def test_get_edges(self):
graph = Graph()
# Create test Verticies
v1,v2,v3 = Vertex("a"), Vertex("b"), Vertex("c")
# Add verticies
graph.add_vertex(v1)
graph.add_vertex(v2)
graph.add_vertex(v3)
self.assertEqual(graph.num_verticies, 3)
self.assertEqual(graph.num_edges, 0)
# Create edges
edges = [
("a", "b", 10),
("b", "c", 10),
("c", "a", 4)
]
# Iterate through edges
for edge in edges:
fromVert, toVert, weight = edge
graph.add_edge(fromVert, toVert, weight)
self.assertEqual(graph.num_edges, 3)
def test_add_neighbor(self):
v1 = "a"
vertex = Vertex(v1)
vertex.add_neighbor("b", 0)
self.assertTrue(any(vertex.neighbors))
self.assertDictEqual(vertex.neighbors, {"b":0})
def add_edge(self, from_vertex_id, to_vertex_id, weight=None):
if from_vertex_id not in self.vertices:
self.vertices[from_vertex_id] = Vertex(from_vertex_id)
self.no_of_vertices += 1
if to_vertex_id not in self.vertices:
self.vertices[to_vertex_id] = Vertex(to_vertex_id)
self.no_of_vertices += 1
self.vertices[from_vertex_id].add_nbr(to_vertex_id, weight)
if self.is_undirected:
self.vertices[to_vertex_id].add_nbr(from_vertex_id, weight)
def text_get_verticies(self):
graph = Graph()
# Create test Verticies
v1,v2,v3 = Vertex("a"), Vertex("b"), Vertex("c")
# Add verticies
graph.add_vertex(v1)
graph.add_vertex(v2)
graph.add_vertex(v3)
self.assertListEqual(graph.get_vertices, ["a","b","c"])
def test_init(self):
# Tests the initialization of the Vertex class
v1 = "a"
vertex = Vertex(v1)
self.assertEqual(vertex.id, "a")
self.assertDictEqual(vertex.neighbors, {})
def create_er_graph(self,
number_of_vertices,
probability,
seed,
thread=None,
**kwargs):
""" Commented lines of code serve debugging purposes. """
self.graph.reset_graph()
if self.graph.graph_representation_type == "matrix":
if kwargs.get('rle'):
self.graph.mode = "memory efficient"
random.seed(seed)
number_of_edges = [0] * number_of_vertices
for i in range(number_of_vertices):
if thread and thread.isStopped(): # --> Thread Status.
sys.exit(0)
self.graph.add_vertex(Vertex(i))
for new_node in range(number_of_vertices):
for adjacency_vertex in range(number_of_vertices):
per = random.uniform(0, 1)
if new_node == adjacency_vertex or adjacency_vertex >= number_of_vertices:
pass
elif probability >= per:
if thread and thread.isStopped(): # --> Thread Status.
sys.exit(0)
if not self.graph.isAdjacent(new_node, adjacency_vertex):
self.graph.add_edge_undirected(new_node,
adjacency_vertex)
number_of_edges[new_node] += 1
number_of_edges[adjacency_vertex] += 1
# print(f"""Connected node {new_node} ({number_of_edges[new_node]}) edges with """
# f"""node {adjacency_vertex} ({number_of_edges[adjacency_vertex]})
# edges with probability {probability} > {per}""")
# print()
# self.graph.get_number_of_edges()
generator.generate(self.graph.graph_representation_type, self.graph,
thread)
analyzer.analyze_generated_graph(self.graph.edges,
self.graph.graph_representation_type,
self.graph.graph_type,
number_of_vertices, None, None, None,
None, probability, seed)
def add_vertex(self, key):
"""
Add a new vertex object to the graph with
the given key and return the vertex.
"""
self.num_verticies += 1
new_vertex = Vertex(key)
self.vert_dict[key] = new_vertex
return new_vertex
def read_graph_file(filename: str) -> (Graph, [Vertex], [tuple]):
"""
Read a graph file from the class specified format.
