public MyAlgorithmOptimization(MainForm form1, Algorithm algorithm)
{
this.algorithm = algorithm;
explored = new List <TargetFunctionPoint>();
this.form1 = form1;
variablesVisualizer = new MultiParameterVisualizer(form1.picBox, form1);
variablesVisualizer.addParameter("max Q", Color.Cyan, 400);
variablesVisualizer.addParameter("target_function", Color.LightCyan, 800);
//VVVVVVVVVVV
// 1)разобраться с косяками на графике всех индивидов
// 2)почему при нахождении центра получаются близкие, но разные числа
// 3)добиться одинакового числа точек в currentHypercube связано с (1)
// 4) прикрутить красивые графики везде, где уместно
// -параллелизм
//for (int i = 0; i < population_value; i++)
// variablesVisualizer.parameters[1].functions.Add(new Function(" [" + i.ToString() + "]", valueToColor(0, population_value, population_value - i - 1)));
report_file_name = form1.pathPrefix + "/MyAlgorithmOptimization/Optimization report " + DateTime.Now.ToString().Replace(':', '-') + ".txt";
P = algorithm.h.Clone();
string reportHeader = "";
for (int i = 0; i < P.nodes.Count; i++)
{
if (P.nodes[i].getAttributeValue("variable") == "numerical")
{
reportHeader += P.nodes[i].getAttributeValue("name") + ';';
variablesCount++;
}
}
variablesVisualizer.enableGrid = false;
int fucnCount = Convert.ToInt32(Math.Pow(3.0, Convert.ToDouble(variablesCount)));
for (int i = 0; i < fucnCount; i++)
{
variablesVisualizer.parameters[1].functions.Add(new Function(" [" + i.ToString() + "]", ParameterVisualizer.valueToColor(0, fucnCount, fucnCount - i - 1)));
}
File.WriteAllText(report_file_name, reportHeader + "Q;" + '\n');
initPool();
variablesVisualizer.refresh();
}
public ExpertOptimization(Expert expert, MainForm form1, int population_value, int test_count, int mutation_rate, double elite_ratio, int Iterarions, DateTime date1, DateTime date2, string rawDatasetFilePath)
{
r = new Random();
this.Iterarions = Iterarions;
this.rawDatasetFilePath = rawDatasetFilePath;
this.form1 = form1;
this.expert = expert;
this.elite_ratio = elite_ratio;
this.mutation_rate = mutation_rate;
this.population_value = population_value;
this.test_count = test_count;
this.date1 = date1;
this.date2 = date2;
variablesVisualizer = new MultiParameterVisualizer(form1.picBox, form1);
population = new Hyperparameters[population_value];
variablesNames = new List <string>();
variablesIDs = new List <int>();
this.agentManager = form1.I.agentManager;
name = expert.expertName;
try { Directory.Delete(form1.pathPrefix + "Optimization\\" + name, true); } catch { }
// refreshAOTree();
variablesVisualizer.enableGrid = false;
variablesVisualizer.addParameter("best_individ", Color.Cyan, 300);
variablesVisualizer.addParameter("target_function", Color.LightCyan, 600);
variablesVisualizer.parameters[1].functions.Add(new Function("averege best", Color.Lime));
//добавление переменных в MultiParameterVisualizer
for (int i = 0; i < population_value; i++)
{
variablesVisualizer.parameters[1].functions.Add(new Function(" [" + i.ToString() + "]", valueToColor(0, population_value, population_value - i - 1)));
}
for (int i = 0; i < population_value; i++)
{
// variablesVisualizer.addParameter("actions [" + i.ToString() + "]", Color.Pink, 50);
variablesVisualizer.addParameter("committee response [" + i.ToString() + "]", Color.Pink, 300);
variablesVisualizer.addParameter("close [" + i.ToString() + "]", Color.Pink, 300);
variablesVisualizer.addParameter("deposit1 [" + i.ToString() + "]", Color.Green, 300);
