qiskit.optimization.applications.ising.common

get_gset_result(x)

Get graph solution in Gset format from binary string.

Parameters

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

Returns

graph solution in Gset format.

Return type

Dict[int, int]

parse_gset_format(filename)

Read graph in Gset format from file.

Parameters

filename (str) – name of the file.

Returns

adjacency matrix as a 2D numpy array.

Return type

numpy.ndarray

random_graph(n, weight_range=10, edge_prob=0.3, negative_weight=True, savefile=None, seed=None)

Generate random Erdos-Renyi graph.

Parameters

• n (int) – number of nodes.
• weight_range (int) – weights will be smaller than this value, in absolute value. range: [1, weight_range).
• edge_prob (float) – probability of edge appearing.
• negative_weight (bool) – allow to have edge with negative weights
• savefile (str or None) – name of file where to save graph.
• seed (int or None) – random seed - if None, will not initialize.

Returns

adjacency matrix (with weights).

Return type

numpy.ndarray

random_number_list(n, weight_range=100, savefile=None, seed=None)

Generate a set of positive integers within the given range.

Parameters

• n (int) – size of the set of numbers.
• weight_range (int) – maximum absolute value of the numbers.
• savefile (str or None) – write numbers to this file.
• seed (Union(int,None)) – random seed - if None, will not initialize.

Returns

the list of integer numbers.

Return type

numpy.ndarray

read_numbers_from_file(filename)

Read numbers from a file

Parameters

filename (str) – name of the file.

Returns

list of numbers as a numpy.ndarray.

Return type

numpy.ndarray

sample_most_likely(state_vector)

Compute the most likely binary string from state vector. :param state_vector: state vector or counts. :type state_vector: numpy.ndarray or dict

Returns

binary string as numpy.ndarray of ints.

Return type

numpy.ndarray