qat.utils.waveform module

class BlackmanFunction(**data)

Bases: ComplexFunction

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

a0: float

a1: float

a2: float

derivative(**kwargs)

First order derivative.

eval(**kwargs)

Function evaluated in domain described by x.

model_config: ClassVar[ConfigDict] = {'extra': 'ignore', 'use_enum_values': False, 'validate_assignment': True}

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

model_post_init(context: Any, /) → None

We need to both initialize private attributes and call the user-defined model_post_init method.

Return type:

None

width: float

class ComplexFunction(**data)

Bases: AllowExtraFieldsModel, ABC

Function object used to represent Complex 1D functions.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

abstract derivative(x, y)

First order derivative.

Return type:

ndarray

dt: float

abstract eval(x)

Function evaluated in domain described by x.

Return type:

ndarray

model_config: ClassVar[ConfigDict] = {'extra': 'ignore', 'use_enum_values': False, 'validate_assignment': True}

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

model_post_init(context, /)

This function is meant to behave like a BaseModel method to initialise private attributes.

It takes context as an argument since that’s what pydantic-core passes when calling it.

Return type:

None

Args:

self: The BaseModel instance. context: The context.

class Cos(**data)

Bases: ComplexFunction

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

derivative(x, _=None)

First order derivative.

eval(**kwargs)

Function evaluated in domain described by x.

frequency: float

internal_phase: float

model_config: ClassVar[ConfigDict] = {'extra': 'ignore', 'use_enum_values': False, 'validate_assignment': True}

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

model_post_init(context: Any, /) → None

We need to both initialize private attributes and call the user-defined model_post_init method.

Return type:

None

class DragGaussianFunction(**data)

Bases: ComplexFunction

Drag Gaussian, tighter on one side and long tail on the other.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

beta: float

derivative(x, _=None)

First order derivative.

eval(**kwargs)

Function evaluated in domain described by x.

model_config: ClassVar[ConfigDict] = {'extra': 'ignore', 'use_enum_values': False, 'validate_assignment': True}

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

model_post_init(context: Any, /) → None

We need to both initialize private attributes and call the user-defined model_post_init method.

Return type:

None

width: float

zero_at_edges: bool

class ExtraSoftSquareFunction(**data)

Bases: NumericFunction

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

eval(**kwargs)

Function evaluated in domain described by x.

model_config: ClassVar[ConfigDict] = {'extra': 'ignore', 'use_enum_values': False, 'validate_assignment': True}

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

model_post_init(context: Any, /) → None

We need to both initialize private attributes and call the user-defined model_post_init method.

Return type:

None

rise: float

width: float

class GaussianFunction(**data)

Bases: ComplexFunction

Gaussian function.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

derivative(**kwargs)

First order derivative.

eval(**kwargs)

Function evaluated in domain described by x.

property k

model_config: ClassVar[ConfigDict] = {'extra': 'ignore', 'use_enum_values': False, 'validate_assignment': True}

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

model_post_init(context: Any, /) → None

We need to both initialize private attributes and call the user-defined model_post_init method.

Return type:

None

rise: float

width: float

class GaussianSquareFunction(**data)

Bases: NumericFunction

A square pulse with a Gaussian rise and fall at the edges.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

eval(**kwargs)

Function evaluated in domain described by x.

model_config: ClassVar[ConfigDict] = {'extra': 'ignore', 'use_enum_values': False, 'validate_assignment': True}

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

model_post_init(context: Any, /) → None

We need to both initialize private attributes and call the user-defined model_post_init method.

Return type:

None

square_width: float

std_dev: float

zero_at_edges: float

class GaussianZeroEdgeFunction(**data)

Bases: ComplexFunction

A Gaussian pulse that can be normalized to be zero at the edges.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

derivative(x, _=None)

First order derivative.

eval(**kwargs)

Function evaluated in domain described by x.

model_config: ClassVar[ConfigDict] = {'extra': 'ignore', 'use_enum_values': False, 'validate_assignment': True}

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

model_post_init(context: Any, /) → None

We need to both initialize private attributes and call the user-defined model_post_init method.

