//Method to create DataFrame
public void createDF()
{
PISetup ps = new PISetup();
Dictionary <DateTime, Object> dict = ps.getArchiveValues();
Double[] db = new double[dict.Count];
String[] dt = new String[dict.Count];
int i = 0;
foreach (object ob in dict.Values)
{
db[i] = Convert.ToDouble(ob);
i += 1;
}
int j = 0;
foreach (DateTime da in dict.Keys)
{
dt[j] = Convert.ToString(da);
j += 1;
}
NumericVector myNum = engine.CreateNumericVector(db);
CharacterVector myCha = engine.CreateCharacterVector(dt);
engine.SetSymbol("Time", myCha);
engine.SetSymbol("BA.TEMP.1", myNum);
engine.Evaluate("df <- data.frame(Timestamp=c(Time), BA.TEMP.1=c(BA.TEMP.1))");
//engine.Evaluate("write.csv(df, file = \"C:/File_1.csv\")");
//engine.Evaluate("View(df)");
}
private void DrawChart(string chartName, IEnumerable <IEnumerable <Tuple <double, double> > > data, double lowX, double highX, double lowY, double highY)
{
if (data.Count() == 0)
{
return;
}
var colorIndex = 0;
var colors = new[] { "red", "green", "blue", "yellow" };
this.engine.Evaluate("dev.new()");
this.engine.SetSymbol("lowX", this.engine.CreateNumeric(lowX));
//this.engine.SetSymbol("main", this.engine.CreateCharacter("Chart number1"));
this.engine.SetSymbol("highX", this.engine.CreateNumeric(highX));
this.engine.SetSymbol("lowY", this.engine.CreateNumeric(lowY));
this.engine.SetSymbol("highY", this.engine.CreateNumeric(highY));
this.engine.Evaluate($"plot(1, type=\"n\", xlab=\"X\", ylab=\"Y\", xlim=c(lowX, highX), ylim=c(lowY, highY), main='{chartName}')");
foreach (var val in data)
{
// get xs
engine.SetSymbol("x", engine.CreateNumericVector(val.Select(e => e.Item1)));
// get ys
engine.SetSymbol("y", engine.CreateNumericVector(val.Select(e => e.Item2)));
engine.SetSymbol("color", engine.CreateCharacterVector(new[] { colors[colorIndex % colors.Length] }));
engine.Evaluate("points(x, y, col = color)");
colorIndex++;
}
}
private void SetupDotNetToRConverters()
{
SetupDotNetToRConverter(typeof(void), p => null);
SetupDotNetToRConverter(typeof(string), p => engine.CreateCharacter((string)p));
SetupDotNetToRConverter(typeof(string[]), p => engine.CreateCharacterVector((string[])p));
SetupDotNetToRConverter(typeof(List <string>), p => engine.CreateCharacterVector((IEnumerable <string>)p));
SetupDotNetToRConverter(typeof(IList <string>), p => engine.CreateCharacterVector((IEnumerable <string>)p));
SetupDotNetToRConverter(typeof(ICollection <string>), p => engine.CreateCharacterVector((IEnumerable <string>)p));
SetupDotNetToRConverter(typeof(IEnumerable <string>), p => engine.CreateCharacterVector((IEnumerable <string>)p));
SetupDotNetToRConverter(typeof(string[, ]), p => engine.CreateCharacterMatrix((string[, ])p));
SetupDotNetToRConverter(typeof(int), p => engine.CreateInteger((int)p));
SetupDotNetToRConverter(typeof(int[]), p => engine.CreateIntegerVector((int[])p));
SetupDotNetToRConverter(typeof(List <int>), p => engine.CreateIntegerVector((IEnumerable <int>)p));
SetupDotNetToRConverter(typeof(IList <int>), p => engine.CreateIntegerVector((IEnumerable <int>)p));
SetupDotNetToRConverter(typeof(ICollection <int>), p => engine.CreateIntegerVector((IEnumerable <int>)p));
SetupDotNetToRConverter(typeof(IEnumerable <int>), p => engine.CreateIntegerVector((IEnumerable <int>)p));
SetupDotNetToRConverter(typeof(int[, ]), p => engine.CreateIntegerMatrix((int[, ])p));
SetupDotNetToRConverter(typeof(bool), p => engine.CreateLogical((bool)p));
SetupDotNetToRConverter(typeof(bool[]), p => engine.CreateLogicalVector((bool[])p));
