def forecast(self, ndata, **kwargs):
if self.partitioner is not None:
ordered_sets = self.partitioner.ordered_sets
else:
ordered_sets = FuzzySet.set_ordered(self.partitioner.sets)
l = len(ndata)
npart = len(self.partitioner)
ret = []
for k in np.arange(0, l):
mv = FuzzySet.fuzzyfy_instance(ndata[k], self.partitioner.sets)
r = [max([ min(self.R[i][j], mv[j]) for j in np.arange(0,npart) ]) for i in np.arange(0,npart)]
fs = np.ravel(np.argwhere(r == max(r)))
if len(fs) == 1:
ret.append(self.partitioner.sets[ordered_sets[fs[0]]].centroid)
else:
mp = [self.partitioner.sets[ordered_sets[s]].centroid for s in fs]
ret.append( sum(mp)/len(mp))
return ret
def forecast(self, ndata, **kwargs):
l = len(ndata)
ret = []
for k in np.arange(0, l):
mv = FuzzySet.fuzzyfy_instance(ndata[k], self.sets)
actual = FuzzySet.get_maximum_membership_fuzzyset(
ndata[k],
self.sets) #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]
ret.append(_flrg.get_midpoint(self.sets))
return ret