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COSC-4P82-Final-Project/lib/lilgp/kernel_mod/gp.c

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/* lil-gp Genetic Programming System, version 1.0, 11 July 1995
* Copyright (C) 1995 Michigan State University
*
* This program is free software; you can redistribute it and/or modify
* it under the terms of version 2 of the GNU General Public License as
* published by the Free Software Foundation.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program; if not, write to the Free Software
* Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
*
* Douglas Zongker (zongker@isl.cps.msu.edu)
* Dr. Bill Punch (punch@isl.cps.msu.edu)
*
* Computer Science Department
* A-714 Wells Hall
* Michigan State University
* East Lansing, Michigan 48824
* USA
*
*/
#include <lilgp.h>
popstats *run_stats;
saved_ind *saved_head, *saved_tail;
#if !defined(POSIX_MT) && !defined(SOLARIS_MT)
globaldata global_g;
#else
int numthreads = 0;
struct thread_param_t {
population *pop;
int startidx;
int endidx;
globaldata g;
};
#ifdef POSIX_MT
#include <pthread.h>
static pthread_key_t g_key;
static pthread_attr_t pthread_attr;
#endif
#ifdef SOLARIS_MT
#include <thread.h>
static thread_key_t g_key;
#endif
#endif /* !defined(POSIX_MT) && !defined(SOLARIS_MT) */
/* run_gp()
*
* the whole enchilada. runs, from generation startgen, using population
* mpop. accumulates time spent evaluating and breeding in t_eval and t_breed.
*/
void run_gp ( multipop *mpop, int startgen,
event *t_eval, event *t_breed, int startfromcheckpoint )
{
char *param;
int gen;
int maxgen;
int exch_gen;
int i, j;
int checkinterval;
char *checkfileformat;
char *checkfilename = NULL;
event start, end, diff;
int term = 0;
int stt_interval = 0;
int bestn;
if ( !startfromcheckpoint )
{
/* get the number of top individuals to track. */
bestn = atoi ( get_parameter ( "output.bestn" ) );
if ( bestn < 1 )
{
error ( E_WARNING, "\"output.bestn\" must be at least 1. defaulting to 1." );
bestn = 1;
}
/* allocate statistics for overall run. */
run_stats = (popstats *)MALLOC ( (mpop->size+1)*sizeof ( popstats ) );
for ( i = 0; i < mpop->size+1; ++i )
{
run_stats[i].bestn = bestn;
run_stats[i].size = -1;
}
/* initialize the linked list of saved individuals. */
saved_head = (saved_ind *)MALLOC ( sizeof ( saved_ind ) );
saved_head->ind = NULL;
saved_head->refcount = 0;
saved_head->next = NULL;
saved_tail = saved_head;
}
/* get the maximum number of generations. */
param = get_parameter ( "max_generations" );
if ( param == NULL )
error ( E_FATAL_ERROR,
"no value specified for \"max_generations\"." );
maxgen = atoi ( param );
if ( maxgen <= 0 )
error ( E_FATAL_ERROR,
"\"max_generations\" must be greater than zero." );
/* get the interval for subpopulation exchanges, if there is more than
one subpopulation. */
if ( mpop->size > 1 )
{
param = get_parameter ( "multiple.exch_gen" );
if ( param == NULL )
error ( E_FATAL_ERROR,
"no value specified for \"multiple.exch_gen\"." );
exch_gen = atoi ( param );
if ( exch_gen <= 0 )
error ( E_FATAL_ERROR,
"\"multiple.exch_gen\" must be greater than zero." );
}
/* get the interval for doing checkpointing. */
param = get_parameter ( "checkpoint.interval" );
if ( param == NULL )
/* checkpointing disabled. */
checkinterval = -1;
else
checkinterval = atoi ( param );
/* get the format string for the checkpoint filenames. */
checkfileformat = get_parameter ( "checkpoint.filename" );
checkfilename = (char *)MALLOC ( strlen ( checkfileformat ) + 50 );
/* get the interval for writing information to the .stt file. */
stt_interval = atoi ( get_parameter ( "output.stt_interval" ) );
if ( stt_interval < 1 )
{
error(E_FATAL_ERROR,
"\"output.stt_interval\" must be greater than zero.");
exit(1);
}
oputs ( OUT_SYS, 10, "\n\nstarting evolution.\n" );
/* print out how often we'll be doing checkpointing. */
if ( checkinterval > 0 )
oprintf ( OUT_SYS, 20,
"checkpointing will be done every %d generations and "\
"after the last generation.\n", checkinterval );
else if ( checkinterval == 0 )
oprintf ( OUT_SYS, 20,
"checkpointing will be done only after the last "\
"generation.\n" );
else
oprintf ( OUT_SYS, 20,
"no checkpointing will be done.\n" );
/* the big loop. */
for ( gen = startgen; gen <= maxgen && !term; ++gen )
{
oprintf ( OUT_SYS, 20,
"=== generation %d.\n", gen );
/* unless this is the first generation after loading a checkpoint
file... */
if ( ! ( startfromcheckpoint && gen == startgen ) )
{
/* evaluate the population. */
event_mark ( &start );
for ( i = 0; i < mpop->size; ++i )
evaluate_pop ( mpop->pop[i] );
