[MRG + 1] move custom error/warning classes into sklearn.exceptions (and move `deprecated` away from `utils.init.py`) #4826

raghavrv · 2015-06-05T19:01:38Z

(@larsmans apologies for proceeding without ur reply... I thought this would be nice to have while fixing #2904 since 2 / 5 classes were in cross_validation.py and grid_search.py)

BTW I left out the utils.arpack.ArpackError and utils.tests.test_estimator_checks.CorrectNotFittedError.

Please review @amueller @larsmans @ogrisel @agramfort :)

raghavrv · 2015-06-06T15:46:53Z

@larsmans Thanks for the review!! I assumed NonBLASDotWarning to have been considered as a part of utills that is not explicitly exposed for public use and hence skipped deprecating it... Please let me know if anything else needs to be done...

Also I agree that NonBLASDotWarning could just be kept as a private class at utils.extmath itself.... Please let me know if I should do so? (also @amueller @agramfort @ogrisel your views on the same? :) )

amueller · 2015-06-06T17:23:16Z

Why did you rename the NonBlasDot warning?

raghavrv · 2015-06-06T17:29:47Z

Lars felt NonBLASDotWarning need not be exposed as such and could perhaps be renamed to EfficiencyWarning before exposing, if needed...

Can I keep it as NonBLASWarning and not expose it in exceptions.py since utils.extmath is not public?

amueller · 2015-06-06T17:36:04Z

I didn't see his comment. it's fine then. Should we deprecate? I have no strong opinion and I'd be fine with merging as-is.

raghavrv · 2015-06-06T17:40:43Z

Thanks for the review! :)

@larsmans One final look at this?

raghavrv · 2015-06-08T11:50:05Z

@jnothman @agramfort Could I trouble you for a review? :)

~~@amueller I'll count your earlier comment as a +1 ?~~ More work to be done here ;)

jnothman · 2015-06-08T11:52:44Z

sklearn/exceptions.py

+    """
+
+
+class FitFailedWarning(RuntimeWarning):


When taken out of context of a particular module, these need docstrings to explain when they should be used or expected. It may even be appropriate to add these to doc/modules/classes.rst as part of the public API.

raghavrv · 2015-06-10T14:16:28Z

Can I skip the doc tests for the added examples?

amueller · 2015-06-10T17:50:17Z

sklearn/exceptions.py

+    >>> import warnings
+    >>> warnings.simplefilter('always', ChangedBehaviorWarning)
+    >>> gs = GridSearchCV(estimator=LinearSVC(random_state=0),
+                          param_grid={'C': [1, 10, 100]}, scoring='f1_micro')


you are missing ... here.

amueller · 2015-06-10T18:03:52Z

the current doctests fail not because of raising warning but because of errors in the doctests.

raghavrv · 2015-06-10T18:10:18Z

@amueller Thanks for the review! :)

Also do you feel the Examples are fine? Or should they be written from a devs perspective (As an example for where (s)he'd use the Error/Warning...)?

raghavrv · 2015-06-11T13:30:47Z

Please let me know if there is anything else to be done! Also do we need a user guide for the exceptions module?

ogrisel · 2015-06-11T13:53:52Z

sklearn/exceptions.py

+    """
+
+
+# TODO Import from model_selection


why this TODO?

I'll remove!

ENH NonBLASDotWarning -> EfficiencyWarning; Improve error message DOC Add exceptions module to modules/classes.rst MAINT Move ConvergenceWarning, UndefinedMetricWarning et al into exceptions MAINT Remove ChangedBehaviorWarning from base DOC/FIX Improve DataConversionWarning's docstring

…classes)

raghavrv · 2015-10-19T20:36:23Z

Done! @GaelVaroquaux and @pletelli could you please review? :)

GaelVaroquaux · 2015-10-19T21:08:51Z

Travis failed!

raghavrv · 2015-10-19T22:38:03Z

Hmm Interesting failure... Looks like deprecating them has side effects that propagate back to the sklearn.exceptions module...

raghavrv · 2015-10-19T22:58:23Z

I think the last commit should fix it... Its not an ugly hack I feel...

GaelVaroquaux · 2015-10-19T23:08:05Z

Still failing.