Args:
* filename - Read in the file specified by filename
Returns:
A tuple that contains a graph object and two lists
"""
graph = Graph()
verts = []
edges = []
is_weighted = None
# Open up the file and parse the graph from text
with open(filename, "r") as file:
counter = 0
# Iterate through the file
for line in file:
# Obtain the type of graph
if counter == 0:
graph_type = line.strip()
if graph_type == "G":
graph = Graph()
elif graph_type == "D":
graph = Digraph()
else:
raise ValueError("Graph type not properly specified")
# Obtain the verticies for the graph.
elif counter == 1:
for key in line.strip().split(","):
verts.append(Vertex(key))
# Obtain all the edges.
elif counter > 1:
edge = line.strip("()\n").split(",")
if is_weighted is None:
is_weighted = bool(len(edge) == 3)
elif is_weighted and len(edge) < 3:
raise ValueError(
"You specified an edge with weights and one without. You should only do one or the other."
)
if len(edge) != 3 and len(edge) != 2:
raise ValueError(
f"You specified an incorrect amount of args for the edge: {line}"
)
edges.append(edge)
counter += 1
return graph, verts, edges
def test_add_vertex(self):
graph = Graph()
# Creates test Verticies
v1,v2,v3 = Vertex("a"), Vertex("b"), Vertex("c")
# Add vertex "a"
graph.add_vertex(v1)
self.assertEqual(graph.num_verticies, 1)
self.assertEqual(graph.num_edges, 0)
# Add vertex "b"
graph.add_vertex(v2)
self.assertEqual(graph.num_verticies, 2)
self.assertEqual(graph.num_edges, 0)
# Add vertex "c"
graph.add_vertex(v3)
self.assertEqual(graph.num_verticies, 3)
self.assertEqual(graph.num_edges, 0)
def traverse_npm_folder(root_path):
seen_verts = set()
edges = []
real_root = root_path.split("/")[-1]
vertices = {real_root: Vertex(real_root)}
for dir_name, subdir_list, _ in os.walk("./" + root_path +
"/node_modules"):
pkg, node_module = dir_name.split("/")[-2], dir_name.split("/")[-1]
for subdir in subdir_list:
if node_module == "node_modules" and subdir != ".bin":
vertices[subdir] = Vertex(subdir)
short_dir_name = os.path.basename(pkg)
if short_dir_name == "":
short_dir_name = real_root
if short_dir_name in vertices and short_dir_name != subdir:
edges.append((subdir, short_dir_name, 1))
return vertices.values(), edges
def add_vertex(self, key):
"""add a new vertex object to the graph with
the given key and return the vertex
"""
# increment the number of vertices
self.num_verticies += 1
# create a new vertex
new_vertex = Vertex(key)
# add the new vertex to the vertex list
self.vert_dict[key] = new_vertex
# return the new vertex
return new_vertex
def add_vertex(self, vertex_id=None, vertex=None):
if vertex is not None:
vid = vertex.get_id()
if vid in self.vertices:
# be careful of any existing nbrs of this vertex (incoming edges)
self.vertices[vid] = vertex
return
else:
self.vertices[vid] = vertex
self.no_of_vertices += 1
return
if vertex_id not in self.vertices:
if vertex_id not in self.vertices:
self.vertices[vertex_id] = Vertex(vertex_id)
self.no_of_vertices += 1
return
def create_homogeneous_graph(self, number_of_vertices, thread=None, **kwargs):
self.graph.reset_graph()
if self.graph.graph_representation_type == "matrix":
if kwargs.get('rle'):
self.graph.mode = "memory efficient"
for i in range(number_of_vertices):
self.graph.add_vertex(Vertex(str(i)))
if thread and thread.isStopped():
sys.exit(0)
for i in range(number_of_vertices):
for j in range(number_of_vertices):
if i != j and i < j:
self.graph.add_edge_undirected(i, j)
if thread and thread.isStopped():
sys.exit(0)
generator.generate(self.graph.graph_representation_type, self.graph, thread)
analyzer.analyze_generated_graph(self.graph.edges, self.graph.graph_representation_type, self.graph.graph_type,
number_of_vertices)
def create_custom_er_graph(self,
number_of_vertices,
number_of_edges,
probability,
seed,
thread=None,
**kwargs):
""" Commented lines of code serve debugging purposes. """
self.graph.reset_graph()
if self.graph.graph_representation_type == "matrix":
if kwargs.get('rle'):
self.graph.mode = "memory efficient"
random.seed(seed)
node_edges = [0] * number_of_vertices
number_of_connected_edges = 0
for i in range(number_of_vertices):
if thread and thread.isStopped(): # --> Thread Status.
