Migration Guide ---------------- Version 1.2 of `lightonopu` and `lightonml` introduce API changes, requiring action on your code: ``lightonopu`` ^^^^^^^^^^^^^^ We noticed that in some situations, two successive transforms on related data can have inconsistent result, fitting the OPU on input data fixes this. The previous methods `transform1d ` and `transform2d ` are still provided for compatibility, but you will get a deprecation warning on calling them. To migrate your code, do the following: - If you do several transform operations on related data (like train and test), first call `fit1d ` or `fit2d ` on one of the data, and then `transform` (notice the 1d/2d suffix is removed) - Alternatively, replace `transform1d `/`transform2d ` calls by `fit_transform1d `/`fit_transform2d ` to get rid of the deprecation warning. ``lightonml`` ^^^^^^^^^^^^^^ Similarly to `lightonopu`, the `OPUMap` objects in `lightonml.projections.sklearn` and `lightonml.projections.torch` now also have a `fit` method. It can be called explicitly, or it will be called automatically when the first transform is performed. The migration procedure is similar: - If you do several transform operations on related data (like train and test), first call `fit` on one of the data, and then `transform`, or `forward` in the case of the Pytorch wrapper - Alternatively, replace `transform` calls by `fit_transform` for the Scikit-learn wrapper.