class TestDominatingSet2(unittest.TestCase):
def setUp(self):
self.N = 7
self.G = Graph(self.N)
self.nodes = range(self.N)
self.edges = [
Edge(0, 1),
Edge(1, 3),
Edge(1, 2),
Edge(1, 4),
Edge(2, 5),
Edge(2, 6)
]
for node in self.nodes:
self.G.add_node(node)
for edge in self.edges:
self.G.add_edge(edge)
#self.G.show()
def test_borie_dset(self):
algorithm = BorieDominatingSet(self.G)
algorithm.run()
expected1 = set([1, 2])
self.assertEqual(algorithm.cardinality, len(expected1))
self.assertEqual(algorithm.dominating_set, expected1)
# Testing dset.
neighbors = set(algorithm.dominating_set)
for node in algorithm.dominating_set:
neighbors.update(self.G.iteradjacent(node))
self.assertEqual(len(neighbors), self.G.v())
def test_tree_dset1(self):
algorithm = TreeDominatingSet1(self.G)
algorithm.run()
expected1 = set([1, 2])
self.assertEqual(algorithm.cardinality, len(expected1))
self.assertEqual(algorithm.dominating_set, expected1)
# Testing dset.
neighbors = set(algorithm.dominating_set)
for node in algorithm.dominating_set:
neighbors.update(self.G.iteradjacent(node))
self.assertEqual(len(neighbors), self.G.v())
def test_tree_dset2(self):
algorithm = TreeDominatingSet2(self.G)
algorithm.run()
expected1 = set([1, 2])
self.assertEqual(algorithm.cardinality, len(expected1))
self.assertEqual(algorithm.dominating_set, expected1)
# Testing dset.
neighbors = set(algorithm.dominating_set)
for node in algorithm.dominating_set:
neighbors.update(self.G.iteradjacent(node))
self.assertEqual(len(neighbors), self.G.v())
def tearDown(self):
pass
class TestDominatingSet(unittest.TestCase):
def setUp(self):
self.N = 6
self.G = Graph(self.N)
self.nodes = range(self.N)
self.edges = [
Edge(0, 1),
Edge(0, 3),
Edge(1, 3),
Edge(1, 4),
Edge(1, 2),
Edge(2, 5),
Edge(3, 4),
Edge(4, 5)
]
for node in self.nodes:
self.G.add_node(node)
for edge in self.edges:
self.G.add_edge(edge)
#self.G.show()
def test_dominating_set(self):
algorithm = RandomSequentialDominatingSet(self.G)
algorithm.run()
used = set(algorithm.dominating_set)
for node in algorithm.dominating_set:
used.update(self.G.iteradjacent(node))
self.assertEqual(len(used), self.N)
self.assertEqual(algorithm.cardinality, len(algorithm.dominating_set))
self.assertTrue(algorithm.cardinality in set([2, 3])) # best = 2
#print ( algorithm.dominating_set )
def test_dominating_set_source(self):
algorithm = RandomSequentialDominatingSet(self.G)
algorithm.run(1)
used = set(algorithm.dominating_set)
for node in algorithm.dominating_set:
used.update(self.G.iteradjacent(node))
self.assertEqual(len(used), self.N)
self.assertEqual(algorithm.cardinality, len(algorithm.dominating_set))
self.assertEqual(algorithm.cardinality, 2) # best = 2
#print ( algorithm.dominating_set )
def test_exceptions(self):
self.assertRaises(ValueError, RandomSequentialDominatingSet,
Graph(5, directed=True))
def tearDown(self):
pass
class TestGraphLadder(unittest.TestCase):
def setUp(self):
self.N = 8 # number of nodes
self.G = Graph(self.N)
self.edges = [
Edge(0, 1, 2),
Edge(0, 2, 1),
Edge(2, 3, 5),
Edge(1, 3, 3),
Edge(2, 4, 4),
Edge(3, 5, 6),
Edge(4, 6, 7),
Edge(4, 5, 8),
Edge(5, 7, 9),
Edge(6, 7, 10)
]
for edge in self.edges:
self.G.add_edge(edge)
def test_basic(self):
self.assertFalse(self.G.is_directed())
self.assertEqual(self.G.v(), self.N)
self.assertEqual(self.G.e(), len(self.edges))
def test_edges(self):
for edge in self.edges:
self.assertTrue(self.G.has_edge(edge))
self.assertEqual(self.G.weight(edge), edge.weight)
self.assertFalse(self.G.has_edge(Edge(0, 3)))
self.assertEqual(self.G.weight(Edge(0, 3)), 0) # no edge
def test_del(self):
