tdomain_res.append(k)
for res in tprofile_res:
for rdef in rdc_data[i][res]:
res1, sp1 , res2, sp2, rdc = rdef[0], rdef[1], rdef[2], rdef[3], rdef[4]
res1_index = tprofile_res.index(res1)
d_res1= tdomain_res[res1_index]
try:
res2_index = tprofile_res.index(res2)
d_res2 = tdomain_res[res2_index]
except:
if res2 == res1-1:
d_res2 = d_res1-1
c1 = pymol.cmd.get_model('('+sname2+' and name '+sp1+' and resi '+str(d_res1)+' )').get_coord_list()
c2 = pymol.cmd.get_model('('+sname2+' and name '+sp2+' and resi '+str(d_res2)+' )').get_coord_list()
if c1 and c2:
v1 = rf.getVector(c1,c2)
vec_gm = rf.getGMR(sp1, sp2)
vec_data.append([v1,vec_gm,rdc])
else:
continue # check this implementation
maxcs = 10000 # maximum number of optimization calls
soln, cov, info, mesg, success = leastsq(rf.RDC_ZYZ, ptensor, args=(scal, vec_data), full_output=1, maxfev=maxcs)
chisq = sum(info["fvec"]*info["fvec"])
tensor_utr = utr.AnglesUTR(soln)
if ud.rdc_filter(tensor_utr):
if chisq/len(vec_data) < 7.0:
# sort_nchi[tnchi]=[temp_nchi,temp_tensor,log,domain]
temp_tensor.append([tensor_utr, vec_data])
temp_nchi.append(chisq/len(vec_data))
if len(temp_nchi) < i+1:
break
