//public void SetTimeDays(DateTime trainStart, int trainDays, int testDays)
//{
// SetTimeMinutesFromTrainStart(trainStart, trainDays * 60 * 24, testDays * 60 * 24);
//}
public void GenerateEaOrder(CandidateClassifier bestClassifierInfo, weka.core.Instances testInstances)
{
if (bestClassifierInfo == null)
return;
//int j = m_bestClassifierInfo.DealType == m_dealType[0] ? 0 : 1;
string eaorderFileName = string.Format("{0}\\ea_order.txt", TestParameters.BaseDir);
//Instances testInstances = bestClassifierInfo.CurrentTestInstances;
//Instances testInstancesNew = null;
//Instances testInstances = null;
//if (m_saveDataFile)
//{
// SetTraining(false);
// string testFileName = GetArffFileName(m_dealType[j], m_newFileAppend);
// WekaUtils.Instance.WriteLog("Load instance of " + testFileName);
// testInstancesNew = WekaUtils.LoadInstances(testFileName);
// testInstances = WekaUtils.LoadInstances(GetArffFileName(m_dealType[j]));
//}
//else
//{
// testInstancesNew = m_testInstancesNew[j];
// testInstances = m_testInstances[j];
//}
System.Data.DataTable dt = null;
if (!testInstances.attribute(0).isDate())
{
dt = Feng.Data.DbHelper.Instance.ExecuteDataTable(string.Format("SELECT Date FROM {0} WHERE Date >= '{1}' AND Date < '{2}' {4}",
"EURUSD" + "_" + "M1",
WekaData.m_testTimeStart.ToString(Parameters.DateTimeFormat), WekaData.m_testTimeEnd.ToString(Parameters.DateTimeFormat),
"ORDER BY Time"));
if (dt.Rows.Count != testInstances.numInstances())
{
WekaUtils.Instance.WriteLog("different count!");
return;
}
}
//else
//{
// if (testInstancesNew.numInstances() != testInstances.numInstances())
// {
// WekaUtils.Instance.WriteLog("different count!");
// return;
// }
//}
// todo: save info in file
//for (int j = 0; j < m_dealType.Length; ++j)
//{
// if (m_saveDataFile)
// {
// string modelFileName = GetModelFileName(m_dealType[j]);
// WriteLog("Load model of " + modelFileName);
// //ObjectInputStream ois = new ObjectInputStream(new FileInputStream(modelFileName));
// //Classifier cls = (Classifier)ois.readObject();
// //ois.close();
// m_bestClassifier[m_dealType[j]] = (Classifier)weka.core.SerializationHelper.read(modelFileName);
// }
//}
//foreach (string testFileName in System.IO.Directory.GetFiles(m_baseDir, NormalizeFileName(string.Format("{0}_{1}_{2}_*.arff", m_symbol, dt1.ToString(m_dateTimeFormat), dt2.ToString(m_dateTimeFormat)))))
//{
// string[] ss2 = System.IO.Path.GetFileNameWithoutExtension(testFileName).Split(new char[] { '_' }, StringSplitOptions.RemoveEmptyEntries);
// if (ss2.Length != 5)
// continue;
// try
// {
// m_trainTimeStart = ConvertFileNameToDateTime(ss2[1]);
// m_trainTimeEnd = ConvertFileNameToDateTime(ss2[2]);
// m_testTimeStart = ConvertFileNameToDateTime(ss2[3]);
// m_testTimeEnd = ConvertFileNameToDateTime(ss2[4]);
// }
// catch (Exception)
// {
// continue;
// }
double[] tr = bestClassifierInfo.CurrentTestRet;
double[] cv = bestClassifierInfo.CurrentClassValue;
using (StreamWriter sw = new StreamWriter(eaorderFileName, true))
{
for (int i = 0; i < testInstances.numInstances(); i++)
{
string clsLabels;
double v = tr[i];
if (v != double.NaN)
{
clsLabels = testInstances.classAttribute().value((int)v);// CalcAction(v);
}
else
{
clsLabels = "0";
}
string clsLabel;
