public static void Save_Experiment_Settings <T>(
string this_experiment__output_folder,
string experiment_name,
MEL__Algorithm <T> map_elites
)
where T : MEL__Individual
{
string experiment_description_file_path =
Path.Combine(this_experiment__output_folder,
"experiment_settings.txt"
);
string text_to_write = "experiment name: " + experiment_name + "\n";
text_to_write += map_elites.Get_Settings_Description();
IO_Utilities.Append_To_File(
experiment_description_file_path,
text_to_write
);
}
public static void Save_Feature_Tables_CSV <T>(
string this_experiment__output_folder,
int random_seed,
int current_iteration,
MEL__Algorithm <T> map_elites
)
where T : MEL__Individual
{
// data analysis tables - folder paths
string individual_exists__csv_folder = Path.Combine(
this_experiment__output_folder, "CSV_0_A_individual_exists");
string fitness__csv_folder = Path.Combine(
this_experiment__output_folder, "CSV_0_B_fitness");
string selections_per_location__csv_folder = Path.Combine(
this_experiment__output_folder, "CSV_1_A_selections_per_location");
string offspring_survivals_per_location__csv_folder = Path.Combine(
this_experiment__output_folder, "CSV_1_B_offspring_survivals_per_location");
IO_Utilities.CreateFolder(individual_exists__csv_folder);
IO_Utilities.CreateFolder(fitness__csv_folder);
IO_Utilities.CreateFolder(selections_per_location__csv_folder);
IO_Utilities.CreateFolder(offspring_survivals_per_location__csv_folder);
/////////////////////////////////////////////////////////////////////////
// SAVE CSV FILES...
////////////////////////////////////////////////////////////////////////
string individual_exists_table__csv__file_path =
Path.Combine(individual_exists__csv_folder,
"individual_exists_table__"
+ "seed_" + random_seed.ToString()
+ "__iter_" + current_iteration.ToString()
+ ".csv"
);
IO_Utilities.Append_To_File(
individual_exists_table__csv__file_path,
map_elites.state.individual_exists.To_CSV_0_1()
);
string fitness_table__csv__file_path =
Path.Combine(fitness__csv_folder,
"fitness_table__"
+ "seed_" + random_seed.ToString()
+ "__iter_" + current_iteration.ToString()
+ ".csv"
);
IO_Utilities.Append_To_File(
fitness_table__csv__file_path,
map_elites.Q_ST_Fitness_Table().To_CSV()
);
string selections_per_location__csv__file_path =
Path.Combine(selections_per_location__csv_folder,
"selections_per_location__"
+ "seed_" + random_seed.ToString()
+ "__iter_" + current_iteration.ToString()
+ ".csv"
);
IO_Utilities.Append_To_File(
selections_per_location__csv__file_path,
map_elites.state.selections__per__location.To_CSV()
);
string offspring_survivals_per_location__csv__file_path =
Path.Combine(offspring_survivals_per_location__csv_folder,
"offspring_survivals_per_location__"
+ "seed_" + random_seed.ToString()
+ "__iter_" + current_iteration.ToString()
+ ".csv"
);
IO_Utilities.Append_To_File(
offspring_survivals_per_location__csv__file_path,
map_elites.state.offspring_survivals__per__location.To_CSV()
);
}
public static void Run_Experiment <T>(
string experiment_name,
List <int> random_seeds, // implies number of repetitions...
MEL__Operator_Settings <T> operator_settings,
MEL__Evaluation_Settings <T> eval_settings,
MEL__Parent_Selection_Method <T> selection_method,
int initial_population,
int total_num_iterations,
List <int> iterations_for_feature_tables_csv,
List <int> iterations_for_feature_tables_png,
List <int> iterations_for_data_logging,
List <int> iterations_for_console_logging
)
where T : MEL__Individual
{
// prepare paths etc...
string general_output_folder = Path.Combine(
Directory.GetCurrentDirectory(),
"output"
);
if (IO_Utilities.Folder_Exists(general_output_folder) == false)
{
// create the general output folder
IO_Utilities.CreateFolder(general_output_folder);
}
string this_experiment__output_folder = Path.Combine(
general_output_folder,
experiment_name + "___" + DateTime.UtcNow.Ticks.ToString()
);
if (IO_Utilities.Folder_Exists(this_experiment__output_folder) == false)
{
// create this experiment's folder
IO_Utilities.CreateFolder(this_experiment__output_folder);
}
string data_logging_file_path = Path.Combine(
this_experiment__output_folder,
experiment_name + "_data.csv"
);
if (IO_Utilities.File_Exists(data_logging_file_path) == false)
{
IO_Utilities.Create_File(data_logging_file_path, false, false);
}
// create and save the data header...
string data_header = Map_Elites__Data_Header();
IO_Utilities.Append_To_File(data_logging_file_path, data_header);
MEL__Algorithm <T> map_elites = new MEL__Algorithm <T>(
operator_settings,
eval_settings,
selection_method
);
Save_Experiment_Settings(
this_experiment__output_folder,
experiment_name,
map_elites
);
foreach (var random_seed in random_seeds)
{
// initialize the random numbers generator...
Random randomness_provider = new Random(random_seed);
map_elites = new MEL__Algorithm <T>(
operator_settings,
eval_settings,
selection_method
);
// generate the initial population
map_elites.Generate_Initial_Population(randomness_provider, initial_population);
// save the data at this stage, before any operation...
Save_Feature_Tables_CSV(
this_experiment__output_folder,
random_seed,
0,
map_elites
);
Save_Feature_Tables_PNG(
this_experiment__output_folder: this_experiment__output_folder,
random_seed: random_seed,
current_iteration: 0,
map_elites: map_elites,
min_fitness: 0.0,
max_fitness: 1.0
);
string data_row = Map_Elites__Data_Row(random_seed, 0, map_elites);
IO_Utilities.Append_To_File(data_logging_file_path, data_row);
Console_Log(experiment_name, random_seed, 0);
for (int current_iteration = 1; current_iteration <= total_num_iterations; current_iteration++)
{
// advance algorithm
map_elites.Select_And_Mutate_Individual(randomness_provider);
// perhaps, save data
if (iterations_for_feature_tables_csv.Contains(current_iteration))
{
Save_Feature_Tables_CSV(
this_experiment__output_folder,
random_seed,
current_iteration,
map_elites
);
}
if (iterations_for_feature_tables_png.Contains(current_iteration))
{
Save_Feature_Tables_PNG(
this_experiment__output_folder: this_experiment__output_folder,
random_seed: random_seed,
current_iteration: current_iteration,
map_elites: map_elites,
min_fitness: 0.0,
max_fitness: 1.0
);
}
if (iterations_for_data_logging.Contains(current_iteration))
{
data_row = Map_Elites__Data_Row(random_seed, current_iteration, map_elites);
IO_Utilities.Append_To_File(data_logging_file_path, data_row);
}
if (iterations_for_console_logging.Contains(current_iteration))
{
Console_Log(experiment_name, random_seed, current_iteration);
}
}
}
}