Loading sas_temper/sas_temper_engine.py +4 −3 Original line number Diff line number Diff line Loading @@ -402,7 +402,7 @@ def est_uncerts(d, f, modconf, best_model): tprof = sas_data.Model(d, unsmeared = False) # preparation work for calculating the Jacobian matrix from the derivative step = 0.01 step = 0.001 for i,p in enumerate(modconf.params): if p.kind not in ["fixed"]: eps.params[i].val = step*(p.max - p.min) Loading @@ -415,6 +415,7 @@ def est_uncerts(d, f, modconf, best_model): tmp.params[i].val = f.params[i].val + eps.params[i].val if tmp.params[i].val >= modconf.params[i].max: tmp.params[i].val = f.params[i].val - eps.params[i].val print("tmp.params[i].val = "+str(tmp.params[i].val)+" f.params[i].val = "+str(f.params[i].val)+" eps.params[i].val = "+str(eps.params[i].val)) stepped.append(tmp) steps.append(eps.params[i].val) Loading Loading @@ -478,8 +479,8 @@ def est_uncerts(d, f, modconf, best_model): for z in range(0,len(tprof.y)): tprof.y[z] = 0.5*(lprof.y[z]-best_model.y[z])/(d.dy[z]*steps[w]) if z==0: print(str(best_model.y[z]) + " " + str(lprof.y[z]) + " " + str(steps[w]) + " tprof.y[0] = "+str(tprof.y[z])) #if z==0: #print(str(best_model.y[z]) + " " + str(lprof.y[z]) + " " + str(steps[w]) + " tprof.y[0] = "+str(tprof.y[z])) JT.append(tprof.y) Loading Loading
sas_temper/sas_temper_engine.py +4 −3 Original line number Diff line number Diff line Loading @@ -402,7 +402,7 @@ def est_uncerts(d, f, modconf, best_model): tprof = sas_data.Model(d, unsmeared = False) # preparation work for calculating the Jacobian matrix from the derivative step = 0.01 step = 0.001 for i,p in enumerate(modconf.params): if p.kind not in ["fixed"]: eps.params[i].val = step*(p.max - p.min) Loading @@ -415,6 +415,7 @@ def est_uncerts(d, f, modconf, best_model): tmp.params[i].val = f.params[i].val + eps.params[i].val if tmp.params[i].val >= modconf.params[i].max: tmp.params[i].val = f.params[i].val - eps.params[i].val print("tmp.params[i].val = "+str(tmp.params[i].val)+" f.params[i].val = "+str(f.params[i].val)+" eps.params[i].val = "+str(eps.params[i].val)) stepped.append(tmp) steps.append(eps.params[i].val) Loading Loading @@ -478,8 +479,8 @@ def est_uncerts(d, f, modconf, best_model): for z in range(0,len(tprof.y)): tprof.y[z] = 0.5*(lprof.y[z]-best_model.y[z])/(d.dy[z]*steps[w]) if z==0: print(str(best_model.y[z]) + " " + str(lprof.y[z]) + " " + str(steps[w]) + " tprof.y[0] = "+str(tprof.y[z])) #if z==0: #print(str(best_model.y[z]) + " " + str(lprof.y[z]) + " " + str(steps[w]) + " tprof.y[0] = "+str(tprof.y[z])) JT.append(tprof.y) Loading