def load_slashdot(request):
with open('slashsave') as slash_save:
slashdot_graph = Graph('slashdot')
slashdot_graph.load_save(slash_save.read())
global current
current = slashdot_graph
dump = slashdot_graph.dump_graph(degree_threshold=250)
with open('dump', 'w+') as dumpfile:
dumpfile.write(json.dumps(dump))
return render(request, "graph_sna/index.html", context={})
def setUp(self):
"""Call before every test case."""
self.graph_a = Graph(name="myGraph")
# Simple graph with three nodes
self.node1 = Node(label='node1')
self.node2 = Node(label='node2')
self.node3 = Node(label='node3')
self.graph_a.add_node(self.node1)
self.graph_a.add_node(self.node2, neighbors={self.node1})
self.graph_a.add_node(self.node3, neighbors={self.node1})
def load_enron(request):
with open('enronsave') as enron_save:
enron_graph = Graph('enron')
enron_graph.load_save(enron_save.read())
global current
current = enron_graph
dump = enron_graph.dump_graph(weight_threshold=0, degree_threshold=0)
with open('dump', 'w+') as dumpfile:
dumpfile.write(json.dumps(dump))
return render(request, "graph_sna/index.html", context={})
def initialise_sample_graph(sample_graph):
graph = Graph(name='SampleGraph')
for each_node in sample_graph['nodes'].keys():
graph.add_node(Node(label=each_node))
for each_edge in sample_graph['weights'].keys():
node = graph.get_node_from_label(each_edge[0])
neighbor = graph.get_node_from_label(each_edge[1])
graph.add_edge(node, neighbor, sample_graph['weights'][each_edge])
return graph
def load_reddit(request):
global current
with open('redditsave') as reddit_save:
reddit_graph = Graph('reddit')
reddit_graph.load_save(reddit_save.read(),weight_threshold=2,degree_threshold=3)
global current
current = reddit_graph
print(reddit_graph.get_threshold(10))
dump = reddit_graph.dump_graph(weight_threshold=2, degree_threshold=15)
with open('dump', 'w+') as dumpfile:
dumpfile.write(json.dumps(dump))
return render(request, "graph_sna/index.html", context={})
class BasicGraphTest(unittest.TestCase):
def setUp(self):
"""Call before every test case."""
self.graph_a = Graph(name="myGraph")
# Simple graph with three nodes
self.node1 = Node(label='node1')
self.node2 = Node(label='node2')
self.node3 = Node(label='node3')
self.graph_a.add_node(self.node1)
self.graph_a.add_node(self.node2, neighbors={self.node1})
self.graph_a.add_node(self.node3, neighbors={self.node1})
def tearDown(self):
"""Call after every test case."""
def test_init(self):
"""
Tests that everything done in the setUp method works correctly.
This test includes
- Confirming that the internal graph of form {<node1>:{<neighbor1>,<neighbor2>},...} is updated
- Confirming that the internal weights of form {(<node1>,<node2>):weight),...} is updated
- Confirming node.neighbors is updated.
- Confirming that node.neighbors and node.weights always reflect each other.
"""
self.assertEqual(len(self.graph_a._graph), 3,
"Node seems to be missing from _graph")
self.assertEqual(len(self.graph_a._weights), 2,
"Weight seems to be missing from _weights ")
self.assertEqual(
self.node2.get_neighbors(), {self.node1},
"Neighbor doesn't seem to be added at the node level")
self.assertEqual(
self.node3.get_neighbors(), {self.node1},
"Neighbor doesn't seem to be added at the node level")
for node in self.graph_a._graph.keys():
neighbors = node.get_neighbors()
if neighbors:
for neighbor in neighbors:
self.assertIn(
(node, neighbor), self.graph_a._weights,
"Weights don't seem to have updated correctly")
def test_has_node(self):
"""
Test the has_node() method.
The expectation is that passing any node that has been added to the graph returns True.
