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.

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

exception AcquisitionProtocolError

Bases: TypeError

Inappropriate argument type.

exception AcquisitionProtocolNotSupportedError

Bases: NotImplementedError

Method or function hasn’t been implemented yet.

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: list[str] | None = None, real_imag: bool = True, batched: bool = False, max_batch_size: int = 1024, always_initialize: bool = True)

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

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.

ScheduleGettable can be set to return either static (demodulated) I and Q values or 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.

_data_labels_specified

always_initialize

is_initialized = False

_compiled_schedule: quantify_scheduler.CompiledSchedule | None = None

real_imag

batched

batch_size

schedule_function

schedule_kwargs

_evaluated_sched_kwargs

quantum_device

_backend = None

_debug_mode: bool = False

_compile(sched: quantify_scheduler.Schedule) → None

Compile schedule, separated to allow for profiling compilation duration.

initialize() → None

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

property compiled_schedule: quantify_scheduler.CompiledSchedule | None

Return the schedule used in this class

get() → tuple[numpy.ndarray, Ellipsis]

Start the experimental sequence and retrieve acquisition data.

The data format returned is dependent on the type of acquisitions used in the schedule. These data formats can be found in the user guide.

Returns:

A tuple of acquisition data per acquisition channel as specified above.

_reshape_data(acq_protocol: str, vals: numpy.typing.NDArray) → list[numpy.typing.NDArray]

process_acquired_data(acquired_data: xarray.Dataset) → tuple[numpy.typing.NDArray[numpy.float64], Ellipsis]

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

Parameters:

acquired_data – Data that is returned by instrument coordinator.

Returns:

A tuple of data, casted to a historical conventions on data format.

initialize_and_get_with_report() → str

Create a report that saves all information from this experiment in a zipfile.

Run initialize() and get() and capture all information from the experiment in a zipfile in the quantify datadir. The basic information in the report includes the schedule, device config and hardware config. The method attempts to compile the schedule, and if it succeeds, it runs the experiment and adds the compiled schedule, a snapshot of the instruments, and logs from the actual hardware (only Qblox instruments supported currently) to the zipfile. A full error trace is also included if any of these steps fail.

Returns:

A path to the generated report. Directory name includes a flag indicating at which state the experiment and report retrieval stopped.

Flags (defined in :func: ~._generate_diagnostics_report):

• failed_initialization: The experiment failed during initialize().

• failed_exp: The experiment initialized failed during get().

• failed_connection_to_hw: The experiment initialized but both get() and retrieve_hardware_logs() failed. Connection to hardware was likely interrupted during runtime.

• failed_hw_log_retrieval: The experiment succeeded but retrieve_hardware_logs() failed.

• completed_exp: The experiment succeeded.

_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