class: "OutputTest"
success: "PASS"
failure: "NO PASS"

# Python statements initializing variables for the test below.
preamble: """
import inference

dist = inference.DiscreteDistribution()
dist['a'] = 1
dist['b'] = 2
dist['c'] = 2
dist['d'] = 0
dist['e'] = 1
N = 100000.0
samples = [dist.sample() for _ in range(int(N))]
ans1 = round(samples.count('a') * 1.0/N, 2)
ans2 = round(samples.count('b') * 1.0/N, 2)
ans3 = round(samples.count('c') * 1.0/N, 2)
ans4 = round(samples.count('d') * 1.0/N, 2)
ans5 = round(samples.count('e') * 1.0/N, 2)

ans = map(float, [ans1, ans2, ans3, ans4, ans5])
"""

# A python expression to be evaluated.  This expression must return the 
# same result for the student and instructor's code.

test: "ans"