code: def lognoiserate(self, trigs):
          
          alphai, ratei, thresh = self.find_fits(trigs)
          newsnr = self.get_newsnr(trigs)
          # alphai is constant of proportionality between single-ifo newsnr and
          #  negative log noise likelihood in given template
          # ratei is rate of trigs in given template compared to average
          # thresh is stat threshold used in given ifo
          lognoisel = - alphai * (newsnr - thresh) + numpy.log(alphai) + \
                        numpy.log(ratei)
          return numpy.array(lognoisel, ndmin=1, dtype=numpy.float32)
docs: Calculate the log noise rate density over single-ifo newsnr
  
          Read in single trigger information, make the newsnr statistic
          and rescale by the fitted coefficients alpha and rate