piel.types

Top Level Types Declaration, all should be imported here.

These types are intended to be pure static types. They can only contain parameter definitions of the data types, add data type validators, and the only functions that can be added in these types is overwriting the base class base hidden methods. No other methods can be added here. This is because these classes are intended to be pure data types which are operated upon purely. If we begin adding custom methods on the type definitions, not only do they become bloated, but functional composition complexity is increased and the “static” data types become a hell to manage.

Submodules

• piel.types.analogue
• piel.types.connectivity
• piel.types.constants
• piel.types.core
• piel.types.digital
• piel.types.digital_electro_optic
• piel.types.electrical
• piel.types.electro_optic
• piel.types.electronic
• piel.types.environment
• piel.types.experimental
• piel.types.file_system
• piel.types.integration
• piel.types.materials
• piel.types.metrics
• piel.types.photonic
• piel.types.physical
• piel.types.quantity
• piel.types.radio_frequency
• piel.types.reference
• piel.types.signal
• piel.types.symbolic
• piel.types.units

Attributes

PathTypes
NumericalTypes
ArrayTypes
TupleIntType
TupleFloatType
TupleNumericalType
PackageArrayType
ModuleType
c
ConnectionTypes
PortTypes
ComponentTypes
TimeMetricsTypes	Corresponds to all the implemented timing metrics accordingly.
ZeroTimeMetrics	Default zero-time metrics defined.
DigitalLogicModule
AbstractBitsType	Alias for measurement representing digital bits.
BitsType	A type representing binary digital bits.
BitsList	An iterable collection of AbstractBitsType elements.
DigitalRunID
HDLSimulator	A literal type representing supported HDL simulators.
HDLTopLevelLanguage	A literal type representing top-level hardware description languages.
LogicSignalsList	A list of strings representing the names of logic signals.
LogicImplementationType
TruthTableLogicType
DCMeasurementDataTypes
DCMeasurementDataCollectionTypes
MeasurementDataTypes
MeasurementDataCollectionTypes
FrequencyMeasurementDataTypes
VoltageCurrentSignalNamePair
FrequencyMeasurementConfigurationTypes
FrequencyMeasurementTypes
MeasurementTypes
MeasurementConfigurationTypes
MeasurementCollectionTypes
PhaseMapType	Alias for phase map measurement.
PhaseTransitionTypes	A literal type for phase transition measurement.
SwitchFunctionParameter
SParameterCollection
ElectronicCircuitComponent	PhotonicCircuitComponent:
RFAmplifierTypes
ProjectType
CircuitComponent
MaterialReferenceType	MaterialReferenceType:
MaterialReferencesTypes	MaterialReferencesTypes:
MaterialSpecificationType	MaterialSpecificationType:
PhotonicCircuitComponent	PhotonicCircuitComponent:
OpticalTransmissionCircuit	OpticalTransmissionCircuit:
RecursiveNetlist	RecursiveNetlist:
SParameterMatrixTuple	SParameterMatrixTuple:
ElectricalSignalDomains
QuantityTypesDC
PhasorTypes	Different ways to represent frequency-domain information. In principle, both array and individual representations of
FrequencyTransmissionModel	Corresponds to a container that contains a s-parameter transmission model, for example.
FrequencyTransmissionList
DataTimeSignalData
EdgeTransitionAnalysisTypes
MultiTimeSignalData
MultiDataTimeSignal	Collection of DataTimeSignals that can be used to analyse a set of signals together in a particular files flow.
MultiDataTimeSignalCollectionTypes
MultiDataTimeSignalAnalysisTypes
DataTimeSignalAnalysisTypes
SignalTimeSources
BaseSIUnitNameList
A
dB
dBm
degree
GHz
Hz
nm
ns
m
MHz
mm2
mW
ohm
ps
ratio
s
us
W
V

Classes

PielBaseModel	A base model class that serves as the foundation for other measurement in the project.
Instance	This represents the fundamental data structure of an element in connectivity
Connection	This represents the fundamental data structure to identify a connection between two connection.
Component	This represents the fundamental data structure to identify a component with connection and internal or external connectivity.
Port	This represents the fundamental data structure to identify a port.
ComponentCollection	This represents the fundamental data structure of an element in connectivity
PhysicalComponent	Represents the data of a physical component or device.
PhysicalConnection	Describes a set of physical connection which are all connected. Represents a physical connection between interfaces.
PhysicalPort	This refers to any form of physical port which can be connected to. The socket refers to the corresponding physical location where such a port is connected to.
ComponentMetrics	Note that a given metrics needs to be matched to a given environment in which the measurements are performed.
TimeMetric	This class contains stastical timing information about a given path.
DispersiveTimeMetrics	A dispersive time-metrics is useful to represent multi-frequency timing information
TruthTable	A model representing a truth table for a digital circuit, including its input and output connection.
BitPhaseMap	A model representing a mapping between digital bits and their corresponding phases.
Environment	Data structure to define a corresponding environment.
Cryostat	This represents the fundamental data structure to identify a component with connection and internal or external connectivity.
TemperatureStage	Standard definition for a generic temperature stage.
Sourcemeter	Represents a sourcemeter.
SourcemeterConfiguration	This class corresponds to the configuration of data which is just inherent to the Sourcemeter connectivity and configuration,
Multimeter	Represents a multimeter.
MultimeterConfiguration	This class corresponds to the configuration of data which is just inherent to the Multimeter connectivity and configuration,
Device	Corresponds to the abstraction of a given device measurement.
DeviceConfiguration	A base model class that serves as the foundation for other measurement in the project.
MeasurementDevice	Corresponds to the abstraction of a given device measurement.
ExperimentInstance	This is a specific instance of an measurement configuration. It can be the result of serialization a given
Experiment	This represents the fundamental data structure of an element in connectivity
ExperimentCollection	This class contains a collection of different experiments,
VNA	Represents a vector-network analyser.
VNAConfiguration	This class corresponds to the configuration of data which is just inherent to the VNA connectivity and configuration,
MeasurementConfiguration	Standard definition for a measurement configuration.
Measurement	Standard definition for a measurement. This should be the container for all the measurement files, it is not the data container.
MeasurementCollection	Generic class for MeasurementCollection
DCSweepMeasurementDataCollection	This represents the fundamental data structure of an element in connectivity
DCMeasurementDataCollection	This represents the fundamental data structure of an element in connectivity
MeasurementData	This represents the fundamental data structure of an element in connectivity
MeasurementDataCollection	This represents the fundamental data structure of an element in connectivity
ExperimentData	This is a definition of a collection of measurement data.
ExperimentDataCollection	This represents the fundamental data structure of an element in connectivity
VNASParameterMeasurementData	This represents the fundamental data structure of an element in connectivity
VNASParameterMeasurementDataCollection	This represents the fundamental data structure of an element in connectivity
VNAPowerSweepMeasurementData	This represents the fundamental data structure of an element in connectivity
FrequencyMeasurementDataCollection	This represents the fundamental data structure of an element in connectivity
PropagationDelayMeasurementData	Standard definition for a collection of files that are part of a propagation delay measurement.
PropagationDelayMeasurementDataCollection	This represents the fundamental data structure of an element in connectivity
OscilloscopeMeasurementData	Standard definition for a collection of files that are part of a generic oscilloscope measurement
OscilloscopeMeasurementDataCollection	This represents the fundamental data structure of an element in connectivity
ElectroOpticDCMeasurement	Standard definition for a measurement. This should be the container for all the measurement files, it is not the data container.
ElectroOpticDCMeasurementCollection	Generic class for MeasurementCollection
VNASParameterMeasurementConfiguration	Standard definition for a measurement configuration.
VNAPowerSweepMeasurementConfiguration	Standard definition for a measurement configuration.
VNASParameterMeasurement	Standard definition for a collection of files that are part of a S-Parameter VNA measurement.
VNAPowerSweepMeasurement	Standard definition for a collection of files that are part of a VNA measurement.
VNAPowerSweepMeasurementCollection	Generic class for MeasurementCollection
VNASParameterMeasurementCollection	Generic class for MeasurementCollection
PropagationDelayMeasurement	Standard definition for a collection of files that are part of a propagation delay measurement.
PropagationDelayMeasurementCollection	Generic class for MeasurementCollection
PropagationDelayMeasurementConfiguration	Standard definition for a measurement configuration.
OscilloscopeMeasurement	Generic, extensible OscilloscopeMeasurement
OscilloscopeMeasurementCollection	Generic class for MeasurementCollection
OscilloscopeMeasurementConfiguration	Standard definition for a measurement configuration.
Oscilloscope	Represents an oscilloscope
OscilloscopeConfiguration	This class corresponds to the configuration of data which is just inherent to the Oscilloscope connectivity and configuration,
WaveformGeneratorConfiguration	This class corresponds to the configuration of data which is just inherent to the WaveformGenerator connectivity and configuration,
WaveformGenerator	Represents a vector-network analyser.
CoaxialCableGeometryType	A base model class that serves as the foundation for other measurement in the project.
CoaxialCableHeatTransferType	All units are in watts.
CoaxialCableMaterialSpecificationType	A base model class that serves as the foundation for other measurement in the project.
DCCableGeometryType	A base model class that serves as the foundation for other measurement in the project.
DCCableHeatTransferType	All units are in watts.
DCCableMaterialSpecificationType	A base model class that serves as the foundation for other measurement in the project.
DCCable	A DC cable is a single core cable that is used to transmit direct current.
CoaxialCable	A coaxial cable is a type of electrical cable that has an inner conductor surrounded by a tubular insulating layer,
PCB	Represents the data of a physical component or device.
Short	Represents the data of a physical component or device.
Open	Represents the data of a physical component or device.
Load	Represents the data of a physical component or device.
Through	Represents the data of a physical component or device.
PowerSplitter	Represents a physical RF (Radio Frequency) component with frequency-related properties.
BiasTee	Represents a physical RF (Radio Frequency) component with frequency-related properties.
FockStatePhaseTransition	A typed dictionary representing a phase transition for Fock states in an electro-optic model.
OpticalStateTransitionCollection	A model representing transitions between optical states, specifically for Fock states in an electro-optic system.
ElectroOpticModulatorMetrics	In this class, we define the corresponding relevant metrics to enable characterizing a modulator device.
ElectroOpticModulator	This is an equivalent model of an Electro-Optical modulator.
PulsedLaserMetrics	In this class, we define the corresponding relevant metrics to enable characterizing a modulator device.
PulsedLaser	This is an equivalent model of an Electro-Optical modulator.
ElectronicCircuit	Represents the data of a physical component or device.
ElectronicChip	A model representing an electronic chip in a photonic circuit.
RFTwoPortAmplifier	Represents a physical RF (Radio Frequency) component with frequency-related properties.
RFAmplifierCollection	This represents the fundamental data structure of an element in connectivity
PowerAmplifierMetrics	A model representing the metrics for a high-voltage amplifier (HVA) or a Power Amplifier (PA).
PowerAmplifier	Represents a physical RF (Radio Frequency) component with frequency-related properties.
LNAMetrics	A model representing the metrics for a low-noise amplifier (LNA).
LowNoiseTwoPortAmplifier	Represents a physical RF (Radio Frequency) component with frequency-related properties.
ScalarMetric	Standard definition for a scalar metrics. It includes the value, mean, min, max, standard deviation and count.
ScalarMetricCollection	A collection of scalar metrics useful when analyzing multiple aspects of a design.
SignalDCCollection	This represents the fundamental data structure of an element in connectivity
SignalTraceDC	Represents a DC signal with all relevant components as defined by Ohm's law but specified through a collection of data defined by a OperatingPointContainer
SignalDC	This is used to define a collection of SignalInstances which compose a DC signal. For example,
Phasor	Contains magnitude and phase frequency response information.
PathTransmission	This represents the fundamental data structure of an element in connectivity
NetworkTransmission	This corresponds to a transmission component or array collection of the power or frequency transmission.
FrequencyMetricCollection	A base model class that serves as the foundation for other measurement in the project.
FrequencyMetric	Creates a mapping between a given input and a given scalar metrics response.
ElectroOpticDCPathTransmission	It is not logically possible to decouple the output signal from the connection at which this is measured, due to the
ElectroOpticDCNetworkTransmission	Applicable when you have multiple inputs and multiple paths
TimeSignalData	Standard definition for a relationship between a relevant files signal and a time reference array.
ExponentialSource	A base model class that serves as the foundation for other measurement in the project.
PulseSource	A base model class that serves as the foundation for other measurement in the project.
PiecewiseLinearSource	A base model class that serves as the foundation for other measurement in the project.
SineSource	A base model class that serves as the foundation for other measurement in the project.
SymbolicValue	A base model class that serves as the foundation for other measurement in the project.
Reference	A base model class that serves as the foundation for other measurement in the project.
Quantity	A base model class that serves as the foundation for other measurement in the project.
Unit	A base model class that serves as the foundation for other measurement in the project.