variablesVisualizer.addParameter("exit [" + i.ToString() + "]", Color.LightSeaGreen, 300);
/* variablesVisualizer.addParameter("deposit history [" + i.ToString() + "]", Color.LightCyan, 300);
* variablesVisualizer.parameters[1 + i].functions.Add(new Function("deposit1 [" + i.ToString() + "]", Color.Pink));
* variablesVisualizer.parameters[1 + i].functions.Add(new Function("deposit2 [" + i.ToString() + "]", Color.Green));
* variablesVisualizer.parameters[1 + i].functions.Add(new Function("exit [" + i.ToString() + "]", Color.LightSeaGreen)); */
}
// recurciveVariableAdding(expert.H, 0, name + "[0]");
variablesVisualizer.refresh();
}
public void TEST()
{
mainThread = System.Threading.Thread.CurrentThread;
double balance_BTC = 0;
double balance_USD = 100;
double lot = 0.001;
Hyperparameters order_book;
var api = new ExmoApi("k", "s");
string responce = "";
string s = "";
vis.addParameter("BTC_USD", Color.White, 1000);
vis.parameters[0].showLastNValues = true;
vis.enableGrid = true;
vis.parameters[0].window = 360;
//наименьшая цена, по которой можно покупать
vis.parameters[0].functions.Add(new Function("bid_top", Color.Blue));
//наивысшая цена, по которой можно продать
vis.parameters[0].functions.Add(new Function("ask_top", Color.Red));
expert = new Expert("Expert_Flex", this);
algorithm = new BidAsk(this, "BidAsk");
algorithm.Open(@"E:\Anton\Desktop\MAIN\Экспертная система\Экспертная система\Алгоритмы прогнозирования\BidAsk\h.json");
expert.AddAlgorithm(algorithm);
int window = int.Parse(algorithm.h.getValueByName("window_size"));
int step = 60000;
string[] input;
double[] predictions = null;
List <string> rawInput = new List <string>();
// List<string> spreads = new List<string>();
rawInput.Add("<DATE_TIME>;<bid_top>;<bid_quantity>;<bid_amount>;<ask_top>;<ask_quantity>;<ask_amount>");
//ЗАПУСК СКРИПТОВ ПОТОЧНОГО ПРОГНОЗИРОВНИЯ
Task[] RunTasks = new Task[expert.algorithms.Count];
foreach (Algorithm algorithm in expert.algorithms)
{
RunTasks[expert.algorithms.IndexOf(algorithm)] = Task.Run(() => algorithm.runGetPredictionScript());
}
//ОЖИДАНИЕ ЗАВЕРШЕНИЯ ЗАПУСКА
foreach (var task in RunTasks)
{
task.Wait();
}
List <double> positions = new List <double>();
while (true)
{
vis.parameters[0].window = 20;
try
{
responce = api.ApiQuery("order_book", new Dictionary <string, string> {
{ "pair", "BTC_USD" }
});
if (responce.Length > 400)
{
responce = responce.Substring(0, 400);
}
if (!responce.Contains("maintenance"))
{
order_book = new Hyperparameters(responce, this);
//<bid_top>;<bid_quantity>;<bid_amount>;<ask_top>;<ask_quantity>;<ask_amount>
s = DateTime.Now.ToString() + ';'
+ order_book.nodes[0].getAttributeValue("bid_top") + ';' + order_book.nodes[0].getAttributeValue("bid_quantity") + ';' + order_book.nodes[0].getAttributeValue("bid_amount") + ';'
+ order_book.nodes[0].getAttributeValue("ask_top") + ';' + order_book.nodes[0].getAttributeValue("ask_quantity") + ';' + order_book.nodes[0].getAttributeValue("ask_amount");
s = s.Replace('.', ',');
double bid_top = Convert.ToDouble(order_book.nodes[0].getAttributeValue("bid_top").Replace('.', ','));
double ask_top = Convert.ToDouble(order_book.nodes[0].getAttributeValue("ask_top").Replace('.', ','));
/*
* double bid_quantity = Convert.ToDouble(order_book.nodes[0].getAttributeValue("bid_quantity").Replace('.', ','));
* double ask_quantity = Convert.ToDouble(order_book.nodes[0].getAttributeValue("ask_quantity").Replace('.', ','));
*
* double bid_amount = Convert.ToDouble(order_book.nodes[0].getAttributeValue("bid_amount").Replace('.', ','));