if (clsLabels == "2")
{
clsLabel = bestClassifierInfo.DealType == 'B' ? "1" : "-1";
}
else
{
clsLabel = "0";
}
//if (clsLabels.Length >= 2)
//{
// if (clsLabels[0] == "1" && clsLabels[1] == "0")
// clsLabel = "1";
// else if (clsLabels[0] == "0" && clsLabels[1] == "1")
// clsLabel = "-1";
// else if (clsLabels[0] == "1" && clsLabels[1] == "1")
// clsLabel = "2";
//}
//else if (clsLabels.Length == 1)
//{
// if (clsLabels[0] == "1")
// {
// if (m_dealType[0] == "B")
// clsLabel = "1";
// else if (m_dealType[0] == "S")
// clsLabel = "-1";
// }
//}
//else
//{
// throw new AssertException("invalid clsLabels.Length");
//}
string date;
string dateClose = string.Empty;
if (testInstances.attribute(0).isDate())
{
date = WekaUtils.GetDateValueFromInstances(testInstances, 0, i).ToString(Parameters.DateTimeFormat);
dateClose = WekaUtils.GetDateValueFromInstances(testInstances, 1, i).ToString(Parameters.DateTimeFormat);
}
else
{
date = ((DateTime)dt.Rows[i]["Date"]).ToString(Parameters.DateTimeFormat);
}
sw.WriteLine(string.Format("{0}, {1}, {2}, {3}, 0, 0, {4}, {5}",
m_actions[clsLabel], date, bestClassifierInfo.Tp, bestClassifierInfo.Sl, dateClose, cv[i] == v ? "Right" : "Wrong"));
//ret[ConvertFileNameToDateTime(date)] = clsLabel;
}
}
//// save labeled data
//BufferedWriter writer = new BufferedWriter(new FileWriter(string.Format("c:\\eurusd_m1_arff.result")));
//writer.write(labeled.toString());
//writer.newLine();
//writer.flush();
//writer.close();
}
private void TrainandTest()
{
var c = new CandidateClassifier("Test", m_currentTp, m_currentSl, Parameters.AllDealTypes[0], 0, null);
TrainandTest(c, null);
//var ev = (new MyEvaluation(TestParameters.CostMatrix));
//ev.evaluateModel(c.Classifier, c.CurrentTrainInstancesNew1);
//ev.evaluateModel(c.Classifier, c.CurrentTestInstancesNew1);
}
public void TrainandTest(CandidateClassifier classifierInfo, CandidateParameter cp)
{
//string dealType = classifierInfo.DealType;
Classifier cls = null;
if (TestParameters.UseTrain)
{
string modelFileName = GetModelFileName(classifierInfo.Name);
if (TestParameters.SaveModel)
{
cls = WekaUtils.TryLoadClassifier(modelFileName);
}
Instances trainInstancesNew, trainInstances;
trainInstances = m_trainInstances;
trainInstancesNew = m_trainInstancesNew;
if (cls == null)
{
if (classifierInfo.Classifier == null)
{
classifierInfo.Classifier = WekaUtils.CreateClassifier(cp.ClassifierType, m_currentTp, m_currentSl);
}
cls = classifierInfo.Classifier;
}
else
{
if (TestParameters.EnableDetailLog)
{
System.Console.WriteLine("Model is loaded.");
}
}
if (m_enableTrainSplitTest)
{
Instances trainTrainInst, trainTestInst;
DateTime splitTrainTimeEnd;
if (m_trainSplitTestNums != -1)
{
int trainTrainSize = trainInstancesNew.numInstances() - m_trainSplitTestNums;
int trainTestSize = m_trainSplitTestNums;
trainTrainInst = new Instances(trainInstancesNew, 0, trainTrainSize);
trainTestInst = new Instances(trainInstancesNew, trainTrainSize, trainTestSize);
splitTrainTimeEnd = WekaUtils.GetDateValueFromInstances(trainInstances, 0, trainTrainSize);
}
else if (m_trainSplitPercent != -1)
{
if (m_trainSplitPercent == 100.0)
{
int trainTrainSize = trainInstancesNew.numInstances();
trainTrainInst = new Instances(trainInstancesNew, 0, trainTrainSize);
