Eval_type 'list' causing errors in mixed-space example

[Dvermetten]

Describe the bug When setting the eval_type to 'list' in the following code, it throws an error, while it works properly with 'dict'.

To Reproduce `def test_mix_space(eval_type): dim_r = 2 # dimension of the real values def obj_fun(x): xr = np.array([x['continuous%d'%i] for i in range(dim_r)]) x_i = x['ordinal'] xd = x['nominal'] = 0 if x_d == 'OK' else 1 return np.sum(x_r * 2) + abs(xi - 10) / 123. + 2

search_space = ContinuousSpace([-5, 5], var_name='continuous') * dim_r + \
    OrdinalSpace([5, 15], var_name='ordinal') + \
    NominalSpace(['OK', 'A', 'B', 'C', 'D', 'E', 'F', 'G'], var_name='nominal')

model = RandomForest(levels=search_space.levels)

opt = ParallelBO(
    search_space=search_space, 
    obj_fun=obj_fun, 
    model=model, 
    max_FEs=6, 
    DoE_size=3,    # the initial DoE size
    eval_type=eval_type,
    acquisition_fun='MGFI',
    acquisition_par={'t' : 2},
    n_job=3,       # number of processes
    n_point=3,     # number of the candidate solution proposed in each iteration
    verbose=True   # turn this off, if you prefer no output
)
xopt, fopt, stop_dict = opt.run()

print('xopt: {}'.format(xopt))
print('fopt: {}'.format(fopt))
print('stop criteria: {}'.format(stop_dict))`