def setUp(self):
"""
Setup internal variables and a fake simulation. Aer is used to get the
structure of the qiskit.Result. The IQ data is generated using gaussian
random number generators.
"""
self.shots = 52
self.qubits = [0, 1]
meas_cal, _ = circuits.tensored_meas_cal([[0], [1]])
backend = Aer.get_backend('qasm_simulator')
job = qiskit.execute(meas_cal,
backend=backend,
shots=self.shots,
meas_level=1)
self.cal_results = job.result()
i0, q0, i1, q1 = 0., -1., 0., 1.
ground = utils.create_shots(i0, q0, 0.1, 0.1, self.shots, self.qubits)
excited = utils.create_shots(i1, q1, 0.1, 0.1, self.shots, self.qubits)
self.cal_results.results[0].meas_level = 1
self.cal_results.results[1].meas_level = 1
self.cal_results.results[0].data = ExperimentResultData(memory=ground)
self.cal_results.results[1].data = ExperimentResultData(memory=excited)
def test_apply(self):
"""
Set-up a discriminator based on simulated data, train it and then
discriminate the calibration data.
"""
meas_cal, _ = circuits.tensored_meas_cal([[0], [1]])
backend = Aer.get_backend('qasm_simulator')
job = qiskit.execute(meas_cal,
backend=backend,
shots=self.shots,
meas_level=1)
cal_results = job.result()
i0, q0, i1, q1 = 0., -1., 0., 1.
ground = utils.create_shots(i0, q0, 0.1, 0.1, self.shots, self.qubits)
excited = utils.create_shots(i1, q1, 0.1, 0.1, self.shots, self.qubits)
cal_results.results[0].meas_level = 1
cal_results.results[1].meas_level = 1
cal_results.results[0].data = ExperimentResultData(memory=ground)
cal_results.results[1].data = ExperimentResultData(memory=excited)
discriminator = LinearIQDiscriminator(cal_results, self.qubits,
['00', '11'])
d_filter = DiscriminationFilter(discriminator)
self.assertEqual(cal_results.results[0].meas_level, 1)
new_results = d_filter.apply(cal_results)
self.assertEqual(new_results.results[0].meas_level, 2)
counts_00 = new_results.results[0].data.counts.to_dict()['0x0']
counts_11 = new_results.results[1].data.counts.to_dict()['0x3']
self.assertEqual(counts_00, self.shots)
self.assertEqual(counts_11, self.shots)