def converter_laplacianeigenmaps_modular(data, k):
from shogun.Features import RealFeatures
from shogun.Converter import LaplacianEigenmaps
features = RealFeatures(data)
converter = LaplacianEigenmaps()
converter.set_target_dim(1)
converter.set_k(k)
converter.set_tau(2.0)
converter.apply(features)
return features
def converter_laplacianeigenmaps_modular(data, k):
try:
from shogun.Features import RealFeatures
from shogun.Converter import LaplacianEigenmaps
features = RealFeatures(data)
converter = LaplacianEigenmaps()
converter.set_target_dim(1)
converter.set_k(k)
converter.set_tau(2.0)
converter.apply(features)
return features
except ImportError:
print('No Eigen3 available')
dm.set_width(1000.0)
converters.append(
(dm, "Diffusion Maps with t=%d, sigma=%f" % (dm.get_t(), dm.get_width())))
from shogun.Converter import HessianLocallyLinearEmbedding
hlle = HessianLocallyLinearEmbedding()
hlle.set_k(6)
converters.append((hlle, "Hessian LLE with k=%d" % (hlle.get_k())))
from shogun.Converter import LocalTangentSpaceAlignment
ltsa = LocalTangentSpaceAlignment()
ltsa.set_k(6)
converters.append((ltsa, "LTSA with k=%d" % (ltsa.get_k())))
from shogun.Converter import LaplacianEigenmaps
le = LaplacianEigenmaps()
le.set_k(20)
le.set_tau(100.0)
converters.append(
(le, "Laplacian Eigenmaps with k=%d, tau=%d" % (le.get_k(), le.get_tau())))
import matplotlib
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
fig = plt.figure()
new_mpl = False
try:
swiss_roll_fig = fig.add_subplot(3, 3, 1, projection='3d')
