Arctanh

class deeptrack.elementwise.Arctanh(feature: Feature | None = None, **kwargs: Any)

Bases: ElementwiseFeature

Apply the inverse hyperbolic tangent function elementwise.

This feature applies xp.arctanh to each element in a NumPy array or a PyTorch tensor. It supports both direct input and pipeline composition.

The input must be within the open interval (-1, 1). Values outside this range will produce NaNs or raise domain errors depending on the backend.

Parameters

feature: Feature | None, optional

The input feature to which the hyperbolic arctangent function will be applied. If None, the function is applied directly to the input array or tensor.

Examples

>>> import deeptrack as dt
>>> from deeptrack.elementwise import Arctanh

Use with NumPy directly:

>>> import numpy as np
>>>
>>> result = Arctanh()(np.array([-0.5, 0.0, 0.5]))
>>> result
array([-0.54930614,  0.        ,  0.54930614])

Use with PyTorch directly:

>>> import torch
>>>
>>> result = Arctanh()(torch.tensor([-0.5, 0.0, 0.5]))
>>> result
tensor([-0.5493,  0.0000,  0.5493])

Use in a pipeline with a NumPy value:

>>> value = dt.Value(value=np.array([-0.5, 0.0, 0.5]))
>>> pipeline = value >> Arctanh()
>>> result = pipeline()
>>> result
array([-0.54930614,  0.        ,  0.54930614])

Use in a pipeline with a PyTorch value:

>>> value = dt.Value(value=torch.tensor([-0.5, 0.0, 0.5]))
>>> pipeline = value >> Arctanh()
>>> result = pipeline()
>>> result
tensor([-0.5493,  0.0000,  0.5493])

These are equivalent to:

>>> pipeline = Arctanh(value)