Version 0.3.1 + README

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.

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