Source code for quantify_scheduler.backends.qblox.helpers

# Repository: https://gitlab.com/quantify-os/quantify-scheduler
# Licensed according to the LICENCE file on the main branch
"""Helper functions for Qblox backend."""
import dataclasses
import re
import warnings
from copy import deepcopy
from typing import Any, Dict, List, Literal, Optional, Tuple, Union

import numpy as np

from quantify_core.utilities import deprecated
from quantify_core.utilities.general import without

from quantify_scheduler.backends.qblox import constants
from quantify_scheduler.helpers.waveforms import exec_waveform_function
from quantify_scheduler.schedules.schedule import AcquisitionMetadata
from quantify_scheduler.helpers.collections import (
    find_all_port_clock_combinations,
    find_port_clock_path,
)
from quantify_scheduler.helpers.schedule import (
    extract_acquisition_metadata_from_acquisition_protocols,
)
from quantify_scheduler import Schedule

from quantify_scheduler.backends.types.qblox import OpInfo
from quantify_scheduler.operations.pulse_library import WindowOperation
from quantify_scheduler.backends.graph_compilation import CompilationConfig


[docs]def generate_waveform_data( data_dict: dict, sampling_rate: float, duration: Optional[float] = None ) -> np.ndarray: """Generates an array using the parameters specified in ``data_dict``. Parameters ---------- data_dict : dict The dictionary that contains the values needed to parameterize the waveform. ``data_dict['wf_func']`` is then called to calculate the values. sampling_rate : float The sampling rate used to generate the time axis values. duration : float or None, optional The duration of the waveform in seconds. This parameter can be used if ``data_dict`` does not contain a ``'duration'`` key. By default None. Returns ------- wf_data : np.ndarray The (possibly complex) values of the generated waveform. The number of values is determined by rounding to the nearest integer. Raises ------ TypeError If ``data_dict`` does not contain a ``'duration'`` entry and ``duration is None``. """ if duration is None: try: duration = data_dict["duration"] except KeyError as exc: raise TypeError( "Parameter 'duration' has value None. If 'data_dict' does not contain " "'duration', the function parameter can be used instead." ) from exc num_samples = round(duration * sampling_rate) t = np.arange(start=0, stop=num_samples, step=1) / sampling_rate wf_data = exec_waveform_function( wf_func=data_dict["wf_func"], t=t, pulse_info=data_dict ) return wf_data
[docs]def generate_waveform_names_from_uuid(uuid: Any) -> Tuple[str, str]: """ Generates names for the I and Q parts of the complex waveform based on a unique identifier for the pulse/acquisition. Parameters ---------- uuid A unique identifier for a pulse/acquisition. Returns ------- uuid_I: Name for the I waveform. uuid_Q: Name for the Q waveform. """ return f"{str(uuid)}_I", f"{str(uuid)}_Q"
[docs]def generate_uuid_from_wf_data(wf_data: np.ndarray, decimals: int = 12) -> str: """ Creates a unique identifier from the waveform data, using a hash. Identical arrays yield identical strings within the same process. Parameters ---------- wf_data: The data to generate the unique id for. decimals: The number of decimal places to consider. Returns ------- : A unique identifier. """ waveform_hash = hash(wf_data.round(decimals=decimals).tobytes()) return str(waveform_hash)
[docs]def add_to_wf_dict_if_unique( wf_dict: Dict[str, Any], waveform: np.ndarray ) -> Tuple[Dict[str, Any], str, int]: """ Adds a waveform to the waveform dictionary if it is not yet in there and returns the uuid and index. If it is already present it simply returns the uuid and index. Parameters ---------- wf_dict: The waveform dict in the format expected by the sequencer. waveform: The waveform to add. Returns ------- Dict[str, Any] The (updated) wf_dict. str The uuid of the waveform. int The index. """ def generate_entry(name: str, data: np.ndarray, idx: int) -> Dict[str, Any]: return {name: {"data": data.tolist(), "index": idx}} if not np.isrealobj(waveform): raise RuntimeError("This function only accepts real arrays.") uuid = generate_uuid_from_wf_data(waveform) if uuid in wf_dict: index: int = wf_dict[uuid]["index"] else: index = len(wf_dict) wf_dict.update(generate_entry(uuid, waveform, len(wf_dict))) return wf_dict, uuid, index
