def test_multiple_circuits_counts(self):
""""
Test that counts are returned either as a list or a single item.
Counts are returned as a list when multiple experiments are executed
and get_counts() is called with no arguments. In all the other cases
get_counts() returns a single item containing the counts for a
single experiment.
"""
raw_counts_1 = {'0x0': 5, '0x3': 12, '0x5': 9, '0xD': 6, '0xE': 2}
processed_counts_1 = {
'0000': 5,
'0011': 12,
'0101': 9,
'1101': 6,
'1110': 2
}
data_1 = models.ExperimentResultData(counts=dict(**raw_counts_1))
exp_result_header_1 = QobjExperimentHeader(creg_sizes=[['c0', 4]],
memory_slots=4)
exp_result_1 = models.ExperimentResult(shots=14,
success=True,
meas_level=2,
data=data_1,
header=exp_result_header_1)
raw_counts_2 = {'0x1': 0, '0x4': 3, '0x6': 6, '0xA': 1, '0xB': 2}
processed_counts_2 = {
'0001': 0,
'0100': 3,
'0110': 6,
'1010': 1,
'1011': 2
}
data_2 = models.ExperimentResultData(counts=dict(**raw_counts_2))
exp_result_header_2 = QobjExperimentHeader(creg_sizes=[['c0', 4]],
memory_slots=4)
exp_result_2 = models.ExperimentResult(shots=14,
success=True,
meas_level=2,
data=data_2,
header=exp_result_header_2)
raw_counts_3 = {'0xC': 27, '0xF': 20}
processed_counts_3 = {'1100': 27, '1111': 20}
data_3 = models.ExperimentResultData(counts=dict(**raw_counts_3))
exp_result_header_3 = QobjExperimentHeader(creg_sizes=[['c0', 4]],
memory_slots=4)
exp_result_3 = models.ExperimentResult(shots=14,
success=True,
meas_level=2,
data=data_3,
header=exp_result_header_3)
mult_result = Result(
results=[exp_result_1, exp_result_2, exp_result_3],
**self.base_result_args)
sing_result = Result(results=[exp_result_1], **self.base_result_args)
self.assertEqual(
mult_result.get_counts(),
[processed_counts_1, processed_counts_2, processed_counts_3])
self.assertEqual(sing_result.get_counts(), processed_counts_1)
def to_result(self):
return Result(backend_name=self.backend_name, backend_version=self.backend_version, qobj_id=self.qobj.qobj_id,
job_id=self.job_id, success=self.status is JobStatus.DONE, results=self.results)
def test_multiple_circuits_counts(self):
""" "
Test that counts are returned either as a list or a single item.
Counts are returned as a list when multiple experiments are executed
and get_counts() is called with no arguments. In all the other cases
get_counts() returns a single item containing the counts for a
single experiment.
"""
raw_counts_1 = {"0x0": 5, "0x3": 12, "0x5": 9, "0xD": 6, "0xE": 2}
processed_counts_1 = {
"0000": 5,
"0011": 12,
"0101": 9,
"1101": 6,
"1110": 2
}
data_1 = models.ExperimentResultData(counts=dict(**raw_counts_1))
exp_result_header_1 = QobjExperimentHeader(creg_sizes=[["c0", 4]],
memory_slots=4)
exp_result_1 = models.ExperimentResult(shots=14,
success=True,
meas_level=2,
data=data_1,
header=exp_result_header_1)
raw_counts_2 = {"0x1": 0, "0x4": 3, "0x6": 6, "0xA": 1, "0xB": 2}
processed_counts_2 = {
"0001": 0,
"0100": 3,
"0110": 6,
"1010": 1,
"1011": 2
}
data_2 = models.ExperimentResultData(counts=dict(**raw_counts_2))
exp_result_header_2 = QobjExperimentHeader(creg_sizes=[["c0", 4]],
memory_slots=4)
exp_result_2 = models.ExperimentResult(shots=14,
success=True,
meas_level=2,
data=data_2,
header=exp_result_header_2)
raw_counts_3 = {"0xC": 27, "0xF": 20}
processed_counts_3 = {"1100": 27, "1111": 20}
data_3 = models.ExperimentResultData(counts=dict(**raw_counts_3))
exp_result_header_3 = QobjExperimentHeader(creg_sizes=[["c0", 4]],
memory_slots=4)
exp_result_3 = models.ExperimentResult(shots=14,
success=True,
meas_level=2,
data=data_3,
header=exp_result_header_3)
mult_result = Result(
results=[exp_result_1, exp_result_2, exp_result_3],
**self.base_result_args)
sing_result = Result(results=[exp_result_1], **self.base_result_args)
self.assertEqual(
mult_result.get_counts(),
[processed_counts_1, processed_counts_2, processed_counts_3])
self.assertEqual(sing_result.get_counts(), processed_counts_1)
def setUp(self):
"""Here, single-shots average to points at plus/minus 1.
The setting corresponds to four single-shots done on two qubits.
"""
super().setUp()
circ_es = ExperimentResultData(memory=[
[[1.1, 0.9], [-0.8, 1.0]],
[[1.2, 1.1], [-0.9, 1.0]],
[[0.8, 1.1], [-1.2, 1.0]],
[[0.9, 0.9], [-1.1, 1.0]],
])
self._sig_gs = np.array([-1.0, 1.0]) / np.sqrt(2.0)
circ_gs = ExperimentResultData(memory=[
[[-1.1, -0.9], [0.8, -1.0]],
[[-1.2, -1.1], [0.9, -1.0]],
[[-0.8, -1.1], [1.2, -1.0]],
[[-0.9, -0.9], [1.1, -1.0]],
])
self._sig_es = np.array([1.0, -1.0]) / np.sqrt(2.0)
circ_x90p = ExperimentResultData(memory=[
[[-1.0, -1.0], [1.0, -1.0]],
[[-1.0, -1.0], [1.0, -1.0]],
[[1.0, 1.0], [-1.0, 1.0]],
[[1.0, 1.0], [-1.0, 1.0]],
])
self._sig_x90 = np.array([0, 0])
circ_x45p = ExperimentResultData(memory=[
[[-1.0, -1.0], [1.0, -1.0]],
[[-1.0, -1.0], [1.0, -1.0]],
[[-1.0, -1.0], [1.0, -1.0]],
[[1.0, 1.0], [-1.0, 1.0]],
])
self._sig_x45 = np.array([-0.5, 0.5]) / np.sqrt(2.0)
res_es = ExperimentResult(
shots=4,
success=True,
meas_level=1,
meas_return="single",
data=circ_es,
header=self.header,
)
res_gs = ExperimentResult(
shots=4,
success=True,
meas_level=1,
meas_return="single",
data=circ_gs,
header=self.header,
)
res_x90p = ExperimentResult(
shots=4,
success=True,
meas_level=1,
meas_return="single",
data=circ_x90p,
header=self.header,
)
res_x45p = ExperimentResult(
shots=4,
success=True,
meas_level=1,
meas_return="single",
data=circ_x45p,
header=self.header,
)
self.data = ExperimentData(FakeExperiment())
self.data.add_data(
Result(results=[res_es, res_gs, res_x90p, res_x45p],
**self.base_result_args))
