Is there any way to set an equality constraint?

[Zeng1998]

Describe the bug

import math
import numpy as np
from math import prod, fabs
from openbox import sp


def mishra(config: sp.Configuration):
    config_dict = config.get_dictionary()
    ws = np.array([config_dict['w%d' % i] for i in range(3)])
    # if fabs(sum(ws)-1)>1e-6:
    #     return {
    #         "objs":[math.inf,],
    #     }

    # if sum(ws) > 1:
    #     return {
    #         "objs": [math.inf, ]
    #     }

    result = dict()
    result['objs'] = [-1 * (ws[0] * 2 + ws[1] * 3 + ws[2]), ]
    # ?
    result["constraints"] = [fabs(sum(ws) - 1) - 1e-6, ]
    return result


N = 3
df = 1 / N
params = {
    'float': {
        f"w{i}": (0, 1, df) for i in range(N)
    }
}
space = sp.Space()
space.add_variables([
    sp.Real(name, *para) for name, para in params['float'].items()
])

from openbox import Optimizer

opt = Optimizer(
    mishra,
    space,
    num_objs=1,
    num_constraints=1,
    surrogate_type='gp',
    acq_optimizer_type='random_scipy',
    max_runs=50,
    time_limit_per_trial=10,
    task_id='soc',
)
history = opt.run()

print(history)

Here is my code, I want the sum of these three parameters to be 1, I tried adding constraints of both 1-sum(ws) and sum(ws)-1 but it doesn't work

[salty-fish-97]

Thanks for your issue. It's very hard for black-box optimization to support black-box equality constraints, as the inner algorithm does not know how the constraint values are exactly computed. For your question, while the constraint value is directly computed by the input values (ws[0-2]), we suggest defining only 2 parameters in the search space, so that the third parameter can be represented by 1-ws[0]-ws[1]. We hope this can solve your problem.

[Zeng1998]

Thanks.