Suppress the annoying np.datetime64 errors

[rboston628]

Description of work

Recently, numpy fully deprecated the use of timezone offsets in np,datetime64 constructor from strings. This was throwing useless errors that confused users and made it seem that every SNAPRed reduction was failing.

These were handled by suppressing the errors inside of the central Time.py module.

Explanation of work

This context manager successfully removes the error:

with warnings.catch_warnings():
  warnings.filterwarnings("ignore", category=Warning)
  time = np.datetime64(ts).astype(int) / 1e9  # convert to seconds

To test

Dev testing

Open, and try running a complete calibration run.

CIS testing

Please run an entire reduction run for a suitable file.

Link to EWM item

EWM#14998

Verification

• the author has read the EWM story and acceptance critera
• the reviewer has read the EWM story and acceptance criteria
• the reviewer certifies the acceptance criteria below reflect the criteria in EWM

Acceptance Criteria

This list is for ease of reference, and does not replace reading the EWM story as part of the review. Verify this list matches the EWM story before reviewing.

• acceptance criterion 1
• acceptance criterion 2

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 96.27%. Comparing base (414862c) to head (ac21b76).
⚠️ Report is 1 commits behind head on next.

Additional details and impacted files

@@           Coverage Diff           @@
##             next     #670   +/-   ##
=======================================
  Coverage   96.27%   96.27%           
=======================================
  Files          77       77           
  Lines        7055     7059    +4     
=======================================
+ Hits         6792     6796    +4     
  Misses        263      263           

Flag	Coverage Δ
integration	49.39% <62.50%> (+0.02%)	⬆️
unittests	95.99% <100.00%> (+<0.01%)	⬆️

Flags with carried forward coverage won't be shown. Click here to find out more.

☔ View full report in Codecov by Sentry.
📢 Have feedback on the report? Share it here.

🚀 New features to boost your workflow:

• ❄️ Test Analytics: Detect flaky tests, report on failures, and find test suite problems.

[mguthriem]

I tested this today using the original replicator and this seems to have solved the problem.