protected String GenerateConfigFile(String filePath, String symbol, String training_file_path, String testing_file_path, String unique_id)
{
String output_file_base = filePath + "_results_";
String config_file_name = filePath + "_config" + unique_id + ".txt";
List <String> labels = new List <String>
{
"KNN_num_neighbors",
"num_training_pts",
"samples_per_group",
"window_size",
"avg_target",
"good_target",
"bad_target",
"min_samples",
"thresh1",
"thresh2",
"future_lookahead",
"s_name",
"description",
"training_file",
"training_start",
"training_end",
"testing_file",
"testing_start",
"testing_end",
"output_csv_file",
"output_txt_file",
"output_pdf_file"
};
List <String> values = new List <String>
{
KNN_num_neighbors.ToString(),
num_training_pts.ToString(),
samples_per_group.ToString(),
window_size.ToString(),
avg_target.ToString(),
good_target.ToString(),
bad_target.ToString(),
min_samples.ToString(),
thresh1.ToString(),
thresh2.ToString(),
FutureValueDaysToLookAhead.ToString(),
symbol,
description,
training_file_path,
TrainingStartDate.ToShortDateString(),
TrainingEndDate.ToShortDateString(),
testing_file_path,
TestingStartDate.ToShortDateString(),
TestingEndDate.ToShortDateString(),
output_file_base + "data" + unique_id + ".csv",
output_file_base + "summary" + unique_id + ".txt",
output_file_base + "plot" + unique_id + ".pdf",
};
List <String> types = new List <String>
{
"int",
"int",
"int",
"int",
"float",
"float",
"float",
"int",
"float",
"float",
"int",
"str",
"str",
"str",
"str",
"str",
"str",
"str",
"str",
"str",
"str",
"str"
};
var cfg = new StringBuilder();
for (int i = 0; i < labels.Count; i++)
{
cfg.AppendLine(labels[i] + "=" + values[i] + "#" + types[i]);
}
File.WriteAllText(config_file_name, cfg.ToString());
return(config_file_name);
}
protected override void OnBarUpdate()
{
//if (CurrentBar > (Count - 2)) //This means we have processed all historical data (https://ninjatrader.com/support/forum/showthread.php?t=66713)
//{
// Random rnd = new Random();
// String unique_id = "_" + rnd.Next(100000, 999999).ToString(); // creates a number between 100k and 999k
// String control_file_path = output_folder + "control_file" + unique_id + ".txt";
// String consolidated_txt_file_path = output_folder + "consolidated_report" + unique_id + ".txt";
// String consolidated_csv_file_path = output_folder + "consolidated_report" + unique_id + ".csv";
// switch (indicator_to_use)
// {
// case IndicatorEnum.indicator_MACD:
// if (Sanitize == false)
// description = "MACD";
// else
// description = "M";
// description = description + "(" + Param1.ToString() + "-" + Param2.ToString() + "-" + Param3.ToString() + ")";
// break;
// case IndicatorEnum.indicator_RSI:
// if (Sanitize == false)
// description = "RSI";
// else
// description = "R";
// description = description + "(" + Param1.ToString() + "-" + Param2.ToString() + ")";
// break;
// default:
// description = "Unknown";
// break;
// }
// description = description + " - " + FutureValueDaysToLookAhead.ToString();
// if (Sanitize == false)
// description = description + " days";
// description = description + " - " + unique_id.Substring(1); //remove preceding "_"
// bool bFirstTime = true;
// for (int i = 1; i < symbol_list.Length; i++) //Start at index=1 since we want to ignore the first primary/dummy instrument
// {
// String symbol_name = symbol_list[i];
// if (Sanitize == true)
// symbol_name = symbol_list[i][0].ToString();
// String base_file_path_for_symbol = output_folder + symbol_name; //i.e. c:\temp\knn\AAPL
// String training_file_path = base_file_path_for_symbol + "_training" + unique_id + ".csv";
// String testing_file_path = base_file_path_for_symbol + "_testing" + unique_id + ".csv";
// WriteListToCSV(list_Indicator_FutureValueChange_Training_ALL[i], training_file_path);
// WriteListToCSV(list_Indicator_FutureValueChange_Testing_ALL[i], testing_file_path);
// String config_file_name = "";
// config_file_name = GenerateConfigFile(base_file_path_for_symbol, symbol_name, training_file_path, testing_file_path, unique_id);
// if (bFirstTime) //create new file
// {
// bFirstTime = false;
// File.WriteAllText(control_file_path, config_file_name + "\r\n");
// }
// else // append to existing file
// {
// File.AppendAllText(control_file_path, config_file_name + "\r\n");
// }
// }
// //Now we can call python for all symbols at once by passing in the control_file as cmd line arg
// CallPythonScript(output_folder + "\\Data_Processing25.py", control_file_path + " " + consolidated_txt_file_path + " " + consolidated_csv_file_path + " true");
//}
//double Current_Value = Closes[0][0]; //get the most recent Close data for the input symbol (index 0)
//double Prev_Value = Closes[0][0];
////double greg_indicator_value = GregIndicator1(BarsArray[0], 1.0)[0];
//if (CurrentBar >= DaysToLookBack) //make sure we have enough data loaded to look back n days
//{
// Prev_Value = Closes[0][DaysToLookBack];
//}
//// if (Current_Value >
//// double Prev_Value = Close[CurrentBar - DaysToLookBack];
//double Percent_Change = (Current_Value / Prev_Value) - 1.0;
//if (Buy_Price != 0.0)
//{
// if ((Current_Value / Buy_Price - 1.0) > 0.02) //sell if gain > 2%
// {
// Buy_Price = 0.0;
// //ExitLong();
// //ExitLong("Percent Drop", "Percent Drop");
// ExitLong(0, 100, "Exit Long from Percent Drop", "Percent Drop");
// //ExitLong("Selling - Went + 2%");
// //EnterShort("Selling - Went + 2%");
// }
// //else if ((CurrentBar - BarBought) > 20) //sell after 20 days
// //{
// // Buy_Price = 0.0;
// // ExitLong();
// // //ExitLong("Selling - Waited 20 days");
// // //EnterShort("Selling - Waited 20 days");
// // }
//}
//if (Percent_Change < -0.02)
//{
// //if (entryOrder == null)
// //{
// EnterLong(0, 100, "Percent Drop");
// //}
// //EnterLong();
// //EnterLong("Buying - Dropped 2%");
// //EnterLong(0, 100, "Percent Drop");
// //SetTrailStop(CalculationMode.Percent, 0.02);
// //SetStopLoss(CalculationMode.Percent, 0.05);
// Buy_Price = Current_Value;
// BarBought = CurrentBar;
// //SetTrailStop(CalculationMode.Percent, 0.01);
//}
int BarIndex = BarsInProgress;
bool bFinishedProcessingAllData = false;
