code: def mathematics_sparseinversecovariance(data, lc):
      try:
          from shogun import SparseInverseCovariance
      except ImportError:
          print("SparseInverseCovariance not available")
          exit(0)
  
      from numpy import dot
  
      sic = SparseInverseCovariance()
      S = dot(data, data.T)
      Si = sic.estimate(S, lc)
  
      return Si
  
label_desc: Use image node_id 1 for calling a global function with example usage: mathematics_sparseinversecovariance(data, lc) and returns: Si