pyFTS/chen.py
Petrônio Cândido de Lima e Silva 728e8414b7 - General refactoring to include **kwargs on methods signatures
- Ensemble FTS
2017-04-14 19:57:39 -03:00

76 lines
2.0 KiB
Python

import numpy as np
from pyFTS.common import FuzzySet, FLR
from pyFTS import fts
class ConventionalFLRG(object):
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
def __len__(self):
return len(self.RHS)
class ConventionalFTS(fts.FTS):
def __init__(self, order, **kwargs):
super(ConventionalFTS, self).__init__(1, "CFTS " + name)
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,order=1,parameters=None):
self.sets = sets
ndata = self.doTransformations(data)
tmpdata = FuzzySet.fuzzySeries(ndata, sets)
flrs = FLR.generateNonRecurrentFLRs(tmpdata)
self.flrgs = self.generateFLRG(flrs)
def forecast(self, data, **kwargs):
ndata = np.array(self.doTransformations(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))
ret = self.doInverseTransformations(ret, params=[data[self.order - 1:]])
return ret