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github.com/unit8co/darts
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Functions
3,734 in github.com/unit8co/darts
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Functions
3,734
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Types & classes
510
↳
Endpoints
59
Method
__iter__
Returns ------- Iterator Iterator on sequence of data transformers
darts/dataprocessing/pipeline.py:311
Method
__iter__
(self)
darts/dataprocessing/dtw/cost_matrix.py:89
Method
__iter__
(self)
darts/dataprocessing/dtw/cost_matrix.py:161
Method
__iter__
Returns ------- Iterator Iterate over all active cells in the window, yielding (i,j) tuple. Expected
darts/dataprocessing/dtw/window.py:83
Method
__iter__
(self)
darts/dataprocessing/dtw/window.py:115
Method
__iter__
(self)
darts/dataprocessing/dtw/window.py:246
Method
__le__
(self, other)
darts/timeseries.py:5512
Method
__len__
(self)
darts/timeseries.py:5369
Method
__len__
(self)
darts/dataprocessing/pipeline.py:320
Method
__len__
(self)
darts/dataprocessing/dtw/window.py:34
Method
__len__
(self)
darts/dataprocessing/dtw/window.py:100
Method
__len__
(self)
darts/dataprocessing/dtw/window.py:261
Method
__len__
(self)
darts/utils/model_selection.py:149
Method
__len__
(self)
darts/utils/data/torch_datasets/inference_dataset.py:207
Method
__len__
The total number of samples that can be extracted.
darts/utils/data/torch_datasets/dataset.py:37
Method
__len__
(self)
darts/utils/data/torch_datasets/training_dataset.py:212
Method
__len__
(self)
darts/models/forecasting/forecasting_model.py:1548
Method
__lt__
(self, other)
darts/timeseries.py:5488
Method
__lt__
(self, other)
darts/utils/ts_utils.py:40
Method
__mul__
(self, other)
darts/timeseries.py:5406
Method
__ne__
(self, other)
darts/timeseries.py:5366
Method
__neg__
(self)
darts/timeseries.py:5475
Method
__new__
(self, n, m)
darts/dataprocessing/dtw/cost_matrix.py:81
Method
__pow__
(self, n)
darts/timeseries.py:5423
Method
__radd__
(self, other)
darts/timeseries.py:5386
Method
__repr__
(self)
darts/timeseries.py:5553
Method
__repr__
(self)
darts/dataprocessing/transformers/base_data_transformer.py:727
Method
__repr__
(self)
darts/utils/likelihood_models/base.py:121
Method
__repr__
Get full description for this estimator (includes all params).
darts/models/forecasting/forecasting_model.py:2776
Method
__rmul__
(self, other)
darts/timeseries.py:5420
Method
__round__
(self, n=None)
darts/timeseries.py:5483
Method
__rsub__
(self, other)
darts/timeseries.py:5403
Method
__rtruediv__
(self, n)
darts/timeseries.py:5467
Method
__setitem__
(self, key, value)
darts/dataprocessing/dtw/cost_matrix.py:37
Method
__setitem__
(self, elem, value)
darts/dataprocessing/dtw/cost_matrix.py:154
Method
__setstate__
(self, d)
darts/models/forecasting/torch_forecasting_model.py:2819
Method
__sklearn_tags__
(self)
darts/tests/models/forecasting/test_classifier_model.py:1117
Method
__sklearn_tags__
(self)
darts/tests/models/forecasting/test_classifier_model.py:1191
Method
__str__
(self)
darts/timeseries.py:5536
Method
__str__
(self)
darts/ad/scorers/kmeans_scorer.py:127
Method
__str__
(self)
darts/ad/scorers/nll_gamma_scorer.py:32
Method
__str__
(self)
darts/ad/scorers/difference_scorer.py:20
Method
__str__
(self)
darts/ad/scorers/wasserstein_scorer.py:136
Method
__str__
(self)
darts/ad/scorers/nll_cauchy_scorer.py:22
Method
__str__
(self)
darts/ad/scorers/pyod_scorer.py:118
Method
__str__
(self)
darts/ad/scorers/nll_gaussian_scorer.py:32
Method
__str__
(self)
darts/ad/scorers/norm_scorer.py:52
Method
__str__
(self)
darts/ad/scorers/nll_laplace_scorer.py:32
Method
__str__
(self)
darts/ad/scorers/nll_exponential_scorer.py:32
Method
__str__
returns the name of the scorer
darts/ad/scorers/scorers.py:254
Method
__str__
(self)
darts/ad/scorers/nll_poisson_scorer.py:32
Method
__str__
(self)
darts/ad/aggregators/or_aggregator.py:30
Method
__str__
(self)
darts/ad/aggregators/and_aggregator.py:29
Method
__str__
(self)
darts/ad/aggregators/ensemble_sklearn_aggregator.py:37
Method
__str__
(self)
darts/models/forecasting/sklearn_model.py:1506
Method
__str__
Get short description for this estimator (only includes params with non-default values).