trainTestInst = new Instances(trainInstancesNew, 0, trainTrainSize);
splitTrainTimeEnd = WekaUtils.GetDateValueFromInstances(trainInstances, 0, trainTrainSize);
}
else
{
int trainTrainSize = (int)Math.Round(trainInstancesNew.numInstances() * m_trainSplitPercent / 100);
int trainTestSize = trainInstancesNew.numInstances() - trainTrainSize;
trainTrainInst = new Instances(trainInstancesNew, 0, trainTrainSize);
trainTestInst = new Instances(trainInstancesNew, trainTrainSize, trainTestSize);
splitTrainTimeEnd = WekaUtils.GetDateValueFromInstances(trainInstances, 0, trainTrainSize);
}
}
else
{
trainTrainInst = new Instances(trainInstancesNew, 0);
trainTestInst = new Instances(trainInstancesNew, 0);
DateTime dt = WekaUtils.GetDateValueFromInstances(trainInstances, 0, trainInstances.numInstances() - 1);
splitTrainTimeEnd = m_trainTimeEnd.AddMinutes(-TestParameters.BatchTestMinutes);
while (splitTrainTimeEnd > dt)
{
splitTrainTimeEnd = splitTrainTimeEnd.AddMinutes(-TestParameters.BatchTestMinutes);
}
for (int i = 0; i < trainInstances.numInstances(); ++i)
{
dt = WekaUtils.GetDateValueFromInstances(trainInstances, 0, i);
if (dt <= splitTrainTimeEnd)
{
var ins = new DenseInstance(trainInstancesNew.instance(i));
trainTrainInst.add(ins);
}
else
{
var ins = new DenseInstance(trainInstancesNew.instance(i));
trainTestInst.add(ins);
}
}
}
cls = WekaUtils.TrainInstances(trainTrainInst, TestParameters.SaveModel ? modelFileName : null, cls);
//m_classifierQueue[dealType].Enqueue(new ClassifierInfo(cls, splitTrainTimeEnd));
//foreach (var i in m_classifierQueue[dealType])
//{
// var e = WekaUtils.TestInstances(trainTestInst, i.Cls);
// i.TotalCost = i.TotalCost * m_classifierQueueFactor + e.totalCost();
// i.TotalNum = (int)(i.TotalNum * m_classifierQueueFactor) + (int)e.numInstances();
//}
//WriteEvalSummary(eval1, string.Format("Test Data from {0} to {1}", m_testTimeStart.ToString(Parameters.DateTimeFormat), m_testTimeEnd.ToString(Parameters.DateTimeFormat)));
}
else
{
cls = WekaUtils.TrainInstances(trainInstancesNew, TestParameters.SaveModel ? modelFileName : null, cls);
//m_classifierQueue[dealType].Enqueue(new ClassifierInfo(cls, m_trainTimeEnd));
//foreach (var i in m_classifierQueue[dealType])
//{
// var e = WekaUtils.TestInstances(trainInstancesNew, i.Cls);
// i.TotalCost = i.TotalCost * m_classifierQueueFactor + e.totalCost();
// i.TotalNum = (int)(i.TotalNum * m_classifierQueueFactor) + (int)e.numInstances();
//}
}
if (TestParameters.EnableDetailLog)
{
System.Console.WriteLine("Model is trained.");
}
classifierInfo.Classifier = cls;
//if (classifierInfo.CurrentTrainInstances1 != null)
//{
// classifierInfo.CurrentTrainInstances1.clear();
//}
//if (classifierInfo.CurrentTrainInstancesNew1 != null)
//{
// classifierInfo.CurrentTrainInstancesNew1.clear();
//}
//classifierInfo.CurrentTrainInstances = new Instances(trainInstances, 0, trainInstances.numInstances());
//classifierInfo.CurrentTrainInstancesNew = new Instances(trainInstancesNew, 0, trainInstancesNew.numInstances());
if (classifierInfo.MoneyManagement == null)
{
classifierInfo.MoneyManagement = WekaUtils.CreateMoneyManagement(cp.MoneyManagementType, m_currentTp, m_currentSl);
}