event_mark ( &end );
event_diff ( &diff, &start, &end );
#ifdef TIMING_AVAILABLE
oprintf ( OUT_SYS, 40, " evaluation complete. (%s)\n",
event_string ( &diff ) );
#else
oprintf ( OUT_SYS, 40, " evaluation complete.\n" );
#endif
event_accum ( t_eval, &diff );
/* calculate and print statistics. returns 1 if user termination
criterion was met, 0 otherwise. */
term = generation_information ( gen, mpop, stt_interval,
run_stats[0].bestn );
if ( term )
oprintf ( OUT_SYS, 30, "user termination criterion met.\n" );
flush_output_streams();
}
/** write a checkpoint file if checkinterval is non-negative and:
we've reached the last generation, or
the user termination criterion has been met, or
we've reached the specified checkpoint interval. **/
if ( checkinterval >= 0 &&
(gen == maxgen || term ||
(checkinterval>0 && gen>startgen && (gen%checkinterval)==0)) )
{
sprintf ( checkfilename, checkfileformat, gen );
write_checkpoint ( gen, mpop, checkfilename );
}
/** if this is not the last generation and the user criterion hasn't
been met, then do breeding. **/
if ( gen != maxgen && !term )
{
/** exchange subpops if it's time. **/
if ( mpop->size>1 && gen && (gen%exch_gen)==0 )
{
exchange_subpopulations ( mpop );
oprintf ( OUT_SYS, 10,
" subpopulation exchange complete.\n" );
}
/* breed the new population. */
event_mark ( &start );
for ( i = 0; i < mpop->size; ++i )
mpop->pop[i] = change_population ( mpop->pop[i], mpop->bpt[i] );
event_mark ( &end );
event_diff ( &diff, &start, &end );
/* call the application end-of-breeding callback. */
app_end_of_breeding ( gen, mpop );
#ifdef TIMING_AVAILABLE
oprintf ( OUT_SYS, 30, " breeding complete. (%s)\n",
event_string ( &diff ) );
#else
oprintf ( OUT_SYS, 30, " breeding complete.\n" );
#endif
event_accum ( t_breed, &diff );
}
/* free unused ERCs. */
ephem_const_gc();
flush_output_streams();
}
/** free up a lot of stuff before returning. */
if ( checkfilename )
FREE ( checkfilename );
ephem_const_gc();
for ( i = 0; i < mpop->size+1; ++i )
{
for ( j = 0; j < run_stats[i].bestn; ++j )
--run_stats[i].best[j]->refcount;
FREE ( run_stats[i].best );
}
FREE ( run_stats );
saved_individual_gc();
FREE ( saved_head );
}
/* generation_information()
*
* calculates and prints population statistics.
*/
int generation_information ( int gen, multipop *mpop, int stt_interval,
int bestn )
{
int i, j;
int newbest;
static int fd = -1;
popstats *gen_stats;
int ret = 0;
FILE *bout, *hout;
/* number of decimal digits to use when printing fitness values. */
if ( fd == -1 )
fd = atoi ( get_parameter ( "output.digits" ) );
/* allocate stats records for the current generation. */
gen_stats = (popstats *)MALLOC ( (mpop->size+1)*sizeof ( popstats ) );
for ( i = 0; i < mpop->size+1; ++i )
{
gen_stats[i].bestn = bestn;
gen_stats[i].size = -1;
}
oprintf ( OUT_GEN, 90, "=== GENERATION %d ===\n", gen );
oprintf ( OUT_PRG, 90, "=== GENERATION %d ===\n", gen );
/* for each subpopulation... */
for ( i = 0; i < mpop->size; ++i )
{
/* calculate stats for subpopulation. */
calculate_pop_stats ( gen_stats+i+1, mpop->pop[i], gen, i );
/* accumulate that into stats for whole popluation... */
accumulate_pop_stats ( gen_stats, gen_stats+i+1 );
/* ...and stats for this subpopulation over the whole run. */
accumulate_pop_stats ( run_stats+i+1, gen_stats+i+1 );
/* if only one subpop, don't print out the subpop stuff. */
if ( mpop->size == 1 )
continue;
/** print much stuff to .gen, .prg, and .stt files. */
if ( test_detail_level ( 90 ) )
{
oprintf ( OUT_GEN, 90, " subpopulation %d:\n", i+1 );
oprintf ( OUT_GEN, 90, " generation:\n" );
oprintf ( OUT_GEN, 90, " mean: nodes: %.3lf (%d-%d); depth: %.3lf (%d-%d)\n",
(double)gen_stats[i+1].totalnodes/gen_stats[i+1].size,
gen_stats[i+1].minnodes, gen_stats[i+1].maxnodes,
(double)gen_stats[i+1].totaldepth/gen_stats[i+1].size,
gen_stats[i+1].mindepth, gen_stats[i+1].maxdepth );
oprintf ( OUT_GEN, 90, " best: nodes: %d; depth: %d\n",
gen_stats[i+1].bestnodes, gen_stats[i+1].bestdepth );
oprintf ( OUT_GEN, 90, " worst: nodes: %d; depth: %d\n",
gen_stats[i+1].worstnodes, gen_stats[i+1].worstdepth );
oprintf ( OUT_GEN, 90, " run: (%d trees)\n",
run_stats[i+1].size );
oprintf ( OUT_GEN, 90, " mean: nodes: %.3lf (%d-%d); depth: %.3lf (%d-%d)\n",
(double)run_stats[i+1].totalnodes/run_stats[i+1].size,
run_stats[i+1].minnodes, run_stats[i+1].maxnodes,
(double)run_stats[i+1].totaldepth/run_stats[i+1].size,
run_stats[i+1].mindepth, run_stats[i+1].maxdepth );
oprintf ( OUT_GEN, 90, " best: nodes: %d; depth: %d\n",
run_stats[i+1].bestnodes, run_stats[i+1].bestdepth );
