class TestEIF2D(unittest.TestCase):
def setUp(self):
self.graph2d = graph2d
print(self.graph2d.Y)
lids2d = np.random.choice(graph2d.X.shape[0], 10, replace=False)
uids = np.delete(np.arange(self.graph2d.Y.shape[0]), lids2d)
self.ym = np.argmax(self.graph2d.Y[uids])
Yl2d = graph2d.Y[lids2d]
graph2d.Y = np.zeros((graph2d.Y.shape[0]))
graph2d.update(lids2d, Yl2d)
self.lp = HMN(self.graph2d)
def test_compute(self):
self.lp.label_propagate(self.graph2d)
print(self.graph2d.Y)
eif = EIF(self.graph2d, self.lp)
uids = np.delete(np.arange(self.graph2d.Y.shape[0]), self.graph2d.lids)
a = []
for id_test in uids:
a.append(eif.compute(int(id_test)))
print("a:", a)
ympred = a[self.ym]
print("max y prediction", ympred)
rank = sorted(a, reverse=True).index(ympred)
print("rank:", rank)
assert len(a) == uids.shape[0]
def test_hmn_2d(self):
hmn = HMN(self.graph2d)
YL = self.graph2d.Y[self.graph2d.lids]
hmn.label_propagate(self.graph2d)
assert np.array_equal(self.graph2d.Y[self.graph2d.lids], YL)
#print("True 2d: ", self.trueY2d[:20])
#print("Label propagation: ", self.graph2d.Y[:20])
print("hmn mse", sum((self.trueY2d - self.graph2d.Y)**2))