik < global_best ( i ).loglik ) { |
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| 376 | i = j; |
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| 377 | } |
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| 378 | } |
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| 379 | |
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| 380 | if ( global_best ( i ).loglik < newone.loglik ) { |
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| 381 | // if ~any(logliks == new.loglik); |
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| 382 | addit = 1; |
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| 383 | |
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| 384 | |
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| 385 | //???????????????????????????????????????????? |
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| 386 | if ( newone.bitstr.length() == 1 ) { |
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| 387 | for ( int j = 0; j < global_best.length(); j++ ) { |
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| 388 | for ( int i = 0; i < global_best ( j ).bitstr.length(); i++ ) { |
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| 389 | |
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| 390 | if ( newone.bitstr ( 0 ) == global_best ( j ).bitstr ( i ) ) { |
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| 391 | addit = 0; |
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| 392 | break; |
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| 393 | } |
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| 394 | } |
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| 395 | } |
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| 396 | } |
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| 397 | |
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| 398 | |
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| 399 | //????????????????????????????????????????????????? |
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| 400 | |
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| 401 | if ( addit ) { |
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| 402 | global_best ( i ) = newone; |
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| 403 | // DEBUGging print: |
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| 404 | // fprintf('ADDED structure, add_new: %s, loglik=%g\n', strPrintstr(new), new.loglik); |
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| 405 | } |
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| 406 | } |
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| 407 | } else |
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| 408 | global_best = concat ( global_best, newone ); |
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| 409 | |
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[646] | 410 | } |
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[648] | 411 | |
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| 412 | |
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| 413 | |
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| 414 | |
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| 415 | |
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| 416 | |
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| 417 | str_aux sestrinsert ( str_aux in, ivec inserted_elements ) { |
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[646] | 418 | // Moves elements into regressor |
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[648] | 419 | int n_strL = in.strL.length(); |
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| 420 | str_aux out = in; |
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| 421 | for ( int j = 0; j < inserted_elements.length(); j++ ) { |
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| 422 | int f = inserted_elements ( j ); |
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| 423 | int posit1 = ( find ( out.strL == 1 ) ) ( 0 ); |
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| 424 | int positf = ( find ( out.strL == f ) ) ( 0 ); |
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| 425 | for ( int g = positf; g <= posit1 - 1; g++ ) { |
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[646] | 426 | |
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[648] | 427 | // BEGIN: We are swapping g and g+1 NOW!!!! |
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| 428 | seswapudl ( out.L, out.d, g ); |
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| 429 | seswapudl ( out.L0, out.d0, g ); |
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| 430 | |
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| 431 | |
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| 432 | int pom_strL = out.strL ( g ); |
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| 433 | out.strL ( g ) = out.strL ( g + 1 ); |
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| 434 | out.strL ( g + 1 ) = pom_strL; |
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| 435 | |
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| 436 | // END |
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| 437 | } |
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| 438 | } |
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| 439 | |
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| 440 | out.posit1 = ( find ( out.strL == 1 ) ) ( 0 ) + 1; |
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| 441 | out.strRgr = out.strL.right ( n_strL - out.posit1 ); |
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| 442 | out.strMis = out.strL.left ( out.posit1 - 1 ); |
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| 443 | str_bitset ( out.bitstr, inserted_elements, out.nbits ); |
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| 444 | |
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| 445 | out.loglik = seloglik1 ( out ); |
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| 446 | |
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| 447 | |
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| 448 | |
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| 449 | return out; |
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| 450 | |
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| 451 | } |
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| 452 | |
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| 453 | double seloglik2 ( str_aux in ) { |
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[646] | 454 | // This is the loglikelihood (constant part) - this should be added to |
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| 455 | // everything at the end. It needs some computation, so it is useless to |
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| 456 | // make it for all the stuff |
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[648] | 457 | double logpi = log ( pi ); |
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[646] | 458 | |
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[648] | 459 | double i1 = lgamma ( in.nu / 2 ) - 0.5 * in.nu * logpi; |
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| 460 | double i0 = lgamma ( in.nu0 / 2 ) - 0.5 * in.nu0 * logpi; |
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| 461 | return i1 - i0; |
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| 462 | } |
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[646] | 463 | |
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[648] | 464 | |
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| 465 | |
