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import time
class Graph(object):
"""
Defines an undirected graph with dictionary structure {}
"""
def __init__(self):
self._edges = dict()
self._nodes = list()
def _add_node(self, node):
"""
Adds a node to the list of nodes in a Graph.
:type node: String
"""
if node not in self._nodes:
self._nodes.append(node)
else:
print("Duplicated Node, skipping.")
def nodes(self):
"""
Returns the nodes in a Graph
"""
return self._nodes
def edges(self):
"""
Returns the edges in a Graph
"""
return list(self._edges.keys())
def add_edge(self, src_node, dst_node, **properties):
"""
Adds an edge to the Graph content dictionary.
Edge structure (src_node, dst_node): {property: value}
:type src_node: String
:type dst_node: String
:param properties: Edge labels.
:type properties: dict
"""
if src_node not in self._nodes:
self._add_node(src_node)
if dst_node not in self._nodes:
self._add_node(dst_node)
if src_node == dst_node:
print("Self loops not supported.")
return
coordinate_right = (src_node, dst_node)
coordinate_left = (dst_node, src_node)
edges = self.edges()
if (coordinate_right not in edges) and (coordinate_left not in edges):
self._edges[coordinate_right] = properties
else:
print("Duplicated edge, skipping.")
def get_edge(self, src_node, dst_node):
"""
Returns an edge value if the edge exist in the Graph.
:type src_node: String
:type dst_node: String
:return: a dict with the properties for the given edge
"""
coordinate_right = (src_node, dst_node)
coordinate_left = (dst_node, src_node)
edges = self.edges()
if coordinate_right in edges:
return self._edges[coordinate_right]
if coordinate_left in edges:
return self._edges[coordinate_left]
else:
return {}
def show(self):
for k, v in self._edges.items():
print("{coordinate}: weight={weight}".format(coordinate=k, weight=v['weight']))
def neighbors(self, node):
"""
Returns the neighbors of a node.
:type node: String
:return: A list with the neighbors of a node
"""
neighbors = list()
for k, v in self._edges.items():
if node in k:
if node == k[0]:
neighbors.append(k[1])
else:
neighbors.append(k[0])
return neighbors
def is_valid(line):
"""
Checks if the content of an edge has a valid format.
<vertex vertex weight>
:param line: A line of the input text.
:type: String
:return: A list if edge is valid, None otherwise.
"""
edge = line.rsplit()
wrong_args_number = len(edge) != 3
is_comment = line.startswith("#")
if wrong_args_number or not edge or is_comment:
return None
try:
int(edge[0])
int(edge[1])
int(edge[2])
except ValueError:
return None
return edge
def generate_edges(content):
"""
Yields an edge <vertex vertex weight> to the graph if it's valid.
:param content: The raw content of the input file.
"""
for edge in content:
valid_edge = is_valid(edge)
if valid_edge:
yield valid_edge
def load_graph_data(content):
"""
Loads the content of the input file as a graph and returns
a graph structure and its first node.
:param content: The raw content of the input file.
:return: An undirected Graph and a Node.
"""
G = Graph()
edges = generate_edges(content)
for edge in edges:
if edge:
G.add_edge(edge[0], edge[1], weight=edge[2])
return G
def dijkstra(graph):
"""
Shortest path algorithm. Returns a dictionary with the shortest distance from each
node in the graph to the initial node '1'.
:param graph: A Graph structure
:return: Dictionary with <node: distance> where the distance is the shortest path to the initial node.
"""
nodes = graph.nodes()
initial_node_index = nodes.index('1')
initial_node = nodes[initial_node_index]
neighbors_initial_node = graph.neighbors(initial_node)
distances = dict()
for node in nodes:
if node in neighbors_initial_node:
distances[node] = int(graph.get_edge(initial_node, node)['weight'])
else:
distances[node] = 2000000000
distances[initial_node] = 0
visited = [initial_node]
while sorted(nodes) != sorted(visited):
current_node = min_vertex(distances, visited)
visited.append(current_node)
for neighbor in graph.neighbors(current_node):
distance_to_neighbor = int(graph.get_edge(current_node, neighbor)['weight'])
temp_dist = distances[current_node] + distance_to_neighbor
if temp_dist < distances[neighbor]:
distances[neighbor] = temp_dist
return distances
def min_vertex(distances, visited):
"""
Returns the vector with the minimum distance which is not yet visited.
:param distances: A dictionary with <node: distance> structure
:param visited: A list with the visited nodes
:return: The non-visited vertex with the minimum distance
"""
min_distance = 2000000000
min_vertex = None
for node, neighbor_distance in distances.items():
if node in visited:
continue
if neighbor_distance < min_distance:
min_distance = neighbor_distance
min_vertex = node
return min_vertex
if __name__ == '__main__':
start = time.time() # wall-clock-time start
filename = sys.argv[-1]
content = open(filename)
graph = load_graph_data(content)
distances = dijkstra(graph)
result_dist = 0
result_vertex = None
for k, v in distances.items():
if k == '1':
continue
if v > result_dist:
result_dist = v
result_vertex = k
elif v == result_dist:
key_list = list(distances.keys())
index_result = key_list.index(result_vertex)
index_current = key_list.index(k)
if index_result < index_current:
result_vertex = k
print('RESULT VERTEX {result_vertex}'.format(result_vertex=result_vertex))
print('RESULT DIST {result_dist}'.format(result_dist=result_dist))
end = time.time() # wall-clock-time end
wall_clock_time = end - start
print('WALL-CLOCK TIME: {0:.2f} seconds'.format(wall_clock_time))
user_time = time.process_time()
print('USER TIME: {0:.2f} seconds'.format(user_time))
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