* double ask_amount = Convert.ToDouble(order_book.nodes[0].getAttributeValue("ask_amount").Replace('.', ','));*/
vis.addPoint(bid_top, "bid_top");
vis.addPoint(ask_top, "ask_top");
vis.refresh();
// log(s);
//запись входных данных
File.AppendAllText("BTC_USD_exmo.txt", s);
rawInput.Add(s);
// spreads.Add(String.Format("{0:0.#####}", bid_top - ask_top));
showInpOutp.fillTextBox1(rawInput);
//+1 для заголовка, +1 для нормализации i/(i-1)
if (rawInput.Count < window + 2)
{
File.AppendAllText("BTC_USD_exmo.txt", "\n");
}
else
{
input = expert.prepareDataset(rawInput.ToArray(), "<DATE_TIME>", true);
//шапка должна оставаться на месте, поэтому 1, а не 0
rawInput.RemoveAt(1);
showInpOutp.fillTextBox2(input);
if (input.Length == window + 1)
{
predictions = expert.getCommitteePrediction(input);
}
else
{
log("input.Length =/= window+1; input.Length = " + input.Length.ToString());
}
string action = expert.getDecision(predictions);
if (action == "error")
{
log("action = error", Color.Red);
}
if (action == "buy")
{
if (balance_USD > ask_top * lot)
{
balance_BTC = balance_BTC + lot;
balance_USD = balance_USD - (ask_top * lot);
positions.Add(ask_top);
log("BUY", Color.Blue);
log(ask_top.ToString());
log(" USD:" + balance_USD.ToString());
log(" BTC:" + balance_BTC.ToString());
vis.parameters[0].functions[2].points[vis.parameters[0].functions[1].points.Count - 1].mark = "BUY‾‾‾‾‾‾‾‾";
}
else
{
// log("Баланс USD: " + balance_USD.ToString() + " Невозможно купить " + (bid_top * lot).ToString() + " BTC");
action += " (fail)";
}
}
for (int i = 0; i < positions.Count; i++)
{
if (positions[i] < bid_top)
{
action = "sell";
positions.RemoveAt(i);
break;
}
}
if (action == "sell")
{
if (bid_top != 0)
{
if (balance_BTC >= lot)
{
balance_BTC = balance_BTC - lot;
balance_USD = balance_USD + (bid_top * lot);
log("SELL", Color.Red);
log(bid_top.ToString());
log(" USD:" + balance_USD.ToString());
log(" BTC:" + balance_BTC.ToString());
vis.parameters[0].functions[1].points[vis.parameters[0].functions[1].points.Count - 1].mark = "SELL‾‾‾‾‾‾‾‾";
}
else
{
// log("Баланс BTC: " + balance_BTC.ToString() + " Невозможно продать " + (lot).ToString() + " BTC");
action += " (fail)";
}
}
else
{
log("bid_top почему-то равно нулю!", Color.Red);
action += " (fail)";
}
}
log(DateTime.Now.ToString() + " " + action);
//запись состояния балансов и последнего действия
File.AppendAllText("BTC_USD_exmo.txt", balance_BTC.ToString() + ';' + balance_USD.ToString() + ';' + action + "\n");
}
}
else
{
log("Технические работы", Color.Red);
}
}
catch (Exception e)
{
log(e.Message, Color.Red);
// log(result);
}
Thread.Sleep(step);
}
}
public void run()
{
for (int it = 0; it < 20; it++)
{
currentHypercube = new List <TargetFunctionPoint>();
iteration();
// поиск максимума
TargetFunctionPoint maxQ = new TargetFunctionPoint(null, 0);
for (int i = 0; i < currentHypercube.Count; i++)
{
variablesVisualizer.addPoint(currentHypercube[i].Q, " [" + i.ToString() + "]");
if (maxQ.Q < currentHypercube[i].Q)
{
maxQ = currentHypercube[i];
}
}
variablesVisualizer.addPoint(maxQ.Q, "max Q");
form1.log(getReportLine(maxQ), Color.Magenta);
bool isOptimumInCenter = true;
for (int i = 0; i < P.nodes.Count; i++)
{
if (P.nodes[i].getAttributeValue("variable") == "numerical")
{
string maxQVariableValue = maxQ.h.nodes[i].getValue();
string variableCenter = getVariableCenter(P.nodes[i]);
if (maxQVariableValue != variableCenter)
{
isOptimumInCenter = false;
