# Created by Leo from: C:\Python22\Tom\concious.leo

# << lonegg declarations >>
import sched
import random
import time
import pickle
import math

timmerthing = sched.scheduler(time.time, time.sleep)



g = random.Random()
h = random.Random()

NuralGuess = range(86399)
for i in range(86399):
	NuralGuess[i] = 0.0

SeccondsinDay = range(86399)
for i in range(86399):
	SeccondsinDay[i] = 0.0

nuralcounter = 0
Testpattern = []
timenow = 0
savecounter = 0
# -- end -- << lonegg declarations >>
# << lonegg methods >> (1 of 7)
def rand(a, b):
	return (b-a)*random.random() + a
# << lonegg methods >> (2 of 7)
def makeMatrix(I, J, fill=0.0):
	m = []
	for i in range(I):
		m.append([fill]*J)
	return m
# << lonegg methods >> (3 of 7)
class NN:
	# << class NN methods >> (1 of 6)
	def __init__(self, ni, nh, no):        
		self.ni = ni + 1 
		self.nh = nh
		self.no = no
		self.NNerror = ''
		self.testpattern = []
		self.ai = [1.0]*self.ni
		self.ah = [1.0]*self.nh
		self.ao = [1.0]*self.no
		self.wi = makeMatrix(self.ni, self.nh)
		self.wo = makeMatrix(self.nh, self.no)
		for i in range(self.ni):
			for j in range(self.nh):
				self.wi[i][j] = rand(-2.0, 2.0)
		for j in range(self.nh):
			for k in range(self.no):
				self.wo[j][k] = rand(-2.0, 2.0) 
		self.ci = makeMatrix(self.ni, self.nh)
		self.co = makeMatrix(self.nh, self.no)
	# << class NN methods >> (2 of 6)
	def update(self, inputs):
		if len(inputs) != self.ni-1:
			raise ValueError, 'wrong number of inputs'
		for i in range(self.ni-1):
			self.ai[i] = inputs[i]
		for j in range(self.nh):
			sum = 0.0
			for i in range(self.ni):
				sum = sum + self.ai[i] * self.wi[i][j]
			self.ah[j] = 1.0/(1.0+math.exp(-sum))
		for k in range(self.no):
			sum = 0.0
			for j in range(self.nh):
				sum = sum + self.ah[j] * self.wo[j][k]
			self.ao[k] = 1.0/(1.0+math.exp(-sum))
		return self.ao[:]
	# << class NN methods >> (3 of 6)
	def backPropagate(self, targets, N, M):
		if len(targets) != self.no:
			raise ValueError, 'wrong number of target values'
		output_deltas = [0.0] * self.no
		for k in range(self.no):
			ao = self.ao[k]
			output_deltas[k] = ao*(1-ao)*(targets[k]-ao)
		hidden_deltas = [0.0] * self.nh
		for j in range(self.nh):
			sum = 0.0
			for k in range(self.no):
				sum = sum + output_deltas[k]*self.wo[j][k]
			hidden_deltas[j] = self.ah[j]*(1-self.ah[j])*sum
		for j in range(self.nh):
			for k in range(self.no):
				change = output_deltas[k]*self.ah[j]
				self.wo[j][k] = self.wo[j][k] + N*change + M*self.co[j][k]
				self.co[j][k] = change
		for i in range(self.ni):
			for j in range(self.nh):
				change = hidden_deltas[j]*self.ai[i]
				self.wi[i][j] = self.wi[i][j] + N*change + M*self.ci[i][j]
				self.ci[i][j] = change
		error = 0.0
		for k in range(len(targets)):
			error = error + 0.5*(targets[k]-self.ao[k])**2
		return error
	# << class NN methods >> (4 of 6)
	def test(self, patterns):
		self.testpattern = []
		for p in patterns:
			self.testpattern.append(self.update(p[0]))        
		return self.testpattern
	# << class NN methods >> (5 of 6)
	def weights(self):
		print 'Input weights:'
		for i in range(self.ni):
			print self.wi[i]
		print
		print 'Output weights:'
		for j in range(self.nh):
			print self.wo[j]
	# << class NN methods >> (6 of 6)
	def train(self, patterns, iterations=2000, N=0.5, M=0.1):
		for i in xrange(iterations):
			error = 0.0
			for p in patterns:
				inputs = p[0]
				targets = p[1]
				self.update(inputs)
				error = error + self.backPropagate(targets, N, M)
			if i % 100 == 0:
				self.NNerror = 'error %-14f' % error
	# -- end -- << class NN methods >>
# << lonegg methods >> (4 of 7)
def plant():