oprintf ( OUT_GEN, 90, " worst: nodes: %d; depth: %d\n",
run_stats[i+1].worstnodes, run_stats[i+1].worstdepth );
}
if ( test_detail_level ( 90 ) )
{
oprintf ( OUT_PRG, 90, " subpopulation %d:\n", i+1 );
oprintf ( OUT_PRG, 90, " generation stats:\n" );
oprintf ( OUT_PRG, 90, " mean: hits: %.3lf (%d-%d); standardized fitness: %.*lf\n",
(double)gen_stats[i+1].totalhits/gen_stats[i+1].size,
gen_stats[i+1].minhits, gen_stats[i+1].maxhits,
fd, (double)gen_stats[i+1].totalfit/gen_stats[i+1].size );
oprintf ( OUT_PRG, 90, " best: hits: %d; standardized fitness: %.*lf\n",
gen_stats[i+1].besthits, fd,
(double)gen_stats[i+1].bestfit );
oprintf ( OUT_PRG, 90, " worst: hits: %d; standardized fitness: %.*lf\n",
gen_stats[i+1].worsthits, fd,
(double)gen_stats[i+1].worstfit );
oprintf ( OUT_PRG, 90, " run stats: (%d trees)\n",
run_stats[i+1].size );
oprintf ( OUT_PRG, 90, " mean: hits: %.3lf (%d-%d); standardized fitness: %.*lf\n",
(double)run_stats[i+1].totalhits/run_stats[i+1].size,
run_stats[i+1].minhits, run_stats[i+1].maxhits,
fd, (double)run_stats[i+1].totalfit/run_stats[i+1].size );
oprintf ( OUT_PRG, 90, " best: hits: %d; standardized fitness: %.*lf; generation: %d\n",
run_stats[i+1].besthits, fd, (double)run_stats[i+1].bestfit,
run_stats[i+1].bestgen );
oprintf ( OUT_PRG, 90, " worst: hits: %d; standardized fitness: %.*lf; generation: %d\n",
run_stats[i+1].worsthits, fd,
(double)run_stats[i+1].worstfit, run_stats[i+1].worstgen );
}
if ( gen%stt_interval == 0 )
{
oprintf ( OUT_STT, 50, "%d %d ", gen, i+1 );
oprintf ( OUT_STT, 50, "%.*lf %.*lf %.*lf ",
fd, gen_stats[i+1].totalfit/gen_stats[i+1].size,
fd, gen_stats[i+1].bestfit,
fd, gen_stats[i+1].worstfit );
oprintf ( OUT_STT, 50, "%.3lf %.3lf %d %d %d %d ",
(double)gen_stats[i+1].totalnodes/gen_stats[i+1].size,
(double)gen_stats[i+1].totaldepth/gen_stats[i+1].size,
gen_stats[i+1].bestnodes, gen_stats[i+1].bestdepth,
gen_stats[i+1].worstnodes, gen_stats[i+1].worstdepth );
oprintf ( OUT_STT, 50, "%.*lf %.*lf %.*lf ",
fd, run_stats[i+1].totalfit/run_stats[i+1].size,
fd, run_stats[i+1].bestfit,
fd, run_stats[i+1].worstfit );
oprintf ( OUT_STT, 50, "%.3lf %.3lf %d %d %d %d ",
(double)run_stats[i+1].totalnodes/run_stats[i+1].size,
(double)run_stats[i+1].totaldepth/run_stats[i+1].size,
run_stats[i+1].bestnodes, run_stats[i+1].bestdepth,
run_stats[i+1].worstnodes, run_stats[i+1].worstdepth );
oprintf ( OUT_STT, 50, "\n" );
}
}
/* merge stats for current generation into overall run stats. */
newbest = accumulate_pop_stats ( run_stats, gen_stats );
/** more printing. **/
if ( test_detail_level ( 90 ) )
{
oprintf ( OUT_GEN, 90, " total population:\n" );
oprintf ( OUT_GEN, 90, " generation:\n" );
oprintf ( OUT_GEN, 90, " mean: nodes: %.3lf (%d-%d); depth: %.3lf (%d-%d)\n",
(double)gen_stats[0].totalnodes/gen_stats[0].size,
gen_stats[0].minnodes, gen_stats[0].maxnodes,
(double)gen_stats[0].totaldepth/gen_stats[0].size,
gen_stats[0].mindepth, gen_stats[0].maxdepth );
oprintf ( OUT_GEN, 90, " best: nodes: %d; depth: %d\n",
gen_stats[0].bestnodes, gen_stats[0].bestdepth );
oprintf ( OUT_GEN, 90, " worst: nodes: %d; depth: %d\n",
gen_stats[0].worstnodes, gen_stats[0].worstdepth );
oprintf ( OUT_GEN, 90, " run: (%d trees)\n",
run_stats[0].size );
oprintf ( OUT_GEN, 90, " mean: nodes: %.3lf (%d-%d); depth: %.3lf (%d-%d)\n",
(double)run_stats[0].totalnodes/run_stats[0].size,
run_stats[0].minnodes, run_stats[0].maxnodes,
(double)run_stats[0].totaldepth/run_stats[0].size,
run_stats[0].mindepth, run_stats[0].maxdepth );
oprintf ( OUT_GEN, 90, " best: nodes: %d; depth: %d\n",
run_stats[0].bestnodes, run_stats[0].bestdepth );
oprintf ( OUT_GEN, 90, " worst: nodes: %d; depth: %d\n",
run_stats[0].worstnodes, run_stats[0].worstdepth );
}
if ( test_detail_level ( 90 ) )
{
oprintf ( OUT_PRG, 90, " total population:\n" );
oprintf ( OUT_PRG, 90, " generation stats:\n" );
oprintf ( OUT_PRG, 90, " mean: hits: %.3lf (%d-%d); standardized fitness: %.*lf\n",
(double)gen_stats[0].totalhits/gen_stats[0].size,
gen_stats[0].minhits, gen_stats[0].maxhits,
fd, (double)gen_stats[0].totalfit/gen_stats[0].size );
oprintf ( OUT_PRG, 90, " best: hits: %d; standardized fitness: %.*lf\n",
gen_stats[0].besthits, fd, (double)gen_stats[0].bestfit );
oprintf ( OUT_PRG, 90, " worst: hits: %d; standardized fitness: %.*lf\n",
gen_stats[0].worsthits, fd, (double)gen_stats[0].worstfit );
oprintf ( OUT_PRG, 90, " run stats: (%d trees)\n",
run_stats[0].size );
oprintf ( OUT_PRG, 90, " mean: hits: %.3lf (%d-%d); standardized fitness: %.*lf\n",
(double)run_stats[0].totalhits/run_stats[0].size,
run_stats[0].minhits, run_stats[0].maxhits,
