def test_special_lca(self):
# Creating graph with networkx library..
G = nx.DiGraph()
# Adding random nodes..
G.add_nodes_from([
'a', 'b', 'b', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm',
'n', 'o', 'p'
])
# Adding random edges..
G.add_edges_from([
('a', 'b'),
('a', 'c'),
('b', 'd'),
('b', 'e'),
('c', 'f'),
('c', 'g'),
('d', 'h'),
('d', 'j'),
('e', 'k'),
('e', 'l'),
('f', 'm'),
('g', 'o'),
('h', 'i'),
('m', 'n'),
('o', 'p'),
])
# Special cases (if one of the nodes is root, the LCA is the root)
self.assertTrue(nx.is_directed_acyclic_graph)
self.assertEqual(lowest_common_ancestor_DAG(G, 'a', 'b'), 'a')
# LCA of nodes x and x is x
self.assertEqual(lowest_common_ancestor_DAG(G, 'a', 'a'), 'a')
self.assertEqual(lowest_common_ancestor_DAG(G, 'd', 'd'), 'd')
def test_node_exists(self):
# Creating graph with networkx library..
G = nx.DiGraph()
# Adding random nodes..
G.add_nodes_from([
'a', 'b', 'b', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm',
'n', 'o', 'p'
])
# Adding random edges..
G.add_edges_from([
('a', 'b'),
('a', 'c'),
('b', 'd'),
('b', 'e'),
('c', 'f'),
('c', 'g'),
('d', 'h'),
('d', 'j'),
('e', 'k'),
('e', 'l'),
('f', 'm'),
('g', 'o'),
('h', 'i'),
('m', 'n'),
('o', 'p'),
])
self.assertTrue(nx.is_directed_acyclic_graph)
self.assertEqual(lowest_common_ancestor_DAG(G, 1, 2), None)
self.assertEqual(lowest_common_ancestor_DAG(G, 'x', 'z'), None)
self.assertEqual(lowest_common_ancestor_DAG(G, 'w', 'y'), None)
def test_wrong_parameters(self):
G = "Hello World"
self.assertEqual(lowest_common_ancestor_DAG(G, 'x', 'x'), None)
G = 7
self.assertEqual(lowest_common_ancestor_DAG(G, 'x', 'x'), None)
G = [1, 2, 3]
self.assertEqual(lowest_common_ancestor_DAG(G, 'x', 'x'), None)
G = 5.4
self.assertEqual(lowest_common_ancestor_DAG(G, 'x', 'x'), None)
def test_directed_acyclic(self): # _a_
# Creating graph with networkx library.. # / \
G = nx.DiGraph() # b c
# Adding random nodes # | |
G.add_nodes_from(['a', 'b', 'c', 'd', 'e', 'f']) # d e
# Adding random edges # \ /
G.add_edges_from([('a', 'b'), ('a', 'c'), ('b', 'd'), ('c', 'e'),
('d', 'f'), ('e', 'f')]) # f
# Testing acyclic
self.assertTrue(nx.is_directed_acyclic_graph)
self.assertEqual(lowest_common_ancestor_DAG(G, 'f', 'b'), 'b')
self.assertEqual(lowest_common_ancestor_DAG(G, 'd', 'e'), 'a')
self.assertEqual(lowest_common_ancestor_DAG(G, 'a', 'a'), 'a')
self.assertEqual(lowest_common_ancestor_DAG(G, 'd', 'c'), 'a')
self.assertEqual(lowest_common_ancestor_DAG(G, 'f', 'f'), 'f')
def test_dag_lca(self):
# Creating graph with networkx library..
G = nx.DiGraph()
# Adding random nodes..
G.add_nodes_from([
'a', 'b', 'b', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm',
'n', 'o', 'p'
])
# Adding random edges..
G.add_edges_from([
('a', 'b'),
('a', 'c'),
('b', 'd'),
('b', 'e'),
('c', 'f'),
('c', 'g'),
('d', 'h'),
('d', 'j'),
('e', 'k'),
('e', 'l'),
('f', 'm'),
('g', 'o'),
('h', 'i'),
('m', 'n'),
('o', 'p'),
])
# General cases (Random nodes for testing) # Graphic of the is_directed_acyclic_graph
self.assertTrue(nx.is_directed_acyclic_graph)
self.assertEqual(lowest_common_ancestor_DAG(G, 'p', 'i'), 'a') # _a_
self.assertEqual(lowest_common_ancestor_DAG(G, 'n', 'o'),
'c') # / \__
self.assertEqual(lowest_common_ancestor_DAG(G, 'b', 'c'),
'a') # b c__
self.assertEqual(lowest_common_ancestor_DAG(G, 'h', 'c'),
'a') # / \ / \
self.assertEqual(lowest_common_ancestor_DAG(G, 'i', 'l'),
'b') # d e f g
self.assertEqual(lowest_common_ancestor_DAG(G, 'i', 'j'),
'd') # / \ /\ / \
self.assertEqual(lowest_common_ancestor_DAG(G, 'i', 'd'),
'd') # h j k l m o
self.assertEqual(lowest_common_ancestor_DAG(G, 'p', 'c'),
'c') # / / \
def test_singleton_graph(self):
# Creating singleton graph with networkx library..
G = nx.DiGraph()
G.add_node('x')
self.assertEqual(lowest_common_ancestor_DAG(G, 'x', 'x'), None)
def test_empty_graph(self):
# Creating empty graph with networkx library..
G = nx.DiGraph()
self.assertEqual(lowest_common_ancestor_DAG(G, 'x', 'x'), None)