def test_recognise_edges(self):
graph = DAG()
graph.add_node('B')
graph.add_node('C')
graph.add_edge('B', 'C')
self.assertRaises(ValueError, graph.add_edge('B', 'C'))
def test_add_edges(self):
graph = DAG()
graph.add_node('B')
graph.add_node('C')
graph.add_edge('B', 'C')
self.assertEqual(graph.graph, {'B': ['C'], 'C': []})
def test_add_nodes(self):
graph = DAG()
graph.add_node('A')
self.assertEqual(graph.graph, {'A': []})
graph.add_node('B')
graph.add_node('C')
self.assertEqual(graph.graph, {'A': [], 'B': [], 'C': []})
def BFS(self, start):
"""
Creates a BFS DAG and returns list of triples (in, out, weight)
Positional Arguments:
start - key in vertex
Return:
[] if start does not exist
"""
leaves, dirtyNodes = ({}, {})
upEdges, queue = ([], [])
dag = DAG()
try:
queue.append(start)
dirtyNodes[start] = 1
except KeyError:
return []
for node in queue:
dag.add_vertex(node)
weight = dirtyNodes[node] + 1
notDirtyNeighbors = []
for edge in self.vertices[node]:
if edge.nextVertex not in dirtyNodes:
notDirtyNeighbors.append(edge.nextVertex)
elif dirtyNodes[edge.nextVertex] == weight:
dag.add_edge(node, edge.nextVertex)
upEdges.append((edge.nextVertex, node))
queue.extend(notDirtyNeighbors)
for neighbor in notDirtyNeighbors:
dirtyNodes[neighbor] = weight
dag.add_edge(node, neighbor)
upEdges.append((neighbor, node))
return dag
def BFS(self, start):
"""
Creates a BFS DAG and returns list of triples (in, out, weight)
Positional Arguments:
start - key in vertex
Return:
[] if start does not exist
"""
leaves, dirtyNodes = ({}, {})
upEdges, queue = ([], [])
dag = DAG()
try:
queue.append(start)
dirtyNodes[start] = 1
except KeyError:
return []
for node in queue:
dag.add_vertex(node)
weight = dirtyNodes[node] + 1
notDirtyNeighbors = []
for edge in self.vertices[node]:
if edge.nextVertex not in dirtyNodes:
notDirtyNeighbors.append(edge.nextVertex)
elif dirtyNodes[edge.nextVertex] == weight:
dag.add_edge(node, edge.nextVertex)
upEdges.append((edge.nextVertex, node))
queue.extend(notDirtyNeighbors)
for neighbor in notDirtyNeighbors:
dirtyNodes[neighbor] = weight
dag.add_edge(node, neighbor)
upEdges.append((neighbor, node))
return dag
def test_complex_lca(self):
graph = DAG()
graph.add_node('A')
graph.add_node('B')
graph.add_node('C')
graph.add_node('D')
graph.add_node('E')
graph.add_node('F')
graph.add_node('G')
graph.add_node('H')
graph.add_node('I')
graph.add_edge('A', 'B')
graph.add_edge('B', 'C')
graph.add_edge('B', 'D')
graph.add_edge('C', 'F')
graph.add_edge('C', 'E')
graph.add_edge('D', 'F')
graph.add_edge('D', 'H')
graph.add_edge('B', 'G')
graph.add_edge('H', 'I')
graph.add_edge('C', 'I')
self.assertEqual(graph.dfs_wrapper(graph.graph, 'A', 'A'), 'A')
self.assertEqual(graph.dfs_wrapper(graph.graph, 'F', 'E'), 'C')
self.assertEqual(graph.dfs_wrapper(graph.graph, 'I', 'G'), 'B')
self.assertEqual(graph.dfs_wrapper(graph.graph, 'F', 'I'), 'C')
def test_basic_lca(self):
graph = DAG()
graph.add_node('A')
print(graph.dfs_wrapper(graph.graph, 'A', 'A'))
def test_complex(self):
graph = DAG()
graph.add_node('A')
graph.add_node('B')
graph.add_node('C')
graph.add_node('D')
graph.add_node('E')
graph.add_node('F')
graph.add_node('G')
graph.add_node('H')
graph.add_node('I')
graph.add_edge('A', 'B')
graph.add_edge('B', 'C')
graph.add_edge('B', 'D')
graph.add_edge('C', 'F')
graph.add_edge('C', 'E')
graph.add_edge('D', 'F')
graph.add_edge('D', 'H')
graph.add_edge('B', 'G')
graph.add_edge('H', 'I')
graph.add_edge('C', 'I')
self.assertEqual(
graph.graph, {
'A': ['B'],
'B': ['C', 'D', 'G'],
'C': ['F', 'E', 'I'],
'D': ['F', 'H'],
'E': [],
'F': [],
'G': [],
'H': ['I'],
'I': []
})
def test_recognise_nodes(self):
graph = DAG()
graph.add_node('A')
self.assertFalse(graph.add_node('A'))