svsim.py

import random


arr_values = [0, 60000000, 120000000, 240000000, 480000000]
arr_prob = [0.0625, 0.5, 0.25, 0.125, 0.0625]

arr_mult_values = [25, 50, 100]
arr_mult_prob = [0.70, 0.20, 0.10]


def probs_index(probs, v):
    t = 0.0
    for i, p in enumerate(probs):
        t += p
        if v <= t:
            return i
    raise "panic"


def choose_from_values(vals, probs):
    r = random.uniform(0, 1)
    i = probs_index(probs, r)
    return vals[i]


def f_cfv(vals, probs):
    return lambda: choose_from_values(vals, probs)


def sim(fns, nsamples=10000):
    samples = []
    for i in range(nsamples):
        vec = tuple(fn() for fn in fns)
        samples.append(vec)
    return samples


def md_freqs_from_sim(val_sets, samples):
    val_freqs = {}
    for s in samples:
        if s not in val_freqs:
            val_freqs[s] = 0
        val_freqs[s] += 1
    return val_freqs


def probs_for_md_freqs(md_freqs, n):
    return {k: v/n for k, v in md_freqs.items()}


sim_fns=[
    f_cfv(arr_values, arr_prob),
    f_cfv(arr_mult_values, arr_mult_prob),
]

simout=sim(sim_fns)
md_freqs=md_freqs_from_sim([arr_values, arr_mult_values], simout)
output=probs_for_md_freqs(md_freqs, len(simout))


for k in sorted(output):
    v=output[k]
    x=','.join([str(x) for x in k])
    print("{},{}".format(x, v))