SetupDotNetToRConverter(typeof(List <bool>), p => engine.CreateLogicalVector((IEnumerable <bool>)p));
SetupDotNetToRConverter(typeof(IList <bool>), p => engine.CreateLogicalVector((IEnumerable <bool>)p));
SetupDotNetToRConverter(typeof(ICollection <bool>), p => engine.CreateLogicalVector((IEnumerable <bool>)p));
SetupDotNetToRConverter(typeof(IEnumerable <bool>), p => engine.CreateLogicalVector((IEnumerable <bool>)p));
SetupDotNetToRConverter(typeof(bool[, ]), p => engine.CreateLogicalMatrix((bool[, ])p));
SetupDotNetToRConverter(typeof(double), p => engine.CreateNumeric((double)p));
SetupDotNetToRConverter(typeof(double[]), p => engine.CreateNumericVector((double[])p));
SetupDotNetToRConverter(typeof(List <double>), p => engine.CreateNumericVector((IEnumerable <double>)p));
SetupDotNetToRConverter(typeof(IList <double>), p => engine.CreateNumericVector((IEnumerable <double>)p));
SetupDotNetToRConverter(typeof(ICollection <double>), p => engine.CreateNumericVector((IEnumerable <double>)p));
SetupDotNetToRConverter(typeof(IEnumerable <double>), p => engine.CreateNumericVector((IEnumerable <double>)p));
SetupDotNetToRConverter(typeof(double[, ]), p => engine.CreateNumericMatrix((double[, ])p));
SetupDotNetToRConverter(typeof(DateTime), p => engine.CreatePosixct((DateTime)p));
SetupDotNetToRConverter(typeof(DateTime[]), p => engine.CreatePosixctVector((DateTime[])p));
SetupDotNetToRConverter(typeof(List <DateTime>), p => engine.CreatePosixctVector((IEnumerable <DateTime>)p));
SetupDotNetToRConverter(typeof(IList <DateTime>), p => engine.CreatePosixctVector((IEnumerable <DateTime>)p));
SetupDotNetToRConverter(typeof(ICollection <DateTime>), p => engine.CreatePosixctVector((IEnumerable <DateTime>)p));
SetupDotNetToRConverter(typeof(IEnumerable <DateTime>), p => engine.CreatePosixctVector((IEnumerable <DateTime>)p));
SetupDotNetToRConverter(typeof(DateTime[, ]), p => engine.CreatePosixctMatrix((DateTime[, ])p));
SetupDotNetToRConverter(typeof(TimeSpan), p => engine.CreateDiffTime((TimeSpan)p));
SetupDotNetToRConverter(typeof(TimeSpan[]), p => engine.CreateDiffTimeVector((TimeSpan[])p));
SetupDotNetToRConverter(typeof(List <TimeSpan>), p => engine.CreateDiffTimeVector((IEnumerable <TimeSpan>)p));
SetupDotNetToRConverter(typeof(IList <TimeSpan>), p => engine.CreateDiffTimeVector((IEnumerable <TimeSpan>)p));
SetupDotNetToRConverter(typeof(ICollection <TimeSpan>), p => engine.CreateDiffTimeVector((IEnumerable <TimeSpan>)p));
SetupDotNetToRConverter(typeof(IEnumerable <TimeSpan>), p => engine.CreateDiffTimeVector((IEnumerable <TimeSpan>)p));
SetupDotNetToRConverter(typeof(TimeSpan[, ]), p => engine.CreateDiffTimeMatrix((TimeSpan[, ])p));
}
private void TransferDataToR()
{
for (int i = 1; i <= piValuesList.Count; i++)
{
double[] values = ConvertValuesToDoubleArray(piValuesList[i - 1]);
double[] ts = ConvertTSToDoubleArray(piValuesList[i - 1]);
NumericVector tagval = engine.CreateNumericVector(values);
engine.SetSymbol("tag" + i.ToString() + "val", tagval);
NumericVector tag_tsd = engine.CreateNumericVector(ts);
engine.SetSymbol("tag" + i.ToString() + "tsd", tag_tsd);
engine.Evaluate("tag" + i.ToString() + "ts<-as.POSIXct(tag" + i.ToString() + "tsd, origin='1970-01-01')");
engine.Evaluate("tag" + i.ToString() + "<- data.frame(tag" + i.ToString() + "ts,tag" + i.ToString() + "val)");
}
}
static void Main(string[] args)
{
REngine.SetEnvironmentVariables();
REngine engine = REngine.GetInstance();
// REngine requires explicit initialization.
