NaNs in MLL output #111

Hello,

Following the example in the documentation, I am trying to use GPFlowOpt to do a parameter search over a 9-dimensional parameter space. The objective function is a function of both accuracy and latency of the algorithm I am finding parameters for. Therefore it is somewhat non-deterministic in that if I evaluate the objective function of the same point in parameter space twice I will obtain different results because the latency depends on the temperature of my laptop etc. It seems to be working, but I am getting stdout outputs like:

iter #  0 - MLL [-7.3] - fmin [15.4]
iter #  1 - MLL [-6.5] - fmin [9.64]
iter #  2 - MLL [-13.5] - fmin [9.64]
iter #  3 - MLL [-7.44] - fmin [9.64]
iter #  4 - MLL [nan] - fmin [9.64]
iter #  5 - MLL [nan] - fmin [9.64]
iter #  6 - MLL [nan] - fmin [9.64]
iter #  7 - MLL [nan] - fmin [9.64]

The nans are worrying. Do you have any idea what is causing them? I have checked the output of each evaluation of the objective function and they all seem sensible, no NaNs there!