Installation
Dependencies
Python (3.6 or later)
netcdf4
joblib
tqdm
Optional dependencies
These need to be installed separately to use some functionality:
holoviews (for some plotting functions)
rpy2 (for sparse CCA)
Instructions
gemmr can be installed with pip
:
$ pip install gemmr
Alternatively, the most current version can be obtained from github:
$ git clone https://github.com/mdhelmer/gemmr.git
$ cd gemmr
$ python setup.py install
Tests
Unit tests can be run with pytest
from the root directory:
$ pytest
References
van der Walt S. et al., “The NumPy Array: A Structure for Efficient Numerical Computation”, Computing in Science & Engineering, 13, 22-30, 2011. DOI: 10.1109/MCSE.2011.37. https://numpy.org
Virtanen P. et al., “SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python”, Nature Methods, 2020. DOI:10.1038/s41592-019-0686-2. https://scipy.org/
McKinney W. “Data structures for statistical computing in python”, Proceedings of the 9th Python in Science Conference, Volume 445, 2010. https://pandas.pydata.org/
Hoyer, S. & Hamman, J. “xarray: N-D labeled Arrays and Datasets in Python”, Journal of Open Research Software. 5(1), p.10. 2017. DOI: 10.5334/jors.148. http://xarray.pydata.org/
Buitinck et al., “API design for machine learning software: experiences from the scikit-learn project”, ECML PKDD Workshop: Languages for Data Mining and Machine Learning, 2013. https://scikit-learn.org/
Seabold, Skipper, and Josef Perktold. “statsmodels: Econometric and statistical modeling with python.” Proceedings of the 9th Python in Science Conference, 2010. https://www.statsmodels.org