adaptação da FTS para receber métodos de transformação multivariada
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@ -15,6 +15,8 @@ class Transformation(object):
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def __init__(self, **kwargs):
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self.is_invertible = True
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self.is_multivariate = False
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"""detemine if this transformation can be applied to multivariate data"""
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self.minimal_length = 1
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self.name = ''
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@ -18,6 +18,7 @@ class SOMTransformation(Transformation):
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self.data: pd.DataFrame = None
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self.grid_dimension: Tuple = grid_dimension
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self.pbc = kwargs.get('PBC', True)
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self.is_multivariate = True
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# debug attributes
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self.name = 'Kohonen Self Organizing Maps FTS'
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@ -25,8 +26,6 @@ class SOMTransformation(Transformation):
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def apply(self,
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data: pd.DataFrame,
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endogen_variable=None,
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names: Tuple[str] = ('x', 'y'),
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param=None,
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**kwargs):
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"""
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@ -45,6 +44,9 @@ class SOMTransformation(Transformation):
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"""
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endogen_variable = kwargs.get('endogen_variable', None)
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names = kwargs.get('names', ('x', 'y'))
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if endogen_variable not in data.columns:
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endogen_variable = None
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cols = data.columns[:-1] if endogen_variable is None else [col for col in data.columns if
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@ -35,6 +35,12 @@ class MVFTS(fts.FTS):
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self.name = "Multivariate FTS"
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self.uod_clip = False
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def append_transformation(self, transformation, **kwargs):
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if not transformation.is_multivariate:
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raise Exception('The transformation is not multivariate')
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self.transformations.append(transformation)
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self.transformations_param.append(kwargs)
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def append_variable(self, var):
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"""
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Append a new endogenous variable to the model
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@ -53,6 +59,9 @@ class MVFTS(fts.FTS):
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def apply_transformations(self, data, params=None, updateUoD=False, **kwargs):
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ndata = data.copy(deep=True)
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for ct, transformation in enumerate(self.transformations):
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ndata = transformation.apply(ndata, **self.transformations_param[ct])
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for var in self.explanatory_variables:
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try:
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values = ndata[var.data_label].values #if isinstance(ndata, pd.DataFrame) else ndata[var.data_label]
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