Quick guide: Four ways to use sdpt3glue

Given an SDP problem P formulated in Cvxpy, the following methods are accommodated.

1. With Matlab installed

Make sure SDPT3 is installed for Matlab and the folder containing SDPT3 is added to your MATLABPATH. Solve the problem by executing the following command:

result = sdpt3glue.sdpt3_solve_problem(P, sdpt3glue.MATLAB, matfile_target,
                                       output_target=output_target)

where matfile_target is the filepath that the problem’s .mat file will be saved to and output_target is the filepath that the SDPT3 solve log will be saved to.

2. With Octave installed

Make sure SDPT3 is installed for Octave and is visible in Octave when the working folder is the folder where matfile_target is.

result = sdpt3glue.sdpt3_solve_problem(P, sdpt3glue.OCTAVE, matfile_target,
    output_target=output_target)

3. Using Docker

Without a locally installed copy of Matlab or Octave, but with Docker, a problem can be solved in the following way:

OCTAVE_CMD = (
    "docker run --rm -it -v {workdir}:/data "
    "jkawamoto/octave-sdpt3 octave"
).format(workdir=os.path.abspath("."))

result = sdpt3glue.sdpt3_solve_problem(P, sdpt3glue.OCTAVE, matfile_target,
    output_target=output_target, cmd=OCTAVE_CMD)

This makes use of a docker image created by Junpei Kawamoto for this purpose.

4. With the NEOS server

With either Firefox or phantomjs installed and for small to medium sized problems (those with .mat files of size less than about 20-25MB), the NEOS server can be used. Disclaimer: In addition to the disclaimer provided by the MIT license, we make special note that we make no guarantees about service provided by the NEOS server, as we are not responsible for its operation. If your problem data is sensitive, take appropriate precautions.

result = sdpt3glue.sdpt3_solve_problem(P, sdpt3glue.NEOS, matfile_target,
    output_target=output_target)