104 lines
2.2 KiB
Python
104 lines
2.2 KiB
Python
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import numpy as np
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from pyFTS import *
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class IntervalFTS(hofts.HighOrderFTS):
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def __init__(self,name):
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super(IntervalFTS, self).__init__(name)
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self.flrgs = {}
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def getUpper(self,flrg):
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ret = np.array([s.upper for s in flrg.RHS])
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return ret
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def getLower(self,flrg):
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ret = np.array([s.lower for s in flrg.RHS])
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return ret
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def getSequenceMembership(self, data, fuzzySets):
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mb = [ fuzzySets[k].membership( data[k] ) for k in np.arange(0,len(data)) ]
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return mb
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def forecast(self,data):
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ndata = np.array(data)
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l = len(ndata)
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ret = []
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for k in np.arange(self.order+1,l):
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up = []
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lo = []
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# Achar os conjuntos que tem pert > 0 para cada lag
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count = 0
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lags = {}
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combinations = 1
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for instance in ndata[k-self.order : k]:
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mb = common.fuzzyInstance(instance, self.sets)
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tmp = np.argwhere( mb )
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idx = np.ravel(tmp) #flatten
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lag = {}
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lag["id"] = count
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lag["sets"] = idx
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lag["memberships"] = [mb[ k ] for k in idx]
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lag["count"] = len(idx)
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lags[count] = lag
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combinations = combinations * lag["count"]
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count = count + 1
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print(combinations)
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# Build a tree exploring all possibilities
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# Trace each path from leaf to roots and reverse path
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# -------
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#return lags
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wflrgs = {}
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# Gerar as permutações possíveis e as FLRG's correspondentes
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lag_inc = [0 for k in np.arange(0,self.order) ]
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isComplete = False
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while (isComplete):
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flrg = hofts.HighOrderFLRG(self.order)
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flrg.appendLHS( self.sets[ lag_inc[0] ] )
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for lag_count in np.arange(1,self.order):
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if lag_count > 1: lag_inc[ lag_count - 1 ] = 0
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# for
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#lag_count = lag_count + 1
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# Achar a pert geral de cada FLRG
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# achar o os bounds de cada FLRG
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# gerar o intervalo
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# tmpdata = common.fuzzySeries(XX,self.sets)
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# tmpflrg = HighOrderFLRG(self.order)
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# for s in tmpdata: tmpflrg.appendLHS(s)
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# if tmpflrg.strLHS() not in self.flrgs:
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# ret.append(tmpdata[-1].centroid)
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# else:
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# flrg = self.flrgs[tmpflrg.strLHS()]
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# mp = self.getMidpoints(flrg)
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# ret.append(sum(mp)/len(mp))
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# return ret
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