}
}
}
if (isOptimumInCenter)
{
//если максимум в центре - сжатие
form1.log("Сжатие", Color.Cyan);
variablesVisualizer.markLast("Сжатие", "max Q");
for (int i = 0; i < P.nodes.Count; i++)
{
if (P.nodes[i].getAttributeValue("variable") == "numerical")
{
string newMin = "";
string newMax = "";
if (P.nodes[i].getAttributeValue("max").Contains('.') || P.nodes[i].getAttributeValue("max").Contains(','))
{
double min_double = double.Parse(P.nodes[i].getAttributeValue("min").Replace('.', ','));
double max_double = double.Parse(P.nodes[i].getAttributeValue("max").Replace('.', ','));
// сужение интервала
if (min_double + ((max_double - min_double) / 4) > 0)
{
newMin = (min_double + ((max_double - min_double) / 4)).ToString().Replace(',', '.');
}
else
{
newMin = min_double.ToString().Replace(',', '.');
}
newMax = (max_double - ((max_double - min_double) / 4)).ToString().Replace(',', '.');
}
else
{
int min_int = int.Parse(P.nodes[i].getAttributeValue("min"));
int max_int = int.Parse(P.nodes[i].getAttributeValue("max"));
// сужение интервала
if (min_int + ((max_int - min_int) / 4) >= 2)
{
newMin = (min_int + ((max_int - min_int) / 4)).ToString();
}
else
{
newMin = min_int.ToString();
}
newMax = (max_int - ((max_int - min_int) / 4)).ToString();
}
P.nodes[i].setAttribute("min", newMin);
P.nodes[i].setAttribute("max", newMax);
}
}
}
else
{
//иначе - перемещение центра в точку максимума
form1.log("Перемещение из " + getReportLine(lastP) + " в " + getReportLine(maxQ), Color.Cyan);
variablesVisualizer.markLast("Перемещение", "max Q");
for (int i = 0; i < P.nodes.Count; i++)
{
if (P.nodes[i].getAttributeValue("variable") == "numerical")
{
string newMin = "";
string newMax = "";
if (P.nodes[i].getAttributeValue("max").Contains('.') || P.nodes[i].getAttributeValue("max").Contains(','))
{
double min_double = double.Parse(P.nodes[i].getAttributeValue("min").Replace('.', ','));
double max_double = double.Parse(P.nodes[i].getAttributeValue("max").Replace('.', ','));
double value = double.Parse(maxQ.h.nodes[i].getValue().Replace('.', ','));
// перемещение центра
if ((value - ((max_double - min_double) / 2)) > 0)
{
newMin = (value - ((max_double - min_double) / 2)).ToString().Replace(',', '.');
}
else
{
newMin = min_double.ToString().Replace(',', '.');
}
newMax = (value + ((max_double - min_double) / 2)).ToString().Replace(',', '.');
}
else
{
int min_int = int.Parse(P.nodes[i].getAttributeValue("min"));
int max_int = int.Parse(P.nodes[i].getAttributeValue("max"));
int value = int.Parse(maxQ.h.nodes[i].getValue());
// перемещение центра
if (value - ((max_int - min_int) / 2) >= 2)
{
newMin = (value - ((max_int - min_int) / 2)).ToString();
}
else
{
newMin = min_int.ToString();
}
newMax = (value + ((max_int - min_int) / 2)).ToString();
}
P.nodes[i].setAttribute("min", newMin);
P.nodes[i].setAttribute("max", newMax);
}
}
}
lastP = maxQ;
variablesVisualizer.refresh();
}
}
public void iteration_of_optimization()
{
if (opt_inc == 1)
{
string new_save_folder;
expert.copyExpertParametersToAlgorithms();
for (int j = 0; j < expert.algorithms.Count; j++)
{
new_save_folder = form1.pathPrefix + "Optimization\\" + name + "\\" + expert.expertName + "[0]" + "\\" + expert.algorithms[j].getValueByName("model_name") + "\\";
Directory.CreateDirectory(new_save_folder);
expert.algorithms[j].h.setValueByName("save_folder", new_save_folder);
string predictionsFilePath = new_save_folder + "predictions.txt";
expert.algorithms[j].h.setValueByName("predictions_file_path", predictionsFilePath);
