from dataclasses import dataclass
from pathlib import Path
from immuneML.data_model.receptor.ChainPair import ChainPair
from immuneML.data_model.receptor.RegionType import RegionType
[docs]
@dataclass
class DatasetImportParams:
path: Path = None
is_repertoire: bool = None
metadata_file: Path = None
paired: bool = None
receptor_chains: ChainPair = None
result_path: Path = None
columns_to_load: list = None
separator: str = None
column_mapping: dict = None
column_mapping_synonyms: dict = None
region_type: RegionType = None
import_productive: bool = None
import_unproductive: bool = None
import_with_stop_codon: bool = None
import_out_of_frame: bool = None
import_illegal_characters: bool = None
metadata_column_mapping: dict = None
number_of_processes: int = 1
sequence_file_size: int = 50000
organism: str = None
import_empty_nt_sequences: bool = None
import_empty_aa_sequences: bool = None
[docs]
@classmethod
def build_object(cls, path: Path = None, metadata_file: Path = None, result_path: Path = None, region_type: str = None, receptor_chains: str = None, **kwargs):
params = {
"path": Path(path) if path is not None else None,
"metadata_file": Path(metadata_file) if metadata_file is not None else None,
"result_path": Path(result_path) if result_path is not None else None,
"region_type": RegionType[region_type.upper()] if region_type else None,
"receptor_chains": ChainPair[receptor_chains.upper()] if receptor_chains else None,
}
params = {**kwargs, **params}
return DatasetImportParams(**params)