torchsig.transforms.dataset_transforms.TimeReversal¶

class torchsig.transforms.dataset_transforms.TimeReversal(allow_spectral_inversion: bool | float = True, **kwargs)[source]¶

Bases: DatasetTransform

Applies a time reversal to the input.

Note that applying a time reversal inherently also applies a spectral inversion. If a time-reversal without spectral inversion is desired, the undo_spectral_inversion argument can be set to True. By setting this value to True, an additional, manual spectral inversion is applied to revert the time-reversal’s inversion effect.

allow_spectral_inversion¶

Whether to allow spectral inversion.

Type:: bool | float, optional

as a time reversal side effect

Type:: True) or not (False

\* If bool, applied to all signals.

\* If float, applied as probability to add signals.

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`	Updates bookkeeping to transforms in DatasetSignal's SignalMetadata and checks signal valididty.
`update_from_parent`	Update numpy and torch number generators with parent seed

__init__(allow_spectral_inversion: bool | float = True, **kwargs) → None[source]¶: Transform initialization as Seedable.

__call__(signal: DatasetSignal) → DatasetSignal[source]¶

Performs transforms.

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

__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: DatasetSignal) → None¶

Updates bookkeeping to transforms in DatasetSignal’s SignalMetadata and checks signal valididty. Inherited classes should always call self.update() after performing transform operation (inside __call__).

Parameters:: signal (DatasetSignal) – transformed DatasetSignal.

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