Update from unit8co/darts. #11
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…2218) * add support for more lr scheduler config parameters to torch models * update changelog
* update dev requirements with new pre commit hook lint dependency versions * black reformatting * fix flake8 checks
* fix: append/prepend correctul retain components names and hierarchy * updated changelog * fix: revert unecessary change * update changelog --------- Co-authored-by: dennisbader <dennis.bader@gmx.ch>
* fix: update hierarchy for single transform window_transform * update changelog * update changelog * fix: using set to check overlap * fix: corrected logic to update the hierarchy after window_transform * fix: hierarchy can be conserved when applying non-overlapping transforms * feat: add new argument, improve logic * feat: adding tests * fix: expected argument match docstring in resample() * fix: addressing review comments * fix: linting issue * fix: linting * linting * update changelog and remane keep_old_names to keep_names --------- Co-authored-by: dennisbader <dennis.bader@gmx.ch>
* remove pytorch lightning upper version cap * fix failing unit test and update changelog
…rror (#2222) * fix: arguments must be provided to model cls in order to check presence of the fitted_values attribute * fix: added a check that parameters is indeed a dict * updated changelog * fix: update test to pass the new sanity checks * fix: addressing review comments --------- Co-authored-by: Dennis Bader <dennis.bader@gmx.ch>
* Change default kwarg * Update CHANGELOG.md --------- Co-authored-by: Dennis Bader <dennis.bader@gmx.ch>
* add output chunk shift to lightning modeuls * training torch model with shifted output * first shifted output inference works for mixed covariates models * full covariateds support for shifted mixed covariates dataset * add shift support to all torch models * update torch model extreme lags with shift * update torch model encoder settings with shift * update torch model encoder settings with shift * add unit test for shifted torch mmodel with encoders * add unit tests for tft model * add unit tests for all torch models * update output_chunk_shift description * apply suggestions from PR review * add output chunk shift to extreme lags * udpate historical forecasts to work with shifted output * update historical forecasts start description for shifted output * apply suggestions from PR review * prepare regression models for output chunk shift * fix failing unit tests * prepare regression models for output chunk shift part 2 * update hist fc for regression models with output shift * update tabularization * add test for comparing results between output shift and normal multi models * historical forecasts for shifted regression models * update tabularization training tests * update tabulirazion get feature times tests * update tabularization get shared times tests * update tabularization get shared bounds tests * update tabularization get lagged prediction data tests * add tests for tabularization without target lags but only covariate lags * update n_steps_between docs * update changelog * add unit tests for inference datasets * add unit tests for sequential training datasts * update changelog * make ocs property non optional * skip output_chunk_shift checks when loading weights since not relevant for parameter shape * apply suggestions from PR review
…#2242) * fix: datetime_attribute account for 0 or 1-indexing of the attributes * feat: 1-indexed date attribute are shifted to enforce 0-indexing for all the generated encodings * updated changelog * fix: remove commented lines * fix: typo in comment * make ONE_INDEXED_FREQS a constant * fix: simplified test by using year 2001 * feat: better handling of years with 53 weeks or 366 days * fix: properly take the index length when adding the extra week * fix: simplifying test * fix: update tests to account for the forced 0-indexing of the datetime attributes encoding * fix: passing lmbda parameter as BoxCox doesn't converge when encodings contains a 0 --------- Co-authored-by: Dennis Bader <dennis.bader@gmx.ch>
