--- /dev/null
+/* -*- mode: c; tab-width: 4; c-basic-offset: 4; indent-tabs-mode: nil -*- */
+
+/*********************************************************************
+ * Clustal Omega - Multiple sequence alignment
+ *
+ * Copyright (C) 2010 University College Dublin
+ *
+ * Clustal-Omega is free software; you can redistribute it and/or
+ * modify it under the terms of the GNU General Public License as
+ * published by the Free Software Foundation; either version 2 of the
+ * License, or (at your option) any later version.
+ *
+ * This file is part of Clustal-Omega.
+ *
+ ********************************************************************/
+
+/*
+ * RCS $Id: hhhit-C.h 245 2011-06-15 12:38:53Z fabian $
+ */
+
+// hhhit.C
+
+#ifndef MAIN
+#define MAIN
+#include <iostream> // cin, cout, cerr
+#include <fstream> // ofstream, ifstream
+#include <stdio.h> // printf
+using std::cout;
+using std::cerr;
+using std::endl;
+using std::ios;
+using std::ifstream;
+using std::ofstream;
+#include <stdlib.h> // exit
+#include <string> // strcmp, strstr
+#include <math.h> // sqrt, pow
+#include <limits.h> // INT_MIN
+#include <float.h> // FLT_MIN
+#include <time.h> // clock
+#include <ctype.h> // islower, isdigit etc
+#include "util-C.h" // imax, fmax, iround, iceil, ifloor, strint, strscn, strcut, substr, uprstr, uprchr, Basename etc.
+#include "list.h" // list data structure
+#include "hash.h" // hash data structure
+#include "hhdecl-C.h" // constants, class
+#include "hhutil-C.h" // imax, fmax, iround, iceil, ifloor, strint, strscn, strcut, substr, uprstr, uprchr, Basename etc.
+#include "hhhmm.h" // class HMM
+#include "hhalignment.h" // class Alignment
+#include "hhhitlist.h" // class HitList
+#endif
+
+#define CALCULATE_MAX6(max, var1, var2, var3, var4, var5, var6, varb) \
+if (var1>var2) { max=var1; varb=STOP;} \
+else { max=var2; varb=MM;}; \
+if (var3>max) { max=var3; varb=GD;}; \
+if (var4>max) { max=var4; varb=IM;}; \
+if (var5>max) { max=var5; varb=DG;}; \
+if (var6>max) { max=var6; varb=MI;};
+
+#define CALCULATE_SUM6(sum, var1, var2, var3, var4, var5, var6, varb) \
+if (var1>var2) { sum=var1; varb=STOP;} \
+else { sum=var2; varb=MM;}; \
+if (var3>sum) { sum=var3; varb=GD;}; \
+if (var4>sum) { sum=var4; varb=IM;}; \
+if (var5>sum) { sum=var5; varb=DG;}; \
+if (var6>sum) { sum=var6; varb=MI;}; \
+sum = var1 + var2 + var3 + var4 + var5 + var6;
+
+#define CALCULATE_MAX4(max, var1, var2, var3, var4, varb) \
+if (var1>var2) { max=var1; varb=STOP;} \
+else { max=var2; varb=MM;}; \
+if (var3>max) { max=var3; varb=MI;}; \
+if (var4>max) { max=var4; varb=IM;};
+
+// Generate random number in [0,1[
+#define frand() ((float) rand()/(RAND_MAX+1.0))
+
+
+// Function declarations
+inline float Score(float* qi, float* tj);
+inline float ProbFwd(float* qi, float* tj);
+inline float max2(const float& xMM, const float& xX, char& b);
+inline int pickprob2(const double& xMM, const double& xX, const int& state);
+inline int pickprob3_GD(const double& xMM, const double& xDG, const double& xGD);
+inline int pickprob3_IM(const double& xMM, const double& xMI, const double& xIM);
+inline int pickprob6(const double& x0, const double& xMM, const double& xGD, const double& xIM, const double& xDG, const double& xMI);
+inline int pickmax2(const double& xMM, const double& xX, const int& state);
+inline int pickmax3_GD(const double& xMM, const double& xDG, const double& xGD);
+inline int pickmax3_IM(const double& xMM, const double& xMI, const double& xIM);
+inline int pickmax6(const double& x0, const double& xMM, const double& xGD, const double& xIM, const double& xDG, const double& xMI);
+inline double Pvalue(double x, double a[]);
+inline double Pvalue(float x, float lamda, float mu);
+inline double logPvalue(float x, float lamda, float mu);
+inline double logPvalue(float x, double a[]);
+inline double Probab(Hit& hit);
+
+//////////////////////////////////////////////////////////////////////////////
+//// Constructor
+//////////////////////////////////////////////////////////////////////////////
+Hit::Hit()
+{
+ longname = name = file = dbfile = NULL;
+ sname = NULL;
+ seq = NULL;
+ bMM = bGD = bDG = bIM = bMI = NULL;
+ self = 0;
+ i = j = NULL;
+ states = NULL;
+ S = S_ss = P_posterior = NULL;
+ Xcons = NULL;
+ B_MM=B_MI=B_IM=B_DG=B_GD=NULL;
+ F_MM=F_MI=F_IM=F_DG=F_GD=NULL;
+ cell_off = NULL;
+ scale = NULL;
+ sum_of_probs=0.0;
+ Neff_HMM=0.0;
+ score_ss = Pval = logPval = Eval = Probab = Pforward = 0.0;
+ nss_conf = nfirst = i1 = i2 = j1 = j2 = matched_cols = ssm1 = ssm2 = 0;
+}
+
+//////////////////////////////////////////////////////////////////////////////
+/**
+ * @brief Free all allocated memory (to delete list of hits)
+ */
+void
+Hit::Delete()
+{
+ if (i){
+ delete[] i; i = NULL;
+ }
+ if (j){
+ delete[] j; j = NULL;
+ }
+ if (states){
+ delete[] states; states = NULL;
+ }
+ if (S){
+ delete[] S; S = NULL;
+ }
+ if (S_ss){
+ delete[] S_ss; S_ss = NULL;
+ }
+ if (P_posterior){
+ delete[] P_posterior; P_posterior = NULL;
+ }
+ if (Xcons){
+ delete[] Xcons; Xcons = NULL;
+ }
+ // delete[] l; l = NULL;
+ i = j = NULL;
+ states = NULL;
+ S = S_ss = P_posterior = NULL;
+ Xcons = NULL;
+ if (irep==1) // if irep>1 then longname etc point to the same memory locations as the first repeat.
+ { // but these have already been deleted.
+ // printf("Delete name = %s\n",name);//////////////////
+ delete[] longname; longname = NULL;
+ delete[] name; name = NULL;
+ delete[] file; file = NULL;
+ delete[] dbfile; dbfile = NULL;
+ for (int k=0; k<n_display; k++)
+ {
+ //delete[] sname[k]; sname[k] = NULL;
+ delete[] seq[k]; seq[k] = NULL;
+ }
+ //delete[] sname; sname = NULL;
+ delete[] seq; seq = NULL;
+ }
+}
+
+
+///////////////////////////////////////////////////////////////////////////
+/**
+ * @brief Allocate/delete memory for dynamic programming matrix
+ */
+void
+Hit::AllocateBacktraceMatrix(int Nq, int Nt)
+{
+ int i;
+ bMM=new(char*[Nq]);
+ bMI=new(char*[Nq]);
+ bIM=new(char*[Nq]);
+ bDG=new(char*[Nq]);
+ bGD=new(char*[Nq]);
+ cell_off=new(char*[Nq]);
+ for (i=0; i<Nq; i++)
+ {
+ bMM[i]=new(char[Nt]);
+ bMI[i]=new(char[Nt]);
+ bIM[i]=new(char[Nt]);
+ bGD[i]=new(char[Nt]);
+ bDG[i]=new(char[Nt]);
+ cell_off[i]=new(char[Nt]);
+ if (!bMM[i] || !bMI[i] || !bIM[i] || !bGD[i] || !bDG[i] || !cell_off[i])
+ {
+ fprintf(stderr,"Error: out of memory while allocating row %i (out of %i) for dynamic programming matrices \n",i+1,Nq);
+ fprintf(stderr,"Suggestions:\n");
+ fprintf(stderr,"1. Cut query sequence into shorter segments\n");
+ fprintf(stderr,"2. Check stack size limit (Linux: ulimit -a)\n");
+ fprintf(stderr,"3. Run on a computer with bigger memory\n");
+ exit(3);
+ }
+ }
+}
+
+/**
+ * @brief
+ */
+void
+Hit::DeleteBacktraceMatrix(int Nq)
+{
+ int i;
+ for (i=0; i<Nq; i++)
+ {
+ delete[] bMM[i]; bMM[i] = NULL;
+ delete[] bMI[i]; bMI[i] = NULL;
+ delete[] bIM[i]; bIM[i] = NULL;
+ delete[] bGD[i]; bGD[i] = NULL;
+ delete[] bDG[i]; bDG[i] = NULL;
+ delete[] cell_off[i]; cell_off[i] = NULL;
+ }
+ delete[] bMM; bMM = NULL;
+ delete[] bMI; bMI = NULL;
+ delete[] bIM; bIM = NULL;
+ delete[] bDG; bDG = NULL;
+ delete[] bGD; bGD = NULL;
+ delete[] cell_off; cell_off = NULL;
+}
+
+
+///////////////////////////////////////////////////////////////////////////////
+/**
+ * @brief Allocate/delete memory for Forward dynamic programming matrix
+ */
+void
+Hit::AllocateForwardMatrix(int Nq, int Nt)
+{
+ F_MM=new(double*[Nq]);
+ F_MI=new(double*[Nq]);
+ F_DG=new(double*[Nq]);
+ F_IM=new(double*[Nq]);
+ F_GD=new(double*[Nq]);
+ scale=new(double[Nq+1]); // need Nq+3?
+ for (int i=0; i<Nq; i++)
+ {
+ F_MM[i] = new(double[Nt]);
+ F_MI[i] = new(double[Nt]);
+ F_DG[i] = new(double[Nt]);
+ F_IM[i] = new(double[Nt]);
+ F_GD[i] = new(double[Nt]);
+ if (!F_MM[i] || !F_MI[i] || !F_IM[i] || !F_GD[i] || !F_DG[i])
+ {
+ fprintf(stderr,"Error: out of memory while allocating row %i (out of %i) for dynamic programming matrices \n",i+1,Nq);
+ fprintf(stderr,"Suggestions:\n");
+ fprintf(stderr,"1. Cut query sequence into shorter segments\n");
+ fprintf(stderr,"2. Check stack size limit (Linux: ulimit -a)\n");
+ fprintf(stderr,"3. Run on a computer with bigger memory\n");
+ exit(3);
+ }
+
+ }
+}
+
+/**
+ * @brief
+ */
+void
+Hit::DeleteForwardMatrix(int Nq)
+{
+ for (int i=0; i<Nq; i++)
+ {
+ delete[] F_MM[i]; F_MM[i] = NULL;
+ delete[] F_MI[i]; F_MI[i] = NULL;
+ delete[] F_IM[i]; F_IM[i] = NULL;
+ delete[] F_GD[i]; F_GD[i] = NULL;
+ delete[] F_DG[i]; F_DG[i] = NULL;
+ }
+ delete[] F_MM; F_MM = NULL;
+ delete[] F_MI; F_MI = NULL;
+ delete[] F_IM; F_IM = NULL;
+ delete[] F_DG; F_DG = NULL;
+ delete[] F_GD; F_GD = NULL;
+ delete[] scale; scale = NULL;
+}
+
+/////////////////////////////////////////////////////////////////////////////////////
+/**
+ * @brief Allocate/delete memory for Backward dynamic programming matrix (DO ONLY AFTER FORWARD MATRIX HAS BEEN ALLOCATED)
+ */
+void
+Hit::AllocateBackwardMatrix(int Nq, int Nt)
+{
+ B_MM=new(double*[Nq]);
+ B_MI=F_MI;
+ B_DG=F_DG;
+ B_IM=F_IM;
+ B_GD=F_GD;
+ for (int i=0; i<Nq; i++)
+ {
+ B_MM[i] = new(double[Nt]);
+ if (!B_MM[i])
+ {
+ fprintf(stderr,"Error: out of memory while allocating row %i (out of %i) for dynamic programming matrices \n",i+1,Nq);
+ fprintf(stderr,"Suggestions:\n");
+ fprintf(stderr,"1. Cut query sequence into shorter segments\n");
+ fprintf(stderr,"2. Check stack size limit (Linux: ulimit -a)\n");
+ fprintf(stderr,"3. Run on a computer with bigger memory\n");
+ exit(3);
+ }
+ }
+}
+
+void Hit::DeleteBackwardMatrix(int Nq)
+{
+ for (int i=0; i<Nq; i++)
+ {
+ delete[] B_MM[i]; B_MM[i] = NULL; /* is this all? FS */
+ }
+ delete[] B_MM; B_MM = NULL;
+ B_MM=B_MI=B_IM=B_DG=B_GD=NULL;
+}
+
+
+
+/////////////////////////////////////////////////////////////////////////////////////
+/**
+ * @brief Compare HMMs with one another and look for sub-optimal alignments that share no pair with previous ones
+ * The function is called with q and t
+ * If q and t are equal (self==1), only the upper right part of the matrix is calculated: j>=i+3
+ */
+void
+Hit::Viterbi(HMM& q, HMM& t, float** Sstruc)
+{
+
+ // Linear topology of query (and template) HMM:
+ // 1. The HMM HMM has L+2 columns. Columns 1 to L contain
+ // a match state, a delete state and an insert state each.
