Matrix<std::string> KappaCoefficientOptimizationThreshold::to_string_matrix(void) const
{
std::ostringstream buffer;
Vector<std::string> labels;
Vector<std::string> values;
// Minimum threshold
labels.push_back("Minimum threshold");
buffer.str("");
buffer << minimum_threshold;
values.push_back(buffer.str());
// Maximum threshold
labels.push_back("Maximum threshold");
buffer.str("");
buffer << maximum_threshold;
values.push_back(buffer.str());
// Step
labels.push_back("Step");
buffer.str("");
buffer << step;
values.push_back(buffer.str());
const size_t rows_number = labels.size();
const size_t columns_number = 2;
Matrix<std::string> string_matrix(rows_number, columns_number);
string_matrix.set_column(0, labels);
string_matrix.set_column(1, values);
return(string_matrix);
}
Matrix<std::string> SimulatedAnnealingOrder::to_string_matrix(void) const
{
std::ostringstream buffer;
Vector<std::string> labels;
Vector<std::string> values;
// Minimum order
labels.push_back("Minimum order");
buffer.str("");
buffer << minimum_order;
values.push_back(buffer.str());
// Maximum order
labels.push_back("Maximum order");
buffer.str("");
buffer << maximum_order;
values.push_back(buffer.str());
// Step
labels.push_back("Cooling Rate");
buffer.str("");
buffer << cooling_rate;
values.push_back(buffer.str());
// Trials number
labels.push_back("Trials number");
buffer.str("");
buffer << trials_number;
values.push_back(buffer.str());
// Tolerance
labels.push_back("Tolerance");
buffer.str("");
buffer << tolerance;
values.push_back(buffer.str());
// Selection performance goal
labels.push_back("Selection performance goal");
buffer.str("");
buffer << selection_performance_goal;
values.push_back(buffer.str());
// Minimum temperature
labels.push_back("Minimum temperature");
buffer.str("");
buffer << minimum_temperature;
values.push_back(buffer.str());
// Maximum iterations number
labels.push_back("Maximum iterations number");
buffer.str("");
buffer << maximum_iterations_number;
values.push_back(buffer.str());
// Maximum time
labels.push_back("Maximum time");
buffer.str("");
buffer << maximum_time;
values.push_back(buffer.str());
// Plot training performance history
labels.push_back("Plot training performance history");
buffer.str("");
buffer << reserve_performance_data;
values.push_back(buffer.str());
// Plot selection performance history
labels.push_back("Plot selection performance history");
buffer.str("");
buffer << reserve_selection_performance_data;
values.push_back(buffer.str());
const size_t rows_number = labels.size();
const size_t columns_number = 2;
Matrix<std::string> string_matrix(rows_number, columns_number);
string_matrix.set_column(0, labels);
string_matrix.set_column(1, values);
return(string_matrix);
}