from typing import Tuple
import numpy as np
from desdeo_tools.utilities import dominates
from numba import njit
@njit()
[docs]def check_domination(
new: np.ndarray, archive: np.ndarray
) -> Tuple[np.ndarray, np.ndarray]:
"""Checks if newly evaluated and archived solutions are non_dominated.
Args:
new (np.ndarray): Newly evaluated solution's fitness values
(should be a 2D array).
archive (np.ndarray): Archive of non-dominated solutions
(also a 2D array, must be mutually non-dominated).
Raises:
ValueError: If the new array is not a 2D array.
Returns:
Tuple[np.ndarray, np.ndarray]: Two arrays of indices that are
non-dominated in the new and archive arrays respectively.
"""
if new.ndim != 2:
raise ValueError("New array should have 2 dimensions.")
non_dominated_in_new = np.ones(len(new), dtype=np.bool_)
non_dominated_in_archive = np.ones(len(archive), dtype=np.bool_)
for i in range(len(new)):
for j in range(len(archive)):
if not non_dominated_in_archive[j]:
continue
if dominates(archive[j], new[i]):
non_dominated_in_new[i] = False
break # No need to check with the rest of the archive
if dominates(new[i], archive[j]):
non_dominated_in_archive[j] = False
return (non_dominated_in_new, non_dominated_in_archive)
