Extra comma on this line?

Alternate idea: either here or in the examples file (or somewhere else the Pyomo team recommends), define

_RANDOM_SEED_FOR_TESTING = 524

Then in all the files that use this random seed, you can import this value.

Then in this file:

if _RANDOM_SEED_FOR_TESTING:
   np.random.seed(_RANDOM_SEED_FOR_TESTING)

This will mean someone only sets the testing random seed in one spot.

@sscini Nudge on this idea

@sscini Nudge on this idea

You'll probably need to put a try ... except around this. You are now making numpy a hard requirement.

This is a good suggestion.

@sscini Do the bootstrap, leave_n_out, ... functionality require numpy or scipy?

@adowling2 Agreed, I will add a try, except. Bootstrap and leave_N_out rely on numpy, graphics.pairwise_plot, and other graphics functions use scipy.

@mrmundt Would the "except" in this case be an import error for numpy? The other option would be adding the seed within each of the test classes, but if the try except works that's a lot less additions.

I think, considering that the random seed is necessary for these tests to run, that it would be best to do something like:

if numpy_available:
    np.random.seed(...)
else:
    raise unittest.SkipTest('Numpy is not available')

You can import numpy_available in line 25:

from pyomo.common.dependencies import numpy as np, numpy_available, pandas as pd, scipy, matplotlib

Caveat: This will make ALL parmest tests unavailable, so don't do that if you still want some tests to run.

@adowling2 Thoughts on this? Numpy is present in a lot of the tests here, so I think having the numpy_available would not be horrible to add.

It would probably be best practice to explicitly set the random seed in only the tests that need it. This gets around the caveat that @mrmundt points out. It also makes it super clear to future developers which tests/features require numpy (or scipy).

@adowling2 @mrmundt Thank you both for suggestions. So final action item I interpreted will be leaving the number (line 37) at the top of the file, and then adding the np.random.seed(...) to the tests that require it at the class level.