Return type:

None

std_dev: float

width: float

zero_at_edges: bool

class NumericFunction(**data)

Bases: ComplexFunction

Base class for functions applying an numerical first derivative.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

derivative(**kwargs)

First order derivative.

model_config: ClassVar[ConfigDict] = {'extra': 'ignore', 'use_enum_values': False, 'validate_assignment': True}

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

model_post_init(context: Any, /) → None

We need to both initialize private attributes and call the user-defined model_post_init method.

Return type:

None

class RoundedSquareFunction(**data)

Bases: ComplexFunction

Rounded square.

___

/ ___| |___

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

derivative(x, _=None)

First order derivative.

eval(**kwargs)

Function evaluated in domain described by x.

model_config: ClassVar[ConfigDict] = {'extra': 'ignore', 'use_enum_values': False, 'validate_assignment': True}

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

model_post_init(context: Any, /) → None

We need to both initialize private attributes and call the user-defined model_post_init method.

Return type:

None

rise_time: float

std_dev: float

step(val)

width: float

class SechFunction(**data)

Bases: ComplexFunction

Implements a sech pulse defined by sech(x / width). Note that it is not normalized to be zero at the edges.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

derivative(x, _=None)

First order derivative.

eval(**kwargs)

Function evaluated in domain described by x.

model_config: ClassVar[ConfigDict] = {'extra': 'ignore', 'use_enum_values': False, 'validate_assignment': True}

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

model_post_init(context: Any, /) → None

We need to both initialize private attributes and call the user-defined model_post_init method.

Return type:

None

width: float

class SetupHoldFunction(**data)

Bases: NumericFunction

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

amp: float

amp_setup: float

eval(**kwargs)

Function evaluated in domain described by x.

model_config: ClassVar[ConfigDict] = {'extra': 'ignore', 'use_enum_values': False, 'validate_assignment': True}

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

model_post_init(context: Any, /) → None

We need to both initialize private attributes and call the user-defined model_post_init method.

Return type:

None

rise: float

width: float

class Sin(**data)

Bases: ComplexFunction

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

derivative(x, _=None)

First order derivative.

eval(**kwargs)

Function evaluated in domain described by x.

frequency: float

internal_phase: float

model_config: ClassVar[ConfigDict] = {'extra': 'ignore', 'use_enum_values': False, 'validate_assignment': True}

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

model_post_init(context: Any, /) → None

We need to both initialize private attributes and call the user-defined model_post_init method.

Return type:

None

class SoftSquareFunction(**data)

Bases: NumericFunction

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

eval(**kwargs)

Function evaluated in domain described by x.

model_config: ClassVar[ConfigDict] = {'extra': 'ignore', 'use_enum_values': False, 'validate_assignment': True}

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

model_post_init(context: Any, /) → None

We need to both initialize private attributes and call the user-defined model_post_init method.

Return type:

None

rise: float

width: float

class SofterGaussianFunction(**data)

Bases: NumericFunction

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

eval(**kwargs)

Function evaluated in domain described by x.

model_config: ClassVar[ConfigDict] = {'extra': 'ignore', 'use_enum_values': False, 'validate_assignment': True}

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

model_post_init(context: Any, /) → None

We need to both initialize private attributes and call the user-defined model_post_init method.

Return type:

None

rise: float

width: float

class SofterSquareFunction(**data)

Bases: NumericFunction

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

eval(**kwargs)

Function evaluated in domain described by x.

model_config: ClassVar[ConfigDict] = {'extra': 'ignore', 'use_enum_values': False, 'validate_assignment': True}

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

model_post_init(context: Any, /) → None

We need to both initialize private attributes and call the user-defined model_post_init method.

Return type:

None

rise: float

width: float

class SquareFunction(**data)

Bases: ComplexFunction

Square function of fixed amplitude.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

derivative(**kwargs)

First order derivative.

eval(**kwargs)

Function evaluated in domain described by x.

model_config: ClassVar[ConfigDict] = {'extra': 'ignore', 'use_enum_values': False, 'validate_assignment': True}

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

model_post_init(context: Any, /) → None

We need to both initialize private attributes and call the user-defined model_post_init method.

Return type:

None