Add custom sampling option to PySMO

[OOAmusat]

Summary/Motivation:

This PR adds a sampling method that allows users to specify the sampling distributions to be used for each input variable/column. Current interface provides random, uniform and normal distribution sampling options.

Changes proposed in this PR:

• Add CustomSampling class
• Add tests

Legal Acknowledgement

By contributing to this software project, I agree to the following terms and conditions for my contribution:

1. I agree my contributions are submitted under the license terms described in the LICENSE.txt file at the top level of this directory.
2. I represent I am authorized to make the contributions and grant the license. If my employer has rights to intellectual property that includes these contributions, I represent that I have received permission to make contributions and grant the required license on behalf of that employer.

[codecov]

Codecov Report

Attention: 3 lines in your changes are missing coverage. Please review.

Comparison is base (021fb14) 77.36% compared to head (361077c) 77.38%.

Files	Patch %	Lines
idaes/core/surrogate/pysmo/sampling.py	98.05%	1 Missing and 2 partials ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #1298      +/-   ##
==========================================
+ Coverage   77.36%   77.38%   +0.02%     
==========================================
  Files         390      390              
  Lines       63462    63547      +85     
  Branches    11671    11699      +28     
==========================================
+ Hits        49099    49179      +80     
- Misses      11832    11836       +4     
- Partials     2531     2532       +1     

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

[bpaul4]

I think this looks very good, and the coverage is very high as well. Nicely done!

[andrewlee94]

A few requests, mostly for more specific exception types and descriptive test names.

[andrewlee94]

These look like tests that could (should) be done using fixed inputs. I.e. do not use the sample generation and mock up a set of known distributions that we can then use to ensure we get the right answer out.

As far as I can tell, sample_points is a case where we can test the method in isolation used manufactured data - i.e. provide the input specification, a mock up of a random dataset and a concrete answer we expect to get back out.

[ksbeattie]

@OOAmusat looks like this did not make the Dec 2.3.0 release...

[OOAmusat]

@OOAmusat looks like this did not make the Dec 2.3.0 release...

Yes, I don't know why as it had the required approvals and tests passing...