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Here is my update to the autoenccoder tutorial.

  • added ability to read datatime from standard python datetime object, for interoperability with other packages
  • broke up some cells to make the tutorial easier to follow, including renaming some variables
  • Added some plots of the data
  • Added the use of pytorch metrics for calculating image metrics
    (more stuff on the way)

@stevehadd stevehadd requested a review from tennlee November 6, 2025 17:29
@stevehadd stevehadd self-assigned this Nov 6, 2025
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@tennlee I've created a draft PR, so that you can see the general direction I'm headed in and whether that direction is accetable to as PET acting BDFL...

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coveralls commented Nov 6, 2025

Pull Request Test Coverage Report for Build 19197223590

Details

  • 2 of 2 (100.0%) changed or added relevant lines in 1 file are covered.
  • No unchanged relevant lines lost coverage.
  • Overall coverage increased (+0.007%) to 61.169%

Totals Coverage Status
Change from base Build 19192762931: 0.007%
Covered Lines: 9547
Relevant Lines: 15191

💛 - Coveralls

…opefully added some functionality that will provide some suggestions on how participants in the hackathon might try this as an exercise and measure improvement.
@stevehadd stevehadd marked this pull request as ready for review November 8, 2025 18:57
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tennlee commented Nov 8, 2025

This is looking good. I think the cell where the tutorial displays the prediction from the untrained network could do with an explanation. People have always been interested to see what a prediction from an untrained network looks like, because it's not totally unstructured. I also think it's good to see the progression from 'untrained' to 'trained' playing itself out.

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tennlee commented Nov 8, 2025

For the example near the end showing the input, prediction and error - this is very helpful to see - maybe consider a bigger gap between samples so they look a bit more different from one another.

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tennlee commented Nov 8, 2025

Having the score calculations at the end is good. It might be worth explaining SSIM is not a perfect metric even though it can be useful. I really like these additions. I am going to go ahead and merge the work so that it's there for Monday morning, but if you can circle back to the comments and address them at some point, I think it would be worthwhile.

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tennlee commented Nov 8, 2025

Hi Stephen - I think your PR contains some files you didn't mean to change. Can you review the changed files and remove any files which were not intended to be changed? Also please run 'black' on time.py? Also, the original AutoEncoder tutorial has been slightly updated on develop to correct the display of the final image - please update your version also accordingly. Or, if you are putting all the changes into the new notebook, just remove AutoEncoder original from your PR.

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tennlee commented Nov 8, 2025

time.py and the new notebook look good. I might use some git tricks to get those onto develop, I am not sure what that will do to this PR however, so when I'm done the diff for this PR might look a little strange!

@tennlee tennlee merged commit 998713f into ACCESS-Community-Hub:develop Nov 9, 2025
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tennlee commented Nov 9, 2025

Okay, so apparently what I did had the side effect of closing this PR, which was unintended. I thought it would leave it open, with some files still not merged. Please also bring test coverage of time.py back up to 100%

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3 participants