code: def get_kneighbors_conn(X_dist, p_neighbors):
      X_dist_out = np.zeros_like(X_dist)
      for i, line in enumerate(X_dist):
          sorted_idx = np.argsort(line)
          sorted_idx = sorted_idx[::-1]
          indices = sorted_idx[:p_neighbors]
          X_dist_out[indices, i] = 1
      return X_dist_out
  
file_path: espnet/egs/libri_css/asr1/diarization/spec_clust.py
imports: import argparse
  import numpy
  import scipy
  from kaldiio import ReadHelper
  from sklearn.cluster import SpectralClustering
label_desc: Use image node_id 5 for calling a global function with example usage: get_kneighbors_conn(X_dist, p_neighbors) and returns: X_dist_out