Scalar Resolution with Regression Test

[AdishreeB]

Description

This PR fixes an IndexError that occurs when using model.debug() on scalar variables.

The issue was that the debug function attempted to index scalar variables using values[mask], which fails because scalars are 0-dimensional and cannot be indexed.

The fix adds a dimension check (values.ndim == 0) before indexing:

• For scalar variables: handles the mask as a single boolean value
• For array variables: uses the original indexing logic

This ensures the debug function works correctly for both scalar and array random variables.

A regression test is included to prevent this bug from reappearing.

Related Issue

• Closes Debug message for scalar values fails #7429
• Related to #

Checklist

• Checked that the pre-commit linting/style checks pass
• Included tests that prove the fix is effective or that the new feature works
• Added necessary documentation (docstrings and/or example notebooks)
• If you are a pro: each commit corresponds to a relevant logical change

Type of change

• New feature / enhancement
• Bug fix
• Documentation
• Maintenance
• Other (please specify):

[codecov]

Codecov Report

❌ Patch coverage is 0% with 5 lines in your changes missing coverage. Please review.
✅ Project coverage is 86.92%. Comparing base (a375fd1) to head (429d157).
⚠️ Report is 38 commits behind head on main.

Files with missing lines	Patch %	Lines
pymc/model/core.py	0.00%	5 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #8103      +/-   ##
==========================================
- Coverage   88.76%   86.92%   -1.84%     
==========================================
  Files         116      123       +7     
  Lines       18971    19525     +554     
==========================================
+ Hits        16840    16973     +133     
- Misses       2131     2552     +421     

Files with missing lines	Coverage Δ
pymc/model/core.py	75.03% <0.00%> (-18.28%)	⬇️

... and 61 files with indirect coverage changes

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[ricardoV94]

test the output directly, instead of just testing it doesn't raise. You can use capsys to capture it.

Also would be nice to test a case that has an error and one that doesn't. Both presumably failed before, but we are still not testing one of them.

You just need to give a negative sigma to the Normal to get a case that fails (at least the logp, not sure about the dlgop).