Returning a list of strategy profiles from Nash solvers is quite thin. It discards useful information about the set of equilibria - including whether the list is known to be complete, whether there are positive-dimensional components, what algorithm parameters were used, and possibly interesting intermediate steps in the algorithm.
We should develop Result classes for Nash solvers, both in Python, and, eventually, at the C++ level. One place to look is at scipy, where e.g. there are Result classes for the results of statistical tests (although there, at present, these are just instances of namedtuple).
Returning a list of strategy profiles from Nash solvers is quite thin. It discards useful information about the set of equilibria - including whether the list is known to be complete, whether there are positive-dimensional components, what algorithm parameters were used, and possibly interesting intermediate steps in the algorithm.
We should develop Result classes for Nash solvers, both in Python, and, eventually, at the C++ level. One place to look is at scipy, where e.g. there are Result classes for the results of statistical tests (although there, at present, these are just instances of namedtuple).