[docs]def output_name_to_outputs(name: str) -> Optional[Union[Tuple[int], Tuple[int, int]]]: """ Finds the output path index associated with the output names specified in the config. For the baseband modules, these indices correspond directly to a physical output ( e.g. index 0 corresponds to output 1 etc.). For the RF modules, index 0 and 2 correspond to path0 of output 1 and output 2 respectively, and 1 and 3 to path1 of those outputs. Parameters ---------- name name of the output channel. e.g. 'complex_output_0'. Returns ------- : A tuple containing the indices of the physical (real) outputs. """ if "output" not in name: return None return { "complex_output_0": (0, 1), "complex_output_1": (2, 3), "real_output_0": (0,), "real_output_1": (1,), "real_output_2": (2,), "real_output_3": (3,), }[name]
[docs]def input_name_to_inputs(name: str) -> Union[Tuple[int], Tuple[int, int]]: """ Finds the input path index associated with the input names specified in the config. For the baseband modules, these indices correspond directly to a physical input ( e.g. index 0 corresponds to input 1 etc.). For the RF modules, index 0 corresponds to path0 of input 1 and path 1 of input 1. Parameters ---------- name name of the input channel. e.g. 'real_input_0'. Returns ------- : A tuple containing the indices of the physical (real) inputs. """ if "input" not in name: return None return { "complex_input_0": (0, 1), "real_input_0": (0,), "real_input_1": (1,), }[name]
[docs]def io_mode_from_ios( io: Union[Tuple[int], Tuple[int, int]] ) -> Literal["complex", "real", "imag"]: """ Takes the specified outputs to use and extracts a "sequencer mode" from it. Modes: - ``"real"``: only path0 is used - ``"imag"``: only path1 is used - ``"complex"``: both path0 and path1 paths are used. Parameters ---------- io The io the sequencer is supposed to use. Note that the outputs start from 0, but the labels on the front panel start counting from 1. So the mapping differs n-1. Returns ------- : The mode Raises ------ RuntimeError The amount of ios is more than 2, which is impossible for one sequencer. """ if len(io) > 2: raise RuntimeError(f"Too many io specified for this channel. Given: {io}.") if len(io) == 2: assert ( io[0] - io[1] ) ** 2 == 1, "Attempting to use two outputs that are not next to each other." if 1 in io: assert 2 not in io, ( "Attempting to use output 1 and output 2 (2 and 3 on front panel) " "together, but they belong to different pairs." ) return "complex" output = io[0] mode = "real" if output % 2 == 0 else "imag" return mode
[docs]def generate_waveform_dict(waveforms_complex: Dict[str, np.ndarray]) -> Dict[str, dict]: """ Takes a dictionary with complex waveforms and generates a new dictionary with real valued waveforms with a unique index, as required by the hardware. Parameters ---------- waveforms_complex Dictionary containing the complex waveforms. Keys correspond to a unique identifier, value is the complex waveform. Returns ------- dict[str, dict] A dictionary with as key the unique name for that waveform, as value another dictionary containing the real-valued data (list) as well as a unique index. Note that the index of the Q waveform is always the index of the I waveform +1. .. admonition:: Examples .. jupyter-execute:: import numpy as np from quantify_scheduler.backends.qblox.helpers import generate_waveform_dict complex_waveforms = {12345: np.array([1, 2])} generate_waveform_dict(complex_waveforms) # {'12345_I': {'data': [1, 2], 'index': 0}, # '12345_Q': {'data': [0, 0], 'index': 1}} """ wf_dict = {} for idx, (uuid, complex_data) in enumerate(waveforms_complex.items()): name_i, name_q = generate_waveform_names_from_uuid(uuid) to_add = { name_i: {"data": complex_data.real.tolist(), "index": 2 * idx}, name_q: {"data": complex_data.imag.tolist(), "index": 2 * idx + 1}, } wf_dict.update(to_add) return wf_dict