:return:
"""
# hasNode successful cases
self.assertTrue(self.graph_a.has_node(self.node1),
"has_node() returning False when it should not")
self.assertTrue(self.graph_a.has_node(self.node2),
"has_node() returning False when it should not")
self.assertTrue(self.graph_a.has_node(self.node3),
"has_node() returning False when it should not")
# hasNode failure cases
fail_node1 = Node()
# node that has been added as a neighbor outside of the graph
fail_neighbor = Node()
fail_node2 = Node(neighbors={fail_neighbor})
self.graph_a.add_node(fail_node2)
# make sure node that has not been added returns false
self.assertFalse(
self.graph_a.has_node(fail_node1),
"has_node() returns True for a node that has not been added")
self.assertTrue(self.graph_a.has_node(fail_node2),
"has_node() returning False when it should not")
error_msg = "Returns True for node that has been added as a neighbor outside of the graph"
self.assertFalse(self.graph_a.has_node(fail_neighbor), error_msg)
def test_has_edge(self):
"""
Tests the has_edge method.
The expectation is that passing any edge (directed) that has been added to the graph returns True.
- Tests that the function returns True when expected
- Tests that the function returns False when expected
- Tests that the function raises an exception when either of the nodes are not in the graph
:return:
"""
# hasEdge successful cases
self.assertTrue(self.graph_a.has_edge(self.node2, self.node1),
"has_edge() returning False when it should not")
self.assertTrue(self.graph_a.has_edge(self.node3, self.node1),
"has_edge() returning False when it should not")
# hasEdge fail cases
self.assertFalse(self.graph_a.has_edge(self.node1, self.node2),
"has_edge() returning True when it should not")
self.assertFalse(self.graph_a.has_edge(self.node1, self.node3),
"has_edge() returning True when it should not")
self.assertFalse(self.graph_a.has_edge(self.node3, self.node3),
"has_edge() returning True for not-added self-edge")
self.assertRaises(AssertionError, self.graph_a.has_edge, self.node1,
Node())
self.assertRaises(AssertionError, self.graph_a.has_edge, Node(),
self.node1)
self.assertRaises(AssertionError, self.graph_a.has_edge, self.node2,
Node({self.node2}))
fail_node1 = Node()
fail_neighbor = Node({fail_node1})
self.assertRaises(AssertionError, self.graph_a.has_edge, fail_node1,
fail_neighbor)
self.assertRaises(AssertionError, self.graph_a.has_edge, fail_neighbor,
fail_node1)
def test_add_node(self):
"""
Tests the add_node() method
:return:
"""
# true cases
self.assertIn(self.node1, self.graph_a._graph,
"has_node failed to add nodes")
self.assertIn(self.node2, self.graph_a._graph,
"has_node failed to add nodes")
self.assertIn(self.node3, self.graph_a._graph,
"has_node failed to add nodes")
# fail cases
node4 = Node()
node5 = Node()
# incorrectly passed node
#self.assertRaises(AssertionError,self.graph_a.add_node,(node4,node5))
self.assertRaises(AssertionError, self.graph_a.add_node, None)
# incorrectly passed neighbors
self.assertRaises(AssertionError, self.graph_a.add_node, node4, node5)
self.assertRaises(AssertionError, self.graph_a.add_node, node5, node5)
def test_add_edge(self):
"""
Tests adding edges between two existing nodes using the add_edge() method
:return:
"""
# generic/correct use
self.graph_a.add_edge(self.node2, self.node3)
self.assertIn(
(self.node2, self.node3),
self.graph_a._weights) # tests that it was added to weights
self.assertIn(self.node3, self.graph_a._graph[
