Closed UltraArceus3 closed 3 days ago
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Hi @rasbt, we're looking at the failed formatting test case. The suggested formatting seems to be strange.
It looks like it is taking issue with two lines in test_association_rules.py
. It is formatting just those two lines rather than the entire block. We could go back and change all the lines to reflect that same format, but then it would take up ~100 lines of just numbers. What are your thoughts?
It looks like it is taking issue with two lines in test_association_rules.py. It is formatting just those two lines rather than the entire block. We could go back and change all the lines to reflect that same format, but then it would take up ~100 lines of just numbers. What are your thoughts?
Thanks for the PR. I am totally fine with not changing the formatting as suggested by black here. Let's see if this can be achieved via an # fmt: off
Thanks @rasbt for reviewing and approving the change. It was fun to contribute to the library!
Thanks @rasbt for approving and reviewing our change! It was a great experience to contribute to this library!
Thank you @rasbt! It was great working with you on this change. We hope to continue contributing to your library in the future!
Description
We have implemented three association rules metrics: Jaccard Coefficient, Certainty Factor, and Kulczynski. We have added appropriate test cases for each of these metrics. We have also added an optional parameter to
association_rules
, calledreturn_metrics
. The user can pass in a list of metrics for the function to return, rather than having the function generate every implemented metric.Related issues or pull requests
Resolves #1096
Pull Request Checklist
./docs/sources/CHANGELOG.md
file (if applicable)./mlxtend/*/tests
directories (if applicable)mlxtend/docs/sources/
(if applicable)PYTHONPATH='.' pytest ./mlxtend -sv
and make sure that all unit tests pass (for small modifications, it might be sufficient to only run the specific test file, e.g.,PYTHONPATH='.' pytest ./mlxtend/classifier/tests/test_stacking_cv_classifier.py -sv
)flake8 ./mlxtend