code: def _human_score_map(human_consensus, methods_attrs):
      """Converts human agreement differences to numerical scores for coloring."""
  
      v = 1 - min(
          np.sum(np.abs(methods_attrs - human_consensus))
          / (np.abs(human_consensus).sum() + 1),
          1.0,
      )
      return v
  
file_path: shap/shap/benchmark/plots.py
imports: import base64
  import io
  import os
  import numpy
  import sklearn
  from matplotlib.colors import LinearSegmentedColormap
  from ..None import __version__
  from ..plots import colors
  from .None import methods, metrics, models
  from .experiments import run_experiments
label_desc: Use image node_id 6 for calling a global function with example usage: _human_score_map(human_consensus, methods_attrs) and returns: v