+ // 2. The Start state is M0, the virtual match state in column i=0 (j=0). (Therefore X[k][0]=ANY)
+ // This column has only a match state and it has only a transitions to the next match state.
+ // 3. The End state is M(L+1), the virtual match state in column i=L+1.(j=L+1) (Therefore X[k][L+1]=ANY)
+ // Column L has no transitions to the delete state: tr[L][M2D]=tr[L][D2D]=0.
+ // 4. Transitions I->D and D->I are ignored, since they do not appear in PsiBlast alignments
+ // (as long as the gap opening penalty d is higher than the best match score S(a,b)).
+
+ // Pairwise alignment of two HMMs:
+ // 1. Pair-states for the alignment of two HMMs are
+ // MM (Q:Match T:Match) , GD (Q:Gap T:Delete), IM (Q:Insert T:Match), DG (Q:Delelte, T:Match) , MI (Q:Match T:Insert)
+ // 2. Transitions are allowed only between the MM-state and each of the four other states.
+
+ // Saving space:
+ // The best score ending in pair state XY sXY[i][j] is calculated from left to right (j=1->t.L)
+ // and top to bottom (i=1->q.L). To save space, only the last row of scores calculated is kept in memory.
+ // (The backtracing matrices are kept entirely in memory [O(t.L*q.L)]).
+ // When the calculation has proceeded up to the point where the scores for cell (i,j) are caculated,
+ // sXY[i-1][j'] = sXY[j'] for j'>=j (A below)
+ // sXY[i][j'] = sXY[j'] for j'<j (B below)
+ // sXY[i-1][j-1]= sXY_i_1_j_1 (C below)
+ // sXY[i][j] = sXY_i_j (D below)
+ // j-1
+ // j
+ // i-1: CAAAAAAAAAAAAAAAAAA
+ // i : BBBBBBBBBBBBBD
+
+
+ // Variable declarations
+ //float sMM[MAXRES]; // sMM[i][j] = score of best alignment up to indices (i,j) ending in (Match,Match)
+ //float sGD[MAXRES]; // sGD[i][j] = score of best alignment up to indices (i,j) ending in (Gap,Delete)
+ //float sDG[MAXRES]; // sDG[i][j] = score of best alignment up to indices (i,j) ending in (Delete,Gap)
+ //float sIM[MAXRES]; // sIM[i][j] = score of best alignment up to indices (i,j) ending in (Ins,Match)
+ //float sMI[MAXRES]; // sMI[i][j] = score of best alignment up to indices (i,j) ending in (Match,Ins)
+ float *sMM = new(float[par.maxResLen]); // sMM[i][j] = score of best alignment up to indices (i,j) ending in (Match,Match)
+ float *sGD = new(float[par.maxResLen]); // sGD[i][j] = score of best alignment up to indices (i,j) ending in (Gap,Delete)
+ float *sDG = new(float[par.maxResLen]); // sDG[i][j] = score of best alignment up to indices (i,j) ending in (Delete,Gap)
+ float *sIM = new(float[par.maxResLen]); // sIM[i][j] = score of best alignment up to indices (i,j) ending in (Ins,Match)
+ float *sMI = new(float[par.maxResLen]); // sMI[i][j] = score of best alignment up to indices (i,j) ending in (Match,Ins)
+ float smin=(par.loc? 0:-FLT_MAX); //used to distinguish between SW and NW algorithms in maximization
+ int i,j; //query and template match state indices
+ float sMM_i_j=0,sMI_i_j,sIM_i_j,sGD_i_j,sDG_i_j;
+ float sMM_i_1_j_1,sMI_i_1_j_1,sIM_i_1_j_1,sGD_i_1_j_1,sDG_i_1_j_1;
+ int jmin,jmax;
+
+ // Reset crossed out cells?
+ if(irep==1) InitializeForAlignment(q,t);
+
+ // Initialization of top row, i.e. cells (0,j)
+ for (j=0; j<=t.L; j++)
+ {
+ sMM[j] = (self? 0 : -j*par.egt);
+ sIM[j] = sMI[j] = sDG[j] = sGD[j] = -FLT_MAX;
+ }
+ score=-INT_MAX; i2=j2=0; bMM[0][0]=STOP;
+
+ // Viterbi algorithm
+ for (i=1; i<=q.L; i++) // Loop through query positions i
+ {
+// if (v>=5) printf("\n");
+
+
+ if (self)
+ {
+ // If q is compared to itself, ignore cells below diagonal+SELFEXCL
+ jmin = i+SELFEXCL;
+ jmax = t.L;
+ if (jmin>jmax) continue;
+ }
+ else
+ {
+ // If q is compared to t, exclude regions where overlap of q with t < min_overlap residues
+ jmin=imax( 1, i+min_overlap-q.L); // Lq-i+j>=Ovlap => j>=i+Ovlap-Lq => jmin=max{1, i+Ovlap-Lq}
+ jmax=imin(t.L,i-min_overlap+t.L); // Lt-j+i>=Ovlap => j<=i-Ovlap+Lt => jmax=min{Lt,i-Ovlap+Lt}
+ }
+
+ // Initialize cells
+ if (jmin==1)
+ {
+ sMM_i_1_j_1 = -(i-1)*par.egq; // initialize at (i-1,0)
+ sMM[0] = -i*par.egq; // initialize at (i,0)
+ sIM_i_1_j_1 = sMI_i_1_j_1 = sDG_i_1_j_1 = sGD_i_1_j_1 = -FLT_MAX; // initialize at (i-1,jmin-1)
+ }
+ else
+ {
+ // Initialize at (i-1,jmin-1) if lower left triagonal is excluded due to min overlap
+ sMM_i_1_j_1 = sMM[jmin-1]; // initialize at (i-1,jmin-1)
+ sIM_i_1_j_1 = sIM[jmin-1]; // initialize at (i-1,jmin-1)
+ sMI_i_1_j_1 = sMI[jmin-1]; // initialize at (i-1,jmin-1)
+ sDG_i_1_j_1 = sDG[jmin-1]; // initialize at (i-1,jmin-1)
+ sGD_i_1_j_1 = sGD[jmin-1]; // initialize at (i-1,jmin-1)
+ sMM[jmin-1] = -FLT_MAX; // initialize at (i,jmin-1)
+ }
+ if (jmax<t.L) // initialize at (i-1,jmmax) if upper right triagonal is excluded due to min overlap
+ sMM[jmax] = sIM[jmax] = sMI[jmax] = sDG[jmax] = sGD[jmax] = -FLT_MAX;
+ sIM[jmin-1] = sMI[jmin-1] = sDG[jmin-1] = sGD[jmin-1] = -FLT_MAX; // initialize at (i,jmin-1)
+
+ for (j=jmin; j<=jmax; j++) // Loop through template positions j
+ {
+
+ if (cell_off[i][j])
+ {
+ sMM_i_1_j_1 = sMM[j]; // sMM_i_1_j_1 (for j->j+1) = sMM(i-1,(j+1)-1) = sMM[j]
+ sGD_i_1_j_1 = sGD[j];
+ sIM_i_1_j_1 = sIM[j];
+ sDG_i_1_j_1 = sDG[j];
+ sMI_i_1_j_1 = sMI[j];
+ sMM[j]=sMI[j]=sIM[j]=sDG[j]=sGD[j]=-FLT_MAX; // sMM[j] = sMM(i,j) is cell_off
+ }
+ else
+ {
+ // Recursion relations
+// printf("S[%i][%i]=%4.1f ",i,j,Score(q.p[i],t.p[j])); // DEBUG!!
+
+ CALCULATE_MAX6( sMM_i_j,
+ smin,
+ sMM_i_1_j_1 + q.tr[i-1][M2M] + t.tr[j-1][M2M],
+ sGD_i_1_j_1 + q.tr[i-1][M2M] + t.tr[j-1][D2M],
+ sIM_i_1_j_1 + q.tr[i-1][I2M] + t.tr[j-1][M2M],
+ sDG_i_1_j_1 + q.tr[i-1][D2M] + t.tr[j-1][M2M],
+ sMI_i_1_j_1 + q.tr[i-1][M2M] + t.tr[j-1][I2M],
+ bMM[i][j]
+ );
+ sMM_i_j += Score(q.p[i],t.p[j]) + ScoreSS(q,t,i,j) + par.shift
+ + (Sstruc==NULL? 0: Sstruc[i][j]);
+
+
+ sGD_i_j = max2
+ (
+ sMM[j-1] + t.tr[j-1][M2D], // MM->GD gap opening in query
+ sGD[j-1] + t.tr[j-1][D2D], // GD->GD gap extension in query
+ bGD[i][j]
+ );
+ sIM_i_j = max2
+ (
+// sMM[j-1] + q.tr[i][M2I] + t.tr[j-1][M2M] ,
+ sMM[j-1] + q.tr[i][M2I] + t.tr[j-1][M2M_GAPOPEN], // MM->IM gap opening in query
+ sIM[j-1] + q.tr[i][I2I] + t.tr[j-1][M2M], // IM->IM gap extension in query
+ bIM[i][j]
+ );
+ sDG_i_j = max2
+ (
+// sMM[j] + q.tr[i-1][M2D],
+// sDG[j] + q.tr[i-1][D2D], //gap extension (DD) in query
+ sMM[j] + q.tr[i-1][M2D] + t.tr[j][GAPOPEN], // MM->DG gap opening in template
+ sDG[j] + q.tr[i-1][D2D] + t.tr[j][GAPEXTD], // DG->DG gap extension in template
+ bDG[i][j]
+ );
+ sMI_i_j = max2
+ (
+ sMM[j] + q.tr[i-1][M2M] + t.tr[j][M2I], // MM->MI gap opening M2I in template
+ sMI[j] + q.tr[i-1][M2M] + t.tr[j][I2I], // MI->MI gap extension I2I in template
+ bMI[i][j]
+ );
+
+ sMM_i_1_j_1 = sMM[j];
+ sGD_i_1_j_1 = sGD[j];
+ sIM_i_1_j_1 = sIM[j];
+ sDG_i_1_j_1 = sDG[j];
+ sMI_i_1_j_1 = sMI[j];
+ sMM[j] = sMM_i_j;
+ sGD[j] = sGD_i_j;
+ sIM[j] = sIM_i_j;
+ sDG[j] = sDG_i_j;
+ sMI[j] = sMI_i_j;
+
+ //if (isnan(sMM_i_j)||isinf(sMM_i_j)){
+ // printf("."); /* <DEBUG> FS*/
+ //}
+ // Find maximum score; global alignment: maxize only over last row and last column
+ if(sMM_i_j>score && (par.loc || i==q.L)) { i2=i; j2=j; score=sMM_i_j; }
+
+ } // end if
+ //printf("i= %d\tj= %d\ti2= %d\tj2= %d\tsMM= %f\tscore= %f\n", i, j, i2, j2, sMM_i_j, score);
+ } //end for j
+
+ // if global alignment: look for best cell in last column
+ if (!par.loc && sMM_i_j>score) { i2=i; j2=jmax; score=sMM_i_j; }
+
+ } // end for i
+
+ state=MM; // state with maximum score is MM state
+
+ // If local alignment do length correction: -log(length)
+ if (par.loc)
+ {
+ if (self)
+ score=score-log(0.5*t.L*q.L/200.0/200.0)/LAMDA - 11.2; // offset of -11.2 to get approx same mean as for -global
+ else
+ if (par.idummy==0 && q.lamda>0) //////////////////////////////////////////////
+ score=score-log(t.L*q.L/200.0/200.0)/q.lamda - 11.2; // offset of -11.2 to get approx same mean as for -global
+ else if (par.idummy<=1) //////////////////////////////////////////////
+ score=score-log(t.L*q.L/200.0/200.0)/LAMDA - 11.2; // offset of -11.2 to get approx same mean as for -global
+ }
+// printf("Template=%-12.12s i=%-4i j=%-4i score=%6.3f\n",t.name,i2,j2,score);
+
+ delete[] sMM; sMM = NULL;
+ delete[] sGD; sGD = NULL;
+ delete[] sDG; sDG = NULL;
+ delete[] sIM; sIM = NULL;
+ delete[] sMI; sMI = NULL;
+
+ return;
+
+} /* this is the end of Hit::Viterbi() */
+
+
+
+/////////////////////////////////////////////////////////////////////////////////////
+/**
+ * @brief Compare two HMMs with Forward Algorithm in lin-space (~ 2x faster than in log-space)
+ */
+int
+Hit::Forward(HMM& q, HMM& t, float** Pstruc)
+{
+
+ // Variable declarations
+ int i,j; // query and template match state indices
+ double pmin=(par.loc? 1.0: 0.0); // used to distinguish between SW and NW algorithms in maximization
+ double Cshift = pow(2.0,par.shift); // score offset transformed into factor in lin-space
+ double Pmax_i; // maximum of F_MM in row i
+ double scale_prod=1.0; // Prod_i=1^i (scale[i])
+ int jmin;
+
+ // First alignment of this pair of HMMs?
