from pyFTS import *

class ConventionalFLRG:
	def __init__(self,LHS):
		self.LHS = LHS
		self.RHS = set()
	
	def append(self,c):
		self.RHS.add(c)

	def __str__(self):
		tmp = self.LHS + " -> "
		tmp2 = ""
		for c in self.RHS:
			if len(tmp2) > 0:
				tmp2 = tmp2 + ","
			tmp2 = tmp2 + c
		return tmp + tmp2


class ConventionalFTS(fts.FTS):
	def __init__(self,name):
		super(ConventionalFTS, self).__init__(1,name)
        
	def forecast(self,data):
        
		actual = self.fuzzy(data)
        
		if actual["fuzzyset"] not in self.flrgs:
			return self.sets[actual["fuzzyset"]].centroid

		flrg = self.flrgs[actual["fuzzyset"]]

		count = 0.0
		denom = 0.0

		for s in flrg.RHS:
			denom = denom + self.sets[s].centroid
			count = count + 1.0

		return denom/count
        
	def train(self, data, sets):
		last = {"fuzzyset":"", "membership":0.0}
		actual = {"fuzzyset":"", "membership":0.0}
		
		for s in sets:
			self.sets[s.name] = s
		
		self.flrgs = {}
		count = 1
		for inst in data:
			actual = self.fuzzy(inst)
			
			if count > self.order:
				if last["fuzzyset"] not in self.flrgs:
					self.flrgs[last["fuzzyset"]] = ConventionalFLRG(last["fuzzyset"])
			
				self.flrgs[last["fuzzyset"]].append(actual["fuzzyset"])    
			count = count + 1
			last = actual