//--------------------------------------------
void read_solution(urdme_model *model, char*file){
mxArray *tspan,*U;
MATFile *input_file;
/* Open mat-file (read-only) */
input_file = matOpen(file,"r");
if (input_file == NULL){
printf("Failed to open mat-file '%s'.\n",file);
return;
}
printf("read in '%s'\n'",file);
/* Get U-matrix. */
init_sol(model,1);
U = matGetVariable(input_file, "U");
if (U == NULL){
printf("No U solution variable in mat-file '%s'\n.",file);
return;
}
int Usz = mxGetNumberOfElements(U);
model->U[0] =(int *)malloc(Usz*sizeof(int));
double*Utmp = mxGetPr(U);
model->nsol = 1;
int i;
for(i=0;i<Usz;i++){
model->U[0][i] = (int) Utmp[i];
}
/* time span (optional) */
tspan = matGetVariable(input_file, "tspan");
if (tspan != NULL){
model->tspan = mxGetPr(tspan);
model->tlen = mxGetNumberOfElements(tspan);
}
}
int main(int argc, char* argv[])
{
int seed,i;
//cout<<"c This is NuMVC, a local search solver for the Minimum Vertex Cover (and also Maximum Independent Set) problem."<<endl;
if(build_instance(argv[1])!=1){
cout<<"can't open instance file"<<endl;
return -1;
}
optimal_size=0;
i=2;
//sscanf(argv[i++],"%d",&cand_count);//if you want to stop the algorithm only cutoff time is reached, set optimal_size to 0.
//sscanf(argv[i++],"%d",&edge_cand);
sscanf(argv[i++],"%d",&seed);
sscanf(argv[i++],"%d",&cutoff_time);
srand(seed);
//cout<<seed<<' ';
//cout<<argv[1]<<' ';
times(&start);
start_time = start.tms_utime + start.tms_stime;
init_sol();
#ifdef individual_analysis_on_init_sls_mode
times(&finish);
init_time = double(finish.tms_utime - start.tms_utime + finish.tms_stime - start.tms_stime) / sysconf(_SC_CLK_TCK);
init_time = round(init_time * 100)/100.0;
#endif
//if(c_size + uncov_stack_fill_pointer > optimal_size )
//{
//cout<<"c Start local search..."<<endl;
cover_LS();
//}
#ifdef individual_analysis_on_init_sls_mode
times(&finish);
sls_time = double(finish.tms_utime - start.tms_utime + finish.tms_stime - start.tms_stime) / sysconf(_SC_CLK_TCK) - init_time;
sls_step_speed_per_ms = double(step) * 0.001 / sls_time;
#endif
//check solution
if(check_solution()==1)
{
cout << "o " << best_c_size << endl;
//cout << best_c_size << ' ';
//print_mvc_solution();
cout << "c searchSteps " << best_step << endl;
//printf("%ld ", best_step);
cout << "c solveTime " << best_comp_time << endl;
//cout << "c stepVelocity(/0.001ms) " << (long double)(best_step) / (best_comp_time * 1000000) << endl;
/*cout<<"c Best found vertex cover size = "<<best_c_size<<endl;
print_solution();
cout<<"c searchSteps = "<<best_step<<endl;
cout<<"c solveTime = "<<best_comp_time<<endl;*/
//cout<<best_c_size<<' '<<best_comp_time<<' '<<best_step<<endl;
#ifdef individual_analysis_on_init_sls_mode
//cout<<"c initTime " << init_time << endl;
//cout<<"c slsTime " << sls_time << endl;
cout<<"c stepSpeed(/ms) "<< sls_step_speed_per_ms << endl;
#endif
}
else
{
cout<<"the solution is wrong."<<endl;
//print_solution();
}
free_memory();
return 0;
}
int main(int argc, char *argv[])
{
char *infile,*outfile;
int i, nt=1, report_level=1;
/* TODO. Parsing of input with error checking.
