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Adjust test_samples_qaoa for Terra#6828 #218

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Merged
mergify merged 3 commits into from
Oct 8, 2021
Merged

Adjust test_samples_qaoa for Terra#6828 #218

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52fb12c
adjust a unit test for terra#6828
t-imamichi Jul 30, 2021
cafe6c9
Merge branch 'main' into terra-pr6828
t-imamichi Oct 7, 2021
2fd0c73
remove tests of number of samples
t-imamichi Oct 7, 2021
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21 changes: 7 additions & 14 deletions test/algorithms/test_min_eigen_optimizer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -21,7 +21,6 @@

import numpy as np
from ddt import data, ddt
from docplex.mp.model import Model
from qiskit import BasicAer
from qiskit.algorithms import QAOA, VQE, NumPyMinimumEigensolver
from qiskit.algorithms.optimizers import COBYLA, SPSA
Expand All @@ -45,7 +44,6 @@
)
from qiskit_optimization.problems import QuadraticProgram
from qiskit_optimization.runtime import VQEProgram, QAOAProgram
from qiskit_optimization.translators import from_docplex_mp


@ddt
Expand Down Expand Up @@ -90,11 +88,10 @@ def setUp(self):
self.op_maximize.linear_constraint(linear={"x": 1, "y": 1}, sense="<=", rhs=1, name="xy")

# test bit ordering
mdl = Model("docplex model")
x = mdl.binary_var("x")
y = mdl.binary_var("y")
mdl.minimize(x - 2 * y)
self.op_ordering = from_docplex_mp(mdl)
self.op_ordering = QuadraticProgram("bit ordering")
self.op_ordering.binary_var("x")
self.op_ordering.binary_var("y")
self.op_ordering.minimize(linear={"x": 1, "y": -2})

@data(
("exact", None, "op_ip1.lp"),
Expand Down Expand Up @@ -251,13 +248,11 @@ def test_samples_qaoa(self, simulator):
# test minimize
algorithm_globals.random_seed = 4
quantum_instance = self.sv_simulator if simulator == "sv" else self.qasm_simulator
qaoa = QAOA(quantum_instance=quantum_instance, reps=2)
qaoa = QAOA(optimizer=COBYLA(), quantum_instance=quantum_instance, reps=2)
min_eigen_optimizer = MinimumEigenOptimizer(qaoa)
result = min_eigen_optimizer.solve(self.op_minimize)
success = OptimizationResultStatus.SUCCESS
opt_sol = 1
self.assertEqual(len(result.samples), 8)
self.assertEqual(len(result.raw_samples), 32)
self.assertAlmostEqual(sum(s.probability for s in result.samples), 1)
self.assertAlmostEqual(sum(s.probability for s in result.raw_samples), 1)
self.assertAlmostEqual(min(s.fval for s in result.samples), 0)
Expand All @@ -275,11 +270,9 @@ def test_samples_qaoa(self, simulator):
self.assertEqual(result.raw_samples[0].status, success)
# test maximize
opt_sol = 2
qaoa = QAOA(quantum_instance=quantum_instance, reps=2)
qaoa = QAOA(optimizer=COBYLA(), quantum_instance=quantum_instance, reps=2)
min_eigen_optimizer = MinimumEigenOptimizer(qaoa)
result = min_eigen_optimizer.solve(self.op_maximize)
self.assertEqual(len(result.samples), 8)
self.assertEqual(len(result.raw_samples), 16)
self.assertAlmostEqual(sum(s.probability for s in result.samples), 1)
self.assertAlmostEqual(sum(s.probability for s in result.raw_samples), 1)
self.assertAlmostEqual(max(s.fval for s in result.samples), 5)
Expand All @@ -305,7 +298,7 @@ def test_samples_qaoa(self, simulator):
self.assertEqual(result.raw_samples[0].status, success)
# test bit ordering
opt_sol = -2
qaoa = QAOA(quantum_instance=quantum_instance, reps=2)
qaoa = QAOA(optimizer=COBYLA(), quantum_instance=quantum_instance, reps=2)
min_eigen_optimizer = MinimumEigenOptimizer(qaoa)
result = min_eigen_optimizer.solve(self.op_ordering)
self.assertEqual(result.fval, opt_sol)
Expand Down