[docs]def to_grid_time(time: float, grid_time_ns: int = constants.GRID_TIME) -> int: """ Takes a float value representing a time in seconds as used by the schedule, and returns the integer valued time in nanoseconds that the sequencer uses. Parameters ---------- time The time to convert. grid_time_ns The grid time to use in ns. Returns ------- : The integer valued nanosecond time. """ time_ns = int(round(time * 1e9)) if time_ns % grid_time_ns != 0: raise ValueError( f"Attempting to use a time interval of {time_ns} ns. " f"Please ensure that the durations of operations and wait times between" f" operations are multiples of {grid_time_ns} ns." ) return time_ns
[docs]def is_multiple_of_grid_time( time: float, grid_time_ns: int = constants.GRID_TIME ) -> bool: """ Takes a time in seconds and converts it to the ns grid time that the Qblox hardware expects. Parameters ---------- time: A time in seconds. grid_time_ns A grid time in ns. Returns ------- : If it the time is a multiple of the grid time. """ time_ns = int(round(time * 1e9)) return time_ns % grid_time_ns == 0
[docs]def get_nco_phase_arguments(phase_deg: float) -> int: """ Converts a phase in degrees to the int arguments the NCO phase instructions expect. We take `phase_deg` modulo 360 to account for negative phase and phase larger than 360. Parameters ---------- phase_deg The phase in degrees Returns ------- : The int corresponding to the phase argument. """ phase_deg %= 360 return round(phase_deg * constants.NCO_PHASE_STEPS_PER_DEG)
[docs]def get_nco_set_frequency_arguments(frequency_hz: float) -> int: """ Converts a frequency in Hz to the int argument the NCO set_freq instruction expects. Parameters ---------- frequency_hz The frequency in Hz. Returns ------- : The frequency expressed in steps for the NCO set_freq instruction. Raises ------ ValueError If the frequency_hz is out of range. """ frequency_steps = round(frequency_hz * constants.NCO_FREQ_STEPS_PER_HZ) if ( frequency_steps < -constants.NCO_FREQ_LIMIT_STEPS or frequency_steps > constants.NCO_FREQ_LIMIT_STEPS ): min_max_frequency_in_hz = ( constants.NCO_FREQ_LIMIT_STEPS / constants.NCO_FREQ_STEPS_PER_HZ ) raise ValueError( f"Attempting to set NCO frequency. " f"The frequency must be between and including " f"-{min_max_frequency_in_hz:e} Hz and {min_max_frequency_in_hz:e} Hz. " f"Got {frequency_hz:e} Hz." ) return frequency_steps
@dataclasses.dataclass
[docs]class Frequencies:
[docs] clock: Optional[float] = None
[docs] LO: Optional[float] = None
[docs] IF: Optional[float] = None
[docs]def determine_clock_lo_interm_freqs( clock_freq: float, lo_freq: Union[float, None], interm_freq: Union[float, None], downconverter_freq: Optional[float] = None, mix_lo: bool = True, ) -> Frequencies: """ From known frequency for the local oscillator or known intermodulation frequency, determine any missing frequency, after optionally applying `downconverter_freq` to the clock frequency. If `mix_lo` is ``True``, the following relation is obeyed: :math:`f_{RF} = f_{LO} + f_{IF}`. If `mix_lo` is ``False``, :math:`f_{RF} = f_{LO}` is upheld. .. warning:: Using `downconverter_freq` requires custom Qblox hardware, do not use otherwise. Parameters ---------- clock_freq : float Frequency of the clock. lo_freq : Union[float, None] Frequency of the local oscillator (LO). interm_freq : Union[float, None] Intermodulation frequency (IF), the frequency of the numerically controlled oscillator (NCO). downconverter_freq : Optional[float] Frequency for downconverting the clock frequency, using: :math:`f_\mathrm{out} = f_\mathrm{downconverter} - f_\mathrm{in}`. mix_lo : bool Flag indicating whether IQ mixing is enabled with the LO. Returns ------- : :class:`.Frequencies` object containing the determined LO and IF frequencies and the optionally downconverted clock frequency. Warns ----- ValueWarning In case `downconverter_freq` is set equal