Releases: etna-team/etna
Releases · etna-team/etna
etna 2.6.0
Highlights
- Add ability to work with integer timestamp by using
freq=None
- Add tutorial about working with misaligned data by using integer timestamp
- Add
TSDataset.create_from_misaligned
constructor - Add
infer_alignment
,apply_alignment
,make_timestamp_df
utils intoetna.dataset
- Add
BinaryOperationTransform
- Add
TFTNativeModel
- Add in
OutliersTransform
possibilities useignore_flag_column
to skip values use ignore - Extend base
TSDataset
constructor to handle long format dataframes - Speed up timestamp transforms
- Update timestamp transforms to work with external timestamp by using
in_column
parameter
Full changelog
Added
- Add
BinaryOperationTransform
to transforms (#260) - Add
TFTNativeModel
(#290) - Add warning on trying to pass numeric timestamp if freq is not None and add
_cast_index_to_datetime
(#214) - Add
infer_alignment
,apply_alignment
,make_timestamp_df
intoetna.dataset.utils
(#256) - Add
TSDataset.create_from_misaligned
constructor (#269) - Add tutorial about working with misaligned data (#288)
- Add in
OutliersTransform
possibilities useignore_flag_column
to skip values use ignore (#291)
Changed
- Update glossary with terms related to working with misaligned data (#288)
- Add ignoring of integer timestamp as a feature into native DL models (#210)
- Update
pytorch_forecasting
models to handle integer timestamp (#208) - Update
datasets
module to work with integer timestamp (#146) - Add tests for
transform
on data with integer timestamp (#153) - Add tests for
models
on data with integer timestamp (#188) - Update
DateFlagsTransform
,TimeFlagsTransform
,HolidayTransform
,SpecialDaysTransform
,FourierTransform
to work with external timestamp (#169) - Update
analysis
module to work with integer timestamp (#161) - Update
StatsForecastARIMAModel
,StatsForecastAutoARIMAModel
,StatsForecastAutoCESModel
,StatsForecastAutoETSModel
,StatsForecastAutoThetaModel
to handle integer timestamp (#197) - Update
MRMRFeatureSelectionTransform
to handle integer timestamp (#164) - Update deseasonality transforms (
STLTransform
,DeseasonalityTransform
) to handle integer timestamp (#174) - Update
HoltModel
,HoltWintersModel
,SimpleExpSmoothingModel
,SARIMAXModel
,AutoARIMAModel
to handle integer timestamp ((#200)[https://github.com//pull/200]) - Update detrend transforms (
LinearTrendTransform
,TheilSenTrendTransform
) to handle integer timestamp (#163) - Update
ResampleWithDistributionTransform
to work with integer timestamp (#165) - Update change point transforms (
ChangePointsSegmentationTransform
,ChangePointsTrendTransform
,ChangePointsLevelTransform
,TrendTransform
) to handle integer timestamp (#176) - Update
BATSModel
,TBATSModel
models to work with integer timestamp (#195) - Update
ProphetModel
to handle external timestamp (#203) - Remove checking frequency in
timestamp_column
ofProphetModel
(#222) - Update
FourierTransform
to handle external datetime timestamp (#223) - Update
FoldMask
to work with integer timestamp, invalidate_on_dataset
method add validation on presence ofFoldMask
parameters ints.index
, add tests forFoldMask
(#226) - Fix
FourierTransform
on integer index, add inference tests (#230) - Update outliers transforms to handle integer timestamp (#229)
- Update pipelines to handle integer timestamp (#241)
- Add
timestamp_range
and refactor code with it (#244) - Update CLI to handle integer timestamp (#246)
- Update
ExogShiftTransform
to handle integer timestamp (#254) - Extend base
TSDataset
constructor to handle long format dataframes, update documentation and tutorials with this change (#266) - Update internal datasets to work with unaligned data (#292)
- Speed up "timestamp" transforms (#295
Fixed
- Fix
PredictionIntervalOutliersTransform
fails to work with created columns (#291) - Prohibit empty list value and duplication of
target_timestamps
parameter inFoldMask
(#226) - Fix
DeseasonalityTransform
fails to inverse transform short series (#174) - Fix indexing in
stl_plot
,plot_periodogram
,plot_holidays
,plot_backtest
,plot_backtest_interactive
,ResampleWithDistributionTransform
(#244) - Fix
DifferencingTransform
to handle integer timestamp on test (#244) - Fix
HolidayTransform
to handle integer timestamp indays_count
mode (#285)
etna 2.5.0
Highlights
- Add built-in datasets:
M3
,M4
,electricity
, etc. The full list can be viewed at the documentation. - Add new
mode="days_count"
toHolidayTransform
- Add method
size
toTSDataset
class - Optimize performance of
DensityOutliersTransform
- Fix method
to_dict
forSklearnPerSegmentModel
andSklearnMultiSegmentModel
- Add the
index_only
parameter to outlier analysis functions
Full changelog
Added
- Add
electricity
to internal datasets (#60) - Add
parts
argument toload_dataset
function (#79) - Add
M4
to internal datasets (#83) - Add
M3
to internal datasets (#91) - Add
traffic_2008
to internal datasets (#94) - Add
traffic_2015
to internal datasets (#100) - Add
tourism
to internal datasets (#120) - Add
weather
