BayesianOptimizer_init.py

from sklearn.gaussian_process import GaussianProcessRegressor
from scipy.stats import norm
from scipy.optimize import minimize
import sys
import pandas as pd

class BayesianOptimizer():
      
    def __init__(self, target_func, x_init, y_init, n_iter, scale, batch_size):
        self.x_init = x_init
        self.y_init = y_init
        self.target_func = target_func
        self.n_iter = n_iter
        self.scale = scale
        self.batch_size = batch_size
        self.gauss_pr = GaussianProcessRegressor()
        self.best_samples_ = pd.DataFrame(columns = ['x', 'y', 'ei'])
        self.distances_ = []