v0.2.0

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