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.