+ if(irep==1)
+ {
+ q.tr[0][M2D] = q.tr[0][M2I] = 0.0;
+ q.tr[0][I2M] = q.tr[0][I2I] = 0.0;
+ q.tr[0][D2M] = q.tr[0][D2D] = 0.0;
+ t.tr[0][M2M] = 1.0;
+ t.tr[0][M2D] = t.tr[0][M2I] = 0.0;
+ t.tr[0][I2M] = t.tr[0][I2I] = 0.0;
+ t.tr[0][D2M] = t.tr[0][D2D] = 0.0;
+ q.tr[q.L][M2M] = 1.0;
+ q.tr[q.L][M2D] = q.tr[q.L][M2I] = 0.0;
+ q.tr[q.L][I2M] = q.tr[q.L][I2I] = 0.0;
+ q.tr[q.L][D2M] = 1.0;
+ q.tr[q.L][D2D] = 0.0;
+ t.tr[t.L][M2M] = 1.0;
+ t.tr[t.L][M2D] = t.tr[t.L][M2I] = 0.0;
+ t.tr[t.L][I2M] = t.tr[t.L][I2I] = 0.0;
+ t.tr[t.L][D2M] = 1.0;
+ t.tr[t.L][D2D] = 0.0;
+ InitializeForAlignment(q,t);
+ }
+
+
+ // Initialization of top row, i.e. cells (0,j)
+ F_MM[1][0] = F_IM[1][0] = F_GD[1][0] = F_MM[0][1] = F_MI[0][1] = F_DG[0][1] = 0.0;
+ for (j=1; j<=t.L; j++)
+ {
+ if (cell_off[1][j])
+ F_MM[1][j] = F_MI[1][j] = F_DG[1][j] = F_IM[1][j] = F_GD[1][j] = 0.0;
+ else
+ {
+ F_MM[1][j] = ProbFwd(q.p[1],t.p[j]) * fpow2(ScoreSS(q,t,1,j)) * Cshift * (Pstruc==NULL? 1: Pstruc[1][j]) ;
+ F_MI[1][j] = F_DG[1][j] = 0.0;
+ F_IM[1][j] = F_MM[1][j-1] * q.tr[1][M2I] * t.tr[j-1][M2M] + F_IM[1][j-1] * q.tr[1][I2I] * t.tr[j-1][M2M];
+ F_GD[1][j] = F_MM[1][j-1] * t.tr[j-1][M2D] + F_GD[1][j-1] * t.tr[j-1][D2D];
+ }
+ }
+ scale[0]=scale[1]=scale[2]=1.0;
+
+ // Forward algorithm
+ for (i=2; i<=q.L; i++) // Loop through query positions i
+ {
+ // if (v>=5) printf("\n");
+
+ if (self) jmin = imin(i+SELFEXCL+1,t.L); else jmin=1;
+
+ if (scale_prod<DBL_MIN*100) scale_prod = 0.0; else scale_prod *= scale[i];
+
+ // Initialize cells at (i,0)
+ if (cell_off[i][jmin])
+ F_MM[i][jmin] = F_MI[i][jmin] = F_DG[i][jmin] = F_IM[i][jmin] = F_GD[i][jmin] = 0.0;
+ else
+ {
+ F_MM[i][jmin] = scale_prod * ProbFwd(q.p[i],t.p[jmin]) * fpow2(ScoreSS(q,t,i,jmin)) * Cshift * (Pstruc==NULL? 1: Pstruc[i][jmin]);
+ F_IM[i][jmin] = F_GD[i][jmin] = 0.0;
+ F_MI[i][jmin] = scale[i] * (F_MM[i-1][jmin] * q.tr[i-1][M2M] * t.tr[jmin][M2I] + F_MI[i-1][jmin] * q.tr[i-1][M2M] * t.tr[jmin][I2I]);
+ F_DG[i][jmin] = scale[i] * (F_MM[i-1][jmin] * q.tr[i-1][M2D] + F_DG[i-1][jmin] * q.tr[i-1][D2D]);
+ }
+ Pmax_i=0;
+
+ for (j=jmin+1; j<=t.L; j++) // Loop through template positions j
+ {
+ // Recursion relations
+ // printf("S[%i][%i]=%4.1f ",i,j,Score(q.p[i],t.p[j]));
+
+ if (cell_off[i][j])
+ F_MM[i][j] = F_MI[i][j] = F_DG[i][j] = F_IM[i][j] = F_GD[i][j] = 0.0;
+ else
+ {
+ F_MM[i][j] = ProbFwd(q.p[i],t.p[j]) * fpow2(ScoreSS(q,t,i,j)) * Cshift * (Pstruc==NULL? 1: Pstruc[i][j]) * scale[i] *
+ ( pmin
+ + F_MM[i-1][j-1] * q.tr[i-1][M2M] * t.tr[j-1][M2M] // BB -> MM (BB = Begin/Begin, for local alignment)
+ + F_GD[i-1][j-1] * q.tr[i-1][M2M] * t.tr[j-1][D2M] // GD -> MM
+ + F_IM[i-1][j-1] * q.tr[i-1][I2M] * t.tr[j-1][M2M] // IM -> MM
+ + F_DG[i-1][j-1] * q.tr[i-1][D2M] * t.tr[j-1][M2M] // DG -> MM
+ + F_MI[i-1][j-1] * q.tr[i-1][M2M] * t.tr[j-1][I2M] // MI -> MM
+ );
+ F_GD[i][j] =
+ ( F_MM[i][j-1] * t.tr[j-1][M2D] // GD -> MM
+ + F_GD[i][j-1] * t.tr[j-1][D2D] // GD -> GD
+ + (Pstruc==NULL? 0 : F_DG[i][j-1] * t.tr[j-1][M2D] * q.tr[i][D2M] ) // DG -> GD (only when structure scores given)
+ );
+ F_IM[i][j] =
+ ( F_MM[i][j-1] * q.tr[i][M2I] * t.tr[j-1][M2M] // MM -> IM
+ + F_IM[i][j-1] * q.tr[i][I2I] * t.tr[j-1][M2M] // IM -> IM
+ + (Pstruc==NULL? 0 : F_MI[i][j-1] * q.tr[i][M2I] * t.tr[j-1][I2M] ) // MI -> IM (only when structure scores given)
+ );
+ F_DG[i][j] = scale[i] *
+ ( F_MM[i-1][j] * q.tr[i-1][M2D] // DG -> MM
+ + F_DG[i-1][j] * q.tr[i-1][D2D] // DG -> DG
+ ) ;
+ F_MI[i][j] = scale[i] *
+ ( F_MM[i-1][j] * q.tr[i-1][M2M] * t.tr[j][M2I] // MI -> MM
+ + F_MI[i-1][j] * q.tr[i-1][M2M] * t.tr[j][I2I] // MI -> MI
+ );
+
+ if(F_MM[i][j]>Pmax_i) Pmax_i=F_MM[i][j];
+
+ } // end else
+
+ } //end for j
+
+ pmin *= scale[i];
+ scale[i+1] = 1.0/(Pmax_i+1.0);
+ // scale[i+1] = 1.0;
+
+ } // end for i
+
+ // Calculate P_forward * Product_{i=1}^{Lq+1}(scale[i])
+ if (par.loc)
+ {
+ Pforward = 1.0; // alignment contains no residues (see Mueckstein, Stadler et al.)
+ for (i=1; i<=q.L; i++) // Loop through query positions i
+ {
+ for (j=1; j<=t.L; j++) // Loop through template positions j
+ Pforward += F_MM[i][j];
+ Pforward *= scale[i+1];
+ }
+ }
+ else // global alignment
+ {
+ Pforward = 0.0;
+ for (i=1; i<q.L; i++) {
+ Pforward = (Pforward + F_MM[i][t.L]) * scale[i+1];
+ }
+ for (j=1; j<=t.L; j++) {
+ Pforward += F_MM[q.L][j];
+ }
+ Pforward *= scale[q.L+1];
+ }
+
+ // Calculate log2(P_forward)
+ score = log2(Pforward)-10.0f;
+ for (i=1; i<=q.L+1; i++) score -= log2(scale[i]);
+ // state = MM;
+
+ if (par.loc)
+ {
+ if (self)
+ score=score-log(0.5*t.L*q.L)/LAMDA+14.; // +14.0 to get approx same mean as for -global
+ else
+ score=score-log(t.L*q.L)/LAMDA+14.; // +14.0 to get approx same mean as for -global
+ }
+
+ // Debugging output
+ if (v>=6)
+ {
+ const int i0=0, i1=q.L;
+ const int j0=0, j1=t.L;
+ scale_prod=1;
+ printf("\nFwd scale ");
+ for (j=j0; j<=j1; j++) printf("%3i ",j);
+ printf("\n");
+ for (i=i0; i<=i1; i++)
+ {
+ scale_prod *= scale[i];
+ printf("%3i: %9.3G ",i,1/scale_prod);
+ for (j=j0; j<=j1; j++)
+ printf("%7.4f ",(F_MM[i][j]+F_MI[i][j]+F_IM[i][j]+F_DG[i][j]+F_GD[i][j]));
+ printf("\n");
+ // printf(" MM %9.5f ",1/scale[i]);
+ // for (j=j0; j<=j1; j++)
+ // printf("%7.4f ",F_MM[i][j]);
+ // printf("\n");
+ }
+ }
+ // printf("Template=%-12.12s score=%6.3f i2=%i j2=%i \n",t.name,score,i2,j2);
+
+ /* check for NaN and or infinities, FS, r241 -> r243 */
+ if (isnan(score) || isinf(score) || isnan(Pforward) || isinf(Pforward) ){
+ fprintf(stderr, "%s:%s:%d: Forward score is %g, Pforward is %g\n",
+ __FUNCTION__, __FILE__, __LINE__, score, Pforward);
+ return FAILURE;
+ }
+ i = q.L-1; j = t.L-1; /* FS, r241 -> r243 */
+ if (isinf(F_MM[i][j]+F_MI[i][j]+F_IM[i][j]+F_DG[i][j]+F_GD[i][j])){
+ fprintf(stderr, "%s:%s:%d: F_MM[i][j]=%g, F_IM[i][j]=%g, F_MI[i][j]=%g, F_DG[i][j]=%g, F_GD[i][j]=%g (i=%d,j=%d)\n",
+ __FUNCTION__, __FILE__, __LINE__, F_MM[i][j], F_MI[i][j], F_IM[i][j], F_DG[i][j], F_GD[i][j], i, j);
+ return FAILURE;
+ }
+ return OK;
+
+} /* this is the end of Hit::Forward() */
+
+
+
+
+
+/////////////////////////////////////////////////////////////////////////////////////
+/**
+ * @brief Compare two HMMs with Backward Algorithm (in lin-space, 2x faster), for use in MAC alignment
+ */
+int
+Hit::Backward(HMM& q, HMM& t)
+{
+
+ // Variable declarations
+ int i,j; // query and template match state indices
+ double pmin=(par.loc? 1.0: 0.0); // used to distinguish between SW and NW algorithms in maximization
+ double Cshift = pow(2.0,par.shift); // score offset transformed into factor in lin-space
+ double scale_prod=scale[q.L+1];
+ int jmin;
+ //double dMaxB = -1.0;
+
+ // Initialization of top row, i.e. cells (0,j)
+ for (j=t.L; j>=1; j--)
+ {
+ if (cell_off[q.L][j])
+ B_MM[q.L][j] = 0.0;
+ else
+ B_MM[q.L][j] = scale[q.L+1];
+ //dMaxB = dMaxB>B_MM[q.L][j]?dMaxB:B_MM[q.L][j];
+ B_IM[q.L][j] = B_MI[q.L][j] = B_DG[q.L][j] = B_GD[q.L][j] = 0.0;
+ }
+ if (par.loc) pmin = scale[q.L+1]; // transform pmin (for local alignment) to scale of present (i'th) row
+
+ // Backward algorithm
+ for (i=q.L-1; i>=1; i--) // Loop through query positions i
+ {
+ // if (v>=5) printf("\n");
+
+ if (self) jmin = imin(i+SELFEXCL,t.L); else jmin=1; // jmin = i+SELFEXCL and not (i+SELFEXCL+1) to set matrix element at boundary to zero
+
+ // Initialize cells at (i,t.L+1)
+ scale_prod *= scale[i+1];
+ if (cell_off[i][t.L])
+ B_MM[i][t.L] = 0.0;
+ else
+ B_MM[i][t.L] = scale_prod;
+ //if (isnan(B_MM[i][t.L])||isinf(B_MM[i][t.L])){
+ // printf("."); /* <DEBUG> FS*/
+ //}
+ //dMaxB = dMaxB>B_MM[i][t.L]?dMaxB:B_MM[i][t.L];
+ B_IM[i][t.L] = B_MI[i][t.L] = B_DG[i][t.L] = B_GD[i][t.L] = 0.0;
+ pmin *= scale[i+1]; // transform pmin (for local alignment) to scale of present (i'th) row
+
+ for (j=t.L-1; j>=jmin; j--) // Loop through template positions j
+ {
+ // Recursion relations
+ // printf("S[%i][%i]=%4.1f ",i,j,Score(q.p[i],t.p[j]));
+ if (cell_off[i][j])
+ B_MM[i][j] = B_GD[i][j] = B_IM[i][j] = B_DG[i][j] = B_MI[i][j] = 0.0;
+ else
+ {
+ double pmatch = B_MM[i+1][j+1] * ProbFwd(q.p[i+1],t.p[j+1]) * fpow2(ScoreSS(q,t,i+1,j+1)) * Cshift * scale[i+1];
+ //if (isnan(pmatch)||isinf(pmatch)){
+ // printf("."); /* <DEBUG> FS*/
+ //}
+ B_MM[i][j] =
+ (
+ + pmin // MM -> EE (End/End, for local alignment)
+ + pmatch * q.tr[i][M2M] * t.tr[j][M2M] // MM -> MM
+ + B_GD[i][j+1] * t.tr[j][M2D] // MM -> GD (q.tr[i][M2M] is already contained in GD->MM)
+ + B_IM[i][j+1] * q.tr[i][M2I] * t.tr[j][M2M] // MM -> IM
+ + B_DG[i+1][j] * q.tr[i][M2D] * scale[i+1] // MM -> DG (t.tr[j][M2M] is already contained in DG->MM)
+ + B_MI[i+1][j] * q.tr[i][M2M] * t.tr[j][M2I] * scale[i+1] // MM -> MI
+ );
+ //if (isnan(B_MM[i][j])||isinf(B_MM[i][j])){
+ // printf("."); /* <DEBUG> FS*/
+ //}
+ //dMaxB = dMaxB>B_MM[i][j]?dMaxB:B_MM[i][j];
+
+ B_GD[i][j] =
+ (
+ + pmatch * q.tr[i][M2M] * t.tr[j][D2M] // GD -> MM
+ + B_GD[i][j+1] * t.tr[j][D2D] // DG -> DG
+ );
+ B_IM[i][j] =
+ (
+ + pmatch * q.tr[i][I2M] * t.tr[j][M2M] // IM -> MM
+ + B_IM[i][j+1] * q.tr[i][I2I] * t.tr[j][M2M] // IM -> IM
+ );
+ B_DG[i][j] =
+ (
+ + pmatch * q.tr[i][D2M] * t.tr[j][M2M] // DG -> MM
+ + B_DG[i+1][j] * q.tr[i][D2D] * scale[i+1] // DG -> DG
+ // + B_GD[i][j+1] * q.tr[i][D2M] * t.tr[j][M2D] // DG -> GD
+ );
+ B_MI[i][j] =
+ (
+ + pmatch * q.tr[i][M2M] * t.tr[j][I2M] // MI -> MM
+ + B_MI[i+1][j] * q.tr[i][M2M] * t.tr[j][I2I] * scale[i+1] // MI -> MI
+ // + B_IM[i][j+1] * q.tr[i][M2I] * t.tr[j][I2M] // MI -> IM
+ );
+
+ } // end else
+
+ } //end for j
+