expert.algorithms[j].h.setValueByName("json_file_path", new_save_folder + "h.json");
File.WriteAllText(new_save_folder + "h.json", expert.algorithms[j].h.toJSON(0), System.Text.Encoding.Default);
expert.algorithms[j].train();
}
expert.copyHyperparametersFromAlgorithmsToExpert();
expert.H.setValueByName("report_path", form1.pathPrefix + "Optimization\\" + name + "\\" + expert.expertName + "[0]");
expert.H.setValueByName("code", "0");
expert.Save(form1.pathPrefix + "Optimization\\" + name + "\\" + expert.expertName + "[0]");
expert.test_trading(date1, date2, rawDatasetFilePath);
//отрисовка истрии баланса
for (int i = 0; i < expert.deposit1History.Count; i++)
{
variablesVisualizer.addPoint(expert.deposit2History[i] + (expert.deposit1History[i] * expert.closeValueHistory[i]), "exit [0]");
variablesVisualizer.addPoint(expert.deposit2History[i], "deposit2 [0]");
variablesVisualizer.addPoint(expert.closeValueHistory[i], "close [0]");
}
for (int i = 0; i < population_value; i++)
{
expert.H.setValueByName("code", i.ToString());
population[i] = Copy(expert.H, form1.pathPrefix + "Optimization\\" + name + "\\" + expert.expertName + "[0]" + "\\", form1.pathPrefix + "Optimization\\" + name + "\\" + expert.expertName + "[" + i.ToString() + "]" + "\\");
}
variablesIDs.Clear();
recurciveVariableAdding(population[0], 0, name + "[0]");
/* for (int i = 1; i < population_value; i++)
* {
* variablesIDs.Clear();
* recurciveVariableAdding(population[i], 0, name + "[" + i.ToString() + "]");
* } */
refreshEOTree();
variablesVisualizer.refresh();
}
else
{
//kill and concieve
kill_and_conceive();
//mutation
for (int i = 0; i < mutation_rate; i++)
{
mutation();
}
for (int i = 0; i < population_value; i++)
{
File.WriteAllText(form1.pathPrefix + "Optimization\\" + name + "\\" + name + "[" + i.ToString() + "]" + "\\h.json", population[i].toJSON(0), System.Text.Encoding.Default);
}
// ВВЕДЕНО МНОГОКРАТНОЕ ТЕСТИРОВНИЕ ИНДИВИДОВ ВСЕХ КАТЕГОРИЙ ДЛЯ ПОВЫШЕНИЯ ПОВТОРЯЕМОСТИ РЕЗУЛЬТАТОВ
// target_functions - матрица результатов тестирования,
// где номер строки (первый индекс (i)) - индекс индивида, а номер столбца (второй индекс (j)) - итерация тестирования
double[,] target_functions = new double[population_value, test_count];
for (int tc = 0; tc < test_count; tc++)
{
if (opt_inc == 2)
{
if (agentManager.agents.Count == 0)
{
if (multiThreadTraining)
{
if (form1.multiThreadTrainingRATE != 0)
{
multiThreadTrainingRATE = form1.multiThreadTrainingRATE;
}
log("multiThreadTrainingRATE = " + multiThreadTrainingRATE.ToString(), Color.Yellow);
if (multiThreadTrainingRATE > population_value)
{
multiThreadTrainingRATE = population_value;
}
for (int begin = 0; begin < population_value; begin += multiThreadTrainingRATE)
{
var now1 = new DateTimeOffset(DateTime.Now);
var start1 = now1.ToUnixTimeSeconds();
int end = 0;
if (begin + multiThreadTrainingRATE >= population_value)
{
end = population_value;
}
else
{
end = begin + multiThreadTrainingRATE;
}
List <Expert> experts = new List <Expert>();
for (int i = begin; i < end; i++)
{
Expert exp = Expert.Open(form1.pathPrefix + "Optimization\\" + name + "\\" + name + "[" + i.ToString() + "]", name, form1);
// exp.H = population[i].Clone();
experts.Add(exp);
}
Task[] trainTasks = new Task[end - begin];
foreach (Expert exp in experts)
{
trainTasks[experts.IndexOf(exp)] = new Task(() => experts[experts.IndexOf(exp)].trainAllAlgorithms(false));
trainTasks[experts.IndexOf(exp)].Start();
}
foreach (var task in trainTasks)