sys.exit(0)
self.graph.add_vertex(Vertex(i))
graph_vector = self.graph.edge_indices.copy()
while number_of_connected_edges < number_of_edges:
new_node = int(random.choice(list(graph_vector.keys())))
adjacency_vertex = int(random.choice(list(graph_vector.keys())))
per = random.uniform(0, 1)
while new_node == adjacency_vertex or self.graph.isAdjacent(
new_node, adjacency_vertex):
if thread and thread.isStopped(): # --> Thread Status.
sys.exit(0)
if len(graph_vector) > 1:
counter = 0
for w, l in graph_vector.items():
if self.graph.isAdjacent(new_node,
w) and new_node != w:
counter += 1
if counter == len(graph_vector) - 1:
break
adjacency_vertex = int(random.choice(list(
graph_vector.keys())))
per = random.uniform(0, 1)
if probability > per:
if thread and thread.isStopped(): # --> Thread Status.
sys.exit(0)
self.graph.add_edge_undirected(new_node, adjacency_vertex)
node_edges[new_node] += 1
node_edges[adjacency_vertex] += 1
number_of_connected_edges += 1
# print(f"""Connected node {new_node} ({node_edges[new_node]}) edges with """
# f"""node {adjacency_vertex} ({node_edges[adjacency_vertex]}) edges with probability
# {probability} > {per}""")
# print(f"Number of connected edges {number_of_connected_edges}")
if node_edges[new_node] >= number_of_vertices - 1:
try:
del graph_vector[str(new_node)]
# print(f"Removed node {new_node} from play.")
# print(graph_vector)
except KeyError:
pass
elif node_edges[adjacency_vertex] >= number_of_vertices - 1:
try:
del graph_vector[str(adjacency_vertex)]
# print(f"Removed node {adjacency_vertex} from play.")
# print(graph_vector)
except KeyError:
pass
elif len(graph_vector) == 1:
last_node = random.choice(list(graph_vector.keys()))
del graph_vector[last_node]
# print(f"Removed node {adjacency_vertex} from play.")
# print(graph_vector)
# print("Terminating...")
break
# print()
# self.graph.get_number_of_edges()
generator.generate(self.graph.graph_representation_type, self.graph,
thread)
analyzer.analyze_generated_graph(self.graph.edges,
self.graph.graph_representation_type,
self.graph.graph_type,
number_of_vertices, None,
number_of_edges, None, None,
probability, seed)
def create_random_fixed_graph(self,
number_of_vertices,
graph_degree,
seed,
thread=None,
**kwargs):
""" Commented lines of code serve debugging purposes. """
self.graph.reset_graph()
if self.graph.graph_representation_type == "matrix":
if kwargs.get('rle'):
self.graph.mode = "memory efficient"
random.seed(seed)
number_of_edges = [0] * number_of_vertices
for i in range(number_of_vertices):
if thread and thread.isStopped():
sys.exit(0)
self.graph.add_vertex(Vertex(i))
graph_vector = self.graph.edge_indices.copy()
for v, i in self.graph.edge_indices.items():
if v in graph_vector:
# print(f"Connecting node {int(v)} with others...")
while number_of_edges[int(v)] < graph_degree and len(
graph_vector) != 0:
if thread and thread.isStopped():
sys.exit(0)
random_node = random.choice(list(graph_vector.keys()))
if random_node == v and len(graph_vector) != 1:
while random_node == v:
random_node = random.choice(
list(graph_vector.keys()))
if number_of_edges[int(random_node)] >= graph_degree:
del graph_vector[random_node]
# print(f"Removed node {int(random_node)} from play.")
# print(graph_vector)
if number_of_edges[int(v)] >= graph_degree:
try:
del graph_vector[v]
# print(f"Removed node {int(v) + 1} from play.")
# print(graph_vector)
except KeyError:
pass
if number_of_edges[int(random_node)] < graph_degree and v != random_node \
and not self.graph.isAdjacent(v, random_node):
self.graph.add_edge_undirected(v, random_node)
number_of_edges[int(v)] += 1
number_of_edges[int(random_node)] += 1
# print(f"""Connected node {int(v)} ({number_of_edges[int(v)]}) """
# f"""edges with node {int(random_node)} ({number_of_edges[int(random_node)]}) edges.""")
if number_of_edges[int(v)] >= graph_degree:
try:
del graph_vector[v]
