def set_default(model_name, func_name):
    """
    Set values and bounds to Model parameters in lmfit.

    Parameters
    ----------
    model_name : class object
        Model class object from lmfit
    func_name : function
        function name of physics peak
    """
    paras = inspect.getargspec(func_name)

    # the first argument is independent variable, also ignored
    # default values are not considered for fitting in this function
    my_args = paras.args[1:]
    para_dict = get_para()

    for name in my_args:

        if para_dict.keys() not in name:
            continue

        my_dict = para_dict[name]
        if my_dict['bound_type'] == 'none':
            model_name.set_param_hint(name, vary=True)
        elif my_dict['bound_type'] == 'fixed':
            model_name.set_param_hint(name, vary=False, value=my_dict['value'])
        elif my_dict['bound_type'] == 'lo':
            model_name.set_param_hint(name, value=my_dict['value'], vary=True,
                                      min=my_dict['min'])
        elif my_dict['bound_type'] == 'hi':
            model_name.set_param_hint(name, value=my_dict['value'], vary=True,
                                      max=my_dict['max'])
        elif my_dict['bound_type'] == 'lohi':
            model_name.set_param_hint(name, value=my_dict['value'], vary=True,
                                      min=my_dict['min'], max=my_dict['max'])
        else:
            raise TypeError("Boundary type {0} can't be "
                            "used".format(my_dict['bound_type']))
dataset/ETHPy150Open scikit-beam/scikit-beam/skbeam/core/fitting/models.py/set_default/swapped operands of `not in`