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()):