Config

Config related classes and methods. Contains the global config object.

AdvancedConfig dataclass

Advanced config options for XLRanker.

Attributes:

Name	Type	Description
intra_in_training	bool	Default to False. If True, intra pairs are included in the positive set for model training. # TODO: May remove this option in future versions

Source code in src/xlranker/config.py

@dataclass
class AdvancedConfig:
    """Advanced config options for XLRanker.

    Attributes:
        intra_in_training (bool): Default to False. If True, intra pairs are included in the positive set for model training. # TODO: May remove this option in future versions

    """

    intra_in_training: bool = False  # allow intra in training data

Config dataclass

Config for XLRanker.

Attributes:

Name	Type	Description
fragile	bool	Default to False. If True, throw error on any warning
detailed	bool	Default to False. If True, perform more analysis about dataset
reduce_fasta	bool	Default to True. If True, when a gene has multiple sequences, only accept longest sequence as the canonical sequence.
human_only	bool	True if all data is human only.
output	str	Default to "xlranker_output/". Directory where output files are saved.
additional_null_values	list[str]	Default to []. Additional null values to consider when reading data files.
advanced	AdvancedConfig	Advanced configuration options
primary_column	str | None	Column name of which omic file should be the representative. If None, default to the first file alphabetically.
mapping	MappingConfig	Configuration related to peptide sequence mapping.

Source code in src/xlranker/config.py

@dataclass
class Config:
    """Config for XLRanker.

    Attributes:
        fragile (bool): Default to False. If True, throw error on any warning
        detailed (bool): Default to False. If True, perform more analysis about dataset
        reduce_fasta (bool): Default to True. If True, when a gene has multiple sequences, only accept longest sequence as the canonical sequence.
        human_only (bool): True if all data is human only.
        output (str): Default to "xlranker_output/". Directory where output files are saved.
        additional_null_values (list[str]): Default to []. Additional null values to consider when reading data files.
        advanced (AdvancedConfig): Advanced configuration options
        primary_column (str | None): Column name of which omic file should be the representative. If None, default to the first file alphabetically.
        mapping (MappingConfig): Configuration related to peptide sequence mapping.

    """

    fragile: bool = False  # Break on any warning
    detailed: bool = False  # Show more detailed information about dataset and analysis
    reduce_fasta: bool = False  # Reduce FASTA file by only keeping the largest sequence
    human_only: bool = True  # Is all data human only?
    output: str = "xlranker_output/"  # output directory
    primary_column: str | None = (
        None  # Which omic file should be the representative omic set for ordering
    )
    additional_null_values: list[str] = field(
        default_factory=list
    )  # additional null values to consider when reading data files
    advanced: AdvancedConfig = field(
        default_factory=AdvancedConfig
    )  # advanced config options
    mapping: MappingConfig = field(default_factory=MappingConfig)

MappingConfig dataclass

Mapping configuration object.

Attributes:

Name	Type	Description
reduce_fasta	bool	If True, only keep longest sequence for duplicated protein entries
custom_table	str | None	Path to custom table for peptide mapping. If None use default FASTA file.
is_fasta	bool	True if custom table is in FASTA format
split_by	str | None	string to split FASTA file for gene symbol extraction
split_index	int | None	0-based index of section containing gene symbol after string splitting
fasta_type	str | None	UNIPROT or GENCODE fasta type. If None, will default to UNIPROT

Source code in src/xlranker/config.py

@dataclass
class MappingConfig:
    """Mapping configuration object.

    Attributes:
        reduce_fasta (bool): If True, only keep longest sequence for duplicated protein entries
        custom_table (str | None): Path to custom table for peptide mapping. If None use default FASTA file.
        is_fasta (bool): True if custom table is in FASTA format
        split_by (str | None): string to split FASTA file for gene symbol extraction
        split_index (int | None): 0-based index of section containing gene symbol after string splitting
        fasta_type (str | None): UNIPROT or GENCODE fasta type. If None, will default to UNIPROT

    """

    reduce_fasta: bool = False  # Reduce FASTA file by only keeping the largest sequence
    custom_table: str | None = None
    is_fasta: bool = True
    split_by: str | None = None
    split_index: int | None = None
    fasta_type: str | None = "UNIPROT"

config_to_dict(config_obj)

Convert Config object to a dictionary.

Parameters:

Name	Type	Description	Default
config_obj	config	config to convert to dictionary like object.	required

Returns:

Type	Description
dict[str, Any] | list[dict[str, Any]]	dict[str, Any] | list[dict[str, Any]]: JSON/YAML serializable object representing the input config

Source code in src/xlranker/config.py

def config_to_dict(config_obj: Config) -> dict[str, Any] | list[dict[str, Any]]:
    """Convert Config object to a dictionary.

    Args:
        config_obj (config): config to convert to dictionary like object.

    Returns:
        dict[str, Any] | list[dict[str, Any]]: JSON/YAML serializable object representing the input config

    """

    def dataclass_to_dict(obj) -> dict[str, Any] | list[dict[str, Any]]:
        if hasattr(obj, "__dataclass_fields__"):
            result = {}
            for field_name in obj.__dataclass_fields__:
                value = getattr(obj, field_name)
                result[field_name] = dataclass_to_dict(value)
            return result
        elif isinstance(obj, list):
            return [dataclass_to_dict(item) for item in obj]
        else:
            return obj

    return dataclass_to_dict(config_obj)

load_from_json(json_file)

Set config to settings in JSON file.

Parameters:

Name	Type	Description	Default
json_file	str	path to JSON file	required

Source code in src/xlranker/config.py

def load_from_json(json_file: str) -> None:
    """Set config to settings in JSON file.

    Args:
        json_file (str): path to JSON file

    """
    with open(json_file) as r:
        json_obj = json.load(r)
    set_config_from_dict(json_obj)

set_config_from_dict(config_dict)

Set config from a dict object.

Parameters:

Name	Type	Description	Default
config_dict	dict[str, Any]	dictionary with config settings	required

Source code in src/xlranker/config.py

def set_config_from_dict(config_dict: dict[str, Any]) -> None:
    """Set config from a dict object.

    Args:
        config_dict (dict[str, Any]): dictionary with config settings

    """
    for key in config_dict:
        if key == "advanced":
            for sub_key in config_dict[key]:
                setattr(config.advanced, sub_key, config_dict[key][sub_key])
        elif key == "mapping":
            for sub_key in config_dict[key]:
                setattr(config.mapping, sub_key, config_dict[key][sub_key])
        else:
            setattr(config, key, config_dict[key])