some LGTM warning changes

X-DataInitiative / tick

Module for statistical learning, with a particular emphasis on time-dependent modelling

https://x-datainitiative.github.io/tick/

BSD 3-Clause "New" or "Revised" License

484 stars 105 forks source link

some LGTM warning changes #463

Closed PhilipDeegan closed 2 years ago

PhilipDeegan commented 4 years ago

https://lgtm.com/projects/g/X-DataInitiative/tick/?mode=list

lgtm-com[bot] commented 4 years ago

This pull request fixes 11 alerts when merging c7117d93df9effda00cf68bb5b7f9c09022a585a into bbc561804eb1fdcb4c71b9e3e2d83a66e7b13a48 - view on LGTM.com

fixed alerts:

2 for Unused import
2 for Variable defined multiple times
2 for Unused exception object
1 for Unnecessary pass
1 for Module is imported more than once
1 for Unused local variable
1 for Unreachable code
1 for Comparison result is always the same

PhilipDeegan commented 2 years ago

@MaryanMorel thoughts https://github.com/X-DataInitiative/tick/runs/4990731694?check_suite_focus=true#step:5:1553 ?

lgtm-com[bot] commented 2 years ago

This pull request fixes 11 alerts when merging 6c2ab67a2984f7979d56e38136f683667f6355a4 into bbc561804eb1fdcb4c71b9e3e2d83a66e7b13a48 - view on LGTM.com

fixed alerts:

2 for Unused import
2 for Variable defined multiple times
2 for Unused exception object
1 for Unnecessary pass
1 for Module is imported more than once
1 for Unused local variable
1 for Unreachable code
1 for Comparison result is always the same

MaryanMorel commented 2 years ago

@MaryanMorel thoughts https://github.com/X-DataInitiative/tick/runs/4990731694?check_suite_focus=true#step:5:1553 ?

It seems like the import path is wrong:

from sklearn.metrics.ranking import roc_auc_score

should be

from sklearn.metrics import roc_auc_score

which is a bit weird, it should have failed a long time ago, unless we were using veeery old versions of scikit-learn maybe?

PhilipDeegan commented 2 years ago

@MaryanMorel thoughts https://github.com/X-DataInitiative/tick/runs/4990731694?check_suite_focus=true#step:5:1553 ?

...

there hasn't been a build in a while. I have fixed that one, but it's more the kf = StratifiedKFold(n_folds, shuffle, self.random_state) one that I can't fix