Fix count rate estimation error for particularly bad GTIs

[matteobachetti]

In StingrayTimeseries.fill_bad_time_intervals, when the buffer size is small and count rates are low, there was the possibility that the count rate estimation failed with a numpy error. E.g., the test test_no_counts_in_buffer I added failed. Here, I catch the condition and warn that this is happening. Also, I made the estimation more robust when only one of the GTIs on the side of the bad time intervals has good data.

[pep8speaks]

Hello @matteobachetti! Thanks for updating this PR. We checked the lines you've touched for PEP 8 issues, and found:

There are currently no PEP 8 issues detected in this Pull Request. Cheers! :beers:

Comment last updated at 2024-02-21 09:20:51 UTC

[codecov[bot]]

Codecov Report

All modified and coverable lines are covered by tests :white_check_mark:

Comparison is base (5777271) 96.27% compared to head (5778e1f) 96.39%.

Additional details and impacted files

```diff @@ Coverage Diff @@ ## main #798 +/- ## ========================================== + Coverage 96.27% 96.39% +0.11% ========================================== Files 44 44 Lines 8855 8866 +11 ========================================== + Hits 8525 8546 +21 + Misses 330 320 -10 ```

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[matteobachetti]

Good point. Sometimes I tend to think about the logic that makes it easier to cover all options with tests, rather than making the code easier to read 😅. I changed the logic slightly following your suggested approach