vectorize infogain computationa cross all candidate acquisition points

[lukasheinrich]

A major bottleneck is the fact that we compute the info gain is python loop for each point separately. It' s conceivable that this can be vectorized, but probably this will require breaking up the kernel components of the GP and writing the vectorized computation by hand for each given kernel.

i.e. instead of

def info_gain(x_candidate,...)
    X_all = np.concatenate([np.array([x_candidate]), meanX]).reshape(1 + n_samples, -1)
    tocat = []
    for gp in gps:
        K_trans_all = gp.kernel_(X_all, gp.X_train_)

[info_gain(x,...) for x in scandetails.acqX]

do

info_gains(scandetails.acqX,...)