to internal datasets (#125) - Add
ETT
to internal datasets (#134) - Add
list_datasets
function (#145) - Add
IHEPC
to internal datasets (#150) - Add dataset integrity check using hash for internal datasets (#151)
- Create page about internal datasets in documentation (#175)
- Add usage example of internal datasets in
101-get_started.ipynb
and305-classification.ipynb
tutorials (#202) - Add new
mode="days_count"
toHolidayTransform
(#239) - Add size method to
TSDataset
class (#238) - Add the
index_only
parameter to outlier analysis functions for return type control (#231)
Changed
- Add
relevance_aggregation_mode
andredundancy_aggregation_mode
intoMRMRFeatureSelectionTransform.params_to_tune
(#212) - Optimized
DensityOutliersTransform
and removed_save_original_values
from outlier transforms (#231) - Update python to 3.10 in CI (#251)
Fixed
- Fix
traffic_2008
(128) - Fix number of segments in docs, column name for tourism dataset and change default save path (#206)
- Fix method
to_dict
forSklearnPerSegmentModel
andSklearnMultiSegmentModel
(#199) - Fix method
fit
forMRMRFeatureSelectionTransform
withredundancy_aggregation_mode
=median
(#212) - Fix method
predict_components
for_CatBoostAdapter
working incorrectly on shuffled columns (#227)
etna 2.4.0
Highlights
- Add module
etna.experimental.prediction_intervals
with new model-agnostic methods to generate prediction intervals - Add notebook about prediction intervals
- Add
DeepARNativeModel
- Optimize
TSDataset.to_hierarchical_dataset
,BasePipeline._validate_backtest_dataset
,datasets.utils.duplicate_data
Full changelog
Added
- Add
params_to_tune
forDeepStateModel
(#115) - Handle new functionality for prediction intervals in the
plot_forecast
(#130) - Add
get_historical_forecasts
to pipelines for forecast estimation at each fold on the historical dataset (#143) ConformalPredictionIntervals
method for prediction intervals estimation (#152)- Add
DeepARNativeModel
(#114) EmpiricalPredictionIntervals
method for prediction intervals estimation (#173)- Prediction intervals tutorial notebook (#189)
Changed
- Change warning condition on loading object saved under different library version (#31)
Fixed
etna 2.3.0
Highlights
- Add
LimitTransform
to forecast within limits - Add
EventTransform
to create features before and after the event - Add parameter
save_ts
to pipeline methodfit
- Rework building docker images to use
poetry.lock
to make them more stable - Add
quickstart
notebook - Rework
get_started
notebook - Add
mechanics_of_forecasting
notebook - Add code to generate new documentation
Full changelog
Added
- Handle prediction intervals similar to target components in
TSDataset
(#97) SavePredictionIntervalsMixin
for theBasePredictionIntervals
(#87)- Base class
BasePredictionIntervals
for prediction intervals into experimental module (#86) - Add
fit_params
parameter toetna.models.sarimax.SARIMAXModel
(#69) - Add
quickstart
notebook, addmechanics_of_forecasting
notebook (#1343) - Add gallery of tutorials divided by level (#46)
- Create documentation page with links to external resources (#44)
- Add documentation page with glossary of terms (#45)
- Add publishing into s3 for the latest documentation version (#50)
- Add publishing into s3 during release (#53)
- Add multiversion switcher into documentation (#55)
- Add error page into documentation (#57)
- Add
LimitTransform
(#63) - Add config for Codecov to control CI (#80)
- Add
EventTransform
(#78) NaiveVariancePredictionIntervals
method for prediction quantiles estimation (#109)- Update interval metrics to work with arbitrary interval bounds (#113)
Changed
- Refactored transform inversion logic in
Pipeline
forecast
method (#72) - Add parameter
save_ts
to pipeline methodfit
(#73) - Add installation page and notes about extensions into documentation of public classes (#1339)
- Merge User Guide and API sections in documentation, limit classes to show in API section (#1324)
- Unify example notebooks, rerun example notebooks (#1330)
- Rework
get_started
notebook (#1343) - Add missing classes from decomposition into API Reference, add modules into page titles in API Reference (#61)
- Update
CONTRIBUTING.md
with scenarios of documentation updates and release instruction (#77) - Set up sharding for running tests (#99)
- Rework saving DL models by separating saving model's hyperparameters and model's weights (#98)
- Deprecated
FutureMixin
(#58)
Fixed
- Fix
ResampleWithDistributionTransform
working with categorical columns (#82) TSDataset._hierarchical_structure_from_level_columns
to supportpandas>=1.4,<1.5
(#107)- Fix links from tinkoff-ai/etna to etna-team/etna (#47)
- Fix CI job
cron-delete-untagged-images
(#95) - Rendering table of contents in notebooks (#1343)
- Fix formatting of docstrings, fix links from netlify to docs.etna.ai (#62)
- Fix multiple warnings, revert catching warnings during testing (#105)
- Fix bug with
numpy.warnings
innumpy>=1.24
, rework building docker images to usepoetry.lock
(#116) - Fix name of steps in
publish
CI (#119)