# probabilisticSetCoverConditionalGain.py
# Author: Vishal Kaushal <vishal.kaushal@gmail.com>
from .setFunction import SetFunction
from submodlib_cpp import ProbabilisticSetCoverConditionalGain
[docs]class ProbabilisticSetCoverConditionalGainFunction(SetFunction):
"""Implementation of the Probabilistic Set Cover Conditional Gain (PSCCG) function.
Given a :ref:`functions.conditional-gain` function, Probabilistic Set Cover Conditional Gain function is its instantiation using a :class:`~submodlib.functions.probabilisticSetCover.ProbabilisticSetCoverFunction`. Mathematically, it takes the following form:
.. math::
f(A | P) = \\sum\\limits_{u \\in \\mathcal{U}} w_u\\bar{P_u}(A)P_u(P)
Parameters
----------
n : int
Number of elements in the ground set. Must be > 0.
num_concepts : int
Number of concepts.
probs : list
List of probability vectors for each data point / image, each probability vector containing the probabilities with which that data point / image covers each concept. Hence each list is num_concepts dimensional and probs contains n such lists.
private_concepts : set
Set of private concepts. That is, the concepts which should not be covered in the optimal subset.
concept_weights : list
Weight :math:`w_i` of each concept. Size must be same as num_concepts.
"""
def __init__(self, n, num_concepts, probs, private_concepts, concept_weights=None):
self.n = n
self.num_concepts = num_concepts
self.probs = probs
self.private_concepts = private_concepts
self.concept_weights = concept_weights
self.cpp_obj = None
if self.n <= 0:
raise Exception("ERROR: Number of elements in ground set must be positive")
if self.n != len(self.probs):
raise Exception("ERROR: Mismtach between n and len(probs)")
if self.num_concepts != len(self.probs[0]):
raise Exception("ERROR: Mismtach between num_concepts and len(probs[0])")
if (type(self.concept_weights) != type(None)):
if self.num_concepts != len(self.concept_weights):
raise Exception("ERROR: Mismtach between num_conepts and len(concept_weights)")
else:
self.concept_weights = [1] * self.num_concepts
self.cpp_obj = ProbabilisticSetCoverConditionalGain(self.n, self.num_concepts, self.probs, self.concept_weights, self.private_concepts)
self.effective_ground = set(range(n))