+ } // end for i
+
+ // Debugging output
+ if (v>=6)
+ {
+ const int i0=0, i1=q.L;
+ const int j0=0, j1=t.L;
+ double scale_prod[q.L+2];
+ scale_prod[q.L] = scale[q.L+1];
+ for (i=q.L-1; i>=1; i--) scale_prod[i] = scale_prod[i+1] * scale[i+1];
+
+ printf("\nBwd scale ");
+ for (j=j0; j<=j1; j++) printf("%3i ",j);
+ printf("\n");
+ for (i=i0; i<=i1; i++)
+ {
+ printf("%3i: %9.3G ",i,1/scale_prod[i]);
+ for (j=j0; j<=j1; j++)
+ printf("%7.4f ",(B_MM[i][j]+B_MI[i][j]+B_IM[i][j]+B_DG[i][j]+B_GD[i][j]) * (ProbFwd(q.p[i],t.p[j])*fpow2(ScoreSS(q,t,i,j)) * Cshift));
+ printf("\n");
+
+ // printf("MM %9.5f ",1/scale[i]);
+ // for (j=j0; j<=j1; j++)
+ // printf("%7.4f ",B_MM[i][j] * (ProbFwd(q.p[i],t.p[j])*fpow2(ScoreSS(q,t,i,j)) * Cshift));
+ // printf("\n");
+ }
+ printf("\nPost scale ");
+ for (j=j0; j<=j1; j++) printf("%3i ",j);
+ printf("\n");
+ for (i=i0; i<=i1; i++)
+ {
+ printf("%3i: %9.3G ",i,1/scale_prod[i]);
+ for (j=j0; j<=j1; j++)
+ printf("%7.4f ",B_MM[i][j]*F_MM[i][j]/Pforward);
+ printf("\n");
+ }
+ printf("\n");
+ }
+
+ if (v>=4) printf("\nForward total probability ratio: %8.3G\n",Pforward);
+
+ // Calculate Posterior matrix and overwrite Backward matrix with it
+ for (i=1; i<=q.L; i++) {
+ for (j=1; j<=t.L; j++) {
+ B_MM[i][j] *= F_MM[i][j]/Pforward;
+ //if (isnan(B_MM[i][j]) || isinf(B_MM[i][j])){
+ // printf("."); /* <DEBUG> FS*/
+ //}
+ //dMaxB = dMaxB>B_MM[i][j]?dMaxB:B_MM[i][j];
+ }
+ }
+
+ //printf("Max-B_MM = %f\n", dMaxB);
+
+ /* check for NaN and or infinities, FS, r241 -> r243 */
+ if (isnan(score) || isinf(score)){
+ fprintf(stderr, "%s:%s:%d: Backward score is %g\n",
+ __FUNCTION__, __FILE__, __LINE__, score);
+ return FAILURE;
+ }
+ i = j = 1;
+ if (isinf(B_MM[i][j]+B_MI[i][j]+B_IM[i][j]+B_DG[i][j]+B_GD[i][j])){
+ fprintf(stderr, "%s:%s:%d: B_MM[1][1]=%g, B_IM[1][1]=%g, B_MI[1][1]=%g, B_DG[1][1]=%g, B_GD[1][1]=%g\n",
+ __FUNCTION__, __FILE__, __LINE__, B_MM[i][j], B_MI[i][j], B_IM[i][j], B_DG[i][j], B_GD[i][j]);
+ for (i = 1; (i < q.L) && isinf(B_MM[i][1]); i++);
+ i--;
+ for (j = 1; (j < t.L) && isinf(B_MM[i][j]); j++);
+ j--;
+ fprintf(stderr, "%s:%s:%d: B_MM[%d][%d]=%g, B_MM[%d][%d]=%g, B_MM[%d][%d]=%g\n",
+ __FUNCTION__, __FILE__, __LINE__,
+ i, j, B_MM[i][j], i+1, 1, B_MM[i+1][1], i, j+1, B_MM[i][j+1]);
+ return FAILURE;
+ }
+ return OK;
+
+} /* this is the end of Hit::Backward() */
+
+
+
+/////////////////////////////////////////////////////////////////////////////////////
+/**
+ * @brief Maximum Accuracy alignment
+ */
+void
+Hit::MACAlignment(HMM& q, HMM& t)
+{
+ // Use Forward and Backward matrices to find that alignment which
+ // maximizes the expected number of correctly aligned pairs of residues (mact=0)
+ // or, more generally, which maximizes the expectation value of the number of
+ // correctly aligned pairs minus (mact x number of aligned pairs)
+ // "Correctly aligned" can be based on posterior probabilities calculated with
+ // a local or a global version of the Forward-Backward algorithm.
+
+ int i,j; // query and template match state indices
+ int jmin,jmax; // range of dynamic programming for j
+ double** S=F_MI; // define alias for new score matrix
+ double score_MAC; // score of the best MAC alignment
+
+ // Initialization of top row, i.e. cells (0,j)
+ for (j=0; j<=t.L; j++) S[0][j] = 0.0;
+ score_MAC=-INT_MAX; i2=j2=0; bMM[0][0]=STOP;
+
+ // Dynamic programming
+ for (i=1; i<=q.L; i++) // Loop through query positions i
+ {
+
+ if (self)
+ {
+ // If q is compared to itself, ignore cells below diagonal+SELFEXCL
+ jmin = i+SELFEXCL;
+ jmax = t.L;
+ if (jmin>jmax) continue;
+ }
+ else
+ {
+ // If q is compared to t, exclude regions where overlap of q with t < min_overlap residues
+ jmin=imax( 1, i+min_overlap-q.L); // Lq-i+j>=Ovlap => j>=i+Ovlap-Lq => jmin=max{1, i+Ovlap-Lq}
+ jmax=imin(t.L,i-min_overlap+t.L); // Lt-j+i>=Ovlap => j<=i-Ovlap+Lt => jmax=min{Lt,i-Ovlap+Lt}
+ }
+
+ // Initialize cells
+ S[i][jmin-1] = 0.0;
+ if (jmax<t.L) S[i-1][jmax] = 0.0; // initialize at (i-1,jmax) if upper right triagonal is excluded due to min overlap
+
+ for (j=jmin; j<=jmax; j++) // Loop through template positions j
+ {
+
+ if (cell_off[i][j])
+ S[i][j] = -FLT_MIN;
+ else
+ {
+ // Recursion
+
+ // NOT the state before the first MM state)
+ CALCULATE_MAX4(
+ S[i][j],
+ B_MM[i][j] - par.mact, // STOP signifies the first MM state, NOT the state before the first MM state (as in Viterbi)
+ S[i-1][j-1] + B_MM[i][j] - par.mact, // B_MM[i][j] contains posterior probability
+ S[i-1][j] - 0.5*par.mact, // gap penalty prevents alignments such as this: XX--xxXX
+ S[i][j-1] - 0.5*par.mact, // YYyy--YY
+ bMM[i][j] // backtracing matrix
+ );
+
+// if (i==6 && j==8)
+// printf("i=%i j=%i S[i][j]=%8.3f MM:%7.3f MI:%7.3f IM:%7.3f b:%i\n",i,j,S[i][j],S[i-1][j-1]+B_MM[i][j]-par.mact,S[i-1][j],S[i][j-1],bMM[i][j]);
+
+ // Find maximum score; global alignment: maximize only over last row and last column
+ if(S[i][j]>score_MAC && (par.loc || i==q.L)) { i2=i; j2=j; score_MAC=S[i][j]; }
+
+ } // end if
+
+ } //end for j
+
+ // if global alignment: look for best cell in last column
+ if (!par.loc && S[i][jmax]>score_MAC) { i2=i; j2=jmax; score_MAC=S[i][jmax]; }
+
+ } // end for i
+
+ // DEBUG
+ if (v>=5)
+ {
+ printf("\nScore ");
+ for (j=0; j<=t.L; j++) printf("%3i ",j);
+ printf("\n");
+ for (i=0; i<=q.L; i++)
+ {
+ printf("%2i: ",i);
+ for (j=0; j<=t.L; j++)
+ printf("%5.2f ",S[i][j]);
+ printf("\n");
+ }
+ printf("\n");
+ printf("Template=%-12.12s i=%-4i j=%-4i score=%6.3f\n",t.name,i2,j2,score);
+ }
+
+ return;
+
+} /* this is the end of Hit::MACAlignment() */
+
+
+/////////////////////////////////////////////////////////////////////////////////////
+/**
+ * @brief Trace back alignment of two profiles based on matrices bXX[][]
+ */
+void
+Hit::Backtrace(HMM& q, HMM& t)
+{
+ // Trace back trough the matrices bXY[i][j] until first match state is found (STOP-state)
+
+ int step; // counts steps in path through 5-layered dynamic programming matrix
+ int i,j; // query and template match state indices
+
+ InitializeBacktrace(q,t);
+
+ // Make sure that backtracing stops when t:M1 or q:M1 is reached (Start state), e.g. sMM[i][1], or sIM[i][1] (M:MM, B:IM)
+ for (i=0; i<=q.L; i++) bMM[i][1]=bGD[i][1]=bIM[i][1] = STOP;
+ for (j=1; j<=t.L; j++) bMM[1][j]=bDG[1][j]=bMI[1][j] = STOP;
+
+
+ // Back-tracing loop
+ matched_cols=0; // for each MACTH (or STOP) state matched_col is incremented by 1
+ step=0; // steps through the matrix correspond to alignment columns (from 1 to nsteps)
+ // state=MM; // state with maximum score must be MM state // already set at the end of Viterbi()
+ i=i2; j=j2; // last aligned pair is (i2,j2)
+ while (state) // while (state!=STOP) because STOP=0
+ {
+ step++;
+ states[step] = state;
+ this->i[step] = i;
+ this->j[step] = j;
+ // Exclude cells in direct neighbourhood from all further alignments
+ for (int ii=imax(i-2,1); ii<=imin(i+2,q.L); ii++)
+ cell_off[ii][j]=1;
+ for (int jj=imax(j-2,1); jj<=imin(j+2,t.L); jj++)
+ cell_off[i][jj]=1;
+
+ switch (state)
+ {
+ case MM: // current state is MM, previous state is bMM[i][j]
+ matched_cols++;
+ state = bMM[i--][j--];
+ break;
+ case GD: // current state is GD
+ switch (bGD[i][j--])
+ {
+ case STOP: state = STOP; break; // current state does not have predecessor
+ case MM: state = MM; break; // previous state is Match state
+ } // default: previous state is same state (GD)
+ break;
+ case IM:
+ switch (bIM[i][j--])
+ {
+ case STOP: state = STOP; break; // current state does not have predecessor
+ case MM: state = MM; break; // previous state is Match state
+ } // default: previous state is same state (IM)
+ break;
+ case DG:
+ switch (bDG[i--][j])
+ {
+ case STOP: state = STOP; break; // current state does not have predecessor
+ case MM: state = MM; break; // previous state is Match state
+ } // default: previous state is same state (DG)
+ break;
+ case MI:
+ switch (bMI[i--][j])
+ {
+ case STOP: state = STOP; break; // current state does not have predecessor
+ case MM: state = MM; break; // previous state is Match state
+ } // default: previous state is same state (MI)
+ break;
+ default:
+ fprintf(stderr,"Error: unallowed state value %i occurred during backtracing at step %i, (i,j)=(%i,%i)\n",state,step,i,j);
+ state=0;
+ v=4;
+ break;
+ } //end switch (state)
+ } //end while (state)
+
+ i1 = this->i[step];
+ j1 = this->j[step];
+ states[step] = MM; // first state (STOP state) is set to MM state
+ nsteps=step;
+
+ // Allocate new space for alignment scores
+ if (t.Xcons) Xcons = new( char[q.L+2]); // for template consensus sequence aligned to query
+ S = new( float[nsteps+1]);
+ S_ss = new( float[nsteps+1]);
+ if (!S_ss) MemoryError("space for HMM-HMM alignments");
+
+ // Add contribution from secondary structure score, record score along alignment,
+ // and record template consensus sequence in master-slave-alignment to query sequence
+ score_ss=0.0f;
+ int ssm=ssm1+ssm2;
+ for (step=1; step<=nsteps; step++)
+ {
+ switch(states[step])
+ {
+ case MM:
+ i = this->i[step];
+ j = this->j[step];
+ S[step] = Score(q.p[i],t.p[j]);
+ S_ss[step] = ScoreSS(q,t,i,j,ssm);
+ score_ss += S_ss[step];
+ if (Xcons) Xcons[i]=t.Xcons[j]; //record database consensus sequence
+ break;
+ case MI: //if gap in template
+ case DG:
+ if (Xcons) Xcons[this->i[step]]=GAP; //(no break hereafter)
+ default: //if gap in T or Q
+ S[step]=S_ss[step]=0.0f;
+ break;
+ }
+ }
+ if (ssm2>=1) score-=score_ss; // subtract SS score added during alignment!!!!
