pyFTS/chen.py
Petrônio Cândido de Lima e Silva 85a47e225a - Otimizações em pfts.forecastAheadDistribution
- Correção da Issue #1
2017-01-16 18:32:15 -02:00

70 lines
1.7 KiB
Python

import numpy as np
from pyFTS.common import FuzzySet, FLR
from pyFTS import fts
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.name + " -> "
tmp2 = ""
for c in sorted(self.RHS, key=lambda s: s.name):
if len(tmp2) > 0:
tmp2 = tmp2 + ","
tmp2 = tmp2 + c.name
return tmp + tmp2
class ConventionalFTS(fts.FTS):
def __init__(self, name):
super(ConventionalFTS, self).__init__(1, "CFTS")
self.name = "Conventional FTS"
self.detail = "Chen"
self.flrgs = {}
def generateFLRG(self, flrs):
flrgs = {}
for flr in flrs:
if flr.LHS.name in flrgs:
flrgs[flr.LHS.name].append(flr.RHS)
else:
flrgs[flr.LHS.name] = ConventionalFLRG(flr.LHS);
flrgs[flr.LHS.name].append(flr.RHS)
return (flrgs)
def train(self, data, sets):
self.sets = sets
tmpdata = FuzzySet.fuzzySeries(data, sets)
flrs = FLR.generateNonRecurrentFLRs(tmpdata)
self.flrgs = self.generateFLRG(flrs)
def forecast(self, data):
ndata = np.array(data)
l = len(ndata)
ret = []
for k in np.arange(0, l):
mv = FuzzySet.fuzzyInstance(ndata[k], self.sets)
actual = self.sets[np.argwhere(mv == max(mv))[0, 0]]
if actual.name not in self.flrgs:
ret.append(actual.centroid)
else:
flrg = self.flrgs[actual.name]
mp = self.getMidpoints(flrg)
ret.append(sum(mp) / len(mp))
return ret