Loading sas_temper/sas_temper_engine.py +4 −0 Original line number Diff line number Diff line Loading @@ -469,6 +469,9 @@ def est_uncerts(d, f, modconf, best_model): # and this is where things get ugly JT = [] for w in range(0,len(stepped)): for a,m in enumerate(stepped[w].params): print("stepped["+str(w)+"] parameters " + str(m.params[a].val)) #calculate the profiles if d.dx is None: lprof = sas_calc.calc_profile_usm(d, stepped[w]) Loading @@ -486,6 +489,7 @@ def est_uncerts(d, f, modconf, best_model): #this is the matrix that we want J_T = np.vstack(JT) J = J_T.T print("Jacobian") print(J) # This is an approximation of the Hessian Loading Loading
sas_temper/sas_temper_engine.py +4 −0 Original line number Diff line number Diff line Loading @@ -469,6 +469,9 @@ def est_uncerts(d, f, modconf, best_model): # and this is where things get ugly JT = [] for w in range(0,len(stepped)): for a,m in enumerate(stepped[w].params): print("stepped["+str(w)+"] parameters " + str(m.params[a].val)) #calculate the profiles if d.dx is None: lprof = sas_calc.calc_profile_usm(d, stepped[w]) Loading @@ -486,6 +489,7 @@ def est_uncerts(d, f, modconf, best_model): #this is the matrix that we want J_T = np.vstack(JT) J = J_T.T print("Jacobian") print(J) # This is an approximation of the Hessian Loading