np.random.seed(8888) mc = MaggotCluster( "0", adj=adj, meta=meta, n_init=25, stashfig=stashfig, max_clusters=8, n_components=None, embed="unscaled_ase", reembed=True, ) mc.fit_candidates() mc.plot_model(6) mc.plot_model(7) mc.select_model(6) np.random.seed(9999) for i, node in enumerate(mc.get_lowest_level()): print(node.name) print() node.fit_candidates() sub_ks = [(2, 3, 4, 5), (2, 3, 4), (2, 4, 5, 6), (2, 3, 4), (2, 3, 4), (2, 3, 4, 5)] for i, node in enumerate(mc.get_lowest_level()): print(node.name) print() for k in sub_ks[i]: node.plot_model(k) # %% [markdown]
"0", adj=adj, meta=meta, n_init=50, # stashfig=stashfig, min_clusters=2, max_clusters=8, X=U, ) mc.fit_candidates() mc.plot_model(6) # %% [markdown] # ## mc.select_model(6) for node in mc.get_lowest_level(): node.fit_candidates() # %% [markdown] # ## for node in mc.get_lowest_level(): node.stashfig = None node.plot_model(2) node.plot_model(3) node.plot_model(4) # %% [markdown] # ## ks = [3, 3, 0, 4] for i, node in enumerate(mc.get_lowest_level()):