def test_transformation(self):
R12 = np.random.rand(5, 3)
t1 = ObjectType('type1', 2)
t2 = ObjectType('type2', 2)
relation = Relation(R12, t1, t2)
fusion_graph = FusionGraph()
fusion_graph.add_relation(relation)
rnds = np.random.RandomState(0)
fuser = Dfmf(init_type='random', random_state=rnds, max_iter=100
).fuse(fusion_graph)
new_R12 = R12[:2].copy()
new_graph = FusionGraph([Relation(new_R12, t1, t2)])
new_rnds = np.random.RandomState(0)
transformer = DfmfTransform(random_state=new_rnds).transform(
t1, new_graph, fuser)
new_G1 = transformer.factor(t1)
G1 = fuser.factor(t1)
G2 = fuser.factor(t2)
S12 = fuser.backbone(relation)
new_R12_hat = np.dot(new_G1, np.dot(S12, G2.T))
R12_hat = np.dot(G1, np.dot(S12, G2.T))
diff_G1 = new_G1 - G1[:2]
diff_hat = new_R12_hat - R12_hat[:2]
self.assertLess(np.sum(diff_G1 ** 2) / diff_G1.size, 1e-5)
self.assertLess(np.sum(diff_hat ** 2) / diff_hat.size, 1e-5)
def test_get_names_by_object_type(self):
rnds = np.random.RandomState(0)
X = rnds.rand(10, 10)
t1_names = list('ABCDEFGHIJ')
t2_names = list('KLMNOPQRST')
rel = Relation(X,
name='Test',
row_type=self.t1,
row_names=t1_names,
col_type=self.t2,
col_names=t2_names)
rel2 = Relation(X,
name='Test2',
row_type=self.t2,
row_names=t2_names,
col_type=self.t3)
fusion_graph = FusionGraph()
fusion_graph.add_relation(rel)
fusion_graph.add_relation(rel2)
self.assertEqual(fusion_graph.get_names(self.t1), t1_names)
self.assertEqual(fusion_graph.get_names(self.t2), t2_names)
t3_names = fusion_graph.get_names(self.t3)
self.assertEqual(len(t3_names), 10)
def test_get_object_type_metadata(self):
rnds = np.random.RandomState(0)
X = rnds.rand(10, 10)
a, b, c = list('ABCDEFGHIJ'), list('0123456789'), list('KLMNOPQRST')
t1_metadata = [{'a': x} for x in a]
t2_metadata = [{'b': x} for x in b]
t2_metadata2 = [{'d': x} for x in b]
rel = Relation(X, name='Test',
row_type=self.t1, row_metadata=t1_metadata,
col_type=self.t2, col_metadata=t2_metadata)
rel2 = Relation(X, name='Test2',
row_type=self.t2, row_metadata=t2_metadata2,
col_type=self.t3)
fusion_graph = FusionGraph()
fusion_graph.add_relation(rel)
fusion_graph.add_relation(rel2)
def merge(d1, d2):
d = {}
d.update(d1)
d.update(d2)
return d
self.assertEqual(fusion_graph.get_metadata(self.t1), t1_metadata)
self.assertEqual(fusion_graph.get_metadata(self.t2), list(map(merge, t2_metadata, t2_metadata2)))
t3_metadata = fusion_graph.get_metadata(self.t3)
self.assertEqual(len(t3_metadata), 10)
for md in t3_metadata:
self.assertFalse(md)
def test_transformation(self):
R12 = np.random.rand(5, 3)
t1 = ObjectType('type1', 2)
t2 = ObjectType('type2', 2)
relation = Relation(R12, t1, t2)
fusion_graph = FusionGraph()
fusion_graph.add_relation(relation)
rnds = np.random.RandomState(0)
fuser = Dfmf(init_type='random', random_state=rnds,
max_iter=100).fuse(fusion_graph)
new_R12 = R12[:2].copy()
new_graph = FusionGraph([Relation(new_R12, t1, t2)])
new_rnds = np.random.RandomState(0)
transformer = DfmfTransform(random_state=new_rnds).transform(
t1, new_graph, fuser)
new_G1 = transformer.factor(t1)
G1 = fuser.factor(t1)
G2 = fuser.factor(t2)
S12 = fuser.backbone(relation)
new_R12_hat = np.dot(new_G1, np.dot(S12, G2.T))
R12_hat = np.dot(G1, np.dot(S12, G2.T))
diff_G1 = new_G1 - G1[:2]
diff_hat = new_R12_hat - R12_hat[:2]
self.assertLess(np.sum(diff_G1**2) / diff_G1.size, 1e-5)
self.assertLess(np.sum(diff_hat**2) / diff_hat.size, 1e-5)
def test_removal_of_loops(self):
