Real#

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

Bases: ElementwiseFeature

Apply the real-part function elementwise.

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

For real-valued inputs, it returns the input unchanged. For complex-valued inputs, it returns the real part.

Parameters#

feature: Feature | None, optional

The input feature to which the real 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 Real

Use with NumPy directly:

>>> import numpy as np
>>> result = Real()(np.array([1+2j, 3+0j, -4.5]))
>>> result
array([ 1. ,  3. , -4.5])

Use with PyTorch directly:

>>> import torch
>>> result = Real()(torch.tensor([1+2j, 3+0j, -4.5+0j]))
>>> result
tensor([ 1.0000,  3.0000, -4.5000])

Use in a pipeline with a NumPy value:

>>> value = dt.Value(value=np.array([1+2j, 3+0j, -4.5]))
>>> pipeline = value >> Real()
>>> result = pipeline()
>>> result
array([ 1. ,  3. , -4.5])

Use in a pipeline with a PyTorch value:

>>> value = dt.Value(value=torch.tensor([1+2j, 3+0j, -4.5+0j]))
>>> pipeline = value >> Real()
>>> result = pipeline()
>>> result
tensor([ 1.0000,  3.0000, -4.5000])

These are equivalent to:

>>> pipeline = Real(value)