code: def _sigmoid(x1):
      """Special case of logistic function to transform to probabilities."""
      with np.errstate(over="ignore", under="ignore"):
          return 1 / (1 + np.exp(-x1))
  
file_path: gplearn/gplearn/functions.py
imports: import numpy
  from joblib import wrap_non_picklable_objects
label_desc: Use image node_id 6 for calling a global function with example usage: _sigmoid(x1) and returns: unknown