#!/usr/bin/python

import numpy as np
import pcn_logic_eg as pcn

def main():
	#or_training = np.array( [ [0,0,0], [1,0,1], [0,1,1], [1,1,1] ])
	or_inputs = np.array( [[0,0], [0,1], [1,0], [1,1]])
	or_targets = np.array([[0],[1],[1],[1]])

	#p = pcn.pcn(a[:,0:2], a[:,2:])
	p = pcn.pcn(or_inputs, or_targets)
	#p.pcntrain(a[:,0:2], a[:, 2:], 0.25, 10)
	p.pcntrain(or_inputs, or_targets, 0.25, 10)
	print "confusion matrix"
	p.confmat(or_inputs, or_targets)

	print "doing"
	print "  for "
	print or_inputs
	inputs_bias = np.concatenate((or_inputs,-np.ones((np.shape(or_inputs)[0],1))), axis=1)
	print "  results"
	print p.pcnfwd(inputs_bias)


main()