code: def get_edge_dist(g, threshold):
      if threshold == "prob":
          return g.edata["prob_conn"][:, 0]
      return 1 - g.edata["raw_affine"]
  
file_path: dgl/examples/pytorch/hilander/utils/deduce.py
imports: import dgl
  import numpy
  import torch
  from sklearn import mixture
  from .density import density_to_peaks, density_to_peaks_vectorize
label_desc: Use image node_id 6 for calling a global function with example usage: get_edge_dist(g, threshold) and returns: unknown, g