code: def simulateTransition(x, s, r, fire):
      
      assert 0 <= x < POPULATION_CLASSES, "'x' must be in " \
          "{0, 1...%s}" % POPULATION_CLASSES - 1
      assert 0 <= s <= 1, "'s' must be in [0; 1]"
      assert 0 <= r <= 1, "'r' must be in [0; 1]"
      assert fire in (True, False), "'fire' must be a boolean value"
      x = int(x)
      if x == 0:
          pass
      elif x == POPULATION_CLASSES - 1:
          if random.random() <= 1 - (1 - s) * (1 - r):
              pass
          else: # with probability (1 - s)(1 - r)
              x -= 1
      else:
          if random.random() <= s:
              pass
          else:
              if random.random() <= r: # with probability (1 - s)r
                  x += 1
              else: # with probability (1 - s)(1 - r)
                  x -= 1
      # Add the effect of a fire, making sure x doesn't go to -1
      if fire and (x > 0):
          x -= 1
      return(x)
docs: Simulate a state transition.
      
      Parameters
      ----------
      x : int
          The current abundance class of the threatened species.
      s : float
          The state-independent probability of the population staying in its
          current abundance class.
      r : float
          The probability the population moves up one abundance class, assuming
          it is not staying in its current state. ``r`` depends on ``F``, the
          time in years since the last fire.
      fire : bool
          True if there has been a fire in the current year, otherwise False.
      
      Returns
      -------
      x : int
          The new abundance class of the threatened species.