void LNLP::prepare_forecast()
{
if(remake_vectors)
{
make_vectors();
init_distances();
}
if(remake_targets)
make_targets();
if(remake_ranges)
{
set_indices_from_range(lib_indices, lib_ranges, (E-1)*tau, -std::max(0, tp), true);
set_indices_from_range(pred_indices, pred_ranges, (E-1)*tau, -std::max(0, tp), false);
check_cross_validation();
which_lib = which_indices_true(lib_indices);
which_pred = which_indices_true(pred_indices);
remake_ranges = false;
}
compute_distances();
return;
}
void LNLP::set_time_series(const NumericVector data)
{
time_series = as<std::vector<double> >(data);
num_vectors = time_series.size();
init_distances();
return;
}
void Xmap::set_block(const NumericMatrix new_block)
{
size_t num_cols = size_t(new_block.ncol());
block.resize(num_cols);
num_vectors = size_t(new_block.nrow());
for(size_t i = 0; i < num_cols; ++i)
{
block[i].resize(num_vectors);
for(size_t j = 0; j < num_vectors; ++j)
block[i][j] = new_block(j,i);
}
init_distances();
return;
}
/*
* @brief Main function to classify a collection (list of datasets)
*
* This function is the main call of the classification system. It takes a set of parameters and launch computations.
*
* @param mParameter* Global parameters to apply for the system
*
*/
void classifyCollection(mParameters *param)
{
collection *datasets;
dataset *current, *test;
distances *distanceSet;
criteria *criterias;
char *directories;
int i;
datasets = importCollection(param->collection, 0);
if (datasets == NULL)
return;
criterias = init_criteria(1);
distanceSet = init_distances(1);
directories = calloc(1024, sizeof(char));
for (i = 0; i < datasets->size; i++)
{
current = NULL;
printf("Processing dataset : %s - %s\n", datasets->name[i], datasets->path[i]);
// Preparing output directories
sprintf(directories, "%s/%s", param->output, datasets->name[i]);
umask(0); mkdir(directories, 0777);
sprintf(directories, "%s/%s/distances", param->output, datasets->name[i]);
umask(0); mkdir(directories, 0777);
sprintf(directories, "%s/%s/optimize_distance", param->output, datasets->name[i]);
umask(0); mkdir(directories, 0777);
sprintf(directories, "%s/%s/optimize_criteria", param->output, datasets->name[i]);
umask(0); mkdir(directories, 0777);
sprintf(directories, "%s/%s/results", param->output, datasets->name[i]);
umask(0); mkdir(directories, 0777);
if (datasets->type[i] == TYPE_LOO || datasets->type[i] == TYPE_TRAIN)
current = importRaw(datasets->path[i], datasets->name[i], NULL, 0);
if (datasets->type[i] == TYPE_LOO_MULTI || datasets->type[i] == TYPE_TRAIN_MULTI)
current = importRawMultiple(datasets->path[i], datasets->name[i]);
if (current == NULL) { printf("Skipping.\n"); continue; }
if (datasets->type[i] == TYPE_LOO)
classifyDatasetLOO(current, distanceSet, criterias);
if (datasets->type[i] == TYPE_LOO_MULTI)
classifyDatasetLOO(current, distanceSet, criterias);
if (datasets->type[i] == TYPE_TRAIN)
{
test = importRaw(datasets->path_test[i], datasets->name[i], current->class_vals, current->nb_classes);
if (test == NULL) { printf("Skipping.\n"); continue; }
optimizeDatasetTT(current, distanceSet, criterias, param);
classifyDatasetTT(current, test, distanceSet, criterias, param);
}
freeDataset(current, datasets->type[i]);
}
free(directories);
}
void run_testcase()
{
int start_point;
graph g;
graph *graphptr = &g;
initialize_graph(graphptr, false);
read_graph(graphptr, false);
initialize_search(graphptr);
scanf("%d", &start_point);
init_distances(start_point);
bfs(graphptr, start_point);
print_distances(graphptr, start_point);
}
/** Fill residue bonds using the bond library. */
void mdt_fill_residue_bonds(struct mdt_residue_bond_list *bondlist,
const struct mdt_library *mlib,
const struct mod_libraries *libs)
{
/* Consider only standard amino acids */
const int n_std_restyp = 20;
GHashTable *res_hash;
/* Do nothing if the information is already populated */
if (bondlist->nres > 0) {
return;
}
res_hash = make_residue_types(bondlist, n_std_restyp, libs);
make_atom_names(bondlist->bonds, mlib->atclass[1], res_hash);
init_distances(bondlist);
add_bonds(bondlist->bonds, mlib->atclass[1], res_hash);
g_hash_table_destroy(res_hash);
fill_distances(bondlist);
}
