Source code for ribs.emitters.operators._gaussian

"""Gaussian Operator"""
import numpy as np

from ribs.emitters.operators._operator_base import OperatorBase

[docs]class GaussianOperator(OperatorBase): """Adds Gaussian noise to solutions. Args: sigma (float or array-like): Standard deviation of the Gaussian distribution. Note we assume the Gaussian is diagonal, so if this argument is an array, it must be 1D. lower_bounds (array-like): Upper bounds of the solution space. Passed in by emitter upper_bounds (array-like): Upper bounds of the solution space. Passed in by emitter seed (int): Value to seed the random number generator. Set to None to avoid a fixed seed. """ def __init__(self, sigma, lower_bounds, upper_bounds, seed=None): self._sigma = sigma self._lower_bounds = lower_bounds self._upper_bounds = upper_bounds self._rng = np.random.default_rng(seed) @property def parent_type(self): """int: Parent Type to be used by selector.""" return 1
[docs] def ask(self, parents): """Adds Gaussian noise to parents. Args: parents (array-like): (batch_size, solution_dim) array of solutions to be mutated. Returns: numpy.ndarray: ``(batch_size, solution_dim)`` array that contains ``batch_size`` mutated solutions. """ parents = np.asarray(parents) noise = self._rng.normal( scale=self._sigma, size=(parents.shape[0], parents.shape[1]), ).astype(parents.dtype) return np.clip(parents + noise, self._lower_bounds, self._upper_bounds)