if (((CurrentBar + 2) == Count) && BarIndex == (symbol_list.Count - 1)) //we are on the last bar to process
{
bFinishedProcessingAllData = true;
}
if ((BarIndex >= 1) && (BarIndex < (symbol_list.Count))) //Start at index=1 since we want to ignore the primary/dummy instrument
{
if (CurrentBar >= (FutureValueDaysToLookAhead)) //just make sure we avoid out of bounds error in case we don't yet have enough data
{
//DateTime current_date = Times[0][0].Date;
DateTime date_to_process = Times[BarIndex][FutureValueDaysToLookAhead].Date; //need to wait FutureValueDaysToLookAhead days before we can make calcs
bool bWithinTrainingPeriod = (date_to_process >= TrainingStartDate) && (date_to_process <= TrainingEndDate);
bool bWithinTestingPeriod = (date_to_process >= TestingStartDate) && (date_to_process <= TestingEndDate);
if ((bWithinTrainingPeriod) || (bWithinTestingPeriod))
{
//TimeSpan diff = TrainingEndDate - TrainingStartDate;
//int training_days = (int)Math.Abs(Math.Round(diff.TotalDays));
double indicator_value = 0.0;
switch (indicator_to_use)
{
case IndicatorEnum.indicator_MACD:
indicator_value = MACD(BarsArray[BarIndex], Param1, Param2, Param3)[FutureValueDaysToLookAhead]; //get the indicator val from n days ago
break;
case IndicatorEnum.indicator_RSI:
indicator_value = RSI(BarsArray[BarIndex], Param1, Param2)[FutureValueDaysToLookAhead]; //get the indicator val from n days ago
break;
case IndicatorEnum.indicator_BOLLINGER:
double upper_band = Bollinger(BarsArray[BarIndex], (double)Param1, Param2).Upper[FutureValueDaysToLookAhead]; //get the indicator val from n days ago
double middle_band = Bollinger(BarsArray[BarIndex], (double)Param1, Param2).Middle[FutureValueDaysToLookAhead]; //get the indicator val from n days ago
double lower_band = Bollinger(BarsArray[BarIndex], (double)Param1, Param2).Lower[FutureValueDaysToLookAhead]; //get the indicator val from n days ago
double current_price = Closes[BarIndex][FutureValueDaysToLookAhead];
double diff = current_price - middle_band;
double band_range = upper_band - middle_band;
indicator_value = diff / band_range; //how far current price is from the middle band (-1.0 means we're at the lower band, +1 means we're at the upper band)
break;
case IndicatorEnum.indicator_STOCHASTIC:
//use the "D" value
indicator_value = Stochastics(BarsArray[BarIndex], Param1, Param2, Param3).D[FutureValueDaysToLookAhead]; //get the indicator val from n days ago
break;
case IndicatorEnum.indicator_STOCHASTIC_RSI:
indicator_value = StochRSI(BarsArray[BarIndex], Param1)[FutureValueDaysToLookAhead]; //get the indicator val from n days ago
break;
case IndicatorEnum.indicator_GREG:
indicator_value = -999.999; // GregIndicator1(BarsArray[BarIndex], (float)Param1)[FutureValueDaysToLookAhead]; //get the indicator val from n days ago
break;
default:
indicator_value = -999.99;
break;
}
if (double.IsNaN(indicator_value))
{
indicator_value = 0.0;
}
double future_price_change = 0.0;
double future_price = Closes[BarIndex][0];
double start_price = Closes[BarIndex][FutureValueDaysToLookAhead];
future_price_change = ((future_price / start_price) - 1.0) * 100.0;
Indicator_FutureValueChange_Pair indicator_pair = new Indicator_FutureValueChange_Pair();
indicator_pair.Date = date_to_process;
indicator_pair.Price = start_price;
indicator_pair.Indicator = indicator_value;
indicator_pair.FutureValueChange = future_price_change;
if (bWithinTrainingPeriod)
{
list_Indicator_FutureValueChange_Training.Add(indicator_pair);
list_Indicator_FutureValueChange_Training_ALL[BarIndex].Add(indicator_pair);
int count_training = list_Indicator_FutureValueChange_Training.Count;
}
else if (bWithinTestingPeriod)
{
list_Indicator_FutureValueChange_Testing.Add(indicator_pair);
list_Indicator_FutureValueChange_Testing_ALL[BarIndex].Add(indicator_pair);
int count_testing = list_Indicator_FutureValueChange_Testing.Count;
}
}
}
}
if (bFinishedProcessingAllData)
{
String unique_id = "_" + rnd.Next(100000, 999999).ToString(); // creates a number between 100k and 999k
String debug_txt = "FINISHEDPROCESSING min_samples=" + min_samples_pct.ToString() + " id=" + unique_id.ToString();
Debug.WriteLine(debug_txt);
String control_file_path = output_folder + "control_file" + unique_id + ".txt";
String consolidated_txt_file_path = output_folder + "consolidated_report" + unique_id + ".txt";
String consolidated_csv_file_path = output_folder + "consolidated_report" + unique_id + ".csv";
switch (indicator_to_use)
{
case IndicatorEnum.indicator_MACD:
if (Sanitize == false)
{
description = "MACD";
}
else
{
description = "M";
}
description = description + "(" + Param1.ToString() + "-" + Param2.ToString() + "-" + Param3.ToString() + ")";
break;
case IndicatorEnum.indicator_RSI:
if (Sanitize == false)
{
description = "RSI";
}
else
{
description = "R";
}
description = description + "(" + Param1.ToString() + "-" + Param2.ToString() + ")";
break;
case IndicatorEnum.indicator_BOLLINGER:
if (Sanitize == false)
{
description = "BOLL";
}
else
{
description = "B";
}
description = description + "(" + Param1.ToString() + "-" + Param2.ToString() + ")";
break;
case IndicatorEnum.indicator_STOCHASTIC:
if (Sanitize == false)
{
description = "STOCH";
}
else
{
description = "S";
}
description = description + "(" + Param1.ToString() + "-" + Param2.ToString() + "-" + Param3.ToString() + ")";
break;
case IndicatorEnum.indicator_STOCHASTIC_RSI:
if (Sanitize == false)
{
description = "STOCH_RSI";
}
else
{
description = "SR";
}
description = description + "(" + Param1.ToString() + ")";
break;
default:
description = "Unknown";
break;
}
description = description + " - " + FutureValueDaysToLookAhead.ToString();
if (Sanitize == false)
{
description = description + " days";
}
description = description + " - " + unique_id.Substring(1); //remove preceding "_"
bool bFirstTime = true;
for (int i = 1; i < symbol_list.Count; i++) //Start at index=1 since we want to ignore the first primary/dummy instrument
{
String symbol_name = symbol_list[i];
String company_name = company_name_list[i];
if (Sanitize == true)
{
String symbol_name_tmp = string.Concat(symbol_list[i].Reverse()).ToLower();
symbol_name = char.ToUpper(symbol_name_tmp[0]) + symbol_name_tmp.Substring(1);
