bool SpikingGroup::write_to_file(const char * filename)
{
if ( !evolve_locally() ) return true;
ofstream outfile;
outfile.open(filename,ios::out);
if (!outfile) {
cerr << "Can't open output file " << filename << endl;
throw AurynOpenFileException();
}
outfile << "# Auryn SpikingGroup state file for n="<< get_rank_size() <<" neurons (ver. " << VERSION << ")" << endl;
outfile << "# Field order: ";
for ( map<string,gsl_vector_float *>::const_iterator iter = state_vector.begin() ;
iter != state_vector.end() ;
++iter ) {
outfile << scientific << iter->first << " ";
}
outfile << "(plus traces)";
outfile << endl;
boost::archive::text_oarchive oa(outfile);
oa << *(delay);
outfile << endl;
for ( NeuronID i = 0 ; i < get_rank_size() ; ++i )
{
outfile << get_output_line(i);
}
outfile.close();
return true;
}
bool SpikingGroup::load_from_file(const char * filename)
{
if ( !evolve_locally() ) return true;
stringstream oss;
oss << "Loading SpikingGroup from " << filename;
logger->msg(oss.str(),NOTIFICATION);
ifstream infile (filename);
if (!infile) {
stringstream oes;
oes << "Can't open input file " << filename;
logger->msg(oes.str(),ERROR);
throw AurynOpenFileException();
}
NeuronID count = 0;
char buffer[1024];
infile.getline (buffer,1024); // skipping header TODO once could make this logic a bit smarter
infile.getline (buffer,1024); // skipping header
boost::archive::text_iarchive ia(infile);
ia >> *delay;
infile.getline (buffer,1024); // jumpting to next line
while ( infile.getline (buffer,1024) )
{
load_input_line(count,buffer);
count++;
}
if ( get_rank_size() != count ) {
// issue warning
stringstream oes;
oes << "SpikingGroup:: NeuronState file corrupted. Read "
<< count << " entries, but "
<< get_rank_size() << " expected in " << filename;
logger->msg(oes.str(),WARNING);
}
infile.close();
return true;
}
bool RateModulatedConnection::write_to_file(string filename)
{
stringstream oss;
oss << filename << ".cstate";
ofstream outfile;
outfile.open(oss.str().c_str(),ios::out);
if (!outfile) {
cerr << "Can't open output file " << filename << endl;
throw AurynOpenFileException();
}
boost::archive::text_oarchive oa(outfile);
oa << rate_estimate ;
oa << rate_modulation_mul ;
outfile.close();
return SparseConnection::write_to_file(filename);
}
bool RateModulatedConnection::load_from_file(string filename)
{
stringstream oss;
oss << filename << ".cstate";
ifstream infile (oss.str().c_str());
if (!infile) {
stringstream oes;
oes << "Can't open input file " << filename;
logger->msg(oes.str(),ERROR);
throw AurynOpenFileException();
}
boost::archive::text_iarchive ia(infile);
ia >> rate_estimate;
ia >> rate_modulation_mul;
infile.close();
return SparseConnection::load_from_file(filename);
}
void StimulusGroup::load_patterns( string filename )
{
ifstream fin (filename.c_str());
if (!fin) {
stringstream oss;
oss << "StimulusGroup:: "
<< "There was a problem opening file "
<< filename
<< " for reading."
<< endl;
logger->msg(oss.str(),ERROR);
throw AurynOpenFileException();
}
char buffer[256];
string line;
stimuli.clear();
type_pattern pattern;
int total_pattern_size = 0;
while(!fin.eof()) {
line.clear();
fin.getline (buffer,255);
line = buffer;
if (line[0] == '#') continue;
if (line == "") {
if ( total_pattern_size > 0 ) {
stringstream oss;
oss << "StimulusGroup:: Read pattern "
<< stimuli.size()
<< " with pattern size "
<< total_pattern_size
<< " ( "
<< pattern.size()
<< " on rank )";
logger->msg(oss.str(),DEBUG);
stimuli.push_back(pattern);
pattern.clear();
total_pattern_size = 0;
}
continue;
}
stringstream iss (line);
NeuronID i ;
iss >> i ;
if ( localrank( i ) ) {
pattern_member pm;
pm.gamma = 1 ;
iss >> pm.gamma ;
pm.i = global2rank( i ) ;
pattern.push_back( pm ) ;
}
total_pattern_size++;
}
fin.close();
// initializing all probabilities as a flat distribution
flat_distribution();
stringstream oss;
oss << "StimulusGroup:: Finished loading " << stimuli.size() << " patterns";
logger->msg(oss.str(),NOTIFICATION);
}
