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())