#NEXUS

[! Output from rid3-paup using the data matrix from data.nex
and starting tree from data.nex

The following settings were used for the analysis:

org.cipres.recidcm3 Parameters:
    SetTreeDecompModule=*,IDL:CipresIDL_api1/TreeDecompose:1.0,org.cipres.dcm3,Roshan DCM
    SetLargeTreeInferenceModule=*,IDL:CipresIDL_api1/TreeImprove:1.0,org.cipres.paup-wrap,Python wrapper around PAUP's HSearch command (using parsimony). file-based io.
    SetSmallTreeInferenceModule=*,IDL:CipresIDL_api1/TreeImprove:1.0,org.cipres.paup-wrap,Python wrapper around PAUP's HSearch command (using parsimony). file-based io.
    SetTreeRefineModule=*,IDL:CipresIDL_api1/TreeRefine:1.0,org.cipres.random-refine,Python implementation of a random refinement of polytomies (Random seed hard-coded for debugging purposes)
    SetTreeMergeModule=*,IDL:CipresIDL_api1/TreeMerge:1.0,org.cipres.PhycasSCMTreeMerge,C++ implementation of SCM (Yu Fan and Paul Lewis)
    SetMaxTaxaSubsetPercent=50;
    SetMaxIterations=10;
    ignoreStartEdgeLen=no;

Tree Decomposer Module Parameters:
    BreakTies=yes;
    SEED=0;

Large Tree Inference Module Parameters:
    default hsearch swap=tbr multrees=no timelimit=3600 ;

Small Tree Inference Module Parameters:
    default hsearch swap=tbr multrees=no [paup.Wrap.n.ratchet.reps=5] [paup.Wrap.ratchet.prop=0.25] [paup.Wrap.ratchet.seed=0] ;

]

BEGIN TAXA;
      Dimensions ntax=12;
      Taxlabels a b c d e f g u v x y t ;
END;

BEGIN TREES;
   Translate
      1   a,
      2   b,
      3   c,
      4   d,
      5   e,
      6   f,
      7   g,
      8   u,
      9   v,
      10   x,
      11   y,
      12   t;

[Starting Tree(s)]
  Tree rep.1[Score=UNSCORED] = [&U]((((1:.1,2:1):1,(12:3.2,7:1):2):1,(3:2,4:1):1):1,(((5:1,6:1):1,8:1):1,9:1.2,(10:0.2,11:1):1):1);

[Result Tree(s)]
  Tree 'Iteration 1 (0h:0m:9s) PAUP 1'[Score=331] = [&U](1:23.0,(2:25.0,(3:15.0,((4:4.0,5:8.0):16.0,(11:20.0,12:20.0):40.0):8.0):11.0):7.0,((((6:0,7:13.0):15.0,8:6.0):19.0,9:29.0):16.0,10:22.0):14.0);
  Tree 'Iteration 2 (0h:0m:11s) PAUP 1'[Score=331] = [&U](1:23.0,2:25.0,((3:15.0,((4:4.0,5:8.0):16.0,(11:20.0,12:20.0):40.0):8.0):8.0,((((6:0,7:13.0):15.0,8:6.0):19.0,9:29.0):15.0,10:23.0):13.0):11.0);
  Tree 'Iteration 3 (0h:0m:12s) PAUP 1'[Score=331] = [&U](1:23.0,(2:26.0,(3:16.0,(4:3.0,5:9.0):21.0):10.0):6.0,((((6:0,7:13.0):10.0,8:11.0):16.0,(9:29.0,(11:20.0,12:20.0):42.0):10.0):13.0,10:21.0):12.0);
  Tree 'Iteration 4 (0h:0m:13s) PAUP 1'[Score=331] = [&U](1:23.0,(2:26.0,(3:16.0,(4:3.0,5:9.0):21.0):10.0):6.0,((((6:0,7:13.0):10.0,8:11.0):16.0,(9:29.0,(11:20.0,12:20.0):42.0):10.0):13.0,10:21.0):12.0);
  Tree 'Iteration 5 (0h:0m:14s) PAUP 1'[Score=331] = [&U](1:23.0,(2:26.0,(3:16.0,(4:3.0,5:9.0):21.0):10.0):6.0,((((6:0,7:13.0):10.0,8:11.0):16.0,(9:29.0,(11:20.0,12:20.0):42.0):10.0):13.0,10:21.0):12.0);
  Tree 'Iteration 6 (0h:0m:14s) PAUP 1'[Score=331] = [&U](1:23.0,(2:26.0,(3:16.0,(4:3.0,5:9.0):21.0):10.0):6.0,((((6:0,7:13.0):10.0,8:11.0):16.0,(9:29.0,(11:20.0,12:20.0):42.0):10.0):13.0,10:21.0):12.0);
  Tree 'Iteration 7 (0h:0m:15s) PAUP 1'[Score=331] = [&U](1:23.0,(2:26.0,(3:16.0,(4:3.0,5:9.0):21.0):10.0):6.0,((((6:0,7:13.0):10.0,8:11.0):16.0,(9:29.0,(11:20.0,12:20.0):42.0):10.0):13.0,10:21.0):12.0);
  Tree 'Iteration 8 (0h:0m:16s) PAUP 1'[Score=331] = [&U](1:23.0,(2:26.0,(3:16.0,(4:3.0,5:9.0):21.0):10.0):6.0,((((6:0,7:13.0):10.0,8:11.0):16.0,(9:29.0,(11:20.0,12:20.0):42.0):10.0):13.0,10:21.0):12.0);
  Tree 'Iteration 9 (0h:0m:19s) PAUP 1'[Score=331] = [&U](1:23.0,(2:26.0,(3:16.0,(4:3.0,5:9.0):21.0):10.0):6.0,((((6:0,7:13.0):10.0,8:11.0):16.0,(9:29.0,(11:20.0,12:20.0):42.0):10.0):13.0,10:21.0):12.0);
  Tree 'Iteration 10 (0h:0m:20s) PAUP 1'[Score=331] = [&U](1:23.0,(2:26.0,(3:16.0,(4:3.0,5:9.0):21.0):10.0):6.0,((((6:0,7:13.0):10.0,8:11.0):16.0,(9:29.0,(11:20.0,12:20.0):42.0):10.0):13.0,10:21.0):12.0);
END;