ConditionalSetProperty

class deeptrack.features.ConditionalSetProperty(feature: Feature, condition: str | bool | Callable[[...], str | bool] | None = None, **kwargs: Any)

Bases: StructuralFeature

Conditionally override the properties of a child feature.

Deprecated since version 2.0: This feature is deprecated and may be removed in a future release. It is recommended to use Arguments instead.

This feature modifies the properties of a child feature only when a specified condition is met. If the condition evaluates to True, the given properties are applied; otherwise, the child feature remains unchanged.

It is advisable to use Arguments instead when possible, since this feature overwrites properties, which may affect future calls to the feature.

If condition is a string, the condition must be explicitly passed when resolving.

The properties applied do not persist unless explicitly stored.

Parameters

feature: Feature

The child feature whose properties will be modified conditionally.

condition: PropertyLike[str | bool] | None, optional

Either a boolean value (True, False) or the name of a boolean property in the feature’s property dictionary. If the condition evaluates to True, the specified properties are applied.

**kwargs: Any

The properties to be applied to the child feature if condition is True.

Methods

get(inputs, condition, **kwargs) -> Any

Resolves the child feature, conditionally applying the specified properties.

Examples

>>> import deeptrack as dt

Define an image:

>>> import numpy as np
>>>
>>> image = np.ones((512, 512))

Define a Gaussian noise feature:

>>> gaussian_noise = dt.Gaussian(sigma=0)

— Using a boolean condition — Apply sigma=5 only if condition=True:

>>> conditional_feature = dt.ConditionalSetProperty(
...     gaussian_noise, sigma=5,
... )

Resolve with condition met:

>>> noisy_image = conditional_feature(image, condition=True)
>>> round(noisy_image.std(), 1)
5.0

Resolve without condition:

>>> conditional_feature.update()  # Essential to reset the property
>>> clean_image = conditional_feature(image, condition=False)
>>> round(clean_image.std(), 1)
0.0

— Using a string-based condition — Define condition as a string:

>>> conditional_feature = dt.ConditionalSetProperty(
...     gaussian_noise, sigma=5, condition="is_noisy"
... )

Resolve with condition met:

>>> noisy_image = conditional_feature(image, is_noisy=True)
>>> round(noisy_image.std(), 1)
5.0

Resolve without condition:

>>> conditional_feature.update()
>>> clean_image = conditional_feature(image, is_noisy=False)
>>> round(clean_image.std(), 1)
0.0

Methods Summary

get(inputs, condition, **kwargs)

Resolve the child, conditionally applying specified properties.

Methods Documentation

get(inputs: Any, condition: str | bool, **kwargs: Any) → Any

Resolve the child, conditionally applying specified properties.

Parameters

inputs: Any

The input data to process.

condition: str or bool

A boolean value or the name of a boolean property in the feature’s property dictionary. If the condition evaluates to True, the specified properties are applied.

**kwargs:: Any

Additional properties to apply to the child feature if the condition is True.

Returns

Any

The resolved child feature, with properties conditionally modified.