to 0, warns to unset via ``null``/``None`` instead. Raises ------ ValueError In case `downconverter_freq` is less than 0. ValueError In case `downconverter_freq` is less than `clock_freq`. """ def _downconvert_clock(downconverter_freq: float, clock_freq: float) -> float: if downconverter_freq == 0: warnings.warn( "Downconverter frequency 0 supplied. To unset 'downconverter_freq', " "set to `null` (json) / `None` instead in hardware configuration.", RuntimeWarning, ) if downconverter_freq < 0: raise ValueError( f"Downconverter frequency must be positive ({downconverter_freq=:e})" ) if downconverter_freq < clock_freq: raise ValueError( f"Downconverter frequency must be greater than clock frequency " f"({downconverter_freq=:e}, {clock_freq=:e})" ) return downconverter_freq - clock_freq freqs = Frequencies(clock=clock_freq, LO=lo_freq, IF=interm_freq) if downconverter_freq is not None: freqs.clock = _downconvert_clock( downconverter_freq=downconverter_freq, clock_freq=clock_freq, ) if not mix_lo: freqs.LO = freqs.clock freqs.IF = None else: if interm_freq is not None: freqs.LO = freqs.clock - interm_freq if lo_freq is not None: freqs.IF = freqs.clock - lo_freq return freqs
[docs]def generate_port_clock_to_device_map( hardware_cfg: Dict[str, Any] ) -> Dict[Tuple[str, str], str]: """ Generates a mapping that specifies which port-clock combinations belong to which device. .. note:: The same device may contain multiple port-clock combinations, but each port-clock combination may only occur once. Parameters ---------- hardware_cfg: The hardware config dictionary. Returns ------- : A dictionary with as key a tuple representing a port-clock combination, and as value the name of the device. Note that multiple port-clocks may point to the same device. """ portclock_map = {} for device_name, device_info in hardware_cfg.items(): if not isinstance(device_info, dict): continue portclocks = find_all_port_clock_combinations(device_info) for portclock in portclocks: portclock_map[portclock] = device_name return portclock_map
# pylint: disable=too-many-locals # pylint: disable=too-many-branches
[docs]def assign_pulse_and_acq_info_to_devices( schedule: Schedule, device_compilers: Dict[str, Any], hardware_cfg: Dict[str, Any], ): """ Traverses the schedule and generates `OpInfo` objects for every pulse and acquisition, and assigns it to the correct `InstrumentCompiler`. Parameters ---------- schedule The schedule to extract the pulse and acquisition info from. device_compilers Dictionary containing InstrumentCompilers as values and their names as keys. hardware_cfg The hardware config dictionary. Raises ------ RuntimeError This exception is raised then the function encountered an operation that has no pulse or acquisition info assigned to it. KeyError This exception is raised when attempting to assign a pulse with a port-clock combination that is not defined in the hardware configuration. KeyError This exception is raised when attempting to assign an acquisition with a port-clock combination that is not defined in the hardware configuration. """ portclock_mapping = generate_port_clock_to_device_map(hardware_cfg) for schedulable in schedule.schedulables.values(): op_hash = schedulable["operation_repr"] op_data = schedule.operations[op_hash] if isinstance(op_data, WindowOperation): continue if not op_data.valid_pulse and not op_data.valid_acquisition: raise RuntimeError( f"Operation {op_hash} is not a valid pulse or acquisition. Please check" f" whether the device compilation been performed successfully. " f"Operation data: {repr(op_data)}" ) operation_start_time = schedulable["abs_time"] for pulse_data in op_data.data["pulse_info"]: if "t0" in pulse_data: pulse_start_time = operation_start_time + pulse_data["t0"] else: pulse_start_time = operation_start_time # Check whether start time aligns with grid time try: _ = to_grid_time(pulse_start_time) except ValueError as exc: raise ValueError( f"An operation start time of {pulse_start_time * 1e9} ns does not " f"align with a grid time of {constants.GRID_TIME} ns. Please make " f"sure the start time of all operations is a multiple of " f"{constants.GRID_TIME} ns.