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)
