Support logp derivation of power(base, rv)

[LukeLB]

Addresses the first case in #6896, allowing users to evaluate the log prob of generalised bases e.g, power(base, x). This constricts base to be either a constant or a continuous random variable as long as its vaue is greater or equal to 0.

I've added a node rewrite function to deal with the power(base, x) case. To make sure that power(x, exponent) is unaffected by this rewrite I have made changes to find_measurable_transform. This is based upon the ordering of the node inputs which is assumed to always be node.inputs = [base, exponent], where the new rewrite takes the case where index 1 is measurable and PowerTransform takes the case where index 0 is measurable.

Closes #6896
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Checklist

• Explain important implementation details 👆
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• Link relevant issues (preferably in nice commit messages)
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New features

• Allows users to evaluate the logp of a generalised power(base, x) or base**x

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📚 Documentation preview 📚: https://pymc--6962.org.readthedocs.build/en/6962/

[codecov]

Codecov Report

Merging #6962 (fc3129a) into main (6f4a040) will decrease coverage by 0.08%.
Report is 13 commits behind head on main.
The diff coverage is 100.00%.

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #6962      +/-   ##
==========================================
- Coverage   92.18%   92.11%   -0.08%     
==========================================
  Files         100      100              
  Lines       16847    16896      +49     
==========================================
+ Hits        15531    15563      +32     
- Misses       1316     1333      +17     

Files	Coverage Δ
pymc/logprob/transforms.py	94.97% <100.00%> (+0.06%)	⬆️

... and 8 files with indirect coverage changes

[ricardoV94]

This looks amazing!!!

Just some small suggestions for comments / tests, but nothing about the fundamentals

[ricardoV94]

Thanks @LukeLB, sounds line we nailed all these Elemwise transforms?

[LukeLB]

Cheers! Yep all done💥