bob.learn.em.znorm() does not work

Created by: ivana7c

When calling the following function, we end up with the following error:

A = numpy.array([[1, 2, 3, 4, 5], [6, 7, 8, 9, 8], [7, 6, 5, 4, 3]], numpy.float64)
B = numpy.array([[5, 4, 7, 8],[9, 8, 7, 4],[5, 6, 3, 2]], numpy.float64)
normalized_scores = bob.learn.em.znorm(A, B)                

Usage (for details, see help):
ztnorm(rawscores_probes_vs_models,rawscores_zprobes_vs_models,rawscores_probes_vs_tmodels,rawscores_zprobes_vs_tmodels,mask_zprobes_vs_tmodels_istruetrial) -> output 

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
RuntimeError: More keyword list entries (5) than format specifiers (2)

There is something wrong with the python bindings. In addition, the tests are wrong as well, since this problem didn't show up earlier.

It was working well on the former major release of bob.