fusion_graph = FusionGraph()
fusion_graph.add_relation(self.relations2[-1])
self.assertEqual(fusion_graph.n_relations, 1)
self.assertEqual(fusion_graph.n_object_types, 1)
fusion_graph.remove_relation(self.relations2[-1])
self.assertEqual(fusion_graph.n_relations, 0)
self.assertEqual(fusion_graph.n_object_types, 0)
def test_removal_single_relation(self):
fusion_graph = FusionGraph()
fusion_graph.add_relation(self.relations1[0])
self.assertEqual(fusion_graph.n_relations, 1)
self.assertEqual(fusion_graph.n_object_types, 2)
fusion_graph.remove_relation(self.relations1[0])
self.assertEqual(fusion_graph.n_relations, 0)
self.assertEqual(fusion_graph.n_object_types, 0)
def test_removal_of_loops(self):
fusion_graph = FusionGraph()
fusion_graph.add_relation(self.relations2[-1])
self.assertEqual(fusion_graph.n_relations, 1)
self.assertEqual(fusion_graph.n_object_types, 1)
fusion_graph.remove_relation(self.relations2[-1])
self.assertEqual(fusion_graph.n_relations, 0)
self.assertEqual(fusion_graph.n_object_types, 0)
def test_removal_single_relation(self):
fusion_graph = FusionGraph()
fusion_graph.add_relation(self.relations1[0])
self.assertEqual(fusion_graph.n_relations, 1)
self.assertEqual(fusion_graph.n_object_types, 2)
fusion_graph.remove_relation(self.relations1[0])
self.assertEqual(fusion_graph.n_relations, 0)
self.assertEqual(fusion_graph.n_object_types, 0)
def test_dfmc(self):
rnds = np.random.RandomState(0)
R12 = rnds.rand(50, 30)
t1 = ObjectType('type1', 50)
t2 = ObjectType('type2', 30)
relation = Relation(R12, t1, t2)
fusion_graph = FusionGraph()
fusion_graph.add_relation(relation)
fuser = Dfmc(init_type='random', random_state=rnds).fuse(fusion_graph)
self.assertEqual(fuser.backbone(relation).shape, (50, 30))
self.assertEqual(fuser.factor(t1).shape, (50, 50))
self.assertEqual(fuser.factor(t2).shape, (30, 30))
np.testing.assert_almost_equal(fuser.complete(relation), relation.data)
def test_dfmc(self):
rnds = np.random.RandomState(0)
R12 = rnds.rand(50, 30)
t1 = ObjectType('type1', 50)
t2 = ObjectType('type2', 30)
relation = Relation(R12, t1, t2)
fusion_graph = FusionGraph()
fusion_graph.add_relation(relation)
fuser = Dfmc(init_type='random', random_state=rnds).fuse(fusion_graph)
self.assertEqual(fuser.backbone(relation).shape, (50, 30))
self.assertEqual(fuser.factor(t1).shape, (50, 50))
self.assertEqual(fuser.factor(t2).shape, (30, 30))
np.testing.assert_almost_equal(fuser.complete(relation), relation.data)
def test_preprocessors(self):
rnds = np.random.RandomState(0)
R12 = rnds.rand(50, 30)
t1 = ObjectType('type1', 50)
t2 = ObjectType('type2', 30)
def preprocessor(data):
return np.ones_like(data)
relation = Relation(R12, t1, t2, preprocessor=preprocessor)
fusion_graph = FusionGraph()
fusion_graph.add_relation(relation)
fuser = Dfmf(init_type='random', random_state=rnds).fuse(fusion_graph)
self.assertEqual(fuser.backbone(relation).shape, (50, 30))
self.assertEqual(fuser.factor(t1).shape, (50, 50))
self.assertEqual(fuser.factor(t2).shape, (30, 30))
trnf = np.ones_like(relation.data)
np.testing.assert_almost_equal(fuser.complete(relation), trnf)
def test_get_names_by_object_type(self):
rnds = np.random.RandomState(0)
X = rnds.rand(10, 10)
t1_names = list('ABCDEFGHIJ')
t2_names = list('KLMNOPQRST')
rel = Relation(X, name='Test',
row_type=self.t1, row_names=t1_names,
col_type=self.t2, col_names=t2_names)
rel2 = Relation(X, name='Test2',
