# quality: gold
import logging
import warnings
from typing import List
from immuneML.environment.Label import Label
from immuneML.util.ParameterValidator import ParameterValidator
[docs]
class LabelConfiguration:
"""
Class that encapsulates labels and transformers for the labels.
Supports two types of labels: CLASSIFICATION and REGRESSION (as defined in LabelType class)
"""
def __init__(self, labels: list = None):
assert labels is None or all(isinstance(label, Label) for label in labels), \
"LabelConfiguration: all labels should be instances of Label class."
self._labels = {label.name: label for label in labels} if labels is not None else {}
[docs]
def add_label(self, label_name: str, values: list = None, auxiliary_labels: list = None, positive_class=None):
vals = list(values) if values else None
if label_name in self._labels and self._labels[label_name] is not None and len(self._labels[label_name]) > 0:
warnings.warn("Label " + label_name + " has already been set. Overriding existing values...", Warning)
if positive_class is not None:
if all(isinstance(val, str) for val in vals) and not isinstance(positive_class, str):
positive_class = str(positive_class)
ParameterValidator.assert_in_valid_list(positive_class, vals, Label.__name__, 'positive_class')
else:
positive_class = self._get_default_positive_class(vals)
logging.info(f"LabelConfiguration: No positive label class was set. "
f"Setting default positive class '{positive_class}' for label {label_name}")
self._labels[label_name] = Label(label_name, vals, auxiliary_labels, positive_class)
def _get_default_positive_class(self, classes):
"""Returns the default positive class when a class pair is given where the positive class is obvious (0, 1; true, false)"""
if len(classes) != 2:
return None
if classes[0] == True and classes[1] == False:
return classes[0]
if classes[1] == True and classes[0] == False:
return classes[1]
for positive_str, negative_str in [("1", "0"), ("true", "false"), ("positive", "negative"), ("+", "-")]:
if set(classes) == {positive_str, negative_str}:
return positive_str
if set(classes) == {positive_str.upper(), negative_str.upper()}:
return positive_str.upper()
if set(classes) == {positive_str.title(), negative_str.title()}:
return positive_str.title()
return sorted(classes)[0]
[docs]
def get_labels_by_name(self):
return sorted(list(self._labels.keys()))
[docs]
def get_label_values(self, label_name: str):
assert label_name in self._labels, label_name + " is not in the list of labels, so there is no information on the values."
return self._labels[label_name].values
[docs]
def get_label_count(self):
return len(self._labels.keys())
[docs]
def get_auxiliary_labels(self, label_name: str):
return self._labels[label_name].auxiliary_label_names
[docs]
def get_label_object(self, label_name: str) -> Label:
return self._labels[label_name]
[docs]
def get_label_objects(self) -> List[Label]:
return list(self._labels.values())