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Merge branch 'MKDT_CNN01'

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Sean
2026-03-10 21:45:50 -04:00
parent 922f99f061 22b387a2e3
commit 05b9ac3897
5 changed files with 343 additions and 17 deletions
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42
MarketDataLib/Generator/CMMomentum/CMMomentumGenerator.cs
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@@ -5,6 +5,7 @@ using MarketData.MarketDataModel;
using MarketData.Utils;
using System;
using System.Collections.Generic;
using System.IO;
using System.Linq;
namespace MarketData.Generator.CMMomentum
@@ -132,6 +133,35 @@ namespace MarketData.Generator.CMMomentum
}
return true;
}
// This method is made public in order that it can be tested
//public static bool PredictCandidate(CMCandidate cmCandidate,CMParams cmParams)
//{
// try
// {
// CNNClient cnnClient=new CNNClient(cmParams.UseCNNHost);
// DataProcessor dataProcessor=new DataProcessor();
// dataProcessor.Width=128;
// dataProcessor.Height=128;
// dataProcessor.PenWidth=1;
// TestCase testCase=new TestCase(cmCandidate.Symbol,cmCandidate.TradeDate,cmParams.UseCNNDayCount,TestCase.CaseType.Test,TestCase.GenerateType.BollingerBand,TestCase.OutputType.OutputStream);
// dataProcessor.ProcessData(testCase);
// String prediction = cnnClient.Predict(CNNClient.Model.resnet50_20241024_270,testCase.LastStream);
// prediction=prediction.Substring(prediction.IndexOf("-->"));
// int result=int.Parse(Utility.BetweenString(prediction,"[[","]"));
// if(1==result)
// {
// cmCandidate.Score*=(1.00+cmParams.UseCNNRewardPercentDecimal); // increase the score by the percentage indicated in the params settings
// cmCandidate.CNNPrediction=true;
// }
// return true;
// }
// catch(Exception exception)
// {
// MDTrace.WriteLine(LogLevel.DEBUG,String.Format("Error encountered calling convolutional model at {0}. Exception was {1}",cmParams.UseCNNHost,exception.ToString()));
// return false;
// }
//}
// This method is made public in order that it can be tested
public static bool PredictCandidate(CMCandidate cmCandidate,CMParams cmParams)
{
@@ -139,12 +169,14 @@ namespace MarketData.Generator.CMMomentum
{
CNNClient cnnClient=new CNNClient(cmParams.UseCNNHost);
DataProcessor dataProcessor=new DataProcessor();
dataProcessor.Width=128;
dataProcessor.Height=128;
int imageDimensions=224;
dataProcessor.Width=imageDimensions;
dataProcessor.Height=imageDimensions;
dataProcessor.PenWidth=1;
TestCase testCase=new TestCase(cmCandidate.Symbol,cmCandidate.TradeDate,cmParams.UseCNNDayCount,TestCase.CaseType.Test,TestCase.GenerateType.BollingerBand,TestCase.OutputType.OutputStream);
TestCase testCase=new TestCase(cmCandidate.Symbol,cmCandidate.TradeDate,cmParams.UseCNNDayCount,TestCase.CaseType.Test,TestCase.GenerateType.BollingerBandWithVIX,TestCase.OutputType.OutputStream);
dataProcessor.ProcessData(testCase);
String prediction = cnnClient.Predict(CNNClient.Model.resnet50_20241024_270,testCase.LastStream);
Stream streamResult = cnnClient.ProcessImage(testCase.LastStream); // process the image through PIL
String prediction = cnnClient.Predict(CNNClient.Model.convnext,streamResult);
prediction=prediction.Substring(prediction.IndexOf("-->"));
int result=int.Parse(Utility.BetweenString(prediction,"[[","]"));
if(1==result)
@@ -160,5 +192,7 @@ namespace MarketData.Generator.CMMomentum
return false;
}
}
}
}