fd, (double)run_stats[0].totalfit/run_stats[0].size );
oprintf ( OUT_PRG, 90, " best: hits: %d; standardized fitness: %.*lf; generation: %d\n",
run_stats[0].besthits, fd, (double)run_stats[0].bestfit,
run_stats[0].bestgen );
oprintf ( OUT_PRG, 90, " worst: hits: %d; standardized fitness: %.*lf; generation: %d\n",
run_stats[0].worsthits, fd, (double)run_stats[0].worstfit,
run_stats[0].worstgen );
}
if ( gen%stt_interval == 0 )
{
if ( test_detail_level ( 50 ) )
{
oprintf ( OUT_STT, 50, "%d 0 ", gen );
oprintf ( OUT_STT, 50, "%.*lf %.*lf %.*lf ",
fd, gen_stats[0].totalfit/gen_stats[0].size,
fd, gen_stats[0].bestfit, fd, gen_stats[0].worstfit );
oprintf ( OUT_STT, 50, "%.3lf %.3lf %d %d %d %d ",
(double)gen_stats[0].totalnodes/gen_stats[0].size,
(double)gen_stats[0].totaldepth/gen_stats[0].size,
gen_stats[0].bestnodes, gen_stats[0].bestdepth,
gen_stats[0].worstnodes, gen_stats[0].worstdepth );
oprintf ( OUT_STT, 50, "%.*lf %.*lf %.*lf ",
fd, run_stats[0].totalfit/run_stats[0].size,
fd, run_stats[0].bestfit, fd, run_stats[0].worstfit );
oprintf ( OUT_STT, 50, "%.3lf %.3lf %d %d %d %d ",
(double)run_stats[0].totalnodes/run_stats[0].size,
(double)run_stats[0].totaldepth/run_stats[0].size,
run_stats[0].bestnodes, run_stats[0].bestdepth,
run_stats[0].worstnodes, run_stats[0].worstdepth );
oprintf ( OUT_STT, 50, "\n" );
}
}
/* rewrite the .bst file, and append to the .his file. */
output_stream_open ( OUT_BST );
oprintf ( OUT_BST, 10, "=== BEST-OF-RUN ===\n" );
oprintf ( OUT_BST, 10, " generation: %d\n",
run_stats[0].bestgen );
if ( mpop->size > 1 )
oprintf ( OUT_BST, 10, " subpopulation: %d\n",
run_stats[0].bestpop+1 );
oprintf ( OUT_BST, 10, " nodes: %d\n",
run_stats[0].bestnodes );
oprintf ( OUT_BST, 10, " depth: %d\n",
run_stats[0].bestdepth );
oprintf ( OUT_BST, 10, " hits: %d\n",
run_stats[0].besthits );
oprintf ( OUT_HIS, 10, "=== BEST-OF-RUN ===\n" );
oprintf ( OUT_HIS, 10, " current generation: %d\n", gen );
oprintf ( OUT_HIS, 10, " generation: %d\n",
run_stats[0].bestgen );
if ( mpop->size > 1 )
oprintf ( OUT_HIS, 10, " subpopulation: %d\n",
run_stats[0].bestpop+1 );
oprintf ( OUT_HIS, 10, " nodes: %d\n",
run_stats[0].bestnodes );
oprintf ( OUT_HIS, 10, " depth: %d\n",
run_stats[0].bestdepth );
oprintf ( OUT_HIS, 10, " hits: %d\n",
run_stats[0].besthits );
/* retrieve the (FILE *) for the .bst and .his files, so that
the trees can be printed to them. */
bout = output_filehandle ( OUT_BST );
hout = output_filehandle ( OUT_HIS );
if ( run_stats[0].bestn == 1 )
{
oprintf ( OUT_BST, 20, "TOP INDIVIDUAL:\n\n" );
oprintf ( OUT_HIS, 20, "TOP INDIVIDUAL:\n\n" );
}
else
{
oprintf ( OUT_BST, 20, "TOP %d INDIVIDUALS (in order):\n\n",
run_stats[0].bestn );
oprintf ( OUT_HIS, 20, "TOP %d INDIVIDUALS (in order):\n\n",
run_stats[0].bestn );
}
for ( i = 0; i < run_stats[0].bestn; ++i )
{
oprintf ( OUT_BST, 20, "\n\n-- #%d --\n", i+1 );
oprintf ( OUT_BST, 20, " hits: %d\n",
run_stats[0].best[i]->ind->hits );
oprintf ( OUT_BST, 20, " raw fitness: %.*lf\n",
fd, run_stats[0].best[i]->ind->r_fitness );
oprintf ( OUT_BST, 20, " standardized fitness: %.*lf\n",
fd, run_stats[0].best[i]->ind->s_fitness );
oprintf ( OUT_BST, 20, " adjusted fitness: %.*lf\n",
fd, run_stats[0].best[i]->ind->a_fitness );
oprintf ( OUT_HIS, 20, "\n\n-- #%d --\n", i+1 );
oprintf ( OUT_HIS, 20, " hits: %d\n",
run_stats[0].best[i]->ind->hits );
oprintf ( OUT_HIS, 20, " raw fitness: %.*lf\n",
fd, run_stats[0].best[i]->ind->r_fitness );
oprintf ( OUT_HIS, 20, " standardized fitness: %.*lf\n",
fd, run_stats[0].best[i]->ind->s_fitness );
oprintf ( OUT_HIS, 20, " adjusted fitness: %.*lf\n",
fd, run_stats[0].best[i]->ind->a_fitness );
/* print the tree to both files here. */
if ( test_detail_level ( 20 ) )
{
pretty_print_individual ( run_stats[0].best[i]->ind, bout );
pretty_print_individual ( run_stats[0].best[i]->ind, hout );
}
}
/* call the end-of-evaluation callback. returns 1 if user termination
criterion is met, 0 otherwise. */
ret = app_end_of_evaluation ( gen, mpop, newbest, gen_stats, run_stats );
/* close the .bst file. */
output_stream_close ( OUT_BST );
/* free stats structures for current generation. */
for ( i = 0; i < mpop->size+1; ++i )
{
for ( j = 0; j < gen_stats[i].bestn; ++j )
--gen_stats[i].best[j]->refcount;
FREE ( gen_stats[i].best );
}
FREE ( gen_stats );
/* deallocate saved individuals that are no longer needed. */
saved_individual_gc();
/* return value the application callback gave us. */
return ret;
}
/* evaluate_pop()
*
* evaluates all the individuals in a population whose cached
* fitness values are invalid.
