Source code for quantify_scheduler.helpers.schedule

# Repository: https://gitlab.com/quantify-os/quantify-scheduler
# Licensed according to the LICENCE file on the main branch
"""Schedule helper functions."""
from __future__ import annotations

from itertools import chain
from typing import TYPE_CHECKING, Any, Dict, List, Tuple

import numpy as np
from quantify_scheduler.helpers.collections import make_hash, without
from quantify_scheduler.schedules.schedule import (
    AcquisitionMetadata,
    CompiledSchedule,
    ScheduleBase,
)

if TYPE_CHECKING:
    from quantify_scheduler import Operation


[docs]def get_pulse_uuid(pulse_info: Dict[str, Any], excludes: List[str] = None) -> int: """ Returns an unique identifier for a pulse. Parameters ---------- pulse_info The pulse information dictionary. Returns ------- : The uuid hash. """ if excludes is None: excludes = ["t0"] return make_hash(without(pulse_info, excludes))
[docs]def get_acq_uuid(acq_info: Dict[str, Any]) -> int: """ Returns an unique identifier for a acquisition protocol. Parameters ---------- acq_info The acquisition information dictionary. Returns ------- : The uuid hash. """ return make_hash(without(acq_info, ["t0", "waveforms"]))
[docs]def get_total_duration(schedule: CompiledSchedule) -> float: """ Returns the total schedule duration in seconds. Parameters ---------- schedule The schedule. Returns ------- : Duration in seconds. """ if len(schedule.schedulables) == 0: return 0.0 def _get_operation_end(pair: Tuple[int, dict]) -> float: """Returns the operations end time in seconds.""" (timeslot_index, _) = pair return get_operation_end( schedule, timeslot_index, ) operations_ends = map( _get_operation_end, enumerate(schedule.schedulables.values()), ) return max( operations_ends, default=0, )
[docs]def get_operation_start( schedule: CompiledSchedule, timeslot_index: int, ) -> float: """ Returns the start of an operation in seconds. Parameters ---------- schedule timeslot_index Returns ------- : The Operation start time in Seconds. """ if len(schedule.schedulables) == 0: return 0.0 schedulable = list(schedule.schedulables.values())[timeslot_index] operation = schedule.operations[schedulable["operation_repr"]] t0: float = schedulable["abs_time"] pulse_info: dict = ( operation["pulse_info"][0] if len(operation["pulse_info"]) > 0 else {"t0": -1, "duration": 0} ) acq_info: dict = ( operation["acquisition_info"][0] if len(operation["acquisition_info"]) > 0 else {"t0": -1, "duration": 0} ) if acq_info["t0"] != -1 and acq_info["t0"] < pulse_info["t0"]: t0 += acq_info["t0"] elif pulse_info["t0"] >= 0: t0 += pulse_info["t0"] return t0
[docs]def get_operation_end( schedule: CompiledSchedule, timeslot_index: int, ) -> float: """ Returns the end of an operation in seconds. Parameters ---------- schedule timeslot_index Returns ------- : The Operation end time in Seconds. """ if len(schedule.schedulables) == 0: return 0.0 schedulable = list(schedule.schedulables.values())[timeslot_index] operation: Operation = schedule.operations[schedulable["operation_repr"]] t0: float = schedulable["abs_time"] return t0 + operation.duration
[docs]def get_port_timeline( schedule: CompiledSchedule, ) -> Dict[str, Dict[int, List[int]]]: """ Returns a new dictionary containing the timeline of pulses, readout- and acquisition pulses of a port. Using iterators on this collection enables sorting. .. code-block:: print(port_timeline_dict) # { {'q0:mw', {0, [123456789]}}, # ... } # Sorted items. print(port_timeline_dict.items()) Parameters ---------- schedule The schedule. """ port_timeline_dict: Dict[str, Dict[int, List[int]]] = {} # Sort timing constraints based on abs_time and keep the original index. schedulables_map = dict( sorted( map( lambda pair: (pair[0], pair[1]), enumerate(schedule.schedulables.values()), ), key=lambda pair: pair[1]["abs_time"], ) ) for timeslot_index, schedulable in schedulables_map.items(): operation = schedule.operations[schedulable["operation_repr"]] abs_time = schedulable["abs_time"] pulse_info_iter = map( lambda pulse_info: (get_pulse_uuid(pulse_info), pulse_info), operation["pulse_info"], ) acq_info_iter = map( lambda acq_info: (get_acq_uuid(acq_info), acq_info), operation["acquisition_info"], ) # Sort pulses and acquisitions within an operation. for uuid, info in sorted( chain(pulse_info_iter, acq_info_iter), key=lambda pair: abs_time # pylint: disable=cell-var-from-loop + pair[1]["t0"], ): port = str(info["port"]) if port not in port_timeline_dict: port_timeline_dict[port] = {} if timeslot_index not in port_timeline_dict[port]: port_timeline_dict[port][timeslot_index] = [] port_timeline_dict[port][timeslot_index].append(uuid) return port_timeline_dict
[docs]def get_schedule_time_offset( schedule: CompiledSchedule, port_timeline_dict: Dict[str, Dict[int, List[int]]], ) -> float: """ Returns the start time in seconds of the first pulse in the CompiledSchedule. The "None" port containing the Reset Operation will be ignored. Parameters ---------- schedule port_timeline_dict Returns ------- : The operation t0 in seconds. """ return min( map( lambda port: get_operation_start( schedule, timeslot_index=next(iter(port_timeline_dict[port])), ) if port != "None" else np.inf, port_timeline_dict.keys(), ), default=0, )