	g.seed()
	h.seed(g)
	return abs(h.random()- g.random())
# << lonegg methods >> (5 of 7)
def OnSaveData():
	global nuralcounter, savecounter,NuralGuess, SeccondsinDay, Testpattern, timenow
	PlotWindow_data = [] 
	tom = open('c:\\python22\\tom\\concious_data2.txt','r+')
	try:
		PlotWindow_data = [ self.PlotWindow_mon.SeccondsinDay,  self.PlotWindow_tues.SeccondsinDay, self.PlotWindow_wed.SeccondsinDay, self.PlotWindow_thurs.SeccondsinDay, self.PlotWindow_fri.SeccondsinDay,  self.PlotWindow_sat.SeccondsinDay, self.PlotWindow_sun.SeccondsinDay, self.PlotWindow_mon.NuralGuess,   self.PlotWindow_tues.NuralGuess, self.PlotWindow_wed.NuralGuess, self.PlotWindow_thurs.NuralGuess,  self.PlotWindow_fri.NuralGuess, self.PlotWindow_sat.NuralGuess, self.PlotWindow_sun.NuralGuess]
		pickle.dump(PlotWindow_data, tom)
	except:
		pass
	self.tom.close()
# << lonegg methods >> (6 of 7)
def OnTimer():
	global nuralcounter, savecounter,NuralGuess, SeccondsinDay, Testpattern, timenow
	nuralcounter = nuralcounter + 1
	savecounter = savecounter + 1
	timenow = time.localtime()[3]*3600 + time.localtime()[4] * 60 + time.localtime()[5]
	SeccondsinDay[timenow] = plant()   
	Testpattern = NuralNet.test([ [ [ SeccondsinDay[timenow - 1] ], [0] ],[ [ SeccondsinDay[timenow] ], [0] ] ])        
	if  (timenow + 60) < 86399:
		NuralGuess[timenow + 60]  =  Testpattern[1][0]
	if nuralcounter == 104:
		nuralcounter = 0
		OnNuralTimer()
	if savecounter == 3600:
		savecounter = 0
		OnSaveData()
# << lonegg methods >> (7 of 7)
def OnNuralTimer():
	global nuralcounter, savecounter,NuralGuess, SeccondsinDay, Testpattern, timenow
	self.Trainpattern = []
	if time.localtime()[3] * 3600 + time.localtime()[4] * 60 + time.localtime()[5] - 60 >= 3600:
		for i in range(time.localtime()[3] * 3600 + time.localtime()[4] * 60 + time.localtime()[5] - 60, time.localtime()[3] * 3600 + time.localtime()[4] * 60 + time.localtime()[5]):
			self.Trainpattern.append([ [ self.SeccondsinDay[i - 3600] ], [ self.SeccondsinDay[i] ] ])
	else:
		for i in range(3600,3660):
			self.Trainpattern.append([ [ self.SeccondsinDay[i - 3600] ], [ self.SeccondsinDay[i]] ])

	self.NuralNet.train(self.Trainpattern)
# -- end -- << lonegg methods >>



timmerthing.enter(1, 1, OnTimer, ())
NuralNet = NN(1, 7, 1)
while 1:
	timmerthing.run()