Loading sas_temper/sas_temper_engine.py +4 −1 Original line number Diff line number Diff line Loading @@ -399,6 +399,7 @@ def est_uncerts(d, f, modconf, best_model): # local profile for the calculation of the derivative lprof_usm = sas_data.Model(d, unsmeared = True) lprof = sas_data.Model(d, unsmeared = False) tprof = sas_data.Model(d, unsmeared = False) # preparation work for calculating the Jacobian matrix from the derivative step = 0.01 Loading Loading @@ -474,7 +475,9 @@ def est_uncerts(d, f, modconf, best_model): lprof_usm = sas_calc.calc_profile_usm(d, stepped[w]) lprof = sas_calc.calc_profile(d,stepped[w],lprof_usm) JT.append((lprof.y-best_model.y)*(lprof.y-best_model.y)/(d.dy*d.dy*steps[w]) tprof.y = (lprof.y-best_model.y)/d.dy tprof.y = tprof.y*tprof.y JT.append(tprof.y/steps[w]) #this is the matrix that we want J_T = np.vstack(JT) Loading Loading
sas_temper/sas_temper_engine.py +4 −1 Original line number Diff line number Diff line Loading @@ -399,6 +399,7 @@ def est_uncerts(d, f, modconf, best_model): # local profile for the calculation of the derivative lprof_usm = sas_data.Model(d, unsmeared = True) lprof = sas_data.Model(d, unsmeared = False) tprof = sas_data.Model(d, unsmeared = False) # preparation work for calculating the Jacobian matrix from the derivative step = 0.01 Loading Loading @@ -474,7 +475,9 @@ def est_uncerts(d, f, modconf, best_model): lprof_usm = sas_calc.calc_profile_usm(d, stepped[w]) lprof = sas_calc.calc_profile(d,stepped[w],lprof_usm) JT.append((lprof.y-best_model.y)*(lprof.y-best_model.y)/(d.dy*d.dy*steps[w]) tprof.y = (lprof.y-best_model.y)/d.dy tprof.y = tprof.y*tprof.y JT.append(tprof.y/steps[w]) #this is the matrix that we want J_T = np.vstack(JT) Loading