IMoneyManagement mm = WekaUtils.TrainInstances4MM(trainInstancesNew, TestParameters.SaveModel ? modelFileName : null, classifierInfo.MoneyManagement);
classifierInfo.MoneyManagement = mm;
}
else
{
if (classifierInfo.Classifier == null)
{
classifierInfo.Classifier = WekaUtils.CreateClassifier(cp.ClassifierType, m_currentTp, m_currentSl);
}
cls = classifierInfo.Classifier;
if (classifierInfo.MoneyManagement == null)
{
classifierInfo.MoneyManagement = WekaUtils.CreateMoneyManagement(cp.MoneyManagementType, m_currentTp, m_currentSl);
}
}
if (m_enableTest)
{
Instances testInstancesNew, testInstances;
testInstances = m_testInstances;
testInstancesNew = m_testInstancesNew;
double[] cv = WekaUtils.ClassifyInstances(testInstancesNew, cls);
if (TestParameters.EnableExcludeClassifier)
{
bool hasPositive = false;
for (int i = 0; i < cv.Length; ++i)
{
if (cv[i] == 2)
{
hasPositive = true;
break;
}
}
if (hasPositive)
{
// Exclude
if (classifierInfo.ExcludeClassifier == null)
{
string modelFileName4Exclude = GetExcludeModelFileName(classifierInfo.Name);
classifierInfo.ExcludeClassifier = WekaUtils.TryLoadClassifier(modelFileName4Exclude);
}
if (classifierInfo.ExcludeClassifier != null)
{
double[] cv2 = WekaUtils.ClassifyInstances(testInstancesNew, classifierInfo.ExcludeClassifier);
// cv2 == 0 -> is class, otherwise = double.NaN;
for (int i = 0; i < cv.Length; ++i)
{
cv[i] = cv[i] == 2 && cv2[i] == 2 ? 2 : 0;
}
}
}
}
classifierInfo.CurrentTestRet = cv;
classifierInfo.CurrentClassValue = new double[testInstances.numInstances()];
for (int i = 0; i < testInstances.numInstances(); ++i)
{
classifierInfo.CurrentClassValue[i] = testInstances.instance(i).classValue();
}
for (int i = 0; i < testInstances.numInstances(); i++)
{
if (cv[i] == 2)
{
double openPrice = testInstances.instance(i).value(testInstances.attribute("mainClose"));
DateTime openTime = WekaUtils.GetDateValueFromInstances(testInstances, 0, i);
if (testInstances.instance(i).classValue() == 2 || testInstances.instance(i).classValue() == 0)
{
classifierInfo.Deals.AddDeal(openTime,
openPrice,
classifierInfo.DealType,
classifierInfo.MoneyManagement.GetVolume(testInstances.instance(i)),
testInstances.instance(i).classValue() == 2 ? -classifierInfo.Tp : classifierInfo.Sl,
WekaUtils.GetDateValueFromInstances(testInstances, 1, i));
}
else if (testInstances.instance(i).classValue() == 1)
{
double closePriceTp, closePriceSl;
if (classifierInfo.DealType == 'B')
{
closePriceTp = openPrice + classifierInfo.Tp * DealsInfo.GetPoint(0);
closePriceSl = openPrice - classifierInfo.Sl * DealsInfo.GetPoint(0);
}
else
{
closePriceTp = openPrice - classifierInfo.Tp * DealsInfo.GetPoint(0);
closePriceSl = openPrice + classifierInfo.Sl * DealsInfo.GetPoint(0);
}
classifierInfo.Deals.AddDeal(openTime,
openPrice,
classifierInfo.DealType,
classifierInfo.MoneyManagement.GetVolume(testInstances.instance(i)),
closePriceTp, closePriceSl);
}
else
{
throw new AssertException("classValue should be 0,1,2.");
}
}
}
}
}
protected void InitClassifierInfos(ParameterdCandidateStrategy parent = null)
{
//int[] sls = m_batchSls != null ? m_batchSls : (m_sl.HasValue ? new int[] { m_sl.Value } : new int[] { 50, 70 });
//int[][] tps = m_batchTps != null ? m_batchTps : (m_tp.HasValue ? new int[][] { new int[] { m_tp.Value } }