// You can set some parameters.
engine.Initialize();
// .NET Framework array to R vector.
NumericVector group1 = engine.CreateNumericVector(new double[] { 30.02, 29.99, 30.11, 29.97, 30.01, 29.99 });
engine.SetSymbol("group1", group1);
// Direct parsing from R script.
NumericVector group2 = engine.Evaluate("group2 <- c(29.89, 29.93, 29.72, 29.98, 30.02, 29.98)").AsNumeric();
// Test difference of mean and get the P-value.
GenericVector testResult = engine.Evaluate("t.test(group1, group2)").AsList();
double p = testResult["p.value"].AsNumeric().First();
Console.WriteLine("Group1: [{0}]", string.Join(", ", group1));
Console.WriteLine("Group2: [{0}]", string.Join(", ", group2));
Console.WriteLine("P-value = {0:0.000}", p);
// you should always dispose of the REngine properly.
// After disposing of the engine, you cannot reinitialize nor reuse it
engine.Dispose();
}
public void ConstruirMejorModeloArmonico(ref REngine motorDeR, string nombreDelVectorDeDatosR, NumericVector datosParaR, double[] vectorDeDatos, out double[] vectorValoresDelModelo, int usarDatosDesde, int usarDatosHasta, out double declinacionInicial, ref double produccionInicial, ref double r2, ref double aic)
{
int numeroDeParametros = 2;
double declinacionInicialLocal;
double produccionInicialLocal;
double[] vectorLocalValoresDelModelo = new double[usarDatosHasta - usarDatosDesde + 1];
NumericVector coeficientesDesdeR = motorDeR.CreateNumericVector(2);
int numeroDeDatos = usarDatosHasta - usarDatosDesde + 1;
motorDeR.Evaluate("matriz <- matrix(nrow = length(" + nombreDelVectorDeDatosR + "), ncol = 2)");
motorDeR.Evaluate("tiempo <- c(1:(length(" + nombreDelVectorDeDatosR + ")))");
motorDeR.Evaluate("matriz[,1] <- 1");
motorDeR.Evaluate("matriz[,2] <- tiempo");
motorDeR.Evaluate("vectorInverso <- 1/(" + nombreDelVectorDeDatosR + ")");
motorDeR.Evaluate("i=1\nwhile (i < length(vectorInverso))\n{\nif (" + nombreDelVectorDeDatosR + "[i] == 0)\n{\nvectorInverso[i] = 0\n}\ni = i + 1\n}");
motorDeR.Evaluate("coeficientesArmonico <- solve(t(matriz) %*% matriz) %*% (t(matriz) %*% vectorInverso)");
coeficientesDesdeR = motorDeR.Evaluate("coeficientesArmonico").AsNumeric();
produccionInicialLocal = 1 / (coeficientesDesdeR[0]);
declinacionInicialLocal = coeficientesDesdeR[1] / coeficientesDesdeR[0];
DarValoresAlModeloArmonico(ref vectorLocalValoresDelModelo, produccionInicialLocal, declinacionInicialLocal);
HallarR2(vectorDeDatos, vectorLocalValoresDelModelo, usarDatosDesde, usarDatosHasta, out r2);
HallarAIC(vectorDeDatos, vectorLocalValoresDelModelo, usarDatosDesde, usarDatosHasta, out aic, numeroDeParametros);
vectorValoresDelModelo = vectorLocalValoresDelModelo;
produccionInicial = produccionInicialLocal;
declinacionInicial = declinacionInicialLocal;
}
public static void barchart_months_revenue(this REngine engine)
{
//# Create the data for the chart.
// H < -c(7, 12, 28, 3, 41)
//M < -c("一月", "二月", "三月", "四月", "五月")
//# Give the chart file a name.
//png(file = "barchart_months_revenue.png")
//# Plot the bar chart.
//barplot(H, names.arg = M, xlab = "月份", ylab = "收入量", col = "blue",
//main = "收入图表", border = "red")
//# Save the file.
