Gemelli

Features

* Robust Aitchison PCA
* with manually chosen n_components
* with auto chosen n_components
* associated tests added for function, standalone, & QIIME2
* Robust centered log-ratio (rclr) transformation
* allows users to use the transform alone outside CTF/RPCA
* associated tests added and extra tests for rclr added
* Tutorials
* Cross-sectional for RPCA (standalone & QIIME2)
* Repeated measure for CTF (standalone & QIIME2)


Miscellaneous

* auto_rpca rank estimation min rank now 3
* added citations for CTF & RPCA (linked when appropriate)
* updated the function descriptions

Features

* The output of the standalone and QIIME2 -CLI now return a state ordination
* Note that only the standalone can handle more than one state due to the lack of lists in QIIME2

Bug fixes

* Fixes in `_transformer.py` and `ctf.py` to utilize QIIME2 metadata passing, this fixes the dtype bool dropping issues in metadata
* Removed imports of QIIME2 metadata in `ctf.py`, this will allow the standalone commandline to run without having QIIME2 installed.
* Update pandas future error of .loc[new_index, :] to .reindex(new_index)
* Centered the subject biplot
* Added flake8 testing to travis

Features

* Tensor Building and RCLR transformation in `preprocessing.rclr` and `preprocessing.build`
* N-mode tensor building and transformation
* Mean of counts for subject-conditional pairs with several samples

Backward-incompatible changes [stable]

* In `preprocessing.build`:
* pervious -> current
* build().sample_order -> build().subject_order
* build().temporal_order -> build().condition_orders
* as a list for N possible condition(s)
* build().tensor -> build().counts

Backward-incompatible changes [experimental]

Performance enhancements

* tensor building and transformation

Bug fixes

* line 369-360 in `factorization.tenals` causes np.nan(s) in solution
* fixed by added pseudocount if any nan in solution

* line 178-179 in `factorization.TenAls`
* was previously checking if all missing/zero not if there were no missing/zero as intended

Deprecated functionality [stable]

* In `preprocessing.rclr` and `preprocessing.build`:
* build().transform() -> `preprocessing.rclr` as standalone function

Deprecated functionality [experimental]

Miscellaneous

* line 175 in `factorization.TenAls` to send ValueError if input is not numpy array

Features

* Tensor factorization in `factorization.tenals` and `factorization.TenALS`
* Accomplished by turning hard-coded operations into for loops and generalizing vectorization using tensor contractions

* Khatri Rao Product

Backward-incompatible changes [stable]

Backward-incompatible changes [experimental]

* `factorization.tenals` returns a list of matrices `loadings` instead of `u1, u2, u3` tuple, along with other arguments

Performance enhancements

* tensor contraction

Bug fixes

Deprecated functionality [stable]

Deprecated functionality [experimental]

Miscellaneous

* various type and spacing fixes