To run the MATLAB implementation, see MATLAB setup
Python dependencies:
sudo easy_install pip
pip install -r requirements.txt
Also needed is scipy. If you find some missing dependencies, please add them here.
To build the simplex projection c extension:
cdintopython/c_extensions- run
python2 setup.py build_ext --inplace
Set up the pre-commit hook (which automatically runs the fast unit tests):
ln -s ../../pre-commit.sh .git/hooks/pre-commit
First download CPLEX for your OS from the IBM website (you'll need to sign up
for an academic initiative account first). It would be a file named
CPLEX_xxxxxxxxxx.bin.
To install, run (using sudo if necessary):
chmod +x CPLEX_xxxxxxxxxx.bin
./CPLEX_xxxxxxxxxx.bin
Note the installation directory, then to install the python bindings (using
sudo if necessary, for OSX users you might need to run sudo -s first before
these steps):
cd <installation-directory>/ILOG/CPLEX_Studio1261/cplex/python/2.7/x86-64_linux
python setup.py install
Install openopt (documentation here: http://openopt.org/cplex):
pip install openopt
To see an example on how to use CPLEX, look at tests/fast/test_cplex.py
Run the python implementation from the traffic-estimation/python directory.
To run the main test, see these examples:
cd ~/traffic-estimation/python
python main.py --file route_assignment_matrices_ntt.mat --log=DEBUG --solver LBFGS
python main.py --file route_assignment_matrices_ntt.mat --log=DEBUG --solver BB
python main.py --file route_assignment_matrices_ntt.mat --log=DEBUG --solver DORE
If the dataset you want to run is not in the data directory, symlink it in from the main dataset.
To run 3-fold cross validation test:
python CrossValidation.py --log=DEBUG
After generating the set of matrices run:
python ISTTT.py --log=DEBUG --solver BB
MATLAB dependencies (must be run every time MATLAB is started):
setup.m
To bind Cythonic extensions to Python
cd python/c_extensions
python setup.py build_ext --inplace
check if it created an executable 'c_extensions.so' and 'c_extensions.cpp'
Run main.m.
Mark Schmidt's L1General, a set of Matlab routines for solving L1-regularization problems.