lint fix

Author: Nabil Fayak

checkmates/objectives/__init__.py

@@ -12,5 +12,9 @@
 from checkmates.objectives.standard_metrics import RootMeanSquaredLogError
 from checkmates.objectives.standard_metrics import MeanSquaredLogError
 
-from checkmates.objectives.binary_classification_objective import BinaryClassificationObjective
-from checkmates.objectives.multiclass_classification_objective import MulticlassClassificationObjective
+from checkmates.objectives.binary_classification_objective import (
+    BinaryClassificationObjective,
+)
+from checkmates.objectives.multiclass_classification_objective import (
+    MulticlassClassificationObjective,
+)

checkmates/objectives/binary_classification_objective.py

@@ -81,4 +81,4 @@ def validate_inputs(self, y_true, y_predicted):
         if len(np.unique(y_true)) > 2:
             raise ValueError("y_true contains more than two unique values")
         if len(np.unique(y_predicted)) > 2 and not self.score_needs_proba:
-            raise ValueError("y_predicted contains more than two unique values")
+            raise ValueError("y_predicted contains more than two unique values")

checkmates/objectives/multiclass_classification_objective.py

@@ -7,4 +7,4 @@ class MulticlassClassificationObjective(ObjectiveBase):
     """Base class for all multiclass classification objectives."""
 
     problem_types = [ProblemTypes.MULTICLASS, ProblemTypes.TIME_SERIES_MULTICLASS]
-    """[ProblemTypes.MULTICLASS, ProblemTypes.TIME_SERIES_MULTICLASS]"""
+    """[ProblemTypes.MULTICLASS, ProblemTypes.TIME_SERIES_MULTICLASS]"""

checkmates/objectives/standard_metrics.py

@@ -3,10 +3,14 @@
 import pandas as pd
 from sklearn import metrics
 
+from checkmates.objectives.binary_classification_objective import (
+    BinaryClassificationObjective,
+)
+from checkmates.objectives.multiclass_classification_objective import (
+    MulticlassClassificationObjective,
+)
 from checkmates.objectives.regression_objective import RegressionObjective
 from checkmates.utils import classproperty
-from checkmates.objectives.binary_classification_objective import BinaryClassificationObjective
-from checkmates.objectives.multiclass_classification_objective import MulticlassClassificationObjective
 
 
 class LogLossBinary(BinaryClassificationObjective):
@@ -36,6 +40,7 @@ def objective_function(
         """Objective function for log loss for binary classification."""
         return metrics.log_loss(y_true, y_predicted, sample_weight=sample_weight)
 
+
 class LogLossMulticlass(MulticlassClassificationObjective):
     """Log Loss for multiclass classification.
 
@@ -68,6 +73,7 @@ def objective_function(
         """Objective function for log loss for multiclass classification."""
         return metrics.log_loss(y_true, y_predicted, sample_weight=sample_weight)
 
+
 class R2(RegressionObjective):
     """Coefficient of determination for regression.
 
@@ -95,6 +101,7 @@ def objective_function(
         """Objective function for coefficient of determination for regression."""
         return metrics.r2_score(y_true, y_predicted, sample_weight=sample_weight)
 
+
 class MedianAE(RegressionObjective):
     """Median absolute error for regression.
 
@@ -127,7 +134,6 @@ def objective_function(
         )
 
 
-
 class RootMeanSquaredLogError(RegressionObjective):
     """Root mean squared log error for regression.
 

checkmates/objectives/utils.py

@@ -20,6 +20,7 @@ def get_non_core_objectives():
         objectives.RootMeanSquaredLogError,
     ]
 
+
 def get_all_objective_names():
     """Get a list of the names of all objectives.
 
@@ -29,6 +30,7 @@ def get_all_objective_names():
     all_objectives_dict = _all_objectives_dict()
     return list(all_objectives_dict.keys())
 
+
 def _all_objectives_dict():
     all_objectives = _get_subclasses(ObjectiveBase)
     objectives_dict = {}