code: def gen_non_lin_separable_data():
      mean1 = [-1, 2]
      mean2 = [1, -1]
      mean3 = [4, -4]
      mean4 = [-4, 4]
      cov = [[1.0, 0.8], [0.8, 1.0]]
      X1 = np.random.multivariate_normal(mean1, cov, 50)
      X1 = np.vstack(
          (X1, np.random.multivariate_normal(mean3, cov, 50))
      )
      y1 = np.ones(len(X1))
      X2 = np.random.multivariate_normal(mean2, cov, 50)
      X2 = np.vstack(
          (X2, np.random.multivariate_normal(mean4, cov, 50))
      )
      y2 = np.ones(len(X2)) * -1
      return X1, y1, X2, y2
  
file_path: lightning/examples/plot_sparse_non_linear.py
imports: import numpy
  import pylab
  from sklearn.metrics.pairwise import rbf_kernel
  from lightning.classification import CDClassifier
  from lightning.classification import KernelSVC
label_desc: Use image node_id 1 for calling a global function with example usage: gen_non_lin_separable_data() and returns: X1,  y1,  X2,  y2