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Cleaning the sources

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Petrônio Cândido de Lima e Silva 2016-11-08 14:29:51 -02:00
parent 7c1e79b30d
commit 84b29bcdf7
2 changed files with 6 additions and 21 deletions
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2
ifts.py
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@ -27,8 +27,6 @@ class IntervalFTS(hofts.HighOrderFTS):
return ret return ret
def getSequenceMembership(self, data, fuzzySets): def getSequenceMembership(self, data, fuzzySets):
#print(data)
#print(fuzzySets)
mb = [ fuzzySets[k].membership( data[k] ) for k in np.arange(0,len(data)) ] mb = [ fuzzySets[k].membership( data[k] ) for k in np.arange(0,len(data)) ]
return mb return mb

25
pifts.py
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@ -67,8 +67,6 @@ class ProbabilisticIntervalFTS(ifts.IntervalFTS):
tmp = self.flrgs[ flrg.strLHS() ] tmp = self.flrgs[ flrg.strLHS() ]
ret = sum(np.array([ tmp.getProbability(s) * self.setsDict[s].upper for s in tmp.RHS])) ret = sum(np.array([ tmp.getProbability(s) * self.setsDict[s].upper for s in tmp.RHS]))
else: else:
#print("hit" + flrg.strLHS())
#ret = flrg.LHS[-1].upper
ret = sum(np.array([ 0.33 * s.upper for s in flrg.LHS])) ret = sum(np.array([ 0.33 * s.upper for s in flrg.LHS]))
return ret return ret
@ -77,17 +75,13 @@ class ProbabilisticIntervalFTS(ifts.IntervalFTS):
tmp = self.flrgs[ flrg.strLHS() ] tmp = self.flrgs[ flrg.strLHS() ]
ret = sum(np.array([ tmp.getProbability(s) * self.setsDict[s].lower for s in tmp.RHS])) ret = sum(np.array([ tmp.getProbability(s) * self.setsDict[s].lower for s in tmp.RHS]))
else: else:
#print("hit" + flrg.strLHS())
#ret = flrg.LHS[-1].lower
ret = sum(np.array([ 0.33 * s.lower for s in flrg.LHS])) ret = sum(np.array([ 0.33 * s.lower for s in flrg.LHS]))
return ret return ret
def forecast(self,data): def forecast(self,data):
ndata = np.array(data) ndata = np.array(data)
#print(ndata)
l = len(ndata) l = len(ndata)
ret = [] ret = []
@ -115,16 +109,14 @@ class ProbabilisticIntervalFTS(ifts.IntervalFTS):
idx = np.ravel(tmp) #flatten the array idx = np.ravel(tmp) #flatten the array
if idx.size == 0: # the element is out of the bounds of the Universe of Discourse if idx.size == 0: # the element is out of the bounds of the Universe of Discourse
#print("high order - idx.size == 0 - " + str(instance))
if math.ceil(instance) <= self.sets[0].lower: if math.ceil(instance) <= self.sets[0].lower:
idx = [0] idx = [0]
elif math.ceil(instance) >= self.sets[-1].upper: elif math.ceil(instance) >= self.sets[-1].upper:
idx = [len(self.sets)-1] idx = [len(self.sets)-1]
#print(idx)
else: else:
raise Exception( instance ) raise Exception( instance )
#print(idx)
lags[count] = idx lags[count] = idx
count = count + 1 count = count + 1
# Build the tree with all possible paths # Build the tree with all possible paths
@ -147,7 +139,7 @@ class ProbabilisticIntervalFTS(ifts.IntervalFTS):
# Find the general membership of FLRG # Find the general membership of FLRG
affected_flrgs_memberships.append(min(self.getSequenceMembership(subset, flrg.LHS))) affected_flrgs_memberships.append(min(self.getSequenceMembership(subset, flrg.LHS)))
#print(self.getSequenceMembership(subset, flrg.LHS))
else: else:
mv = common.fuzzyInstance(ndata[k],self.sets) # get all membership values mv = common.fuzzyInstance(ndata[k],self.sets) # get all membership values
@ -155,20 +147,17 @@ class ProbabilisticIntervalFTS(ifts.IntervalFTS):
idx = np.ravel(tmp) # flatten the array idx = np.ravel(tmp) # flatten the array
if idx.size == 0: # the element is out of the bounds of the Universe of Discourse if idx.size == 0: # the element is out of the bounds of the Universe of Discourse
#print("idx.size == 0")
if math.ceil(ndata[k]) <= self.sets[0].lower: if math.ceil(ndata[k]) <= self.sets[0].lower:
idx = [0] idx = [0]
elif math.ceil(ndata[k]) >= self.sets[-1].upper: elif math.ceil(ndata[k]) >= self.sets[-1].upper:
idx = [len(self.sets)-1] idx = [len(self.sets)-1]
#print(idx)
else: else:
raise Exception( ndata[k] ) raise Exception( ndata[k] )
#print(idx)
for kk in idx: for kk in idx:
flrg = hofts.HighOrderFLRG(self.order) flrg = hofts.HighOrderFLRG(self.order)
flrg.appendLHS(self.sets[ kk ]) flrg.appendLHS(self.sets[ kk ])
affected_flrgs.append( flrg ) affected_flrgs.append( flrg )
#print(mv[kk])
affected_flrgs_memberships.append(mv[kk]) affected_flrgs_memberships.append(mv[kk])
count = 0 count = 0
@ -186,7 +175,6 @@ class ProbabilisticIntervalFTS(ifts.IntervalFTS):
norm = sum(norms) norm = sum(norms)
if norm == 0: if norm == 0:
ret.append( [ 0, 0 ] ) ret.append( [ 0, 0 ] )
print("disparou")
else: else:
ret.append( [ sum(lo)/norm, sum(up)/norm ] ) ret.append( [ sum(lo)/norm, sum(up)/norm ] )
@ -194,12 +182,11 @@ class ProbabilisticIntervalFTS(ifts.IntervalFTS):
def forecastAhead(self,data,steps): def forecastAhead(self,data,steps):
ret = [[data[k],data[k]] for k in np.arange(len(data)-self.order,len(data))] ret = [[data[k],data[k]] for k in np.arange(len(data)-self.order,len(data))]
#print(ret)
for k in np.arange(self.order-1,steps): for k in np.arange(self.order-1,steps):
if ret[-1][0] <= self.sets[0].lower and ret[-1][1] >= self.sets[-1].upper: if ret[-1][0] <= self.sets[0].lower and ret[-1][1] >= self.sets[-1].upper:
ret.append(ret[-1]) ret.append(ret[-1])
#print("disparou")
else: else:
lower = self.forecast( [ret[x][0] for x in np.arange(k-self.order,k)] ) lower = self.forecast( [ret[x][0] for x in np.arange(k-self.order,k)] )
upper = self.forecast( [ret[x][1] for x in np.arange(k-self.order,k)] ) upper = self.forecast( [ret[x][1] for x in np.arange(k-self.order,k)] )