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Probabilistic Inference on Noisy Time Series
http://pints.readthedocs.io
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Rt Notebook example - corrected #1523

Open I-Bouros opened 3 months ago

codecov[bot] commented 3 months ago

Codecov Report

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Project coverage is 100.00%. Comparing base (abcc8e5) to head (3d7ac11).

Additional details and impacted files ```diff @@ Coverage Diff @@ ## main #1523 +/- ## ========================================= Coverage 100.00% 100.00% ========================================= Files 97 97 Lines 9577 9577 ========================================= Hits 9577 9577 ```

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MichaelClerx commented 3 months ago

Can you give a bit of background about this example? What's the reason for including it (from a PINTS point of view: which features does it highlight)?

In its current form I don't think it belong in the "toy" section of examples, as those all showcase a toy model included in the PINTS module.

If you did want to make this into a PINTS toy problem, we would have to think about how (or whether) to include the CSV data, as we would have to then package this data as part of the pints module

I-Bouros commented 3 months ago

Can you give a bit of background about this example? What's the reason for including it (from a PINTS point of view: which features does it highlight)?

In its current form I don't think it belong in the "toy" section of examples, as those all showcase a toy model included in the PINTS module.

If you did want to make this into a PINTS toy problem, we would have to think about how (or whether) to include the CSV data, as we would have to then package this data as part of the pints module

It's meant to be an additional example for the paper, and to showcase how someone can try and define their own logPDF objects rather than resorting to singleOutput problems. I did struggle to find a good place to include it, to be honest.

MichaelClerx commented 3 months ago

I suppose it could always go under "Miscellaneous", or it could go in a separate repo? (pints-team/rt-estimation-renewal-equation?), or in a repo with things related to the paper?

MichaelClerx commented 3 weeks ago

@ben18785 want to comment on the science of this? Or shall we just merge it in?