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torchtime: Time series data sets for PyTorch

Darke, Philip

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

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

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
If you use this software, please cite it as below.
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Publication date:
April 8, 2022
DOI:
10.5281/zenodo.6425750

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Versions

Version v0.6.1 10.5281/zenodo.8032839 Jun 13, 2023
Version v0.6.0 10.5281/zenodo.8029992 Jun 12, 2023
Version v0.5.1 10.5281/zenodo.6957141 Mar 31, 2022
Version v0.5.0 10.5281/zenodo.6949670 Mar 31, 2022
Version v0.4.2 10.5281/zenodo.6803572 Mar 31, 2022
...
Version 0.2.0 10.5281/zenodo.6425750 Apr 8, 2022
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Cite all versions? You can cite all versions by using the DOI 10.5281/zenodo.6402406. This DOI represents all versions, and will always resolve to the latest one. Read more.

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