torchsig.transforms.impairments.Impairments¶

class torchsig.transforms.impairments.Impairments(all_levels_signal_transforms: List[SignalTransform], all_levels_dataset_transforms: List[DatasetTransform], level: int, **kwargs)[source]¶

Bases: Transform

Applies signal and dataset transformations at specific impairment levels.

This class applies a set of signal and dataset transforms based on a given impairment level. The impairment level must be between 0 and 2, where each level corresponds to different sets of transformations for signals and datasets. * Level 0: Perfect * Level 1: Cabled enviornment * Level 2: Wireless environment

Parameters:

all_levels_signal_transforms (List[SignalTransform]) – A list of signal transformations for all impairment levels.
all_levels_dataset_transforms (List[DatasetTransform]) – A list of dataset transformations for all impairment levels.
level (int) – The impairment level (must be between 0 and 2).
**kwargs – Additional keyword arguments passed to the parent class Transform.

Raises:

ValueError – If the provided impairment level is outside the valid range (0, 1, 2).

level¶

The specified impairment level.

Type:: int

signal_transforms¶

The composed signal transformations corresponding to the given impairment level.

Type:: Compose

dataset_transforms¶

The composed dataset transformations corresponding to the given impairment level.

Type:: Compose

Methods

`add_parent`	Add parent Seedable object and set up RNGs accordingly
`get_distribution`
`get_second_seed`	Gets second seed, usually used to seed both torch and numpy generators with slightly different seeds
`seed`	Seed number generators with given seed.
`setup_rngs`	Initialize torch and numpy number generators, and update its children.
`update`	Update bookeeping for signals
`update_from_parent`	Update numpy and torch number generators with parent seed

__init__(all_levels_signal_transforms: List[SignalTransform], all_levels_dataset_transforms: List[DatasetTransform], level: int, **kwargs)[source]¶: Transform initialization as Seedable.

__call__(signal: Signal | DatasetSignal) → Signal | DatasetSignal¶

Performs transforms

Parameters:: signal (Any) – Signal to be transformed.
Raises:: NotImplementedError – Inherited classes must override this method.
Returns:: Transformed Signal.
Return type:: Any

__repr__() → str¶

Transform string representation. Should be able to recreate class from this string.

Returns:: Transform representation.
Return type:: str

__str__() → str¶: Return str(self).

add_parent(parent) → None¶: Add parent Seedable object and set up RNGs accordingly

get_second_seed(seed: int) → int¶

Gets second seed, usually used to seed both torch and numpy generators with slightly different seeds

Parameters:: seed (int) – Seed to use.
Returns:: New seed.
Return type:: int

seed(seed: int) → None¶

Seed number generators with given seed.

Parameters:: seed (int) – Seed to use.

setup_rngs() → None¶: Initialize torch and numpy number generators, and update its children.

update(signal: Signal | DatasetSignal) → None¶

Update bookeeping for signals

Parameters:: signal (Signal | DatasetSignal) – signal to update metadata.
Raises:: NotImplementedError – Inherited classes must override this method.

update_from_parent() → None¶: Update numpy and torch number generators with parent seed