[docs]def get_pulse_info_by_uuid( schedule: CompiledSchedule, ) -> Dict[int, Dict[str, Any]]: """ Returns a lookup dictionary of pulses with its hash as unique identifiers. Parameters ---------- schedule The schedule. """ pulseid_pulseinfo_dict: Dict[int, Dict[str, Any]] = {} for schedulable in schedule.schedulables.values(): operation = schedule.operations[schedulable["operation_repr"]] for pulse_info in operation["pulse_info"]: pulse_id = get_pulse_uuid(pulse_info) if pulse_id in pulseid_pulseinfo_dict: # Unique pulse info already populated in the dictionary. continue pulseid_pulseinfo_dict[pulse_id] = pulse_info for acq_info in operation["acquisition_info"]: for pulse_info in acq_info["waveforms"]: pulse_id = get_pulse_uuid(pulse_info) if pulse_id in pulseid_pulseinfo_dict: # Unique pulse info already populated in the dictionary. continue pulseid_pulseinfo_dict[pulse_id] = pulse_info return pulseid_pulseinfo_dict
[docs]def get_acq_info_by_uuid(schedule: CompiledSchedule) -> Dict[int, Dict[str, Any]]: """ Returns a lookup dictionary of unique identifiers of acquisition information. Parameters ---------- schedule The schedule. """ acqid_acqinfo_dict: Dict[int, Dict[str, Any]] = {} for schedulable in schedule.schedulables.values(): operation = schedule.operations[schedulable["operation_repr"]] for acq_info in operation["acquisition_info"]: acq_id = get_acq_uuid(acq_info) if acq_id in acqid_acqinfo_dict: # Unique acquisition info already populated in the dictionary. continue acqid_acqinfo_dict[acq_id] = acq_info return acqid_acqinfo_dict
[docs]def extract_acquisition_metadata_from_schedule( schedule: ScheduleBase, ) -> AcquisitionMetadata: """ Extracts acquisition metadata from a schedule. This function operates under certain assumptions with respect to the schedule. - The acquisition_metadata should be sufficient to initialize the xarray dataset (described in quantify-core !212) that executing the schedule will result in. - All measurements in the schedule use the same acquisition protocol. - The used acquisition index channel combinations for each measurement are unique. - The used acquisition indices for each channel are the same. - When :class:`~quantify_scheduler.enums.BinMode` is :code:`APPEND` The number of data points per acquisition index assumed to be given by the schedule's repetition property. This implies no support for feedback (conditional measurements). Parameters ---------- schedule schedule containing measurements from which acquisition metadata can be extracted. Returns ------- : The acquisition metadata provides a summary of the acquisition protocol, bin-mode, return-type and acquisition indices of the acquisitions in the schedule. Raises ------ AssertionError If not all acquisition protocols in a schedule are the same. If not all acquisitions use the same bin_mode. If the return type of the acquisitions is different. """ # FIXME update when quantify-core!212 spec is ready # pylint: disable=fixme # a dictionary containing the acquisition indices used for each channel acqid_acqinfo_dict = get_acq_info_by_uuid(schedule) return extract_acquisition_metadata_from_acquisition_protocols( acquisition_protocols=list(acqid_acqinfo_dict.values()), repetitions=schedule.repetitions, )
[docs]def extract_acquisition_metadata_from_acquisition_protocols( acquisition_protocols: List[Dict[str, Any]], repetitions: int ) -> AcquisitionMetadata: """ Private function containing the logic of extract_acquisition_metadata_from_schedule. The logic is factored out as to work around limitations of the different interfaces required. Parameters ---------- acquisition_protocols A list of acquisition protocols. repetitions How many times the acquisition was repeated. """ acq_indices: Dict[int, List[int]] = {} for i, acq_protocol in enumerate(acquisition_protocols): if i == 0: # the protocol and bin mode of the first protocol = acq_protocol["protocol"] bin_mode = acq_protocol["bin_mode"] acq_return_type = acq_protocol["acq_return_type"] # test limitation: all acquisition protocols in a schedule must be of # the same kind if ( acq_protocol["protocol"] != protocol or acq_protocol["bin_mode"] != bin_mode or acq_protocol["acq_return_type"] != acq_return_type ): raise RuntimeError( "Acquisition protocols or bin mode or acquisition return type are not" " of the same kind. " f"Expected protocol: {acquisition_protocols[0]}. " f"Offending: {i}, {acq_protocol} \n" ) # add the individual channel if acq_protocol["acq_channel"] not in acq_indices.keys(): acq_indices[acq_protocol["acq_channel"]] = [] acq_indices[acq_protocol["acq_channel"]].append(acq_protocol["acq_index"]) # combine the information in the acq metadata dataclass. acq_metadata = AcquisitionMetadata( acq_protocol=protocol, bin_mode=bin_mode, acq_indices=acq_indices, acq_return_type=acq_return_type, repetitions=repetitions, ) return acq_metadata