company_name = "?";
}
String base_file_path_for_symbol = output_folder + symbol_name; //i.e. c:\temp\knn\AAPL
String training_file_path = base_file_path_for_symbol + "_training" + unique_id + ".csv";
String testing_file_path = base_file_path_for_symbol + "_testing" + unique_id + ".csv";
WriteListToCSV(list_Indicator_FutureValueChange_Training_ALL[i], training_file_path);
WriteListToCSV(list_Indicator_FutureValueChange_Testing_ALL[i], testing_file_path);
String config_file_name = "";
config_file_name = GenerateConfigFile(base_file_path_for_symbol, symbol_name, company_name, training_file_path, testing_file_path, unique_id);
//mut.WaitOne();
if (bFirstTime) //create new file
{
bFirstTime = false;
File.WriteAllText(control_file_path, config_file_name + "\r\n");
}
else // append to existing file
{
File.AppendAllText(control_file_path, config_file_name + "\r\n");
}
//mut.ReleaseMutex();
}
//Now we can call python for all symbols at once by passing in the control_file as cmd line arg
mut.WaitOne();
string args = control_file_path + " " + consolidated_txt_file_path + " " + consolidated_csv_file_path + " c:\\temp\\knn\\master_report.csv" + " false";
CallPythonScript(output_folder + "\\Data_Processing33.py", args);
mut.ReleaseMutex();
}
}
protected override void OnStateChange()
{
if (State == State.SetDefaults)
{
Description = "test";
Name = "KNN_Generator6";
DaysToLookBack = 1;
FutureValueDaysToLookAhead = 5;
TrainingStartDate = new DateTime(2017, 01, 01);
TrainingEndDate = new DateTime(2017, 09, 30);
TestingStartDate = new DateTime(2017, 10, 1);
TestingEndDate = new DateTime(2017, 12, 31);
//Custom params
indicator_to_use = IndicatorEnum.indicator_MACD;
KNN_num_neighbors = 3;
num_training_pts = 200;
samples_per_group = 10;
window_size = 1;
avg_target = 1.0f;
good_target = 0.5f;
bad_target = 0.25f;
min_samples = 10;
thresh1 = 1.0f;
thresh2 = -1.0f;
output_folder = "C:\\temp\\knn\\";
Param1 = 12; //Defaults for MACD
Param2 = 26;
Param3 = 9;
Sanitize = false;
// This strategy has been designed to take advantage of performance gains in Strategy Analyzer optimizations
// See the Help Guide for additional information
IsInstantiatedOnEachOptimizationIteration = false;
}
else if (State == State.Configure)
{
for (int i = 0; i < symbol_list.Length; i++)
{
//Don't add the dummy instrument (but we still need a placeholder list which is added below)
if (i != 0)
{
AddDataSeries(symbol_list[i], Data.BarsPeriodType.Day, 1);
}
list_Indicator_FutureValueChange_Training_ALL.Add(new List <Indicator_FutureValueChange_Pair>());
list_Indicator_FutureValueChange_Testing_ALL.Add(new List <Indicator_FutureValueChange_Pair>());
}
SetStopLoss(CalculationMode.Percent, 0.05);
// Sets a 20 tick trailing stop for an open position
//SetTrailStop(CalculationMode.Ticks, 20);
}
else if (State == State.DataLoaded)
{
double input_param = 2.0;
greg1 = GregIndicator1(input_param);
AddChartIndicator(greg1);
}
else if (State == State.Transition) //finished processing historical data (and ready for real-time)
{
//System.Windows.Forms.MessageBox.Show("test");
Random rnd = new Random();
String unique_id = "_" + rnd.Next(100000, 999999).ToString(); // creates a number between 100k and 999k
String control_file_path = output_folder + "control_file" + unique_id + ".txt";
String consolidated_txt_file_path = output_folder + "consolidated_report" + unique_id + ".txt";
String consolidated_csv_file_path = output_folder + "consolidated_report" + unique_id + ".csv";
switch (indicator_to_use)
{
case IndicatorEnum.indicator_MACD:
if (Sanitize == false)
{
description = "MACD";
}
else
{
description = "M";
}
description = description + "(" + Param1.ToString() + "-" + Param2.ToString() + "-" + Param3.ToString() + ")";
break;
case IndicatorEnum.indicator_RSI:
if (Sanitize == false)
{
description = "RSI";
}
else
{
description = "R";
}
description = description + "(" + Param1.ToString() + "-" + Param2.ToString() + ")";
break;
default:
description = "Unknown";
break;
}
description = description + " - " + FutureValueDaysToLookAhead.ToString();
if (Sanitize == false)
{
description = description + " days";
}
description = description + " - " + unique_id.Substring(1); //remove preceding "_"
bool bFirstTime = true;
for (int i = 1; i < symbol_list.Length; i++) //Start at index=1 since we want to ignore the first primary/dummy instrument
{
String symbol_name = symbol_list[i];
if (Sanitize == true)
{
symbol_name = symbol_list[i][0].ToString();
}
String base_file_path_for_symbol = output_folder + symbol_name; //i.e. c:\temp\knn\AAPL
String training_file_path = base_file_path_for_symbol + "_training" + unique_id + ".csv";
String testing_file_path = base_file_path_for_symbol + "_testing" + unique_id + ".csv";
WriteListToCSV(list_Indicator_FutureValueChange_Training_ALL[i], training_file_path); //trying out +1!!!
WriteListToCSV(list_Indicator_FutureValueChange_Testing_ALL[i], testing_file_path);
String config_file_name = "";
config_file_name = GenerateConfigFile(base_file_path_for_symbol, symbol_name, training_file_path, testing_file_path, unique_id);
if (bFirstTime) //create new file
{
bFirstTime = false;
File.WriteAllText(control_file_path, config_file_name + "\r\n");
}
else // append to existing file
{
File.AppendAllText(control_file_path, config_file_name + "\r\n");
}
}
//Now we can call python for all symbols at once by passing in the control_file as cmd line arg
CallPythonScript(output_folder + "\\Data_Processing24.py", control_file_path + " " + consolidated_txt_file_path + " " + consolidated_csv_file_path + " true");
}
}
protected override void OnStateChange()
{
if (State == State.SetDefaults)
{
if (bFirst)
{
bFirst = false;
}
String sp500_csv_file_path = "c:\\temp\\knn\\sp500.csv";
String sp500_config_file_path = "c:\\temp\\knn\\sp500_config_file.txt";
System.IO.StreamReader file1 = new System.IO.StreamReader(sp500_config_file_path);
String line1 = file1.ReadLine();
if (line1 != null)
{
sp500_csv_file_path = line1;
}
file1.Close();
symbol_list = new List <String> {
"DUMMY"
};
company_name_list = new List <String> {
"DUMMY"
};
String line2;
// Read the file and display it line by line.
