torchsig.transforms.base_transforms.Normalize¶

class torchsig.transforms.base_transforms.Normalize(norm: int | float | Literal['fro', 'nuc'] | None = 2, flatten: bool = False, seed: int | None = None, **kwargs)[source]¶

Bases: Transform

Normalize an IQ data vector.

norm¶

Order of the norm (refer to numpy.linalg.norm).

Type:: str

flatten¶

Specifies if the norm should be calculated on the flattened representation of the input tensor.

Type:: bool

Example

>>> import torchsig.transforms as ST
>>> transform = ST.Normalize(norm=2) # normalize by l2 norm
>>> transform = ST.Normalize(norm=1) # normalize by l1 norm
>>> transform = ST.Normalize(norm=2, flatten=True) # normalize by l1 norm of the 1D representation

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__(norm: int | float | Literal['fro', 'nuc'] | None = 2, flatten: bool = False, seed: int | None = None, **kwargs) → None[source]¶: Transform initialization as Seedable.

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

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