def commit(self): self.Error.seasonal_decompose_fail.clear() data = self.data if not data or not self.selected: self.Outputs.time_series.send(data) return selected_subset = Timeseries( Domain(self.selected, source=data.domain), data) # FIXME: might not pass selected interpolation method with self.progressBar(len(self.selected)) as progress: try: adjusted_data = seasonal_decompose( selected_subset, self.DECOMPOSITION_MODELS[self.decomposition], self.n_periods, callback=lambda *_: progress.advance()) except ValueError as ex: self.Error.seasonal_decompose_fail(str(ex)) adjusted_data = None if adjusted_data is not None: ts = Timeseries(Timeseries.concatenate((data, adjusted_data))) ts.time_variable = data.time_variable else: ts = None self.Outputs.time_series.send(ts)
def commit(self): data = self.data if not data or not self.selected: self.send(Output.TIMESERIES, data) return selected_subset = Timeseries(Domain(self.selected, source=data.domain), data) # FIXME: might not pass selected interpolation method with self.progressBar(len(self.selected)) as progress: adjusted_data = seasonal_decompose( selected_subset, self.DECOMPOSITION_MODELS[self.decomposition], self.n_periods, callback=lambda *_: progress.advance()) ts = Timeseries(Timeseries.concatenate((data, adjusted_data))) ts.time_variable = data.time_variable self.send(Output.TIMESERIES, ts)