From a20c7441796db92b097064b6e40bea8c3ea032aa Mon Sep 17 00:00:00 2001 From: zethson Date: Mon, 16 Oct 2023 09:53:16 +0200 Subject: [PATCH] Version 0.3.1 + README --- README.md | 24 +++++++++++------------- sparsecca/__init__.py | 2 +- 2 files changed, 12 insertions(+), 14 deletions(-) diff --git a/README.md b/README.md index 4c78ffd..c3d37d4 100644 --- a/README.md +++ b/README.md @@ -1,30 +1,28 @@ -## sparsecca +# sparsecca Python implementations for Sparse CCA algorithms. Includes: * Sparse (multiple) CCA based on Penalized Matrix Decomposition (PMD) from Witten et al, 2009. * Sparse CCA based on Iterative Penalized Least Squares from Mai et al, 2019. - -One main difference between these two is that while the first is very simple it assumes datasets to be white. - -### Installation -#### Dependencies +One main difference between these two is that while the first is very simple it assumes datasets to be white. -In addition to basic scientific packages such as numpy and scipy, iterative penalized least squares needs either glmnet\_python or pyglmnet to be installed. +## Installation -#### This package can be installed normally with +### sparsecca is available on PyPI ``` -git clone https://github.com/theislab/sparsecca -cd sparsecca -pip install . +pip install sparsecca ``` -### Usage +### Iterative penalized least squares support + +In addition to basic scientific packages such as numpy and scipy, iterative penalized least squares needs either glmnet\_python or pyglmnet to be installed. + +## Usage See examples, https://teekuningas.github.io/sparsecca -### Acknowledgements +## Acknowledgements Great thanks to the original authors, see Witten et al, 2009 and Mai et al, 2019. diff --git a/sparsecca/__init__.py b/sparsecca/__init__.py index 8b0a35f..6864cad 100644 --- a/sparsecca/__init__.py +++ b/sparsecca/__init__.py @@ -1,4 +1,4 @@ -__version__ = "0.3.0" +__version__ = "0.3.1" from ._cca_pmd import cca as cca_pmd from ._multicca_pmd import multicca as multicca_pmd