\n\nOffending operation:" f"\n{repr(op_data)}." ) from exc port = pulse_data["port"] clock = pulse_data["clock"] combined_data = OpInfo( name=op_data.data["name"], data=pulse_data, timing=pulse_start_time, ) if port is None: # Distribute clock operations to all sequencers utilizing that clock for (map_port, map_clock), device_name in portclock_mapping.items(): if map_clock == clock: device_compilers[device_name].add_pulse( port=map_port, clock=clock, pulse_info=combined_data ) else: if (port, clock) not in portclock_mapping: raise KeyError( f"Could not assign pulse data to device. The combination " f"of port {port} and clock {clock} could not be found " f"in hardware configuration.\n\nAre both the port and clock " f"specified in the hardware configuration?\n\n" f"Relevant operation:\n{combined_data}." ) device_name = portclock_mapping[(port, clock)] device_compilers[device_name].add_pulse( port=port, clock=clock, pulse_info=combined_data ) for acq_data in op_data.data["acquisition_info"]: if "t0" in acq_data: acq_start_time = operation_start_time + acq_data["t0"] else: acq_start_time = operation_start_time port = acq_data["port"] clock = acq_data["clock"] if port is None: continue hashed_dict = without(acq_data, ["t0", "waveforms"]) hashed_dict["waveforms"] = [] for acq in acq_data["waveforms"]: if "t0" in acq: # TODO 'without' will raise a KeyError if the key is not already # present. Keep only the else-part and update the requirements when # quantify-core!438 is in the latest release. hashed_dict["waveforms"].append(without(acq, ["t0"])) else: hashed_dict["waveforms"].append(acq) combined_data = OpInfo( name=op_data.data["name"], data=acq_data, timing=acq_start_time, ) if (port, clock) not in portclock_mapping: raise KeyError( f"Could not assign acquisition data to device. The combination " f"of port {port} and clock {clock} could not be found " f"in hardware configuration.\n\nAre both the port and clock " f"specified in the hardware configuration?\n\n" f"Relevant operation:\n{combined_data}." ) device_name = portclock_mapping[(port, clock)] device_compilers[device_name].add_acquisition( port=port, clock=clock, acq_info=combined_data )
@deprecated( "0.16.0", "`convert_hw_config_to_portclock_configs_spec` will be removed in a future " "version.", )
[docs]def convert_hw_config_to_portclock_configs_spec( hw_config: Dict[str, Any], ) -> Dict[str, Any]: """ Converts possibly old hardware configs to the new format introduced by the new dynamic sequencer allocation feature. Manual assignment between sequencers and port-clock combinations under each output is removed, and instead only a list of port-clock configurations is specified, under the new ``"portclock_configs"`` key. Furthermore, we scan for ``"latency_correction"`` defined at sequencer or portclock_configs level and store under ``"port:clock"`` under toplevel ``"latency_corrections"`` key. Parameters ---------- hw_config The hardware config to be upgraded to the new specification. Returns ------- : A hardware config compatible with the specification required by the new dynamic sequencer allocation feature. """ def _update_hw_config(nested_dict, max_depth=4): if max_depth == 0: return # List is needed because the dictionary keys are changed during recursion for key, value in list(nested_dict.items()): if isinstance(key, str) and re.match(r"^seq\d+$", key): nested_dict["portclock_configs"] = nested_dict.get( "portclock_configs", [] ) # Move latency_corrections to parent level of hw_config if "latency_correction" in value.keys(): hw_config["latency_corrections"] = hw_config.get( "latency_corrections", {} ) latency_correction_key = f"{value['port']}-{value['clock']}" hw_config["latency_corrections"][latency_correction_key] = value[ "latency_correction" ] del value["latency_correction"] nested_dict["portclock_configs"].append(value) del nested_dict[key] elif isinstance(value, dict): _update_hw_config(value, max_depth - 1) hw_config = deepcopy(hw_config) _update_hw_config(hw_config) return hw_config
