Add level-weighted module #5
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- Python port of NanoLocz level_weighted.m for AFM images and stacks - Supports region-weighted methods: 'plane', 'line', 'med_line', 'med_line_y', 'smed_line' - Implements polynomial and median-based background subtraction with per-region weighting - Handles 2D images and 3D stacks - Includes robust handling of masks, small regions, and degenerate cases - Preserves MATLAB-like centering and scaling for polynomial fits - Compatible with NumPy/SciPy ecosystem; ready for integration into NanoLocz workflow Also add typing to satisfy mypy.
Codecov Report❌ Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## main #5 +/- ##
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+ Coverage 96.48% 96.64% +0.16%
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Files 4 5 +1
Lines 455 776 +321
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+ Hits 439 750 +311
- Misses 16 26 +10 ☔ View full report in Codecov by Sentry. 🚀 New features to boost your workflow:
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This PR introduces a new module, level_weighted, providing weighted-region AFM image flattening and background leveling routines. The module is a Python port of the Nanolocz-lib MATLAB level_weighted.m used in the NanoLocz workflow and implements region-wise polynomial and median-based background estimation.
https://github.com/George-R-Heath/NanoLocz-Matlab-Library/blob/main/NanoLocz-lib/level_weighted.m
Supported levelling methods include:
The module supports masked images, handling multiple regions with weighted aggregation, and is compatible with both 2D images and 3D stacks.