Package Contents

PathTypes

class PielBaseModel(/, **data: Any)

Bases: pydantic.BaseModel

A base model class that serves as the foundation for other measurement in the project. This class extends pydantic’s BaseModel and includes additional configuration settings for strict validation and immutability.

Config

A nested class to configure the behavior of the model. arbitrary_types_allowed (bool): Allows arbitrary measurement. extra (str): Forbids extra attributes not defined in the model. validate_assignment (bool): Validates fields on assignment. strict (bool): Enforces strict type validation. allow_mutation (bool): Prevents mutation of the model’s fields.

supplied_parameters() → list[str]

Returns a list of parameter names that have been supplied (i.e., are not None).

class Config

arbitrary_types_allowed = True

extra = 'ignore'

validate_assignment = True

strict = True

NumericalTypes

ArrayTypes

TupleIntType

TupleFloatType

TupleNumericalType

PackageArrayType

ModuleType

class Instance(/, **data: Any)

Bases: piel.types.PielBaseModel

This represents the fundamental data structure of an element in connectivity

name: str = ''

attrs: dict

c

class Connection(/, **data: Any)

Bases: piel.types.connectivity.core.Instance

This represents the fundamental data structure to identify a connection between two connection.

Note that any connection has a

ports: tuple[Port, Port] | list[Port] = ()

time: piel.types.connectivity.timing.TimeMetricsTypes

class Component(/, **data: Any)

Bases: piel.types.connectivity.core.Instance

This represents the fundamental data structure to identify a component with connection and internal or external connectivity.

ports: list[Port] = []

connections: list[Connection] = []

components: list[Component] = []

Note the recursive relationship that a component can be composed of multiple components.

metrics: list[piel.types.connectivity.metrics.ComponentMetrics] = []

Note that a given component might have a set of metrics corresponding to multiple variations of the testing conditions.

get_port(port_name: str) → Port | None

Get a port by its name.

class Port(/, **data: Any)

Bases: piel.types.connectivity.core.Instance

This represents the fundamental data structure to identify a port.

parent_component_name: str = ''

ConnectionTypes

PortTypes

ComponentTypes

class ComponentCollection(/, **data: Any)

Bases: piel.types.connectivity.abstract.Instance

This represents the fundamental data structure of an element in connectivity

components: list[ComponentTypes] = []

class PhysicalComponent(/, **data: Any)

Bases: piel.types.connectivity.abstract.Component

Represents the data of a physical component or device.

ports: list[PhysicalPort | piel.types.connectivity.abstract.Port] | tuple[PhysicalPort | piel.types.connectivity.abstract.Port] = []

connections: list[PhysicalConnection | piel.types.connectivity.abstract.Connection] | tuple[PhysicalConnection | piel.types.connectivity.abstract.Connection] = []

components: list[piel.types.connectivity.abstract.Component | PhysicalComponent] = []

Note the recursive relationship that a component can be composed of multiple components.

environment: piel.types.environment.Environment

manufacturer: str = ''

The manufacturer of the device.

model: str = ''

The model of the device.

class PhysicalConnection(/, **data: Any)

Bases: piel.types.core.PielBaseModel

Describes a set of physical connection which are all connected. Represents a physical connection between interfaces.

The components represent the physical implementation of the connections for the same connection index.

connections: list[piel.types.connectivity.abstract.Connection | Any] = []

components: tuple[piel.types.connectivity.abstract.Component, Ellipsis] | list[piel.types.connectivity.abstract.Component] = []

class PhysicalPort(/, **data: Any)

Bases: piel.types.connectivity.abstract.Port

This refers to any form of physical port which can be connected to. The socket refers to the corresponding physical location where such a port is connected to.

domain: piel.types.signal.core.ElectricalSignalDomains | None = None

connector: str = ''

manifold: str = ''

class ComponentMetrics(/, **data: Any)

Bases: piel.types.connectivity.abstract.Instance

Note that a given metrics needs to be matched to a given environment in which the measurements are performed. For example, room temperature metrics are not equivalent to cryogenic metrics measurements, and as such require a collection of variables.

reference: piel.types.reference.Reference

environment: piel.types.environment.Environment

class TimeMetric(/, **data: Any)

Bases: piel.types.metrics.ScalarMetric

This class contains stastical timing information about a given path.

Notes

Each component has some relevant time metrics which characterize the propagation of a signal across it. Now, this is more intricate in the case of dispersive of multi-frequency signals propagating through a device since propagation is dependent on signal frequency. One way to conceptualize it is that each frequency corresponds to an individual frequency, but this ignores recombination or superposition between the frequencies in a dispersive model.

Also, timing information is in relation to the input signal that is being propagated through a component.

We can create a higher level dispersive time metrics for multi-frequency components based on this one.

The relevant timing we are interested in is as follows, as it has multiple definitions

• In-to-Out Timing Propagation through a component

• Group Delay of a signal through an interconnect

• 10% to 90% rise time of the output waveform of an active component

Having a shared timing definition is essential to perform correct timing analysis

value: piel.types.core.NumericalTypes = 0

mean: piel.types.core.NumericalTypes | None = 0

min: piel.types.core.NumericalTypes | None = 0

max: piel.types.core.NumericalTypes | None = 0

standard_deviation: piel.types.core.NumericalTypes | None = 0

unit: piel.types.units.Unit

class DispersiveTimeMetrics(/, **data: Any)

Bases: piel.types.connectivity.core.Instance

A dispersive time-metrics is useful to represent multi-frequency timing information based on the harmonic nature of signals.

frequency_group: dict[float, TimeMetric]

Definition of a mutli-frequency component.

TimeMetricsTypes

Corresponds to all the implemented timing metrics accordingly.

ZeroTimeMetrics

Default zero-time metrics defined.

DigitalLogicModule

AbstractBitsType

Alias for measurement representing digital bits. Can be one of: - str: A string representation of bits. - bytes: A byte representation of bits. - int: An integer representation of bits.

Type:

AbstractBitsType

BitsType

A type representing binary digital bits. It is an alias for the ‘str’ type.