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| 466 | |
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| 467 | ivec straux1 ( ldmat Ld, double nu, ldmat Ld0, double nu0, ivec belief, int nbest, int max_nrep, double lambda, int order_k, Array<str_aux> &rgrsout/*, stat &statistics*/ ) { |
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[646] | 468 | // see utia_legacy/ticket_12/ implementation and str_test.m |
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| 469 | |
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[648] | 470 | const mat &L = Ld._L(); |
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| 471 | const vec &d = Ld._D(); |
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[646] | 472 | |
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[648] | 473 | const mat &L0 = Ld0._L(); |
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| 474 | const vec &d0 = Ld0._D(); |
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[646] | 475 | |
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[648] | 476 | int n_data = d.length(); |
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[646] | 477 | |
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[648] | 478 | ivec belief_out = find ( belief == 4 ) + 2; // we are avoiding to put this into regressor |
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| 479 | ivec belief_in = find ( belief == 1 ) + 2; // we are instantly keeping this in regressor |
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[646] | 480 | |
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| 481 | |
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[648] | 482 | str_aux full; |
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[646] | 483 | |
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[648] | 484 | full.d0 = d0; |
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| 485 | full.nu0 = nu0; |
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| 486 | full.L0 = L0; |
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| 487 | full.L = L; |
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| 488 | full.d = d; |
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[646] | 489 | |
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| 490 | |
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| 491 | |
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[648] | 492 | /*full.d0 = "0.012360650875200 0.975779169502626 1.209840558439000"; |
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[646] | 493 | |
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[648] | 494 | full.L0 = "1.0000 0 0;" |
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| 495 | "0.999427690134298 1.0000 0;" |
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| 496 | "0.546994424043659 0.534335486953833 1.0000"; |
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[646] | 497 | |
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| 498 | |
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[648] | 499 | full.L = "1.0000 0 0;" |
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| 500 | "0.364376353850780 1.0000 0;" |
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| 501 | "1.222141096674815 1.286534510946323 1.0000"; |
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[646] | 502 | |
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[648] | 503 | full.d = "0.001610356837691 3.497566869589465 3.236640487818002"; |
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| 504 | */ |
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[646] | 505 | |
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[648] | 506 | fstream F; |
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[646] | 507 | |
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| 508 | |
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| 509 | |
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| 510 | |
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[648] | 511 | F.open ( "soubor3.txt", ios::in ); |
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| 512 | F << setiosflags ( ios::scientific ); |
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| 513 | F << setprecision ( 16 ); |
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[661] | 514 | // F.flags ( 0x1 ); |
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[646] | 515 | |
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| 516 | |
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[648] | 517 | for ( int i = 0; i < n_data ; i++ ) { |
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| 518 | F >> full.d0 ( i ); |
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| 519 | } |
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[646] | 520 | |
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| 521 | |
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| 522 | |
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[648] | 523 | for ( int i = 0; i < n_data; i++ ) { |
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| 524 | for ( int j = 0 ; j < n_data ; j++ ) { |
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| 525 | F >> full.L0 ( j, i ); |
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| 526 | } |
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| 527 | } |
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[646] | 528 | |
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[648] | 529 | for ( int i = 0; i < n_data ; i++ ) { |
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| 530 | F >> full.d ( i ); |
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| 531 | } |
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[646] | 532 | |
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| 533 | |
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[648] | 534 | for ( int i = 0; i < n_data; i++ ) { |
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| 535 | for ( int j = 0 ; j < n_data ; j++ ) { |
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| 536 | F >> full.L ( j, i ); |
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| 537 | } |
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| 538 | } |
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[646] | 539 | |
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[648] | 540 | |
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| 541 | full.nu0 = nu0; |
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| 542 | full.nu = nu; |
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| 543 | full.strL = linspace ( 1, n_data ); |
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| 544 | full.strRgr = linspace ( 2, n_data ); |
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| 545 | full.strMis = ivec ( 0 ); |
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| 546 | full.posit1 = 1; |
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| 547 | full.bitstr.set_size ( n_data - 1 ); |
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| 548 | full.bitstr.clear(); |
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| 549 | str_bitset ( full.bitstr, full.strRgr, full.nbits ); |
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[646] | 550 | //full.nbits = std::numeric_lim its<double>::digits-1; // number of bits available in double |
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[648] | 551 | /*bvec in(n_data-1); |
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| 552 | in.clear(); |
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| 553 | full.bitstr = str_bitset(in,full.strRgr,full.nbits);*/ |
