Small bugfix in GranularWMVFTS
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@ -44,9 +44,9 @@ class ClusteredMVFTS(mvfts.MVFTS):
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def train(self, data, **kwargs):
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def train(self, data, **kwargs):
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self.fts_params['order'] = self.order
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self.model = self.fts_method(partitioner=self.partitioner, **self.fts_params)
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self.model = self.fts_method(partitioner=self.partitioner, **self.fts_params)
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if self.model.is_high_order:
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self.model.order = self.order
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ndata = self.check_data(data)
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ndata = self.check_data(data)
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@ -21,6 +21,7 @@ class GranularWMVFTS(cmvfts.ClusteredMVFTS):
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def train(self, data, **kwargs):
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def train(self, data, **kwargs):
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self.partitioner = grid.IncrementalGridCluster(
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self.partitioner = grid.IncrementalGridCluster(
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explanatory_variables=self.explanatory_variables,
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explanatory_variables=self.explanatory_variables,
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target_variable=self.target_variable)
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target_variable=self.target_variable,
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neighbors=self.knn)
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super(GranularWMVFTS, self).train(data,**kwargs)
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super(GranularWMVFTS, self).train(data,**kwargs)
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@ -186,14 +186,13 @@ vavg = variable.Variable("Radiation", data_label="glo_avg", alias='rad',
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partitioner=Grid.GridPartitioner, npart=25, alpha_cut=.3,
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partitioner=Grid.GridPartitioner, npart=25, alpha_cut=.3,
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data=train)
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data=train)
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from pyFTS.models.multivariate import mvfts, wmvfts, cmvfts, grid
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from pyFTS.models.multivariate import mvfts, wmvfts, cmvfts, grid, granular
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fs = grid.GridCluster(explanatory_variables=[vmonth, vhour, vavg], target_variable=vavg)
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model = granular.GranularWMVFTS(explanatory_variables=[vmonth, vhour, vavg], target_variable=vavg,
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order=2, knn=7)
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model = cmvfts.ClusteredMVFTS(explanatory_variables=[vmonth, vhour, vavg], target_variable=vavg,
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partitioner=fs, knn=3)
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model.fit(train)
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model.fit(train)
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model.predict(test)
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print(model)
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#model.predict(test)
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