* feat: adding docstring and check to get_multioutput_estimator * fix: added lowbound check * fix: update docstring, indexing account for multi_models param * feat: added corresponding test * feat: added tests for estimator getter * feat: store and expose the lagged label names (for each model estimator) * fix: rephrasing docstring * update changelog * fix: linting * fix: replaced ocl with hrz in naming of the lagged label * fix: update error messages * feat: simplify test, overfit XGB on only one training example * feat: added a method to get estimator for models supporting multi-output natively * feat: added corresponding test * update changelog * fix: linting * Update CHANGELOG.md --------- Co-authored-by: Dennis Bader <dennis.bader@gmx.ch>
* update changelog * bump u8darts 0.27.2 to 0.28.0 * update changelog
* update code owners * udpated PR template
* Remove unnessesary `pass` statements * Rename ForecastingModel_is_probabilistic to supports_probabilistic_prediction, rearrange some documentation * Remove redundant overrides * Reformat * Add CHANGELOG entry --------- Co-authored-by: Dennis Bader <dennis.bader@gmx.ch>
* fix type hinting for _with_sanity_checks * update changelog
* Add optional inverse transform in historical forecast * Update variables names and docstrings * Move the inverse transform to InvertibleDataTransformer * Fix single element list * Update docstrings * Move the inverse transform of list of lists to inverse_transform method * make invertible transformers act on list of lists of series * add tests * update changelog --------- Co-authored-by: dennisbader <dennis.bader@gmx.ch>
* lxml_html_clean for nbshinx * update changelog
* fix lighgbm segmentation fualt * update changelog * parameterize unit tests
* fix lighgbm segmentation fualt * update changelog * parameterize unit tests * make metric_kwargs metric specific rather than infereing which kwarg belongs to which metric * update hierarchical reconciliation notebook * fix failing residuals tests
* use pytest to skip torch tests * fix some mistakes in tsmixer notebook
* add TimesSeries.from_group_dataframe parallel mode * remove code mess * add doc string for new parameters * update CHANGELOG.md * add miss dtype * fix static covariates * make parallel function as local and fix tests * fix parallel utils imports * update changelog * Update CHANGELOG.md --------- Co-authored-by: Bohdan Bilonoh <bilonogo@rozetka.ua> Co-authored-by: dennisbader <dennis.bader@gmx.ch>
* bump black[jupyter] 24.1.1 to 24.3.0 * update changeloig
…shift (#2647) * Add output_chunk_shift to summary_plot title * Update CHANGELOG.md * Update darts/explainability/shap_explainer.py Co-authored-by: Dennis Bader <dennis.bader@gmx.ch> --------- Co-authored-by: Dennis Bader <dennis.bader@gmx.ch>
* Add a function to find the intersection of multiple time series * Add empty sequence treatment. * Used logic of slice_intersect for faster code. * Improved complexity of slice_intersect. * Intersect times indexes to avoid creating new TimeSeries for optimization purposes. * Add early exit in case of empty intersection. * Modified slice_intersect for empty TimeSeries treatment. * Added an entry in the changelog. * last updates for pr --------- Co-authored-by: madtoinou <32447896+madtoinou@users.noreply.github.com> Co-authored-by: dennisbader <dennis.bader@gmx.ch>
* Add agg/fill methods for resampling timeseries * Update CHANGELOG.md * Add test points and comments * Format tests * Add test for unknown method * fix typo * Add method_kwargs as resample arg, move supported list into utils * Update darts/timeseries.py Co-authored-by: Dennis Bader <dennis.bader@gmx.ch> * Update darts/timeseries.py Co-authored-by: Dennis Bader <dennis.bader@gmx.ch> * Update resample docstring * Fix typo * last updates for pr * update changelog --------- Co-authored-by: jonasblanc <jonas.blanc@unit8.co> Co-authored-by: Jonas Blanc <44334351+jonasblanc@users.noreply.github.com> Co-authored-by: madtoinou <32447896+madtoinou@users.noreply.github.com>
* Add metric wmape * Update CHANGELOG * Fix wmape * Update test_metrics * Fix wmape and add test of wmape * Update test_metrics.py * Update darts/metrics/metrics.py Co-authored-by: Dennis Bader <dennis.bader@gmx.ch> * Update CHANGELOG.md Co-authored-by: Dennis Bader <dennis.bader@gmx.ch> * Update darts/metrics/__init__.py Co-authored-by: Dennis Bader <dennis.bader@gmx.ch> --------- Co-authored-by: Dennis Bader <dennis.bader@gmx.ch>