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[646] | 554 | |
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| 555 | |
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| 556 | |
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| 557 | |
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[648] | 558 | full.loglik = seloglik1 ( full ); // % loglikelihood |
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[646] | 559 | |
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| 560 | |
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| 561 | |
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| 562 | |
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[648] | 563 | |
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[646] | 564 | //% construct full and empty structure |
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[648] | 565 | full = sestrremove ( full, belief_out ); |
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| 566 | str_aux empty = sestrremove ( full, setdiff ( full.strRgr, belief_in ) ); |
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| 567 | |
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[646] | 568 | //% stopping rule calculation: |
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| 569 | |
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| 570 | |
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| 571 | |
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| 572 | |
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[648] | 573 | bmat local_max ( 0, 0 ); |
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| 574 | int to, muto = 0; |
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| 575 | |
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[646] | 576 | //% statistics: |
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[648] | 577 | //double cputime0 = cputime; |
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[646] | 578 | //if nargout>=3; |
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| 579 | |
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[648] | 580 | CPU_Timer timer; |
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| 581 | timer.start(); |
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[646] | 582 | |
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[648] | 583 | ivec mutos ( max_nrep + 2 ); |
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| 584 | vec maxmutos ( max_nrep + 2 ); |
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| 585 | mutos.zeros(); |
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| 586 | maxmutos.zeros(); |
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| 587 | |
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| 588 | |
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[646] | 589 | //end; |
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| 590 | //% ---------------------- |
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[648] | 591 | |
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[646] | 592 | //% For stopping-rule calculation |
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| 593 | //%so = 2^(n_data -1-length(belief_in)- length(belief_out)); % do we use this ? |
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| 594 | //% ---------------------- |
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| 595 | |
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[648] | 596 | ivec all_str = linspace ( 1, n_data ); |
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[646] | 597 | |
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[648] | 598 | Array<str_aux> global_best ( 1 ); |
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| 599 | global_best ( 0 ) = full; |
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| 600 | |
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| 601 | |
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[646] | 602 | //% MAIN LOOP is here. |
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| 603 | |
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[648] | 604 | str_aux best; |
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| 605 | for ( int n_start = -1; n_start <= max_nrep; n_start++ ) { |
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| 606 | str_aux last, best; |
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| 607 | |
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| 608 | to = n_start + 2; |
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| 609 | |
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| 610 | if ( n_start == -1 ) { |
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| 611 | //% start from the full structure |
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| 612 | last = full; |
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| 613 | } else { |
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| 614 | if ( n_start == 0 ) |
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| 615 | //% start from the empty structure |
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| 616 | last = empty; |
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| 617 | |
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| 618 | else { |
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| 619 | //% start from random structure |
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| 620 | |
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| 621 | ivec last_str = find ( to_bvec<int> ( ::concat<int> ( 0, floor_i ( 2 * randu ( n_data - 1 ) ) ) ) );// this creates random vector consisting of indexes, and sorted |
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| 622 | last = sestrremove ( full, setdiff ( all_str, ::concat<int> ( ::concat<int> ( 1 , last_str ), empty.strRgr ) ) ); |
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| 623 | |
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| 624 | } |
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[646] | 625 | } |
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[648] | 626 | //% DEBUGging print: |
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| 627 | //%fprintf('STRUCTURE generated in loop %2i was %s\n', n_start, strPrintstr(last)); |
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| 628 | |
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| 629 | //% The loop is repeated until likelihood stops growing (break condition |
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| 630 | //% used at the end; |
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| 631 | |
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| 632 | |
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| 633 | while ( 1 ) { |
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| 634 | //% This structure is going to hold the best elements |
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| 635 | best = last; |
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| 636 | //% Nesting by removing elements (enpoorment) |
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| 637 | ivec removed_items = setdiff ( last.strRgr, belief_in ); |
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| 638 | |
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| 639 | ivec removed_item; |
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| 640 | str_aux newone; |
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| 641 | |
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| 642 | for ( int i = 0; i < removed_items.length(); i++ ) { |
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| 643 | removed_item = vec_1 ( removed_items ( i ) ); |