+ if (Xcons)
+ {
+ for (i=0; i<i1; i++) Xcons[i]=ENDGAP; // set end gap code at beginning and end of template consensus sequence
+ for (i=i2+1; i<=q.L+1; i++) Xcons[i]=ENDGAP;
+ }
+
+ // Add contribution from correlation of neighboring columns to score
+ float Scorr=0;
+ if (nsteps)
+ {
+ for (step=2; step<=nsteps; step++) Scorr+=S[step]*S[step-1];
+ for (step=3; step<=nsteps; step++) Scorr+=S[step]*S[step-2];
+ for (step=4; step<=nsteps; step++) Scorr+=S[step]*S[step-3];
+ for (step=5; step<=nsteps; step++) Scorr+=S[step]*S[step-4];
+ score+=par.corr*Scorr;
+ }
+
+ // Set score, P-value etc.
+ score_sort = score_aass = -score;
+ logPval=0; Pval=1;
+ if (t.mu)
+ {
+ logPvalt=logPvalue(score,t.lamda,t.mu);
+ Pvalt=Pvalue(score,t.lamda,t.mu);
+ }
+ else { logPvalt=0; Pvalt=1;}
+ // printf("%-10.10s lamda=%-9f score=%-9f logPval=%-9g\n",name,t.lamda,score,logPvalt);
+
+
+ //DEBUG: Print out Viterbi path
+ if (v>=4)
+ {
+ printf("NAME=%7.7s score=%7.3f score_ss=%7.3f\n",name,score,score_ss);
+ printf("step Q T i j state score T Q cf ss-score\n");
+ for (step=nsteps; step>=1; step--)
+ {
+ switch(states[step])
+ {
+ case MM:
+ printf("%4i %1c %1c ",step,q.seq[q.nfirst][this->i[step]],seq[nfirst][this->j[step]]);
+ break;
+ case GD:
+ case IM:
+ printf("%4i - %1c ",step,seq[nfirst][this->j[step]]);
+ break;
+ case DG:
+ case MI:
+ printf("%4i %1c - ",step,q.seq[q.nfirst][this->i[step]]);
+ break;
+ }
+ printf("%4i %4i %2i %7.2f ",this->i[step],this->j[step],(int)states[step],S[step]);
+ printf("%c %c %1i %7.2f\n",i2ss(t.ss_dssp[this->j[step]]),i2ss(q.ss_pred[this->i[step]]),q.ss_conf[this->i[step]]-1,S_ss[step]);
+ }
+ }
+
+ return;
+
+} /* this is the end of Hit::Backtrace() */
+
+
+
+/////////////////////////////////////////////////////////////////////////////////////
+/**
+ * @brief GLOBAL stochastic trace back through the forward matrix of probability ratios
+ */
+void
+Hit::StochasticBacktrace(HMM& q, HMM& t, char maximize)
+{
+ int step; // counts steps in path through 5-layered dynamic programming matrix
+ int i,j; // query and template match state indices
+// float pmin=(par.loc? 1.0: 0.0); // used to distinguish between SW and NW algorithms in maximization
+ const float pmin=0;
+ double* scale_cum = new(double[q.L+2]);
+
+
+ scale_cum[0]=1;
+ for (i=1; i<=q.L+1; i++) scale_cum[i] = scale_cum[i-1]*scale[i];
+
+ // Select start cell for GLOBAL alignment
+ // (Implementing this in a local version would make this method work for local backtracing as well)
+ if (maximize)
+ {
+ double F_max=0;
+ for (i=q.L-1; i>=1; i--)
+ if (F_MM[i][t.L]/scale_cum[i]>F_max) {i2=i; j2=t.L; F_max=F_MM[i][t.L]/scale_cum[i];}
+ for (j=t.L; j>=1; j--)
+ if (F_MM[q.L][j]/scale_cum[q.L]>F_max) {i2=q.L; j2=j; F_max=F_MM[q.L][j]/scale_cum[q.L];}
+ }
+ else
+ {
+// float sumF[q.L+t.L];
+ double* sumF=new(double[q.L+t.L]);
+ sumF[0]=0.0;
+ for (j=1; j<=t.L; j++) sumF[j] = sumF[j-1] + F_MM[q.L][j]/scale_cum[q.L];;
+ for (j=t.L+1; j<t.L+q.L; j++) sumF[j] = sumF[j-1] + F_MM[j-t.L][t.L]/scale_cum[j-t.L];;
+ float x = sumF[t.L+q.L-1]*frand(); // generate random number between 0 and sumF[t.L+q.L-1]
+ for (j=1; j<t.L+q.L; j++)
+ if (x<sumF[j]) break;
+ if (j<=t.L) {i2=q.L; j2=j;} else {i2=j-t.L; j2=t.L;}
+ delete[] sumF; sumF = NULL;
+ }
+
+ InitializeBacktrace(q,t);
+
+ int (*pick2)(const double&, const double&, const int&);
+ int (*pick3_GD)(const double&, const double&, const double&);
+ int (*pick3_IM)(const double&, const double&, const double&);
+ int (*pick6)(const double&, const double&, const double&, const double&, const double&, const double&);
+ if (maximize)
+ {
+ pick2 = &pickmax2;
+ pick3_GD = &pickmax3_GD;
+ pick3_IM = &pickmax3_IM;
+ pick6 = &pickmax6;
+ }
+ else
+ {
+ pick2 = &pickprob2;
+ pick3_GD = &pickprob3_GD;
+ pick3_IM = &pickprob3_IM;
+ pick6 = &pickprob6;
+ }
+
+ // Back-tracing loop
+ matched_cols=0; // for each MACTH (or STOP) state matched_col is incremented by 1
+ step=0; // steps through the matrix correspond to alignment columns (from 1 to nsteps)
+ state = MM;
+ i=i2; j=j2; // start at end of query and template
+ while (state) // while not reached STOP state or upper or left border
+ {
+ step++;
+ states[step] = state;
+ this->i[step] = i;
+ this->j[step] = j;
+
+ switch (state)
+ {
+
+ case MM: // current state is MM, previous state is state
+// fprintf(stderr,"%4i %1c %1c %4i %4i MM %7.2f\n",step,q.seq[q.nfirst][i],seq[nfirst][j],i,j,Score(q.p[i],t.p[j]));
+// printf("0:%7.3f MM:%7.3f GD:%7.3f IM:%7.3f DG:%7.3f MI:%7.3f \n",
+// pmin*scale_cum[i-1],
+// F_MM[i-1][j-1] * q.tr[i-1][M2M] * t.tr[j-1][M2M],
+// F_GD[i-1][j-1] * q.tr[i-1][M2M] * t.tr[j-1][D2M],
+// F_IM[i-1][j-1] * q.tr[i-1][I2M] * t.tr[j-1][M2M],
+// F_DG[i-1][j-1] * q.tr[i-1][D2M] * t.tr[j-1][M2M],
+// F_MI[i-1][j-1] * q.tr[i-1][M2M] * t.tr[j-1][I2M]);
+ matched_cols++;
+ if (j>1 && i>1)
+ state = (*pick6)(
+ pmin*scale_cum[i-1],
+ F_MM[i-1][j-1] * q.tr[i-1][M2M] * t.tr[j-1][M2M],
+ F_GD[i-1][j-1] * q.tr[i-1][M2M] * t.tr[j-1][D2M],
+ F_IM[i-1][j-1] * q.tr[i-1][I2M] * t.tr[j-1][M2M],
+ F_DG[i-1][j-1] * q.tr[i-1][D2M] * t.tr[j-1][M2M],
+ F_MI[i-1][j-1] * q.tr[i-1][M2M] * t.tr[j-1][I2M]
+ );
+ else state=0;
+ i--; j--;
+ break;
+ case GD: // current state is GD
+// fprintf(stderr,"%4i - %1c %4i %4i GD %7.2f\n",step,q.seq[q.nfirst][j],i,j,Score(q.p[i],t.p[j]));
+ if (j>1)
+ state = (*pick3_GD)(
+ F_MM[i][j-1] * t.tr[j-1][M2D],
+ F_DG[i][j-1] * t.tr[j-1][M2D] * q.tr[i][D2M], // DG -> GD
+ F_GD[i][j-1] * t.tr[j-1][D2D] // gap extension (DD) in template
+ );
+ else state=0;
+ j--;
+ break;
+ case IM:
+// fprintf(stderr,"%4i - %1c %4i %4i IM %7.2f\n",step,q.seq[q.nfirst][j],i,j,Score(q.p[i],t.p[j]));
+ if (j>1)
+ state = (*pick3_IM)(
+ F_MM[i][j-1] * q.tr[i][M2I] * t.tr[j-1][M2M_GAPOPEN],
+ F_MI[i][j-1] * q.tr[i][M2I] * t.tr[j-1][I2M], // MI -> IM
+ F_IM[i][j-1] * q.tr[i][I2I] * t.tr[j-1][M2M] // gap extension (II) in query
+ );
+ else state=0;
+ j--;
+ break;
+ case DG:
+// fprintf(stderr,"%4i %1c - %4i %4i DG %7.2f\n",step,q.seq[q.nfirst][i],i,j,Score(q.p[i],t.p[j]));
+ if (i>1)
+ state = (*pick2)(
+ F_MM[i-1][j] * q.tr[i-1][M2D] * t.tr[j][GAPOPEN],
+ F_DG[i-1][j] * q.tr[i-1][D2D] * t.tr[j][GAPEXTD], //gap extension (DD) in query
+ DG
+ );
+ else state=0;
+ i--;
+ break;
+ case MI:
+// fprintf(stderr,"%4i %1c - %4i %4i MI %7.2f\n",step,q.seq[q.nfirst][i],i,j,Score(q.p[i],t.p[j]));
+ if (i>1)
+ state = (*pick2)(
+ F_MM[i-1][j] * q.tr[i-1][M2M] * t.tr[j][M2I],
+ F_MI[i-1][j] * q.tr[i-1][M2M] * t.tr[j][I2I], //gap extension (II) in template
+ MI
+ );
+ else state=0;
+ i--;
+ break;
+
+ } //end switch (state)
+
+ } //end while (state)
+
+ i1 = this->i[step];
+ j1 = this->j[step];
+ states[step] = MM; // first state (STOP state) is set to MM state
+ nsteps=step;
+
+ // Allocate new space for alignment scores
+ if (t.Xcons) Xcons = new( char[q.L+2]); // for template consensus sequence aligned to query
+ S = new( float[nsteps+1]);
+ S_ss = new( float[nsteps+1]);
+ if (!S_ss) MemoryError("space for HMM-HMM alignments");
+
+ // Add contribution from secondary structure score, record score along alignment,
+ // and record template consensus sequence in master-slave-alignment to query sequence
+ score_ss=0.0f;
+ int ssm=ssm1+ssm2;
+ for (step=1; step<=nsteps; step++)
+ {
+ switch(states[step])
+ {
+ case MM:
+ i = this->i[step];
+ j = this->j[step];
+ S[step] = Score(q.p[i],t.p[j]);
+ S_ss[step] = ScoreSS(q,t,i,j,ssm);
+ score_ss += S_ss[step];
+ if (Xcons) Xcons[i]=t.Xcons[j]; //record database consensus sequence
+ break;
+ case MI: //if gap in template
+ case DG:
+ if (Xcons) Xcons[this->i[step]]=GAP; //(no break hereafter)
+ default: //if gap in T or Q
+ S[step]=S_ss[step]=0.0f;
+ break;
+ }
+ }
+ if (ssm2>=1) score-=score_ss; // subtract SS score added during alignment!!!!