System.IO.StreamReader file2 = new System.IO.StreamReader(sp500_csv_file_path);
while ((line2 = file2.ReadLine()) != null)
{
string[] values = line2.Split(',');
if (values.Length == 2)
{
symbol_list.Add(values[0]);
company_name_list.Add(values[1]);
}
}
file2.Close();
Description = "test";
Name = "KNN_Generator10";
DaysToLookBack = 1;
FutureValueDaysToLookAhead = 5;
TrainingStartDate = new DateTime(2017, 01, 01);
TrainingEndDate = new DateTime(2017, 12, 31);
TestingStartDate = new DateTime(2018, 1, 1);
TestingEndDate = DateTime.Today;
//Custom params
indicator_to_use = IndicatorEnum.indicator_MACD;
KNN_num_neighbors = 3;
num_training_pts = 200;
num_groups = 20;
stagger_factor = 0;
window_size = 1;
avg_target = 1.0f;
good_target = 0.5f;
bad_target = 0.20f;
min_samples_pct = 0.06f;
thresh1 = 1.0f;
thresh2 = -1.0f;
output_folder = "C:\\temp\\knn\\";
Param1 = 12; //Defaults for MACD
Param2 = 26;
Param3 = 9;
Sanitize = false;
bDataLoaded = false;
// This strategy has been designed to take advantage of performance gains in Strategy Analyzer optimizations
// See the Help Guide for additional information
IsInstantiatedOnEachOptimizationIteration = true;
//IsInstantiatedOnEachOptimizationIteration = false;
}
else if (State == State.Configure)
{
//System.Windows.Forms.MessageBox.Show("Configure");
bDataLoaded = false;
for (int i = 0; i < symbol_list.Count; i++)
{
//Don't add the dummy instrument (but we still need a placeholder list which is added below)
if (i != 0)
{
AddDataSeries(symbol_list[i], Data.BarsPeriodType.Day, 1);
}
list_Indicator_FutureValueChange_Training_ALL.Add(new List <Indicator_FutureValueChange_Pair>());
list_Indicator_FutureValueChange_Testing_ALL.Add(new List <Indicator_FutureValueChange_Pair>());
}
SetStopLoss(CalculationMode.Percent, 0.05);
// Sets a 20 tick trailing stop for an open position
//SetTrailStop(CalculationMode.Ticks, 20);
}
else if (State == State.DataLoaded)
{
//String debug_txt = "DATALOADED min_samples=" + min_samples.ToString();
//Debug.WriteLine(debug_txt);
//double input_param = 2.0;
//greg1 = GregIndicator1(input_param);
//AddChartIndicator(greg1);
bDataLoaded = true;
}
else if ((bDataLoaded == true) && ((State == State.Transition) || (State == State.Terminated))) //finished processing historical data (and ready for real-time)
{
if (false) //list_Indicator_FutureValueChange_Training_ALL.Count > 0)
{
//String debug_txt = "TERMINATED min_samples=" + min_samples.ToString();
//Debug.WriteLine(debug_txt);
//if (bExecutedPython == false)
//{
// bExecutedPython = true;
//System.Threading.Thread.Sleep(2000);
//System.Windows.Forms.MessageBox.Show("test");
Random rnd = new Random();
String unique_id = "_" + rnd.Next(100000, 999999).ToString(); // creates a number between 100k and 999k
String control_file_path = output_folder + "control_file" + unique_id + ".txt";
String consolidated_txt_file_path = output_folder + "consolidated_report" + unique_id + ".txt";
String consolidated_csv_file_path = output_folder + "consolidated_report" + unique_id + ".csv";
switch (indicator_to_use)
{
case IndicatorEnum.indicator_MACD:
if (Sanitize == false)
{
description = "MACD";
}
else
{
description = "M";
}
description = description + "(" + Param1.ToString() + "-" + Param2.ToString() + "-" + Param3.ToString() + ")";
break;
case IndicatorEnum.indicator_RSI:
if (Sanitize == false)
{
description = "RSI";
}
else
{
description = "R";
}
description = description + "(" + Param1.ToString() + "-" + Param2.ToString() + ")";
break;
case IndicatorEnum.indicator_BOLLINGER:
if (Sanitize == false)
{
description = "BOLL";
}
else
{
description = "B";
}
break;
case IndicatorEnum.indicator_STOCHASTIC:
if (Sanitize == false)
{
description = "STOCH";
}
else
{
description = "S";
}
description = description + "(" + Param1.ToString() + "-" + Param2.ToString() + ")";
break;
default:
description = "Unknown";
break;
}
description = description + " - " + FutureValueDaysToLookAhead.ToString();
if (Sanitize == false)
{
description = description + " days";
}
description = description + " - " + unique_id.Substring(1); //remove preceding "_"
bool bFirstTime = true;
for (int i = 1; i < symbol_list.Count; i++) //Start at index=1 since we want to ignore the first primary/dummy instrument
{
String symbol_name = symbol_list[i];
if (Sanitize == true)
{
symbol_name = symbol_list[i][0].ToString();
}
String base_file_path_for_symbol = output_folder + symbol_name; //i.e. c:\temp\knn\AAPL
String training_file_path = base_file_path_for_symbol + "_training" + unique_id + ".csv";
String testing_file_path = base_file_path_for_symbol + "_testing" + unique_id + ".csv";
WriteListToCSV(list_Indicator_FutureValueChange_Training_ALL[i], training_file_path);
WriteListToCSV(list_Indicator_FutureValueChange_Testing_ALL[i], testing_file_path);
String config_file_name = "";
config_file_name = GenerateConfigFile(base_file_path_for_symbol, symbol_name, company_name_list[i], training_file_path, testing_file_path, unique_id);
if (bFirstTime) //create new file
{
bFirstTime = false;
File.WriteAllText(control_file_path, config_file_name + "\r\n");
}
else // append to existing file
{
File.AppendAllText(control_file_path, config_file_name + "\r\n");
}
}
//Now we can call python for all symbols at once by passing in the control_file as cmd line arg
//CallPythonScript(output_folder + "\\Data_Processing25.py", control_file_path + " " + consolidated_txt_file_path + " " + consolidated_csv_file_path + " true");
//bDataLoaded = false;
}
// }
}
}
protected String GenerateConfigFile(String filePath, String symbol, String company, String training_file_path, String testing_file_path, String unique_id)
{
String output_file_base = filePath + "_results_";
String config_file_name = filePath + "_config" + unique_id + ".txt";
List <String> labels = new List <String>
{
"KNN_num_neighbors",
"num_training_pts",
"num_groups",
"stagger_factor",
"window_size",
"avg_target",
"good_target",
"bad_target",
"min_samples_pct",
"thresh1",
"thresh2",
"future_lookahead",
"s_name",
"co_name",
"description",
"training_file",
"training_start",
"training_end",
"testing_file",
"testing_start",
"testing_end",
"output_csv_file",
"output_txt_file",
"output_pdf_file"
};
List <String> values = new List <String>
{
KNN_num_neighbors.ToString(),
num_training_pts.ToString(),
num_groups.ToString(),
stagger_factor.ToString(),
window_size.ToString(),
avg_target.ToString(),
good_target.ToString(),
bad_target.ToString(),
min_samples_pct.ToString(),
thresh1.ToString(),
thresh2.ToString(),
FutureValueDaysToLookAhead.ToString(),
symbol,
company,
description,
training_file_path,
TrainingStartDate.ToShortDateString(),
TrainingEndDate.ToShortDateString(),
testing_file_path,
TestingStartDate.ToShortDateString(),
TestingEndDate.ToShortDateString(),
output_file_base + "data" + unique_id + ".csv",
output_file_base + "summary" + unique_id + ".txt",
output_file_base + "plot" + unique_id + ".pdf",
};
List <String> types = new List <String>
{
"int",
"int",
"int",
"int",
"int",
"float",
"float",
"float",
"float",
"float",
"float",
"int",
"str",
"str",
"str",
"str",
"str",
"str",
"str",
"str",
"str",
"str",
"str",
"str"
};
var cfg = new StringBuilder();
for (int i = 0; i < labels.Count; i++)
{
cfg.AppendLine(labels[i] + "=" + values[i] + "#" + types[i]);
}
//mut.WaitOne(); //wait until safe to enter; prior thread has completed writing.
