training: datasets only in prev [], only in new []; differing: ['INPUTS/BoostedJets/fj_tau21', 'INPUTS/BoostedJets/fj_tau32']
   fj_tau21: prev median 0.488 -> new 0.492; frac >=0.95 0.0389 -> 0.0001; frac new<=prev 0.5343
   fj_tau32: prev median 0.784 -> new 0.766; frac >=0.95 0.0725 -> 0.0017; frac new<=prev 0.6283
   new settings nsubjettiness: beta=1.0, axes=onepass_kt git_sha b05a2190a55569c801e6aed2d0b08e1731dceaad
testing: datasets only in prev [], only in new []; differing: ['INPUTS/BoostedJets/fj_tau21', 'INPUTS/BoostedJets/fj_tau32']
   fj_tau21: prev median 0.474 -> new 0.482; frac >=0.95 0.0374 -> 0.0000; frac new<=prev 0.5344
   fj_tau32: prev median 0.788 -> new 0.766; frac >=0.95 0.0751 -> 0.0007; frac new<=prev 0.6375
   new settings nsubjettiness: beta=1.0, axes=onepass_kt git_sha b05a2190a55569c801e6aed2d0b08e1731dceaad