Add tests using testthat

[nikolase90]

If you're working on one of these files, please add the url to your branch or the pull request. Mark the box if the changes are merged with master.

R-files

• [ ] clustering.R
• [x] explanation.R#128
• [x] features.R https://github.com/NorskRegnesentral/shapr/pull/70
• [x] observations.R https://github.com/NorskRegnesentral/shapr/pull/95
• [x] plot.R https://github.com/NorskRegnesentral/shapr/pull/86
• [x] predictions.R https://github.com/NorskRegnesentral/shapr/pull/109
• [x] sampling.Rhttps://github.com/NorskRegnesentral/shapr/pull/92
• [x] shapley.R #128
• [x] transformation.R https://github.com/NorskRegnesentral/shapr/pull/77
• [x] utils.R Currently there are zero functions in R/utils.R.
• [x] models.R https://github.com/NorskRegnesentral/shapr/pull/129

src-files

• [ ] AICc.cpp
• [ ] distance.cpp
• [x] impute_data.cpp https://github.com/NorskRegnesentral/shapr/pull/78
• [x] weighted_matrix.cpp https://github.com/NorskRegnesentral/shapr/pull/73

The following files should not be tested

• R/shapr-package.R
• R/zzz.R

[martinju]

I am getting a bit worried that every time we make a change to shap or explain functions, we have to re-create the test objects (explanation_explain_obj.rds and similar) which compares the results of the previous run to pass the tests. That means we don't have a good test for this. This is especially dangerous if one does many changes in the same PR (although we seldom do that).

My suggestion is to add a seperate test that checks only the shapley values from the different test models. We could run a lapply call to the ex_list, extract only the data.table with the shapley values, and then do a testthat::expect_known_value or testthat::expect_known_object on that. What do you think @nikolase90 ? Or is there a better option?

[nikolase90]

@martinju I think that sounds like a good way to do it.