misc/math/stochastic.py at be926d3ed018b1fde8ae62b95ba875a17af11c45 · daedalus/misc · GitHub

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#!/usr/bin/env python
# Author Dario Clavijo 2016
# GPLv3
# don't know if the theory is right

a = [0.0, 1.0, 0.0, 1.0]
b = [0.0, 0.0, 1.0, 1.0]
aANDb = [0, 0, 0, 1]
aORb = [0, 1, 1, 1]
aXORb = [0, 1, 1, 0]

# def f(p,q):
# 	return (p*q) / ((p*q) + (1-p)*(1-q))


def stochastic_average_fAND(p, q):
    return (p * q) / 2


def stochastic_average_fOR(p, q):
    return (p + q) / 2


def stochastic_average_fXOR(p, q):
    return ((p - q) * (p - q)) / 2


def AND(p, q):
    return float(stochastic_average_fAND(p, q) > 0)


def OR(p, q):
    return float(stochastic_average_fOR(p, q) > 0)


def XOR(p, q):
    return float(stochastic_average_fXOR(p, q) > 0)


print("a\tb\tand\tor\txor")
for i in range(0, 4):
    print(
        a[i],
        b[i],
        stochastic_average_fAND(a[i], b[i]),
        stochastic_average_fOR(a[i], b[i]),
        stochastic_average_fXOR(a[i], b[i]),
    )

print("a\tb\tand\tor\txor")
for i in range(0, 4):
    print(a[i], b[i], AND(a[i], b[i]), OR(a[i], b[i]), XOR(a[i], b[i]))