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)