(Regression) tests against example datasets from the R MLCM package#23
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Setup specific paths for finding R, sometimes necessary.
For each trial response, a comment that explains the reasoning of that row. Also swap the dimensions around: this clears up the resulting scales a bit. Now, the numerical dimA is on the rows, and separate columns (scales) for the ordinal/categorical dimB.
Changes to how strings are handled in pandas, as well as whether `replace` downcasts.
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I reviewed it, alll good. I added some comments on top of conftest.py, to explain what are those fixtures for, as it was unclear to me the first time I saw it. I took the liberity to push those changes directly. |
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The R {{MLCM}} package comes with several example datasets -- primarily the ones on Bumpiness and Glossiness, from Ho, Land and Maloney (2008).
Example (testing) datasets
Here, these datasets are included as part of the test-suite in
tests/example_datasets/. Each dataset comes with:wrangled_<...>.csvdata, which is the data as it is included in the R package, though with slightly more informative column headers.trials_<...>.csv, as it would most likely come out of the experiment (this is reverse-engineered from the wrangled data)test_<...>.py, which contains the actual tests. This also has the hardcoded the resulting perceptual scales that are produced by running the MLCM scale estimation in R. These are hardcoded, because those values should be unaffected by any changes we make in this Python package.Additional changes
Along the way, a few other fixes have been made:
epsilonto the scale estimationpython==3.14, also as part of the CIpandas>=3.0-- these were warned about through deprecation warnings, so it's good to have tackled them. These fixes are also backwards compatible withpandas<3.0, so nothing lost there.