Source code for immuneML.preprocessing.Preprocessor

import abc
from pathlib import Path

from immuneML.data_model.dataset.RepertoireDataset import RepertoireDataset

[docs]class Preprocessor(metaclass=abc.ABCMeta): def __init__(self, result_path: Path = None): self.result_path = result_path
[docs] @abc.abstractmethod def process_dataset(self, dataset: RepertoireDataset, result_path: Path) -> RepertoireDataset: pass
[docs] def check_dataset_type(self, dataset, valid_dataset_types: list, location: str): assert type(dataset) in valid_dataset_types, f"{location}: this preprocessing can only be applied to datasets of type: " \ f"{', '.join([dataset_type.__name__ for dataset_type in valid_dataset_types])}. " \ f"Your dataset is a {type(dataset).__name__}. " \ f"Please use a different preprocessing, or omit the preprocessing for this dataset."
[docs] def keeps_example_count(self) -> bool: """ Defines if the preprocessing can be run with TrainMLModel instruction; to be able to run with it, the preprocessing cannot change the number of examples in the dataset """ return True