code: def _pred_to_binrel(pred):
      if not isinstance(pred, AppliedPredicate):
          return pred
  
      if pred.function in pred_to_pos_neg_zero:
          f = pred_to_pos_neg_zero[pred.function]
          if f is False:
              return False
          pred = f(pred.arguments[0])
  
      if pred.function == Q.positive:
          pred = Q.gt(pred.arguments[0], 0)
      elif pred.function == Q.negative:
          pred = Q.lt(pred.arguments[0], 0)
      elif pred.function == Q.zero:
          pred = Q.eq(pred.arguments[0], 0)
      elif pred.function == Q.nonpositive:
          pred = Q.le(pred.arguments[0], 0)
      elif pred.function == Q.nonnegative:
          pred = Q.ge(pred.arguments[0], 0)
      elif pred.function == Q.nonzero:
          pred = Q.ne(pred.arguments[0], 0)
  
      return pred
  
file_path: sympy/sympy/assumptions/lra_satask.py
imports: from sympy.assumptions.assume import global_assumptions
  from sympy.assumptions.cnf import CNF, EncodedCNF
  from sympy.assumptions.ask import Q
  from sympy.logic.inference import satisfiable
  from sympy.logic.algorithms.lra_theory import UnhandledInput, ALLOWED_PRED
  from sympy.matrices.kind import MatrixKind
  from sympy.core.kind import NumberKind
  from sympy.assumptions.assume import AppliedPredicate
  from sympy.core.mul import Mul
  from sympy.core.singleton import S
label_desc: Use image node_id 4 for calling a global function with example usage: _pred_to_binrel(pred) and returns: pred, pred, False