ba1b4fbae6
- Otimização do GridPartitioner - Correção na geração de PFLRG's em PFTS - Métodos de __str__ mais intuitivos
60 lines
1.4 KiB
Python
60 lines
1.4 KiB
Python
import numpy as np
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from pyFTS import *
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class FTS:
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def __init__(self, order, name):
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self.sets = {}
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self.flrgs = {}
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self.order = order
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self.shortname = name
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self.name = name
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self.detail = name
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self.hasSeasonality = False
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self.hasPointForecasting = True
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self.hasIntervalForecasting = False
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self.hasDistributionForecasting = False
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self.dump = False
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def fuzzy(self, data):
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best = {"fuzzyset": "", "membership": 0.0}
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for f in self.sets:
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fset = self.sets[f]
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if best["membership"] <= fset.membership(data):
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best["fuzzyset"] = fset.name
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best["membership"] = fset.membership(data)
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return best
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def forecast(self, data):
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pass
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def forecastInterval(self, data):
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pass
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def forecastDistribution(self, data):
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pass
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def forecastAhead(self, data, steps):
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pass
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def forecastAheadInterval(self, data, steps):
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pass
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def forecastAheadDistribution(self, data, steps):
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pass
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def train(self, data, sets):
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pass
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def getMidpoints(self, flrg):
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ret = np.array([s.centroid for s in flrg.RHS])
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return ret
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def __str__(self):
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tmp = self.name + ":\n"
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for r in sorted(self.flrgs):
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tmp = tmp + str(self.flrgs[r]) + "\n"
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return tmp
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