Slice

class deeptrack.features.Slice(slices: PropertyLike[Iterable[PropertyLike[int] | PropertyLike[slice] | PropertyLike[...]]], **kwargs: dict[str, Any])

Bases: Feature

Dynamically applies array indexing to input Image(s).

This feature allows dynamic slicing of an image using integer indices, slice objects, or ellipses (…). While normal array indexing is preferred for static cases, Slice is useful when the slicing parameters must be computed dynamically based on other properties.

Parameters

slices: Iterable[int | slice | …]

The slicing instructions for each dimension. Each element corresponds to a dimension in the input image.

**kwargs: dict of str to Any

Additional keyword arguments passed to the parent Feature class.

Methods

get(image: np.ndarray, slices: tuple[int | slice | …], **kwargs: dict[str, Any]) -> np.ndarray

Applies the specified slices to the input image.

Examples

>>> import deeptrack as dt
>>> import numpy as np

Recommended Approach: Use Normal Indexing for Static Slicing >>> feature = dt.DummyFeature() >>> static_slicing = feature[:, 1:2, ::-2] >>> result = static_slicing.resolve(np.arange(27).reshape((3, 3, 3))) >>> print(result)

Using `Slice` for Dynamic Slicing (when necessary) If slices depend on computed properties, use Slice: >>> feature = dt.DummyFeature() >>> dynamic_slicing = feature >> dt.Slice( … slices=(slice(None), slice(1, 2), slice(None, None, -2)) … ) >>> result = dynamic_slicing.resolve(np.arange(27).reshape((3, 3, 3))) >>> print(result)

In both cases, slices can be defined dynamically based on feature properties.

Methods Summary

get(image, slices, **kwargs)

Apply the specified slices to the input image.

Methods Documentation

get(image: np.ndarray, slices: tuple[Any, ...] | Any, **kwargs: dict[str, Any])

Apply the specified slices to the input image.

Parameters

image: np.ndarray

The input image to be sliced.

slices: tuple[int | slice | ellipsis, …] | int | slice | ellipsis

The slicing instructions for the input image. Each element in the tuple corresponds to a dimension in the input image. If a single element is provided, it is converted to a tuple.

**kwargs: dict of str to Any

Additional keyword arguments (unused in this implementation).

Returns

np.ndarray

The sliced image.