title: Nonlinear constrained optimization package for Python with direct support of matrix variables
body: <p>I've been looking around for a nonlinear constrained optimization package for Python (to deal with problems that are NOT necessarily convex) that can directly handle matrix variables. More specifically, I'm dealing with optimization problems where the optimization variables are matrices, and where there are equality constraints with both sides of the equations being matrices. An example of such an optimization problem is the Orthogonal Procrustes problem (<a href="https://en.wikipedia.org/wiki/Orthogonal_Procrustes_problem" rel="noreferrer">https://en.wikipedia.org/wiki/Orthogonal_Procrustes_problem</a>).</p>
  
  <p>In my search I have come across SciPy, pyOpt, Ipopt and GEKKO, but neither of them seem to directly support matrix variables (from the documentation I was able to find). I have considered doing some maneuvering to convert the matrices into vectors when necessary and vice versa (through <code>numpy.reshape</code> or something similar), but I would like to avoid that option as much as possible. The reason for this is that my problems are fairly large, and constantly reshaping arrays would significantly harm the efficiency of the optimization procedure.</p>
  
  <p>Any suggestions?</p>