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@racohn racohn commented Jun 4, 2025

In the new notebook I roughly replicate the workflow carried out in the central park birds example, but applying it to fish data from this source: https://datadryad.org/landing/show?id=doi%3A10.5061%2Fdryad.sbcc2fr2h#usage

Since there is no food in this example, it's not really foraging, but we just look at distance between neighbors in the school. Hope to incorporate fish velocity into the predictors next.

racohn added 3 commits May 29, 2025 22:32
This reverts commit 57d1933.
Created a workflow very similar to the one used for central park birds, applied to fish data from
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@dimkab dimkab requested a review from emackev June 5, 2025 03:52
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i dont think this file should be in the PR

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review-notebook-app bot commented Jun 9, 2025

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dimkab commented on 2025-06-09T14:30:54Z
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  • Please add some basic explanation of the dataset and what we are trying to accomplish in this notebook
  • The output should be consistent with the code, e.g. running the notebook from beginning to end without any error messages etc.

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dimkab commented on 2025-06-09T14:30:55Z
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would be great to add code for downloading the data and checking if the data is already downloaded


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dimkab commented on 2025-06-09T14:30:56Z
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this is independent of the rest of the notebook right? can we learn something from these distributions?


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dimkab commented on 2025-06-09T14:30:57Z
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the x axis says "inter-bird"


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dimkab commented on 2025-06-09T14:30:58Z
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  • can we add uncertainty intervals for the coefficients?
  • I think the order is a bit messed up, maybe first we should run the loop over the optimal distances (this plot), and only then select a certain optimal distance.

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dimkab commented on 2025-06-09T14:30:59Z
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Some conclusions?


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dimkab commented Jun 9, 2025

@racohn also please notice the automatic checks (lint/test) should pass. You can see the error by clicking on the failed check links below. Also please see the Contributing section in the README

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2 participants