*/
void evaluate_pop ( population *pop )
{
int i;
#if defined(POSIX_MT) || defined(SOLARIS_MT)
int start, end, inc, err;
struct thread_param_t *t_param;
#endif
#if POSIX_MT
pthread_t *t_ids;
#endif
#ifdef DEBUG
print_individual ( pop->ind, stdout );
#ifdef COEVOLUTION
printf("Can't do COEVOLUTION and DEBUG at the same time, sorry!\n");
#else
app_eval_fitness ( pop->ind );
#endif
exit(0);
#endif
#if !defined(POSIX_MT) && !defined(SOLARIS_MT)
#ifdef COEVOLUTION
if (pop->size % 2)
{
/* It's not even! */
error ( E_FATAL_ERROR, "Population must be even to do COEVOLUTION\n");
}
for ( i = 0; i < pop->size; i+=2)
if ( pop->ind[i].evald != EVAL_CACHE_VALID ||
pop->ind[i+1].evald != EVAL_CACHE_VALID )
app_eval_fitness ( (pop->ind)+i );
#else
for ( i = 0; i < pop->size; ++i )
if ( pop->ind[i].evald != EVAL_CACHE_VALID )
app_eval_fitness ( (pop->ind)+i );
#endif
#else
#if POSIX_MT
t_ids = (pthread_t *)malloc( numthreads * sizeof( pthread_t ));
#endif
t_param = (struct thread_param_t *)malloc( numthreads *
sizeof( struct thread_param_t ));
/* figure out how many pop members per thread */
inc = pop->size / numthreads;
if (pop->size != inc * numthreads) inc++;
start = 0;
for (i=0; i<numthreads; i++) {
end = start + inc;
if (end > pop->size) end = pop->size;
/* setup the paramater to pass */
t_param[i].pop = pop;
t_param[i].startidx = start;
t_param[i].endidx = end;
t_param[i].g = *(get_globaldata());
#ifdef POSIX_MT
err = pthread_create(&t_ids[i], &pthread_attr,
evaluate_pop_chunk, &t_param[i]);
#endif
#ifdef SOLARIS_MT
err = thr_create(NULL, (int)NULL, evaluate_pop_chunk,
&t_param[i], (int)NULL,NULL);
#endif
if (err != 0) {
error ( E_FATAL_ERROR, "cannot create thread");
}
start = end;
}
#ifdef SOLARIS_MT
while (thr_join(NULL, NULL, NULL) == 0);
#endif
#ifdef POSIX_MT
for (i=0; i < numthreads; i++) {
pthread_join( t_ids[i], NULL);
}
#endif
#endif
}
/* calculate_pop_stats()
*
* tabulates stats for a population: fitness and size of best, worst,
* mean, etc. also finds top N individuals and saves them.
*/
void calculate_pop_stats ( popstats *s, population *pop, int gen,
int subpop )
{
int i, j, k, l;
int b;
saved_ind *shp;
individual **temp;
/* allocate a list of the top N individuals. */
s->best = (saved_ind **)MALLOC ( s->bestn *
sizeof ( saved_ind * ) );
temp = (individual **)MALLOC ( (s->bestn+1) * sizeof ( individual * ) );
s->size = pop->size;
/** this is all pretty obvious -- set all the max and min values to the
first individual's values, then go through the population looking for
things that are bigger/smaller/better/worse/etc. **/
s->maxnodes = s->minnodes = s->totalnodes = s->bestnodes = s->worstnodes =
individual_size ( pop->ind+0 );
s->maxdepth = s->mindepth = s->totaldepth = s->bestdepth = s->worstdepth =
individual_depth ( pop->ind+0 );
s->maxhits = s->minhits = s->totalhits = s->besthits = s->worsthits =
pop->ind[0].hits;
s->bestfit = s->worstfit = s->totalfit = pop->ind[0].a_fitness;
temp[0] = pop->ind;
b = 1;
s->bestgen = s->worstgen = gen;
s->bestpop = s->worstpop = subpop;
for ( i = 1; i < s->size; ++i )
{
j = individual_size ( pop->ind+i );
s->totalnodes += j;
if ( j < s->minnodes ) s->minnodes = j;
if ( j > s->maxnodes ) s->maxnodes = j;
k = individual_depth ( pop->ind+i );
s->totaldepth += k;
if ( k < s->mindepth ) s->mindepth = k;
if ( k > s->maxdepth ) s->maxdepth = k;
l = pop->ind[i].hits;
s->totalhits += l;
if ( l < s->minhits ) s->minhits = l;
if ( l > s->maxhits ) s->maxhits = l;
s->totalfit += pop->ind[i].a_fitness;
if ( pop->ind[i].a_fitness > s->bestfit )
{
s->bestfit = pop->ind[i].a_fitness;
s->bestnodes = j;
s->bestdepth = k;
s->besthits = l;
}
else if ( pop->ind[i].a_fitness < s->worstfit )
{
s->worstfit = pop->ind[i].a_fitness;
s->worstnodes = j;
s->worstdepth = k;
s->worsthits = l;
}
/** insert the current individual into the top N list
(if it belongs there). **/
for ( j = b; j > 0; --j )
{
if ( pop->ind[i].a_fitness < temp[j-1]->a_fitness )
break;
temp[j] = temp[j-1];
}
if ( j < s->bestn )
temp[j] = pop->ind+i;
if ( b < s->bestn )
++b;
}
/** now save copies of the individuals in the "temp" list **/
for ( i = 0; i < b; ++i )
{
shp = (saved_ind *)MALLOC ( sizeof ( saved_ind ) );
shp->ind = (individual *)MALLOC ( sizeof ( individual ) );
shp->ind->tr = (tree *)MALLOC ( tree_count * sizeof ( tree ) );
duplicate_individual ( shp->ind, temp[i] );
for ( j = 0; j < tree_count; ++j )
reference_ephem_constants ( shp->ind->tr[j].data, 1 );
shp->refcount = 1;
shp->next = NULL;
saved_tail->next = shp;
saved_tail = shp;
++saved_head->refcount;
s->best[i] = shp;
}
#ifdef DEBUG
printf ( "the best list is:\n" );
for ( j = 0; j < s->bestn; ++j )
printf ( " %08x %lf\n", s->best[j], s->best[j]->ind->a_fitness );
#endif
FREE ( temp );
}
/* accumulate_pop_stats()
*
* this merges the second statistics record into the first, so that it reflects
* the "sum" of the underlying populations. returns 1 if the best individual
* of the first record has changed (that is, if the second record has a better
* best individual.
