feat: add abstract and concrete classes for negative controls and regions #81
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Caution Review failedThe pull request is closed. WalkthroughThis pull request introduces several changes, primarily focusing on the addition of a new path in the Changes
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Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## main #81 +/- ##
===========================================
- Coverage 60.92% 44.51% -16.41%
===========================================
Files 10 16 +6
Lines 540 739 +199
===========================================
Hits 329 329
- Misses 211 410 +199 ☔ View full report in Codecov by Sentry. |
…dability in main module
strixy16
reviewed
Dec 11, 2024
|
addressing this comment
this is a good catch, when I initially defined the base classes I didnt know how the transformations were done and then I didnt know what other regions might be implemented in the future so I left the if we arent looking to implement new regions we can remove the parameter. some ideas I had for regions that would use the original class ThresholdRegion(RegionStrategy):
"""
Region strategy to include only pixels in the image where intensity exceeds a threshold.
Unlike ROI-based strategies, this strategy does not consider the mask_array.
"""
region_name: str = "threshold"
def __init__(self, threshold: float):
"""
Initialize the region strategy with a given intensity threshold.
Parameters
----------
threshold : float
The intensity threshold for including pixels in the region.
"""
self.threshold = threshold
def __call__(self, image_array: np.ndarray, _: np.ndarray) -> np.ndarray:
"""
Apply the threshold-based region mask to the image.
Parameters
----------
image_array : np.ndarray
The full image array to evaluate pixel intensities.
_ : np.ndarray
Ignored in this implementation.
Returns
-------
np.ndarray
A binary mask including only pixels in the image that exceed the threshold.
"""
# Apply the threshold directly to the image array
region_mask = np.where(image_array > self.threshold, 1, 0)
# Validate that the resulting mask is not empty
if not region_mask.any():
raise ValueError("No pixels in the image exceed the specified intensity threshold.")
return region_mask |
strixy16
reviewed
Dec 11, 2024
strixy16
reviewed
Dec 11, 2024
…docstrings and type hints
… with detailed parameter description and reference link
strixy16
reviewed
Dec 11, 2024
strixy16
approved these changes
Dec 11, 2024
… in abstract classes and manager
jjjermiah
deleted the
jjjermiah/refactor/negative-controls/abstract-and-concrete-classes
branch
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4D-Lung
Order of operations
negative_control_strategy(image, mask=mask, region=region_strategy)__call__on thenegative_control_strategy__call__ofregion(image_array, mask_array)transformmethod of theNegativeControlStrategyconcrete classes toimage_array[mask_indices] = transformed_valuesResource on Strategy Pattern: https://refactoring.guru/design-patterns/strategy/python/example
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