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| 644 | newone = sestrremove ( last, removed_item ); |
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| 645 | if ( nbest > 1 ) { |
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| 646 | add_new ( global_best, newone, nbest ); |
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| 647 | } |
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| 648 | if ( newone.loglik > best.loglik ) { |
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| 649 | best = newone; |
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| 650 | } |
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| 651 | } |
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| 652 | //% Nesting by adding elements (enrichment) |
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| 653 | ivec added_items = setdiff ( last.strMis, belief_out ); |
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| 654 | ivec added_item; |
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| 655 | |
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| 656 | for ( int j = 0; j < added_items.length(); j++ ) { |
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| 657 | added_item = vec_1 ( added_items ( j ) ); |
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| 658 | newone = sestrinsert ( last, added_item ); |
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| 659 | if ( nbest > 1 ) { |
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| 660 | add_new ( global_best, newone, nbest ); |
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| 661 | } |
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| 662 | if ( newone.loglik > best.loglik ) { |
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| 663 | best = newone; |
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| 664 | } |
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| 665 | } |
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| 666 | |
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| 667 | |
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| 668 | |
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| 669 | |
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| 670 | |
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| 671 | //% Break condition if likelihood does not change. |
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| 672 | if ( best.loglik <= last.loglik ) |
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| 673 | break; |
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| 674 | else |
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| 675 | //% Making best structure last structure. |
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| 676 | last = best; |
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| 677 | |
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| 678 | |
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[646] | 679 | } |
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[648] | 680 | |
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| 681 | |
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| 682 | |
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| 683 | |
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| 684 | |
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| 685 | // % DEBUGging print: |
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| 686 | //%fprintf('STRUCTURE found (local maxima) in loop %2i was %s randun_seed=%11lu randun_counter=%4lu\n', n_start, strPrintstr(best), randn('seed'), RANDUN_COUNTER); |
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| 687 | |
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| 688 | //% Collecting of the best structure in case we don't need the second parameter |
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| 689 | if ( nbest <= 1 ) { |
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| 690 | if ( best.loglik > global_best ( 0 ).loglik ) { |
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| 691 | global_best = best; |
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| 692 | } |
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[646] | 693 | } |
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| 694 | |
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[648] | 695 | //% uniqueness of the structure found |
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| 696 | int append = 1; |
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[646] | 697 | |
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| 698 | |
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[648] | 699 | for ( int j = 0; j < local_max.rows() ; j++ ) { |
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| 700 | if ( best.bitstr == local_max.get_row ( j ) ) { |
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| 701 | append = 0; |
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| 702 | break; |
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| 703 | } |
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| 704 | } |
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[646] | 705 | |
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| 706 | |
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[648] | 707 | if ( append ) { |
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| 708 | local_max.append_row ( best.bitstr ); |
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| 709 | muto = muto + 1; |
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| 710 | } |
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[646] | 711 | |
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[648] | 712 | //% stopping rule: |
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| 713 | double maxmuto = ( to - order_k - 1 ) / lambda - to + 1; |
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| 714 | if ( to > 2 ) { |
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| 715 | if ( maxmuto >= muto ) { |
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| 716 | //% fprintf('*'); |
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| 717 | break; |
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| 718 | } |
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| 719 | } |
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[646] | 720 | |
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[648] | 721 | // do statistics if necessary: |
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| 722 | //if (nargout>=3){ |
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| 723 | mutos ( to - 1 ) = muto; |
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| 724 | maxmutos ( to - 1 ) = maxmuto; |
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| 725 | //} |
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| 726 | } |
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[646] | 727 | |
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| 728 | //% Aftermath: The best structure was in: global_best |
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[648] | 729 | |
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[646] | 730 | //% Updating loglikelihoods: we have to add the constant stuff |
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| 731 | |
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| 732 | |
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| 733 | |
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[648] | 734 | for ( int f = 0 ; f < global_best.length(); f++ ) { |
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| 735 | global_best ( f ).loglik = global_best ( f ).loglik + seloglik2 ( global_best ( f ) ); |