*/
int accumulate_pop_stats ( popstats *total, popstats *n )
{
int ret = 0;
int i, j, k;
saved_ind **temp;
if ( total->size == -1 )
{
/* if the "total" record is empty, then just copy the second record
into it. */
memcpy ( total, n, sizeof ( popstats ) );
total->best = (saved_ind **)MALLOC ( total->bestn *
sizeof ( saved_ind * ) );
memcpy ( total->best, n->best, total->bestn *
sizeof ( saved_ind * ) );
ret = 1;
}
else
{
/* sum the totals. */
total->size += n->size;
total->totalnodes += n->totalnodes;
total->totaldepth += n->totaldepth;
total->totalhits += n->totalhits;
total->totalfit += n->totalfit;
/* find the maximums. */
if ( n->maxnodes > total->maxnodes ) total->maxnodes = n->maxnodes;
if ( n->maxdepth > total->maxdepth ) total->maxdepth = n->maxdepth;
if ( n->maxhits > total->maxhits ) total->maxhits = n->maxhits;
/* find the minimums. */
if ( n->minnodes < total->minnodes ) total->minnodes = n->minnodes;
if ( n->mindepth < total->mindepth ) total->mindepth = n->mindepth;
if ( n->minhits < total->minhits ) total->minhits = n->minhits;
/* find the best individual's numbers. */
if ( n->bestfit > total->bestfit )
{
total->bestfit = n->bestfit;
total->bestnodes = n->bestnodes;
total->bestdepth = n->bestdepth;
total->besthits = n->besthits;
total->bestgen = n->bestgen;
total->bestpop = n->bestpop;
ret = 1;
}
/* find the worst individual's numbers. */
if ( n->worstfit < total->worstfit )
{
total->worstfit = n->worstfit;
total->worstnodes = n->worstnodes;
total->worstdepth = n->worstdepth;
total->worsthits = n->worsthits;
total->worstgen = n->worstgen;
total->worstpop = n->worstpop;
}
#ifdef DEBUG
printf ( "total list:\n" );
for ( i = 0; i < total->bestn; ++i )
printf ( " %08x %lf\n",
total->best[i], total->best[i]->ind->a_fitness );
printf ( "new list:\n" );
for ( i = 0; i < n->bestn; ++i )
printf ( " %08x %lf\n",
n->best[i], n->best[i]->ind->a_fitness );
#endif
/** here we merge the two "top N" lists into one, discarding
the remaining N individuals. **/
temp = (saved_ind **)MALLOC ( total->bestn *
sizeof ( saved_ind * ) );
j = 0; /* position in "total"s list */
k = 0; /* position in "n"s list */
for ( i = 0; i < total->bestn; ++i )
{
/* if the n list is empty, take from the total list. */
if ( k == -1 )
temp[i] = total->best[j++];
/* if the total list is empty, take from the n list. */
else if ( j == -1 )
{
ret |= (i==0);
temp[i] = n->best[k++];
}
/* if neither list is empty, take the better individual. */
else if ( total->best[j]->ind->a_fitness <
n->best[k]->ind->a_fitness )
{
ret |= (i==0);
temp[i] = n->best[k++];
}
else
temp[i] = total->best[j++];
/* have we run off the end of either list? */
if ( j >= total->bestn )
j = -1;
if ( k >= n->bestn )
k = -1;
}
/* decrement the reference count of the old "best" list. */
for ( i = 0; i < total->bestn; ++i )
--total->best[i]->refcount;
FREE ( total->best );
total->best = temp;
#ifdef DEBUG
printf ( "new total list:\n" );
for ( i = 0; i < total->bestn; ++i )
printf ( " %08x %lf\n",
total->best[i], total->best[i]->ind->a_fitness );
#endif
}
/* increment the reference count of the new "best" list. */
for ( i = 0; i < total->bestn; ++i )
++total->best[i]->refcount;
return ret;
}
/* saved_individual_gc()
*
* go through the list of saved individuals, deleting any which are no longer
* referred to.
*/
void saved_individual_gc ( void )
{
int j;
saved_ind *shp = saved_head->next;
saved_ind *shm = saved_head;
while ( shp )
{
if ( shp->refcount == 0 )
{
/** found one that needs to be deleted. **/
/* dereference its trees' ERCs and delete the trees. */
for ( j = 0; j < tree_count; ++j )
{
reference_ephem_constants ( shp->ind->tr[j].data, -1 );
free_tree ( shp->ind->tr+j );
}
FREE ( shp->ind->tr );
FREE ( shp->ind );
/* cut the record out of the linked list. */
shm->next = shp->next;
if ( saved_tail == shp )
saved_tail = shm;
FREE ( shp );
shp = shm->next;
/* the refcount field of the list head (a dummy node) holds the
size of the list. */
--saved_head->refcount;
}
else
{
/* move down the list. */
shm = shp;
shp = shp->next;
}
}
}
/* read_saved_individuals()
*
* reads the list of saved individuals from a checkpoint file. constructs
* an index translating indices to addresses.
