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CHANGELOG.md

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Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

Unreleased

0.6.1 - 2023-06-13

Fixed

  • Support for PyTorch 1.13.x to 2.0.x
  • GitHub Actions badge

0.6.0 - 2023-06-12

Added

  • Support for Python 3.10 and 3.11

Changed

  • Updated dependencies

0.5.1 - 2022-08-03

Changed

  • Adopt updated sktime version

0.5.0 - 2022-08-01

Added

  • "zero" value imputation
  • Download progress bars

Changed

  • One-hot encoded PhysioNet2012 ICUType channel
  • Updated pre-commit hooks

Fixed

  • overwrite_cache now re-downloads data
  • scikit-learn dependency

0.4.2 - 2022-07-06

Added

  • torchtime.data.PhysioNet2019Binary data set, a binary prediction variant of the PhysioNet 2019 challenge
  • SHA256 checksums to verify integrity of cached data
  • standardise argument to standarise data
  • overwrite_cache argument to update a cached data set
  • Impute a subset of channels using forward imputation with select argument
  • Progress bars for PhysioNet data set processing
  • Additional argument validation
  • Additional unit tests
  • Code copy button in documentation

Changed

  • Code refactor
  • Removed torchtime.data.TensorTimeSeriesDataset class
  • Removed downscale argument
  • override argument renamed channel_means
  • Download UEA/UCR data directly (not via sktime)
  • overwrite_cache argument to update cached data
  • Updated console messages
  • Rename cache directories
  • test directory renamed tests
  • Using MacOS runner for GitHub Actions
  • Updated tutorials with automated code testing
  • Updated documentation

Fixed

  • Continuous deployment

[0.4.1] - 2022-07-06

Release pulled

[0.4.0] - 2022-07-06

Release pulled

0.3.0 - 2022-04-25

Added

  • torchtime.data.PhysioNet2012 data set
  • PhysioNet and UEA/UCR unit tests
  • Utility function module
  • Better console messages

Changed

  • More efficient PhysioNet data set downscaling
  • Updated documentation

Fixed

  • Replace PhysioNet 2019 missing data indicator with NaN
  • Code coverage badge

0.2.0 - 2022-04-08

Added

  • impute argument to support missing data imputation using mean and forward imputation methods or a custom imputation function
  • downscale argument to reduce the size of data sets for testing/model development
  • torchtime.data.TensorTimeSeriesDataset class to create a data set from input tensors

Changed

  • Processed data are now cached in the .torchtime directory
  • train_split and val_split arguments are renamed train_prop and val_prop respectively
  • Introduced generic torchtime.data_TimeSeriesDataSet class behind the scenes - note training/validation/test data splits have changed for a given seed
  • torchtime.collate.packed_sequence now returns both X and y as a PackedSequence object
  • Expanded unit tests - note coverage is currently limited as PhysioNet2019 tests cannot be run under CI
  • Updated documentation

Fixed

  • Use float32/torch.float and int64/torch.long precision for all data sets
  • Shape of y data in PhysioNet2019 data
  • Bug when adding time delta channels without a missing data mask

0.1.1 - 2022-03-31

Added

  • Missing data simulation for UEA/UCR data sets
  • Support appending missing data masks and time delta channels
  • torchtime.collate.packed_sequence collate function
  • Documentation now includes a tutorial
  • Automated releases using GitHub Actions
  • DOI

Changed

  • Simplified training/validation/test split approach
  • Default file path for PhysioNet2019 data set is now data/physionet2019
  • Refactored torchtime.data to share utility functions across data classes
  • Expanded unit tests
  • Updated documentation

0.1.0 - 2022-03-28

First release to PyPi