code: def traptransit_lhood(pars, ts, fs, sigs, maxslope=MAXSLOPE):
      
      if pars[0] < 0 or pars[1] < 0 or pars[2] < 2 or pars[2] > maxslope:
          return -np.inf
  
      fmod = traptransit(ts, pars)
      tot = 0
      for i in range(len(ts)):
          tot += -0.5*(fmod[i] - fs[i])*(fmod[i] - fs[i]) / (sigs[i]*sigs[i])
          #tot += np.log(1./pars[2]) #logflat prior on slope
  
      return tot
docs: Params: depth, duration, slope, t0