This release is the first release of SidechainNet that includes all intended functionality and data elements. Still, this repository is considered to be under development and is designed for research purposes only.
This version:
* fixes a handful of corner cases with regards to data parsing for the dataset itself (D-amino acids, non-standard amino acids, etc.),
* provides support for secondary structure and structure resolution information, (when available, and for training data only), and
* modifies the way data is batched when using the custom provided Dataloaders (i.e. `scn.load(...with_pytorch='dataloaders')`).
It is important to note that this release is **not completely backward compatible with prior releases** with respect to the manner in which items are yielded from Dataloaders during training. The SidechainNet datasets themselves have also been improved. Please see the updated [Colab Walkthrough](https://colab.research.google.com/drive/11ZZyqwfu7ZTyUKdqt9uy59AqqYccRVcU?usp=sharing) for updated usage examples.
In prior releases, Dataloaders yielded tuples that contained information for training such as ProteinNet/SidechainNet IDs, sequences, angles, etc. This required the user to know the exact order of the returned items. To make this easier, v0.2 uses Dataloaders that yield a single item for training, a `Batch` `collections.namedtuple` object. Please see the README for more information on accessing training information from the `namedtuple`.