Fix for issue 7369

[westford14]

Fix for numpy deprecation warning (#7369)

Description

Small PR that addresses the numpy deprecation warnings that are seen when running tests:

tests/step_methods/test_metropolis.py: 15950 warnings
  REDACTED/pymc/pymc/backends/ndarray.py:118: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)
    data[key][self.draw_idx] = val

Change looks at the type of the val and if it is a np.ndarray and has .shape[0] == 1, then we pop the item out to prevent the deprecation warning.

Related Issue

• Closes Numpy deprecation warning issued from within test_metropolis.py #7369
• 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):

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📚 Documentation preview 📚: https://pymc--7514.org.readthedocs.build/en/7514/

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[ricardoV94]

Can val have more than one dim? More importantly it would be good if we didn't need this check in every iteration/ for every stat.

Can we solve it from another angle?

[westford14]

none of the tests passed in any values of greater than one dimension -- but noted on the point about trying to solve this outside the loop!

[westford14]

@ricardoV94 -- spent a little time looking at this and i think this problem is hard to solve outside the loop context given the setup of the sampler_stats object. At runtime we don't know what it's going to contain so we have to at some point loop through the values and look for np.ndarrays. In reference to your point about it being only one item, i think this is the case as this error only occurs when we're converting a 1-d array directly to a scalar, if the val isn't one dimensional we won't see this deprecation warning so we're fine to just check if it's just one value and, if it's not, continue

let me know what you think

[ricardoV94]

What happens if val has shape==(1, 2)? Your code will try to cerce into a scalar and fail right?

Taking a step back, the problem here seems to be the buffer was allocated with the wrong shape? If a stat has shape (1,) in every draw, the buffer should have (draws, 1) shape, not (draws,) and no coercing to scalar would be needed.

Am I off track here?

[westford14]

What happens if val has shape==(1, 2)? Your code will try to cerce into a scalar and fail right?

Taking a step back, the problem here seems to be the buffer was allocated with the wrong shape? If a stat has shape (1,) in every draw, the buffer should have (draws, 1) shape, not (draws,) and no coercing to scalar would be needed.

Am I off track here?

okay yea that makes sense -- i'm not sure if there's a better way to coerce here than trying to find arrays of shape (1,) because i don't think it makes sense to traverse the sampler_stats prior to this inner loop

[ricardoV94]

We should look at the code where the stats arrays are allocated to see how it's deciding on the shape

[ricardoV94]

The assumption that stats are scalars happens here:

pymc/pymc/backends/ndarray.py

Line 90 in 45069a9

data[varname] = np.zeros(draws, dtype=dtype)

If that's a requirement, then the problem is in Metropolis not respecting it. If that's not a requirement, the problem is in assuming the stats will be scalars. Which statistic from Metropolis step sampler is not respecting the scalar shape?