{
task.Wait();
}
for (int i = begin; i < end; i++)
{
// experts[i].copyHyperparametersFromAlgorithmsToExpert();
experts[i - begin].Save(form1.pathPrefix + "Optimization\\" + name + "\\" + name + "[" + i.ToString() + "]");
population[i] = experts[i - begin].H.Clone();
}
log((end).ToString() + '/' + population_value.ToString() + " training comlete" + TimeSpan.FromSeconds((new DateTimeOffset(DateTime.Now).ToUnixTimeSeconds()) - start1).ToString(), Color.LimeGreen);
}
}
else
{
for (int i = 0; i < population_value; i++)
{
expert = Expert.Open(form1.pathPrefix + "Optimization\\" + name + "\\" + name + "[" + i.ToString() + "]", name, form1);
expert.trainAllAlgorithms(false);
expert.Save(form1.pathPrefix + "Optimization\\" + name + "\\" + name + "[" + i.ToString() + "]");
population[i] = expert.H.Clone();
log((i + 1).ToString() + '/' + population_value.ToString() + " training comlete", Color.LimeGreen);
}
}
}
else
{
for (int i = 0; i < population_value; i++)
{
var algorithmBranches = population[i].getNodesByparentID(expert.committeeNodeID);
foreach (Node algorithmBranch in algorithmBranches)
{
agentManager.tasks.Add(new AgentTask("train", new Hyperparameters(population[i].toJSON(algorithmBranch.ID), form1)));
}
Task.Factory.StartNew(() => { agentManager.work(); }).Wait();
// СПИСОК ВЕТВЕЙ АЛГОРИТМОВ
List <Node> toDelete = population[i].getNodesByparentID(expert.committeeNodeID);
//удаление старых конфигураций алгоритмов
for (int j = 0; j < toDelete.Count; j++)
{
population[i].deleteBranch(toDelete[j].ID);
}
//приращение новых конфигураций к узлу "committee"
for (int j = 0; j < agentManager.tasks.Count; j++)
{
population[i].addBranch(agentManager.tasks[j].h, agentManager.tasks[j].h.nodes[0].name(), expert.committeeNodeID);
}
agentManager.tasks.Clear();
// expert.synchronizeHyperparameters();
File.WriteAllText(form1.pathPrefix + "Optimization\\" + name + "\\" + name + "[" + i.ToString() + "]" + "\\h.json", population[i].toJSON(0), System.Text.Encoding.Default);
}
}
}
for (int i = 0; i < population_value; i++)
{
variablesVisualizer.Clear("committee response [" + i.ToString() + "]");
variablesVisualizer.Clear("deposit2 [" + i.ToString() + "]");
variablesVisualizer.Clear("deposit1 [" + i.ToString() + "]");
variablesVisualizer.Clear("exit [" + i.ToString() + "]");
variablesVisualizer.Clear("close [" + i.ToString() + "]");
}
//Тестирование (вычисление целевой функции)
for (int i = 0; i < population_value; i++)
{
expert = Expert.Open(form1.pathPrefix + "Optimization\\" + name + "\\" + name + "[" + i.ToString() + "]", name, form1);
expert.test_trading(date1, date2, rawDatasetFilePath);
log("test[" + i.ToString() + "]: " + expert.H.getValueByName("expert_target_function"), Color.Purple);
population[i] = expert.H.Clone();
File.WriteAllText(form1.pathPrefix + "Optimization\\" + name + "\\" + name + "[" + i.ToString() + "]" + "\\h.json", population[i].toJSON(0), System.Text.Encoding.Default);
target_functions[i, tc] = Convert.ToDouble(population[i].getValueByName("expert_target_function").Replace('.', ','));
//отрисовка истрии баланса
for (int j = 0; j < expert.deposit1History.Count; j++)
{
variablesVisualizer.addPoint(expert.committeeResponseHistory[j][0], "committee response [" + i.ToString() + "]");
// variablesVisualizer.addPoint(expert.actionHistory[j], "actions [" + i.ToString() + "]");
variablesVisualizer.addPoint(expert.deposit2History[j] + (expert.deposit1History[j] * expert.closeValueHistory[j]), "exit [" + i.ToString() + "]");