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| 736 | } |
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[646] | 737 | |
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[648] | 738 | /*for f=1:length(global_best); |
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| 739 | global_best(f).loglik = global_best(f).loglik + seloglik2(global_best(f)); |
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| 740 | end;*/ |
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[646] | 741 | |
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[648] | 742 | |
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[646] | 743 | //% Making first output parameter: |
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| 744 | |
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[648] | 745 | int max_i = 0; |
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| 746 | for ( int j = 1; j < global_best.length(); j++ ) |
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| 747 | if ( global_best ( max_i ).loglik < ( global_best ( j ).loglik ) ) max_i = j; |
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[646] | 748 | |
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[648] | 749 | best = global_best ( max_i ); |
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[646] | 750 | |
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| 751 | //% Making the second output parameter |
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| 752 | |
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[648] | 753 | vec logliks ( global_best.length() ); |
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| 754 | for ( int j = 0; j < logliks.length(); j++ ) |
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| 755 | logliks ( j ) = global_best ( j ).loglik; |
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[646] | 756 | |
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[648] | 757 | ivec i = sort_index ( logliks ); |
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| 758 | rgrsout.set_length ( global_best.length() ); |
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[646] | 759 | |
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[648] | 760 | for ( int j = global_best.length() - 1; j >= 0; j-- ) |
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| 761 | rgrsout ( j ) = global_best ( i ( j ) ); |
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| 762 | |
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[646] | 763 | //if (nargout>=3); |
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| 764 | |
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[648] | 765 | |
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| 766 | str_statistics statistics; |
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| 767 | |
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| 768 | statistics.allstrs = 2 ^ ( n_data - 1 - length ( belief_in ) - length ( belief_out ) ); |
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| 769 | statistics.nrand = to - 2; |
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| 770 | statistics.unique = muto; |
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| 771 | statistics.to = to; |
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| 772 | statistics.cputime_seconds = timer.get_time(); |
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| 773 | statistics.itemspeed = statistics.to / statistics.cputime_seconds; |
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| 774 | statistics.muto = muto; |
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| 775 | statistics.mutos = mutos; |
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| 776 | statistics.maxmutos = maxmutos; |
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[646] | 777 | //end; |
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| 778 | |
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[648] | 779 | return best.strRgr; |
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[646] | 780 | |
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[648] | 781 | } |
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[646] | 782 | |
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| 783 | #ifdef LADIM |
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| 784 | //% randun seed stuff: |
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| 785 | //%randn('seed',SEED); |
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[648] | 786 | |
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[646] | 787 | //% --------------------- END of MAIN program -------------------- |
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[648] | 788 | |
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[646] | 789 | % This is needed for bitstr manipulations |
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| 790 | /*function out = str_bitset(in,ns,nbits) |
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| 791 | out = in; |
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| 792 | for n = ns; |
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| 793 | index = 1+floor((n-2)/nbits); |
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| 794 | bitindex = 1+rem(n-2,nbits); |
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| 795 | out(index) = bitset(out(index),bitindex); |
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[648] | 796 | end; |
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[646] | 797 | function out = str_bitres(in,ns,nbits) |
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| 798 | out = in; |
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| 799 | for n = ns; |
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| 800 | index = 1+floor((n-2)/nbits); |
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| 801 | bitindex = 1+rem(n-2,nbits); |
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| 802 | mask = bitset(0,bitindex); |
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| 803 | out(index) = bitxor(bitor(out(index),mask),mask); |
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| 804 | end;*/ |
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[648] | 805 | |
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| 806 | function out = strPrintstr ( in ) |
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| 807 | out = '0'; |
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| 808 | nbits = in.nbits; |
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| 809 | for f = 2: |
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| 810 | length ( in.d0 ); |
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| 811 | index = 1 + floor ( ( f - 2 ) / nbits ); |
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| 812 | bitindex = 1 + rem ( f - 2, nbits ); |
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| 813 | if bitget ( in.bitstr ( index ), bitindex ); |
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| 814 | out ( f ) = '1'; |
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| 815 | else; |
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| 816 | out ( f ) = '0'; |
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| 817 | end; |
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| 818 | end; |
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| 819 | |
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[646] | 820 | /*function global_best_out = add_new(global_best,new,nbest) |
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| 821 | % Eventually add to global best, but do not go over nbest values |
