Macau-cpp - Bayesian Factorization with Side Information

Highly optimized and parallelized methods for Bayesian Factorization, including BPMF and Macau. The package uses optimized OpenMP/C++ code with a Cython wrapper to factorize large scale matrices. Macau method is able to perform matrix and tensor factorization while incorporating high-dimensional side information to the factorization.

Examples

For examples see documentation.

Installation

To install Macau it possible to use pre-compiled binaries or compile it from source.

Source installation on Ubuntu

# install dependencies:
sudo apt-get install libopenblas-dev autoconf gfortran
pip install numpy scipy cython pandas
pip install requests

# checkout and install Macau
git clone https://github.com/jaak-s/macau.git
cd macau
python setup.py install --user

Installing with pip

If you have openblas installed (package libopenblas-dev in Ubuntu) available and gcc and g++ installed, then following steps install macau:

git clone https://github.com/jaak-s/macau.git
cd macau
pip install .

Instead of pip install . one can use

python setup.py install --user

Source installation on Mac

# install dependencies
pip install numpy
pip install scipy
pip install pandas
pip install cython
pip install requests
# install brew (http://brew.sh/)
brew install homebrew/core/openblas
brew install gcc

# checkout and install Macau
git clone https://github.com/jaak-s/macau.git
cd macau
CC=g++-5 CXX=g++-5 python setup.py install

Docker

Macau is also available using Docker image at stadius/macau.

Without mounting a local directory the docker can be executed by

docker run -it --rm -p 8888:8888 stadius/macau

To mount a local directory add -v ~/my_data_dir:/data where ~/my_data_dir is on the local system and /data will be the folder in the container:

docker run -v ~/my_data_dir:/data -it --rm -p 8888:8888 stadius/macau

Binary installion on Ubuntu

There is a plan to support Python wheel packages. Currently, we do not have one built yet.

Contributors

• Jaak Simm (Macau C++ version, Cython wrapper, Macau MPI version, Tensor factorization)
• Adam Arany (Probit noise model)
• Tom Vander Aa (OpenMP optimized BPMF)
• Tom Haber (Original BPMF code)