… output_chunk_shift>0 (#2655) * if clause modified to correct bug * contribution added to changelog * implemented modifications from reviewer * unit tests added --------- Co-authored-by: “authierj” <“jules.authier@unit8.co”>
…r GlobalForecastingModel (#2649) * Add option to drop training_series during save() for GlobalForecastingModel * Update error on predict with no training series, update tests * Update CHANGELOG.md * Add _clean fonction to get a cleaned instance of the models * Use shallow copy to get clean model * Update darts/models/forecasting/regression_model.py Co-authored-by: Dennis Bader <dennis.bader@gmx.ch> * Update darts/models/forecasting/torch_forecasting_model.py Co-authored-by: Dennis Bader <dennis.bader@gmx.ch> * Define _clean() in ForecastingModel * Fix typo in docstring Co-authored-by: Dennis Bader <dennis.bader@gmx.ch> * Reformulate comment Co-authored-by: Dennis Bader <dennis.bader@gmx.ch> * Update CHANGELOG.md Co-authored-by: Dennis Bader <dennis.bader@gmx.ch> * Add clean argument in model.save for conformal and ensemble models * Update docstring * Remove additional training params on clean, update tests * Fix _clean and save logic, update save/load test * Update darts/models/forecasting/forecasting_model.py Co-authored-by: Dennis Bader <dennis.bader@gmx.ch> * Remove map_location on model load, set cpu as default accelerator * Update CHANGELOG.md * Add covariate to save/load test * Update CHANGELOG.md * Add _clean() to clean sub-model, update unit tests * Add _clean() to clean sub-models, update unit tests * minor refactor * further upadtes * pickle tfm model wrapper instead of torch save / load * update changelog * last fix --------- Co-authored-by: Dennis Bader <dennis.bader@gmx.ch>
* convert some supports_* methods to properties * update changelog * fix failing tests
* relax sklearn upper version cap * update changelog * fix failing tests for sklearn>=1.6.0
* Bump jinja2 from 3.1.4 to 3.1.5 in /requirements Bumps [jinja2](https://github.com/pallets/jinja) from 3.1.4 to 3.1.5. - [Release notes](https://github.com/pallets/jinja/releases) - [Changelog](https://github.com/pallets/jinja/blob/main/CHANGES.rst) - [Commits](pallets/jinja@3.1.4...3.1.5) --- updated-dependencies: - dependency-name: jinja2 dependency-type: direct:production ... Signed-off-by: dependabot[bot] <support@github.com> * Update CHANGELOG.md --------- Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> Co-authored-by: Dennis Bader <dennis.bader@gmx.ch>
* update window anomaly scorer docs * update changelog * Update CHANGELOG.md
…#2626) * Fix/val_sample_weight error for models inherited from RegressionModel * modify change log * modify the statement * update changelog * add unit tests * Update CHANGELOG.md --------- Co-authored-by: madtoinou <32447896+madtoinou@users.noreply.github.com> Co-authored-by: dennisbader <dennis.bader@gmx.ch>
* bump u8darts 0.32.0 to 0.33.0 * update changelog
* remove untrained_model from autodoc exclude-members * update changelog and untrained_model docs --------- Co-authored-by: dennisbader <dennis.bader@gmx.ch>
* feat: wrapping around pl.to_onnx to export models to ONNX, still require testing * feat: cleaned implementation of the to_onnx method * fix: generation of input name, shape of input_batch for PastCov torch module * feat: adding example of onnx usage in userguide * update changelog * fix: revert some changes * fix: export to onnx for RNNModel * feat: added a comment about RNNModel for onnx inference * update changelog * fix: address review comments * update changelog * update torch user guide * update to_onnx --------- Co-authored-by: dennisbader <dennis.bader@gmx.ch>
* fix python path if working locally * changelog updated * Update CHANGELOG.md --------- Co-authored-by: Dennis Bader <dennis.bader@gmx.ch>
Co-authored-by: Dennis Bader <dennis.bader@gmx.ch>
