# -*- coding: utf-8 -*-
# Contributors:
# Antonio López Martínez-Carrasco <antoniolopezmc1995@gmail.com>
"""This file contains the implementation of the Sensitivity quality measure. This quality measure is also called as Recall or True Positive Rate.
"""
from subgroups.quality_measures.quality_measure import QualityMeasure
from subgroups.exceptions import SubgroupParameterNotFoundError
# Python annotations.
from typing import Union
[docs]
class Sensitivity(QualityMeasure):
"""This class defines the Sensitivity quality measure. This quality measure is also called as Recall or True Positive Rate.
"""
_singleton = None
__slots__ = ()
def __new__(cls) -> 'Sensitivity':
if Sensitivity._singleton is None:
Sensitivity._singleton = object().__new__(cls)
return Sensitivity._singleton
[docs]
def compute(self, dict_of_parameters : dict[str, Union[int, float]]) -> float:
"""Method to compute the Sensitivity quality measure (you can also call to the instance for this purpose).
:param dict_of_parameters: python dictionary which contains all the necessary parameters used to compute this quality measure.
:return: the computed value for the Sensitivity quality measure.
"""
if type(dict_of_parameters) is not dict:
raise TypeError("The type of the parameter 'dict_of_parameters' must be 'dict'.")
if (QualityMeasure.TRUE_POSITIVES not in dict_of_parameters):
raise SubgroupParameterNotFoundError("The subgroup parameter 'tp' is not in 'dict_of_parameters'.")
if (QualityMeasure.TRUE_POPULATION not in dict_of_parameters):
raise SubgroupParameterNotFoundError("The subgroup parameter 'TP' is not in 'dict_of_parameters'.")
tp = dict_of_parameters[QualityMeasure.TRUE_POSITIVES]
TP = dict_of_parameters[QualityMeasure.TRUE_POPULATION]
return tp / TP # tp / (tp + fn)
[docs]
def get_name(self) -> str:
"""Method to get the quality measure name (equal to the class name).
"""
return "Sensitivity"
[docs]
def optimistic_estimate_of(self) -> dict[str, QualityMeasure]:
"""Method to get a python dictionary with the quality measures of which this one is an optimistic estimate.
:return: a python dictionary in which the keys are the quality measure names and the values are the instances of those quality measures.
"""
return dict()
def __call__(self, dict_of_parameters : dict[str, Union[int, float]]) -> float:
"""Compute the Sensitivity quality measure.
:param dict_of_parameters: python dictionary which contains all the needed parameters with which to compute this quality measure.
:return: the computed value for the Sensitivity quality measure.
"""
return self.compute(dict_of_parameters)