self.node2]) # tests that it was added to _graph
# adding multiple edges
neighbor_list = []
for _ in range(400):
temp_node = Node()
neighbor_list.append(temp_node)
self.graph_a.add_node(temp_node)
self.graph_a.add_edge(self.node3, temp_node)
for neighbor in neighbor_list:
self.assertIn((self.node3, neighbor), self.graph_a._weights.keys()
) # tests that it was added to weights
self.assertIn(neighbor, self.graph_a._graph[
self.node3]) # tests that it was added to _graph
# add a -> b and b -> a
for neighbor in neighbor_list:
self.graph_a.add_edge(neighbor, self.node3)
for neighbor in neighbor_list:
self.assertIn((neighbor, self.node3), self.graph_a._weights.keys()
) # tests that it was added to weights
self.assertIn(self.node3, self.graph_a._graph[neighbor]
) # tests that it was added to _graph
def test_delete_node(self):
""" test the delete_node method"""
self.graph_a.add_edge(self.node1, self.node3)
self.assertIn((self.node1, self.node3), self.graph_a._weights)
self.assertIn((self.node3, self.node1), self.graph_a._weights)
self.assertTrue(self.graph_a.has_node(self.node1))
self.graph_a.delete_node(self.node1)
print(self.graph_a.get_all_edges(stringify=True))
self.assertFalse(self.graph_a.has_node(self.node1))
# confirm that the internal methods for clearing out the relationships were successful
self.assertNotIn((self.node1, self.node3), self.graph_a._weights)
self.assertNotIn((self.node3, self.node1), self.graph_a._weights)
self.assertRaises(KeyError, self.graph_a._graph.__getitem__,
self.node1)
# confirm _graph neighbors have been deleted
for node, neighbors in self.graph_a._graph.items():
print(self.node1, "|||", node)
self.assertNotIn(self.node1, neighbors)
self.assertNotIn(self.node1, self.graph_a._graph.keys())
def test_incoming_node_neighbors(self):
self.assertEqual(self.graph_a.get_incoming_neighbors(self.node1),
{self.node2, self.node3})
def test_thresholding(self):
self.graph_a.add_edge(self.node1, self.node3, 4)
self.graph_a.add_edge(self.node1, self.node2, 2)
print(self.graph_a.get_threshold(25))
def test_save_graph(self):
self.graph_a.load_save(self.graph_a.get_save())
def generate_graph(self):
"""
To be used after the data has been saved to an enrondump file by the parser
:return:
"""
graph = Graph('Enron')
emails = json.loads(open('enrondump').read())
for email in emails:
sender_email = email['from']
if graph.has_node_by_label(sender_email):
sender = graph.get_node_from_label(label=sender_email)
else:
sender = Node(label=sender_email)
graph.add_node(sender)
recipients = json.loads(email['To'])
for recipient_email in recipients:
if graph.has_node_by_label(recipient_email):
recipient = graph.get_node_from_label(recipient_email)
else:
recipient = Node(label=recipient_email)
graph.add_node(recipient)
if not graph.has_edge(sender, recipient):
graph.add_edge(sender, recipient, 1)
else:
# Increment the weight by 1
graph.update_edge(sender, recipient,
graph.get_weight(sender, recipient,) + 1)
return graph
class BasicGraphTest(unittest.TestCase):
def setUp(self):
"""Call before every test case."""
self.basic_graph = Graph(name="myGraph")
# Simple graph with three nodes
self.node1 = Node(label='node1')
self.node2 = Node(label='node2')
self.node3 = Node(label='node3')
self.basic_graph.add_node(self.node1)
self.basic_graph.add_node(self.node2, neighbors={self.node1})
self.basic_graph.add_node(self.node3, neighbors={self.node1})
self.graph_algorithms = GraphAlgorithms()
def tearDown(self):
"""Call after every test case."""
