code: def _protected_log(x1):
      """Closure of log for zero and negative arguments."""
      with np.errstate(divide="ignore", invalid="ignore"):
          return np.where(np.abs(x1) > 0.001, np.log(np.abs(x1)), 0.0)
  
file_path: gplearn/gplearn/functions.py
imports: import numpy
  from joblib import wrap_non_picklable_objects
label_desc: Use image node_id 4 for calling a global function with example usage: _protected_log(x1) and returns: np