Cos

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

Bases: ElementwiseFeature

Apply the cosine function elementwise.

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

Parameters

feature: Feature | None, optional

The input feature to which the cosine 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 Cos

Use with NumPy directly:

>>> import numpy as np
>>>
>>> result = Cos()(np.array([0, np.pi / 2, np.pi]))
>>> result
array([ 1.000000e+00,  6.123234e-17, -1.000000e+00])

Use with PyTorch directly:

>>> import torch
>>>
>>> result = Cos()(torch.tensor([0, torch.pi / 2, torch.pi]))
>>> result
tensor([ 1.0000e+00, -4.3711e-08, -1.0000e+00])

Use in a pipeline with a NumPy value:

>>> value = dt.Value(value=np.array([0, np.pi / 2, np.pi]))
>>> pipeline = value >> Cos()
>>> result = pipeline()
>>> result
array([ 1.000000e+00,  6.123234e-17, -1.000000e+00])

Use in a pipeline with a PyTorch value:

>>> value = dt.Value(value=torch.tensor([0, torch.pi / 2, torch.pi]))
>>> pipeline = value >> Cos()
>>> result = pipeline()
>>> result
tensor([ 1.0000e+00, -4.3711e-08, -1.0000e+00])

These are equivalent to:

>>> pipeline = Cos(value)