void second_check(sparsegraph * sg)
{
int nCuts = (1<<(n-1))-1;
for (int i=0; i<nCuts; i++) {
for (int j=i+1; j<nCuts; j++) {
bool merger = true;
int sum = 0, m=-1;
for (int o=0; o<k; o++)
if (oMark[i][o] != oMark[j][o]) {
merger = false;
break;
} else {
sum += (oMark[i][o]) ? 1:0;
if (!oMark[i][o]) m = o;
}
if (merger && sum == k-1) {
//printf("%0o %0o\n", i,j);
if (isMerger(m,i,j,sg)) {
//printf("Never mind. There is a merger.\n");
return;
}
}
}
}
nTarget++;
printf("find one! graph %d (e=%d).\n", count, sg->nde/2);
printNetwork();
}
void printNetworkToFile(char * filename, GAindividual individual)
{
ReactionNetwork * r = (ReactionNetwork*)individual;
FILE *stream;
int i, n;
if (!r || (r->type < 0) || (r->type > NUMBER_OF_NETWORK_TYPES)) return;
stream = fopen(filename, "w");
if (!stream) return;
printNetwork(stream,individual);
fclose(stream);
}
static int callBackWithLogKeeping(int iter, int popSz, GApopulation pop, double * fitnessArray, int *** parentsArray)
{
unsigned long long * seeds;
double f;
int i,j,k,*parents, num = 10*popSz, max = 0, stop = 0;
int * temp = 0, * ids = 0;
GAindividual * p;
//save
int each_fitness = PRINT_EACH_FITNESS,
each_script = PRINT_EACH_SCRIPT,
each_size = PRINT_EACH_SIZE,
each_best_lineage = PRINT_EACH_BEST_LINEAGE,
each_all_fitness = PRINT_EACH_ALL_FITNESS,
each_all_lineage = PRINT_EACH_ALL_LINEAGE;
if (USER_CALLBACK_FNC)
stop = USER_CALLBACK_FNC(iter,popSz,pop,fitnessArray, parentsArray);
if (!stop)
stop = (iter == _MAX_ITER);
if (stop)
{
//cheat
PRINT_EACH_FITNESS = PRINT_FINAL_FITNESS;
PRINT_EACH_SCRIPT = PRINT_FINAL_SCRIPT;
PRINT_EACH_SIZE = PRINT_FINAL_SIZE;
PRINT_EACH_BEST_LINEAGE = PRINT_FINAL_BEST_LINEAGE;
PRINT_EACH_ALL_FITNESS = PRINT_FINAL_ALL_FITNESS;
PRINT_EACH_ALL_LINEAGE = PRINT_FINAL_ALL_LINEAGE;
//printf("\n========final results=======\n");
fprintf(LOGFILE,"\n========final results=======\n");
if (LOGFILE && PRINT_SEEDS)
{
seeds = getMTseeds();
fprintf(LOGFILE,"random number generator seeds: %llf,%llf,%llf,%llf\n",seeds[0],seeds[1],seeds[2],seeds[3]);
}
}
if (iter == 0) //header
{
printf("gen");
fprintf(LOGFILE,"gen");
if (PRINT_EACH_FITNESS && !PRINT_EACH_ALL_FITNESS)
{
printf("\tfitness ");
fprintf(LOGFILE,"\tfitness ");
}
if (PRINT_EACH_ALL_FITNESS)
{
for (i=0; i < popSz; ++i)
{
//printf("\tfitness_%i",i);
fprintf(LOGFILE,"\tfitness_%i",i);
}
}
if (PRINT_EACH_SIZE)
{
printf("\tspecies\treactions");
fprintf(LOGFILE,"\tspecies\treactions");
}
if (TRACK_NETWORK_PARENTS && (PRINT_EACH_BEST_LINEAGE || PRINT_EACH_ALL_LINEAGE))
{
//printf("\tparents");
fprintf(LOGFILE,"\tparents");
}
printf("\n");
fprintf(LOGFILE,"\n");
printf("---");
fprintf(LOGFILE,"---");
if (PRINT_EACH_FITNESS && !PRINT_EACH_ALL_FITNESS)
{
printf("\t------- ");
fprintf(LOGFILE,"\t------- ");
}
if (PRINT_EACH_ALL_FITNESS)
{
for (i=0; i < popSz; ++i)
{
//printf("\t----------",i);
fprintf(LOGFILE,"\t -------- ",i);
}
}
if (PRINT_EACH_SIZE)
{
printf("\t-------\t---------");
fprintf(LOGFILE,"\t-------\t---------");
}
if (TRACK_NETWORK_PARENTS && (PRINT_EACH_BEST_LINEAGE || PRINT_EACH_ALL_LINEAGE))
{
//printf("\t-------");
fprintf(LOGFILE,"\t-------");
}
printf("\n");
fprintf(LOGFILE,"\n");
}
if (TRACK_NETWORK_PARENTS && (PRINT_EACH_BEST_LINEAGE || PRINT_EACH_ALL_LINEAGE))
{
ids = (int*)malloc(num * sizeof(int));
