def test_real_trees(self):
def distance_builder(**kwargs):
distance = StartExitDistance()
distance.supported[TrafficEvent] = True
return distance
tree_one = real_tree()
tree_two = real_tree(path="data/c01-007-102/2/1129-2-process.csv")
prototype_names = ["1", "2"]
prototype_caches = []
for index, tree in enumerate([tree_one, tree_two]):
prototype_caches.append(PrototypeSignatureCache.from_signature_caches(
[tree.to_index(signature=ParentChildByNameTopologySignature(),
supported={
ProcessStartEvent: True,
ProcessExitEvent: True,
TrafficEvent: True
},
statistics_cls=SetStatistics)],
prototype=prototype_names[index], threshold=0))
decorator = AnomalyDecorator()
algorithm = IncrementalDistanceAlgorithm(
signature=ParentChildByNameTopologySignature(),
distance=distance_builder,
cache_statistics=SetStatistics
)
prototype_cache = prototype_caches[0]
for cache in prototype_caches[1:]:
prototype_cache += cache
algorithm.cluster_representatives(
signature_prototypes=[prototype_cache],
prototypes=prototype_names
)
decorator.wrap_algorithm(algorithm)
for tree in [tree_one, tree_two]:
algorithm.start_tree()
for event in tree.event_iter(supported=algorithm.supported):
try:
algorithm.add_event(event)
except EventNotSupportedException:
pass
algorithm.finish_tree()
# First tree vs. first is False for start
self.assertFalse(decorator.data()[0][0][0][0])
# ... and end
self.assertFalse(decorator.data()[0][0][0][-1])
# First tree vs. second is False for start
self.assertFalse(decorator.data()[0][0][1][0])
# and True for end
self.assertTrue(decorator.data()[0][0][1][-1])
# Second tree vs. first is False for start
self.assertFalse(decorator.data()[1][0][0][0])
# ... and True for end
self.assertTrue(decorator.data()[1][0][0][-1])
# Second tree vs. second is False for start
self.assertFalse(decorator.data()[1][0][1][0])
# ... and False for end
self.assertFalse(decorator.data()[1][0][1][-1])
def test_initialisation_of_cluster_representatitives(self):
def distance_builder(**kwargs):
distance = StartExitDistance(weight=.5, **kwargs)
distance.supported[TrafficEvent] = True
return distance
tree_one = real_tree()
tree_two = real_tree(path="data/c01-007-102/2/1129-2-process.csv")
tree_three = real_tree(path="data/c01-007-102/2/1136-3-process.csv")
distance = StartExitDistance(weight=.5)
distance.supported[TrafficEvent] = True
signature = ParentChildByNameTopologySignature()
tree_profiles = [
tree_one.to_index(signature=signature,
supported=distance.supported,
statistics_cls=SetStatistics),
tree_two.to_index(signature=signature,
supported=distance.supported,
statistics_cls=SetStatistics),
tree_three.to_index(signature=signature,
supported=distance.supported,
statistics_cls=SetStatistics)
]
algorithm = IncrementalDistanceAlgorithm(
signature=ParentChildByNameTopologySignature(),
distance=distance_builder,
cache_statistics=SetStatistics)
cluster_distance = ClusterDistance(distance=distance)
prototype_names = ["test"]
prototype_signatures = []
for prototype in prototype_names:
prototype_signatures.append(
cluster_distance.mean(tree_profiles, prototype=prototype))
algorithm.cluster_representatives(
signature_prototypes=prototype_signatures,
prototypes=prototype_names)
algorithm.start_tree()
