code: def _inertia_(i, j, Features):
      """
      Compute the variance of the set which is
      the concatenation of Feature[i] and Features[j]
      """
      if np.size(np.shape(Features[i])) < 2:
          print(i, np.shape(Features[i]), Features[i])
      if np.size(np.shape(Features[i])) < 2:
          print(j, np.shape(Features[j]), Features[j])
      if np.shape(Features[i])[1] != np.shape(Features[j])[1]:
          print(i, j, np.shape(Features[i]), np.shape(Features[j]))
      localset = np.vstack((Features[i], Features[j]))
      return np.var(localset, 0).sum()
  
imports: from warnings import warn
  import numpy
  from ..graph.forest import Forest
  from ..graph.graph import WeightedGraph
label_desc: Use image node_id 4 for calling a global function with example usage: _inertia_(i, j, Features) and returns: np