zanetta_second_error

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-39-840bfeb05f2a> in <module>()
----> 1 m.fit_background(bounded=True)

c:\users\me\documents\github\hyperspy\hyperspy\models\edsmodel.py in fit_background(self, start_energy, end_energy, windows_sigma, kind, **kwargs)
    445                         windows_sigma[1] * component.sigma.value)
    446             if kind == 'single':
--> 447                 self.fit(**kwargs)
    448             if kind == 'multi':
    449                 self.multifit(**kwargs)

c:\users\me\documents\github\hyperspy\hyperspy\model.py in fit(self, fitter, method, grad, bounded, ext_bounding, update_plot, **kwargs)
   1064                     output = \
   1065                         least_squares(self._errfunc, self.p0[:],
-> 1066                                       args=args, bounds=ls_b, **kwargs)
   1067                     self.p0 = output.x
   1068 

C:\ProgramData\Anaconda3\envs\py\lib\site-packages\scipy\optimize\_lsq\least_squares.py in least_squares(fun, x0, jac, bounds, method, ftol, xtol, gtol, x_scale, loss, f_scale, diff_step, tr_solver, tr_options, jac_sparsity, max_nfev, verbose, args, kwargs)
    797         x0 = make_strictly_feasible(x0, lb, ub)
    798 
--> 799     f0 = fun_wrapped(x0)
    800 
    801     if f0.ndim != 1:

C:\ProgramData\Anaconda3\envs\py\lib\site-packages\scipy\optimize\_lsq\least_squares.py in fun_wrapped(x)
    792 
    793     def fun_wrapped(x):
--> 794         return np.atleast_1d(fun(x, *args, **kwargs))
    795 
    796     if method == 'trf':

c:\users\me\documents\github\hyperspy\hyperspy\models\model1d.py in _errfunc(self, param, y, weights)
    437         if weights is None:
    438             weights = 1.
--> 439         errfunc = self._model_function(param) - y
    440         return errfunc * weights
    441 

c:\users\me\documents\github\hyperspy\hyperspy\model.py in _model_function(self, param)
    838         self.p0 = param
    839         self._fetch_values_from_p0()
--> 840         to_return = self.__call__(non_convolved=False, onlyactive=True)
    841         return to_return
    842 

c:\users\me\documents\github\hyperspy\hyperspy\models\model1d.py in __call__(self, non_convolved, onlyactive)
    402                 for component in self:
    403                     if component.active:
--> 404                         sum_ += component.function(axis)
    405             else:
    406                 for component in self:

c:\users\me\documents\github\hyperspy\hyperspy\_components\physical_background.py in function(self, x)
    279         Cthickness=self.coating_thickness.value
    280 
--> 281         Mu=Mucoef(self.model,self.quanti.value)
    282         Mu=np.array(Mu,dtype=float)
    283         #Mu=Mu[self.model.channel_switches]

c:\users\me\documents\github\hyperspy\hyperspy\_components\physical_background.py in Mucoef(model, quanti)
    140 
    141     if np.sum(quanti)==0:
--> 142         raise ValueError("The quantification cannot be nul, but an an array with all weight percents set to 0 have been provided" )
    143     else:
    144         t=(np.linspace(model._signal.axes_manager[-1].offset,model._signal.axes_manager[-1].size*model._signal.axes_manager[-1].scale,model._signal.axes_manager[-1].size))

ValueError: The quantification cannot be nul, but an an array with all weight percents set to 0 have been provided