def test_string_representation(self): self.assertTrue( isinstance(QuantifierRegistry.find("softmax_entropy"), SoftmaxEntropy)) self.assertTrue( isinstance(QuantifierRegistry.find("SoftmaxEntropy"), SoftmaxEntropy))
def test_string_representation(self): self.assertTrue( isinstance(QuantifierRegistry.find("predictive_entropy"), PredictiveEntropy) ) self.assertTrue( isinstance(QuantifierRegistry.find("pred_entropy"), PredictiveEntropy) )
def test_string_representation(self): self.assertTrue( isinstance(QuantifierRegistry.find("mutual_information"), MutualInformation)) self.assertTrue( isinstance(QuantifierRegistry.find("mutu_info"), MutualInformation))
def test_string_representation(self): self.assertTrue( isinstance(QuantifierRegistry.find("variation_ratio"), VariationRatio)) self.assertTrue( isinstance(QuantifierRegistry.find("var_ratio"), VariationRatio)) self.assertTrue( isinstance(QuantifierRegistry.find("VR"), VariationRatio))
def test_string_representation(self): self.assertTrue( isinstance(QuantifierRegistry.find("standard_deviation"), StandardDeviation)) self.assertTrue( isinstance(QuantifierRegistry.find("std"), StandardDeviation)) self.assertTrue( isinstance(QuantifierRegistry.find("stddev"), StandardDeviation))
def test_string_representation(self): self.assertTrue( isinstance(QuantifierRegistry.find("PCS"), PredictionConfidenceScore)) self.assertTrue( isinstance( QuantifierRegistry.find("prediction_confidence_score"), PredictionConfidenceScore, ))
def _quantifiers_as_list(quantifier): is_single_quantifier = False if isinstance(quantifier, list): quantifiers = quantifier else: quantifiers = [quantifier] is_single_quantifier = True quantifier_objects = [] for quantifier in quantifiers: if isinstance(quantifier, str): quantifier_objects.append(QuantifierRegistry.find(quantifier)) elif isinstance(quantifier, Quantifier): quantifier_objects.append(quantifier) else: raise TypeError( "The passed quantifier is neither a quantifier instance nor a quantifier alias (str)." f"Type of the passed object {str(type(quantifier))}") point_prediction_quantifiers = [ q for q in quantifier_objects if q.takes_samples() is False ] samples_based_quantifiers = [ q for q in quantifier_objects if q.takes_samples() is True ] return ( quantifier_objects, point_prediction_quantifiers, samples_based_quantifiers, is_single_quantifier, )
def test_string_representation(self): self.assertTrue( isinstance(QuantifierRegistry.find("softmax"), MaxSoftmax)) self.assertTrue( isinstance(QuantifierRegistry.find("max_softmax"), MaxSoftmax))
def test_string_representation(self): self.assertTrue( isinstance(QuantifierRegistry.find("mean_softmax"), MeanSoftmax)) self.assertTrue( isinstance(QuantifierRegistry.find("ensembling"), MeanSoftmax))
def test_string_representation(self): self.assertTrue( isinstance(QuantifierRegistry.find("DeepGini"), DeepGini)) self.assertTrue( isinstance(QuantifierRegistry.find("deep_gini"), DeepGini))
def test_error_if_invalid_quantifier_alias(self): with self.assertRaises(ValueError): QuantifierRegistry.find("nonexistent_q_hi1ö2rn1ld")
def test_error_if_alias_already_exists(self): with self.assertRaises(ValueError): QuantifierRegistry.register(VariationRatio())