try
{
File.WriteAllText(config_file_name, cfg.ToString());
//mut.ReleaseMutex();
}
catch (System.Exception exp)
{
Log("File write error for file name '" + filePath + "' Error '" + exp.Message + "'", LogLevel.Warning);
}
return(config_file_name);
}
public void BuildIndicatorAndDescriptionStrings(IndicatorEnum this_ind) //, int Param1, int Param2, int Param3)
{
switch (this_ind)
{
case IndicatorEnum.indicator_MACD:
if (Sanitize == false)
{
description = "MACD";
}
else
{
description = "M";
}
indicator = description;
description = description + "(" + Param1.ToString() + "-" + Param2.ToString() + "-" + Param3.ToString() + ")";
break;
case IndicatorEnum.indicator_RSI:
if (Sanitize == false)
{
description = "RSI";
}
else
{
description = "R";
}
indicator = description;
description = description + "(" + Param1.ToString() + "-" + Param2.ToString() + ")";
break;
case IndicatorEnum.indicator_BOLLINGER:
if (Sanitize == false)
{
description = "BOLL";
}
else
{
description = "B";
}
indicator = description;
description = description + "(" + Param1.ToString() + "-" + Param2.ToString() + ")";
break;
case IndicatorEnum.indicator_STOCHASTIC:
if (Sanitize == false)
{
description = "STOCH";
}
else
{
description = "S";
}
indicator = description;
description = description + "(" + Param1.ToString() + "-" + Param2.ToString() + "-" + Param3.ToString() + ")";
break;
case IndicatorEnum.indicator_STOCHASTIC_RSI:
if (Sanitize == false)
{
description = "STOCH_RSI";
}
else
{
description = "SR";
}
indicator = description;
description = description + "(" + Param1.ToString() + ")";
break;
default:
description = "Unknown";
indicator = description;
break;
}
description = description + " - " + FutureValueDaysToLookAhead.ToString();
if (Sanitize == false)
{
description = description + " days";
}
description = description + " - " + uid;
}
protected String GenerateConfigFile(String filePath, String symbol, String company, String training_file_path, String testing_file_path, String unique_id)
{
String output_file_base = filePath + "_results_";
String config_file_name = filePath + "_config" + unique_id + ".txt";
List <List <String> > param_list = new List <List <String> >();
param_list.Add(new List <String>()
{
"uid", uid, "str"
});
param_list.Add(new List <String>()
{
"KNN_num_neighbors", KNN_num_neighbors.ToString(), "int"
});
param_list.Add(new List <String>()
{
"num_training_pts", num_training_pts.ToString(), "int"
});
param_list.Add(new List <String>()
{
"num_groups", num_groups.ToString(), "int"
});
param_list.Add(new List <String>()
{
"stagger_factor", stagger_factor.ToString(), "int"
});
param_list.Add(new List <String>()
{
"window_size", window_size.ToString(), "int"
});
param_list.Add(new List <String>()
{
"avg_target", avg_target.ToString(), "float"
});
param_list.Add(new List <String>()
{
"good_target", good_target.ToString(), "float"
});
param_list.Add(new List <String>()
{
"bad_target", bad_target.ToString(), "float"
});
param_list.Add(new List <String>()
{
"min_samples_pct", min_samples_pct.ToString(), "float"
});
param_list.Add(new List <String>()
{
"thresh1", thresh1.ToString(), "float"
});
param_list.Add(new List <String>()
{
"thresh2", thresh2.ToString(), "float"
});
param_list.Add(new List <String>()
{
"future_lookahead", FutureValueDaysToLookAhead.ToString(), "int"
});
param_list.Add(new List <String>()
{
"s_name", symbol, "str"
});
param_list.Add(new List <String>()
{
"co_name", company, "str"
});
param_list.Add(new List <String>()
{
"description", description, "str"
});
param_list.Add(new List <String>()
{
"indicator", indicator, "str"
});
param_list.Add(new List <String>()
{
"param1", Param1.ToString(), "int"
});
param_list.Add(new List <String>()
{
"param2", Param2.ToString(), "int"
});
param_list.Add(new List <String>()
{
"param3", Param3.ToString(), "int"
});
param_list.Add(new List <String>()
{
"training_file", training_file_path, "str"
});
param_list.Add(new List <String>()
{
"training_start", TrainingStartDate.ToShortDateString(), "str"
});
param_list.Add(new List <String>()
{
"training_end", TrainingEndDate.ToShortDateString(), "str"
});
param_list.Add(new List <String>()
{
"testing_file", testing_file_path, "str"
});
param_list.Add(new List <String>()
{
"testing_start", TestingStartDate.ToShortDateString(), "str"
});
param_list.Add(new List <String>()
{
"testing_end", TestingEndDate.ToShortDateString(), "str"
});
param_list.Add(new List <String>()
{
"output_csv_file", output_file_base + "data" + unique_id + ".csv", "str"
});
param_list.Add(new List <String>()
{
"output_txt_file", output_file_base + "summary" + unique_id + ".txt", "str"
});
param_list.Add(new List <String>()
{
"output_pdf_file", output_file_base + "plot" + unique_id + ".pdf", "str"
});
var cfg = new StringBuilder();
for (int i = 0; i < param_list.Count; i++)
{
cfg.AppendLine(param_list[i][0] + "=" + param_list[i][1] + "#" + param_list[i][2]);
}
//mut.WaitOne(); //wait until safe to enter; prior thread has completed writing.
try
{
File.WriteAllText(config_file_name, cfg.ToString());
//mut.ReleaseMutex();
}
catch (System.Exception exp)
{
Log("File write error for file name '" + filePath + "' Error '" + exp.Message + "'", LogLevel.Warning);
}
return(config_file_name);
}
protected override void OnStateChange()
{
if (State == State.SetDefaults)
{
Description = "test";
Name = "KNN_Generator3";
DaysToLookBack = 1;
FutureValueDaysToLookAhead = 5;
TrainingStartDate = new DateTime(2017, 01, 01);
TrainingEndDate = new DateTime(2017, 09, 30);
TestingStartDate = new DateTime(2017, 10, 1);
TestingEndDate = new DateTime(2017, 12, 31);
//Custom params
indicator_to_use = IndicatorEnum.indicator_MACD;
KNN_num_neighbors = 3;
num_training_pts = 200;
samples_per_group = 10;
window_size = 1;
avg_target = 1.0f;
good_target = 0.5f;
bad_target = 0.25f;
min_samples = 10;
thresh1 = 1.0f;
thresh2 = -1.0f;
output_folder = "C:\\temp\\knn\\";
// This strategy has been designed to take advantage of performance gains in Strategy Analyzer optimizations
// See the Help Guide for additional information
IsInstantiatedOnEachOptimizationIteration = false;
}
else if (State == State.Configure)
{
for (int i = 1; i < symbol_list.Length; i++) //start at 1 since SLB already added by default
{
// Add an MSFT 1 day Bars object to the strategy
AddDataSeries(symbol_list[i], Data.BarsPeriodType.Day, 1);
//private List<Indicator_FutureValueChange_Pair> list_Indicator_FutureValueChange_Training = new List<Indicator_FutureValueChange_Pair>();
list_Indicator_FutureValueChange_Training_ALL.Add(new List <Indicator_FutureValueChange_Pair>());
list_Indicator_FutureValueChange_Testing_ALL.Add(new List <Indicator_FutureValueChange_Pair>());
}
//Add extra one????
list_Indicator_FutureValueChange_Training_ALL.Add(new List <Indicator_FutureValueChange_Pair>());
list_Indicator_FutureValueChange_Testing_ALL.Add(new List <Indicator_FutureValueChange_Pair>());
SetStopLoss(CalculationMode.Percent, 0.05);
// Sets a 20 tick trailing stop for an open position
//SetTrailStop(CalculationMode.Ticks, 20);
}
else if (State == State.DataLoaded)
{
double input_param = 2.0;
greg1 = GregIndicator1(input_param);
AddChartIndicator(greg1);
}
else if (State == State.Transition) //finished processing historical data (and ready for real-time)
{
//System.Windows.Forms.MessageBox.Show("test");
String control_file_path = output_folder + "control_file.txt";
switch (indicator_to_use)
{
case IndicatorEnum.indicator_MACD:
if (bSanitize == false)
{
description = "MACD";
}
else
{
description = "M";
}
break;
case IndicatorEnum.indicator_RSI:
if (bSanitize == false)
{
description = "RSI";
}
else
{
description = "R";
}
break;
default:
description = "Unknown";
break;
}
description = description + " - " + FutureValueDaysToLookAhead.ToString();
if (bSanitize == false)
{
description = description + " days";
}
bool bFirstTime = true;
for (int i = 1; i < symbol_list.Length; i++)
{
String base_file_path_for_symbol = output_folder + symbol_list[i]; //i.e. c:\temp\knn\AAPL
String training_file_path = base_file_path_for_symbol + "_training.csv";
String testing_file_path = base_file_path_for_symbol + "_testing.csv";
WriteListToCSV(list_Indicator_FutureValueChange_Training_ALL[i], training_file_path); //trying out +1!!!
