def __init__(self, x_table, q_table, objects, attributes):
"""
Create a partial context from cross and question tables
and list of objects, list of attributes.
cross_table_x - the list of bool lists representing first context
(only x in context)
cross_table_q - the list of bool lists representing second context
(only questions(q) in context)
cross_table_x \subseteq cross_table_q
objects - the list of objects
attributes - the list of attributes
"""
if not subseteq_table(x_table, q_table):
raise ValueError('x table should be \subseteq q table')
else:
self.objects = copy(objects)
self.attributes = copy(attributes)
self.x_context = Context(x_table, objects[:], self.attributes[:])
self.q_context = Context(q_table, objects[:], self.attributes[:])
if indexes:
if mode == "part":
ret = _filter_part(lattice, indexes, opt)
elif mode == "abs":
ret = _filter_abs(lattice, indexes, opt)
elif mode == "value":
ret = _filter_value(lattice, indexes, opt)
return ret
if __name__ == '__main__':
# Test code
from fca import ConceptLattice, Context
from .probability import compute_probability
from .stability import (compute_estability, compute_istability)
from .separation import compute_separation_index
ct = [[True, False, False, True], [True, False, True, False],
[False, True, True, False], [False, True, True, True]]
objs = ['1', '2', '3', '4']
attrs = ['a', 'b', 'c', 'd']
c = Context(ct, objs, attrs)
cl = ConceptLattice(c)
# compute_index(cl, compute_probability, "Probability")
# cs = filter_concepts(cl, compute_probability, "abs", 4)
# compute_index(cl, compute_separation_index, "Separation")
# cs = filter_concepts(cl, compute_probability, "value", 0.5)
# compute_index(cl, compute_istability, "Intensional Stability")
# print cl
cs = filter_concepts(cl, compute_istability, "abs", 2)
print(cs)