Type:

BitsType

BitsList

An iterable collection of AbstractBitsType elements. Represents a sequence of digital bits.

Type:

BitsList

DigitalRunID

HDLSimulator

A literal type representing supported HDL simulators. Can be one of: - “icarus”: Refers to Icarus Verilog simulator. - “verilator”: Refers to Verilator simulator.

Type:

HDLSimulator

HDLTopLevelLanguage

A literal type representing top-level hardware description languages. Can be one of: - “verilog”: Refers to the Verilog HDL. - “vhdl”: Refers to the VHDL HDL.

Type:

HDLTopLevelLanguage

LogicSignalsList

A list of strings representing the names of logic signals.

Type:

LogicSignalsList

LogicImplementationType

class TruthTable(/, **data: Any)

Bases: piel.types.core.PielBaseModel

A model representing a truth table for a digital circuit, including its input and output connection.

input_ports

List of input signal names for the truth table.

Type:

LogicSignalsList

output_ports

List of output signal names for the truth table.

Type:

LogicSignalsList

Properties:

keys_list (list[str]): A combined list of input and output signal names. dataframe (pd.DataFrame): A pandas DataFrame representation of the truth table, excluding input and output connection. implementation_dictionary (dict): A dictionary including only the keys specified within input_ports and output_ports.

model_config

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

input_ports: LogicSignalsList

List of input signal names for the truth table.

Type:

input_ports (LogicSignalsList)

output_ports: LogicSignalsList

List of output signal names for the truth table.

Type:

output_ports (LogicSignalsList)

property ports_list: list[str]

Returns a combined list of input and output signal names.

Returns:

The concatenated list of input and output connection.

Return type:

list[str]

property dataframe: pandas.DataFrame

Returns a pandas DataFrame representation of the truth table, excluding the input and output connection.

Returns:

A DataFrame with the truth table files, excluding input and output port keys.

Return type:

pd.DataFrame

property implementation_dictionary: dict

Returns a dictionary including only the keys specified within input_ports and output_ports.

Returns:

A dictionary with keys that are part of the input and output connection.

Return type:

dict

TruthTableLogicType

class BitPhaseMap(/, **data: Any)

Bases: piel.types.core.PielBaseModel

A model representing a mapping between digital bits and their corresponding phases.

bits

An iterable collection of bits. Can be a list, tuple, or numpy array of elements that match the AbstractBitsType.

Type:

list[AbstractBitsType] | tuple[AbstractBitsType] | np.ndarray

phase

An iterable collection of phases. Can be a list, tuple, or numpy array of elements that match the NumericalTypes.

Type:

list[NumericalTypes] | tuple[NumericalTypes] | np.ndarray

Properties:

dataframe (pd.DataFrame):

A pandas DataFrame representation of the BitPhaseMap, combining the bits and phases into a tabular format.

bits: list[piel.types.digital.BitsType] | tuple[piel.types.digital.BitsType] | numpy.ndarray

bits (list[AbstractBitsType] | tuple[AbstractBitsType] | np.ndarray): An iterable collection of bits. Can be a list, tuple, or numpy array of elements that are of type AbstractBitsType.

phase: list[piel.types.core.NumericalTypes] | tuple[piel.types.core.NumericalTypes] | numpy.ndarray

phase (list[NumericalTypes] | tuple[NumericalTypes] | np.ndarray): An iterable collection of phases. Can be a list, tuple, or numpy array of elements that are of type NumericalTypes.

property dataframe: pandas.DataFrame

Returns a pandas DataFrame representation of the BitPhaseMap.

Returns:

A DataFrame containing the bits and their corresponding phases.

Return type:

pd.DataFrame

class Environment(/, **data: Any)

Bases: piel.types.core.PielBaseModel

Data structure to define a corresponding environment.

temperature_K: float = 293

region: str = ''

class Cryostat(/, **data: Any)

Bases: piel.types.connectivity.abstract.Component

This represents the fundamental data structure to identify a component with connection and internal or external connectivity.

temperature_stages: list[TemperatureStage] = []

class TemperatureStage(/, **data: Any)

Bases: piel.types.environment.Environment, piel.types.connectivity.abstract.Component

Standard definition for a generic temperature stage.

surface_area_m2: float = None

class Sourcemeter(/, **data: Any)

Bases: piel.types.experimental.device.Device

Represents a sourcemeter.

configuration: SourcemeterConfiguration = None

class SourcemeterConfiguration(/, **data: Any)

Bases: piel.types.experimental.device.DeviceConfiguration

This class corresponds to the configuration of data which is just inherent to the Sourcemeter connectivity and configuration, not the measurement setup connectivity.

voltage_set_V: float | None = None

voltage_range_V: tuple | None = None

current_limit_A: float | None = None

voltage_limit_V: float | None = None

class Multimeter(/, **data: Any)

Bases: piel.types.experimental.device.Device

Represents a multimeter.

class MultimeterConfiguration(/, **data: Any)

Bases: piel.types.experimental.device.DeviceConfiguration

This class corresponds to the configuration of data which is just inherent to the Multimeter connectivity and configuration,

class Device(/, **data: Any)

Bases: piel.types.connectivity.physical.PhysicalComponent

Corresponds to the abstraction of a given device measurement.

configuration: DeviceConfiguration | None = None

serial_number: str = ''

class DeviceConfiguration(/, **data: Any)

Bases: piel.types.core.PielBaseModel

A base model class that serves as the foundation for other measurement in the project. This class extends pydantic’s BaseModel and includes additional configuration settings for strict validation and immutability.

Config

A nested class to configure the behavior of the model. arbitrary_types_allowed (bool): Allows arbitrary measurement. extra (str): Forbids extra attributes not defined in the model. validate_assignment (bool): Validates fields on assignment. strict (bool): Enforces strict type validation. allow_mutation (bool): Prevents mutation of the model’s fields.

supplied_parameters() → list[str]

Returns a list of parameter names that have been supplied (i.e., are not None).

class MeasurementDevice(/, **data: Any)

Bases: Device

Corresponds to the abstraction of a given device measurement.

measurement: piel.types.experimental.measurements.core.MeasurementConfiguration | None = None

Contains the measurement information.

class ExperimentInstance(/, **data: Any)

Bases: piel.types.connectivity.core.Instance

This is a specific instance of an measurement configuration. It can be the result of serialization a given experiment configuration. The experiment contains all devices that correspond a specific setup. Each device contains a particular configuration, or may have information about the environment, etc.

components: list[piel.types.connectivity.generic.ComponentTypes] | tuple[piel.types.connectivity.generic.ComponentTypes] = []

Contains all references to the instantiated devices.

connections: list[piel.types.connectivity.generic.ConnectionTypes] | tuple[piel.types.connectivity.generic.ConnectionTypes] = []

All the connectivity information is stored here.

goal: str = ''

The goal of the experiment test.

parameters: dict

A dictionary of reference parameters in this measurement instance. Does not contain all the serialised measurement data.

index: int = 0

A defined index of the experiment instance tuple.

date_configured: str = ''

The date the experiment was configured.

date_measured: str = ''

The date the experiment was measured.

measurement_configuration_list: list[piel.types.experimental.measurements.generic.MeasurementConfigurationTypes] = []

class Experiment(/, **data: Any)

Bases: piel.types.connectivity.core.Instance

This represents the fundamental data structure of an element in connectivity

name: str = ''

Every experiment is required to have a name.

goal: str = ''

The goal of the complete experiment.

experiment_instances: list[ExperimentInstance] = []

Contains all the experiment instances.

parameters_list: list[dict]

List of basic important parameters in dictionaries used to do basic metadata analysis of the experiment.

parent_directory: piel.types.core.PathTypes = ''

Optional parameter to specify the parent_directory of the Experiment, where the directories containing the data and metadata of the ExperimentInstances are constructed.

__getitem__

property parameters

class ExperimentCollection(/, **data: Any)

Bases: piel.types.connectivity.core.Instance

This class contains a collection of different experiments, each which may contain a large set of measurements internally.

experiment_list: list[Experiment] = []

class VNA(/, **data: Any)

Bases: piel.types.experimental.device.Device

Represents a vector-network analyser.

configuration: VNAConfiguration | None = None

Just overwrites this section of the device definition.

ports: tuple[piel.types.connectivity.physical.PhysicalPort] | list[piel.types.connectivity.physical.PhysicalPort]

Defaults to a two-port VNA, defined as PORT1 and PORT2.

class VNAConfiguration(/, **data: Any)

Bases: piel.types.experimental.device.DeviceConfiguration

This class corresponds to the configuration of data which is just inherent to the VNA connectivity and configuration, not the measurement setup connectivity.

calibration_setting_name: str = ''

measurement_configuration: piel.types.experimental.measurements.generic.FrequencyMeasurementConfigurationTypes = None

class MeasurementConfiguration(/, **data: Any)

Bases: piel.types.connectivity.abstract.Instance

Standard definition for a measurement configuration.

name: str = ''

parent_directory: piel.types.core.PathTypes = ''

measurement_type: str = ''

class Measurement(/, **data: Any)

Bases: piel.types.connectivity.abstract.Instance

Standard definition for a measurement. This should be the container for all the measurement files, it is not the data container.

name: str = ''

type: str = ''

parent_directory: piel.types.core.PathTypes = ''

class MeasurementCollection(/, **data: Any)

Bases: piel.types.connectivity.abstract.Instance

Generic class for MeasurementCollection

type: str = ''

collection: list[Measurement] = []

class DCSweepMeasurementDataCollection(/, **data: Any)

