v0.3.0 (mlcolvar)

First mlcolvar release

The library went through a complete refactoring (including being renamed from mlcvs to mlcolvar) with new structure and APIs.

Main changes

• Pytorch lightning support
• Modular CV structure
• Dict-like datasets
• Many new CVs methods

Pull requests

Only the recent changes are shown in this list:

• First implementation of a Variation Autoencoder CV by @andrrizzi in #27
• Change base cv attributes by @luigibonati in #32
• change MSE_loss signature from diff to input, target by @luigibonati in #37
• add option in ae/vae to compare output of the decoder with a different target by @luigibonati in #38
• Improve load_dataframe by @luigibonati in #41
• Implement Loss classes, some PEP8 fixes by @andrrizzi in #42
• Switch from functional to class losses by @andrrizzi in #43
• Add PCA method by @luigibonati in #44
• Support for multiple datasets by @andrrizzi in #45
• Added reduced_rank to TICA by @pietronvll in #36
• Multi-task CV and various fixes by @andrrizzi in #46
• rename library v2 by @luigibonati in #49
• Fix device loss by @luigibonati in #50
• Rename data objects by @luigibonati in #51
• Support for task-specific layers by @andrrizzi in #53
• Merge lightning into main by @luigibonati in #55
• Add paper experiments by @luigibonati in #56
• Code fixes by @luigibonati in #58

New Contributors

• @andrrizzi made their first contribution in #27
• @pietronvll made their first contribution in #36

Full Changelog: v0.2.2...v0.3.0