def test_only_accept_numpy_arrays(self):
"""Verifys ValueError exception is raised when a array is not
provided"""
with self.assertRaises(ValueError):
ensembler = ensemble.BinaryEnsembler()
ensembler.fit(1, targets)
with self.assertRaises(ValueError):
ensembler = ensemble.BinaryEnsembler()
ensembler.fit(predictions, 1)
with self.assertRaises(ValueError):
ensembler = ensemble.BinaryEnsembler()
ensembler.fit("example", targets)
with self.assertRaises(ValueError):
ensembler = ensemble.BinaryEnsembler()
ensembler.fit(predictions, "example")
def test_rows_average_correctly(self):
"""Verifys that the sum of each row is correct when the mean
method is used."""
ensembler = ensemble.BinaryEnsembler(method="mean")
ensembler.fit(predictions, targets)
ensemble_ps = ensembler.predict(predictions)
self.assertTrue(all(ensemble_ps == true_averages))
def test_warning_raised_if_no_weights_provided(self):
"""Verifys a warning is raised if weights are not provided but
method=="weighted"."""
with self.assertWarns(UserWarning):
ensembler = ensemble.BinaryEnsembler(method="weighted")
ensembler.fit(predictions, targets)
def test_weights_are_applied(self):
"""Verify correct ensembled predictions when weights applied."""
ensembler = ensemble.BinaryEnsembler(method="weighted")
ensembler.fit(predictions, targets, weights=ex_weights)
ensemble_ps = ensembler.predict(predictions)
self.assertTrue(all(ensemble_ps == weighted_average_predictions))
def test_preserves_number_of_rows(self):
"""Verifys that averaging is performed along the columnar axis."""
ensembler = ensemble.BinaryEnsembler(method="mean")
ensembler.fit(predictions, targets)
ensemble_ps = ensembler.predict(predictions)
self.assertTrue(ensemble_ps.shape[0] == predictions.shape[0])