ce5dbf57781e10fd0e0367008a76f91521b59651,moabb/evaluations/base.py,BaseEvaluation,__init__,#BaseEvaluation#,15

Before Change

        Init.
        
        if random_state is None:
            self.random_state = np.random.randint(0, 1000, 1)[0]
        self.n_jobs = n_jobs

    @abstractmethod
    def evaluate(self, dataset, subject, clf, paradigm):

After Change

        self.n_jobs = n_jobs

        // check paradigm
        if not isinstance(paradigm, BaseParadigm):
            raise(ValueError("paradigm must be an Paradigm instance"))
        self.paradigm = paradigm

        // if no dataset provided, then we get the list from the paradigm
        if datasets is None:
            datasets = self.paradigm.datasets

        if not isinstance(datasets, list):
            if isinstance(datasets, BaseDataset):
                datasets = [datasets]
            else:
                raise(ValueError("datasets must be a list or a dataset "
                                 "instance"))

        for dataset in datasets:
            if not(isinstance(dataset, BaseDataset)):
                raise(ValueError("datasets must only contains dataset "
                                 "instance"))

        for dataset in datasets:
            self.paradigm.verify(dataset)

        self.datasets = datasets

    def process(self, pipelines, overwrite=False, suffix=""):
        """
        Runs tasks on all given datasets.

Instances