old_contents: from numpy import *
  from numpy.random import rand
  from shogun.Features import RealFeatures, Labels
  from shogun.Kernel import CustomKernel
  from shogun.Classifier import LibSVM
  
  C=1
  dim=7
  
  lab=sign(2*rand(dim) - 1)
  data=rand(dim, dim)
  symdata=data+data.T
  
  kernel=CustomKernel()
  kernel.set_full_kernel_matrix_from_full(data)
  labels=Labels(lab)
  svm=LibSVM(C, kernel, labels)
  svm.train()
  out=svm.classify().get_labels()
  
new_contents: from numpy import *
  from numpy.random import rand
  from shogun.Features import RealFeatures, Labels
  from shogun.Kernel import CustomKernel
  from shogun.Classifier import LibSVM
  
  C=1
  dim=7
  
  lab=sign(2*rand(dim) - 1)
  data=rand(dim, dim)
  symdata=data*data.T
  
  kernel=CustomKernel()
  kernel.set_full_kernel_matrix_from_full(data)
  labels=Labels(lab)
  svm=LibSVM(C, kernel, labels)
  svm.train()
  out=svm.classify().get_labels()
  
subject: make example comput. easier