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@AbeHandler

AbeHandler/markov_sample.py

Last active October 13, 2019 02:01
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markov_sample.py
import random
def prob_a_to_b(): return int(random.uniform(0,1) > 0)
def prob_b_to_a(): return int(random.uniform(0,1) > .5)
current_state, samples = 0, []
for i in range(10000):
samples.append(current_state)
if current_state == 0: # i.e. you are in state a
current_state = prob_a_to_b()
else: # i.e. you are in state b
current_state = prob_b_to_a()
print("p(a): {}".format(sum(1 for i in samples if i == 0)/len(samples)))
print("p(b): {}".format(sum(1 for i in samples if i == 1)/len(samples)))
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