# Clique#

class Clique(graph, size=None)[fuente]#

Optimization application for the «clique»  problem based on a NetworkX graph.

Referencias

: «Clique (graph theory)», https://en.wikipedia.org/wiki/Clique_(graph_theory)

Parámetros:
• graph (Graph | ndarray | List) – A graph representing a problem. It can be specified directly as a NetworkX graph, or as an array or list format suitable to build out a NetworkX graph.

• size (int | None) – The size of the clique. When it’s None, the default, this class makes an optimization model for a maximal clique instead of the specified size of a clique.

Attributes

graph#

Getter of the graph

Devuelve:

A graph for a problem

size#

Getter of size

Devuelve:

The size of the clique, None when maximal clique

Methods

draw(result=None, pos=None)#

Draw a graph with the result. When the result is None, draw an original graph without colors.

Parámetros:
interpret(result)[fuente]#

Interpret a result as a list of node indices

Parámetros:

result (OptimizationResult | ndarray) – The calculated result of the problem

Devuelve:

The list of node indices whose corresponding variable is 1

Tipo del valor devuelto:

List[int]

static sample_most_likely(state_vector)#

Compute the most likely binary string from state vector.

Parámetros:

state_vector (QuasiDistribution | Statevector | ndarray | Dict) – state vector or counts or quasi-probabilities.

Devuelve:

binary string as numpy.ndarray of ints.

Muestra:

ValueError – if state_vector is not QuasiDistribution, Statevector, np.ndarray, or dict.

Tipo del valor devuelto:

ndarray

Convert a clique problem instance into a `QuadraticProgram`. When «size» is None, this makes an optimization model for a maximal clique instead of the specified size of a clique.
The `QuadraticProgram` created from the clique problem instance.