public static void LoadExternalFeatureBinary(Asset asset, ExternalFeatureData externalFeature, MessageDelegate messageDelegate)
{
//Read the results into the bars from the binary file that python has written over
PreCalculatedFeatures pcFeatures = new PreCalculatedFeatures();
//[ASSET] is used as a placeholder so insert the assetname here
string filename = externalFeature.BinaryFilepath.Replace("[ASSET]", asset.Name);
byte[] bytes = File.ReadAllBytes(filename);
//Traverse the byte array to add in the values to the Data attribute of the corresponding bar
int i = 0;
while (i < bytes.Length)
{
//Read the required data from the byte array and increment the index
long timestamp = BitConverter.ToInt64(bytes, i);
i += 8;
//convert from python to .net date
DateTime dt = DateTime.FromBinary(timestamp / 100).AddYears(1969);
//Add a new bar
Dictionary <string, double?> barData = new Dictionary <string, double?>();
pcFeatures.Data.Add(dt, barData);
foreach (string field in externalFeature.FieldNames)
{
double val = BitConverter.ToDouble(bytes, i);
barData.Add(field, val);
i += 8;
}
}
//add this data to the asset (or overwrite if exists)
if (!asset.Data.ContainsKey(externalFeature.Timeframe))
{
asset.Data.Add(externalFeature.Timeframe, pcFeatures);
}
else
{
asset.Data[externalFeature.Timeframe] = pcFeatures;
}
}
public static void PythonFeatureBuilder(PythonBridge pb, Asset asset, ExternalFeatureData externalFeatureData, MessageDelegate messageDelegate = null)
{
messageDelegate?.Invoke(asset.Name + " Precalcualting Features ...");
//Record start time of process for time taken message
DateTime now = DateTime.Now;
//build the features into a semicolon sepearated string
string featureCommand = externalFeatureData.FeatureCommands;
//get the dataset for this timeframe
Dictionary <int, Bar[]> timeframes = DataBuilder.BuildTimeFrames(asset, new int[] { externalFeatureData.Timeframe });
//Use a temporary Share directory for this data
string filename = asset.DataPath.Replace(".bin", "_Share.bin");
//Generate a tempory binary file containing the datafeed to be used for calculation and save to disk
string datasetType = "single";
if (externalFeatureData.CalculateOn == DataFeedType.Ask || externalFeatureData.CalculateOn == DataFeedType.Bid) //otherwise include all bid or ask OHLC and volume.
{
datasetType = "whole";
DataBuilder.DatasetToBinary(filename, timeframes[externalFeatureData.Timeframe], externalFeatureData.CalculateOn);
}
else //Faster way if just need a single data feed
{
DataBuilder.DatasetToBinarySingle(filename, timeframes[externalFeatureData.Timeframe], externalFeatureData.CalculateOn);
}
//[ASSET] is a placeholder
string transformedFilename = externalFeatureData.BinaryFilepath.Replace("[ASSET]", asset.Name);
//Bridge python to calculate the data
string[] commands = new string[] { datasetType, filename, transformedFilename,
externalFeatureData.FeatureCommands };
pb.RunScript(FeatureBuildPath, commands);
File.Delete(filename);
messageDelegate?.Invoke(asset.Name + " feature calculations took: " + (DateTime.Now - now).TotalSeconds + " secs");
}
