void Align(const std::string& ref_seq, const std::string& read_seq,
std::string& ref_seq_al, std::string& read_seq_al,
float* score, std::vector<BamTools::CigarOp>& cigar_list) {
int L1 = ref_seq.length();
int L2 = read_seq.length();
int mat_size = (L1+1)*(L2+1);
// Scoring matrices
std::vector<float> M(mat_size); // Ref and read bases aligned
std::vector<float> Iref(mat_size); // Ref base aligned with gap
std::vector<float> Iread(mat_size); // Read base aligned with gap
// Traceback matrices
std::vector<int> traceM(mat_size);
std::vector<int> traceIref(mat_size);
std::vector<int> traceIread(mat_size);
M[0] = 0.0;
Iref[0] = -LARGE; // Impossible
Iread[0] = -LARGE; // Impossible
// Fill in row (0,n)
for(int i = 1; i < L1+1; i++){
// No penalty for leading affine gap in reference seq
Iref[i] = 0.0;
traceIref[i] = 1;
// Impossible
Iread[i] = -LARGE;
traceIread[i] = -1;
// Impossible
M[i] = -LARGE;
traceM[i] = -1;
}
// Fill in column (n, 0)
for(int i = 1; i < L2+1; i++){
int index = i*(L1+1);
// Penalty for leading affine gap in read sequence
Iread[index] = -GAPOPEN-(i-1)*GAPEXTEND;
traceIread[index] = 2;
// Impossible
Iref[index] = -LARGE;
traceIref[index] = -1;
// Impossible
M[index] = -LARGE;
traceM[index] = -1;
}
// Determine optimal alignment
nw_helper(M, Iref, Iread, traceM, traceIref, traceIread,
ref_seq, read_seq, ref_seq_al, read_seq_al, score, cigar_list);
}
static int
process(Engine *ep, char *parname, char *resname)
{
FILE *f;
FileInfo fi;
char *s;
int *asv, asvkind[3], i, j, k, m1, n1, n2, nd, *p, rc;
mxArray *X;
real *x;
rc = 1;
if (!strcmp(parname,"setup") &&
!strcmp(resname,"workspace"))
{
printf("pre-processing with setupworkspace.m\n");
fflush(stdout);
engEvalString(ep, "setupworkspace");
return 0;
}
if (!(fi.f = fopen(parname,"r"))) {
BadOpen("parameters_file", parname);
goto done1;
}
fi.fname = s;
fi.lineno = 0;
n1 = Iread(&fi, "variables");
X = mxCreateDoubleMatrix(1, n1, mxREAL);
x = (real*)mxGetPr(X);
for(i = 0; i < n1; i++)
x[i] = Dread(&fi);
m1 = Iread(&fi, "functions");
asvkind[0] = asvkind[1] = asvkind[2] = 0;
asv = (int*)Malloc((n1+m1)*sizeof(int));
p = asv + m1;
for(i = 0; i < m1; i++) {
asv[i] = j = Iread(&fi,0);
for(k = 0; k < 3 && j; k++, j >>= 1)
if (j & 1)
++asvkind[k];
}
nd = Iread(&fi, "derivative_variables");
for(i = 0; i < nd; i++)
p[i] = Iread(&fi, 0) - 1;
fclose(fi.f);
f = fopen(resname, "w");
if (!f) {
BadOpen("results_file", resname);
mxDestroyArray(X);
goto done1;
}
engPutVariable(ep, "x", X);
mxDestroyArray(X);
X = mxCreateDoubleMatrix(1, 3, mxREAL);
x = (real*)mxGetPr(X);
for(i = 0; i < 3; i++)
x[i] = asvkind[i];
engPutVariable(ep, "asv", X);
mxDestroyArray(X);
if (asvkind[0]) {
engEvalString(ep, "eval(FunctionEvaluation);");
//engEvalString(ep, "y = f(x);");
X = engGetVariable(ep,"y");
if (!X) {
Squawk("MATLAB didn't return y = f(x)\n");
goto done;
}
x = (real*)mxGetPr(X);
for(i = 0; i < m1; i++)
if (asv[i] & 1)
fprintf(f, " %.17g\n", x[i]);
mxDestroyArray(X);
}
if (asvkind[1]) {
engEvalString(ep, "eval(GradientEvaluation);");
//engEvalString(ep, "yp = fp(x);");
X = engGetVariable(ep,"yp");
if (!X) {
Squawk("MATLAB didn't return yp = fp(x)\n");
goto done;
}
x = (real*)mxGetPr(X);
for(i = 0; i < m1; i++, x += n1)
if (asv[i] & 2)
grdout(f, n1, p, x);
mxDestroyArray(X);
}
if (asvkind[2]) {
engEvalString(ep, "eval(HessianEvaluation);");
//engEvalString(ep, "ypp = fpp(x);");
X = engGetVariable(ep,"ypp");
if (!X) {
Squawk("MATLAB didn't return ypp = fpp(x)\n");
goto done;
}
x = (real*)mxGetPr(X);
n2 = n1*n1;
for(i = 0; i < m1; i++, x += n2)
if (asv[i] & 4)
hesout(f, n1, p, x);
mxDestroyArray(X);
}
rc = 0;
done:
fclose(f);
done1:
free(asv);
return rc;
}
