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Check for partially generated fovs #416
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Check out this pull request on See visual diffs & provide feedback on Jupyter Notebooks. Powered by ReviewNB |
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Looks good!
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Looks good, just one tweak
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# get fov and channel info | ||
fovs = io_utils.list_folders(extraction_dir, "fov") | ||
channels = io_utils.list_files(os.path.join(extraction_dir, fovs[0]), ".tiff") |
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I think we should always have the gold channel as one of these. Will you confirm that this doesn't materially change the false positive/false negative rate on the recent data once you update?
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Just re-ran it and got the same result.
# Conflicts: # templates/3b_extract_images_from_bin.ipynb
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What is the purpose of this PR?
Closes #400. Checks for incomplete FOV images which are missing data.
How did you implement your changes
Since scanning during a run starts at the top of the FOV, if something goes wrong we see this resulting in mostly 0 signal values at the bottom of the image. To be thorough, we check a specified number of images (default 5), and if the amount of non-zero pixels in that last 10 rows is less than 2%, we can identify this as a partial FOV.
Remaining issues