row_type=self.t2, row_names=t2_names,
col_type=self.t3)
fusion_graph = FusionGraph()
fusion_graph.add_relation(rel)
fusion_graph.add_relation(rel2)
self.assertEqual(fusion_graph.get_names(self.t1), t1_names)
self.assertEqual(fusion_graph.get_names(self.t2), t2_names)
t3_names = fusion_graph.get_names(self.t3)
self.assertEqual(len(t3_names), 10)
def test_preprocessors(self):
rnds = np.random.RandomState(0)
R12 = rnds.rand(50, 30)
t1 = ObjectType('type1', 50)
t2 = ObjectType('type2', 30)
def preprocessor(data):
return np.ones_like(data)
relation = Relation(R12, t1, t2, preprocessor=preprocessor)
fusion_graph = FusionGraph()
fusion_graph.add_relation(relation)
fuser = Dfmf(init_type='random', random_state=rnds).fuse(fusion_graph)
self.assertEqual(fuser.backbone(relation).shape, (50, 30))
self.assertEqual(fuser.factor(t1).shape, (50, 50))
self.assertEqual(fuser.factor(t2).shape, (30, 30))
trnf = np.ones_like(relation.data)
np.testing.assert_almost_equal(fuser.complete(relation), trnf)
def test_postprocessors(self):
rnds = np.random.RandomState(0)
R12 = rnds.rand(50, 30)
R12 = np.ma.masked_greater(R12, 0.7)
t1 = ObjectType('type1', 50)
t2 = ObjectType('type2', 30)
def postprocessor(data):
return data - 10
relation = Relation(R12, t1, t2, name='R', postprocessor=postprocessor)
fusion_graph = FusionGraph()
fusion_graph.add_relation(relation)
fuser = Dfmc(init_type='random', random_state=rnds).fuse(fusion_graph)
self.assertEqual(fuser.backbone(relation).shape, (50, 30))
self.assertEqual(fuser.factor(t1).shape, (50, 50))
self.assertEqual(fuser.factor(t2).shape, (30, 30))
trnf = relation.data - 10
np.testing.assert_almost_equal(fuser.complete(relation), trnf)
np.testing.assert_equal(fusion_graph.get_relation('R').data, R12)
def test_postprocessors(self):
rnds = np.random.RandomState(0)
R12 = rnds.rand(50, 30)
R12 = np.ma.masked_greater(R12, 0.7)
t1 = ObjectType('type1', 50)
t2 = ObjectType('type2', 30)
def postprocessor(data):
return data - 10
relation = Relation(R12, t1, t2, name='R', postprocessor=postprocessor)
fusion_graph = FusionGraph()
fusion_graph.add_relation(relation)
fuser = Dfmc(init_type='random', random_state=rnds).fuse(fusion_graph)
self.assertEqual(fuser.backbone(relation).shape, (50, 30))
self.assertEqual(fuser.factor(t1).shape, (50, 50))
self.assertEqual(fuser.factor(t2).shape, (30, 30))
trnf = relation.data - 10
np.testing.assert_almost_equal(fuser.complete(relation), trnf)
np.testing.assert_equal(fusion_graph.get_relation('R').data, R12)
def test_get_object_type_metadata(self):
rnds = np.random.RandomState(0)
X = rnds.rand(10, 10)
a, b, c = list('ABCDEFGHIJ'), list('0123456789'), list('KLMNOPQRST')
t1_metadata = [{'a': x} for x in a]
t2_metadata = [{'b': x} for x in b]
t2_metadata2 = [{'d': x} for x in b]
rel = Relation(X,
name='Test',
row_type=self.t1,
row_metadata=t1_metadata,
col_type=self.t2,
col_metadata=t2_metadata)
rel2 = Relation(X,
name='Test2',
row_type=self.t2,
row_metadata=t2_metadata2,
col_type=self.t3)
fusion_graph = FusionGraph()
fusion_graph.add_relation(rel)
fusion_graph.add_relation(rel2)
def merge(d1, d2):
d = {}
d.update(d1)
d.update(d2)
return d
self.assertEqual(fusion_graph.get_metadata(self.t1), t1_metadata)
self.assertEqual(fusion_graph.get_metadata(self.t2),
list(map(merge, t2_metadata, t2_metadata2)))
t3_metadata = fusion_graph.get_metadata(self.t3)
self.assertEqual(len(t3_metadata), 10)
for md in t3_metadata:
self.assertFalse(md)