Maxcut#

class Maxcut(graph)[source]#

Optimization application for the "max-cut" [1] problem based on a NetworkX graph.

References

[1]: "Maximum cut", https://en.wikipedia.org/wiki/Maximum_cut

প্যারামিটার:

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.

Attributes

graph#

Getter of the graph

রিটার্নস:

A graph for a problem

Methods

draw(result=None, pos=None)#

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

প্যারামিটার:
static get_gset_result(x)[source]#

Get graph solution in Gset format from binary string.

প্যারামিটার:

x (ndarray) -- binary string as numpy array.

রিটার্নস:

A graph solution in Gset format.

রিটার্ন টাইপ:

Dict[int, int]

interpret(result)[source]#

Interpret a result as two lists of node indices

প্যারামিটার:

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

রিটার্নস:

Two lists of node indices correspond to two node sets for the Max-cut

রিটার্ন টাইপ:

List[List[int]]

static parse_gset_format(filename)[source]#

Read graph in Gset format from file.

প্যারামিটার:

filename (str) -- the name of the file.

রিটার্নস:

An adjacency matrix as a 2D numpy array.

রিটার্ন টাইপ:

ndarray

static sample_most_likely(state_vector)#

Compute the most likely binary string from state vector.

প্যারামিটার:

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

রিটার্নস:

binary string as numpy.ndarray of ints.

রেইজেস:

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

রিটার্ন টাইপ:

ndarray

Convert a Max-cut problem instance into a `QuadraticProgram`
The `QuadraticProgram` created from the Max-cut problem instance.