(self, datasets: list, detectors: callable, output_dir: {str} = None, seed: int = None,
                 create_log_file=True)
:param datasets: list of datasets
        :param detectors: callable that returns list of detectors
:param datasets: list of datasets
        :param detectors: callable that returns list of detectors
: param datasets : list of datasets : param detectors : callable that returns list of detectors
def __init__(self, datasets: list, detectors: callable, output_dir: {str} = None, seed: int = None,
                 create_log_file=True):
        """
        :param datasets: list of datasets
        :param detectors: callable that returns list of detectors
        """
        assert np.unique([x.name for x in datasets]).size == len(datasets), 'Some datasets have the same name!'
        self.datasets = datasets
        self._detectors = detectors
        self.output_dir = output_dir or 'reports'
        self.results = dict()
        if create_log_file:
            init_logging(os.path.join(self.output_dir, 'logs'))
        self.logger = logging.getLogger(__name__)
        # Dirty hack: Is set by the main.py to insert results from multiple evaluator runs
        self.benchmark_results = None
        # Last passed seed value in evaluate()
        self.seed = seed
def __init__ ( self , datasets : list , detectors : callable , output_dir : { str } = None , seed : int = None , create_log_file = True ) : assert np . unique ( [ x . name for x in datasets ] ) . size == len ( datasets ) , 'Some datasets have the same name!' self . datasets = datasets self . _detectors = detectors self . output_dir = output_dir or 'reports' self . results = dict ( ) if create_log_file : init_logging ( os . path . join ( self . output_dir , 'logs' ) ) self . logger = logging . getLogger ( __name__ ) # Dirty hack: Is set by the main.py to insert results from multiple evaluator runs self . benchmark_results = None # Last passed seed value in evaluate() self . seed = seed