Are you running the tests on your computer? This might save you some time.

raghavrv · 2015-10-20T08:05:30Z

Apologies! I got a bit overconfident and assumed it would pass :/ (This version passes on my machine!)

raghavrv · 2015-10-20T08:05:37Z

and on travis too :)

GaelVaroquaux · 2015-10-20T08:37:34Z

sklearn/exceptions.py

+    """
+
+
+class UndefinedMetricWarning(UserWarning):


Maybe this guy should have a description.

GaelVaroquaux · 2015-10-20T08:48:41Z

👍

Merging. Good job!

[MRG + 1] move custom error/warning classes into sklearn.exceptions (and move `deprecated` away from `utils.__init__.py`)

raghavrv · 2015-10-20T08:49:55Z

Wait.. Description for undefined metric warning?

raghavrv · 2015-10-20T08:50:13Z

Anyway thanks for the review and merge :)

GaelVaroquaux · 2015-10-20T08:53:23Z

Wait.. Description for undefined metric warning?

Oh, yeah. Can you send a new PR. I'll merge it ASAP.

raghavrv · 2015-10-20T13:29:29Z

Done and merged at #5478

Squashed commit messages - (For reference) Major ----- * ENH p --> n_labels * FIX *ShuffleSplit: all float/invalid type errors at init and int error at split * FIX make PredefinedSplit accept test_folds in constructor; Cleanup docstrings * ENH+TST KFold: make rng to be generated at every split call for reproducibility * FIX/MAINT KFold: make shuffle a public attr * FIX Make CVIterableWrapper private. * FIX reuse len_cv instead of recalculating it * FIX Prevent adding *SearchCV estimators from the old grid_search module * re-FIX In all_estimators: the sorting to use only the 1st item (name) To avoid collision between the old and the new GridSearch classes. * FIX test_validate.py: Use 2D X (1D X is being detected as a single sample) * MAINT validate.py --> validation.py * MAINT make the submodules private * MAINT Support old cv/gs/lc until 0.19 * FIX/MAINT n_splits --> get_n_splits * FIX/TST test_logistic.py/test_ovr_multinomial_iris: pass predefined folds as an iterable * MAINT expose BaseCrossValidator * Update the model_selection module with changes from master - From scikit-learn#5161 - - MAINT remove redundant p variable - - Add check for sparse prediction in cross_val_predict - From scikit-learn#5201 - DOC improve random_state param doc - From scikit-learn#5190 - LabelKFold and test - From scikit-learn#4583 - LabelShuffleSplit and tests - From scikit-learn#5300 - shuffle the `labels` not the `indxs` in LabelKFold + tests - From scikit-learn#5378 - Make the GridSearchCV docs more accurate. - From scikit-learn#5458 - Remove shuffle from LabelKFold - From scikit-learn#5466(scikit-learn#4270) - Gaussian Process by Jan Metzen - From scikit-learn#4826 - Move custom error / warnings into sklearn.exception Minor ----- * ENH Make the KFold shuffling test stronger * FIX/DOC Use the higher level model_selection module as ref * DOC in check_cv "y : array-like, optional" * DOC a supervised learning problem --> supervised learning problems * DOC cross-validators --> cross-validation strategies * DOC Correct Olivier Grisel's name ;) * MINOR/FIX cv_indices --> kfold * FIX/DOC Align the 'See also' section of the new KFold, LeaveOneOut * TST/FIX imports on separate lines * FIX use __class__ instead of classmethod * TST/FIX import directly from model_selection * COSMIT Relocate the random_state documentation * COSMIT remove pass * MAINT Remove deprecation warnings from old tests * FIX correct import at test_split * FIX/MAINT Move P_sparse, X, y defns to top; rm unused W_sparse, X_sparse * FIX random state to avoid doctest failure * TST n_splits and split wrapping of _CVIterableWrapper * FIX/MAINT Use multilabel indicator matrix directly * TST/DOC clarify why we conflate classes 0 and 1 * DOC add comment that this was taken from BaseEstimator * FIX use of labels is not needed in stratified k fold * Fix cross_validation reference * Fix the labels param doc

