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()