WriteListToCSV(list_Indicator_FutureValueChange_Testing_ALL[i], testing_file_path);
//WriteListToCSV(list_Indicator_FutureValueChange_Training_ALL[i], training_file_path);
//WriteListToCSV(list_Indicator_FutureValueChange_Testing_ALL[i], testing_file_path);
String config_file_name = "";
config_file_name = GenerateConfigFile(base_file_path_for_symbol, symbol_list[i], training_file_path, testing_file_path);
if (bFirstTime) //create new file
{
bFirstTime = false;
File.WriteAllText(control_file_path, config_file_name + "\r\n");
}
else // append to existing file
{
File.AppendAllText(control_file_path, config_file_name + "\r\n");
}
}
//Now we can call python for all symbols at once by passing in the control_file as cmd line arg
CallPythonScript(output_folder + "\\Data_Processing18.py", control_file_path);
}
}
protected override void OnBarUpdate()
{
if (OnlyGeneratePlots)
{
return;
}
int BarIndex = BarsInProgress;
bool bFinishedProcessingAllData = false;
String debug_txt1 = "Date=" + Times[BarIndex][0].Date.ToShortDateString() + "BarIndex=" + BarIndex.ToString() + "CurrentBar=" + CurrentBar.ToString() + "Count=" + Count.ToString();
Debug.WriteLine(debug_txt1);
DateTime current_bar_date = Times[BarIndex][0].Date;
Boolean bLastSymbol = BarIndex == (symbol_list.Count - 1);
if (current_bar_date > TestingEndDate)
{
return;
}
else if (bLastSymbol &&
(((CurrentBar + 1) == Count) || (current_bar_date == TestingEndDate))) //we are on the last bar to process
{
Debug.WriteLine("bFinished trigger");
bFinishedProcessingAllData = true;
}
if (((ProcessAllTickers == true) && (BarIndex >= 1) && (BarIndex < (symbol_list.Count))) || //Start at index=1 since we want to ignore the primary/dummy instrument
((ProcessAllTickers == false) && (BarIndex == 0)))
{
if (CurrentBar >= (FutureValueDaysToLookAhead)) //just make sure we avoid out of bounds error in case we don't yet have enough data
{
DateTime date_to_process = Times[BarIndex][FutureValueDaysToLookAhead].Date; //need to wait FutureValueDaysToLookAhead days before we can make calcs
bool bWithinTrainingPeriod = (date_to_process >= TrainingStartDate) && (date_to_process <= TrainingEndDate);
bool bWithinTestingPeriod = (date_to_process >= TestingStartDate) && (date_to_process <= TestingEndDate);
if ((bWithinTrainingPeriod) || (bWithinTestingPeriod))
{
for (int i = 0; i < indicator_list.Count; i++)
{
Indicator_FutureValueChange_Pair indicator_pair = GetIndicatorValue(indicator_list[i], BarIndex, FutureValueDaysToLookAhead, date_to_process);
if (bWithinTrainingPeriod)
{
//list_Indicator_FutureValueChange_Training.Add(indicator_pair);
//list_Indicator_FutureValueChange_Training_ALL[BarIndex].Add(indicator_pair);
master_list_training[i][BarIndex].Add(indicator_pair);
}
else if (bWithinTestingPeriod)
{
//list_Indicator_FutureValueChange_Testing.Add(indicator_pair);
//list_Indicator_FutureValueChange_Testing_ALL[BarIndex].Add(indicator_pair);
master_list_testing[i][BarIndex].Add(indicator_pair);
}
}
}
}
}
if (bFinishedProcessingAllData)
{
String debug_txt2 = "finished processing all data";
Debug.WriteLine(debug_txt2);
for (int bar_index = 1; bar_index < symbol_list.Count; bar_index++)
{
for (int i = 0; i < indicator_list.Count; i++)
{
int num_bars_for_symbol = Times[bar_index].Count;
if (CurrentBar < num_bars_for_symbol) //Check for missing data
{
for (int j = (FutureValueDaysToLookAhead - 1); j >= 0; j--)
{
DateTime date_to_process = Times[bar_index][j].Date;
debug_txt2 = "date_to_process=" + date_to_process.ToShortDateString();
Debug.WriteLine(debug_txt2);
Indicator_FutureValueChange_Pair indicator_pair = GetIndicatorValue(indicator_to_use, bar_index, j, date_to_process);
//Add to the "Testing" lists since these should be the ones capturing most recent values
//list_Indicator_FutureValueChange_Testing.Add(indicator_pair);
//list_Indicator_FutureValueChange_Testing_ALL[bar_index].Add(indicator_pair);
master_list_testing[i][bar_index].Add(indicator_pair);
}
}
}
}
uid = rnd.Next(100000, 999999).ToString();
String unique_id = "_" + uid; // creates a number between 100k and 999k
String control_file_path = output_folder + "control_file" + unique_id + ".txt";
String consolidated_txt_file_path = output_folder + "consolidated_report" + unique_id + ".txt";
String consolidated_csv_file_path = output_folder + "consolidated_report" + unique_id + ".csv";
bool bFirstTime = true;
int start_index = 1;
int max_index = symbol_list.Count;
if (ProcessAllTickers == false)
{
start_index = 0;
max_index = 1;
}
for (int j = 0; j < indicator_list.Count; j++)
{
uid = rnd.Next(100000, 999999).ToString();
unique_id = "_" + uid; // creates a number between 100k and 999k
String debug_txt = "FINISHEDPROCESSING min_samples=" + min_samples_pct.ToString() + " id=" + unique_id.ToString();
Debug.WriteLine(debug_txt);
switch (indicator_list[j])
{
case IndicatorEnum.indicator_MACD:
if (Sanitize == false)
{
description = "MACD";
}
else
{
description = "M";
}
indicator = description;
description = description + "(" + Param1.ToString() + "-" + Param2.ToString() + "-" + Param3.ToString() + ")";
break;
case IndicatorEnum.indicator_RSI:
if (Sanitize == false)
{
description = "RSI";
}
else
{
description = "R";
}
indicator = description;
description = description + "(" + Param1.ToString() + "-" + Param2.ToString() + ")";
break;
case IndicatorEnum.indicator_BOLLINGER:
if (Sanitize == false)
{
description = "BOLL";
}
else
{
description = "B";
}
indicator = description;
description = description + "(" + Param1.ToString() + "-" + Param2.ToString() + ")";
break;
case IndicatorEnum.indicator_STOCHASTIC:
if (Sanitize == false)
{
description = "STOCH";
}
else
{
description = "S";
}
indicator = description;
description = description + "(" + Param1.ToString() + "-" + Param2.ToString() + "-" + Param3.ToString() + ")";
break;
case IndicatorEnum.indicator_STOCHASTIC_RSI:
if (Sanitize == false)
{
description = "STOCH_RSI";
}
else
{
description = "SR";
}
indicator = description;
description = description + "(" + Param1.ToString() + ")";
break;
default:
description = "Unknown";
indicator = description;
break;
}
description = description + " - " + FutureValueDaysToLookAhead.ToString();
if (Sanitize == false)
{
description = description + " days";
}
description = description + " - " + unique_id.Substring(1); //remove preceding "_"
for (int i = start_index; i < max_index; i++) //Start at index=1 since we want to ignore the first primary/dummy instrument
{
String symbol_name = symbol_list[i];
if (ProcessAllTickers == false)
{
symbol_name = master_symbol_name;
}
String company_name = company_name_list[i];
if (Sanitize == true)
{
String symbol_name_tmp = string.Concat(symbol_name.Reverse()).ToLower();
symbol_name = char.ToUpper(symbol_name_tmp[0]) + symbol_name_tmp.Substring(1);
