remove fill_missing() method

[henrikingo]

In particular, for the 1dimensional case, a missing test result is simply missing. It is common that some tests aren't run on every commit. (also, we don't run tests every second either) You just run the algo on the points you have.

More importantly, in cases where data points missing may be a problem, then padding is the wrong soluton.

[ItsZetty]

@henrikingo
Hi, if this issue is still open, may I work on it?

[henrikingo]

Hi

Yes, you are very welcome to :-)

In general (also for someone else who might read this) ...in open source projects it works well if you simply start working on something, and then submit the patch for review as a pull request. While we might assign issues to someone who intended to work on it, we are all volunteers here, so we can't expect anyone to deliver some work in any given time frame. So this means, even if someone has said they intend to work on some issue, another contributor is still welcome to work on it too. Whoever actually completes the work first is then likely to get their PR merged.

Another reason why this is okay, is that if we would happen to receive two competing PRs at the same time, we can then have a discussion about how they differ and why, and this is a great learning experience for all of us.

So in conclusion, you are always welcome to work on any issue that is open

[tejrai07]

Hi @henrikingo , I see this issue is still unassigned and there hasn't been activity for a while. I am a sophomore student and would love to take this on as my first contribution. Could you please assign it to me? I'm already looking into where the fill_missing() method is used.

[tejrai07]

@henrikingo ,
I’ve finished a local technical analysis of the codebase to prepare for this refactor. Here is my proposed plan to ensure a clean removal:
Impacted Files Identified: My grep results show that fill_missing is defined in otava/analysis.py and utilized in otava/series.py (lines 31, 248, 398).
Refactor Strategy: - I will remove the fill_missing() definition from otava/analysis.py.
In otava/series.py, I will refactor the logic to handle raw data points directly, following your guidance that running the algorithm on available points is preferred over padding.
Verification: I will remove the corresponding unit tests in tests/analysis_test.py and run the full test suite to ensure no regression in the core series logic.
I’m ready to start as soon as I’m assigned. Thanks!

[henrikingo]

I actually thought I had assigned this, but like I wrote above, it doesn't matter. You are welcome to propose a pull request whether or not you are assigned, in fact also whether or not there is an issue in the first place.

Some friendly advice: This is a simple task. If you are studying computer science, then I warmly recommend you to NOT use Claude for this task, rather try to do it 100% on your own.

We currently don't have any guidelines for how to submit patches that were Co-authored with an AI, but one requirement probably will be that the human author must be prepared to demonstrate that you understand the patch as well as you would if you had written it 100% yourself