variablesVisualizer.addPoint(expert.deposit1History[j], "deposit1 [" + i.ToString() + "]");
variablesVisualizer.addPoint(expert.closeValueHistory[j], "close [" + i.ToString() + "]");
}
variablesVisualizer.refresh();
}
log((tc + 1).ToString() + '/' + test_count.ToString() + " test comlete", Color.LimeGreen);
}
variablesVisualizer.refresh();
//вычисление итоговых значений критерия оптимальности
for (int i = 0; i < population_value; i++)
{
double sum = 0;
// AVG
for (int j = 0; j < test_count; j++)
{
sum += target_functions[i, j];
}
double AVG = sum / test_count;
sum = 0;
// StdDev
for (int j = 0; j < test_count; j++)
{
sum += (AVG - target_functions[i, j]) * (AVG - target_functions[i, j]);
}
double StdDev = Math.Sqrt(sum / test_count);
// если target_function равна (AVG - StdDev), то последующее вычисление критерия оптимальности будет давать результаты ВЫШЕ, чем target_function
population[i].setValueByName("expert_target_function", (AVG - StdDev).ToString().Replace(',', '.'));
population[i].setValueByName("expert_target_function_AVG", (AVG).ToString().Replace(',', '.'));
population[i].setValueByName("expert_target_function_StdDev", (StdDev).ToString().Replace(',', '.'));
// File.WriteAllText(population[i].getValueByName("json_file_path"), population[i].toJSON(0), System.Text.Encoding.Default);
}
// сортировка
Hyperparameters temp;
for (int i = 0; i < population_value - 1; i++)
{
for (int j = i + 1; j < population_value; j++)
{
double i_value = Convert.ToDouble(population[i].getValueByName("expert_target_function").Replace('.', ','));
double j_value = Convert.ToDouble(population[j].getValueByName("expert_target_function").Replace('.', ','));
if (i_value < j_value || (double.IsNaN(i_value) && (!double.IsNaN(j_value))))
{
log(" [" + i.ToString() + "] <- [" + j.ToString() + "]: " + i_value + "<" + j_value, Color.Orchid);
string tempFolder = form1.pathPrefix + "Optimization\\" + name + "\\temp";
string path_to_i = form1.pathPrefix + "Optimization\\" + name + "\\" + name + "[" + i.ToString() + "]";
string path_to_j = form1.pathPrefix + "Optimization\\" + name + "\\" + name + "[" + j.ToString() + "]";
temp = Copy(population[i], path_to_i, tempFolder);
population[i] = Copy(population[j], path_to_j, path_to_i);
population[j] = Copy(temp, tempFolder, path_to_j);
population[i].setValueByName("report_path", form1.pathPrefix + "Optimization\\" + name + "\\" + expert.expertName + "[" + i.ToString() + "]");
population[j].setValueByName("report_path", form1.pathPrefix + "Optimization\\" + name + "\\" + expert.expertName + "[" + j.ToString() + "]");
}
}
}
}
for (int i = 0; i < population_value; i++)
{
population[i].setValueByName("name", population[i].nodes[0].name() + "[" + i.ToString() + "]");
}
log("Обновление отображаемых параметров", Color.Lime);
refreshEOTree();
// A.draw(0, form1.picBox, form1, 15, 150);
variableChangeMonitoring();
variablesVisualizer.addPoint(Convert.ToDouble(population[0].getValueByName("expert_target_function").Replace('.', ',')), "best_individ");
double averegeBest = 0;
for (int i = 0; i < population_value; i++)
{
var t_f = Convert.ToDouble(population[i].getValueByName("expert_target_function").Replace('.', ','));
if (i < population_value * elite_ratio)
{
averegeBest += t_f;
}
variablesVisualizer.addPoint(t_f, " [" + population[i].getValueByName("code") + "]");
}
variablesVisualizer.addPoint((averegeBest / (population_value * elite_ratio)).ToString(), "averege best");
variablesVisualizer.refresh();
}