Bases: piel.types.experimental.measurements.data.core.MeasurementDataCollection

This represents the fundamental data structure of an element in connectivity

collection: list[piel.types.signal.dc_data.SignalDCCollection] = []

class DCMeasurementDataCollection(/, **data: Any)

Bases: piel.types.experimental.measurements.data.core.MeasurementDataCollection

This represents the fundamental data structure of an element in connectivity

collection: list[DCMeasurementDataTypes] | DCSweepMeasurementDataCollection = []

DCMeasurementDataTypes

DCMeasurementDataCollectionTypes

class MeasurementData(/, **data: Any)

Bases: piel.types.connectivity.core.Instance

This represents the fundamental data structure of an element in connectivity

type: str | None = ''

class MeasurementDataCollection(/, **data: Any)

Bases: piel.types.connectivity.core.Instance

This represents the fundamental data structure of an element in connectivity

type: str = ''

collection: list[MeasurementData] = []

__getitem__

class ExperimentData(/, **data: Any)

Bases: piel.types.connectivity.core.Instance

This is a definition of a collection of measurement data.

experiment: piel.types.experimental.experiment.Experiment = None

data: piel.types.experimental.measurements.data.generic.MeasurementDataCollectionTypes = None

__getitem__

class ExperimentDataCollection(/, **data: Any)

Bases: piel.types.connectivity.core.Instance

This represents the fundamental data structure of an element in connectivity

collection: list[ExperimentData] = []

MeasurementDataTypes

MeasurementDataCollectionTypes

FrequencyMeasurementDataTypes

class VNASParameterMeasurementData(/, **data: Any)

Bases: piel.types.experimental.measurements.data.core.MeasurementData

This represents the fundamental data structure of an element in connectivity

type: str = 'VNASParameterMeasurementData'

network: piel.types.signal.frequency.transmission.FrequencyTransmissionModel = None

class VNASParameterMeasurementDataCollection(/, **data: Any)

Bases: piel.types.experimental.measurements.data.core.MeasurementDataCollection

This represents the fundamental data structure of an element in connectivity

type: str = 'VNASParameterMeasurementDataCollection'

collection: list[VNASParameterMeasurementData] = []

class VNAPowerSweepMeasurementData(/, **data: Any)

Bases: piel.types.experimental.measurements.data.core.MeasurementData

This represents the fundamental data structure of an element in connectivity

type: str = 'VNAPowerSweepMeasurementData'

network: piel.types.signal.frequency.transmission.FrequencyTransmissionModel | None = None

class FrequencyMeasurementDataCollection(/, **data: Any)

Bases: piel.types.experimental.measurements.data.core.MeasurementDataCollection

This represents the fundamental data structure of an element in connectivity

type: str = 'FrequencyMeasurementDataCollection'

collection: list[FrequencyMeasurementDataTypes] = []

class PropagationDelayMeasurementData(/, **data: Any)

Bases: piel.types.experimental.measurements.data.core.MeasurementData

Standard definition for a collection of files that are part of a propagation delay measurement.

The collection includes the device waveform, the measurement files and the reference waveform as per a propagation delay measurement.

measurements

The collection of signal measurements.

Type:

Optional[SignalMetricsMeasurementCollection]

dut_waveform

The device waveform.

Type:

Optional[TimeSignalData]

reference_waveform

The reference waveform.

Type:

Optional[TimeSignalData]

type: str = 'PropagationDelayMeasurementData'

measurements: piel.types.metrics.ScalarMetricCollection | None = None

dut_waveform: piel.types.signal.time_data.TimeSignalData | None = None

reference_waveform: piel.types.signal.time_data.TimeSignalData | None = None

class PropagationDelayMeasurementDataCollection(/, **data: Any)

Bases: piel.types.experimental.measurements.data.core.MeasurementDataCollection

This represents the fundamental data structure of an element in connectivity

type: str = 'PropagationDelayMeasurementDataCollection'

collection: list[PropagationDelayMeasurementData] = []

class OscilloscopeMeasurementData(/, **data: Any)

Bases: piel.types.experimental.measurements.data.core.MeasurementData

Standard definition for a collection of files that are part of a generic oscilloscope measurement

The collection includes a list of waveform files, and a measurements file.

measurements

The collection of signal measurements.

Type:

Optional[SignalMetricsMeasurementCollection]

waveform_list

The collection of waveforms.

Type:

MultiTimeSignalData

type: str = 'OscilloscopeMeasurementData'

measurements: piel.types.metrics.ScalarMetricCollection | None = None

waveform_list: piel.types.signal.time_data.MultiTimeSignalData = []

class OscilloscopeMeasurementDataCollection(/, **data: Any)

Bases: piel.types.experimental.measurements.data.core.MeasurementDataCollection

This represents the fundamental data structure of an element in connectivity

type: str = 'OscilloscopeMeasurementDataCollection'

collection: list[OscilloscopeMeasurementData] = []

VoltageCurrentSignalNamePair

class ElectroOpticDCMeasurement(/, **data: Any)

Bases: piel.types.experimental.measurements.core.Measurement

Standard definition for a measurement. This should be the container for all the measurement files, it is not the data container.

dc_transmission_file: piel.types.core.PathTypes

connection: piel.types.connectivity.generic.ConnectionTypes

class ElectroOpticDCMeasurementCollection(/, **data: Any)

Bases: piel.types.experimental.measurements.core.MeasurementCollection

Generic class for MeasurementCollection

collection: list[ElectroOpticDCMeasurement]

class VNASParameterMeasurementConfiguration(/, **data: Any)

Bases: piel.types.experimental.measurements.core.MeasurementConfiguration

Standard definition for a measurement configuration.

measurement_configuration_type: str = 'VNASParameterMeasurementConfiguration'

frequency_range_Hz: tuple[float, float] | list[float] = []

sweep_points: int = 0

test_port_power_dBm: float = 0.0

class VNAPowerSweepMeasurementConfiguration(/, **data: Any)

Bases: piel.types.experimental.measurements.core.MeasurementConfiguration

Standard definition for a measurement configuration.

measurement_configuration_type: str = 'VNAPowerSweepMeasurementConfiguration'

base_frequency_Hz: float = 0.0

power_range_dBm: tuple[float, float] | list[float] = []

class VNASParameterMeasurement(/, **data: Any)

Bases: piel.types.experimental.measurements.core.Measurement

Standard definition for a collection of files that are part of a S-Parameter VNA measurement.

type: str = 'VNASParameterMeasurement'

spectrum_file: piel.types.core.PathTypes = ''

class VNAPowerSweepMeasurement(/, **data: Any)

Bases: piel.types.experimental.measurements.core.Measurement

Standard definition for a collection of files that are part of a VNA measurement.

type: str = 'VNAPowerSweepMeasurement'

spectrum_file: piel.types.core.PathTypes = ''

class VNAPowerSweepMeasurementCollection(/, **data: Any)

Bases: piel.types.experimental.measurements.core.MeasurementCollection

Generic class for MeasurementCollection

type: str = 'VNAPowerSweepMeasurementCollection'

collection: list[VNAPowerSweepMeasurement] = []

class VNASParameterMeasurementCollection(/, **data: Any)

Bases: piel.types.experimental.measurements.core.MeasurementCollection

Generic class for MeasurementCollection

type: str = 'VNASParameterMeasurementCollection'

collection: list[VNASParameterMeasurement] = []

class PropagationDelayMeasurement(/, **data: Any)

Bases: piel.types.experimental.measurements.core.Measurement

Standard definition for a collection of files that are part of a propagation delay measurement. The collection includes the device name, the measurement name and the date of the measurement. This configuration requires a device waveform, a measurement file and a reference waveform as per a propagation delay measurement. TODO add link to the documentation of the propagation delay measurement.

type: str = 'PropagationDelayMeasurement'

dut_waveform_file: piel.types.core.PathTypes = ''

reference_waveform_file: piel.types.core.PathTypes = ''

measurements_file: piel.types.core.PathTypes = ''

class PropagationDelayMeasurementCollection(/, **data: Any)

Bases: piel.types.experimental.measurements.core.MeasurementCollection

Generic class for MeasurementCollection

type: str = 'PropagationDelayMeasurementCollection'

collection: list[PropagationDelayMeasurement] = []

class PropagationDelayMeasurementConfiguration(/, **data: Any)

Bases: piel.types.experimental.measurements.core.MeasurementConfiguration

Standard definition for a measurement configuration.

measurement_configuration_type: str = 'PropagationDelayMeasurementConfiguration'

class OscilloscopeMeasurement(/, **data: Any)

Bases: piel.types.experimental.measurements.core.Measurement

Generic, extensible OscilloscopeMeasurement

type: str = 'OscilloscopeMeasurement'

waveform_file_list: list[piel.types.core.PathTypes] = []

measurements_file: piel.types.core.PathTypes = ''

class OscilloscopeMeasurementCollection(/, **data: Any)

Bases: piel.types.experimental.measurements.core.MeasurementCollection

Generic class for MeasurementCollection

type: str = 'OscilloscopeMeasurementCollection'

collection: list[OscilloscopeMeasurement] = []

class OscilloscopeMeasurementConfiguration(/, **data: Any)

Bases: piel.types.experimental.measurements.core.MeasurementConfiguration

Standard definition for a measurement configuration.

measurement_configuration_type: str = 'OscilloscopeMeasurementConfiguration'

FrequencyMeasurementConfigurationTypes

FrequencyMeasurementTypes

MeasurementTypes

MeasurementConfigurationTypes

MeasurementCollectionTypes

class Oscilloscope(/, **data: Any)

Bases: piel.types.experimental.device.MeasurementDevice

Represents an oscilloscope

configuration: OscilloscopeConfiguration | None = None

Just overwrites this section of the device definition.

class OscilloscopeConfiguration(/, **data: Any)

Bases: piel.types.experimental.device.DeviceConfiguration

This class corresponds to the configuration of data which is just inherent to the Oscilloscope connectivity and configuration, not the measurement setup connectivity.

bandwidth_Hz: piel.types.metrics.ScalarMetric = None

class WaveformGeneratorConfiguration(/, **data: Any)

Bases: piel.types.experimental.device.DeviceConfiguration

This class corresponds to the configuration of data which is just inherent to the WaveformGenerator connectivity and configuration, not the measurement setup connectivity.

signal: piel.types.signal.time_sources.SignalTimeSources = None

Contains an instantiation of the signal configuration applied as a reference.

class WaveformGenerator(/, **data: Any)

Bases: piel.types.experimental.device.Device

Represents a vector-network analyser.

configuration: WaveformGeneratorConfiguration = None

Just overwrites this section of the device definition.

class CoaxialCableGeometryType(/, **data: Any)

Bases: piel.types.quantity.Quantity

A base model class that serves as the foundation for other measurement in the project. This class extends pydantic’s BaseModel and includes additional configuration settings for strict validation and immutability.