*/
saved_ind ** read_saved_individuals ( ephem_const **eind, FILE *f )
{
char *buffer;
int count;
int i;
saved_ind *p;
saved_ind **sind;
buffer = (char *)MALLOC ( MAXCHECKLINELENGTH );
/* read the number of saved individuals. */
fscanf ( f, "%*s %d\n", &count );
/* allocate the index. */
sind = (saved_ind **)MALLOC ( count * sizeof ( saved_ind * ) );
/* allocate the head of the linked list (a dummy node whose refcount
equals the number of individuals on the list). */
saved_head = (saved_ind *)MALLOC ( sizeof ( saved_ind ) );
saved_head->ind = NULL;
saved_head->refcount = count;
p = saved_head;
for ( i = 0; i < count; ++i )
{
/* allocate the next saved_ind on the list. */
p->next = (saved_ind *)MALLOC ( sizeof ( saved_ind ) );
p = p->next;
/* allocate the individual. */
p->ind = (individual *)MALLOC ( sizeof ( individual ) );
/* make the index entry. */
sind[i] = p;
/* read the refcount. */
fscanf ( f, "%d ", &(p->refcount) );
/* read the individual. */
read_individual ( p->ind, eind, f, buffer );
}
/* mark the end of the list. */
p->next = NULL;
saved_tail = p;
FREE ( buffer );
return sind;
}
/* read_stats_checkpoint()
*
* read the overall run statistics structures from a checkpoint file.
*/
void read_stats_checkpoint ( multipop *mpop, ephem_const **eind, FILE *f )
{
int i, j, k;
saved_ind **sind;
/* read and index the saved individuals list. */
sind = read_saved_individuals ( eind, f );
/* allocate the run_stats array. */
run_stats = (popstats *)MALLOC ( (mpop->size+1)*sizeof ( popstats ) );
for ( i = 0; i < mpop->size+1; ++i )
{
/* read lots of integer values into run_stats. */
fscanf ( f, "%d %d %d %d %d %d %d %d %d %d %d %d %d %d %d %d\n",
&(run_stats[i].size),
&(run_stats[i].maxnodes), &(run_stats[i].minnodes),
&(run_stats[i].totalnodes), &(run_stats[i].bestnodes),
&(run_stats[i].worstnodes),
&(run_stats[i].maxdepth), &(run_stats[i].mindepth),
&(run_stats[i].totaldepth), &(run_stats[i].bestdepth),
&(run_stats[i].worstdepth),
&(run_stats[i].maxhits), &(run_stats[i].minhits),
&(run_stats[i].totalhits), &(run_stats[i].besthits),
&(run_stats[i].worsthits) );
/** double-precision values are stored as hex data to avoid loss
of precision. **/
read_hex_block ( &(run_stats[i].bestfit), sizeof ( double ), f );
fgetc ( f );
read_hex_block ( &(run_stats[i].worstfit), sizeof ( double ), f );
fgetc ( f );
read_hex_block ( &(run_stats[i].totalfit), sizeof ( double ), f );
/* they are also printed as decimal values, for the benefit of human
readers -- skip these fields. */
fscanf ( f, " %*f %*f %*f\n" );
/* read some more integers. */
fscanf ( f, "%d %d %d %d %d ",
&(run_stats[i].bestgen), &(run_stats[i].worstgen),
&(run_stats[i].bestpop), &(run_stats[i].worstpop),
&(run_stats[i].bestn) );
run_stats[i].best = (saved_ind **)MALLOC ( run_stats[i].bestn *
sizeof ( saved_ind * ) );
/** read the indices of the contents of the best array, and look up
the addresses in the index. **/
for ( j = 0; j < run_stats[i].bestn; ++j )
{
fscanf ( f, "%d\n", &k );
run_stats[i].best[j] = sind[k];
}
}
FREE ( sind );
}
/* write_saved_individuals()
*
* writes the linked list of saved individuals to a checkpoint file. returns
* an index for translating saved_ind addresses to integer indices.
*/
saved_ind ** write_saved_individuals ( ephem_index *eind, FILE *f )
{
saved_ind **index;
saved_ind *shp;
int i = 0;
index = (saved_ind **)MALLOC ( saved_head->refcount *
sizeof ( saved_ind * ) );
/* write the count of individuals. */
fprintf ( f, "saved-individual-count: %d\n", saved_head->refcount );
shp = saved_head->next;
/** traverse the linked list. **/
while ( shp )
{
/* write the reference count and individual. */
fprintf ( f, "%d ", shp->refcount );
write_individual ( shp->ind, eind, f );
/* record the address in the index. */
index[i++] = shp;
shp = shp->next;
}
return index;
}
/* write_stats_checkpoint()
*
* write the overall run statistics structures to a checkpoint file.
