# Source code for macop.operators.crossovers.RandomSplitCrossover

    """Crossover implementation which generated new solution by randomly splitting best solution and current solution
    """
    # main imports
    import random
    import sys
    import pkgutil

    # module imports
    from .Crossover import Crossover
    from ...utils.modules import load_class

    class RandomSplitCrossover(Crossover):
        """Crossover implementation which generated new solution by randomly splitting best solution and current solution

        Attributes:
            kind: {KindOperator} -- specify the kind of operator
        """
        def apply(self, _solution):
            """Create new solution based on best solution found and solution passed as parameter

            Args:
                _solution: {Solution} -- the solution to use for generating new solution

            Returns:
                {Solution} -- new generated solution
            """
            size = _solution.size

            # copy data of solution
            firstData = _solution.data.copy()
            # get best solution from current algorithm
            secondData = self.algo.bestSolution.data.copy()

            splitIndex = random.randint(0, len(secondData))

            if random.uniform(0, 1) > 0.5:
                firstData[splitIndex:(size - 1)] = firstData[splitIndex:(size - 1)]
                currentData = firstData
            else:
                secondData[splitIndex:(size - 1)] = firstData[splitIndex:(size -
                                                                          1)]
                currentData = secondData

            # create solution of same kind with new data
            class_name = type(_solution).__name__

            # dynamically load solution class if unknown
            if class_name not in sys.modules:
                load_class(class_name, globals())

            return getattr(globals()['macop.solutions.' + class_name],
                           class_name)(currentData, size)