Config

A nested class to configure the behavior of the model. arbitrary_types_allowed (bool): Allows arbitrary measurement. extra (str): Forbids extra attributes not defined in the model. validate_assignment (bool): Validates fields on assignment. strict (bool): Enforces strict type validation. allow_mutation (bool): Prevents mutation of the model’s fields.

supplied_parameters() → list[str]

Returns a list of parameter names that have been supplied (i.e., are not None).

core_cross_sectional_area_m2: float | None = 0

The cross-sectional area of the core in meters squared.

length_m: float = 0

The length of the cable in meters.

sheath_cross_sectional_area_m2: float | None = 0

The cross-sectional area of the sheath in meters squared.

total_cross_sectional_area_m2: float | None = 0

The total cross-sectional area of the cable in meters squared.

class CoaxialCableHeatTransferType(/, **data: Any)

Bases: piel.types.quantity.Quantity

All units are in watts.

core: float | None = 0

The computed heat transfer in watts for the core of the cable.

sheath: float | None = 0

The computed heat transfer in watts for the sheath of the cable.

dielectric: float | None = 0

The computed heat transfer in watts for the dielectric of the cable.

total: float = 0

The total computed heat transfer in watts for the cable.

units: str = 'W'

class CoaxialCableMaterialSpecificationType(/, **data: Any)

Bases: piel.types.quantity.Quantity

A base model class that serves as the foundation for other measurement in the project. This class extends pydantic’s BaseModel and includes additional configuration settings for strict validation and immutability.

Config

A nested class to configure the behavior of the model. arbitrary_types_allowed (bool): Allows arbitrary measurement. extra (str): Forbids extra attributes not defined in the model. validate_assignment (bool): Validates fields on assignment. strict (bool): Enforces strict type validation. allow_mutation (bool): Prevents mutation of the model’s fields.

supplied_parameters() → list[str]

Returns a list of parameter names that have been supplied (i.e., are not None).

core: piel.types.materials.MaterialReferenceType | None = None

The material of the core.

sheath: piel.types.materials.MaterialReferenceType | None = None

The material of the sheath.

dielectric: piel.types.materials.MaterialReferenceType | None = None

The material of the dielectric.

supplied_parameters()

Returns a list of parameter names that have been supplied (i.e., are not None).

Returns:

A list of parameter names with non-None values.

Return type:

list[str]

class DCCableGeometryType(/, **data: Any)

Bases: piel.types.quantity.Quantity

A base model class that serves as the foundation for other measurement in the project. This class extends pydantic’s BaseModel and includes additional configuration settings for strict validation and immutability.

Config

A nested class to configure the behavior of the model. arbitrary_types_allowed (bool): Allows arbitrary measurement. extra (str): Forbids extra attributes not defined in the model. validate_assignment (bool): Validates fields on assignment. strict (bool): Enforces strict type validation. allow_mutation (bool): Prevents mutation of the model’s fields.

supplied_parameters() → list[str]

Returns a list of parameter names that have been supplied (i.e., are not None).

core_cross_sectional_area_m2: float = 0

The cross-sectional area of the core in meters squared.

length_m: float = 0

The length of the cable in meters.

total_cross_sectional_area_m2: float = 0

The total cross-sectional area of the cable in meters squared.

class DCCableHeatTransferType(/, **data: Any)

Bases: piel.types.quantity.Quantity

All units are in watts.

core: float | None = 0

The computed heat transfer in watts for the core of the cable.

total: float = 0

The total computed heat transfer in watts for the cable.

units: str = 'W'

class DCCableMaterialSpecificationType(/, **data: Any)

Bases: piel.types.quantity.Quantity

A base model class that serves as the foundation for other measurement in the project. This class extends pydantic’s BaseModel and includes additional configuration settings for strict validation and immutability.

Config

A nested class to configure the behavior of the model. arbitrary_types_allowed (bool): Allows arbitrary measurement. extra (str): Forbids extra attributes not defined in the model. validate_assignment (bool): Validates fields on assignment. strict (bool): Enforces strict type validation. allow_mutation (bool): Prevents mutation of the model’s fields.

supplied_parameters() → list[str]

Returns a list of parameter names that have been supplied (i.e., are not None).

core: piel.types.materials.MaterialReferenceType | None = None

The material of the core.

class DCCable(/, **data: Any)

Bases: Cable

A DC cable is a single core cable that is used to transmit direct current.

geometry: DCCableGeometryType | None = None

heat_transfer: DCCableHeatTransferType | None = None

material_specification: DCCableMaterialSpecificationType | None = None

class CoaxialCable(/, **data: Any)

Bases: piel.types.radio_frequency.RFPhysicalComponent

A coaxial cable is a type of electrical cable that has an inner conductor surrounded by a tubular insulating layer, surrounded by a tubular conducting shield.

geometry: CoaxialCableGeometryType | None

heat_transfer: CoaxialCableHeatTransferType | None = None

material_specification: CoaxialCableMaterialSpecificationType | None = None

class PCB(/, **data: Any)

Bases: piel.types.connectivity.physical.PhysicalComponent

Represents the data of a physical component or device.

class Short(/, **data: Any)

Bases: piel.types.PhysicalComponent

Represents the data of a physical component or device.

ports: list[piel.types.PhysicalPort]

class Open(/, **data: Any)

Bases: piel.types.PhysicalComponent

Represents the data of a physical component or device.

ports: list[piel.types.PhysicalPort]

class Load(/, **data: Any)

Bases: piel.types.PhysicalComponent

Represents the data of a physical component or device.

ports: list[piel.types.PhysicalPort]

class Through(/, **data: Any)

Bases: piel.types.PhysicalComponent

Represents the data of a physical component or device.

ports: list[piel.types.PhysicalPort]

class PowerSplitter(/, **data: Any)

Bases: piel.types.radio_frequency.RFPhysicalComponent

Represents a physical RF (Radio Frequency) component with frequency-related properties.

This class extends the PhysicalComponent class to include RF-specific attributes.

Attributes:

networkFrequencyTransmissionModel | None

A representation of the component’s frequency network, typically containing s-parameter data. This is currently a placeholder and may be None.

metricsFrequencyMetricCollection

A collection of frequency-related metrics for this RF component, including bandwidth and center transmission.

Inherits all attributes from PhysicalComponent.

Notes:

• The ‘network’ attribute is currently using a placeholder type (Any | None) and is intended to be updated with a proper s-parameter representation in the future.

• This class combines physical component properties with RF-specific metrics, making it suitable for modeling and analyzing RF devices in a physical context.

class BiasTee(/, **data: Any)

Bases: piel.types.radio_frequency.RFPhysicalComponent

Represents a physical RF (Radio Frequency) component with frequency-related properties.

This class extends the PhysicalComponent class to include RF-specific attributes.

Attributes:

networkFrequencyTransmissionModel | None

A representation of the component’s frequency network, typically containing s-parameter data. This is currently a placeholder and may be None.

metricsFrequencyMetricCollection

A collection of frequency-related metrics for this RF component, including bandwidth and center transmission.

Inherits all attributes from PhysicalComponent.

Notes:

• The ‘network’ attribute is currently using a placeholder type (Any | None) and is intended to be updated with a proper s-parameter representation in the future.

• This class combines physical component properties with RF-specific metrics, making it suitable for modeling and analyzing RF devices in a physical context.

class FockStatePhaseTransition

Bases: typing_extensions.TypedDict

A typed dictionary representing a phase transition for Fock states in an electro-optic model.

phase

The phase mapping for the transition.

Type:

PhaseMapType

input_fock_state

The input Fock state as a tuple of integers.

Type:

TupleIntType

output_fock_state

The output Fock state as a tuple of integers.

Type:

TupleIntType

target_mode_output

Indicates whether the target mode is output (1 or True) or not (0 or False).

Type:

Optional[bool | int]

phase: PhaseMapType

input_fock_state: piel.types.core.TupleIntType

output_fock_state: piel.types.core.TupleIntType

target_mode_output: bool | int | None | None

class OpticalStateTransitionCollection(/, **data: Any)

Bases: piel.types.core.PielBaseModel

A model representing transitions between optical states, specifically for Fock states in an electro-optic system.

mode_amount

The number of modes in the system.