company_name = "?";
}
String base_file_path_for_symbol = output_folder + symbol_name; //i.e. c:\temp\knn\AAPL
String training_file_path = base_file_path_for_symbol + "_training" + unique_id + ".csv";
String testing_file_path = base_file_path_for_symbol + "_testing" + unique_id + ".csv";
//WriteListToCSV(list_Indicator_FutureValueChange_Training_ALL[i], training_file_path);
//WriteListToCSV(list_Indicator_FutureValueChange_Testing_ALL[i], testing_file_path);
WriteListToCSV(master_list_training[j][i], training_file_path);
WriteListToCSV(master_list_testing[j][i], testing_file_path);
String config_file_name = "";
config_file_name = GenerateConfigFile(base_file_path_for_symbol, symbol_name, company_name, training_file_path, testing_file_path, unique_id);
//mut.WaitOne();
if (bFirstTime) //create new file
{
bFirstTime = false;
File.WriteAllText(control_file_path, config_file_name + "\r\n");
}
else // append to existing file
{
File.AppendAllText(control_file_path, config_file_name + "\r\n");
}
//mut.ReleaseMutex();
}
}
Debug.WriteLine("Before Python mutex");
//Now we can call python for all symbols at once by passing in the control_file as cmd line arg
mut_python.WaitOne();
string mode = " BEST";
if (FindBestSolutions == false)
{
mode = " RECENT";
}
string args = control_file_path + " " + consolidated_txt_file_path + " " + consolidated_csv_file_path + " c:\\temp\\knn\\master_report.csv" + " c:\\temp\\knn\\master_trig.csv" + " false" + " false" + mode + " c:\\temp\\knn\\master_sorted.csv" + " " + GeneratePlotsForBestSolutions.ToString() + " " + NumPlotsToGenerate.ToString();
Debug.WriteLine("Python args" + args);
CallPythonScript(output_folder + "\\Data_Processing45.py", args);
mut_python.ReleaseMutex();
Debug.WriteLine("After Python mutex");
}
}
protected override void OnBarUpdate()
{
int BarIndex = BarsInProgress;
bool bFinishedProcessingAllData = false;
if (((CurrentBar + 2) == Count) && BarIndex == (symbol_list.Count - 1)) //we are on the last bar to process
{
bFinishedProcessingAllData = true;
}
if (((ProcessAllTickers == true) && (BarIndex >= 1) && (BarIndex < (symbol_list.Count))) || //Start at index=1 since we want to ignore the primary/dummy instrument
((ProcessAllTickers == false) && (BarIndex == 0)))
{
if (CurrentBar >= (FutureValueDaysToLookAhead)) //just make sure we avoid out of bounds error in case we don't yet have enough data
{
DateTime current_bar_date = Times[BarIndex][0].Date;
DateTime date_to_process = Times[BarIndex][FutureValueDaysToLookAhead].Date; //need to wait FutureValueDaysToLookAhead days before we can make calcs
bool bWithinTrainingPeriod = (date_to_process >= TrainingStartDate) && (date_to_process <= TrainingEndDate);
bool bWithinTestingPeriod = (date_to_process >= TestingStartDate) && (date_to_process <= TestingEndDate);
if ((bWithinTrainingPeriod) || (bWithinTestingPeriod))
{
//TimeSpan diff = TrainingEndDate - TrainingStartDate;
//int training_days = (int)Math.Abs(Math.Round(diff.TotalDays));
double indicator_value = 0.0;
switch (indicator_to_use)
{
case IndicatorEnum.indicator_MACD:
indicator_value = MACD(BarsArray[BarIndex], Param1, Param2, Param3)[FutureValueDaysToLookAhead]; //get the indicator val from n days ago
break;
case IndicatorEnum.indicator_RSI:
indicator_value = RSI(BarsArray[BarIndex], Param1, Param2)[FutureValueDaysToLookAhead]; //get the indicator val from n days ago
break;
case IndicatorEnum.indicator_BOLLINGER:
double upper_band = Bollinger(BarsArray[BarIndex], (double)Param1, Param2).Upper[FutureValueDaysToLookAhead]; //get the indicator val from n days ago
double middle_band = Bollinger(BarsArray[BarIndex], (double)Param1, Param2).Middle[FutureValueDaysToLookAhead]; //get the indicator val from n days ago
double lower_band = Bollinger(BarsArray[BarIndex], (double)Param1, Param2).Lower[FutureValueDaysToLookAhead]; //get the indicator val from n days ago
double current_price = Closes[BarIndex][FutureValueDaysToLookAhead];
double diff = current_price - middle_band;
double band_range = upper_band - middle_band;
indicator_value = diff / band_range; //how far current price is from the middle band (-1.0 means we're at the lower band, +1 means we're at the upper band)
break;
case IndicatorEnum.indicator_STOCHASTIC:
//use the "D" value
indicator_value = Stochastics(BarsArray[BarIndex], Param1, Param2, Param3).D[FutureValueDaysToLookAhead]; //get the indicator val from n days ago
break;
case IndicatorEnum.indicator_STOCHASTIC_RSI:
indicator_value = StochRSI(BarsArray[BarIndex], Param1)[FutureValueDaysToLookAhead]; //get the indicator val from n days ago
break;
case IndicatorEnum.indicator_GREG:
indicator_value = -999.999; // GregIndicator1(BarsArray[BarIndex], (float)Param1)[FutureValueDaysToLookAhead]; //get the indicator val from n days ago
break;
default:
indicator_value = -999.99;
break;
}
if (double.IsNaN(indicator_value))
{
indicator_value = 0.0;
}
double future_price_change = 0.0;
double future_price = Closes[BarIndex][0];
double start_price = Closes[BarIndex][FutureValueDaysToLookAhead];
future_price_change = ((future_price / start_price) - 1.0) * 100.0;
Indicator_FutureValueChange_Pair indicator_pair = new Indicator_FutureValueChange_Pair();
indicator_pair.Date = date_to_process;
indicator_pair.Price = start_price;
indicator_pair.Indicator = indicator_value;
indicator_pair.FutureValueChange = future_price_change;
if (bWithinTrainingPeriod)
{
list_Indicator_FutureValueChange_Training.Add(indicator_pair);
list_Indicator_FutureValueChange_Training_ALL[BarIndex].Add(indicator_pair);
int count_training = list_Indicator_FutureValueChange_Training.Count;
}
else if (bWithinTestingPeriod)
{
list_Indicator_FutureValueChange_Testing.Add(indicator_pair);
list_Indicator_FutureValueChange_Testing_ALL[BarIndex].Add(indicator_pair);
int count_testing = list_Indicator_FutureValueChange_Testing.Count;
}
}
}
}
else
{
}
if (bFinishedProcessingAllData)
{
for (int bar_index = 1; bar_index < symbol_list.Count; bar_index++)
{
for (int j = FutureValueDaysToLookAhead; j >= 0; j--)
{
DateTime date_to_process = Times[bar_index][j].Date;
double indicator_value = 0.0;
switch (indicator_to_use)
{
case IndicatorEnum.indicator_MACD:
indicator_value = MACD(BarsArray[bar_index], Param1, Param2, Param3)[j]; //get the indicator val from n days ago
break;
case IndicatorEnum.indicator_RSI:
indicator_value = RSI(BarsArray[bar_index], Param1, Param2)[0]; //get the indicator val from n days ago
break;
case IndicatorEnum.indicator_BOLLINGER:
double upper_band = Bollinger(BarsArray[bar_index], (double)Param1, Param2).Upper[j]; //get the indicator val from n days ago
double middle_band = Bollinger(BarsArray[bar_index], (double)Param1, Param2).Middle[j]; //get the indicator val from n days ago
