bootstrap_predict.py

from typing import List
import numpy as np
from sklearn.base import BaseEstimator

def bootstrap_contour_predict(bootstrapped_models: List[BaseEstimator], xx: np.array, yy: np.array) -> np.ndarray:
    """
    Makes a prediction for len(xx) * len(yy) data points - a mesh grid
    :param bootstrapped_models: a list of fitted sklearn estimators
    :param xx: Numpy array of values from 1st dimension mesh axis
    :param yy: Numpy array of values from 2nd dimension mesh axis
    :return: 2D Numpy array of predicted values for mesh grid
    """
    Z = np.zeros(xx.shape)
    for model in bootstrapped_models:
        Z += model.predict(np.c_[xx.ravel(), yy.ravel()]).reshape(xx.shape)
    # average and then round to nearest whole number
    return np.around(Z / (len(bootstrapped_models) * 1.0))