def test_swissroll(self):
graphs.SwissRoll(srtype='uniform')
graphs.SwissRoll(srtype='classic')
graphs.SwissRoll(noise=True)
graphs.SwissRoll(noise=False)
graphs.SwissRoll(dim=2)
graphs.SwissRoll(dim=3)
Gs[i + 1].mr = {
'idx': ind,
'orig_idx': Gs[i].mr['orig_idx'][ind],
'level': i
}
L_reg = Gs[i].L + reg_eps * sparse.eye(Gs[i].N)
Gs[i].mr['K_reg'] = kronReduction(L_reg, ind)
Gs[i].mr['green_kernel'] = filters.Filter(Gs[i], lambda x: 1. /
(reg_eps + x))
return Gs
G = graphs.SwissRoll(N=1000, seed=42)
levels = 5
Gs = multiresolution(G, levels, sparsify=True)
fig = plt.figure(figsize=(10, 2.5))
for i in range(4):
ax = fig.add_subplot(1, 4, i + 1, projection='3d')
plotting.plot_graph(Gs[i + 1], ax=ax)
_ = ax.set_title(
'Pyramid Level: {} \n Number of nodes: {} \n Number of edges: {}'.
format(i + 1, Gs[i + 1].N, Gs[i + 1].Ne))
ax.set_axis_off()
fig.tight_layout()
plt.show()
G = graphs.Sensor(1200, distribute=True)
def test_SwissRoll():
G = graphs.SwissRoll()
def test_SwissRoll():
G = graphs.SwissRoll()
needed_attributes_testing(G)