* colors arg added, accept lists of length num_comp * color or c in kwargs * check added * changelog entry added * refactoring after discussion with Dennis * CHANGELOG changed Co-authored-by: Dennis Bader <dennis.bader@gmx.ch> * custom_colors instead of multi_color Co-authored-by: Dennis Bader <dennis.bader@gmx.ch> * logic check upgraded Co-authored-by: Dennis Bader <dennis.bader@gmx.ch> * doc corrected * spelling Co-authored-by: Dennis Bader <dennis.bader@gmx.ch> * change of logic Co-authored-by: Dennis Bader <dennis.bader@gmx.ch> * change of logic follow-up Co-authored-by: Dennis Bader <dennis.bader@gmx.ch> * alpha moved to arguments, error if color and c are used at the same time * update plotting --------- Co-authored-by: Dennis Bader <dennis.bader@gmx.ch> Co-authored-by: madtoinou <32447896+madtoinou@users.noreply.github.com>
…#2692) * revert back to saving and loading a TFM with torch rather than pickle * update changelog
…#2661) * narwhals implementation for and test benchmark * changes from MarcoGorelli incorporated * improvement thanks to reviewers * added comments about slow and fast parts of the code * using pandas index to avoid .to_list() * bug fix added * updated test script * narwhals timeseries added * from_series changed, names changed * changelog updated * small improvement * clean test scripts added * BUGFIX added for non_pandas df * tests added for polars df * polars and narwhals added to dependencies. Ideally, polars should be an optional dependency. * refactoring pd_series and pd_dataframe * removed test scripts from git repo * Update CHANGELOG.md Co-authored-by: Dennis Bader <dennis.bader@gmx.ch> * Update darts/timeseries.py Co-authored-by: Dennis Bader <dennis.bader@gmx.ch> * easy corrections applied * narwhals_test_time removed * Update requirements/core.txt Co-authored-by: Dennis Bader <dennis.bader@gmx.ch> * Update darts/timeseries.py Co-authored-by: Francesco Bruzzesi <42817048+FBruzzesi@users.noreply.github.com> * most corrections added * polars tests removed * tests corrected * Update darts/timeseries.py Co-authored-by: Dennis Bader <dennis.bader@gmx.ch> * Update darts/timeseries.py Co-authored-by: Dennis Bader <dennis.bader@gmx.ch> * no time_col, define one --------- Co-authored-by: “authierj” <“jules.authier@unit8.co”> Co-authored-by: Dennis Bader <dennis.bader@gmx.ch> Co-authored-by: Francesco Bruzzesi <42817048+FBruzzesi@users.noreply.github.com>
Bumps [jinja2](https://github.com/pallets/jinja) from 3.1.5 to 3.1.6. - [Release notes](https://github.com/pallets/jinja/releases) - [Changelog](https://github.com/pallets/jinja/blob/main/CHANGES.rst) - [Commits](pallets/jinja@3.1.5...3.1.6) --- updated-dependencies: - dependency-name: jinja2 dependency-type: direct:production ... Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
* Replace MultioutputRegressor by native multioutput from CastBoost, wip * Add _native_support_multioutput() to regression models, wip * Fix logic, replace RMSE with MultiRMSE when multioutput is required * Add entry to change log * Adapt shapexplainer test to support all native multioutput * Let user decide on native multioutput usage * Update CHANGELOG.md * Update CHANGELOG.md * Add recursive call for native multioutput * Add test for native multioutput support * Fix logic, only sklearn model should be passed to RegressionModel * Set loss_function in kwargs following model default * Fix SNM logic to be independant of MOR wrapper * Use __sklearn_tags__ instead of _get_tags as required in sklearn 1.7 * Update CHANGELOG.md * Minor rewriting * Remove logic for xboost<2.0.0 * minor updates --------- Co-authored-by: dennisbader <dennis.bader@gmx.ch>
…s series (#2710) * fix: bug when several static covariates have only one category * feat: added corresponding tests * update changelog * update changelog --------- Co-authored-by: dennisbader <dennis.bader@gmx.ch>
* feat: adding support for getting estimator based on quantile and associated tests * updated changelog * minor updates * fix: combined get_multioutput_estimator and get_estimator into a single method * fix: typo * update changelog * update changelog --------- Co-authored-by: dennisbader <dennis.bader@gmx.ch>
* notes * dennis note * trying a few things * seems to fix it * fix and tests * note removal * overlap_end taken into account * pr corrections * changelog updated * comment adpated * make optimized hfc work identically as non optimized * update changelog * update changelog --------- Co-authored-by: dennisbader <dennis.bader@gmx.ch>
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