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Bug fix - correct for multiple lengths of series in input sequence when adding static covariates to regression models #1469

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merged 13 commits into from Jan 10, 2023
Merged

Bug fix - correct for multiple lengths of series in input sequence when adding static covariates to regression models #1469

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c931b91
corrects for case where input sequence contains series of different l…
eliane-maalouf Jan 5, 2023
79790cb
improved doc string
eliane-maalouf Jan 5, 2023
73cfd9a
Merge branch 'master' into 1460-bug-static-covariates-error-when-trai…
eliane-maalouf Jan 5, 2023
636092d
improved doc string
eliane-maalouf Jan 5, 2023
62725a9
Merge remote-tracking branch 'origin/1460-bug-static-covariates-error…
eliane-maalouf Jan 5, 2023
a3d2f8f
removed print
eliane-maalouf Jan 6, 2023
77e4d31
Merge branch 'master' into 1460-bug-static-covariates-error-when-trai…
hrzn Jan 8, 2023
c65e8cb
changed map name
eliane-maalouf Jan 8, 2023
d3740ec
controlled for the order of the static covariates
eliane-maalouf Jan 8, 2023
6b338f9
controlled for the order of the static covariates
eliane-maalouf Jan 9, 2023
429b2de
corrected old tests
eliane-maalouf Jan 9, 2023
f9a9f27
force copy
eliane-maalouf Jan 9, 2023
50fe7aa
added test with different series sizes
eliane-maalouf Jan 9, 2023
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18 changes: 16 additions & 2 deletions darts/models/forecasting/regression_model.py
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Expand Up @@ -337,7 +337,13 @@ def _create_lagged_data(
)

training_samples = _add_static_covariates(
self.model, target_series, training_samples
self,
training_samples,
target_series,
*self.extreme_lags,
past_covariates=past_covariates,
future_covariates=future_covariates,
max_samples_per_ts=max_samples_per_ts,
)

return training_samples, training_labels
Expand Down Expand Up @@ -675,7 +681,15 @@ def predict(

# concatenate retrieved lags
X = np.concatenate(np_X, axis=1)
X = _add_static_covariates(self.model, series, X)
X = _add_static_covariates(
self,
X,
series,
*self.extreme_lags,
past_covariates=past_covariates,
future_covariates=future_covariates,
max_samples_per_ts=1,
)

# X has shape (n_series * n_samples, n_regression_features)
prediction = self._predict_and_sample(X, num_samples, **kwargs)
Expand Down