-------------------- * ENH Reogranize classes/fn from grid_search into search.py * ENH Reogranize classes/fn from cross_validation into split.py * ENH Reogranize cls/fn from cross_validation/learning_curve into validate.py * MAINT Merge _check_cv into check_cv inside the model_selection module * MAINT Update all the imports to point to the model_selection module * FIX use iter_cv to iterate throught the new style/old style cv objs * TST Add tests for the new model_selection members * ENH Wrap the old-style cv obj/iterables instead of using iter_cv * ENH Use scipy's binomial coefficient function comb for calucation of nCk * ENH Few enhancements to the split module * ENH Improve check_cv input validation and docstring * MAINT _get_test_folds(X, y, labels) --> _get_test_folds(labels) * TST if 1d arrays for X introduce any errors * ENH use 1d X arrays for all tests; * ENH X_10 --> X (global var) Minor ----- * ENH _PartitionIterator --> _BaseCrossValidator; * ENH CVIterator --> CVIterableWrapper * TST Import the old SKF locally * FIX/TST Clean up the split module's tests. * DOC Improve documentation of the cv parameter * COSMIT consistently hyphenate cross-validation/cross-validator * TST Calculate n_samples from X * COSMIT Use separate lines for each import. * COSMIT cross_validation_generator --> cross_validator Commits merged manually ----------------------- * FIX Document the random_state attribute in RandomSearchCV * MAINT Use check_cv instead of _check_cv * ENH refactor OVO decision function, use it in SVC for sklearn-like decision_function shape * FIX avoid memory cost when sampling from large parameter grids ENH Major to Minor incremental enhancements to the model_selection Squashed commit messages - (For reference) Major ----- * ENH p --> n_labels * FIX *ShuffleSplit: all float/invalid type errors at init and int error at split * FIX make PredefinedSplit accept test_folds in constructor; Cleanup docstrings * ENH+TST KFold: make rng to be generated at every split call for reproducibility * FIX/MAINT KFold: make shuffle a public attr * FIX Make CVIterableWrapper private. * FIX reuse len_cv instead of recalculating it * FIX Prevent adding *SearchCV estimators from the old grid_search module * re-FIX In all_estimators: the sorting to use only the 1st item (name) To avoid collision between the old and the new GridSearch classes. * FIX test_validate.py: Use 2D X (1D X is being detected as a single sample) * MAINT validate.py --> validation.py * MAINT make the submodules private * MAINT Support old cv/gs/lc until 0.19 * FIX/MAINT n_splits --> get_n_splits * FIX/TST test_logistic.py/test_ovr_multinomial_iris: pass predefined folds as an iterable * MAINT expose BaseCrossValidator * Update the model_selection module with changes from master - From #5161 - - MAINT remove redundant p variable - - Add check for sparse prediction in cross_val_predict - From #5201 - DOC improve random_state param doc - From #5190 - LabelKFold and test - From #4583 - LabelShuffleSplit and tests - From #5300 - shuffle the `labels` not the `indxs` in LabelKFold + tests - From #5378 - Make the GridSearchCV docs more accurate. - From #5458 - Remove shuffle from LabelKFold - From #5466(#4270) - Gaussian Process by Jan Metzen - From #4826 - Move custom error / warnings into sklearn.exception Minor ----- * ENH Make the KFold shuffling test stronger * FIX/DOC Use the higher level model_selection module as ref * DOC in check_cv "y : array-like, optional" * DOC a supervised learning problem --> supervised learning problems * DOC cross-validators --> cross-validation strategies * DOC Correct Olivier Grisel's name ;) * MINOR/FIX cv_indices --> kfold * FIX/DOC Align the 'See also' section of the new KFold, LeaveOneOut * TST/FIX imports on separate lines * FIX use __class__ instead of classmethod * TST/FIX import directly from model_selection * COSMIT Relocate the random_state documentation * COSMIT remove pass * MAINT Remove deprecation warnings from old tests * FIX correct import at test_split * FIX/MAINT Move P_sparse, X, y defns to top; rm unused W_sparse, X_sparse * FIX random state to avoid doctest failure * TST n_splits and split wrapping of _CVIterableWrapper * FIX/MAINT Use multilabel indicator matrix directly * TST/DOC clarify why we conflate classes 0 and 1 * DOC add comment that this was taken from BaseEstimator * FIX use of labels is not needed in stratified k fold * Fix cross_validation reference * Fix the labels param doc FIX/DOC/MAINT Addressing the review comments by Arnaud and Andy COSMIT Sort the members alphabetically COSMIT len_cv --> n_splits COSMIT Merge 2 if; FIX Use kwargs DOC Add my name to the authors :D DOC make labels parameter consistent FIX Remove hack for boolean indices; + COSMIT idx --> indices; DOC Add Returns COSMIT preds --> predictions DOC Add Returns and neatly arrange X, y, labels FIX idx(s)/ind(s)--> indice(s) COSMIT Merge if and else to elif COSMIT n --> n_samples COSMIT Use bincount only once COSMIT cls --> class_i / class_i (ith class indices) --> perm_indices_class_i FIX/ENH/TST Addressing the final reviews COSMIT c --> count FIX/TST make check_cv raise ValueError for string cv value TST nested cv (gs inside cross_val_score) works for diff cvs FIX/ENH Raise ValueError when labels is None for label based cvs; TST if labels is being passed correctly to the cv and that the ValueError is being propagated to the cross_val_score/predict and grid search FIX pass labels to cross_val_score FIX use make_classification DOC Add Returns; COSMIT Remove scaffolding TST add a test to check the _build_repr helper REVERT the old GS/RS should also be tested by the common tests. ENH Add a tuple of all/label based CVS FIX raise VE even at get_n_splits if labels is None FIX Fabian's comments PEP8