Type:

int

target_mode_index

The index of the target mode in the system.

Type:

int

transmission_data

A list of Fock state phase transition mappings.

Type:

list[FockStatePhaseTransition]

Properties:

transition_dataframe (pd.DataFrame): A DataFrame representation of the transmission files. target_output_dataframe (pd.DataFrame): A DataFrame filtered to include only the transitions where target_mode_output is 1.

_ignore_keys: list[str] = ['unitary', 'raw_output']

model_config

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

mode_amount: int | None = None

mode_amount (int): The number of modes in the system.

target_mode_index: int | None = None

target_mode_index (int): The index of the target mode in the system.

transmission_data: list[OpticalTransmission]

transmission_data (list[FockStatePhaseTransition]): A list of dictionaries representing the phase transitions for Fock states.

property dataframe: pandas.DataFrame

Returns a full pandas DataFrame representation of the transmission files.

Returns:

A DataFrame containing the transmission files for the optical states.

Return type:

pd.DataFrame

property keys_list: list[str]

Returns a list of keys from the first entry in the transmission files, excluding specified keys.

Returns:

A list of keys from the first transmission files entry, excluding the keys specified in _ignore_keys.

Return type:

List[str]

Notes

The keys specified in _ignore_keys will be excluded from the list of connection.

property transition_dataframe: pandas.DataFrame

Returns a pandas DataFrame representation of the transmission files, excluding specific keys.

Returns:

A DataFrame containing the transmission files for the optical states, with specified keys excluded.

Return type:

pd.DataFrame

Notes

The keys ‘unitary’ and ‘raw_output’ will be excluded from the transmission files.

property target_output_dataframe: pandas.DataFrame

Returns a pandas DataFrame filtered to include only the transitions where target_mode_output is 1.

Returns:

A DataFrame containing only the transitions where the target mode is an output.

Return type:

pd.DataFrame

PhaseMapType

Alias for phase map measurement. Can be one of: - TupleFloatType: A tuple of float values. - TupleIntType: A tuple of integer values.

Type:

PhaseMapType

PhaseTransitionTypes

A literal type for phase transition measurement. Can be one of: - “cross”: Refers to a cross-type phase transition. - “bar”: Refers to a bar-type phase transition.

Type:

PhaseTransitionTypes

SwitchFunctionParameter

SParameterCollection

class ElectroOpticModulatorMetrics(/, **data: Any)

Bases: piel.types.connectivity.metrics.ComponentMetrics

In this class, we define the corresponding relevant metrics to enable characterizing a modulator device.

class ElectroOpticModulator(/, **data: Any)

Bases: piel.types.connectivity.physical.PhysicalComponent

This is an equivalent model of an Electro-Optical modulator.

metrics: list[ElectroOpticModulatorMetrics] = []

Note that a given component might have a set of metrics corresponding to multiple variations of the testing conditions.

class PulsedLaserMetrics(/, **data: Any)

Bases: piel.types.connectivity.metrics.ComponentMetrics

In this class, we define the corresponding relevant metrics to enable characterizing a modulator device.

wavelength_nm: piel.types.metrics.ScalarMetric

pulse_power_W: piel.types.metrics.ScalarMetric

average_power_W: piel.types.metrics.ScalarMetric

pulse_repetition_rate_Hz: piel.types.metrics.ScalarMetric

pulse_width_s: piel.types.metrics.ScalarMetric

class PulsedLaser(/, **data: Any)

Bases: piel.types.connectivity.physical.PhysicalComponent

This is an equivalent model of an Electro-Optical modulator.

metrics: list[PulsedLaserMetrics] = []

Note that a given component might have a set of metrics corresponding to multiple variations of the testing conditions.

class ElectronicCircuit(/, **data: Any)

Bases: piel.types.connectivity.physical.PhysicalComponent

Represents the data of a physical component or device.

class ElectronicChip(/, **data: Any)

Bases: piel.types.connectivity.physical.PhysicalComponent

A model representing an electronic chip in a photonic circuit.

ElectronicCircuitComponent

PhotonicCircuitComponent: A type representing a component in a photonic circuit, as defined in the gdsfactory framework. This type is used to handle and manipulate photonic components in circuit designs.

class RFTwoPortAmplifier(/, **data: Any)

Bases: piel.types.electronic.core.RFElectronicCircuit

Represents a physical RF (Radio Frequency) component with frequency-related properties.

This class extends the PhysicalComponent class to include RF-specific attributes.

Attributes:

networkFrequencyTransmissionModel | None

A representation of the component’s frequency network, typically containing s-parameter data. This is currently a placeholder and may be None.

metricsFrequencyMetricCollection

A collection of frequency-related metrics for this RF component, including bandwidth and center transmission.

Inherits all attributes from PhysicalComponent.

Notes:

• The ‘network’ attribute is currently using a placeholder type (Any | None) and is intended to be updated with a proper s-parameter representation in the future.

• This class combines physical component properties with RF-specific metrics, making it suitable for modeling and analyzing RF devices in a physical context.

class RFAmplifierCollection(/, **data: Any)

Bases: piel.types.connectivity.generic.ComponentCollection

This represents the fundamental data structure of an element in connectivity

components: list[RFAmplifierTypes] = []

RFAmplifierTypes

class PowerAmplifierMetrics(/, **data: Any)

Bases: piel.types.connectivity.metrics.ComponentMetrics

A model representing the metrics for a high-voltage amplifier (HVA) or a Power Amplifier (PA).

footprint_mm2

The physical footprint of the amplifier in square millimeters.

Type:

ScalarMetric

bandwidth_Hz

The operational bandwidth of the amplifier in Hertz, given as a range (min, max).

Type:

ScalarMetric

power_added_efficiency

The power added efficiency of the amplifier, given as a range (min, max).

Type:

ScalarMetric

power_consumption_mW

The power consumption of the amplifier in milliwatts, given as a range (min, max).

Type:

ScalarMetric

power_gain_dB

The power gain of the amplifier in decibels, given as a range (min, max).

Type:

ScalarMetric

saturated_power_output_dBm

The saturated power output of the amplifier in dBm.

Type:

ScalarMetric

supply_voltage_V

The supply voltage of the amplifier in volts.

Type:

ScalarMetric

technology_nm

The technology node of the amplifier in nanometers.

Type:

ScalarMetric

technology_material

The material technology used in the amplifier.

Type:

Optional[str]

footprint_mm2: piel.types.metrics.ScalarMetric

footprint_mm2 ( ScalarMetric ): The physical footprint of the amplifier in square millimeters.

bandwidth_Hz: piel.types.metrics.ScalarMetric

bandwidth_Hz ( ScalarMetric ): The operational bandwidth of the amplifier in Hertz, given as a range (min, max).

power_added_efficiency: piel.types.metrics.ScalarMetric

power_added_efficiency ( ScalarMetric ): The power added efficiency of the amplifier, given as a range (min, max).

power_consumption_mW: piel.types.metrics.ScalarMetric

power_consumption_mW ( ScalarMetric ): The power consumption of the amplifier in milliwatts, given as a range (min, max).

power_gain_dB: piel.types.metrics.ScalarMetric

power_gain_dB ( ScalarMetric ): The power gain of the amplifier in decibels, given as a range (min, max).

saturated_power_output_dBm: piel.types.metrics.ScalarMetric

saturated_power_output_dBm ( ScalarMetric ): The saturated power output of the amplifier in dBm.

supply_voltage_V: piel.types.metrics.ScalarMetric

supply_voltage_V ( ScalarMetric ): The supply voltage of the amplifier in volts.

technology_nm: piel.types.metrics.ScalarMetric

technology_nm ( ScalarMetric ): The technology node of the amplifier in nanometers.

technology_material: str = ''

technology_material (Optional[str]): The material technology used in the amplifier.

class PowerAmplifier(/, **data: Any)

Bases: piel.types.electronic.amplifier.RFTwoPortAmplifier

Represents a physical RF (Radio Frequency) component with frequency-related properties.

This class extends the PhysicalComponent class to include RF-specific attributes.

Attributes:

networkFrequencyTransmissionModel | None

A representation of the component’s frequency network, typically containing s-parameter data. This is currently a placeholder and may be None.

metricsFrequencyMetricCollection

A collection of frequency-related metrics for this RF component, including bandwidth and center transmission.

Inherits all attributes from PhysicalComponent.

Notes:

• The ‘network’ attribute is currently using a placeholder type (Any | None) and is intended to be updated with a proper s-parameter representation in the future.

• This class combines physical component properties with RF-specific metrics, making it suitable for modeling and analyzing RF devices in a physical context.

metrics: list[PowerAmplifierMetrics] = []

Note that a given component might have a set of metrics corresponding to multiple variations of the testing conditions.

class LNAMetrics(/, **data: Any)

Bases: piel.types.connectivity.metrics.ComponentMetrics

A model representing the metrics for a low-noise amplifier (LNA).

footprint_mm2

The physical footprint of the amplifier in square millimeters.

Type:

ScalarMetric

bandwidth_Hz

The operational bandwidth of the amplifier in Hertz, given as a range (min, max).

Type:

ScalarMetric

noise_figure

The noise figure of the amplifier, given as a range (min, max).

Type:

ScalarMetric

power_consumption_mW

The power consumption of the amplifier in milliwatts, given as a range (min, max).

Type:

ScalarMetric

power_gain_dB

The power gain of the amplifier in decibels, given as a range (min, max).

Type:

ScalarMetric

supply_voltage_V

The supply voltage of the amplifier in volts.