def test_node_count(self):
node_count = self.graph_algorithms.node_count(self.basic_graph)
self.assertEqual(node_count, 3)
sample_graph_a = initialise_sample_graph(sample_graphs.graph_a)
self.assertEqual(self.graph_algorithms.node_count(sample_graph_a), 5)
def test_edge_count(self):
edge_count = self.graph_algorithms.edge_count(self.basic_graph)
self.assertEqual(edge_count, 2)
sample_graph_a = initialise_sample_graph(sample_graphs.graph_a)
self.assertEqual(self.graph_algorithms.edge_count(sample_graph_a), 5)
def test_shortest_path(self):
sample_graph_a = initialise_sample_graph(sample_graphs.graph_a)
paths = {}
for source_node in sample_graph_a.get_all_nodes():
shortest_dist, prev = self.graph_algorithms.shortest_path_length(
sample_graph_a, source_node)
source_label = source_node.label
length_list = [None] * 5
for node in shortest_dist.keys():
# print(source_label+'>'+node.label+':'+str(shortest_dist[node]))
length_list.__setitem__(int(node.label), shortest_dist[node])
paths[source_label] = length_list
# print(paths)
# print(sample_graphs.graph_a['minpath'])
self.assertEqual(paths, sample_graphs.graph_a['minpath'])
def test_average_path(self):
self.assertEqual(
self.graph_algorithms.minimum_average_path(self.basic_graph), 1,
"minimum average path failed")
sample_graph_a = initialise_sample_graph(sample_graphs.graph_a)
self.assertEqual(
self.graph_algorithms.minimum_average_path(sample_graph_a),
sample_graphs.graph_a['avgpath'])
def test_diameter(self):
self.assertEqual(self.graph_algorithms.diameter(self.basic_graph), 1,
'diameter algorithm failed for basic graph')
sample_graph_a = initialise_sample_graph(sample_graphs.graph_a)
self.assertEqual(self.graph_algorithms.diameter(sample_graph_a),
sample_graphs.graph_a['diameter'],
'diameter algorithm failed for sample graph a')
def test_mode_path(self):
self.assertEqual(
self.graph_algorithms.mode_path_length(self.basic_graph), (1, 2),
'mode_path_length algorithm failed for basic graph')
sample_graph_a = initialise_sample_graph(sample_graphs.graph_a)
self.assertEqual(
self.graph_algorithms.mode_path_length(sample_graph_a),
sample_graphs.graph_a['mode_path_length'],
'mode_path_length algorithm failed for sample graph a')
def test_median_path(self):
self.assertEqual(
self.graph_algorithms.median_path_length(self.basic_graph), 1,
'median_path_length algorithm failed for basic graph')
sample_graph_a = initialise_sample_graph(sample_graphs.graph_a)
self.assertEqual(
self.graph_algorithms.median_path_length(sample_graph_a),
sample_graphs.graph_a['median_path_length'],
'median_path_length algorithm failed for sample graph a')
def test_average_edges_per_node(self):
self.assertEqual(
self.graph_algorithms.average_edges_per_node(self.basic_graph),
0.67, 'average_edges_per_node algorithm failed for sample graph a')
sample_graph_a = initialise_sample_graph(sample_graphs.graph_a)
self.assertEqual(
self.graph_algorithms.average_edges_per_node(sample_graph_a), 1.0,
'average_edges_per_node algorithm failed for sample graph a')
def test_dfs(self): # todo finish test_dfs
print(
self.graph_algorithms.depth_first_search(self.basic_graph,
self.node1))
def test_discover_components(self): # todo finish test_clustering
sample_graph_b = initialise_sample_graph(sample_graphs.graph_b)
print(self.graph_algorithms.discover_components(sample_graph_b))
def test_edmonds(self):
sample_graph_c = initialise_sample_graph(sample_graphs.graph_c)
source = sample_graph_c.get_node_from_label('0')
sink = sample_graph_c.get_node_from_label('11')
print(self.graph_algorithms.edmonds_karp(sample_graph_c, source, sink))
def test_local_clustering_coefficient(self):
print(
self.graph_algorithms.local_clustering_coefficient(
self.basic_graph, self.node1))
def test_global_clustering_coefficient(self):
print(
self.graph_algorithms.average_clustering_coefficient(
self.basic_graph))
def test_save_graph_agls(self):
test_graph = Graph('test')
test_graph.load_save(self.basic_graph.get_save())
print(self.graph_algorithms.node_count(test_graph))
def test_structural_holes(self):
sample_graph_c = initialise_sample_graph(sample_graphs.graph_c)
print(sample_graph_c.get_save())
print(self.graph_algorithms.structural_holes(sample_graph_c))
def test_save_graph_agls(self):
test_graph = Graph('test')
test_graph.load_save(self.basic_graph.get_save())
print(self.graph_algorithms.node_count(test_graph))