def show_progress(self, history):
scale, err = nllf_scale(self.problem)
chisq = format_uncertainty(scale * history.value[0], err)
self.status_text.value = '<table width="50%%"><tr><td>step</td><td>%s</td><td>cost</td><td>%s</td></tr></table>' % (
history.step[0], chisq)
self.steps.append(history.step[0])
self.chis.append(scale * history.value[0])
def show_progress(self, history):
scale, err = nllf_scale(self.problem)
chisq = format_uncertainty(scale * history.value[0], err)
self.ptxt.SetLabel('step: %s/%s\tcost: %s' %
(history.step[0], self.pbar.GetRange(), chisq))
self.pbar.SetValue(history.step[0])
self.steps.append(history.step[0])
self.chis.append(scale * history.value[0])
Mq.A0.range(0, 0.05)
Mq.A1.range(0, 1)
Mq.hwhm1.range(0, 0.5)
Mq.hwhm2.range(0, 3)
# Q-independent parameters
if i == 0:
QA0 = Mq.A0
else:
Mq.A0 = QA0
M.append(Mq)
problem = bmp.FitProblem(M)
# Preview of the settings
print('Initial chisq', problem.chisq_str())
problem.plot()
result = fit(problem, method='lm', steps=100, verbose=True)
problem.plot()
# Print chi**2 and parameters' values after fit
print("final chisq", problem.chisq_str())
for k, v, dv in zip(problem.labels(), result.x, result.dx):
print(k, ":", format_uncertainty(v, dv))
plt.show()
Mq.A0.range(0, 1)
Mq.hwhm.range(0, 2)
# Q-independent parameters
if i == 0:
QA0 = Mq.A0
else:
Mq.A0 = QA0
M.append(Mq)
problem = bmp.FitProblem(M)
# Preview of the settings
print('Initial chisq', problem.chisq_str())
problem.plot()
result = fit(problem, method='lm', steps=100, verbose=True)
problem.plot()
# Print chi**2 and parameters' values after fit
print("final chisq", problem.chisq_str())
for k, v, dv in zip(problem.labels(), result.x, result.dx):
if k in dict_physical_units.keys():
print(k, ":", format_uncertainty(v, dv), dict_physical_units[k])
else:
print(k, ":", format_uncertainty(v, dv))
plt.show()