Type:

ScalarMetric

technology_nm

The technology node of the amplifier in nanometers.

Type:

ScalarMetric

technology_material

The material technology used in the amplifier.

Type:

Optional[str]

footprint_mm2: piel.types.metrics.ScalarMetric

footprint_mm2 ( ScalarMetric ): The physical footprint of the amplifier in square millimeters.

bandwidth_Hz: piel.types.metrics.ScalarMetric

bandwidth_Hz ( ScalarMetric ): The operational bandwidth of the amplifier in Hertz, given as a range (min, max).

noise_figure: piel.types.metrics.ScalarMetric

noise_figure ( ScalarMetric ): The noise figure of the amplifier, given as a range (min, max).

power_consumption_mW: piel.types.metrics.ScalarMetric

power_consumption_mW ( ScalarMetric ): The power consumption of the amplifier in milliwatts, given as a range (min, max).

power_gain_dB: piel.types.metrics.ScalarMetric

power_gain_dB ( ScalarMetric ): The power gain of the amplifier in decibels, given as a range (min, max).

supply_voltage_V: piel.types.metrics.ScalarMetric

supply_voltage_V ( ScalarMetric ): The supply voltage of the amplifier in volts.

technology_nm: piel.types.metrics.ScalarMetric

technology_nm ( ScalarMetric ): The technology node of the amplifier in nanometers.

technology_material: str = ''

technology_material (Optional[str]): The material technology used in the amplifier.

class LowNoiseTwoPortAmplifier(/, **data: Any)

Bases: piel.types.electronic.amplifier.RFTwoPortAmplifier

Represents a physical RF (Radio Frequency) component with frequency-related properties.

This class extends the PhysicalComponent class to include RF-specific attributes.

Attributes:

networkFrequencyTransmissionModel | None

A representation of the component’s frequency network, typically containing s-parameter data. This is currently a placeholder and may be None.

metricsFrequencyMetricCollection

A collection of frequency-related metrics for this RF component, including bandwidth and center transmission.

Inherits all attributes from PhysicalComponent.

Notes:

• The ‘network’ attribute is currently using a placeholder type (Any | None) and is intended to be updated with a proper s-parameter representation in the future.

• This class combines physical component properties with RF-specific metrics, making it suitable for modeling and analyzing RF devices in a physical context.

metrics: list[LNAMetrics] = []

Note that a given component might have a set of metrics corresponding to multiple variations of the testing conditions.

ProjectType

CircuitComponent

MaterialReferenceType

MaterialReferenceType: A tuple used to reference materials, where: - The first element is a mandatory string, usually representing the material name or identifier. - The second element is an optional string, which might provide additional details or context about the material.

MaterialReferencesTypes

MaterialReferencesTypes: A list of material references, where each reference is a tuple as defined by MaterialReferenceType. This is used to handle collections of material references in applications.

MaterialSpecificationType

MaterialSpecificationType: A literal type used for defining material specifications. This is typically used to enforce specific string values in material specifications.

class ScalarMetric(/, **data: Any)

Bases: piel.types.connectivity.abstract.Instance

Standard definition for a scalar metrics. It includes the value, mean, min, max, standard deviation and count.

value: piel.types.core.NumericalTypes | None = None

mean: piel.types.core.NumericalTypes | None = None

min: piel.types.core.NumericalTypes | None = None

max: piel.types.core.NumericalTypes | None = None

standard_deviation: piel.types.core.NumericalTypes | None = None

count: piel.types.core.NumericalTypes | None = None

unit: piel.types.units.Unit

property data

property table

class ScalarMetricCollection(/, **data: Any)

Bases: piel.types.connectivity.abstract.Instance

A collection of scalar metrics useful when analyzing multiple aspects of a design.

metrics: list[ScalarMetric] = []

property data

property table

Composes a full table with the names and all the individual metrics that are part of this collection.

Returns:

A DataFrame containing all scalar metrics with their respective values.

Return type:

pd.DataFrame

__getitem__(index)

Allows for indexing and slicing of the metrics list.

Parameters:

index – An integer or slice object for indexing.

Returns:

A new ScalarMetricCollection containing the specified slice of metrics.

PhotonicCircuitComponent

PhotonicCircuitComponent: A type representing a component in a photonic circuit, as defined in the gdsfactory framework. This type is used to handle and manipulate photonic components in circuit designs.

OpticalTransmissionCircuit

OpticalTransmissionCircuit: A callable type representing an optical transmission circuit in the SAX framework. This is used for functions that model the behavior of optical circuits.

RecursiveNetlist

RecursiveNetlist: A type representing a recursive netlist in the SAX framework. This type is used to describe the hierarchical structure of photonic circuits.

SParameterMatrixTuple

SParameterMatrixTuple: A tuple representing an S-parameter matrix used in circuit simulations. It includes: - ArrayTypes: A matrix (numpy or jax array) representing the S-parameters. - ConnectionTypes: A tuple of strings representing the corresponding port names.

ElectricalSignalDomains

QuantityTypesDC

class SignalDCCollection(/, **data: Any)

Bases: piel.types.connectivity.abstract.Instance

This represents the fundamental data structure of an element in connectivity

inputs: list[SignalDC] = []

The input DC signals.

outputs: list[SignalDC] = []

The output DC signals.

power: list[SignalDC] = []

The power DC signals.

class SignalTraceDC(/, **data: Any)

Bases: piel.types.connectivity.abstract.Instance

Represents a DC signal with all relevant components as defined by Ohm’s law but specified through a collection of data defined by a OperatingPointContainer

The values are the values of the signal. The name is the name of the signal. Can be both an operating point or a sweep collection of data.

A DC signal might have a current and a voltage attached to it, so it would be a collection of data. Current and voltage are both physical representations of electrical quantities in this case in the context of DC operation. These operating points can reference an array of data points that are collected from a DC sweep.

unit: piel.types.units.Unit

Intended for DC electrical types such as voltage, current, power and resistance.

values: piel.types.core.ArrayTypes = []

The values of the operating points in an array format.

class SignalDC(/, **data: Any)

Bases: piel.types.connectivity.abstract.Instance

This is used to define a collection of SignalInstances which compose a DC signal. For example, the voltage and current of the same signal would be `SignalInstance`s but the total signal is the collection of these data references.

These DC signals may refer to a single trace, with a collection of voltage, current, resistance or power data points. These may still be referencing the original node.

trace_list: list[SignalTraceDC] = []

class Phasor(/, **data: Any)

Bases: piel.types.connectivity.abstract.Instance

Contains magnitude and phase frequency response information. Can represent both an array or individual response. Equivalent to a single-frequency response. Contains a very clear notation to translate with a complex number and this term.

\[Ae^{i(\omega t+ heta)}\]

magnitude: piel.types.core.NumericalTypes | piel.types.core.ArrayTypes

Should represent an absolute value real number.

phase: piel.types.core.NumericalTypes | piel.types.core.ArrayTypes

Should represent an absolute value real number.

frequency: piel.types.core.NumericalTypes | piel.types.core.ArrayTypes

Should represent an absolute value real number.

frequency_unit: piel.types.units.Unit

phase_unit: piel.types.units.Unit

magnitude_unit: piel.types.units.Unit

property data

property table

check_lengths_consistency(model)

Validates that the lengths of magnitude, phase, and frequency are exactly the same. All must have the same length, regardless of being scalar or arrays.

PhasorTypes

Different ways to represent frequency-domain information. In principle, both array and individual representations of complex numbers which can represent phasors. These could be input-arrays, as input components.

Contains a very clear notation to translate with a complex number that is a full input-representation.

\[Ae^{i(\omega t+ heta)}\]

class PathTransmission(/, **data: Any)

Bases: piel.types.connectivity.abstract.Instance

This represents the fundamental data structure of an element in connectivity

connection: piel.types.connectivity.generic.ConnectionTypes

transmission: piel.types.signal.frequency.generic.PhasorTypes

A frequency-domain representation of transmission requires the full input response which can be represented as an array, an individual value, or a static-typed data structure - as per performance requirements.

class NetworkTransmission(/, **data: Any)

Bases: piel.types.connectivity.abstract.Instance

This corresponds to a transmission component or array collection of the power or frequency transmission. For example, for the reflected power (ie S11 transmission), this contains magnitude and phase information from a source. Instead of responding to a given input. Note that this does not contain mode information, but could be extended to implement this.

This can represent frequency to single-state conversion and a sckit-rf collective model too, based on its definition.

This implementation is flexible because making the transmission individual is kind of essential when dealing with both electronic-photonic s-parameter state management, or otherwise it involves writing a mapping function. This is not the fastest approach, but certainly complete. Maybe someone can come up with a more complete approach that is not so resource intensive or we can abstract this into defined base-types (but I think this is it though if any validation is to be applied?)

This can also be equivalent to a sckit-rf Network static data container, just that it decomposes each specific transmission to a given frequency or power-point. It implements translation between RF models and Photonic models which are more-port specific as defined by SAX. This enables more specific electronic-photonic state mapping.

input: piel.types.signal.frequency.generic.PhasorTypes

The combined definition of the input state input with magnitude and phase information. Could be extended to a spectral input incidence. The length of the PhasorType should match the length of the equivalent PathTransmission for one dimension of the input representation.

network: list[PathTransmission] = []

Contains the entire frequency transmission response per component. Can be defined both per state and per full collection.

TODO implement port mapping already.

check_length_consistency(model)

FrequencyTransmissionModel

Corresponds to a container that contains a s-parameter transmission model, for example.

