code: def calc_nfalse(d):
      
  
      dtfactor = n.sum([1./i for i in d['dtarr']])    # assumes dedisperse-all algorithm
      ntrials = d['readints'] * dtfactor * len(d['dmarr']) * d['npixx'] * d['npixy']
      qfrac = 1 - (erf(d['sigma_image1']/n.sqrt(2)) + 1)/2.
      nfalse = int(qfrac*ntrials)
      return nfalse
docs: Calculate the number of thermal-noise false positives per segment.