// : new int[][] { new int[] { 100, 140 }, new int[] { 50, 70 } });
//if (Parameters.AllDealTypes == null || Parameters.AllDealTypes.Length == 0)
//{
// Parameters.AllDealTypes = new char[] { 'B', 'S' };
//}
if (parent == null)
{
m_classifierInfos.Clear();
m_classifierInfoIdxs = new CandidateClassifier[Parameters.AllDealTypes.Length, this.CandidateParameter.BatchTps.Length, this.CandidateParameter.BatchSls.Length, Parameters.AllHour];
m_totalScores = new double[m_classifierInfoIdxs.GetLength(0), m_classifierInfoIdxs.GetLength(1), m_classifierInfoIdxs.GetLength(2), m_classifierInfoIdxs.GetLength(3)];
m_totalDeals = new int[m_classifierInfoIdxs.GetLength(0), m_classifierInfoIdxs.GetLength(1), m_classifierInfoIdxs.GetLength(2), m_classifierInfoIdxs.GetLength(3)];
for (int k = 0; k < m_classifierInfoIdxs.GetLength(0); ++k)
{
for (int i = 0; i < m_classifierInfoIdxs.GetLength(1); ++i)
{
for (int j = 0; j < m_classifierInfoIdxs.GetLength(2); ++j)
{
int tp = this.CandidateParameter.BatchTps[i];
int sl = this.CandidateParameter.BatchSls[j];
if (!TestParameters.EnablePerhourTrain)
{
string name = string.Format("{0}_{1}_{2}", Parameters.AllDealTypes[k], tp, sl);
m_classifierInfos[name] = new CandidateClassifier(name, tp, sl, Parameters.AllDealTypes[k], -1, this.CandidateParameter);
m_classifierInfoIdxs[k, i, j, 0] = m_classifierInfos[name];
m_totalScores[k, i, j, 0] = 0;
m_totalDeals[k, i, j, 0] = 0;
}
else
{
for (int h = 0; h < m_classifierInfoIdxs.GetLength(3); ++h)
{
//if (h != 9)
// continue;
string name = string.Format("{0}_{1}_{2}_H{3}", Parameters.AllDealTypes[k], tp, sl, h);
m_classifierInfos[name] = new CandidateClassifier(name, tp, sl, Parameters.AllDealTypes[k], h, this.CandidateParameter);
m_classifierInfoIdxs[k, i, j, h] = m_classifierInfos[name];
m_totalScores[k, i, j, h] = 0;
m_totalDeals[k, i, j, h] = 0;
}
}
}
}
}
this.HasParent = false;
}
else
{
m_classifierInfoIdxs = parent.m_classifierInfoIdxs;
m_totalScores = new double[m_classifierInfoIdxs.GetLength(0), m_classifierInfoIdxs.GetLength(1), m_classifierInfoIdxs.GetLength(2), m_classifierInfoIdxs.GetLength(3)];
m_totalDeals = new int[m_classifierInfoIdxs.GetLength(0), m_classifierInfoIdxs.GetLength(1), m_classifierInfoIdxs.GetLength(2), m_classifierInfoIdxs.GetLength(3)];
m_classifierInfos = parent.m_classifierInfos;
this.HasParent = true;
}
}
public void SaveTestData(CandidateClassifier clsInfo, DateTime nowDate)
{
if (TestParameters.OnlyNewestTestDataSaved)
{
string sql = string.Format("DELETE FROM {0}", m_testDataTableName);
Feng.Data.DbHelper.Instance.ExecuteNonQuery(sql);
}
string str = WekaUtils.DoubleArrayToIntString(clsInfo.CurrentTestRet);
string scv = WekaUtils.DoubleArrayToIntString(clsInfo.CurrentClassValue);
if (m_testDataInsertTable == null)
{
m_testDataInsertTable = new System.Data.DataTable();
m_testDataInsertTable.Columns.Add("Id", typeof(int));
m_testDataInsertTable.Columns.Add("Time", typeof(long));
//m_testDataInsertTable.Columns.Add("Type", typeof(int));
m_testDataInsertTable.Columns.Add("ClsName", typeof(string));
m_testDataInsertTable.Columns.Add("TestResult", typeof(string));
m_testDataInsertTable.Columns.Add("ClassValue", typeof(string));
m_testDataInsertTable.Columns.Add("DealsInfo", typeof(byte[]));
