code: def kernel_combined(
      fm_train_real=traindat,
      fm_test_real=testdat,
      fm_train_dna=traindna,
      fm_test_dna=testdna,
  ):
      kernel = sg.create_kernel("CombinedKernel")
      feats_train = sg.create_features("CombinedFeatures")
      feats_test = sg.create_features("CombinedFeatures")
  
      subkfeats_train = sg.create_features(fm_train_real)
      subkfeats_test = sg.create_features(fm_test_real)
      subkernel = sg.create_kernel("GaussianKernel", width=1.0)
      feats_train.add("feature_array", subkfeats_train)
      feats_test.add("feature_array", subkfeats_test)
      kernel.add("kernel_array", subkernel)
  
      subkfeats_train = sg.create_string_features(fm_train_dna, sg.DNA)
      subkfeats_test = sg.create_string_features(fm_test_dna, sg.DNA)
      degree = 3
      subkernel = sg.create_kernel(
          "FixedDegreeStringKernel", degree=degree
      )
      feats_train.add("feature_array", subkfeats_train)
      feats_test.add("feature_array", subkfeats_test)
      kernel.add("kernel_array", subkernel)
  
      subkfeats_train = sg.create_string_features(fm_train_dna, sg.DNA)
      subkfeats_test = sg.create_string_features(fm_test_dna, sg.DNA)
      subkernel = sg.create_kernel("LocalAlignmentStringKernel")
      feats_train.add("feature_array", subkfeats_train)
      feats_test.add("feature_array", subkfeats_test)
      kernel.add("kernel_array", subkernel)
  
      print(feats_train)
      print(feats_test)
  
      kernel.init(feats_train, feats_train)
      km_train = kernel.get_kernel_matrix()
      kernel.init(feats_train, feats_test)
      km_test = kernel.get_kernel_matrix()
      return km_train, km_test, kernel
  
label_desc: Use image node_id 1 for calling a global function with example usage: kernel_combined(fm_train_real, fm_test_real, fm_train_dna, fm_test_dna) and returns: km_train,  km_test,  kernel