code: def ceafe(clusters, gold_clusters):
      clusters = [c for c in clusters if len(c) != 1]
      scores = np.zeros((len(gold_clusters), len(clusters)))
      for i in range(len(gold_clusters)):
          for j in range(len(clusters)):
              scores[i, j] = phi4(gold_clusters[i], clusters[j])
      matching = linear_sum_assignment(-scores)
      matching = np.transpose(np.asarray(matching))
      similarity = sum(scores[matching[:, 0], matching[:, 1]])
      return similarity, len(clusters), similarity, len(gold_clusters)
  
imports: import logging
  import numpy
  from collections import Counter, defaultdict
  from scipy.optimize import linear_sum_assignment
  from .blanc import blanc, tuple_to_metric
label_desc: Use image node_id 6 for calling a global function with example usage: ceafe(clusters, gold_clusters) and returns: similarity,  len,  similarity,  len