Traceback (most recent call last):


 "pet_weights.py", line 69, in <module>

fire.Fire(MyClass)


 "/home/maye/miniconda3/envs/py37/lib/python3.7/site-packages/fire/core.py", line 164, in Fire

_PrintResult(component_trace, verbose=component_trace.verbose)


 "/home/maye/miniconda3/envs/py37/lib/python3.7/site-packages/fire/core.py", line 267, in _PrintResult

result, trace=component_trace, verbose=verbose)


 "/home/maye/miniconda3/envs/py37/lib/python3.7/site-packages/fire/helptext.py", line 63, in HelpText

actions_grouped_by_kind = _GetActionsGroupedByKind(component, verbose=verbose)


 "/home/maye/miniconda3/envs/py37/lib/python3.7/site-packages/fire/helptext.py", line 332, in _GetActionsGroupedByKind

members = completion.VisibleMembers(component, verbose=verbose)


 "/home/maye/miniconda3/envs/py37/lib/python3.7/site-packages/fire/completion.py", line 366, in VisibleMembers

(member_name, member) for member_name, member in members


 "/home/maye/miniconda3/envs/py37/lib/python3.7/site-packages/fire/completion.py", line 368, in <listcomp>

verbose=verbose)


 "/home/maye/miniconda3/envs/py37/lib/python3.7/site-packages/fire/completion.py", line 311, in MemberVisible

if member in (absolute_import, division, print_function):


 "/home/maye/miniconda3/envs/py37/lib/python3.7/site-packages/pandas/core/generic.py", line 1479, in __nonzero__

f"The truth value of a {type(self).__name__} is ambiguous. "
ValueError: The truth value of a DataFrame is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

Traceback (most recent call last):


 "<stdin>", line 1, in <module>


 "C:\Python27\lib\site-packages\spyderlib\widgets\externalshell\sitecustomize.py", line 685, in runfile

execfile(filename, namespace)


 "C:\Python27\lib\site-packages\spyderlib\widgets\externalshell\sitecustomize.py", line 71, in execfile

exec(compile(scripttext, filename, 'exec'), glob, loc)


 "C:/Users/l.breuer/Desktop/lmfit_bug.py", line 60, in <module>

result = mod.fit(T, pars, x=x)


 "C:\Python27\lib\site-packages\lmfit\model.py", line 541, in fit

output.fit(data=data, weights=weights)


 "C:\Python27\lib\site-packages\lmfit\model.py", line 747, in fit

_ret = self.minimize(method=self.method)


 "C:\Python27\lib\site-packages\lmfit\minimizer.py", line 1168, in minimize

return function(**kwargs)


 "C:\Python27\lib\site-packages\lmfit\minimizer.py", line 1008, in leastsq

lsout = scipy_leastsq(self.__residual, vars, **lskws)


 "C:\Python27\lib\site-packages\scipy\optimize\minpack.py", line 381, in leastsq

gtol, maxfev, epsfcn, factor, diag)


 "C:\Python27\lib\site-packages\lmfit\minimizer.py", line 331, in __residual

out = _nan_policy(out, nan_policy=self.nan_policy)


 "C:\Python27\lib\site-packages\lmfit\minimizer.py", line 1357, in _nan_policy

raise ValueError("The input contains nan values")
ValueError: The input contains nan values
