public static void RunStocks(Random rnd, MonitoredFunction function, string cbName, int iterations, Tree <long> closestValueQuery, int numOfNodes, int window, DateTime startingDateTime,
int minAmountAtDay, ApproximationType approximation,
string stocksDirPath, string resultDir)
{
var vectorLength = closestValueQuery.Data.Length;
var resultPath =
PathBuilder.Create(resultDir, "Entropy_" + cbName)
.AddProperty("Dataset", "Stocks")
.AddProperty("VectorLength", vectorLength.ToString())
.AddProperty("Nodes", numOfNodes.ToString())
.AddProperty("Window", window.ToString())
.AddProperty("StartingTime", startingDateTime.ToShortDateString().Replace('/', '-'))
.AddProperty("MinAmountAtDay", minAmountAtDay.ToString())
.AddProperty("Approximation", approximation.AsString())
.ToPath("csv");
using (var resultCsvFile = AutoFlushedTextFile.Create(resultPath, AccumaltedResult.Header(numOfNodes)))
using (var stocksProbabilityWindow = StocksProbabilityWindow.Init(stocksDirPath, startingDateTime, minAmountAtDay, numOfNodes, window, closestValueQuery))
{
var initProbabilityVectors = stocksProbabilityWindow.CurrentProbabilityVector();
if (!initProbabilityVectors.All(v => v.Sum().AlmostEqual(1.0, 0.000001)))
{
throw new Exception();
}
var multiRunner = MultiRunner.InitAll(initProbabilityVectors, numOfNodes, vectorLength,
approximation, function);
int i = 0;
while (stocksProbabilityWindow.MoveNext() && (i++ < iterations))
{
var changeProbabilityVectors = stocksProbabilityWindow.CurrentChangeProbabilityVector();
if (!changeProbabilityVectors.All(v => v.Sum().AlmostEqual(0.0, 0.000001)))
{
throw new Exception();
}
multiRunner.Run(changeProbabilityVectors, rnd, false)
.Select(r => r.AsCsvString())
.ForEach(resultCsvFile.WriteLine);
}
}
}
public static void RunStocks(Random rnd, int iterations, Tree <long> closestValueQuery, int numOfNodes, int window, int collapseDimension, DateTime startingDateTime,
int minAmountAtDay, ApproximationType approximation,
string stocksDirPath, string resultDir)
{
var vectorLength = closestValueQuery.Data.Length;
var resultPath =
PathBuilder.Create(resultDir, "EntropySketch")
.AddProperty("Dataset", "Stocks")
.AddProperty("BucketLength", vectorLength.ToString())
.AddProperty("SketchDimension", collapseDimension.ToString())
.AddProperty("Nodes", numOfNodes.ToString())
.AddProperty("Window", window.ToString())
.AddProperty("StartingTime", startingDateTime.ToShortDateString().Replace('/', '-'))
.AddProperty("MinAmountAtDay", minAmountAtDay.ToString())
.AddProperty("Approximation", approximation.AsString())
.ToPath("csv");
var entropySketch = new EntropySketchFunction(collapseDimension);
using (var resultCsvFile = AutoFlushedTextFile.Create(resultPath, AccumaltedResult.Header(numOfNodes) + ",Entropy"))
using (var stocksProbabilityWindow = StocksProbabilityWindow.Init(stocksDirPath, startingDateTime, minAmountAtDay, numOfNodes, window, closestValueQuery))
{
var initProbabilityVectors = stocksProbabilityWindow.CurrentProbabilityVector().Map(entropySketch.CollapseProbabilityVector);
var multiRunner = MultiRunner.InitAll(initProbabilityVectors, numOfNodes, collapseDimension,
approximation, entropySketch.MonitoredFunction);
int i = 0;
while (stocksProbabilityWindow.MoveNext() && (i++ < iterations))
{
var changeProbabilityVectors = stocksProbabilityWindow.CurrentChangeProbabilityVector()
.Map(entropySketch.CollapseProbabilityVector);
var entropy = Vector.AverageVector(stocksProbabilityWindow.CurrentProbabilityVector())
.IndexedValues.Values.Sum(p => - p * Math.Log(p));
multiRunner.Run(changeProbabilityVectors, rnd, false)
.Select(r => r.AsCsvString() + "," + entropy)
.ForEach(resultCsvFile.WriteLine);
}
}
}