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| 822 | % Also avoids repeating things, which makes this function awfully slow |
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| 823 | if length(global_best)>=nbest; |
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| 824 | logliks = [global_best.loglik]; |
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| 825 | [loglik i] = min(logliks); |
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| 826 | global_best_out = global_best; |
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| 827 | if loglik<new.loglik; |
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| 828 | % if ~any(logliks == new.loglik); |
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| 829 | addit=1; |
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| 830 | for f = [global_best.bitstr]; |
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| 831 | if f == new.bitstr; |
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| 832 | addit = 0; |
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| 833 | break; |
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| 834 | end; |
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[648] | 835 | end; |
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[646] | 836 | if addit; |
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| 837 | global_best_out(i) = new; |
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| 838 | % DEBUGging print: |
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| 839 | % fprintf('ADDED structure, add_new: %s, loglik=%g\n', strPrintstr(new), new.loglik); |
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[648] | 840 | end; |
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[646] | 841 | end; |
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| 842 | else; |
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| 843 | global_best_out = [global_best new]; |
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| 844 | end;*/ |
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[648] | 845 | |
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[646] | 846 | /*function out = sestrremove(in,removed_elements); |
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| 847 | % Removes elements from regressor |
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| 848 | n_strL = length(in.strL); |
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| 849 | out = in; |
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| 850 | for f=removed_elements; |
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| 851 | posit1 = find(out.strL==1); |
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| 852 | positf = find(out.strL==f); |
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| 853 | for g=(positf-1):-1:posit1; |
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| 854 | % BEGIN: We are swapping g and g+1 NOW!!!! |
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| 855 | [out.L, out.d] = seswapudl(out.L, out.d, g); |
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| 856 | [out.L0, out.d0] = seswapudl(out.L0, out.d0, g); |
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| 857 | out.strL([g g+1]) = [out.strL(g+1) out.strL(g)]; |
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| 858 | % END |
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| 859 | end; |
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| 860 | end; |
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| 861 | out.posit1 = find(out.strL==1); |
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| 862 | out.strRgr = out.strL((out.posit1+1):n_strL); |
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| 863 | out.strMis = out.strL(1:(out.posit1-1)); |
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| 864 | out.bitstr = str_bitres(out.bitstr,removed_elements,out.nbits); |
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| 865 | out.loglik = seloglik1(out);*/ |
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[648] | 866 | |
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[646] | 867 | /*function out = sestrinsert(in,inserted_elements); |
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| 868 | % Moves elements into regressor |
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| 869 | n_strL = length(in.strL); |
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| 870 | out = in; |
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| 871 | for f=inserted_elements; |
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| 872 | posit1 = find(out.strL==1); |
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| 873 | positf = find(out.strL==f); |
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| 874 | for g=positf:(posit1-1); |
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| 875 | % BEGIN: We are swapping g and g+1 NOW!!!! |
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| 876 | [out.L, out.d] = seswapudl(out.L, out.d, g); |
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| 877 | [out.L0, out.d0] = seswapudl(out.L0, out.d0, g); |
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| 878 | out.strL([g g+1]) = [out.strL(g+1) out.strL(g)]; |
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| 879 | % END |
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| 880 | end; |
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[648] | 881 | end; |
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[646] | 882 | out.posit1 = find(out.strL==1); |
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| 883 | out.strRgr = out.strL((out.posit1+1):n_strL); |
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| 884 | out.strMis = out.strL(1:(out.posit1-1)); |
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| 885 | out.bitstr = str_bitset(out.bitstr,inserted_elements,out.nbits); |
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| 886 | out.loglik = seloglik1(out);*/ |
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[648] | 887 | |
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[646] | 888 | % |
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| 889 | % seloglik_real = seloglik1 + seloglik2 |
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[648] | 890 | % |
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| 891 | |
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| 892 | /*function l = seloglik1(in) |
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| 893 | % This is the loglikelihood (non-constant part) - this should be used in |
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| 894 | % frequent computation |
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| 895 | len = length(in.d); |
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| 896 | p1 = in.posit1; |
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| 897 | |
---|
| 898 | i1 = -0.5*in.nu *log(in.d (p1)) -0.5*sum(log(in.d ((p1+1):len))); |
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| 899 | i0 = -0.5*in.nu0*log(in.d0(p1)) -0.5*sum(log(in.d0((p1+1):len))); |
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| 900 | l = i1-i0; |
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| 901 | |
---|
| 902 | % DEBUGGing print: |
---|
| 903 | % fprintf('SELOGLIK1: str=%s loglik=%g\n', strPrintstr(in), l);*/ |
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| 904 | |
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| 905 | |
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| 906 | function l = seloglik2 ( in ) |
