""" A Python Class
A simple Python graph class, demonstrating the essential
facts and functionalities of graphs.
"""
class Graph(object):
def __init__(self, graph_dict={}):
""" initializes a graph object """
self.__graph_dict = graph_dict
def vertices(self):
""" returns the vertices of a graph """
return list(self.__graph_dict.keys())
def edges(self):
""" returns the edges of a graph """
return self.__generate_edges()
def add_vertex(self, vertex):
""" If the vertex "vertex" is not in
self.__graph_dict, a key "vertex" with an empty
list as a value is added to the dictionary.
Otherwise nothing has to be done.
"""
if vertex not in self.__graph_dict:
self.__graph_dict[vertex] = []
def add_edge(self, edge):
""" assumes that edge is of type set, tuple or list;
between two vertices can be multiple edges!
"""
edge = set(edge)
vertex1 = edge.pop()
if edge:
# not a loop
vertex2 = edge.pop()
else:
# a loop
vertex2 = vertex1
if vertex1 in self.__graph_dict:
self.__graph_dict[vertex1].append(vertex2)
else:
self.__graph_dict[vertex1] = [vertex2]
def __generate_edges(self):
""" A static method generating the edges of the
graph "graph". Edges are represented as sets
with one (a loop back to the vertex) or two
vertices
"""
edges = []
for vertex in self.__graph_dict:
for neighbour in self.__graph_dict[vertex]:
if {neighbour, vertex} not in edges:
edges.append({vertex, neighbour})
return edges
def __str__(self):
res = "vertices: "
for k in self.__graph_dict:
res += str(k) + " "
res += "\nedges: "
for edge in self.__generate_edges():
res += str(edge) + " "
return res
def find_isolated_vertices(self):
""" returns a list of isolated vertices. """
graph = self.__graph_dict
isolated = []
for vertex in graph:
print(isolated, vertex)
if not graph[vertex]:
isolated += [vertex]
return isolated
def find_path(self, start_vertex, end_vertex, path=[]):
""" find a path from start_vertex to end_vertex
in graph """
graph = self.__graph_dict
path = path + [start_vertex]
if start_vertex == end_vertex:
return path
if start_vertex not in graph:
return None
for vertex in graph[start_vertex]:
if vertex not in path:
extended_path = self.find_path(vertex,
end_vertex,
path)
if extended_path:
return extended_path
return None
def find_all_paths(self, start_vertex, end_vertex, path=[]):
""" find all paths from start_vertex to
end_vertex in graph """
graph = self.__graph_dict
path = path + [start_vertex]
if start_vertex == end_vertex:
return [path]
if start_vertex not in graph:
return []
paths = []
for vertex in graph[start_vertex]:
if vertex not in path:
extended_paths = self.find_all_paths(vertex,
end_vertex,
path)
for p in extended_paths:
paths.append(p)
return paths
def is_connected(self,
vertices_encountered = set(),
start_vertex=None):
""" determines if the graph is connected """
gdict = self.__graph_dict
vertices = gdict.keys()
if not start_vertex:
# chosse a vertex from graph as a starting point
start_vertex = vertices[0]
vertices_encountered.add(start_vertex)
if len(vertices_encountered) != len(vertices):
for vertex in gdict[start_vertex]:
if vertex not in vertices_encountered:
if self.is_connected(vertices_encountered, vertex):
return True
else:
return True
return False
def vertex_degree(self, vertex):
""" The degree of a vertex is the number of edges connecting
it, i.e. the number of adjacent vertices. Loops are counted
double, i.e. every occurence of vertex in the list
of adjacent vertices. """
adj_vertices = self.__graph_dict[vertex]
degree = len(adj_vertices) + adj_vertices.count(vertex)
return degree
def degree_sequence(self):
""" calculates the degree sequence """
seq = []
for vertex in self.__graph_dict:
seq.append(self.vertex_degree(vertex))
seq.sort(reverse=True)
return tuple(seq)
@staticmethod
def is_degree_sequence(sequence):
""" Method returns True, if the sequence "sequence" is a
degree sequence, i.e. a non-increasing sequence.
Otherwise False is returned.
"""
# check if the sequence sequence is non-increasing:
return all( x>=y for x, y in zip(sequence, sequence[1:]))
def delta(self):
""" the minimum degree of the vertices """
min = 100000000
for vertex in self.__graph_dict:
vertex_degree = self.vertex_degree(vertex)
if vertex_degree < min:
min = vertex_degree
return min
def Delta(self):
""" the maximum degree of the vertices """
max = 0
for vertex in self.__graph_dict:
vertex_degree = self.vertex_degree(vertex)
if vertex_degree > max:
max = vertex_degree
return max
def density(self):
""" method to calculate the density of a graph """
g = self.__graph_dict
V = len(g.keys())
E = len(self.edges())
return 2.0 * E / (V *(V - 1))
def diameter(self):
""" calculates the diameter of the graph """
v = self.vertices()
pairs = [ (v[i],v[j]) for i in range(len(v)-1) for j in range(i+1, len(v))]
smallest_paths = []
for (s,e) in pairs:
paths = self.find_all_paths(s,e)
smallest = sorted(paths, key=len)[0]
smallest_paths.append(smallest)
smallest_paths.sort(key=len)
# longest path is at the end of list,
# i.e. diameter corresponds to the length of this path
diameter = len(smallest_paths[-1])
return diameter
@staticmethod
def erdoes_gallai(dsequence):
""" Checks if the condition of the Erdoes-Gallai inequality
is fullfilled
"""
if sum(dsequence) % 2:
# sum of sequence is odd
return False
if Graph.is_degree_sequence(dsequence):
for k in range(1,len(dsequence) + 1):
left = sum(dsequence[:k])
right = k * (k-1) + sum([min(x,k) for x in dsequence[k:]])
if left > right:
return False
else:
# sequence is increasing
return False
return True
if __name__ == "__main__":
g = { "a" : ["d"],
"b" : ["c"],
"c" : ["b", "c", "d", "e"],
"d" : ["a", "c"],
"e" : ["c"],
"f" : []
}
graph = Graph(g)
print(graph)
for node in graph.vertices():
print(graph.vertex_degree(node))
print("List of isolated vertices:")
print(graph.find_isolated_vertices())
print("""A path from "a" to "e":""")
print(graph.find_path("a", "e"))
print("""All pathes from "a" to "e":""")
print(graph.find_all_paths("a", "e"))
print("The maximum degree of the graph is:")
print(graph.Delta())
print("The minimum degree of the graph is:")
print(graph.delta())
print("Edges:")
print(graph.edges())
print("Degree Sequence: ")
ds = graph.degree_sequence()
print(ds)
fullfilling = [ [2, 2, 2, 2, 1, 1],
[3, 3, 3, 3, 3, 3],
[3, 3, 2, 1, 1]
]
non_fullfilling = [ [4, 3, 2, 2, 2, 1, 1],
[6, 6, 5, 4, 4, 2, 1],
[3, 3, 3, 1] ]
for sequence in fullfilling + non_fullfilling :
print(sequence, Graph.erdoes_gallai(sequence))
print("Add vertex 'z':")
graph.add_vertex("z")
print(graph)
print("Add edge ('x','y'): ")
graph.add_edge(('x', 'y'))
print(graph)
print("Add edge ('a','d'): ")
graph.add_edge(('a', 'd'))
print(graph)