thingy

import numpy as np
import itertools

# update rule for neuron x1
def update_1((a, b, c)):
    test = c-b+2
    if (test > 0):
        new = 1
    elif (test == 0):
        new = a
    elif (test < 0):
        new = 0
    return [new, b, c]

# update rule for neuron x2
def update_2((a, b, c)):
    test = c-a+2
    if (test > 0):
        new = 1
    elif (test == 0):
        new = b
    elif (test < 0):
        new = 0
    return [a, new, c]

# update rule for neuron x3
def update_3((a, b, c)):
    test = a+b-2
    if (test > 0):
        new = 1
    elif (test == 0):
        new = c
    elif (test < 0):
        new = 0
    return [a, b, new]

# update all neurons
def update((a, b, c)):
    print "updating neuron 1: " + str(update_1((a, b, c)))
    print "updating neuron 2: " + str(update_2((a, b, c)))
    print "updating neuron 2: " + str(update_3((a, b, c)))

# generate all combinations: [[0, 0, 0], [0, 0, 1],...,[1, 1, 1]]
def generate_combinations(n):
    sequences = ["".join(seq) for seq in itertools.product("01", repeat=n)]
    outarray = []
    for s in sequences:
        string_pieces = list(s)
        int_pieces = []
        for j in range(n):
            int_pieces.append(int(string_pieces[j]))
        outarray.append(int_pieces)
    return outarray

# for 3 neurons
N = 3
inputs = generate_combinations(N)

# cycle through all possible inputs and work out the next period configuration
for i in inputs:
    print "========="
    print "input: " + str(i)
    update(i)
    print "========="