pyFTS/fts.py
Petrônio Cândido de Lima e Silva b613c6db8a Acréscimo de informações aos modelos
2016-10-25 16:21:32 -02:00

41 lines
823 B
Python

import numpy as np
from pyFTS import *
class FTS:
def __init__(self,order,name):
self.sets = {}
self.flrgs = {}
self.order = order
self.shortname = name
self.name = name
self.detail = name
self.isSeasonal = False
self.isInterval = False
def fuzzy(self,data):
best = {"fuzzyset":"", "membership":0.0}
for f in self.sets:
fset = self.sets[f]
if best["membership"] <= fset.membership(data):
best["fuzzyset"] = fset.name
best["membership"] = fset.membership(data)
return best
def forecast(self,data):
pass
def train(self, data, sets):
pass
def getMidpoints(self,flrg):
ret = np.array([s.centroid for s in flrg.RHS])
return ret
def __str__(self):
tmp = self.name + ":\n"
for r in sorted(self.flrgs):
tmp = tmp + str(self.flrgs[r]) + "\n"
return tmp