self.assertEqual(self.G.e(), 10)
self.G.del_node(7)
self.assertEqual(self.G.e(), 8)
self.G.del_node(2)
self.assertEqual(self.G.e(), 5)
def test_adjacent(self):
for node in self.G.iteradjacent(0):
self.assertTrue(node in [1, 2])
for node in self.G.iteradjacent(2):
self.assertTrue(node in [0, 3, 4])
def tearDown(self):
pass
class TestGraphLadder(unittest.TestCase):
def setUp(self):
self.N = 8 # number of nodes
self.G = Graph(self.N)
self.edges = [
Edge(0, 1, 2), Edge(0, 2, 1), Edge(2, 3, 5),
Edge(1, 3, 3), Edge(2, 4, 4), Edge(3, 5, 6), Edge(4, 6, 7),
Edge(4, 5, 8), Edge(5, 7, 9), Edge(6, 7, 10)]
for edge in self.edges:
self.G.add_edge(edge)
def test_basic(self):
self.assertFalse(self.G.is_directed())
self.assertEqual(self.G.v(), self.N)
self.assertEqual(self.G.e(), len(self.edges))
def test_edges(self):
for edge in self.edges:
self.assertTrue(self.G.has_edge(edge))
self.assertEqual(self.G.weight(edge), edge.weight)
self.assertFalse(self.G.has_edge(Edge(0, 3)))
self.assertEqual(self.G.weight(Edge(0, 3)), 0) # no edge
def test_del(self):
self.assertEqual(self.G.e(), 10)
self.G.del_node(7)
self.assertEqual(self.G.e(), 8)
self.G.del_node(2)
self.assertEqual(self.G.e(), 5)
def test_adjacent(self):
for node in self.G.iteradjacent(0):
self.assertTrue(node in [1, 2])
for node in self.G.iteradjacent(2):
self.assertTrue(node in [0, 3, 4])
def tearDown(self): pass
def make_random_ktree(n, k): # using list
"""Make a random k-tree with n vertices."""
if k >= n:
raise ValueError("bad k") # run time error possible
graph = Graph(n)
if n < 1:
raise ValueError("bad n")
elif n == 1:
graph.add_node(0)
else:
for node in xrange(n):
graph.add_node(node)
# Make {n-k-1, ..., n-1} into (k+1)-clique in graph.
for source in xrange(n - k - 1, n):
for target in xrange(n - k - 1, n):
if source < target:
graph.add_edge(Edge(source, target))
node = n - k - 2
while node >= 0:
# Wybor source z przedzialu od node+1 do n-k-1.
# To jest jakby wybor duzej (k+1)-kliki,
source = random.choice(xrange(node + 1, n - k))
# Teraz zbieram wierzcholki tej kliki, ale one maja byc
# wieksze od source, wieksze numery!
neighbors = list(target for target in graph.iteradjacent(source)
if source < target)
neighbors.append(source) # closed neighborhood
# Z duzej (k+1)-kliki wybieram mala k-klike.
idx = random.randrange(0, len(neighbors))
swap(neighbors, idx, -1)
neighbors.pop()
# Connect node to all nodes from neighbors.
for target in neighbors:
graph.add_edge(Edge(node, target))
node -= 1
return graph
def make_random_ktree(n, k): # using list
"""Make a random k-tree with n vertices."""
if k >= n:
raise ValueError("bad k") # run time error possible
graph = Graph(n)
if n < 1:
raise ValueError("bad n")
elif n == 1:
graph.add_node(0)
else:
for node in xrange(n):
graph.add_node(node)
# Make {n-k-1, ..., n-1} into (k+1)-clique in graph.
for source in xrange(n-k-1, n):
for target in xrange(n-k-1, n):
if source < target:
graph.add_edge(Edge(source, target))
node = n-k-2
while node >= 0:
# Wybor source z przedzialu od node+1 do n-k-1.
# To jest jakby wybor duzej (k+1)-kliki,
source = random.choice(xrange(node+1, n-k))
# Teraz zbieram wierzcholki tej kliki, ale one maja byc
# wieksze od source, wieksze numery!
neighbors = list(target for target in graph.iteradjacent(source)
if source < target)
neighbors.append(source) # closed neighborhood
# Z duzej (k+1)-kliki wybieram mala k-klike.
idx = random.randrange(0, len(neighbors))
swap(neighbors, idx, -1)
neighbors.pop()
# Connect node to all nodes from neighbors.
for target in neighbors:
graph.add_edge(Edge(node, target))
node -= 1
return graph
