Welcome to fca_algorithms’s documentation!

FCA algorithms

This is a module providing a set of commonly used algorithms in FCA, RCA, and some of its variants. Its general intention is to provide an easy to use API so that it’s easier to create other programs using these algorithms. Since it’s built with python, the overall performance is not expected to be outstanding. Having that said, the chosen algorithms have a somewhat low algorithmic temporal complexity.

CLI

FCA

Plot a hasse diagram from a context

$ fca_cli -c input.csv --show_hasse

The context is expected to be a csv with the following format

name

attr1

attr2

o1

x

o2

x

o3

x

x

o4

Output files

$ fca_cli -c input.csv --show_hasse --output_dir path/to/folder/

Will create two files, one representing the hasse graph, the other one with a concept for each line. The line is the index in the hasse graph.

RCA

To plot the hasse diagrams of the contexts 1 and 2 after applying RCA with exists

$ fca_cli -k context_1.csv context_2.csv -r relation_1_2.csv relation_2_1.csv --show_hasse

to specify operator

$ fca_cli -k context_1.csv context_2.csv -r relation_1_2.csv relation_2_1.csv --show_hasse -o forall

FCA utils

Module for FCA basics such as retrieving concepts, drawing a hasse diagram, etc

Getting formal concepts

In batch

from fca.api_models import Context

c = Context(O, A, I)
concepts = c.get_concepts(c)

Incrementally

  • By intent

from fca.api_models import IncLattice

l = IncLattice(attributes=['a', 'b', 'c', 'd'])
l.add_intent('o1', [0, 2])  # numbers are the indices of the attributes
l.add_intent('o2', [1, 2])

  • By pair

from fca.api_models import IncLattice

l = IncLattice()
l.add_pair('o1', 'a')
l.add_pair('o2', 'b')
l.add_pair('o2', 'a')

Getting association rules

from fca.api_models import Context

c = Context(O, A, I)
c.get_association_rules(min_support=0.4, min_confidence=1)

Drawing hasse diagram

from fca.plot.plot import plot_from_hasse
from fca.api_models import Context


k = Context(O, A, I)
k.get_lattice().plot()
# plot receives a number of kwargs such as print_latex=True|False


l = IncLattice(attributes=['a', 'b', 'c', 'd'])
l.add_intent('o1', [0, 2])  # numbers are the indices of the attributes
l.add_intent('o2', [1, 2])
.
.
.
l.plot()

Contributors

  • Ramshell (Nicolas Leutwyler)

Contents:

Indices and tables