Merge branch 'master' of https://github.com/petroniocandido/pyFTS
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commit
52544aca88
@ -19,6 +19,10 @@ class HighOrderFTS(fts.FTS):
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self.detail = "Hwang"
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self.detail = "Hwang"
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def forecast(self, ndata, **kwargs):
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def forecast(self, ndata, **kwargs):
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if 'order' in kwargs:
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self.order = kwargs.get('order',self.order)
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self.max_lag = self.order
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if self.sets == None:
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if self.sets == None:
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self.sets = self.partitioner.sets
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self.sets = self.partitioner.sets
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@ -57,4 +61,4 @@ class HighOrderFTS(fts.FTS):
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return ret
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return ret
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def train(self, data, **kwargs):
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def train(self, data, **kwargs):
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pass
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pass
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@ -81,14 +81,18 @@ class ContextualMultiSeasonalFTS(sfts.SeasonalFTS):
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ndata = self.indexer.get_data(data)
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ndata = self.indexer.get_data(data)
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for k in np.arange(0, len(data)):
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for k in np.arange(0, len(data)):
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if str(index[k]) in self.flrgs:
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flrg = self.flrgs[str(index[k])]
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flrg = self.flrgs[str(index[k])]
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d = FuzzySet.get_fuzzysets(ndata[k], self.sets, ordered_sets, alpha_cut=self.alpha_cut)
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d = FuzzySet.get_fuzzysets(ndata[k], self.sets, ordered_sets, alpha_cut=self.alpha_cut)
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mp = self.get_midpoints(flrg, d)
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mp = self.get_midpoints(flrg, d)
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ret.append(sum(mp) / len(mp))
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ret.append(sum(mp) / len(mp))
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else:
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ret.append(np.nan)
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return ret
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return ret
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