Reputation: 449
I am trying to calculate the probability of an outcome with a hierarchical tree structure
The top is computer Computer A, the next 2 are Computer B & C, and the last 4 are Computer BD, BE, and CD, CE. I am trying to find the probability that if computer A gets infected with a virus what is the probability that B or C gets infected with a virus. And if B or C gets infected what is the probability that BD, BE, CD, CE gets infected with a virus
I want to run 100 trials to find the answer. I am new to doing probability on python. However here is the code I have so far:
import random, time
#prob that computers will get virus
CompA = 0.50
CompB = .25
CompC = .25
CompBD = .125
CompBE= .125
CompCD= .125
CompCE= .125
def generate():
x = random.random()
if x =< CompA: #Computer A has virus
prob_compa= sum(generate() for i in range(100)) #prob that Comp A has virus in a 100 rounds
print (prob_compa/100 + 'percent chance of getting virus')
try:
if CompB<.125:
prob_compa sum(generate() for i in range(100)) #prob that Comp B has virus in a 100 rounds
print (prob_compa/100 + 'percent chance of getting virus')
elif CompB<.125:
prob_compa= sum(generate() for i in range(100)) #prob that Comp C is sick in a 100 rounds
print (prob_compa/100 + 'percent chance of getting virus')
#I continue this method for the rest of the tree
Is there a better way and simpler way for me to get the results? random.uniform???
Upvotes: 2
Views: 9027
Reputation: 2744
As far as I understood this is what you are trying to achieve:
#python_test2.py
import random, time
virus_probabilities= { "CompA" : 0.50, "CompB" : .25, "CompC" : .25, "CompBD" : .125,
"CompBE" : .125, "CompCD" : .125, "CompCE" : .125}
def check_probability(computer_name, n_repetitions = 100):
prob_comp, repetitions = 0, 0
p_computer = virus_probabilities[computer_name]
while repetitions < n_repetitions:
x = random.random()
if x <= p_computer:
prob_comp += 1
repetitions += 1
print ("{0} % chance of getting virus on {1}".format(round(prob_comp/100.0, 2), computer_name))
for key in virus_probabilities:
check_probability(key, 1000)
When I run the file from the console, I get:
mabe@ubuntu:~/Desktop $ python test_2.py
2.49 % chance of getting virus on CompB
2.6 % chance of getting virus on CompC
5.07 % chance of getting virus on CompA
1.38 % chance of getting virus on CompBE
1.16 % chance of getting virus on CompBD
1.18 % chance of getting virus on CompCD
1.36 % chance of getting virus on CompCE
Upvotes: 1
Reputation: 19
Brilliant code from mabe02, perhaps worth adding a very minor improvement to the core function avoid confusion/future bugs:
def check_probability(computer_name, n_repetitions):
prob_comp, repetitions = 0, 0
p_computer = virus_probabilities[computer_name]
while repetitions < n_repetitions:
x = random.random()
if x <= p_computer:
prob_comp += 1
repetitions += 1
print ("{0} % changes of getting virus on {1}".format(round(prob_comp/n_repetitions, 2), computer_name))
Doing so would actually bring probabilities closer to the starting one which is expected as n_repetitions gets bigger.
Although for more specifics on conditional probability you should definitely have a look at this post: A simple explanation of Naive Bayes Classification
Upvotes: 1