def test_dimensions(self):
x = Table('iris')[:20].X
xt = Table('iris')[:20].X.T
mah = MahalanobisDistance(x)
mah(x[0], x[1])
mah = MahalanobisDistance(xt)
mah(xt[0], xt[1])
def test_correctness(self):
mah = MahalanobisDistance(self.x)
d = scipy.spatial.distance.pdist(self.x, 'mahalanobis')
d = scipy.spatial.distance.squareform(d)
for i in range(self.n):
for j in range(self.n):
self.assertAlmostEqual(d[i][j], mah(self.x[i], self.x[j]),
delta=1e-5)
def test_distance_combo(self):
"""Check distances when the metric changes"""
self.assertEqual(self.widget.metrics_combo.count(), len(METRICS))
self.send_signal("Data", self.iris)
for i, metric in enumerate(METRICS):
if isinstance(metric, MahalanobisDistance):
metric = MahalanobisDistance(self.iris)
self.widget.metrics_combo.activated.emit(i)
self.widget.metrics_combo.setCurrentIndex(i)
self.send_signal("Data", self.iris)
np.testing.assert_array_equal(metric(self.iris),
self.get_output("Distances"))
def test_attributes(self):
metric = MahalanobisDistance(self.x)
self.assertEqual(metric(self.x[0], self.x[1]).shape, (1, 1))
self.assertEqual(metric(self.x).shape, (self.n, self.n))
self.assertEqual(metric(self.x[0:3], self.x[5:7]).shape, (3, 2))
self.assertEqual(metric(self.x1, self.x2).shape, (1, 1))
metric(self.x, impute=True)
metric(self.x[:-1, :])
self.assertRaises(ValueError, metric, self.x[:, :-1])
self.assertRaises(ValueError, metric, self.x1[:-1], self.x2)
self.assertRaises(ValueError, metric, self.x1, self.x2[:-1])
self.assertRaises(ValueError, metric, self.x.T)
def test_knn_distance(self):
icp = InductiveClassifier(KNNDistance(Euclidean), self.train,
self.calibrate)
pred = icp(self.test.x, 0.1)
self.assertEqual(pred, ['Iris-setosa'])
icp = InductiveClassifier(KNNDistance(Cosine, 5), self.train,
self.calibrate)
pred = icp(self.test.x, 0.1)
self.assertEqual(pred, ['Iris-setosa'])
from Orange.distance import Mahalanobis
icp = InductiveClassifier(KNNDistance(Mahalanobis, 5), self.train,
self.calibrate)
pred = icp(self.test.x, 0.1)
self.assertEqual(pred, ['Iris-setosa'])
from Orange.distance import MahalanobisDistance
Mah = MahalanobisDistance(self.train)
icp = InductiveClassifier(KNNDistance(Mah, 5), self.train,
self.calibrate)
pred = icp(self.test.x, 0.1)
self.assertEqual(pred, ['Iris-setosa'])
def test_iris(self):
tab = Table('iris')
metric = MahalanobisDistance(tab)
self.assertEqual(metric(tab).shape, (150, 150))
self.assertEqual(metric(tab[0], tab[1]).shape, (1, 1))
