| import numpy as np | |
| from ..base import Base | |
| class Random(Base): | |
| """ | |
| Class to randomly interpolate by picking values between maximum and | |
| minimum measurements. | |
| Note: Even if a point on the requested grid is present in | |
| the training set, we return a random value for it. | |
| """ | |
| def __init__(self, resolution="standard", coordinate_type="Euclidean"): | |
| super().__init__(resolution, coordinate_type) | |
| def _fit(self, X, y): | |
| """Function for fitting random interpolation. | |
| This function is not supposed to be called directly. | |
| """ | |
| self.ymax = max(y) | |
| self.ymin = min(y) | |
| return self | |
| def _predict_grid(self, x1lim, x2lim): | |
| """Function for random grid interpolation. | |
| This function is not supposed to be called directly. | |
| """ | |
| return np.random.uniform( | |
| low=self.ymin, | |
| high=self.ymax, | |
| size=(self.resolution, self.resolution), | |
| ) | |
| def _predict(self, X): | |
| """Function for random interpolation. | |
| This function is not supposed to be called directly. | |
| """ | |
| return np.random.uniform( | |
| low=self.ymin, high=self.ymax, size=(X.shape[0]) | |
| ) | |