bugfix in Measures.get_point_statistics for supporting multivariate models
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@ -324,7 +324,9 @@ def get_point_statistics(data, model, **kwargs):
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if steps_ahead == 1:
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forecasts = model.predict(ndata, **kwargs)
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if model.is_multivariate:
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if model.is_multivariate and model.has_seasonality:
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ndata = model.indexer.get_data(ndata)
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elif model.is_multivariate:
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ndata = ndata[model.target_variable.data_label].values
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if not isinstance(forecasts, (list, np.ndarray)):
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@ -31,7 +31,15 @@ class SeasonalIndexer(object):
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class LinearSeasonalIndexer(SeasonalIndexer):
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"""Use the data array/list position to index the seasonality """
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def __init__(self, seasons, units, ignore=None, **kwargs):
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"""
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Indexer for array/list position
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:param seasons: A list with the season group (i.e: 7 for week, 30 for month, etc)
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:param units: A list with the units used for each season group, the default is 1 for each
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:param ignore:
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:param kwargs:
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"""
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super(LinearSeasonalIndexer, self).__init__(len(seasons), **kwargs)
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self.seasons = seasons
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self.units = units
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@ -81,11 +89,19 @@ class LinearSeasonalIndexer(SeasonalIndexer):
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class DataFrameSeasonalIndexer(SeasonalIndexer):
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def __init__(self,index_fields,index_seasons, data_fields,**kwargs):
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"""Use the Pandas.DataFrame index position to index the seasonality """
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def __init__(self,index_fields,index_seasons, data_field,**kwargs):
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"""
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:param index_fields: DataFrame field to use as index
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:param index_seasons: A list with the season group, i. e., multiples of positions that are considered a season (i.e: 7 for week, 30 for month, etc)
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:param data_fields: DataFrame field to use as data
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:param kwargs:
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"""
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super(DataFrameSeasonalIndexer, self).__init__(len(index_seasons), **kwargs)
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self.fields = index_fields
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self.seasons = index_seasons
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self.data_fields = data_fields
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self.data_field = data_field
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def get_season_of_data(self,data):
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#data = data.copy()
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@ -111,25 +127,34 @@ class DataFrameSeasonalIndexer(SeasonalIndexer):
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data = data[data[f]== season[c]]
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else:
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data = data[(data[f] // self.seasons[c]) == season[c]]
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return data[self.data_fields]
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return data[self.data_field]
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def get_index_by_season(self, indexes):
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raise Exception("Operation not available!")
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def get_data(self, data):
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return data[self.data_fields].tolist()
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return data[self.data_field].tolist()
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def set_data(self, data, value):
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data.loc[:,self.data_fields] = value
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data.loc[:,self.data_field] = value
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return data
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class DateTimeSeasonalIndexer(SeasonalIndexer):
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def __init__(self,date_field, index_fields, index_seasons, data_fields,**kwargs):
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"""Use a Pandas.DataFrame date field to index the seasonality """
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def __init__(self,date_field, index_fields, index_seasons, data_field,**kwargs):
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"""
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:param date_field: DataFrame field that contains the datetime field used on index
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:param index_fields: List with commom.DataTime fields
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:param index_seasons: Multiples of index_fields, the default is 1
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:param data_field: DataFrame field with the time series data
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:param kwargs:
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"""
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super(DateTimeSeasonalIndexer, self).__init__(len(index_seasons), **kwargs)
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self.fields = index_fields
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self.seasons = index_seasons
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self.data_fields = data_fields
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self.data_field = data_field
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self.date_field = date_field
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def get_season_of_data(self, data):
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@ -151,7 +176,7 @@ class DateTimeSeasonalIndexer(SeasonalIndexer):
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date = data[self.date_field]
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season = []
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for c, f in enumerate(self.fields, start=0):
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season.append(self.strip_datepart(date, f, self.seasons[c]))
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season.append(common.strip_datepart(date, f, self.seasons[c]))
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ret.append(season)
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return ret
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@ -166,10 +191,12 @@ class DateTimeSeasonalIndexer(SeasonalIndexer):
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raise Exception("Operation not available!")
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def get_data(self, data):
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return data[self.data_fields].tolist()
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return data[self.data_field].tolist()
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def get_index(self, data):
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return data[self.date_field].tolist() if isinstance(data, pd.DataFrame) else data[self.date_field]
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def set_data(self, data, value):
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raise Exception("Operation not available!")
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raise Exception("Operation not available!")
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