run.py

from FireflyAlgorithm import *
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

df=np.random.randint(30,100,(30,3)) # creating a Random dataset for 30 traffic signal
df=pd.DataFrame(df,columns =['no_of_vehicle','avg_speed','avg_distance_btw_them'])
df.to_csv('data.csv')
df=df.values
prob_dim=(len(df))
pop_size=3000
data_set=[[0 for x in range(prob_dim)] for x in range(pop_size)]

def generate(df):
    no_of_lane=prob_dim
    for i in range(pop_size):
        for j in range(no_of_lane):
            data_set[i][j]=((df[j][0]*df[j][1])//df[j][2]) #using random created dataset for initializing the fireflies 
            # print(data_set[i][j])
    return data_set


data_set=generate(df)
# print(data_set)


def function(D, sol): #a fitness function for fireflies 
    val = 0.0
    for i in range(D):
        val = val + sol[i] * sol[i]
    return val




Algorithm = FireflyAlgorithm(10, 10, 100, 0.5, 0.2,0.9,30, 180, function,data_set)

Best = Algorithm.Run()


print ('best solution is ',Best[0],'and best fiteness ',Best[1])
plt.figure(figsize=(150,120)) #increasing figsize for better visualization
plt.bar([x+1 for x in range(prob_dim)],Algorithm.nbest)#1st list is the traffic light no
plt.title("Graph of traffic light No and their allocated timing in minutes")
plt.xlabel('Traffic light no')
plt.ylabel('allocated time')
plt.show()