quantify_scheduler.gettables

Module containing quantify_core.measurement.types.Gettables for use with quantify-scheduler.

Warning

The gettable module is expected to change significantly as the acquisition protocols (#36 and #80) get fully supported by the scheduler. Currently different Gettables are required for different acquisition modes. The intent is to have one generic ScheduleGettable. Expect breaking changes.

Module Contents

Classes

ScheduleGettable

Generic gettable for a quantify schedule using vector (I,Q) acquisition. Can be

Functions

_evaluate_parameter_dict(→ Dict[str, Any])

Loop over the keys and values in a dict and replaces parameters with their current

Attributes

logger

logger

class ScheduleGettable(quantum_device: quantify_scheduler.device_under_test.quantum_device.QuantumDevice, schedule_function: Callable[Ellipsis, quantify_scheduler.Schedule], schedule_kwargs: Dict[str, Any], num_channels: int = 1, data_labels: Optional[List[str]] = None, real_imag: bool = True, batched: bool = False, max_batch_size: int = 1024, always_initialize=True)

Generic gettable for a quantify schedule using vector (I,Q) acquisition. Can be set to return either static (demodulated) I and Q values or magnitude and phase.

The gettable evaluates the parameters passed as schedule_kwargs, then generates the quantify_scheduler.schedules.schedule.Schedule using the schedule_function, this is then compiled and finally executed by the InstrumentCoordinator.

Create a new instance of ScheduleGettable which is used to do I and Q acquisition or alternatively magnitude and phase.

Parameters

• quantum_device – The qcodes instrument representing the quantum device under test (DUT) containing quantum device properties and setup configuration information.

• schedule_function – A function which returns a quantify_scheduler.schedules.schedule.Schedule. The function is required to have the repetitions keyword argument.

• schedule_kwargs – The schedule function keyword arguments, when a value in this dictionary is a Parameter, this parameter will be evaluated every time .get() is called before being passed to the schedule_function.

• num_channels – The number of channels to expect in the acquisition data.

• data_labels – Allows to specify custom labels. Needs to be precisely 2*num_channels if specified. The order is [Voltage I 0, Voltage Q 0, Voltage I 1, Voltage Q 1, …], in case real_imag==True, otherwise [Magnitude 0, Phase 0, Magnitude 1, Phase 1, …].

• real_imag – If true, the gettable returns I, Q values. Otherwise, magnitude and phase (degrees) are returned.

• batched – Used to indicate if the experiment is performed in batches or in an iterative fashion.

• max_batch_size – Determines the maximum number of points to acquire when acquiring in batched mode. Can be used to split up a program in parts if required due to hardware constraints.

• always_initialize – If True, then reinitialize the schedule on each invocation of get. If False, then only initialize the first invocation of get.

property compiled_schedule: quantify_scheduler.Schedule

Return the schedule used in this class

_compile(sched)

Compile schedule, separated to allow for profiling compilation duration.

initialize()

This generates the schedule and uploads the compiled instructions to the hardware using the instrument coordinator.

get() → Union[Tuple[float, Ellipsis], Tuple[numpy.ndarray, Ellipsis]]

Start the experimental sequence and retrieve acquisition data.

Returns

The acquired I/Q voltage signal as a complex number, split into a tuple of floats: either real/imaginary parts or magnitude/phase, depending on whether real_imag is True.

_reshape_data(acq_metadata, vals)

_process_acquired_data_trigger_count(acquired_data, acq_metadata: quantify_scheduler.helpers.schedule.AcquisitionMetadata, repetitions: int) → Dict[int, numpy.ndarray]

Reformat acquired data in a dictionary. Used by process_acquired_data.

Parameters

• acquired_data – Acquired data as returned by instrument coordinator

• acq_metadata – Acquisition metadata from schedule

• repetitions – Number of repetitions of the schedule

Returns

Dictionary with reformatted data. Keys correspond to the acquisition channel. Values are 1d numpy arrays with trigger counts.

Raises

NotImplementedError – If acquisition protocol other than BinMode.APPEND is used.

process_acquired_data(acquired_data, acq_metadata: quantify_scheduler.helpers.schedule.AcquisitionMetadata, repetitions: int) → Union[Tuple[float, Ellipsis], Tuple[numpy.ndarray, Ellipsis]]

Reshapes the data as returned from the instrument coordinator into the form accepted by the measurement control.

generate_diagnostics_report(execute_get: bool = False, update: bool = False) → str

Create a report that saves all information contained in this ScheduleGettable and save it in the quantify datadir with its own tuid. The information in the report includes the generated schedule, device config, hardware config and snapshot of the instruments.

Parameters

• execute_get – When True, executes self.get() before generating the report.

• update – When True, updates all parameters before saving the snapshot.

Returns

The tuid of the generated report.

_evaluate_parameter_dict(parameters: Dict[str, Any]) → Dict[str, Any]

Loop over the keys and values in a dict and replaces parameters with their current value.

Parameters

parameters – A dictionary containing a mix of Parameters and normal values.

Returns

The parameters dictionary, but with the parameters replaced by their current value.

Raises

TypeError – If a parameter returns None