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| 907 | % This is the loglikelihood ( constant part ) - this should be added to |
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| 908 | % everything at the end. It needs some computation, so it is useless to |
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| 909 | % make it for all the stuff |
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| 910 | logpi = log ( pi ); |
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| 911 | |
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| 912 | i1 = gammaln ( in.nu / 2 ) - 0.5*in.nu *logpi; |
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| 913 | i0 = gammaln ( in.nu0 / 2 ) - 0.5*in.nu0*logpi; |
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| 914 | l = i1 - i0; |
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| 915 | |
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| 916 | |
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[646] | 917 | /*function [Lout, dout] = seswapudl(L,d,i); |
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| 918 | %SESWAPUDL swaps information matrix in decomposition V=L^T diag(d) L |
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| 919 | % |
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| 920 | % [Lout, dout] = seswapudl(L,d,i); |
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| 921 | % |
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| 922 | % L : lower triangular matrix with 1's on diagonal of the decomposistion |
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| 923 | % d : diagonal vector of diagonal matrix of the decomposition |
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[648] | 924 | % i : index of line to be swapped with the next one |
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[646] | 925 | % Lout : output lower triangular matrix |
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| 926 | % dout : output diagional vector of diagonal matrix D |
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| 927 | % |
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| 928 | % Description: |
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| 929 | % Lout' * diag(dout) * Lout = P(i,i+1) * L' * diag(d) * L * P(i,i+1); |
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[648] | 930 | % |
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[646] | 931 | % Where permutation matrix P(i,j) permutates columns if applied from the |
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| 932 | % right and line if applied from the left. |
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[648] | 933 | % |
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[646] | 934 | % Note: naming: |
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| 935 | % se = structure estimation |
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| 936 | % lite = light, simple |
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| 937 | % udl = U*D*L, or more precisely, L'*D*L, also called as ld |
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[648] | 938 | % |
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[646] | 939 | % Design : L. Tesar |
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| 940 | % Updated : Feb 2003 |
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| 941 | % Project : post-ProDaCTool |
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| 942 | % Reference: sedydr |
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[648] | 943 | |
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[646] | 944 | j = i+1; |
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[648] | 945 | |
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[646] | 946 | pomd = d(i); |
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| 947 | d(i) = d(j); |
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| 948 | d(j) = pomd; |
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[648] | 949 | |
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[646] | 950 | pomL = L(i,:); |
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| 951 | L(i,:) = L(j,:); |
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| 952 | L(j,:) = pomL; |
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[648] | 953 | |
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[646] | 954 | pomL = L(:,i); |
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| 955 | L(:,i) = L(:,j); |
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| 956 | L(:,j) = pomL; |
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[648] | 957 | |
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[646] | 958 | % We must be working with LINES of matrix L ! |
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[648] | 959 | |
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| 960 | r = L(i,:)'; |
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[646] | 961 | f = L(j,:)'; |
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| 962 | Dr = d(i); |
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| 963 | Df = d(j); |
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[648] | 964 | |
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[646] | 965 | [r, f, Dr, Df] = sedydr(r, f, Dr, Df, j); |
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[648] | 966 | |
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[646] | 967 | r0 = r(i); |
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| 968 | Dr = Dr*r0*r0; |
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| 969 | r = r/r0; |
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[648] | 970 | |
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| 971 | L(i,:) = r'; |
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[646] | 972 | L(j,:) = f'; |
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| 973 | d(i) = Dr; |
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| 974 | d(j) = Df; |
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[648] | 975 | |
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[646] | 976 | L(i,i) = 1; |
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| 977 | L(j,j) = 1; |
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[648] | 978 | |
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[646] | 979 | Lout = L; |
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| 980 | dout = d;*/ |
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[648] | 981 | |
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[646] | 982 | /*function [rout, fout, Drout, Dfout, kr] = sedydr(r,f,Dr,Df,R,jl,jh); |
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| 983 | %SEDYDR dyadic reduction, performs transformation of sum of 2 dyads |
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| 984 | % |
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| 985 | % [rout, fout, Drout, Dfout, kr] = sedydr(r,f,Dr,Df,R,jl,jh); |
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| 986 | % [rout, fout, Drout, Dfout] = sedydr(r,f,Dr,Df,R); |
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| 987 | % |
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[648] | 988 | % Description: dyadic reduction, performs transformation of sum of |
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[646] | 989 | % 2 dyads r*Dr*r'+ f*Df*f' so that the element of r pointed by R is zeroed |
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| 990 | % |
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| 991 | % r : column vector of reduced dyad |
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| 992 | % f : column vector of reducing dyad |
