Boolean variables not supported in combination with other categoricals #10
Description
Describe the bug
When the search space contains a boolean variable in addition to another categorical variable which is non-boolean, the search will fail.
To Reproduce
The following is a slight modification of an existing test to show the problem
`dim_r = 2 # dimension of the real values
def obj_fun(x):
x_r = np.array([x['continuous_%d'%i] for i in range(dim_r)])
x_i = x['ordinal']
x_d = x['nominal']
_ = 0 if x_d == 'OK' else 1
return np.sum(x_r ** 2) + abs(x_i - 10) / 123. + _ * 2
search_space = ContinuousSpace([-5, 5], var_name='continuous') * dim_r +
OrdinalSpace([5, 15], var_name='ordinal') +
NominalSpace(['OK', 'A', None], var_name='nominal') +
NominalSpace([True, False], var_name='boolvar')
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='dict',
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=False # turn this off, if you prefer no output
)
xopt, fopt, stop_dict = opt.run()`
Expected behavior
This should perform exactly the same as the case without boolean variable
Additional context
It seems to be related to the checking of input in the random forest