code: def _build_func(eq, **args):
      r'''
      Take a symbolic equation and return the lambdified version plus the
      linearization of form S1 * x + S2
      '''
      eq_prime = eq.diff(args['x'])
      s1 = eq_prime
      s2 = eq - eq_prime*args['x']
      EQ = _syp.lambdify(args.values(), expr=eq, modules='numpy')
      S1 = _syp.lambdify(args.values(), expr=s1, modules='numpy')
      S2 = _syp.lambdify(args.values(), expr=s2, modules='numpy')
      return EQ, S1, Sf _build_func(eq, **args):
      r'''
      Take a symbolic equation and return the lambdified version plus the
      linearization of form S1 * x + S2
      '''
      eq_prime = eq.diff(args['x'])
      s1 = eq_prime
      s2 = eq - eq_prime*args['x']
      EQ = _syp.lambdify(args.values(), expr=eq, modules='numpy')
      S1 = _syp.lambdify(args.values(), expr=s1, modules='numpy')
      S2 = _syp.lambdify(args.values(), expr=s2, modules='numpy')
      return EQ, S1, S2
docs: r'''
      Take a symbolic equation and return the lambdified version plus the
      linearization of form S1 * x + S2