+ if (Xcons)
+ {
+ for (i=0; i<i1; i++) Xcons[i]=ENDGAP; // set end gap code at beginning and end of template consensus sequence
+ for (i=i2+1; i<=q.L+1; i++) Xcons[i]=ENDGAP;
+ }
+
+ delete[] scale_cum; scale_cum = NULL;
+
+ return;
+}
+
+
+
+
+
+/////////////////////////////////////////////////////////////////////////////////////
+/**
+ * @brief Trace back alignment of two profiles based on matrices bXX[][]
+ */
+void
+Hit::BacktraceMAC(HMM& q, HMM& t)
+{
+ // Trace back trough the matrix b[i][j] until STOP state is found
+
+ char** b=bMM; // define alias for backtracing matrix
+ int step; // counts steps in path through 5-layered dynamic programming matrix
+ int i,j; // query and template match state indices
+
+ InitializeBacktrace(q,t);
+
+ // Make sure that backtracing stops when t:M1 or q:M1 is reached (Start state), e.g. sMM[i][1], or sIM[i][1] (M:MM, B:IM)
+ for (i=0; i<=q.L; i++) b[i][1] = STOP;
+ for (j=1; j<=t.L; j++) b[1][j] = STOP;
+
+
+ // Back-tracing loop
+ // In contrast to the Viterbi-Backtracing, STOP signifies the first Match-Match state, NOT the state before the first MM state
+ matched_cols=1; // for each MACTH (or STOP) state matched_col is incremented by 1
+ state=MM; // lowest state with maximum score must be match-match state
+ step=0; // steps through the matrix correspond to alignment columns (from 1 to nsteps)
+ i=i2; j=j2; // last aligned pair is (i2,j2)
+ while (state!=STOP)
+ {
+ step++;
+ states[step] = state = b[i][j];
+ this->i[step] = i;
+ this->j[step] = j;
+ // Exclude cells in direct neighbourhood from all further alignments
+ for (int ii=imax(i-2,1); ii<=imin(i+2,q.L); ii++)
+ cell_off[ii][j]=1;
+ for (int jj=imax(j-2,1); jj<=imin(j+2,t.L); jj++)
+ cell_off[i][jj]=1;
+ if (state==MM) matched_cols++;
+
+ switch (state)
+ {
+ case MM: i--; j--; break;
+ case IM: j--; break;
+ case MI: i--; break;
+ case STOP: break;
+ default:
+ fprintf(stderr,"Error: unallowed state value %i occurred during backtracing at step %i, (i,j)=(%i,%i)\n",state,step,i,j);
+ state=0;
+ v=4;
+ break;
+ } //end switch (state)
+ } //end while (state)
+
+ i1 = this->i[step];
+ j1 = this->j[step];
+ states[step] = MM; // first state (STOP state) is set to MM state
+ nsteps=step;
+
+ // Allocate new space for alignment scores
+ if (t.Xcons) Xcons = new( char[q.L+2]); // for template consensus sequence aligned to query
+ S = new( float[nsteps+1]);
+ S_ss = new( float[nsteps+1]);
+ P_posterior = new( float[nsteps+1]);
+ if (!P_posterior) MemoryError("space for HMM-HMM alignments");
+
+ // Add contribution from secondary structure score, record score along alignment,
+ // and record template consensus sequence in master-slave-alignment to query sequence
+ score_ss=0.0f;
+ sum_of_probs=0.0; // number of identical residues in query and template sequence
+ int ssm=ssm1+ssm2;
+// printf("Hit=%s\n",name); /////////////////////////////////////////////////////////////
+ for (step=1; step<=nsteps; step++)
+ {
+ switch(states[step])
+ {
+ case MM:
+ i = this->i[step];
+ j = this->j[step];
+ S[step] = Score(q.p[i],t.p[j]);
+ S_ss[step] = ScoreSS(q,t,i,j,ssm);
+ score_ss += S_ss[step];
+ P_posterior[step] = B_MM[this->i[step]][this->j[step]];
+ // Add probability to sum of probs if no dssp states given or dssp states exist and state is resolved in 3D structure
+ if (t.nss_dssp<0 || t.ss_dssp[j]>0) sum_of_probs += P_posterior[step];
+// printf("j=%-3i dssp=%1i P=%4.2f sum=%6.2f\n",j,t.ss_dssp[j],P_posterior[step],sum_of_probs); //////////////////////////
+ if (Xcons) Xcons[i]=t.Xcons[j]; //record database consensus sequence
+ break;
+ case MI: //if gap in template
+ case DG:
+ if (Xcons) Xcons[this->i[step]]=GAP; //(no break hereafter)
+ default: //if gap in T or Q
+ S[step] = S_ss[step] = P_posterior[step] = 0.0;
+ break;
+ }
+ }
+// printf("\n"); /////////////////////////////////////////////////////////////
+ if (ssm2>=1) score-=score_ss; // subtract SS score added during alignment!!!!
+ if (Xcons)
+ {
+ for (i=0; i<i1; i++) Xcons[i]=ENDGAP; // set end gap code at beginning and end of template consensus sequence
+ for (i=i2+1; i<=q.L+1; i++) Xcons[i]=ENDGAP;
+ }
+
+ // Add contribution from correlation of neighboring columns to score
+ float Scorr=0;
+ if (nsteps)
+ {
+ for (step=1; step<=nsteps-1; step++) Scorr+=S[step]*S[step+1];
+ for (step=1; step<=nsteps-2; step++) Scorr+=S[step]*S[step+2];
+ for (step=1; step<=nsteps-3; step++) Scorr+=S[step]*S[step+3];
+ for (step=1; step<=nsteps-4; step++) Scorr+=S[step]*S[step+4];
+ score+=par.corr*Scorr;
+ }
+
+ // Set score, P-value etc.
+ score_sort = score_aass = -score;
+ logPval=0; Pval=1;
+ if (t.mu)
+ {
+ logPvalt=logPvalue(score,t.lamda,t.mu);
+ Pvalt=Pvalue(score,t.lamda,t.mu);
+ }
+ else { logPvalt=0; Pvalt=1;}
+// printf("%-10.10s lamda=%-9f score=%-9f logPval=%-9g\n",name,t.lamda,score,logPvalt);
+
+
+ //DEBUG: Print out MAC alignment path
+ if (v>=4)
+ {
+ float sum_post=0.0;
+ printf("NAME=%7.7s score=%7.3f score_ss=%7.3f\n",name,score,score_ss);
+ printf("step Q T i j state score T Q cf ss-score P_post Sum_post\n");
+ for (step=nsteps; step>=1; step--)
+ {
+ switch(states[step])
+ {
+ case MM:
+ sum_post+=P_posterior[step];
+ printf("%4i %1c %1c ",step,q.seq[q.nfirst][this->i[step]],seq[nfirst][this->j[step]]);
+ break;
+ case IM:
+ printf("%4i - %1c ",step,seq[nfirst][this->j[step]]);
+ break;
+ case MI:
+ printf("%4i %1c - ",step,q.seq[q.nfirst][this->i[step]]);
+ break;
+ }
+ printf("%4i %4i %2i %7.1f ",this->i[step],this->j[step],(int)states[step],S[step]);
+ printf("%c %c %1i %7.1f ",i2ss(t.ss_dssp[this->j[step]]),i2ss(q.ss_pred[this->i[step]]),q.ss_conf[this->i[step]]-1,S_ss[step]);
+ printf("%7.5f %7.2f\n",P_posterior[step],sum_post);
+ }
+ }
+
+ return;
+}
+
+
+
+/////////////////////////////////////////////////////////////////////////////////////
+/**
+ * @brief Functions that calculate probabilities
+ */
+void
+Hit::InitializeForAlignment(HMM& q, HMM& t)
+{
+ int i,j;
+
+ // SS scoring during (ssm2>0) or after (ssm1>0) alignment? Query SS known or Template SS known?
+ switch (par.ssm)
+ {
+ case 0:
+ ssm1=0;
+ ssm2=0;
+ break;
+ case 1:
+ ssm2=0; // SS scoring after alignment
+ if (t.nss_dssp>=0 && q.nss_pred>=0) ssm1=1;
+ else if (q.nss_dssp>=0 && t.nss_pred>=0) ssm1=2;
+ else if (q.nss_pred>=0 && t.nss_pred>=0) ssm1=3;
+ else ssm1=0;
+ break;
+ case 2:
+ ssm1=0; // SS scoring during alignment
+ if (t.nss_dssp>=0 && q.nss_pred>=0) ssm2=1;
+ else if (q.nss_dssp>=0 && t.nss_pred>=0) ssm2=2;
+ else if (q.nss_pred>=0 && t.nss_pred>=0) ssm2=3;
+ else ssm2=0;
+ break;
+ case 3:
+ ssm2=0; // SS scoring after alignment
+ if (q.nss_pred>=0 && t.nss_pred>=0) ssm1=3; else ssm1=0;
+ break;
+ case 4:
+ ssm1=0; // SS scoring during alignment
+ if (q.nss_pred>=0 && t.nss_pred>=0) ssm2=3; else ssm2=0;
+ break;
+ // case 5:
+ // ssm2=0; // SS scoring after alignment
+ // if (q.nss_dssp>=0 && t.nss_dssp>=0) ssm1=4; else ssm1=0;
+ // break;
+ // case 6:
+ // ssm1=0; // SS scoring during alignment
+ // if (q.nss_dssp>=0 && t.nss_dssp>=0) ssm2=4; else ssm2=0;
+ // break;
+ }
+
+ if (self)
+ {
+ // Cross out cells in lower diagonal for self-comparison?
+ for (i=1; i<=q.L; i++)
+ {
+ int jmax = imin(i+SELFEXCL,t.L);
+ for (j=1; j<=jmax; j++)
+ cell_off[i][j]=1; // cross out cell near diagonal
+ for (j=jmax+1; j<=t.L+1; j++)
+ cell_off[i][j]=0; // no other cells crossed out yet
+ }
+ }
+ else
+ // Compare two different HMMs Q and T
+ {
+ // Activate all cells in dynamic programming matrix
+ for (i=1; i<=q.L; i++)
+ for (j=1; j<=t.L; j++)
+ cell_off[i][j]=0; // no other cells crossed out yet
+
+ // Cross out cells that are excluded by the minimum-overlap criterion
+ if (par.min_overlap==0)
+ min_overlap = imin(60, (int)(0.333f*imin(q.L,t.L))+1); // automatic minimum overlap
+ else
+ min_overlap = imin(par.min_overlap, (int)(0.8f*imin(q.L,t.L)));
+
+ for (i=0; i<min_overlap; i++)
+ for (j=i-min_overlap+t.L+1; j<=t.L; j++) // Lt-j+i>=Ovlap => j<=i-Ovlap+Lt => jmax=min{Lt,i-Ovlap+Lt}
+ cell_off[i][j]=1;
+ for (i=q.L-min_overlap+1; i<=q.L; i++)
+ for (j=1; j<i+min_overlap-q.L; j++) // Lq-i+j>=Ovlap => j>=i+Ovlap-Lq => jmin=max{1, i+Ovlap-Lq}
+ cell_off[i][j]=1;
+ }
+
+ // Cross out rows which are contained in range given by exclstr ("3-57,238-314")
+ if (par.exclstr)
+ {
+ char* ptr=par.exclstr;
+ int i0, i1;
+ while (1)
+ {
+ i0 = abs(strint(ptr));
+ i1 = abs(strint(ptr));
+ if (!ptr) break;
+ for (i=i0; i<=imin(i1,q.L); i++)
+ for (j=1; j<=t.L; j++)
+ cell_off[i][j]=1;
+ }
+ }
+}
+
+/////////////////////////////////////////////////////////////////////////////////////
+/**
+ * @brief Allocate memory for data of new alignment (sequence names, alignment, scores,...)