# print(f"Removed node {int(v)} from play.")
# print(graph_vector)
except KeyError:
pass
if number_of_edges[int(random_node)] >= graph_degree:
del graph_vector[random_node]
# print(f"Removed node {int(random_node)} from play.")
# print(graph_vector)
elif len(graph_vector) == 1:
break
elif len(graph_vector) > 1:
counter = 0
for w, l in graph_vector.items():
if self.graph.isAdjacent(v, w) and v != w:
counter += 1
if counter == len(graph_vector) - 1:
break
elif not self.graph.isAdjacent(v, random_node) and len(
graph_vector) == 2 and v != random_node:
self.graph.add_edge_directed(v, random_node)
number_of_edges[int(v)] += 1
number_of_edges[int(random_node)] += 1
# print(f"""Connected node {int(v)} ({number_of_edges[int(v)]}) edges with """
# f"""node {int(random_node)} ({number_of_edges[int(random_node)]}) edges.""")
# print()
# self.graph.get_number_of_edges()
generator.generate(self.graph.graph_representation_type, self.graph,
thread)
analyzer.analyze_generated_graph(self.graph.edges,
self.graph.graph_representation_type,
self.graph.graph_type,
number_of_vertices, graph_degree,
None, None, None, None, seed)
def add_edge(self, from_key, to_key, weight=0):
if from_key not in self.vertices:
self.add_vertex(Vertex(from_key))
if to_key not in self.vertices:
self.add_vertex(Vertex(to_key))
self.vertices[from_key].add_neighbor(self.vertices[to_key], weight)
def create_scale_free_graph(self,
number_of_vertices,
seed,
thread=None,
**kwargs):
""" Commented lines of code serve debugging purposes. """
self.graph.reset_graph()
if self.graph.graph_representation_type == "matrix":
if kwargs.get('rle'):
self.graph.mode = "memory efficient"
number_of_edges = [0] * number_of_vertices
number_of_connected_edges = 0
random.seed(seed)
# Generate the tank with all nodes and a support graph vector.
for i in range(number_of_vertices):
if thread and thread.isStopped(): # --> Thread Status.
sys.exit(0)
self.graph.add_vertex(Vertex(i))
graph_vector = self.graph.edge_indices.copy()
# ======================================
# Make a random initial connection.
random_node1 = random.choice(list(
self.graph.edge_indices.keys())) # random_node1 --> str
random_node2 = random.choice(list(
self.graph.edge_indices.keys())) # random_node2 --> str
while random_node1 == random_node2:
random_node2 = random.choice(list(
self.graph.edge_indices.keys())) # random_node2 --> str
self.graph.add_edge_undirected(random_node1, random_node2)
number_of_edges[int(random_node1)] += 1
number_of_edges[int(random_node2)] += 1
number_of_connected_edges += 1
del graph_vector[random_node1]
del graph_vector[random_node2]
# print("Initial connection: ")
# print(f"""Connected node {int(random_node1) + 1} ({number_of_edges[int(random_node1)]}) edges with """
# f"""node {int(random_node2) + 1} ({number_of_edges[int(random_node2)]}) edges.\n""")
# ======================================
# Connected the rest of the nodes with all other with specified probability.
while len(graph_vector) != 0:
if thread and thread.isStopped(): # --> Thread Status.
sys.exit(0)
random_node3 = random.choice(list(graph_vector.keys()))
# print(f"Connecting node {int(random_node3) + 1} with others...")
for j in range(number_of_vertices):
if thread and thread.isStopped(): # --> Thread Status.