*/
void write_stats_checkpoint ( multipop *mpop, ephem_index *eind, FILE *f )
{
int i, j, k;
saved_ind **sind;
/* write and index the saved individuals list. */
sind = write_saved_individuals ( eind, f );
for ( i = 0; i < mpop->size+1; ++i )
{
/* write many integer values. */
fprintf ( f, "%d %d %d %d %d %d %d %d %d %d %d %d %d %d %d %d\n",
run_stats[i].size,
run_stats[i].maxnodes, run_stats[i].minnodes,
run_stats[i].totalnodes, run_stats[i].bestnodes,
run_stats[i].worstnodes,
run_stats[i].maxdepth, run_stats[i].mindepth,
run_stats[i].totaldepth, run_stats[i].bestdepth,
run_stats[i].worstdepth,
run_stats[i].maxhits, run_stats[i].minhits,
run_stats[i].totalhits, run_stats[i].besthits,
run_stats[i].worsthits );
/** write double-precision values as hex data. **/
write_hex_block ( &(run_stats[i].bestfit), sizeof ( double ), f );
fputc ( ' ', f );
write_hex_block ( &(run_stats[i].worstfit), sizeof ( double ), f );
fputc ( ' ', f );
write_hex_block ( &(run_stats[i].totalfit), sizeof ( double ), f );
/* also write them as decimal values. */
fprintf ( f, " %f %f %f\n", run_stats[i].bestfit,
run_stats[i].worstfit, run_stats[i].totalfit );
/* write more integers. */
fprintf ( f, "%d %d %d %d %d ",
run_stats[i].bestgen, run_stats[i].worstgen,
run_stats[i].bestpop, run_stats[i].worstpop,
run_stats[i].bestn );
/** write the best array, indexing saved individuals using integers. **/
for ( j = 0; j < run_stats[i].bestn; ++j )
{
/** search the index for the address. **/
for ( k = 0; k < saved_head->refcount; ++k )
if ( run_stats[i].best[j] == sind[k] )
{
/* print the index to the checkpoint file. */
fprintf ( f, " %d", k );
break;
}
/** address was not found in the index. **/
if ( k == saved_head->refcount )
{
/* this shouldn't ever happen. */
fprintf ( f, " -1" );
error ( E_WARNING, "bestn pointer is bad." );
}
}
fputc ( '\n', f );
}
FREE ( sind );
}
#if !defined(POSIX_MT) && !defined(SOLARIS_MT)
/* return the globaldata structure */
globaldata *get_globaldata(void) {
return( &global_g );
}
#else /* continues to end of file */
/* provide each thread with seperate copy of 'g' */
globaldata *get_globaldata(void) {
globaldata *retval;
#ifdef POSIX_MT
retval = pthread_getspecific( g_key );
#endif
#ifdef SOLARIS_MT
thr_getspecific( g_key, (void *)&retval );
#endif
if (retval == NULL) {
error ( E_FATAL_ERROR, "get_globaldata() tried to return NULL");
}
return( retval );
}
/*
* initialize_threading()
*
* Setup the program for multithreading use.
*/
void initialize_threading( void ) {
char *numthreads_str;
globaldata *main_g;
/* numthreads_str = getenv( "NUM_THREADS" );*/
numthreads_str= get_parameter("num_threads"); /* Now in input file */
if (numthreads_str == NULL) {
error ( E_FATAL_ERROR, "num_threads undefined");
}
numthreads = atoi( numthreads_str );
if (numthreads < 1) {
error ( E_FATAL_ERROR, "num_threads must be > 0");
}
printf("numthreads: %d\n",numthreads);
/* create the thread key for access to 'g' */
#ifdef POSIX_MT
pthread_key_create( &g_key, NULL );
#endif
#ifdef SOLARIS_MT
thr_keycreate( &g_key, NULL );
#endif
/* main thread needs its own 'g' */
main_g = (globaldata *)malloc(sizeof(globaldata));
#ifdef POSIX_MT
pthread_setspecific(g_key, main_g);
#endif
#ifdef SOLARIS_MT
thr_setspecific(g_key, main_g);
#endif
#ifdef POSIX_MT
/* Setup default thread attributes */
pthread_attr_init(&pthread_attr);
pthread_attr_setscope(&pthread_attr, PTHREAD_SCOPE_SYSTEM);
if (1)
{
size_t size;
size_t guard;
/* Double the stack size */
pthread_attr_getstacksize(&pthread_attr,&size);
printf("Kernel Old Size %d\n",(int)size);
pthread_attr_setstacksize(&pthread_attr,size * 2);
pthread_attr_getstacksize(&pthread_attr,&size);
printf("Kernel New Size %d\n",(int)size);
/* Double the Guard size (account for old pthread implementation) */
#ifdef PTHREAD_1.X
pthread_attr_getguardsize_np(&pthread_attr,&guard);
printf("Kernel Old Guard %d\n",(int)guard);
pthread_attr_setguardsize_np(&pthread_attr,2*guard);
pthread_attr_getguardsize_np(&pthread_attr,&guard);
#else
pthread_attr_getguardsize(&pthread_attr,&guard);
printf("Kernel Old Guard %d\n",(int)guard);
pthread_attr_setguardsize(&pthread_attr,2*guard);
pthread_attr_getguardsize(&pthread_attr,&guard);
#endif
printf("Kernel New Guard %d\n",(int) guard);
}
#endif
#ifdef SOLARIS_MT
/* let the OS know how many threads to run at once */
thr_setconcurrency( numthreads );
#endif
}
/* evaluate_pop_chuck()
*
* Called from evaluate_pop to do a chunk of evaluations on a pop.
* This was done to allow multithreading.
*/
void *evaluate_pop_chunk( void *param ) {
int k, startidx, endidx;
population *pop;
globaldata* g;
struct thread_param_t *t_param;
t_param = (struct thread_param_t *)param;
pop = t_param->pop;
startidx = t_param->startidx;
endidx = t_param->endidx;
#ifdef POSIX_MT
pthread_setspecific(g_key, &t_param->g);
#endif
#ifdef SOLARIS_MT
thr_setspecific(g_key, &t_param->g);
#endif
g=get_globaldata();
/* printf("START: %d,%d\n", startidx, endidx); */
#ifdef COEVOLUTION /* Here we hack it to provide *two* individuals */
if ((endidx-startidx)%2) /* it it's not even */
{
char xx[256];
sprintf(xx,"Uneven number of individuals (%d) at %d",
endidx-startidx,startidx);
error ( E_FATAL_ERROR,xx);
}
for ( k = startidx; k < endidx; k+=2 )
/* It's GOT to have even number of inds */
if ( pop->ind[k].evald != EVAL_CACHE_VALID ||
pop->ind[k+1].evald != EVAL_CACHE_VALID )
{
app_eval_fitness ( (pop->ind)+k, (pop->ind)+(k+1) );
}
#else
for ( k = startidx; k < endidx; ++k )
if ( pop->ind[k].evald != EVAL_CACHE_VALID )
{
app_eval_fitness ( (pop->ind)+k );
}
#endif
}
#endif /* !defined(POSIX_MT) && !defined(SOLARIS_MT) */
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