A fast and flexible numpy-based wrapper for CPLex's Optimization Suite.
Project description
PyCPX is a python wrapper for the CPlex Optimization Suite that
focuses on speed, ease of use, and seamless integration with numpy.
CPlex is a powerful solver for linear and quadratic programs over
real, linear, and boolean variables. PyCPX allows one to naturally
express such programs using numpy and natural python constructs.
PyCPX requires IBM's `ILog Concert Technology`_ Suite, which is
available for free under IBM's Academic Initiative program or as part
of the CPlex Optimization Suite.
To install, type
python setup.py install
This compiles the included C++ source generated by cython. To compile
the cython source file into C++, type
python setup.py install --cython
To compile the documentation, type
make html
in the doc/ directory. The documentation will then be in
doc/.build/html.
Additional documentation can be found at
http://www.stat.washington.edu/~hoytak/code/pycpx/.
focuses on speed, ease of use, and seamless integration with numpy.
CPlex is a powerful solver for linear and quadratic programs over
real, linear, and boolean variables. PyCPX allows one to naturally
express such programs using numpy and natural python constructs.
PyCPX requires IBM's `ILog Concert Technology`_ Suite, which is
available for free under IBM's Academic Initiative program or as part
of the CPlex Optimization Suite.
To install, type
python setup.py install
This compiles the included C++ source generated by cython. To compile
the cython source file into C++, type
python setup.py install --cython
To compile the documentation, type
make html
in the doc/ directory. The documentation will then be in
doc/.build/html.
Additional documentation can be found at
http://www.stat.washington.edu/~hoytak/code/pycpx/.
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