  The MIXANDMIX (mixtures by Anderson mixing) tool for the computation of the
empirical spectral distribution of random matrices generated by mixtures of
populations is described. Within the population mixture model the mapping
between the population distributions and the limiting spectral distribution can
be obtained by solving a set of systems of non-linear equations, for which an
efficient implementation is provided. The contributions include a method for
accelerated fixed point convergence, a homotopy continuation strategy to
prevent convergence to non-admissible solutions, a blind non-uniform grid
construction for effective distribution support detection and approximation,
and a parallel computing architecture. Comparisons are performed with available
packages for the single population case and with results obtained by simulation
for the more general model implemented here. Results show competitive
performance and improved flexibility.