darts/models/forecasting/forecasting_model.py:2782
Method
__str__
(self)
darts/models/forecasting/baselines.py:219
Method
__str__
(self)
darts/models/filtering/kalman_filter.py:71
Method
__sub__
(self, other)
darts/timeseries.py:5389
Method
__truediv__
(self, other)
darts/timeseries.py:5444
Method
_add_val_set_to_kwargs
( self, kwargs: dict, val_series: Sequence[TimeSeries], val_past_covariates: S
darts/models/forecasting/catboost_model.py:407
Method
_apply_interval
(self, pred: np.ndarray, q_hat: tuple[np.ndarray, np.ndarray])
darts/models/forecasting/conformal_models.py:1707
Method
_apply_interval
(self, pred: np.ndarray, q_hat: tuple[np.ndarray, np.ndarray])
darts/models/forecasting/conformal_models.py:1863
Method
_apply_promo_mechanism
(promo_mechanism)
darts/tests/models/forecasting/test_sklearn_models.py:398
Method
_assert_comps
(comp, comps)
darts/tests/dataprocessing/transformers/test_reconciliation.py:71
Method
_batch_collate_fn
Returns a batch Tuple from a list of samples
darts/models/forecasting/torch_forecasting_model.py:2024
Function
_benchmark_dtw
()
darts/tests/dataprocessing/dtw/test_dtw.py:246
Function
_build_classification_metrics
()
darts/metrics/__init__.py:234
Method
_build_explainer
( self, model: SKLearnModel, background_arr: np.ndarray, shap_method: SHAPMeth
darts/explainability/shap_adapters/sklearn_shap_adapter.py:69
Method
_build_explainer
Builds the SHAP explainer based on the specified SHAP method. Parameters ---------- func The function wr
darts/explainability/shap_adapters/torch_shap_adapter.py:138
Method
_build_feature_names
(self)
darts/explainability/shap_adapters/sklearn_shap_adapter.py:200
Method
_build_feature_names
(self)
darts/explainability/shap_adapters/torch_shap_adapter.py:122
Function
_build_time_dependent_metrics
()
darts/metrics/__init__.py:229
Method
_build_train_dataset
( self, series: Sequence[TimeSeries], past_covariates: Sequence[TimeSeries] | None,
darts/models/forecasting/tcn_model.py:543
Method
_build_train_dataset
( self, series: Sequence[TimeSeries], past_covariates: Sequence[TimeSeries] | None,
darts/models/forecasting/tft_model.py:1171
Method
_build_train_dataset
( self, series: Sequence[TimeSeries], past_covariates: Sequence[TimeSeries] | None,
darts/models/forecasting/global_baseline_models.py:242
Method
_calibrate_interval
( self, residuals: np.ndarray )
darts/models/forecasting/conformal_models.py:1682
Method
_calibrate_interval
( self, residuals: np.ndarray )
darts/models/forecasting/conformal_models.py:1827
Method
_categorical_fit_param
Returns the name of the categorical features parameter from model's `fit` method .
darts/models/forecasting/sklearn_model.py:1940
Method
_categorical_fit_param
Returns the name of the categorical features parameter from model's `fit` method .
darts/models/forecasting/catboost_model.py:461
Method
_categorical_fit_param
Returns the name of the categorical features parameter from model's `fit` method .
darts/models/forecasting/lgbm.py:368
Method
_check_ckpt_parameters
(self, tfm_save)
darts/models/forecasting/block_rnn_model.py:578
Method
_check_ckpt_parameters
(self, tfm_save)
darts/models/forecasting/tide_model.py:730
Method
_check_dt
()
darts/timeseries.py:5681
Method
_check_optimizable_historical_forecasts
Historical forecast can be optimized if no re-training is involved
darts/models/forecasting/sklearn_model.py:1544
Method
_check_optimizable_historical_forecasts
Historical forecast can be optimized if no re-training is involved
darts/models/forecasting/torch_forecasting_model.py:2592
Method
_check_plot
(n_figs_expected, n_axes_expected, **kwargs)
darts/tests/explainability/test_tft_explainer.py:439
Method
_check_range
()
darts/timeseries.py:5691
Method
_check_sizes
(tup, name)
darts/models/forecasting/nhits.py:770
Method
_check_univariate
Checks if `anomalies` contains only univariate series, which is required if any of the scorers returns a univariate score.
darts/ad/scorers/scorers.py:279
Method
_check_univariate
Checks if `anomalies` contains only univariate series, which is required if any of the scorers returns a univariate score.
darts/ad/anomaly_model/anomaly_model.py:170
Method
_clean
Returns a cleaned instance of the model by removing the training series and covariates.
darts/models/forecasting/forecasting_model.py:3179
Method
_clean
Cleans the model and sub-models.
darts/models/forecasting/ensemble_model.py:534
Method
_clean
Cleans the model and sub-model.
darts/models/forecasting/conformal_models.py:1373
Method
_compononents_and
(s: TimeSeries)
darts/ad/aggregators/and_aggregator.py:35
Method
_compononents_or
(s: TimeSeries)
darts/ad/aggregators/or_aggregator.py:36
Method
_compute_diff
(values_: np.ndarray, times_)
darts/timeseries.py:3016
Method
_compute_loss
(self, output, target, criterion, sample_weight)
darts/models/forecasting/tirex_model.py:125
Method
_compute_loss
(self, output, target, criterion, sample_weight)
darts/models/forecasting/timesfm2p5_model.py:338
Method
_compute_loss
(self, output, target, criterion, sample_weight)
darts/models/forecasting/chronos2_model.py:571
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