def getEdgeRobustness(Graph):
new = mst.Graph(Graph.V)
new.graph = Graph.graph
new.r = mRE.randomConnections(new, 1)
efficiency = []
while True:
try:
new.dist()
efficiency.append(eff.getEfficiency(new))
new.newConnection(1, 0)
except IndexError:
return mean(efficiency)
def main():
#Gets User input
initial, groups = get_user_input() #, totalnodes, inc
#Creates Plots according to user inputs
numPlots = 1 #int(((totalnodes - initial)/inc)) + 1
fig, axs = plt.subplots(numPlots, sharex=True)
fig.suptitle('Efficiency vs Edges at nodes')
i = 0
#Loops user inputs so creates n starting points with nodes,
for num1 in range(initial, initial + 1, 1): #totalnodes + 1, inc):
g = mst.Graph(num1)
g.newMST()
edges = int((num1 * (num1 - 1)) / 2 - (num1 - 1)) + 1
interval = int(float(edges) * float(groups / 100))
Data = {
'Edges': list(range(1, edges, interval)),
'Efficiency': [],
'Efficiency Alt': [],
# 'Network Connectivity': [],
# 'Robustness': [],
# 'Edge Robustness': []
}
add_Network_Data(g, Data, interval)
df = pd.DataFrame(
Data,
columns=[
'Edges',
'Efficiency',
'Efficiency Alt',
# 'Network Connectivity', 'Robustness',
# 'Edge Robustness'
])
name = 'Nodes=' + str(num1)
create_Graph(numPlots, axs, i, df, name)
create_dataframe_folder(df, name)
i += 1
#Shows final plot
if len(sys.argv) > 1:
plt.show()
import distances
import cities
import MST
distances = distances.get_distances()
cities = cities.get_cities()
vertices = len(distances)
graph = MST.Graph(vertices)
for city, endpoints in distances.items():
for city2 in endpoints:
graph.add_edge(city2['start_id'], city2['end_id'], city2['distance'])
result, cost = graph.MST()
print ("Edges of MST")
for u, v, weight in result:
print("%s <-> %s = ~%d km" % (cities[u]['name'], cities[v]['name'], weight))
print("Total Cost => " , cost)
