def test_swiss_roll(self):
X = sr.swiss_roll(6, 10)
self.assertEqual(X.shape, (10, 3))
X, theta = sr.swiss_roll(3.0, 25, theta_noise=0, radius_noise=0,
return_theta=True)
self.assertEqual(X.shape, (25, 3))
self.assertEqual(theta.shape, (25,))
self.assertAlmostEqual(theta.max(), 3.0)
def main():
X, theta = swiss_roll(8, 500, return_theta=True)
D = pairwise_distances(X)
graph_info = [
_c('5-NN', neighbor_graph, D, k=6, precomputed=True),
_c('b-matching', b_matching, D, 6),
_c('gabriel', gabriel_graph, X),
_c('rel. neighborhood', relative_neighborhood_graph,D,metric='precomputed'),
_c('manifold spanning', manifold_spanning_graph, X, 2),
_c('L1', sparse_regularized_graph, X, k=10, alpha=0.0005),
_c('SAFFRON', saffron, X, q=15, k=5, tangent_dim=2),
_c('MST', mst, D, metric='precomputed'),
_c('dMST', disjoint_mst, D, metric='precomputed'),
]
print('Plotting graphs & embeddings')
fig1, axes1 = plt.subplots(nrows=3, ncols=3, subplot_kw=dict(projection='3d'))
fig2, axes2 = plt.subplots(nrows=3, ncols=3)
fig1.suptitle('Original Coordinates')
fig2.suptitle('Isomap Embeddings')
plot_kwargs = dict(directed=False, weighted=False, edge_style='k-')
for ax1, ax2, info in zip(axes1.flat, axes2.flat, graph_info):
label, G, gg, emb, mask = info
G.plot(X, ax=ax1, title=label, vertex_style=dict(c=theta), **plot_kwargs)
gg.plot(emb, ax=ax2, title=label, vertex_style=dict(c=theta[mask]),
**plot_kwargs)
ax1.view_init(elev=5, azim=70)
ax1.set_axis_off()
ax2.set_axis_off()
plt.show()
def main():
np.random.seed(1234)
X, theta = swiss_roll(8, 500, return_theta=True)
print('Figure 1 of 3: bare coordinates in 3d')
ax = Axes3D(plt.figure())
ax.scatter(*X.T, c=theta)
print('Figure 2 of 3: 5-NN graph in original coordinates')
g = neighbor_graph(X, k=5).symmetrize('max')
g.plot(X, directed=False, weighted=False, fig='new', edge_style='k-',
vertex_style=dict(c=theta))
print('Writing swiss_roll.html for force-directed layout demo')
g.to_html('swiss_roll.html', directed=False, weighted=False,
vertex_colors=theta)
print('Figure 3 of 3: 2d Isomap embedding of 5-NN graph')
emb = g.isomap(num_dims=2)
_, ax = plt.subplots(figsize=(10, 5))
g.plot(emb, directed=False, weighted=False, ax=ax, edge_style='k-',
vertex_style=dict(c=theta))
ax.xaxis.set_ticks([])
ax.yaxis.set_ticks([])
plt.show()
def test_swiss_roll(self):
np.random.seed(1234)
X, theta = swiss_roll(6, 120, radius=4.8, return_theta=True)
GT = np.hstack((theta[:, None], X[:, 1:2]))
GT -= GT.min(axis=0)
GT /= GT.max(axis=0)
G = manifold_spanning_graph(X, 2)
self.assertEqual(error_ratio(G, GT), 0.0)