[docs]def calc_from_units_volt( voltage_range, name: str, param_name: str, cfg: Dict[str, Any] ) -> Optional[float]: """ Helper method to calculate the offset from mV or V. Then compares to given voltage range, and throws a ValueError if out of bounds. Parameters ---------- voltage_range The range of the voltage levels of the device used. name The name of the device used. param_name The name of the current parameter the method is used for. cfg The hardware config of the device used. Returns ------- : The normalized offsets. Raises ------ RuntimeError When a unit range is given that is not supported, or a value is given that falls outside the allowed range. """ offset_in_config = cfg.get(param_name, None) # Always in volts if offset_in_config is None: return None conversion_factor = 1 if voltage_range.units == "mV": conversion_factor = 1e3 elif voltage_range.units != "V": raise RuntimeError( f"Parameter {param_name} of {name} specifies " f"the units {voltage_range.units}, but the Qblox " f"backend only supports mV and V." ) calculated_offset = offset_in_config * conversion_factor if ( calculated_offset < voltage_range.min_val or calculated_offset > voltage_range.max_val ): raise ValueError( f"Attempting to set {param_name} of {name} to " f"{offset_in_config} V. {param_name} has to be between " f"{voltage_range.min_val / conversion_factor} and " f"{voltage_range.max_val / conversion_factor} V!" ) return calculated_offset
[docs]def extract_acquisition_metadata_from_acquisitions( acquisitions: List[OpInfo], repetitions: int ) -> AcquisitionMetadata: """ Variant of :func:`~quantify_scheduler.helpers.schedule.extract_acquisition_metadata_from_acquisition_protocols` for use with the Qblox backend. """ return extract_acquisition_metadata_from_acquisition_protocols( acquisition_protocols=[acq.data for acq in acquisitions], repetitions=repetitions, )
[docs]def single_scope_mode_acquisition_raise(sequencer_0, sequencer_1, module_name): """ Raises an error stating that only one scope mode acquisition can be used per module. Parameters ---------- sequencer_0 First sequencer which attempts to use the scope mode acquisition. sequencer_1 Second sequencer which attempts to use the scope mode acquisition. module_name Name of the module. Raises ------ ValueError Always raises the error message. """ raise ValueError( f"Both sequencer '{sequencer_0}' and '{sequencer_1}' " f"of '{module_name}' attempts to perform scope mode acquisitions. " f"Only one sequencer per device can " f"trigger raw trace capture.\n\nPlease ensure that " f"only one port-clock combination performs " f"raw trace acquisition per instrument." )
[docs]def generate_hardware_config(compilation_config: CompilationConfig): """ Extract the old-style Qblox hardware config from the CompilationConfig. Parameters ---------- config: CompilationConfig CompilationConfig from which hardware config is extracted. Returns ------- hardware_config : dict Qblox hardware configuration. Raises ------ KeyError If the CompilationConfig.connectivity does not contain a hardware config. ValueError If a value is specified in both the hardware options and the hardware config. RuntimeError If no external local oscillator is found in the generated Qblox hardware configuration. """ if not isinstance(compilation_config.connectivity, Dict): raise KeyError( f"CompilationConfig.connectivity does not contain a " f"hardware config dict:\n {compilation_config.connectivity=}" ) hardware_config = deepcopy(compilation_config.connectivity) hardware_options = compilation_config.hardware_options # Add latency corrections from hardware options to hardware config latency_corrections = hardware_options.dict()["latency_corrections"] legacy_latency_corrections = hardware_config.get("latency_corrections") if latency_corrections is None: pass elif legacy_latency_corrections is None: hardware_config["latency_corrections"] = latency_corrections elif legacy_latency_corrections != latency_corrections: raise ValueError( f"Trying to set latency corrections to {latency_corrections} from " f"the hardware options while it has previously been set to " f"{legacy_latency_corrections} in the hardware config. To avoid conflicting " f"settings, please make sure these corrections are only set in one place." ) # Add distortion corrections from hardware options to hardware config distortion_corrections = hardware_options.dict()["distortion_corrections"] legacy_distortion_corrections = hardware_config.get("distortion_corrections") if distortion_corrections is None: pass elif legacy_distortion_corrections is None: hardware_config["distortion_corrections"] = distortion_corrections elif legacy_distortion_corrections != distortion_corrections: raise ValueError( f"Trying to set distortion corrections to {distortion_corrections} from " f"the hardware options while it has previously been set to " f"{legacy_distortion_corrections} in the hardware config. To avoid conflicting " f"settings, please make sure these corrections are only set in one place." ) if compilation_config.hardware_options.modulation_frequencies is not None: for port, clock in find_all_port_clock_combinations(hardware_config): if ( pc_mod_freqs := compilation_config.hardware_options.modulation_frequencies.get( f"{port}-{clock}" ) ) is None: # No modulation frequencies to set for this port-clock. continue pc_path = find_port_clock_path( hardware_config=hardware_config, port=port, clock=clock ) # Set the interm_freq in the port-clock config. pc_config = hardware_config for key in pc_path: pc_config = pc_config[key] legacy_interm_freq = pc_config.get("interm_freq", "not_present") # Using default="not_present" because IF=None is also a valid setting if legacy_interm_freq == "not_present": pc_config["interm_freq"] = pc_mod_freqs.interm_freq elif legacy_interm_freq != pc_mod_freqs.interm_freq: raise ValueError( f"Trying to set IF for {port=}, {clock=} to" f" {pc_mod_freqs.interm_freq} from the hardware options while it" f" has previously been set to {legacy_interm_freq} in the hardware" f" config. To avoid conflicting settings, please make sure this" f" value is only set in one place." ) # Extract instrument config and output config. instr_config = hardware_config # Exclude the port-clock config index, "portclock_config", and "complex_output_X" keys. for key in pc_path[:-3]: instr_config = instr_config[key] output_config = instr_config[pc_path[-3]] # If RF module, set the lo frequency in the output config: if "RF" in instr_config["instrument_type"]: legacy_lo_freq = output_config.get("lo_freq", "not_present") # Using default="not_present" because lo_freq=None is also a valid setting if legacy_lo_freq == "not_present": output_config["lo_freq"] = pc_mod_freqs.lo_freq elif legacy_lo_freq != pc_mod_freqs.lo_freq: raise ValueError( f"Trying to set frequency for {lo_name} to" f" {pc_mod_freqs.lo_freq} from the hardware options while" f" it has previously been set to {legacy_lo_freq} in" f" the hardware config. To avoid conflicting settings," f" please make sure this value is only set in one place." ) # Else, set the lo frequency in the external lo config: else: lo_name: str = output_config["lo_name"] if (lo_config := hardware_config.get(lo_name)) is None: raise RuntimeError( f"External local oscillator '{lo_name}' set to " f"be used for {port=} and {clock=} not found! Make " f"sure it is present in the hardware configuration." ) legacy_lo_freq = lo_config.get("frequency", "not_present") # Using default="not_present" because lo_freq=None is also a valid setting if legacy_lo_freq == "not_present": lo_config["frequency"] = pc_mod_freqs.lo_freq elif legacy_lo_freq != pc_mod_freqs.lo_freq: raise ValueError( f"Trying to set frequency for {lo_name} to" f" {pc_mod_freqs.lo_freq} from the hardware options while" f" it has previously been set to {legacy_lo_freq} in" f" the hardware config. To avoid conflicting settings," f" please make sure this value is only set in one place." ) return hardware_config