This type alias is currently a placeholder (Any | None). The idea is that this is a collective static data representation compatible with both a sax-translation as with the standard sckit-rf network models.

FrequencyTransmissionList

class FrequencyMetricCollection(/, **data: Any)

Bases: piel.types.core.PielBaseModel

A base model class that serves as the foundation for other measurement in the project. This class extends pydantic’s BaseModel and includes additional configuration settings for strict validation and immutability.

Config

A nested class to configure the behavior of the model. arbitrary_types_allowed (bool): Allows arbitrary measurement. extra (str): Forbids extra attributes not defined in the model. validate_assignment (bool): Validates fields on assignment. strict (bool): Enforces strict type validation. allow_mutation (bool): Prevents mutation of the model’s fields.

supplied_parameters() → list[str]

Returns a list of parameter names that have been supplied (i.e., are not None).

metrics: list[FrequencyMetric] = []

class FrequencyMetric(/, **data: Any)

Bases: piel.types.core.PielBaseModel

Creates a mapping between a given input and a given scalar metrics response.

This assumes the following relationships structure:

Network(INPUT) = OUTPUT

This means that there is a directional relationship between the input and the transmission output. This type of metric includes this dimensionality assuming the metric is always related to the transmission output and that the input can be represented in the frequency domain as input. However, for the sake of completeness the input will just be called input, in case there is a higher dimensionality input into a frequency network.

This may still be valid also for other DC networks and inputs in higher-dimensional relationships as a given response might be a result of multiple values within a higher level system.

input: piel.types.signal.frequency.core.Phasor | None = None

metric: piel.types.metrics.ScalarMetric

property table

class ElectroOpticDCPathTransmission(/, **data: Any)

Bases: piel.types.connectivity.abstract.Instance

It is not logically possible to decouple the output signal from the connection at which this is measured, due to the vectorial and non-scalar nature of the electro-optic network relationship.

input_dc: piel.types.signal.dc_data.SignalDC

output: piel.types.signal.frequency.transmission.PathTransmission

class ElectroOpticDCNetworkTransmission(/, **data: Any)

Bases: piel.types.connectivity.abstract.Instance

Applicable when you have multiple inputs and multiple paths

path_transmission_list: list[ElectroOpticDCPathTransmission] = []

class TimeSignalData(/, **data: Any)

Bases: piel.types.core.PielBaseModel

Standard definition for a relationship between a relevant files signal and a time reference array. Sources could be both measurement and simulation.

time_s: piel.types.core.ArrayTypes = []

data: piel.types.core.ArrayTypes = []

data_name: str = ''

time_s_unit: piel.types.units.Unit

data_unit: piel.types.units.Unit

DataTimeSignalData

EdgeTransitionAnalysisTypes

MultiTimeSignalData

MultiDataTimeSignal

Collection of DataTimeSignals that can be used to analyse a set of signals together in a particular files flow.

MultiDataTimeSignalCollectionTypes = ['equivalent', 'different']

MultiDataTimeSignalAnalysisTypes

DataTimeSignalAnalysisTypes

class ExponentialSource(/, **data: Any)

Bases: piel.types.core.PielBaseModel

A base model class that serves as the foundation for other measurement in the project. This class extends pydantic’s BaseModel and includes additional configuration settings for strict validation and immutability.

Config

A nested class to configure the behavior of the model. arbitrary_types_allowed (bool): Allows arbitrary measurement. extra (str): Forbids extra attributes not defined in the model. validate_assignment (bool): Validates fields on assignment. strict (bool): Enforces strict type validation. allow_mutation (bool): Prevents mutation of the model’s fields.

supplied_parameters() → list[str]

Returns a list of parameter names that have been supplied (i.e., are not None).

voltage_1_V: float

voltage_2_V: float

rise_delay_time_s: float

rise_time_constant_s: float

fall_delay_time_s: float

fall_time_constant_s: float

class PulseSource(/, **data: Any)

Bases: piel.types.core.PielBaseModel

A base model class that serves as the foundation for other measurement in the project. This class extends pydantic’s BaseModel and includes additional configuration settings for strict validation and immutability.

Config

A nested class to configure the behavior of the model. arbitrary_types_allowed (bool): Allows arbitrary measurement. extra (str): Forbids extra attributes not defined in the model. validate_assignment (bool): Validates fields on assignment. strict (bool): Enforces strict type validation. allow_mutation (bool): Prevents mutation of the model’s fields.

supplied_parameters() → list[str]

Returns a list of parameter names that have been supplied (i.e., are not None).

voltage_1_V: float

voltage_2_V: float

delay_time_s: float

rise_time_s: float

fall_time_s: float

pulse_width_s: float

period_s: float

class PiecewiseLinearSource(/, **data: Any)

Bases: piel.types.core.PielBaseModel

A base model class that serves as the foundation for other measurement in the project. This class extends pydantic’s BaseModel and includes additional configuration settings for strict validation and immutability.

Config

A nested class to configure the behavior of the model. arbitrary_types_allowed (bool): Allows arbitrary measurement. extra (str): Forbids extra attributes not defined in the model. validate_assignment (bool): Validates fields on assignment. strict (bool): Enforces strict type validation. allow_mutation (bool): Prevents mutation of the model’s fields.

supplied_parameters() → list[str]

Returns a list of parameter names that have been supplied (i.e., are not None).

time_voltage_pairs: List[tuple]

class SineSource(/, **data: Any)

Bases: piel.types.core.PielBaseModel

A base model class that serves as the foundation for other measurement in the project. This class extends pydantic’s BaseModel and includes additional configuration settings for strict validation and immutability.

Config

A nested class to configure the behavior of the model. arbitrary_types_allowed (bool): Allows arbitrary measurement. extra (str): Forbids extra attributes not defined in the model. validate_assignment (bool): Validates fields on assignment. strict (bool): Enforces strict type validation. allow_mutation (bool): Prevents mutation of the model’s fields.

supplied_parameters() → list[str]

Returns a list of parameter names that have been supplied (i.e., are not None).

offset_voltage_V: float

amplitude_V: float

frequency_Hz: float

delay_time_s: float | None

damping_factor: float | None

SignalTimeSources

class SymbolicValue(/, **data: Any)

Bases: piel.types.core.PielBaseModel

A base model class that serves as the foundation for other measurement in the project. This class extends pydantic’s BaseModel and includes additional configuration settings for strict validation and immutability.

Config

A nested class to configure the behavior of the model. arbitrary_types_allowed (bool): Allows arbitrary measurement. extra (str): Forbids extra attributes not defined in the model. validate_assignment (bool): Validates fields on assignment. strict (bool): Enforces strict type validation. allow_mutation (bool): Prevents mutation of the model’s fields.

supplied_parameters() → list[str]

Returns a list of parameter names that have been supplied (i.e., are not None).

name: str = ''

label: str = ''

Label used in plots and more.

shorthand: str = ''

symbol: str = ''

class Reference(/, **data: Any)

Bases: piel.types.PielBaseModel

A base model class that serves as the foundation for other measurement in the project. This class extends pydantic’s BaseModel and includes additional configuration settings for strict validation and immutability.

Config

A nested class to configure the behavior of the model. arbitrary_types_allowed (bool): Allows arbitrary measurement. extra (str): Forbids extra attributes not defined in the model. validate_assignment (bool): Validates fields on assignment. strict (bool): Enforces strict type validation. allow_mutation (bool): Prevents mutation of the model’s fields.

supplied_parameters() → list[str]

Returns a list of parameter names that have been supplied (i.e., are not None).

text: str = ''

bibtex_id: str = ''

bibtex: str = ''

class Quantity(/, **data: Any)

Bases: piel.types.symbolic.SymbolicValue

A base model class that serves as the foundation for other measurement in the project. This class extends pydantic’s BaseModel and includes additional configuration settings for strict validation and immutability.

Config

A nested class to configure the behavior of the model. arbitrary_types_allowed (bool): Allows arbitrary measurement. extra (str): Forbids extra attributes not defined in the model. validate_assignment (bool): Validates fields on assignment. strict (bool): Enforces strict type validation. allow_mutation (bool): Prevents mutation of the model’s fields.

supplied_parameters() → list[str]

Returns a list of parameter names that have been supplied (i.e., are not None).

name: str = ''

value: piel.types.core.NumericalTypes | None = None

unit: piel.types.units.Unit

__add__

__mul__

__sub__

__radd__

__rmul__

__rsub__

__truediv__

__rtruediv__

__iadd__

__imul__

__isub__

class Unit(/, **data: Any)

Bases: piel.types.symbolic.SymbolicValue

A base model class that serves as the foundation for other measurement in the project. This class extends pydantic’s BaseModel and includes additional configuration settings for strict validation and immutability.

Config

A nested class to configure the behavior of the model. arbitrary_types_allowed (bool): Allows arbitrary measurement. extra (str): Forbids extra attributes not defined in the model. validate_assignment (bool): Validates fields on assignment. strict (bool): Enforces strict type validation. allow_mutation (bool): Prevents mutation of the model’s fields.

supplied_parameters() → list[str]

Returns a list of parameter names that have been supplied (i.e., are not None).

datum: BaseSIUnitNameList | str

base: piel.types.core.NumericalTypes = 1

In the format 1eN

__mul__

__rmul__

__add__

__radd__

__truediv__

__rtruediv__

BaseSIUnitNameList

A

dB

dBm

degree

GHz

Hz

nm

ns

m

MHz

mm2

mW

ohm

ps

ratio

s

us

W

V