pyFTS/ismailefendi.py
2016-10-18 17:48:02 -02:00

62 lines
1.5 KiB
Python

import numpy as np
from pyFTS import *
class ImprovedWeightedFLRG:
def __init__(self,LHS):
self.LHS = LHS
self.RHS = {}
self.count = 0.0
def append(self,c):
if c not in self.RHS:
self.RHS[c] = 1.0
else:
self.RHS[c] = self.RHS[c] + 1.0
self.count = self.count + 1.0
def weights(self):
return np.array([ self.RHS[c]/self.count for c in self.RHS.keys() ])
def __str__(self):
tmp = self.LHS + " -> "
tmp2 = ""
for c in self.RHS.keys():
if len(tmp2) > 0:
tmp2 = tmp2 + ","
tmp2 = tmp2 + c + "(" + str(round(self.RHS[c]/self.count,3)) + ")"
return tmp + tmp2
class ImprovedWeightedFTS(fts.FTS):
def __init__(self,name):
super(ImprovedWeightedFTS, self).__init__(1,name)
def generateFLRG(self, flrs):
flrgs = {}
for flr in flrs:
if flr.LHS in flrgs:
flrgs[flr.LHS].append(flr.RHS)
else:
flrgs[flr.LHS] = ImprovedWeightedFLRG(flr.LHS);
flrgs[flr.LHS].append(flr.RHS)
return (flrgs)
def train(self, data, sets):
self.sets = sets
tmpdata = common.fuzzySeries(data,sets)
flrs = common.generateRecurrentFLRs(tmpdata)
self.flrgs = self.generateFLRG(flrs)
def forecast(self,data):
mv = common.fuzzyInstance(data, self.sets)
actual = self.sets[ np.argwhere( mv == max(mv) )[0,0] ]
if actual.name not in self.flrgs:
return actual.centroid
flrg = self.flrgs[actual.name]
mi = np.array([self.sets[s].centroid for s in flrg.RHS.keys()])
return mi.dot( flrg.weights() )