double lower_band = Bollinger(BarsArray[bar_index], (double)Param1, Param2).Lower[j]; //get the indicator val from n days ago
double current_price = Closes[bar_index][j];
double diff = current_price - middle_band;
double band_range = upper_band - middle_band;
indicator_value = diff / band_range; //how far current price is from the middle band (-1.0 means we're at the lower band, +1 means we're at the upper band)
break;
case IndicatorEnum.indicator_STOCHASTIC:
//use the "D" value
indicator_value = Stochastics(BarsArray[bar_index], Param1, Param2, Param3).D[j]; //get the indicator val from n days ago
break;
case IndicatorEnum.indicator_STOCHASTIC_RSI:
indicator_value = StochRSI(BarsArray[bar_index], Param1)[j]; //get the indicator val from n days ago
break;
case IndicatorEnum.indicator_GREG:
indicator_value = -999.999; // GregIndicator1(BarsArray[BarIndex], (float)Param1)[FutureValueDaysToLookAhead]; //get the indicator val from n days ago
break;
default:
indicator_value = -999.99;
break;
}
if (double.IsNaN(indicator_value))
{
indicator_value = 0.0;
}
double future_price_change = 0.0;
double future_price = Closes[bar_index][j];
double start_price = Closes[bar_index][j];
future_price_change = ((future_price / start_price) - 1.0) * 100.0;
Indicator_FutureValueChange_Pair indicator_pair = new Indicator_FutureValueChange_Pair();
indicator_pair.Date = date_to_process;
indicator_pair.Price = start_price;
indicator_pair.Indicator = indicator_value;
indicator_pair.FutureValueChange = future_price_change;
//if (bWithinTrainingPeriod)
//{
// list_Indicator_FutureValueChange_Training.Add(indicator_pair);
// list_Indicator_FutureValueChange_Training_ALL[BarIndex].Add(indicator_pair);
// int count_training = list_Indicator_FutureValueChange_Training.Count;
//}
//else if (bWithinTestingPeriod)
//{
list_Indicator_FutureValueChange_Testing.Add(indicator_pair);
list_Indicator_FutureValueChange_Testing_ALL[bar_index].Add(indicator_pair);
int count_testing = list_Indicator_FutureValueChange_Testing.Count;
//}
}
}
//if (CurrentBar >= (FutureValueDaysToLookAhead)) //just make sure we avoid out of bounds error in case we don't yet have enough data
//{
// DateTime current_bar_date = Times[bar_index][0].Date;
// DateTime date_to_process = Times[bar_index][0].Date; //need to wait FutureValueDaysToLookAhead days before we can make calcs
// bool bWithinTrainingPeriod = (date_to_process >= TrainingStartDate) && (date_to_process <= TrainingEndDate);
// bool bWithinTestingPeriod = (date_to_process >= TestingStartDate) && (date_to_process <= TestingEndDate);
// if ((bWithinTrainingPeriod) || (bWithinTestingPeriod))
// {
// //TimeSpan diff = TrainingEndDate - TrainingStartDate;
// //int training_days = (int)Math.Abs(Math.Round(diff.TotalDays));
// }
//}
////////
uid = rnd.Next(100000, 999999).ToString();
String unique_id = "_" + uid; // creates a number between 100k and 999k
String debug_txt = "FINISHEDPROCESSING min_samples=" + min_samples_pct.ToString() + " id=" + unique_id.ToString();
Debug.WriteLine(debug_txt);
String control_file_path = output_folder + "control_file" + unique_id + ".txt";
String consolidated_txt_file_path = output_folder + "consolidated_report" + unique_id + ".txt";
String consolidated_csv_file_path = output_folder + "consolidated_report" + unique_id + ".csv";
switch (indicator_to_use)
{
case IndicatorEnum.indicator_MACD:
if (Sanitize == false)
{
description = "MACD";
}
else
{
description = "M";
}
indicator = description;
description = description + "(" + Param1.ToString() + "-" + Param2.ToString() + "-" + Param3.ToString() + ")";
break;
case IndicatorEnum.indicator_RSI:
if (Sanitize == false)
{
description = "RSI";
}
else
{
description = "R";
}
indicator = description;
description = description + "(" + Param1.ToString() + "-" + Param2.ToString() + ")";
break;
case IndicatorEnum.indicator_BOLLINGER:
if (Sanitize == false)
{
description = "BOLL";
}
else
{
description = "B";
}
indicator = description;
description = description + "(" + Param1.ToString() + "-" + Param2.ToString() + ")";
break;
case IndicatorEnum.indicator_STOCHASTIC:
if (Sanitize == false)
{
description = "STOCH";
}
else
{
description = "S";
}
indicator = description;
description = description + "(" + Param1.ToString() + "-" + Param2.ToString() + "-" + Param3.ToString() + ")";
break;
case IndicatorEnum.indicator_STOCHASTIC_RSI:
if (Sanitize == false)
{
description = "STOCH_RSI";
}
else
{
description = "SR";
}
indicator = description;
description = description + "(" + Param1.ToString() + ")";
break;
default:
description = "Unknown";
indicator = description;
break;
}
description = description + " - " + FutureValueDaysToLookAhead.ToString();
if (Sanitize == false)
{
description = description + " days";
}
description = description + " - " + unique_id.Substring(1); //remove preceding "_"
bool bFirstTime = true;
int start_index = 1;
int max_index = symbol_list.Count;
if (ProcessAllTickers == false)
{
start_index = 0;
max_index = 1;
}
for (int i = start_index; i < max_index; i++) //Start at index=1 since we want to ignore the first primary/dummy instrument
{
String symbol_name = symbol_list[i];
if (ProcessAllTickers == false)
{
symbol_name = master_symbol_name;
}
String company_name = company_name_list[i];
if (Sanitize == true)
{
String symbol_name_tmp = string.Concat(symbol_name.Reverse()).ToLower();
symbol_name = char.ToUpper(symbol_name_tmp[0]) + symbol_name_tmp.Substring(1);
company_name = "?";
}
String base_file_path_for_symbol = output_folder + symbol_name; //i.e. c:\temp\knn\AAPL
String training_file_path = base_file_path_for_symbol + "_training" + unique_id + ".csv";
String testing_file_path = base_file_path_for_symbol + "_testing" + unique_id + ".csv";
WriteListToCSV(list_Indicator_FutureValueChange_Training_ALL[i], training_file_path);
WriteListToCSV(list_Indicator_FutureValueChange_Testing_ALL[i], testing_file_path);
String config_file_name = "";
config_file_name = GenerateConfigFile(base_file_path_for_symbol, symbol_name, company_name, training_file_path, testing_file_path, unique_id);
//mut.WaitOne();
if (bFirstTime) //create new file
{
bFirstTime = false;
File.WriteAllText(control_file_path, config_file_name + "\r\n");
}
else // append to existing file
{
File.AppendAllText(control_file_path, config_file_name + "\r\n");
}
//mut.ReleaseMutex();
}
//Now we can call python for all symbols at once by passing in the control_file as cmd line arg
mut.WaitOne();
string mode = " BEST";
if (FindBestSolutions == false)
{
mode = " SINGLE";
}
string args = control_file_path + " " + consolidated_txt_file_path + " " + consolidated_csv_file_path + " c:\\temp\\knn\\master_report.csv" + " c:\\temp\\knn\\master_trig.csv" + " false" + mode;
CallPythonScript(output_folder + "\\Data_Processing39.py", args);
mut.ReleaseMutex();
}
}