Scripts/Landcombsch.run

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Landcombsch
Author: Santiago A. Catalano.
Version: 1.0.
For: not provided.
Arguments: not provided.
Notes:
Example: not provided.
Script
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Landcombsch.run macro=;


 sil-con ; quote *
 This script allows running tree seaches combining landmark data 
 with other sources of evidence. Each replicate starts from a Wagner
 tree (RAS) and is followed by TBR. Only a single optimal tree is kept in memory.   

 You should specify one argument: 
 1st = stength ofthe run: modifies the number of replicates and
    precision in landmark optimization
    (0: lowest (fast) , 4: highest (slow). Default = 0) 
 

if (argnumber < 1)

sil-con ;quote * Ups... You forgot the arguments! 
 1st = stength ofthe run: modifies the number of replicates and
     precision in landmark optimization
     (0: lowest (fast) , 4: highest (slow). Default = 0) 

proc/ ; end tsave *all_trees.tre ; ts/ ; var: best_scor curr_scor rounds repls bescor bestre arbol escor level fact


sil=all ; lm lowmem ; macreport - ; report - ; tsave *all_trees.tre ; k0 ; if ( argnumber > 0 )

  set level %1 ;

if ('level' == 0)

set repls 1 ;

lm notermpoints; lm cell 5 nest 0 ; lm iter ; end if ('level' == 1) set repls 3 ; lm notermpoints; lm cell 5 nest 1 2 ; lm iter ; end if ('level' == 2) set repls 3 ; lm termpoints; lm cell 5 nest 3 2 ; lm iter ; end if ('level' == 3) set repls 5 ; lm termpoints; lm cell 8 nest 4 2 ; lm iter ; end if ('level' == 4) set repls 5 ; lm termpoints; lm cell 10 nest 8 2 ; lm iter ;

      end

else

set repls 1 ; /* change here the number of replicates to do */

end loop 0 ('repls'-1)

rseed 0 ;
ra 1 ;
set best_scor lmscore [ 0 ] ;  
set best_scor ('best_scor' + score [0] );
macfloat 4 ;
report - ; 
set rounds 1 ; 

tbrit 0

  progress percswap 100 Replicate #1 of 'repls' Score 'best_scor' ; 
  progress= ; 
  set rounds ++ ; 
  set curr_scor lmscore [ 0 ] + score [0];
  
  if ( 'curr_scor' < 'best_scor' )
   set best_scor 'curr_scor' ;
   resetswap ;
  end

stop

save ; 

end

sil=all ; 
k0 ; 

stop ; ts/ ; p all_trees.tre ;

set bescor 100000 ;

loop=ar 0 ('repls'-1)

 set arbol #ar ; 
 set escor lmscore ['arbol']  ;
 set escor ('escor' + score [0]) ;  
if ('escor' < 'bescor' )
 set bescor 'escor' ;
 set bestre 'arbol' ;   
end
stop 

tsave *best_tree.tre ; tch 'bestre' ; save ; ts/;

lquote= ; lquote [ ;

sil-buff ; quote * Best tree = replicate 'bestre'

Score = 'bescor' 
Optimal tree kept in memory and sent to  best_tree.tre file   
Best tree of each run sent to all_trees.tre file; 

progress/ ; sil=all ; report-;

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