sys.exit(0)
if int(random_node3) != j and number_of_edges[j] != 0:
probability = number_of_edges[j] / number_of_connected_edges
probability_random = random.uniform(0, 1)
if probability > probability_random:
self.graph.add_edge_undirected(int(random_node3), j)
number_of_edges[int(random_node3)] += 1
number_of_edges[j] += 1
number_of_connected_edges += 1
# print(f"""Connected node {int(random_node3) + 1} ({number_of_edges[int(random_node3)]}) """
# f"""edges with node {j + 1} ({number_of_edges[j]}) edges with probability {probability}""")
# print()
del graph_vector[random_node3]
# ======================================
# self.graph.get_number_of_edges()
generator.generate(self.graph.graph_representation_type, self.graph,
thread)
analyzer.analyze_generated_graph(self.graph.edges,
self.graph.graph_representation_type,
self.graph.graph_type,
number_of_vertices, None, None, None,
None, None, seed)
def create_full_scale_free_graph(self, number_of_vertices, number_of_initial_nodes, seed, thread=None,
initial_connections_per_node=None, **kwargs):
""" Commented lines of code serve debugging purposes. """
self.graph.reset_graph()
if self.graph.graph_representation_type == "matrix":
if kwargs.get('rle'):
self.graph.mode = "memory efficient"
number_of_edges = [0] * number_of_vertices
number_of_connected_edges = 0
random.seed(seed)
graph_vector = {}
# In case there is only one initial node.
if number_of_initial_nodes == 1:
number_of_connected_edges += 1
# Generating tank with all nodes inside.
for i in range(number_of_vertices):
if thread and thread.isStopped(): # --> Thread Status.
sys.exit(0)
graph_vector[str(i)] = i
# Adding random mo initial nodes to the graph.
# print("Initial nodes:")
for i in range(number_of_initial_nodes):
if thread and thread.isStopped(): # --> Thread Status.
sys.exit(0)
random_node = random.choice(list(graph_vector.keys()))
self.graph.add_vertex(Vertex(random_node))
del graph_vector[random_node]
# print(int(random_node) + 1)
# Connecting all mo (initial nodes).
if number_of_initial_nodes == 1: # If number of initial node is one give the node a starting edge.
for v, i in list(self.graph.edge_indices.items()):
number_of_edges[int(v)] += 1
for v, i in list(self.graph.edge_indices.items()):
for b, j in list(self.graph.edge_indices.items()):
if thread and thread.isStopped(): # --> Thread Status.
sys.exit(0)
# If Custom Full Scale-Free Graph is chosen.
if initial_connections_per_node is not None and number_of_connected_edges >= initial_connections_per_node:
break
if v != b and v < b:
self.graph.add_edge_undirected(v, b)
number_of_edges[int(v)] += 1
number_of_edges[int(b)] += 1
number_of_connected_edges += 1
# If Custom Full Scale-Free Graph is chosen.
if initial_connections_per_node is not None and number_of_connected_edges >= initial_connections_per_node:
break
# print(f"""Connected node {int(v) + 1} ({number_of_edges[int(v)]}) edges with """
# f"""node {int(b) + 1} ({number_of_edges[int(b)]}) edges with probability 1.0""")
# print("Finished initial nodes.")
# ======================================
# Go for the rest nodes.
while len(graph_vector) != 0:
random_node = random.choice(list(graph_vector.keys())) # random_node --> str
self.graph.add_vertex(Vertex(random_node))
del graph_vector[random_node]
for v, i in list(self.graph.edge_indices.items()):
if thread and thread.isStopped(): # --> Thread Status.
sys.exit(0)
if v != random_node:
probability = number_of_edges[int(v)] / number_of_connected_edges
probability_random = random.uniform(0, 1)
if probability > probability_random:
self.graph.add_edge_undirected(random_node, v)
number_of_edges[int(random_node)] += 1
number_of_edges[int(v)] += 1
number_of_connected_edges += 1
# print(f"""Connected node {int(random_node) + 1} ({number_of_edges[int(random_node)]}) """
# f"""edges with node {int(v) + 1} ({number_of_edges[int(v)]}) edges with probability """
# f"""{probability}""")
graph_vector.clear()
# Sort randomized graph order.
# Method 1
self.graph.edge_indices = {int(c): v for c, v in self.graph.edge_indices.items()}
self.graph.edge_indices = OrderedDict(sorted(self.graph.edge_indices.items()))
self.graph.edge_indices = {str(c): v for c, v in self.graph.edge_indices.items()}
# self.graph.get_number_of_edges()
generator.generate(self.graph.graph_representation_type, self.graph, thread)
analyzer.analyze_generated_graph(self.graph.edges, self.graph.graph_representation_type, self.graph.graph_type,
number_of_vertices, None, None, initial_connections_per_node, None, None, seed)