def func_inference(crosscat):
synthesizer = GibbsCrossCat(crosscat)
n_step = 540 if integration else 1
for _step in xrange(n_step):
synthesizer.transition_row_assignments()
synthesizer.transition_hypers_row_divide()
synthesizer.transition_hypers_distributions()
synthesizer.transition_view_assignments()
return synthesizer
def test_dependencies_no_cpp():
prng = get_prng(2)
ensemble = CrossCatEnsemble(outputs=(0, 1),
inputs=[],
Ci=[(0, 1)],
distributions=[('normal', None)] * 2,
chains=5,
rng=prng)
ensemble.observe(0, {0: 0, 1: 1})
synthesizer = GibbsCrossCat(ensemble.cgpms[0], Ci=ensemble.Ci)
synthesizer.transition_view_assignments()