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A Python program to generate event counts using a Poisson process
import random
import math
_lambda = 5
_num_total_arrivals = 150
_num_arrivals = 0
_arrival_time = 0
_num_arrivals_in_unit_time = []
_time_tick = 1
print('RANDOM_N,INTER_ARRIVAL_TIME,EVENT_ARRIVAL_TIME')
for i in range(_num_total_arrivals):
#Get the next probability value from Uniform(0,1)
p = random.random()
#Plug it into the inverse of the CDF of Exponential(_lamnbda)
_inter_arrival_time = -math.log(1.0 - p)/_lambda
#Add the inter-arrival time to the running sum
_arrival_time = _arrival_time + _inter_arrival_time
#Increment the number of arrival per unit time
_num_arrivals = _num_arrivals + 1
if _arrival_time > _time_tick:
_num_arrivals_in_unit_time.append(_num_arrivals)
_num_arrivals = 0
_time_tick = _time_tick + 1
#print it all out
print(str(p)+','+str(_inter_arrival_time)+','+str(_arrival_time))
print('\nNumber of arrivals in successive unit length intervals ===>')
print(_num_arrivals_in_unit_time)
print('Mean arrival rate for sample:' + str(sum(_num_arrivals_in_unit_time)/len(_num_arrivals_in_unit_time)))
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