QAOABenchmark

class QAOABenchmark(benchmark_data, optimal_solution, cost_function)

This class is a wrapper for representing and evaluating the data collected in the .benchmark method.

Attributes:

layer_depthlist[int]

The amount of QAOA layers for each run.

circuit_depthlist[int]

The depth of the compiled circuit of each run.

qubit_amountlist[int]

The amount of qubits of the compiled circuit of each run.

shotslist[int]

The amount of shots per backend call of each run.

iterationslist[int]

The amount of backend calls of each run.

countslist[dict]

The measurement results of the optimized circuit of each run.

runtimelist[float]

The amount of time passed (in seconds) of each run.

optimal_solution-

The optimal solution of the problem.

cost_functioncallable

The classical cost function of the benchmarked problem.

Methods

QAOABenchmark.evaluate([cost_metric, ...])	Evaluates the data in terms of a cost and a gain metric.
QAOABenchmark.visualize([cost_metric, ...])	Plots the results of .evaluate.
QAOABenchmark.rank([metric, print_res, ...])	Ranks the runs of the benchmark according to a given metric.
QAOABenchmark.save(filename)	Saves the data to the harddrive for later use.
QAOABenchmark.load(filename)	Loads benchmark data from the harddrive that has been saved by .save.