def test_analysis_result_attributes(self):
"""Test analysis result attributes."""
attrs = {
"name": "my_type",
"device_components": [Qubit(1), Qubit(2)],
"experiment_id": "1234",
"result_id": "5678",
"quality": "Good",
"verified": False,
}
result = DbAnalysisResult(value={"foo": "bar"}, tags=["tag1", "tag2"], **attrs)
self.assertEqual({"foo": "bar"}, result.value)
self.assertEqual(["tag1", "tag2"], result.tags)
for key, val in attrs.items():
self.assertEqual(val, getattr(result, key))
def _extra_database_entry(self, fit_data: curve.FitData) -> List[AnalysisResultData]:
"""Calculate Hamiltonian coefficients from fit values."""
extra_entries = []
for control in ("z", "i"):
for target in ("x", "y", "z"):
p0_val = fit_data.fitval(f"p{target}0")
p1_val = fit_data.fitval(f"p{target}1")
if control == "z":
coef_val = 0.5 * (p0_val - p1_val) / (2 * np.pi)
else:
coef_val = 0.5 * (p0_val + p1_val) / (2 * np.pi)
extra_entries.append(
AnalysisResultData(
name=f"omega_{control}{target}",
value=coef_val,
chisq=fit_data.reduced_chisq,
device_components=[Qubit(q) for q in self._physical_qubits],
extra={"unit": "Hz"},
)
)
return extra_entries
def callback1(exp_data):
"""Callback function that call add_analysis_callback"""
exp_data.add_analysis_callback(callback2)
result = DbAnalysisResult("result_name", 0, [Qubit(0)], "experiment_id")
exp_data.add_analysis_results(result)
figure = get_non_gui_ax().get_figure()
exp_data.add_figures(figure, "figure.svg")
exp_data.add_data({"key": 1.2})
exp_data.data()
def _get_experiment_components(self, experiment_data: ExperimentData):
"""Subclasses may override this method to specify the experiment components."""
if "physical_qubits" in experiment_data.metadata:
experiment_components = [
Qubit(qubit) for qubit in experiment_data.metadata["physical_qubits"]
]
else:
experiment_components = []
return experiment_components
def run(
self,
experiment_data: ExperimentData,
**options,
) -> ExperimentData:
"""Run analysis and update ExperimentData with analysis result.
Args:
experiment_data: the experiment data to analyze.
options: additional analysis options. See class documentation for
supported options.
Returns:
An experiment data object containing the analysis results and figures.
Raises:
QiskitError: if experiment_data container is not valid for analysis.
"""
if not isinstance(experiment_data, self.__experiment_data__):
raise QiskitError(
f"Invalid experiment data type, expected {self.__experiment_data__.__name__}"
f" but received {type(experiment_data).__name__}")
# Get experiment device components
if "physical_qubits" in experiment_data.metadata:
experiment_components = [
Qubit(qubit)
for qubit in experiment_data.metadata["physical_qubits"]
]
else:
experiment_components = []
# Get analysis options
analysis_options = self._default_options()
analysis_options.update_options(**options)
analysis_options = analysis_options.__dict__
# Run analysis
results, figures = self._run_analysis(experiment_data,
**analysis_options)
# Add components
analysis_results = [
self._format_analysis_result(result, experiment_data.experiment_id,
experiment_components)
for result in results
]
# Update experiment data with analysis results
experiment_data.add_analysis_results(analysis_results)
if figures:
experiment_data.add_figures(figures)
return experiment_data
def _extra_database_entry(
self, fit_data: curve.FitData) -> List[AnalysisResultData]:
"""Calculate EPC."""
extra_entries = []
# Calculate EPC
alpha = fit_data.fitval("alpha")
scale = (2**self._num_qubits - 1) / (2**self._num_qubits)
epc = scale * (1 - alpha)
extra_entries.append(
AnalysisResultData(
name="EPC",
value=epc,
chisq=fit_data.reduced_chisq,
quality=self._evaluate_quality(fit_data),
))
# Calculate EPG
if not self.options.gate_error_ratio:
# we attempt to get the ratio from the backend properties
if not self.options.error_dict:
gate_error_ratio = RBUtils.get_error_dict_from_backend(
backend=self._backend, qubits=self._physical_qubits)
else:
gate_error_ratio = self.options.error_dict
else:
gate_error_ratio = self.options.gate_error_ratio
count_ops = []
for meta in self._data(label="raw_data").metadata:
count_ops += meta.get("count_ops", [])
if len(count_ops) > 0 and gate_error_ratio is not None:
gates_per_clifford = RBUtils.gates_per_clifford(count_ops)
num_qubits = len(self._physical_qubits)
if num_qubits == 1:
epg_dict = RBUtils.calculate_1q_epg(
epc,
self._physical_qubits,
gate_error_ratio,
gates_per_clifford,
)
elif num_qubits == 2:
epg_1_qubit = self.options.epg_1_qubit
epg_dict = RBUtils.calculate_2q_epg(
epc,
self._physical_qubits,
gate_error_ratio,
gates_per_clifford,
epg_1_qubit=epg_1_qubit,
)
else:
# EPG calculation is not supported for more than 3 qubits RB
epg_dict = None
if epg_dict:
for qubits, gate_dict in epg_dict.items():
for gate, value in gate_dict.items():
extra_entries.append(
AnalysisResultData(
f"EPG_{gate}",
value,
chisq=fit_data.reduced_chisq,
quality=self._evaluate_quality(fit_data),
device_components=[Qubit(i) for i in qubits],
))
return extra_entries
def test_str(self):
"""Test string representation."""
q1 = Qubit(1)
r1 = Resonator(1)
self.assertEqual("Q1", str(q1))
self.assertEqual("R1", str(r1))
def run(
self,
experiment_data: ExperimentData,
replace_results: bool = False,
**options,
) -> ExperimentData:
"""Run analysis and update ExperimentData with analysis result.
Args:
experiment_data: the experiment data to analyze.
replace_results: if True clear any existing analysis results and
figures in the experiment data and replace with
new results. See note for additional information.
options: additional analysis options. See class documentation for
supported options.
Returns:
An experiment data object containing the analysis results and figures.
Raises:
QiskitError: if experiment_data container is not valid for analysis.
.. note::
**Updating Results**
If analysis is run with ``replace_results=True`` then any analysis results
and figures in the experiment data will be cleared and replaced with the
new analysis results. Saving this experiment data will replace any
previously saved data in a database service using the same experiment ID.
If analysis is run with ``replace_results=False`` and the experiment data
being analyzed has already been saved to a database service, or already
contains analysis results or figures, a copy with a unique experiment ID
will be returned containing only the new analysis results and figures.
This data can then be saved as its own experiment to a database service.
"""
# Make a new copy of experiment data if not updating results
if not replace_results and _requires_copy(experiment_data):
experiment_data = experiment_data.copy()
# Get experiment device components
if "physical_qubits" in experiment_data.metadata:
experiment_components = [
Qubit(qubit)
for qubit in experiment_data.metadata["physical_qubits"]
]
else:
experiment_components = []
# Set Analysis options
if not options:
analysis = self
else:
analysis = self.copy()
analysis.set_options(**options)
def run_analysis(expdata):
results, figures = analysis._run_analysis(expdata)
# Add components
analysis_results = [
analysis._format_analysis_result(result, expdata.experiment_id,
experiment_components)
for result in results
]
# Update experiment data with analysis results
experiment_data._clear_results()
if analysis_results:
expdata.add_analysis_results(analysis_results)
if figures:
expdata.add_figures(figures)
experiment_data.add_analysis_callback(run_analysis)
return experiment_data