m_testDataInsertTable.Columns.Add("DealsData", typeof(byte[]));
}
var row = m_testDataInsertTable.NewRow();
row["ClsName"] = clsInfo.Name;
//row["Type"] = m_testDataType;
row["Time"] = WekaUtils.GetTimeFromDate(nowDate);
row["TestResult"] = str;
row["ClassValue"] = scv;
row["DealsInfo"] = Feng.Windows.Utils.SerializeHelper.Serialize(clsInfo.Deals);
bool shouldSave = false;
if (nowDate.DayOfWeek != DayOfWeek.Sunday && nowDate.DayOfWeek != DayOfWeek.Saturday && nowDate.Day == 20)
{
shouldSave = true;
}
if (nowDate.Day == 21 && nowDate.DayOfWeek == DayOfWeek.Monday)
{
shouldSave = true;
}
if (nowDate.Day == 22 && nowDate.DayOfWeek == DayOfWeek.Monday)
{
shouldSave = true;
}
if (TestParameters.OnlyNewestTestDataSaved)
{
shouldSave = true;
}
if (shouldSave)
{
byte[] dealsData = Feng.Windows.Utils.SerializeHelper.Serialize(clsInfo.Deals.Deals);
System.IO.MemoryStream outStream = new System.IO.MemoryStream();
using (System.IO.Compression.GZipStream zipStream =
new System.IO.Compression.GZipStream(outStream, System.IO.Compression.CompressionMode.Compress))
{
System.IO.MemoryStream inStream = new System.IO.MemoryStream(dealsData);
inStream.CopyTo(zipStream);
}
row["DealsData"] = outStream.ToArray();
}
else
{
row["DealsData"] = System.DBNull.Value;
}
m_testDataInsertTable.Rows.Add(row);
if (m_testDataInsertTable.Rows.Count > 100)
{
//WekaUtils.Instance.WriteLog("Save Test Data.");
try
{
Feng.Data.DbHelper.Instance.BulkCopy(m_testDataInsertTable, m_testDataTableName);
}
catch (Exception ex)
{
WekaUtils.Instance.WriteLog(ex.Message);
}
m_testDataInsertTable.Rows.Clear();
}
//SqlCommand cmd = new SqlCommand("INSERT INTO TestData ([ClsName],[Time], [Type], TestResult, ClassValue, DealsData) VALUES (@ClsName, @Time, @Type, @TestResult, @ClassValue, @DealsData)");
//cmd.Parameters.AddWithValue("@ClsName", clsInfo.Name);
//cmd.Parameters.AddWithValue("@Type", m_testDataType);
//cmd.Parameters.AddWithValue("@Time", WekaUtils.GetTimeFromDate(currentDate));
//cmd.Parameters.AddWithValue("@TestResult", str);
//cmd.Parameters.AddWithValue("@ClassValue", scv);
//cmd.Parameters.AddWithValue("@DealsData", Feng.Utils.SerializeHelper.Serialize(clsInfo.Deals));
//SetTransaction(cmd);
}
protected void InitClassifierInfos(ParameterdCandidateStrategy parent = null)
{
//int[] sls = m_batchSls != null ? m_batchSls : (m_sl.HasValue ? new int[] { m_sl.Value } : new int[] { 50, 70 });
//int[][] tps = m_batchTps != null ? m_batchTps : (m_tp.HasValue ? new int[][] { new int[] { m_tp.Value } }
// : new int[][] { new int[] { 100, 140 }, new int[] { 50, 70 } });
//if (Parameters.AllDealTypes == null || Parameters.AllDealTypes.Length == 0)
//{
// Parameters.AllDealTypes = new char[] { 'B', 'S' };
//}
if (parent == null)
{
m_classifierInfos.Clear();
m_classifierInfoIdxs = new CandidateClassifier[Parameters.AllDealTypes.Length, this.CandidateParameter.BatchTps.Length, this.CandidateParameter.BatchSls.Length, Parameters.AllHour];
m_totalScores = new double[m_classifierInfoIdxs.GetLength(0), m_classifierInfoIdxs.GetLength(1), m_classifierInfoIdxs.GetLength(2), m_classifierInfoIdxs.GetLength(3)];
m_totalDeals = new int[m_classifierInfoIdxs.GetLength(0), m_classifierInfoIdxs.GetLength(1), m_classifierInfoIdxs.GetLength(2), m_classifierInfoIdxs.GetLength(3)];
