Seasonal FTS

sfts.py

@@ -0,0 +1,57 @@
+import numpy as np
+from pyFTS import *
+
+class SeasonalFLRG(fts.FTS):
+	def __init__(self,seasonality):
+		self.LHS = seasonality
+		self.RHS = []
+
+	def append(self,c):
+		self.RHS.append(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 SeasonalFTS(fts.FTS):
+	def __init__(self,name):
+		super(WeightedFTS, self).__init__(1,name)
+        
+	def defuzzy(self,data):
+        
+		actual = self.fuzzy(data)
+        
+		if actual["fuzzyset"] not in self.flrgs:
+			return self.sets[actual["fuzzyset"]].centroid
+
+		flrg = self.flrgs[actual["fuzzyset"]]
+
+		mi = np.array([self.sets[s].centroid for s in flrg.RHS])
+        
+		return mi.dot( flrg.weights() )
+        
+	def learn(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"]] = WeightedFLRG(last["fuzzyset"])
+			
+				self.flrgs[last["fuzzyset"]].append(actual["fuzzyset"])    
+			count = count + 1
+			last = actual