old_contents: import numpy
  tt = numpy.genfromtxt('../../../../data/toy/swissroll_color.dat',unpack=True).T
  X = numpy.genfromtxt('../../../../data/toy/swissroll.dat',unpack=True).T
  N = X.shape[1]
  preprocs = []
  
  from shogun.Preprocessor import LocallyLinearEmbedding
  lle = LocallyLinearEmbedding()
  lle.set_k(9)
  preprocs.append((lle, "Locally Linear Embedding with k=%d" % lle.get_k()))
  
  from shogun.Preprocessor import ClassicMDS
  mds = ClassicMDS()
  preprocs.append((mds, "Classic MDS"))
  
  from shogun.Preprocessor import LandmarkMDS
  lmds = LandmarkMDS()
  lmds.set_landmark_number(50)
  preprocs.append((lmds,"Landmark MDS with %d landmarks" % lmds.get_landmark_number()))
  
  from shogun.Preprocessor import ClassicIsomap, KISOMAP
  cisomap = ClassicIsomap()
  cisomap.set_type(KISOMAP)
  cisomap.set_k(9)
  preprocs.append((cisomap,"Classic Isomap with k=%d" % cisomap.get_k()))
  
  from shogun.Preprocessor import LandmarkIsomap
  lisomap = LandmarkIsomap()
  lisomap.set_landmark_number(50)
  lisomap.set_type(KISOMAP)
  lisomap.set_k(9)
  preprocs.append((lisomap,"Landmark Isomap with k=%d" % lisomap.get_k()))
  
  import matplotlib.pyplot as plt
  from mpl_toolkits.mplot3d import Axes3D
  
  fig = plt.figure()
  swiss_roll_fig = fig.add_subplot(len(preprocs)/2+1,len(preprocs)/2,1,projection='3d')
  swiss_roll_fig.scatter(X[0], X[1], X[2], s=10, c=tt, cmap=plt.cm.Spectral)
  plt.subplots_adjust(hspace=0.4)
  
  from shogun.Features import RealFeatures
  
  for (i, (preproc, label)) in enumerate(preprocs):
  	X = numpy.genfromtxt('../../../../data/toy/swissroll.dat',unpack=True).T
  	features = RealFeatures(X)
  	preproc.set_target_dim(2)
  	new_feats = preproc.apply_to_feature_matrix(features)
  	preproc_subplot = fig.add_subplot(len(preprocs)/2+1,len(preprocs)/2,i+2)
  	preproc_subplot.scatter(new_feats[0],new_feats[1], c=tt, cmap=plt.cm.Spectral)
  	plt.title(label)
  	print preproc.get_name(), 'done'
  	
  plt.show()
  
new_contents: import numpy
  tt = numpy.genfromtxt('../../../../data/toy/swissroll_color.dat',unpack=True).T
  X = numpy.genfromtxt('../../../../data/toy/swissroll.dat',unpack=True).T
  N = X.shape[1]
  preprocs = []
  
  from shogun.Preprocessor import LocallyLinearEmbedding
  lle = LocallyLinearEmbedding()
  lle.set_k(9)
  preprocs.append((lle, "Locally Linear Embedding with k=%d" % lle.get_k()))
  
  from shogun.Preprocessor import ClassicMDS
  mds = ClassicMDS()
  preprocs.append((mds, "Classic MDS"))
  
  from shogun.Preprocessor import LandmarkMDS
  lmds = LandmarkMDS()
  lmds.set_landmark_number(50)
  preprocs.append((lmds,"Landmark MDS with %d landmarks" % lmds.get_landmark_number()))
  
  from shogun.Preprocessor import ClassicIsomap, KISOMAP
  cisomap = ClassicIsomap()
  cisomap.set_type(KISOMAP)
  cisomap.set_k(9)
  preprocs.append((cisomap,"Classic K-Isomap with k=%d" % cisomap.get_k()))
  
  from shogun.Preprocessor import LandmarkIsomap
  lisomap = LandmarkIsomap()
  lisomap.set_landmark_number(50)
  lisomap.set_type(KISOMAP)
  lisomap.set_k(9)
  preprocs.append((lisomap,"L-K-Isomap with k=%d, %d landmarks" % (lisomap.get_k(),lisomap.get_landmark_number())))
  
  import matplotlib.pyplot as plt
  from mpl_toolkits.mplot3d import Axes3D
  
  fig = plt.figure()
  swiss_roll_fig = fig.add_subplot(len(preprocs)/2+1,len(preprocs)/2,1,projection='3d')
  swiss_roll_fig.scatter(X[0], X[1], X[2], s=10, c=tt, cmap=plt.cm.Spectral)
  plt.subplots_adjust(hspace=0.4)
  
  from shogun.Features import RealFeatures
  
  for (i, (preproc, label)) in enumerate(preprocs):
  	X = numpy.genfromtxt('../../../../data/toy/swissroll.dat',unpack=True).T
  	features = RealFeatures(X)
  	preproc.set_target_dim(2)
  	new_feats = preproc.apply_to_feature_matrix(features)
  	preproc_subplot = fig.add_subplot(len(preprocs)/2+1,len(preprocs)/2,i+2)
  	preproc_subplot.scatter(new_feats[0],new_feats[1], c=tt, cmap=plt.cm.Spectral)
  	plt.title(label)
  	print preproc.get_name(), 'done'
  	
  plt.show()
  
subject: Fix for swissroll graphical example