raghavrv force-pushed the exceptions branch 4 times, most recently from 74a6ef6 to b9faf05 Compare June 6, 2015 15:27

jnothman reviewed Jun 8, 2015
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larsmans changed the title ~~MAINT move custom error/warning classes into sklearn.exceptions~~ [WIP] move custom error/warning classes into sklearn.exceptions Jun 8, 2015

raghavrv force-pushed the exceptions branch 2 times, most recently from d62316b to 66cedb6 Compare June 10, 2015 09:43

amueller reviewed Jun 10, 2015
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raghavrv force-pushed the exceptions branch 5 times, most recently from 9156de2 to e2dd2a1 Compare June 11, 2015 13:23

raghavrv force-pushed the exceptions branch from e2dd2a1 to bcdf38f Compare June 11, 2015 13:35

ogrisel reviewed Jun 11, 2015
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raghavrv added 4 commits October 19, 2015 22:35

DOC/SPHINX Add template for classes which don't have init (Exception …

09f0fa7

…classes)

MAINT Deprecated the UndefinedMetricWarning at sklearn.metrics.base

e19a981

MAINT move deprecated into deprecation.py

61ae8d5

raghavrv force-pushed the exceptions branch from acce9cf to 61ae8d5 Compare October 19, 2015 20:36

raghavrv force-pushed the exceptions branch from 93404dc to 087b0df Compare October 19, 2015 23:09

FIX/ENH Make the moved class resilient to the deprecation patching

857cb09

raghavrv force-pushed the exceptions branch from 087b0df to 857cb09 Compare October 19, 2015 23:24

GaelVaroquaux reviewed Oct 20, 2015
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sklearn/exceptions.py

"""

class UndefinedMetricWarning(UserWarning):

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Maybe this guy should have a description.

GaelVaroquaux added a commit that referenced this pull request Oct 20, 2015

Merge pull request #4826 from rvraghav93/exceptions

d4e9d79

[MRG + 1] move custom error/warning classes into sklearn.exceptions (and move `deprecated` away from `utils.__init__.py`)

GaelVaroquaux merged commit d4e9d79 into scikit-learn:master Oct 20, 2015

raghavrv deleted the exceptions branch October 20, 2015 13:29

Uh oh!

[MRG + 1] move custom error/warning classes into sklearn.exceptions (and move deprecated away from utils.__init__.py) #4826

[MRG + 1] move custom error/warning classes into sklearn.exceptions (and move deprecated away from utils.__init__.py) #4826

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raghavrv commented Jun 5, 2015

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[MRG + 1] move custom error/warning classes into sklearn.exceptions (and move `deprecated` away from `utils.init.py`) #4826

[MRG + 1] move custom error/warning classes into sklearn.exceptions (and move `deprecated` away from `utils.init.py`) #4826