v4.01

The main algorithmic addition to this release is the "cca" flag in the pls routine that allows you to calculate Covariant spaces in X that are strictly correlated with the Y space (achieving what OPLS would when the correct number of orthogonal components are used. Some additional bells and whistles are added to plots (e.g. you can add the scores from the model to a score plot for a new observation). The documentation is much improved also, finally I reorganized the examples.

PyPhi v4.0

The main algorithmic addition to this release is the "cca" flag in the pls routine that allows you to calculate Covariant spaces in X that are strictly correlated with the Y space (achieving what OPLS would when the correct number of orthogonal components are used. Some additional bells and whistles are added to plots (e.g. you can add the scores from the model to a score plot for a new observation). The documentation is much improved also, finally I reorganized the examples.

PyPhi v3.0

A much extended version of PyPhi with the LPLS, JRPLS and TPLS models with their respective plotting tools. Also a much improved pyphi_batch with routines for alignment using an indicator variables, batch contributions, batch predictors, the capability to mimic a soft-sensor in batch monitoring and utilities such as a sample distribution generator, a batch descriptor generator (to collect for example min/max/mean values for a trajectory during a phase) and a routine to calculate relative batch times based on the timestamp.

PyPhi Release 2.0

I added Batch Anaysis

pyPhi v1.0.1

Little bugs addressed, added diagnostics to pca_pred and pls_pred

pyPhi

v1.0

Update README.md