Add python sampler for residential

[rajeee]

Pull Request Description

Python version of the sampling script. There are also helper testing script that can verify if a given buildstock.csv is correct or not according to the TSVs.

Use buildstockbatch normally, and it will use the faster python based sampler automatically for residential.

To use the sampler stand alone, a new command resstock_sampler can be used.

>> resstock_sampler --help
Usage: resstock_sampler [OPTIONS] COMMAND [ARGS]...

  Perform sampling or verify existing samples (in buildstock.csv). Type
  `resstock_sampler sample --help` or `resstock_sampler verify --help` to know
  more.

Options:
  --help  Show this message and exit.

Commands:
  sample  Performs sampling for project and writes output csv file.
  verify  Checks the buildstock.csv file (BUILDSTOCK_FILE) for correctness.

There are two commands available sample to perform sampling, and verify to verify existing buildstock.csv for correctness.

> resstock_sampler sample --help
Usage: resstock_sampler sample [OPTIONS]

  Performs sampling for project and writes output csv file.

Options:
  -p, --project TEXT            The path to the project (most have
                                housing_characteristics folder inside)
                                [required]
  -n, --num_datapoints INTEGER  The number of datapoints to sample.
                                [required]
  -o, --output TEXT             The output filename with path.  [required]
  --help                        Show this message and exit.

> resstock_sampler verify --help
  Checks the buildstock.csv file (BUILDSTOCK_FILE) for correctness. BUILDSTOCK_FILE is considered correct if
  the probability distribution in project TSVs can result in the BUILDSTOCK_FILE using quota sampling.

  In addition to correctness verification, it also calculates the sample probability distribution error for the
  options in each TSVs between the BUILDSTOCK_FILE and what one would expect based on the probabilities. It also
  calculates smapling errors for each group in the TSV. An example is provided below to explain the error
  calculation further.
  Consider a project with three TSVs.
  Bedrooms.tsv
  ----------
  Option=1    Option=2    Option=3    Option=4    Option=5    sampling_probability
       0.2         0.2         0.2         0.2         0.2                     1.0
  
  Fan.tsv
  ----------
  Dependency=param1    Option=None    Option=Standard    Option=Premium    sampling_probability
                 1            0.35              0.35                0.3                     0.2
                 2            0.35              0.35                0.3                     0.2
                 3            0.35              0.35                0.3                     0.2
                 4            0.35              0.35                0.3                     0.2
                 5            0.35              0.35                0.3                     0.2
  
  AC.tsv
  ----------
  Dependency=param2    Option=Yes    Option=No    sampling_probability
               None           0.9          0.1                    0.35
           Standard           0.8          0.2                    0.35
            Premium           0.1          0.9                    0.3
  Quota sampling in the above project for 10 samples can generate a buildstock.csv that looks like this:
  buildstock.csv
  -------------
  Building  Bedrooms         Fan            AC
         *         1         None          Yes
         *         1         Standard      Yes
         *         2         None          Yes
         *         2         Standard      Yes
         *         3         None          Yes
         *         3         Standard      Yes
         *         4         None          Yes
         *         4         Standard      Yes
         *         5         None          Yes
         *         5         Standard       No
  
  For nsamples=10, the error calculation for each of the TSV will be as follows.
  For Bedrooms.tsv, distribution of various bedrooms is 0.2 in the buildstock.csv which exactly matches with the
  distribution in the TSV. Hences, max_option_error = total_option_error = 0.
  Since there are no dependencies, the max_group_error and total_group_error is also 0.
  
  For Fan.tsv, we expect the sample distribution for None, Standard and Premium to be 0.35, 0.35 and 0.3.
  The actual distribution is 0.5, 0.5 and 0.0. This gives absolute distribution errors as 0.15, 0.15 and 0.3.
  Hence, the max_option_error is 0.3 and total_option_error is 0.6
  There are 5 dependency groups [(1,), (2,), (3,), (4,), (5,)] in Fan.tsv with expected sample distribution of
  [0.2, 0.2, 0.2, 0.2, 0.2]. The actual probability distribution for these groups are also the same, both the
  max_group_error and total_group_error is 0.
  
  For AC.tsv, expect the sample distribution for Yes and No to be 0.625 (0.9 * 0.35 + 0.8 * 0.35 + 0.1 * 0.3) and
  0.375. The actual sample distribution we have for Yes and No is 0.9 and 0.1. This gives absolute distribution
  errors as 0.275 and 0.275. Hence, the max_option_error = 0.275 and total_option_error is 0.55.
  There are 3 dependency groups [(None,), (Standard,), (Premium,)] in AC.tsv with expected sample distribution of
  0.35, 0.35 and 0.3. The actual sample distribution we have for [(None,), (Standard,), (Premium,)] is 0.5, 0.5, 0.
  This gives absolute distribution error for group as 0.15, 0.15 and 0.3. Hence, max_group_error is 0.3 and
  total_group_eror is 0.6

Options:
  -p, --project TEXT  The path to the project (most have
                      housing_characteristics folder inside)  [required]
  -o, --output TEXT   The output filename for error report.
  --help              Show this message and exit.

Usage example:
resstock_sampler sample -p /Users/radhikar/Documents/resstock/project_national -o resstock_sampler_test.csv

resstock_sampler verify resstock_sampler_test.csv -p /Users/radhikar/Documents/resstock/project_national

Checklist

Not all may apply

• Code changes (must work)
• Tests exercising your feature/bug fix (check coverage report on Checks -> BuildStockBatch Tests -> Artifacts)
• Coverage has increased or at least not decreased. Update minimum_coverage in .github/workflows/ci.yml as necessary.
• All other unit tests passing
• Update validation for project config yaml file changes
• Update existing documentation
• Run a small batch run to make sure it all works (local is fine, unless an Eagle specific feature)
• Add to the changelog_dev.rst file and propose migration text in the pull request

[github-actions]

File	Coverage
All files	82%	✅
base.py	81%	✅
eagle.py	74%	✅
exc.py	57%	✅
localdocker.py	27%	✅
postprocessing.py	84%	✅
utils.py	96%	✅
sampler/base.py	69%	✅
sampler/downselect.py	33%	✅
sampler/precomputed.py	93%	✅
sampler/residential_quota.py	60%	✅
sampler/residential_sampler/sampler.py	71%	✅
sampler/residential_sampler/sampling_utils.py	99%	✅
test/test_validation.py	96%	✅
workflow_generator/base.py	90%	✅
workflow_generator/commercial.py	24%	✅
workflow_generator/residential.py	96%	✅
workflow_generator/residential_hpxml.py	59%	✅

Minimum allowed coverage is 24%

Generated by 🐒 cobertura-action against 0aefb48

[nmerket]

I appreciate the thorough testing. Is this ready for primetime?

Rather than replacing the current ruby based sampler here, I'd prefer if you added a new sampler file and class. That way people can go back to the old one for a while during a transition period.

[nmerket]

Why are we only testing Python 3.10 now? I'd like to keep some level of backwards compatibility.