@@ -438,7 +438,7 @@ def test_set_max(self):
438438 # case 1: the estimator is not fitted yet
439439 regressor = mock .MockClassifier ()
440440 learner = modAL .models .BayesianOptimizer (estimator = regressor )
441- self .assertEqual (None , learner .max_val )
441+ self .assertEqual (- np . inf , learner .max_val )
442442
443443 # case 2: the estimator is fitted already
444444 for n_samples in range (1 , 100 ):
@@ -453,15 +453,15 @@ def test_set_max(self):
453453 )
454454 np .testing .assert_almost_equal (max_val , learner .max_val )
455455
456- def test_check_max (self ):
456+ def test_set_new_max (self ):
457457 for n_reps in range (100 ):
458458 # case 1: the learner is not fitted yet
459459 for n_samples in range (1 , 10 ):
460460 y = np .random .rand (n_samples )
461461 regressor = mock .MockClassifier ()
462462 learner = modAL .models .BayesianOptimizer (estimator = regressor )
463- learner ._check_max (y )
464- self .assertEqual (learner .max_val , None )
463+ learner ._set_max (y )
464+ self .assertEqual (learner .max_val , np . max ( y ) )
465465
466466 # case 2: new value is not a maximum
467467 for n_samples in range (1 , 10 ):
@@ -476,7 +476,7 @@ def test_check_max(self):
476476
477477 y_new = y - np .random .rand ()
478478 old_max = learner .max_val
479- learner ._check_max (y_new )
479+ learner ._set_max (y_new )
480480 np .testing .assert_almost_equal (old_max , learner .max_val )
481481
482482 # case 3: new value is a maximum
@@ -491,14 +491,10 @@ def test_check_max(self):
491491 )
492492
493493 y_new = y + np .random .rand ()
494- learner ._check_max (y_new )
494+ learner ._set_max (y_new )
495495 np .testing .assert_almost_equal (np .max (y_new ), learner .max_val )
496496
497497
498-
499-
500-
501-
502498class TestCommittee (unittest .TestCase ):
503499
504500 def test_set_classes (self ):
@@ -649,4 +645,4 @@ def test_examples(self):
649645
650646
651647if __name__ == '__main__' :
652- unittest .main ()
648+ unittest .main (verbosity = 2 )
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