Input syntax on form: -numtraj=4 etc. ?*/
if (argc < 3){
printf("To few arguments to nsm.");
exit(-1);
}
/* Input file. */
infile = argv[1];
/* Output file (or directory). */
outfile = argv[2];
/* Read model specification */
urdme_model *model;
model = read_model(infile);
model->infile = infile;
if (model == NULL){
printf("Fatal error. Couldn't load model file or currupt model file.");
return(-1);
}
/*reopen MAT file*/
MATFile *input_file;
mxArray *temp,*sopts;
input_file = matOpen(infile,"r");
if (input_file == NULL){
printf("Failed to open mat-file.\n");
return(-1);
}
/* Initialize RNG(s). */
/* Look for seed */
temp = matGetVariable(input_file, "seed");
/* Initialize rng from GSL. */
const gsl_rng_type * T;
T = gsl_rng_taus2;
gsl_rng_env_setup();
runif = gsl_rng_alloc (T);
//gsl_rng_set (runif, 463728648); //Why would we seed the name number each time??
long int seed;
/* If seed is provided as a parameter, it takes precedence. */
if (argc > 3) {
srand48((long int)atoi(argv[3]));
gsl_rng_set(runif,(long int)atoi(argv[3]));
}else if(temp != NULL){
seed = (long int) mxGetScalar(temp);
srand48(seed);
gsl_rng_set(runif,seed);
}else{
/* Not a foolproof solution */
//srand48((long int)time(NULL)+(long int)(1e9*clock()));
srand48( time(NULL) * getpid() );
gsl_rng_set(runif,time(NULL) * getpid());
}
/* Look for an optional parameter matrix. */
const double *matfile_parameters;
int mpar = 0;
int npar = 0;
int param_case=0;
temp = matGetVariable(input_file, "parameters");
if (temp != NULL) {
matfile_parameters = (double *)mxGetPr(temp);
mpar = mxGetM(temp);
npar = mxGetN(temp);
}
/* Look if a parameter case if supplied as a parameter. */
if (argc > 4) {
param_case = (int)atoi(argv[4]);
}
if (param_case > npar ) {
printf("nsmcore: Fatal error, parameter case is larger than n-dimension in parameter matrix.\n");
exit(-1);
}
/* Create global parameter variable for this parameter case. */
parameters = (double *)malloc(mpar*sizeof(double));
memcpy(parameters,&matfile_parameters[npar*param_case],mpar*sizeof(double));
/* Initialize extra args */
model->num_extra_args = 4;
model->extra_args=malloc(model->num_extra_args*sizeof(void *));
/* Set report level */
temp = matGetVariable(input_file, "report");
if (temp != NULL)
report_level = (int) mxGetScalar(temp);
else
if (nt > 1)
report_level=0;
else
report_level=1;
model->extra_args[0] = malloc(sizeof(int));
*(int *)(model->extra_args[0]) = report_level;
/* Set tau_d */
sopts = matGetVariable(input_file, "sopts");
if(sopts==NULL){
printf("Step length (tau_d) is missing in the model file\n");
return(-1);
}
model->extra_args[1] = malloc(sizeof(double));
model->extra_args[2] = malloc(sizeof(double));
model->extra_args[3] = malloc(sizeof(double));
double*sopts_tmp = mxGetPr(sopts);
//printf("HERE: tau_d=%e\n",sopts_tmp[0]);
//printf("HERE: max_jump=%e\n",sopts_tmp[1]);
//printf("HERE: err_tol=%e\n",sopts_tmp[2]);
*(double*)model->extra_args[1] = sopts_tmp[0];
*(double*)model->extra_args[2] = sopts_tmp[1];
*(double*)model->extra_args[3] = sopts_tmp[2];
//printf("HERE: tau_d=%e\n",*(double *)(model->extra_args[1]));
//printf("HERE: max_jump=%e\n",*(double *)(model->extra_args[2]));
//printf("HERE: err_tol=%e\n",*(double *)(model->extra_args[3]));
/* close MAT file*/
matClose(input_file);
/* Allocate memory to hold nt solutions. */
init_sol(model,nt);
/* Get a writer to store the output trajectory on a hdf5 file. */
urdme_output_writer *writer;
writer = get_urdme_output_writer(model,outfile);
printf("writer = get_urdme_output_writer(model,%s);\n",outfile);
printf("dfsp_core\n");
dfsp_core(model, writer);
/* Write the timespan vector to the output file */
printf("write_tspan\n");
write_tspan(writer,model);
//free(parameters);
printf("destroy_output_writer\n");
destroy_output_writer(writer);
printf("destroy_model\n");
destroy_model(model);
return(0);
}
