Purpose: To compile the original Fortran code of GLMNET to use it in Python which contains the Poisson link function that many people and me use in the lab.
Requirements:
gitf2py (translator from fortran to python)gfortran (fortrain compiler)scikit-learn (for the example)clone repository from github
$ git clone https://github.com/dwf/glmnet-python
change directory and compile
$ cd glmnet-python
$ python setup.py build
compile fortran code
$ cd glmnet/
$ f2py -c --fcompiler=gnu95 --f77flags='-fdefault-real-8' --f90flags='-fdefault-real-8' glmnet.pyf glmnet.f
test code by going to root of project
cd ..
and in IPython run this example to see if it works
from glmnet import ElasticNet
from cv import CVGlmNet
from sklearn.datasets.samples_generator import make_regression
enet = ElasticNet(alpha=.1)
enet_cv = CVGlmNet(enet, n_folds=10, n_jobs=10)
X, y = make_regression(n_samples=100, n_features=10, n_informative=10, random_state=0, noise=35)
enet_cv.fit(X, y)
plot
enet_cv.plot_oof_devs()