for (int k = 0; k < m_classifierInfoIdxs.GetLength(0); ++k)
{
for (int i = 0; i < m_classifierInfoIdxs.GetLength(1); ++i)
{
for (int j = 0; j < m_classifierInfoIdxs.GetLength(2); ++j)
{
int tp = this.CandidateParameter.BatchTps[i];
int sl = this.CandidateParameter.BatchSls[j];
if (!TestParameters.EnablePerhourTrain)
{
string name = string.Format("{0}_{1}_{2}", Parameters.AllDealTypes[k], tp, sl);
m_classifierInfos[name] = new CandidateClassifier(name, tp, sl, Parameters.AllDealTypes[k], -1, this.CandidateParameter);
m_classifierInfoIdxs[k, i, j, 0] = m_classifierInfos[name];
m_totalScores[k, i, j, 0] = 0;
m_totalDeals[k, i, j, 0] = 0;
}
else
{
for (int h = 0; h < m_classifierInfoIdxs.GetLength(3); ++h)
{
//if (h != 9)
// continue;
string name = string.Format("{0}_{1}_{2}_H{3}", Parameters.AllDealTypes[k], tp, sl, h);
m_classifierInfos[name] = new CandidateClassifier(name, tp, sl, Parameters.AllDealTypes[k], h, this.CandidateParameter);
m_classifierInfoIdxs[k, i, j, h] = m_classifierInfos[name];
m_totalScores[k, i, j, h] = 0;
m_totalDeals[k, i, j, h] = 0;
}
}
}
}
}
this.HasParent = false;
}
else
{
m_classifierInfoIdxs = parent.m_classifierInfoIdxs;
m_totalScores = new double[m_classifierInfoIdxs.GetLength(0), m_classifierInfoIdxs.GetLength(1), m_classifierInfoIdxs.GetLength(2), m_classifierInfoIdxs.GetLength(3)];
m_totalDeals = new int[m_classifierInfoIdxs.GetLength(0), m_classifierInfoIdxs.GetLength(1), m_classifierInfoIdxs.GetLength(2), m_classifierInfoIdxs.GetLength(3)];
m_classifierInfos = parent.m_classifierInfos;
this.HasParent = true;
}
}
public static void PrintDealInfoSum(DateTime date)
{
string sql = ("SELECT Time, ClsName, TestResult, ClassValue, DealsInfo, DealsData FROM TestData WHERE [Time] >= @Time1 AND [Time] < @Time2 ORDER BY Time, ClsName");
SqlCommand cmd = new SqlCommand(string.Format(sql));
cmd.Parameters.AddWithValue("@Time1", WekaUtils.GetTimeFromDate(date));
cmd.Parameters.AddWithValue("@Time2", WekaUtils.GetTimeFromDate(date.AddDays(1)));
var dt = DbHelper.Instance.ExecuteDataTable(cmd);
StringBuilder sb = new StringBuilder();
foreach (System.Data.DataRow row in dt.Rows)
{
var clsInfo = new CandidateClassifier(row["ClsName"].ToString(), 0, 0, 'B', -1, null);
clsInfo.SetData((string)row["TestResult"], (string)row["ClassValue"], (byte[])row["DealsInfo"], (byte[])row["DealsData"]);
string s = clsInfo.Deals.PrintAll();
sb.AppendLine(clsInfo.Name);
sb.AppendLine(s);
}
Console.WriteLine(sb.ToString());
Console.ReadLine();
}
public static void PrintDealInfoDetail(string clsInfoName, DateTime date)
{
string sql = ("SELECT Time, ClsName, TestResult, ClassValue, DealsInfo, DealsData FROM TestData WHERE [Time] = @Time AND ClsName = @ClsName");
SqlCommand cmd = new SqlCommand(string.Format(sql));
cmd.Parameters.AddWithValue("@Time", WekaUtils.GetTimeFromDate(date));
cmd.Parameters.AddWithValue("@ClsName", clsInfoName);
var dt = DbHelper.Instance.ExecuteDataTable(cmd);
var row = dt.Rows[0];
var clsInfo = new CandidateClassifier(clsInfoName, 0, 0, 'B', -1, null);
clsInfo.SetData((string)row["TestResult"], (string)row["ClassValue"], (byte[])row["DealsInfo"], (byte[])row["DealsData"]);
string s = clsInfo.Deals.PrintAll(true);
Console.WriteLine(s);
Console.ReadLine();
}