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| 993 | % Dr : scalar with weight of reduced dyad |
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| 994 | % Df : scalar with weight of reducing dyad |
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| 995 | % R : scalar number giving 1 based index to the element of r, |
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[648] | 996 | % which is to be reduced to |
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[646] | 997 | % zero; the corresponding element of f is assumed to be 1. |
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[648] | 998 | % jl : lower index of the range within which the dyads are |
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[646] | 999 | % modified (can be omitted, then everything is updated) |
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[648] | 1000 | % jh : upper index of the range within which the dyads are |
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[646] | 1001 | % modified (can be omitted then everything is updated) |
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| 1002 | % rout,fout,Drout,dfout : resulting two dyads |
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| 1003 | % kr : coefficient used in the transformation of r |
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| 1004 | % rnew = r + kr*f |
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| 1005 | % |
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[648] | 1006 | % Description: dyadic reduction, performs transformation of sum of |
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[646] | 1007 | % 2 dyads r*Dr*r'+ f*Df*f' so that the element of r indexed by R is zeroed |
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| 1008 | % Remark1: Constant mzero means machine zero and should be modified |
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| 1009 | % according to the precision of particular machine |
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| 1010 | % Remark2: jl and jh are, in fact, obsolete. It takes longer time to |
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| 1011 | % compute them compared to plain version. The reason is that we |
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| 1012 | % are doing vector operations in m-file. Other reason is that |
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| 1013 | % we need to copy whole vector anyway. It can save half of time for |
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| 1014 | % c-file, if you use it correctly. (please do tests) |
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| 1015 | % |
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| 1016 | % Note: naming: |
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| 1017 | % se = structure estimation |
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| 1018 | % dydr = dyadic reduction |
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| 1019 | % |
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| 1020 | % Original Fortran design: V. Peterka 17-7-89 |
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| 1021 | % Modified for c-language: probably R. Kulhavy |
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| 1022 | % Modified for m-language: L. Tesar 2/2003 |
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| 1023 | % Updated: Feb 2003 |
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| 1024 | % Project: post-ProDaCTool |
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| 1025 | % Reference: none |
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[648] | 1026 | |
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[646] | 1027 | if nargin<6; |
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| 1028 | update_whole=1; |
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| 1029 | else |
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| 1030 | update_whole=0; |
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| 1031 | end; |
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[648] | 1032 | |
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[646] | 1033 | mzero = 1e-32; |
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[648] | 1034 | |
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[646] | 1035 | if Dr<mzero; |
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| 1036 | Dr=0; |
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| 1037 | end; |
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[648] | 1038 | |
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[646] | 1039 | r0 = r(R); |
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| 1040 | kD = Df; |
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| 1041 | kr = r0 * Dr; |
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| 1042 | Dfout = kD + r0 * kr; |
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[648] | 1043 | |
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[646] | 1044 | if Dfout > mzero; |
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| 1045 | kD = kD / Dfout; |
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| 1046 | kr = kr / Dfout; |
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| 1047 | else; |
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| 1048 | kD = 1; |
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| 1049 | kr = 0; |
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| 1050 | end; |
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[648] | 1051 | |
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[646] | 1052 | Drout = Dr * kD; |
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[648] | 1053 | |
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[646] | 1054 | % Try to uncomment marked stuff (*) if in numerical problems, but I don't |
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| 1055 | % think it can make any difference for normal healthy floating-point unit |
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| 1056 | if update_whole; |
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| 1057 | rout = r - r0*f; |
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| 1058 | % rout(R) = 0; % * could be needed for some nonsense cases(or numeric reasons?), normally not |
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| 1059 | fout = f + kr*rout; |
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| 1060 | % fout(R) = 1; % * could be needed for some nonsense cases(or numeric reasons?), normally not |
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[648] | 1061 | else; |
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[646] | 1062 | rout = r; |
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| 1063 | fout = f; |
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| 1064 | rout(jl:jh) = r(jl:jh) - r0 * f(jl:jh); |
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[648] | 1065 | rout(R) = 0; |
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[646] | 1066 | fout(jl:jh) = f(jl:jh) + kr * rout(jl:jh); |
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| 1067 | end;*/ |
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[648] | 1068 | |
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| 1069 | |
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| 1070 | |
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[646] | 1071 | #endif |
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[648] | 1072 | |
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| 1073 | |
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[646] | 1074 | } |
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