+ */
+void
+Hit::InitializeBacktrace(HMM& q, HMM& t)
+{
+ if (irep==1) //if this is the first single repeat repeat hit with this template
+ {
+ //Copy information about template profile to hit and reset template pointers to avoid destruction
+ longname=new(char[strlen(t.longname)+1]);
+ name =new(char[strlen(t.name)+1]);
+ file =new(char[strlen(t.file)+1]);
+ if (!file) MemoryError("space for alignments with database HMMs. \nNote that all alignments have to be kept in memory");
+ strcpy(longname,t.longname);
+ strcpy(name,t.name);
+ strcpy(fam ,t.fam);
+ strcpy(sfam ,t.sfam);
+ strcpy(fold ,t.fold);
+ strcpy(cl ,t.cl);
+ strcpy(file,t.file);
+ sname=new(char*[t.n_display]); // Call Compare only once with irep=1
+ seq =new(char*[t.n_display]); // Call Compare only once with irep=1
+ if (!sname || !seq)
+ MemoryError("space for alignments with database HMMs.\nNote that all sequences for display have to be kept in memory");
+
+ for (int k=0; k<t.n_display; k++) {
+ if (NULL != t.sname){
+ sname[k]=t.sname[k]; t.sname[k]=NULL;
+ }
+ else {
+ sname[k]=NULL;
+ }
+ seq[k] =t.seq[k]; t.seq[k]=NULL;
+ }
+
+ n_display=t.n_display; t.n_display=0;
+ ncons = t.ncons;
+ nfirst = t.nfirst;
+ nss_dssp = t.nss_dssp;
+ nsa_dssp = t.nsa_dssp;
+ nss_pred = t.nss_pred;
+ nss_conf = t.nss_conf;
+ L = t.L;
+ Neff_HMM = t.Neff_HMM;
+ Eval = 1.0;
+ Pval = 1.0;
+ Pvalt = 1.0;
+ logPval = 0.0;
+ logPvalt= 0.0;
+ Probab = 1.0;
+ }
+
+ // Allocate new space
+ this->i = new( int[i2+j2+2]);
+ this->j = new( int[i2+j2+2]);
+ states = new( char[i2+j2+2]);
+ S = S_ss = P_posterior = NULL; // set to NULL to avoid deleting data from irep=1 when hit with irep=2 is removed
+ Xcons = NULL;
+}
+
+/////////////////////////////////////////////////////////////////////////////////////
+// Some score functions
+/////////////////////////////////////////////////////////////////////////////////////
+
+
+/**
+ * @brief Calculate score between columns i and j of two HMMs (query and template)
+ */
+inline float
+Score(float* qi, float* tj)
+{
+// if (par.columnscore==9)
+// return (tj[0] *qi[0] +tj[1] *qi[1] +tj[2] *qi[2] +tj[3] *qi[3] +tj[4]*qi[4]
+// +tj[5] *qi[5] +tj[6] *qi[6] +tj[7] *qi[7] +tj[8] *qi[8] +tj[9]*qi[9]
+// +tj[10]*qi[10]+tj[11]*qi[11]+tj[12]*qi[12]+tj[13]*qi[13]+tj[14]*qi[14]
+// +tj[15]*qi[15]+tj[16]*qi[16]+tj[17]*qi[17]+tj[18]*qi[18]+tj[19]*qi[19]);
+// else
+ return fast_log2(
+ tj[0] *qi[0] +tj[1] *qi[1] +tj[2] *qi[2] +tj[3] *qi[3] +tj[4] *qi[4]
+ +tj[5] *qi[5] +tj[6] *qi[6] +tj[7] *qi[7] +tj[8] *qi[8] +tj[9] *qi[9]
+ +tj[10]*qi[10]+tj[11]*qi[11]+tj[12]*qi[12]+tj[13]*qi[13]+tj[14]*qi[14]
+ +tj[15]*qi[15]+tj[16]*qi[16]+tj[17]*qi[17]+tj[18]*qi[18]+tj[19]*qi[19]
+ );
+}
+
+/**
+ * @brief Calculate score between columns i and j of two HMMs (query and template)
+ */
+inline float
+ProbFwd(float* qi, float* tj)
+{
+ return tj[0] *qi[0] +tj[1] *qi[1] +tj[2] *qi[2] +tj[3] *qi[3] +tj[4] *qi[4]
+ +tj[5] *qi[5] +tj[6] *qi[6] +tj[7] *qi[7] +tj[8] *qi[8] +tj[9] *qi[9]
+ +tj[10]*qi[10]+tj[11]*qi[11]+tj[12]*qi[12]+tj[13]*qi[13]+tj[14]*qi[14]
+ +tj[15]*qi[15]+tj[16]*qi[16]+tj[17]*qi[17]+tj[18]*qi[18]+tj[19]*qi[19];
+}
+
+
+/**
+ * @brief Calculate secondary structure score between columns i and j of two HMMs (query and template)
+ */
+inline float
+Hit::ScoreSS(HMM& q, HMM& t, int i, int j, int ssm)
+{
+ switch (ssm) //SS scoring during alignment
+ {
+ case 0: // no SS scoring during alignment
+ return 0.0;
+ case 1: // t has dssp information, q has psipred information
+ return par.ssw * S73[ (int)t.ss_dssp[j]][ (int)q.ss_pred[i]][ (int)q.ss_conf[i]];
+ case 2: // q has dssp information, t has psipred information
+ return par.ssw * S73[ (int)q.ss_dssp[i]][ (int)t.ss_pred[j]][ (int)t.ss_conf[j]];
+ case 3: // q has dssp information, t has psipred information
+ return par.ssw * S33[ (int)q.ss_pred[i]][ (int)q.ss_conf[i]][ (int)t.ss_pred[j]][ (int)t.ss_conf[j]];
+// case 4: // q has dssp information, t has dssp information
+// return par.ssw*S77[ (int)t.ss_dssp[j]][ (int)t.ss_conf[j]];
+ }
+ return 0.0;
+}
+
+/**
+ * @brief Calculate secondary structure score between columns i and j of two HMMs (query and template)
+ */
+inline float
+Hit::ScoreSS(HMM& q, HMM& t, int i, int j)
+{
+ return ScoreSS(q,t,i,j,ssm2);
+}
+
+
+/**
+ * @brief Calculate score between columns i and j of two HMMs (query and template)
+ */
+inline float
+Hit::ScoreTot(HMM& q, HMM& t, int i, int j)
+{
+ return Score(q.p[i],t.p[j]) + ScoreSS(q,t,i,j) + par.shift;
+}
+
+/*
+ * Calculate score between columns i and j of two HMMs (query and template)
+ */
+inline float
+Hit::ScoreAA(HMM& q, HMM& t, int i, int j)
+{
+ return Score(q.p[i],t.p[j]);
+}
+
+
+/////////////////////////////////////////////////////////////////////////////////////
+/*
+ * Function for Viterbi()
+ */
+inline float
+max2(const float& xMM, const float& xX, char& b)
+{
+ if (xMM>xX) { b=MM; return xMM;} else { b=SAME; return xX;}
+}
+
+
+/////////////////////////////////////////////////////////////////////////////////////
+/*
+ * Functions for StochasticBacktrace()
+ */
+
+inline int
+pickprob2(const double& xMM, const double& xX, const int& state)
+{
+ if ( (xMM+xX)*frand() < xMM) return MM; else return state;
+}
+
+inline int
+pickprob3_GD(const double& xMM, const double& xDG, const double& xGD)
+{
+ double x = (xMM+xDG+xGD)*frand();
+ if ( x<xMM) return MM;
+ else if ( x<xMM+xDG) return DG;
+ else return GD;
+}
+
+inline int
+pickprob3_IM(const double& xMM, const double& xMI, const double& xIM)
+{
+ double x = (xMM+xMI+xIM)*frand();
+ if ( x<xMM) return MM;
+ else if ( x<xMM+xMI) return MI;
+ else return IM;
+}
+
+inline int
+pickprob6(const double& x0, const double& xMM, const double& xGD, const double& xIM, const double& xDG, const double& xMI)
+{
+ double x = (x0+xMM+xGD+xIM+xDG+xMI)*frand();
+ x-=xMM; if (x<0) return MM;
+ x-=x0; if (x<0) return STOP;
+ x-=xGD; if (x<0) return GD;
+ x-=xIM; if (x<0) return IM;
+ if (x < xDG) return DG; else return MI;
+}
+
+inline int
+pickmax2(const double& xMM, const double& xX, const int& state)
+{
+ if (xMM > xX) return MM; else return state;
+}
+
+inline int
+pickmax3_GD(const double& xMM, const double& xDG, const double& xGD)
+{
+ char state;
+ double x;
+ if ( xMM>xDG) {state=MM; x=xMM;}
+ else {state=DG; x=xDG;}
+ if ( xGD>x) {state=GD; x=xGD;}
+ return state;
+}
+
+inline int
+pickmax3_IM(const double& xMM, const double& xMI, const double& xIM)
+{
+ char state;
+ double x;
+ if ( xMM>xMI) {state=MM; x=xMM;}
+ else {state=MI; x=xMI;}
+ if ( xIM>x) {state=IM; x=xIM;}
+ return state;
+}
+
+inline int
+pickmax6(const double& x0, const double& xMM, const double& xGD, const double& xIM, const double& xDG, const double& xMI)
+{
+ char state;
+ double x;
+ if ( x0 >xMM) {state=STOP; x=x0;}
+ else {state=MM; x=xMM;}
+ if ( xGD>x) {state=GD; x=xGD;}
+ if ( xIM>x) {state=IM; x=xIM;}
+ if ( xDG>x) {state=DG; x=xDG;}
+ if ( xMI>x) {state=MI; x=xMI;}
+ return state;
+}
+
+
+/////////////////////////////////////////////////////////////////////////////////////
+//// Functions that calculate P-values and probabilities
+/////////////////////////////////////////////////////////////////////////////////////
+
+
+//// Evaluate the CUMULATIVE extreme value distribution at point x
+//// p(s)ds = lamda * exp{ -exp[-lamda*(s-mu)] - lamda*(s-mu) } ds = exp( -exp(-x) - x) dx = p(x) dx
+//// => P(s>S) = integral_-inf^inf {p(x) dx} = 1 - exp{ -exp[-lamda*(S-mu)] }
+inline double
+Pvalue(double x, double a[])
+{
+ //a[0]=lamda, a[1]=mu
+ double h = a[0]*(x-a[1]);
+ return (h>10)? exp(-h) : double(1.0)-exp( -exp(-h));
+}
+
+inline double
+Pvalue(float x, float lamda, float mu)
+{
+ double h = lamda*(x-mu);
+ return (h>10)? exp(-h) : (double(1.0)-exp( -exp(-h)));
+}
+
+inline double
+logPvalue(float x, float lamda, float mu)
+{
+ double h = lamda*(x-mu);
+ return (h>10)? -h : (h<-2.5)? -exp(-exp(-h)): log( ( double(1.0) - exp(-exp(-h)) ) );
+}
+
+inline double
+logPvalue(float x, double a[])
+{
+ double h = a[0]*(x-a[1]);
+ return (h>10)? -h : (h<-2.5)? -exp(-exp(-h)): log( ( double(1.0) - exp(-exp(-h)) ) );
+}
+
+// Calculate probability of true positive : p_TP(score)/( p_TP(score)+p_FP(score) )
+// TP: same superfamily OR MAXSUB score >=0.1
+inline double
+Probab(Hit& hit)
+{
+ double s=-hit.score_aass;
+ double t;
+ if (s>200) return 100.0;
