code: def sparse_euclidean(ind1, data1, ind2, data2):
      _, aux_data = sparse_diff(ind1, data1, ind2, data2)
      result = 0.0
      for i in range(aux_data.shape[0]):
          result += aux_data[i] ** 2
      return np.sqrt(result)
  
imports: from __future__ import print_function
  import locale
  import numpy
  import numba
  from pynndescent.utils import norm, tau_rand
  from pynndescent.distances import kantorovich, jensen_shannon_divergence, symmetric_kl_divergence
label_desc: Use image node_id 11 for calling a global function with example usage: sparse_euclidean(ind1, data1, ind2, data2) and returns: np