for (i=0; i < num; ++i)
ids[i] = 0;
for (i=0; i < popSz; ++i)
{
p = pop[i];
if (!p) continue;
parents = GAgetOriginalParents(i,iter,parentsArray);
if (parents)
{
for (j=0; parents[j] > 0; ++j)
{
if (parents[j] >= max)
max = parents[j];
if (parents[j] >= num)
{
temp = ids;
ids = (int*)malloc( num * 2 * sizeof(int) );
for (k=0; k < num; ++k)
ids[k] = temp[k];
num *= 2;
for (; k < num; ++k)
ids[k] = 0;
free(temp);
}
ids[ parents[j] ] += 1;
}
}
else
{
}
if (PRINT_EACH_BEST_LINEAGE && !PRINT_EACH_ALL_LINEAGE)
break;
}
}
printf("%i",iter);
fprintf(LOGFILE,"%i",iter);
if (PRINT_EACH_FITNESS && !PRINT_EACH_ALL_FITNESS)
{
f = fitnessArray[0];
printf("\t%lf",f);
fprintf(LOGFILE,"\t%lf",f);
}
if (PRINT_EACH_ALL_FITNESS)
{
for (i=0; i < popSz; ++i)
{
f = fitnessArray[i];
//printf("\t%lf",f);
fprintf(LOGFILE,"\t%lf",f);
}
}
if (PRINT_EACH_SIZE)
{
printf("\t%i\t%i",getNumSpecies(pop[0]),getNumReactions(pop[0]));
fprintf(LOGFILE,"\t%i\t%i",getNumSpecies(pop[0]),getNumReactions(pop[0]));
}
if (TRACK_NETWORK_PARENTS && (PRINT_EACH_BEST_LINEAGE || PRINT_EACH_ALL_LINEAGE))
{
for (i=0; i < max; ++i)
{
//printf("\t%i",ids[i]);
fprintf(LOGFILE,"\t%i",ids[i]);
}
}
if (PRINT_EACH_SCRIPT)
{
//printf("\n========script=======\n");
fprintf(LOGFILE,"\n========script=======\n");
//printNetwork(stdout,pop[0]);
printNetwork(LOGFILE,pop[0]);
//printf("\n=====================\n");
fprintf(LOGFILE,"\n=====================\n");
}
printf("\n");
fprintf(LOGFILE,"\n");
if (ids && (num > 0))
free(ids);
if (iter == _MAX_ITER)
{
//restore
PRINT_EACH_FITNESS = each_fitness;
PRINT_EACH_SCRIPT = each_script;
PRINT_EACH_SIZE = each_size;
PRINT_EACH_BEST_LINEAGE = each_best_lineage;
PRINT_EACH_ALL_FITNESS = each_all_fitness;
PRINT_EACH_ALL_LINEAGE = each_all_lineage;
}
return stop;
}
int
main( int argc, char *argv[] )
{
nn_type nn;
double atof();
FILE *log_file;
FILE *out_file;
if( argc != 6 ) {
fprintf( stderr, "Usage: nn learning_rate k hidden log_file out_file < digits_train.txt\n" );
fprintf( stderr, " log_file - file to record progress of training\n");
fprintf( stderr, " out_file - file to record final network\n");
exit(0);
}
nn.learning_rate = atof( argv[1] );
nn.k = atof( argv[2] );
nn.n_hidden = atoi( argv[3] );
if( (log_file = fopen( argv[4], "w" )) == NULL ) {
fprintf( stderr, "Could not open file %s\n", argv[4] );
exit( 0 );
}
if( (out_file = fopen( argv[5], "w" )) == NULL ) {
fprintf( stderr, "Could not open file %s\n", argv[5] );
exit( 0 );
}
fprintf( log_file, "learning rate: %0.2f\n", nn.learning_rate );
fprintf( log_file, "multiplicative constant (k): %0.1f\n", nn.k );
fprintf( log_file, "hidden units: %d\n", nn.n_hidden );
/*
* Number of input lines.
* NO NEED TO CHANGE THIS.
*/
nn.n_input = 64;
/*
* Number of output lines.
* NO NEED TO CHANGE THIS.
*/
nn.n_output = 10;
/*
* Total amount of data.
* YOU MAY WISH TO CHANGE THIS.
*/
all_data.n = N_EXAMPLES; /* total amount of data */
if( all_data.n > N_EXAMPLES ) {
fprintf( stderr, "Too many examples; increase N_EXAMPLES\n" );
exit( 0 );
}
readData( nn.n_input, nn.n_output, &all_data );
splitData( nn.n_input, nn.n_output,
&all_data, &training_data, &test_data );
trainNetwork( log_file, &nn, &training_data );
testNetwork( log_file, &nn, &test_data );
printNetwork( out_file, &nn );
fclose( log_file );
fclose( out_file );
}