+ if (par.loc)
+ {
+ if (par.ssm && (hit.ssm1 || hit.ssm2) && par.ssw>0)
+ {
+ // local with SS
+ const double a=sqrt(6000.0);
+ const double b=2.0*2.5;
+ const double c=sqrt(0.12);
+ const double d=2.0*32.0;
+ t = a*exp(-s/b) + c*exp(-s/d);
+ }
+ else
+ {
+ // local no SS
+ const double a=sqrt(4000.0);
+ const double b=2.0*2.5;
+ const double c=sqrt(0.15);
+ const double d=2.0*34.0;
+ t = a*exp(-s/b) + c*exp(-s/d);
+ }
+ }
+ else
+ {
+ if ( (par.ssm>0) && (par.ssw>0) ) /* FIXME: was '&', should be '&&' (or not?) */
+ {
+ // global with SS
+ const double a=sqrt(4000.0);
+ const double b=2.0*3.0;
+ const double c=sqrt(0.13);
+ const double d=2.0*34.0;
+ t = a*exp(-s/b) + c*exp(-s/d);
+ }
+ else
+ {
+ // global no SS
+ const double a=sqrt(6000.0);
+ const double b=2.0*2.5;
+ const double c=sqrt(0.10);
+ const double d=2.0*37.0;
+ t = a*exp(-s/b) + c*exp(-s/d);
+ }
+
+ }
+
+ return 100.0/(1.0+t*t);
+}
+
+// #define Weff(Neff) (1.0+par.neffa*(Neff-1.0)+(par.neffb-4.0*par.neffa)/16.0*(Neff-1.0)*(Neff-1.0))
+
+// /////////////////////////////////////////////////////////////////////////////////////
+// // Merge HMM with next aligned HMM
+// /////////////////////////////////////////////////////////////////////////////////////
+// void Hit::MergeHMM(HMM& Q, HMM& t, float wk[])
+// {
+// int i,j; // position in query and target
+// int a; // amino acid
+// int step; // alignment position (step=1 is end)
+// float Weff_M, Weff_D, Weff_I;
+// for (step=nsteps; step>=2; step--) // iterate only to one before last alignment column
+// {
+// i = this->i[step];
+// j = this->j[step];
+// switch(states[step])
+// {
+// case MM:
+// Weff_M = Weff(t.Neff_M[j]-1.0);
+// Weff_D = Weff(t.Neff_D[j]-1.0);
+// Weff_I = Weff(t.Neff_I[j]-1.0);
+// for (a=0; a<20; a++) Q.f[i][a] += t.f[j][a]*wk[j]*Weff_M;
+// switch(states[step-1])
+// {
+// case MM: // MM->MM
+// Q.tr_lin[i][M2M]+= t.tr_lin[j][M2M]*wk[j]*Weff_M;
+// Q.tr_lin[i][M2D]+= t.tr_lin[j][M2D]*wk[j]*Weff_M;
+// Q.tr_lin[i][M2I]+= t.tr_lin[j][M2I]*wk[j]*Weff_M;
+// Q.tr_lin[i][D2M]+= t.tr_lin[j][D2M]*wk[j]*Weff_D;
+// Q.tr_lin[i][D2D]+= t.tr_lin[j][D2D]*wk[j]*Weff_D;
+// Q.tr_lin[i][I2M]+= t.tr_lin[j][I2M]*wk[j]*Weff_I;
+// Q.tr_lin[i][I2I]+= t.tr_lin[j][I2I]*wk[j]*Weff_I;
+// break;
+// case MI: // MM->MI
+// Q.tr_lin[i][M2D]+= t.tr_lin[j][M2M]*wk[j]*Weff_M;
+// Q.tr_lin[i][M2D]+= t.tr_lin[j][M2D]*wk[j]*Weff_M;
+// Q.tr_lin[i][M2M]+= t.tr_lin[j][M2I]*wk[j]*Weff_M;
+// Q.tr_lin[i][D2D]+= t.tr_lin[j][D2M]*wk[j]*Weff_D;
+// Q.tr_lin[i][D2D]+= t.tr_lin[j][D2D]*wk[j]*Weff_D;
+// Q.tr_lin[i][I2M]+= t.tr_lin[j][I2M]*wk[j]*Weff_I;
+// Q.tr_lin[i][I2I]+= t.tr_lin[j][I2I]*wk[j]*Weff_I;
+// break;
+// case DG: // MM->DG
+// Q.tr_lin[i][M2D]+= t.tr_lin[j][M2M]*wk[j]*Weff_M;
+// Q.tr_lin[i][M2D]+= t.tr_lin[j][M2D]*wk[j]*Weff_M;
+// Q.tr_lin[i][M2M]+= t.tr_lin[j][M2I]*wk[j]*Weff_M;
+// Q.tr_lin[i][D2D]+= t.tr_lin[j][D2M]*wk[j]*Weff_D;
+// Q.tr_lin[i][D2D]+= t.tr_lin[j][D2D]*wk[j]*Weff_D;
+// Q.tr_lin[i][I2M]+= t.tr_lin[j][I2M]*wk[j]*Weff_I;
+// Q.tr_lin[i][I2I]+= t.tr_lin[j][I2I]*wk[j]*Weff_I;
+// break;
+// case IM: // MM->IM
+// Q.tr_lin[i][M2I]+= t.tr_lin[j][M2M]*wk[j]*Weff_M;
+// Q.tr_lin[i][M2M]+= t.tr_lin[j][M2D]*wk[j]*Weff_M;
+// Q.tr_lin[i][M2I]+= t.tr_lin[j][M2I]*wk[j]*Weff_M;
+// Q.tr_lin[i][D2M]+= t.tr_lin[j][D2M]*wk[j]*Weff_D;
+// Q.tr_lin[i][D2D]+= t.tr_lin[j][D2D]*wk[j]*Weff_D;
+// Q.tr_lin[i][I2M]+= t.tr_lin[j][I2M]*wk[j]*Weff_I;
+// Q.tr_lin[i][I2I]+= t.tr_lin[j][I2I]*wk[j]*Weff_I;
+// break;
+// case GD: // MM->GD
+// Q.tr_lin[i][M2I]+= t.tr_lin[j][M2M]*wk[j]*Weff_M;
+// Q.tr_lin[i][M2M]+= t.tr_lin[j][M2D]*wk[j]*Weff_M;
+// Q.tr_lin[i][M2I]+= t.tr_lin[j][M2I]*wk[j]*Weff_M;
+// Q.tr_lin[i][D2M]+= t.tr_lin[j][D2M]*wk[j]*Weff_D;
+// Q.tr_lin[i][D2D]+= t.tr_lin[j][D2D]*wk[j]*Weff_D;
+// Q.tr_lin[i][I2M]+= t.tr_lin[j][I2M]*wk[j]*Weff_I;
+// Q.tr_lin[i][I2I]+= t.tr_lin[j][I2I]*wk[j]*Weff_I;
+// break;
+// }
+// break;
+
+// case MI: // if gap in template
+// Weff_I = Weff(t.Neff_I[j]-1.0);
+// switch(states[step-1])
+// {
+// case MI: // MI->MI
+// Q.tr_lin[i][M2M]+= t.tr_lin[j][I2I]*wk[j]*Weff_I;
+// break;
+// case MM: // MI->MM
+// Q.tr_lin[i][M2M]+= t.tr_lin[j][I2M]*wk[j]*Weff_I;
+// break;
+// }
+// break;
+
+// case DG:
+// Weff_M = Weff(t.Neff_M[j]-1.0);
+// Weff_D = Weff(t.Neff_D[j]-1.0);
+// Weff_I = Weff(t.Neff_I[j]-1.0);
+// switch(states[step-1])
+// {
+// case DG: // DG->DG
+// Q.tr_lin[i][D2D]+= t.tr_lin[j][M2M]*wk[j]*Weff_M;
+// Q.tr_lin[i][D2D]+= t.tr_lin[j][D2M]*wk[j]*Weff_D;
+// Q.tr_lin[i][D2D]+= t.tr_lin[j][D2D]*wk[j]*Weff_D;
+// Q.tr_lin[i][M2M]+= t.tr_lin[j][I2I]*wk[j]*Weff_I;
+// Q.tr_lin[i][M2D]+= t.tr_lin[j][I2M]*wk[j]*Weff_I;
+// break;
+// case MM: // DG->MM
+// Q.tr_lin[i][D2M]+= t.tr_lin[j][M2M]*wk[j]*Weff_M;
+// Q.tr_lin[i][D2D]+= t.tr_lin[j][M2D]*wk[j]*Weff_M;
+// Q.tr_lin[i][D2M]+= t.tr_lin[j][D2M]*wk[j]*Weff_D;
+// Q.tr_lin[i][D2D]+= t.tr_lin[j][D2D]*wk[j]*Weff_D;
+// Q.tr_lin[i][I2I]+= t.tr_lin[j][I2I]*wk[j]*Weff_I;
+// Q.tr_lin[i][M2M]+= t.tr_lin[j][I2M]*wk[j]*Weff_I;
+// break;
+// }
+// break;
+
+// case IM: // if gap in query
+// Weff_M = Weff(t.Neff_M[j]-1.0);
+// switch(states[step-1])
+// {
+// case IM: // IM->IM
+// Q.tr_lin[i][I2I]+= t.tr_lin[j][M2M]*wk[j]*Weff_M;
+// Q.tr_lin[i][I2M]+= t.tr_lin[j][M2D]*wk[j]*Weff_M;
+// Q.tr_lin[i][I2I]+= t.tr_lin[j][M2I]*wk[j]*Weff_M;
+// break;
+// case MM: // IM->MM
+// Weff_D = Weff(t.Neff_D[j]-1.0);
+// Weff_I = Weff(t.Neff_I[j]-1.0);
+// Q.tr_lin[i][I2M]+= t.tr_lin[j][M2M]*wk[j]*Weff_M;
+// Q.tr_lin[i][I2M]+= t.tr_lin[j][M2D]*wk[j]*Weff_M;
+// Q.tr_lin[i][I2I]+= t.tr_lin[j][M2I]*wk[j]*Weff_M;
+// Q.tr_lin[i][I2M]+= t.tr_lin[j][D2M]*wk[j]*Weff_D;
+// Q.tr_lin[i][D2D]+= t.tr_lin[j][D2D]*wk[j]*Weff_D;
+// Q.tr_lin[i][I2M]+= t.tr_lin[j][I2M]*wk[j]*Weff_I;
+// Q.tr_lin[i][I2I]+= t.tr_lin[j][I2I]*wk[j]*Weff_I;
+// break;
+// }
+// break;
+
+// case GD:
+// Weff_M = Weff(t.Neff_M[j]-1.0);
+// switch(states[step-1])
+// {
+// case GD: // GD->GD
+// Weff_I = Weff(t.Neff_I[j]-1.0);
+// Q.tr_lin[i][I2I]+= t.tr_lin[j][M2M]*wk[j]*Weff_M;
+// Q.tr_lin[i][I2M]+= t.tr_lin[j][M2D]*wk[j]*Weff_M;
+// Q.tr_lin[i][I2I]+= t.tr_lin[j][M2I]*wk[j]*Weff_M;
+// Q.tr_lin[i][I2I]+= t.tr_lin[j][I2M]*wk[j]*Weff_I;
+// Q.tr_lin[i][I2I]+= t.tr_lin[j][I2I]*wk[j]*Weff_I;
+// break;
+// case MM: // GD->MM
+// Weff_D = Weff(t.Neff_D[j]-1.0);
+// Weff_I = Weff(t.Neff_I[j]-1.0);
+// Q.tr_lin[i][I2M]+= t.tr_lin[j][M2M]*wk[j]*Weff_M;
+// Q.tr_lin[i][I2M]+= t.tr_lin[j][M2D]*wk[j]*Weff_M;
+// Q.tr_lin[i][I2I]+= t.tr_lin[j][M2I]*wk[j]*Weff_M;
+// Q.tr_lin[i][D2D]+= t.tr_lin[j][D2D]*wk[j]*Weff_D;
+// Q.tr_lin[i][I2M]+= t.tr_lin[j][I2M]*wk[j]*Weff_I;
+// Q.tr_lin[i][I2I]+= t.tr_lin[j][I2I]*wk[j]*Weff_I;
+// break;
+// }
+// break;
+
+// }
+// }
+// i = this->i[step];
+// j = this->j[step];
+// Weff_M = Weff(t.Neff_M[j]-1.0);
+// for (a=0; a<20; a++) Q.f[i][a] += t.f[j][a]*wk[j]*Weff_M;
+// }
+
+
+#ifdef CLUSTALO
+/* @* Hit::ClobberGlobal (eg, hit)
+ *
+ */
+void
+Hit::ClobberGlobal(void){
+
+ if (i){
+ //delete[] i;
+ i = NULL;
+ }
+ if (j){
+ //delete[] j;
+ j = NULL;
+ }
+ if (states){
+ //delete[] states;
+ states = NULL;
+ }
+ if (S){
+ //delete[] S;
+ S = NULL;
+ }
+ if (S_ss){
+ //delete[] S_ss;
+ S_ss = NULL;
+ }
+ if (P_posterior){
+ //delete[] P_posterior;
+ P_posterior = NULL;
+ }
+ if (Xcons){
+ //delete[] Xcons;
+ Xcons = NULL;
+ }
+ // delete[] l; l = NULL;
+ i = j = NULL;
+ states = NULL;
+ S = S_ss = P_posterior = NULL;
+ Xcons = NULL;
+ if (irep==1) // if irep>1 then longname etc point to the same memory locations as the first repeat.
+ { // but these have already been deleted.
+ // printf("Delete name = %s\n",name);//////////////////////////
+ //delete[] longname;
+ longname = NULL;
+ //delete[] name;
+ name = NULL;
+ //delete[] file;
+ file = NULL;
+ //delete[] dbfile;
+ dbfile = NULL;
+ /*for (int k=0; k<n_display; k++)
+ {
+ delete[] sname[k]; sname[k] = NULL;
+ delete[] seq[k]; seq[k] = NULL;
+ }*/
+ //delete[] sname;
+ sname = NULL;
+ //delete[] seq;
+ seq = NULL;
+ }
+
+ score = score_sort = score_aass = 0.0;
+ Pval = Pvalt = Eval = Probab = 0;
+ Pforward = sum_of_probs = 0.00;
+ L = irep = nrep = n_display = nsteps = 0;
+ i1 = i2 = j1 = j2 = matched_cols = min_overlap = 0;
+}
+#endif
+
+
+/*
+ * EOF hhhit-C.h
+ */
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