//dev.off()
var numVer = engine.CreateNumericVector(new double[] { 110, 300, 390, 200 });
var charVer = engine.CreateCharacterVector(new string[] { "一月", "二月", "三用", "四月" });
var mainChar = engine.CreateCharacter("收入图表");
engine.SetSymbol("H", numVer);
engine.SetSymbol("M", charVer);
engine.SetSymbol("name", mainChar);
engine.Evaluate("png(file = 'barchart_months_revenue.jpg')");
engine.Evaluate("barplot(H,names.arg=M,xlab='月份',ylab='收入量',col='blue',main=name,border='red')");
engine.Evaluate("dev.off()");
}
/// <summary>
///
/// </summary>
/// <param name="engine"></param>
public static void Age_title_colours(this REngine engine)
{
//# Create data for the graph.
// x < -c(11, 30, 39, 20)
//labels < -c("70后", "80后", "90后", "00后")
//# Give the chart file a name.
//png(file = "age_title_colours.jpg")
//# Plot the chart with title and rainbow color pallet.
//pie(x, labels, main = "出生年龄段 - 饼状图", col = rainbow(length(x)))
//# Save the file.
//dev.off()
var numVer = engine.CreateNumericVector(new double[] { 11, 30, 39, 20 });
var charVer = engine.CreateCharacterVector(new string[] { "70后", "80后", "90后", "00后" });
var mainChar = engine.CreateCharacter("出生年龄段 - 饼状图");
engine.SetSymbol("x", numVer);
engine.SetSymbol("labels", charVer);
engine.SetSymbol("main", mainChar);
var length = engine.Evaluate("rainbow(length(x))");
engine.SetSymbol("col", length);
engine.Evaluate("png(file = 'age_title_colours.jpg')");
engine.Evaluate("pie(x,labels,main=main,col = col)");
engine.Evaluate("dev.off()");
}
static void Main(string[] args)
{
REngine.SetEnvironmentVariables(@"c:\Program Files\Microsoft\R Client\R_SERVER\bin\x64\", @"c:\Program Files\Microsoft\R Client\R_SERVER\"); // <-- May be omitted; the next line would call it.
REngine engine = REngine.GetInstance();
// A somewhat contrived but customary Hello World:
//CharacterVector charVec = engine.CreateCharacterVector(new[] { "Hello, R world!, .NET speaking" });
//engine.SetSymbol("greetings", charVec);
//engine.Evaluate("str(greetings)"); // print out in the console
//string[] a = engine.Evaluate("'Hi there .NET, from the R engine'").AsCharacter().ToArray();
//Console.WriteLine("R answered: '{0}'", a[0]);
//Console.WriteLine("Press any key to exit the program");
//Console.ReadKey();
// .NET Framework array to R vector.
NumericVector group1 = engine.CreateNumericVector(new double[] { 30.02, 29.99, 30.11, 29.97, 30.01, 29.99 });
engine.SetSymbol("group1", group1);
// Direct parsing from R script.
NumericVector group2 = engine.Evaluate("group2 <- c(29.89, 29.93, 29.72, 29.98, 30.02, 29.98)").AsNumeric();
// Test difference of mean and get the P-value.
GenericVector testResult = engine.Evaluate("t.test(group1, group2)").AsList();
double p = testResult["p.value"].AsNumeric().First();
Console.WriteLine("Group1: [{0}]", string.Join(", ", group1));
Console.WriteLine("Group2: [{0}]", string.Join(", ", group2));
Console.WriteLine("P-value = {0:0.000}", p);
Console.ReadKey();
engine.Dispose();
}
/// <summary>
/// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
/// </summary>
public override void Initialize()
{
SetStartDate(2013, 10, 07); //Set Start Date
SetEndDate(2013, 10, 11); //Set End Date
SetCash(100000); //Set Strategy Cash
// Find more symbols here: http://quantconnect.com/data
AddEquity("SPY", Resolution.Second);
REngine engine = REngine.GetInstance();
engine.Evaluate("print('This is from R command.')");
// .NET Framework array to R vector.
NumericVector group1 = engine.CreateNumericVector(new double[] { 30.02, 29.99, 30.11, 29.97, 30.01, 29.99 });
engine.SetSymbol("group1", group1);
// Direct parsing from R script.
NumericVector group2 = engine.Evaluate("group2 <- c(29.89, 29.93, 29.72, 29.98, 30.02, 29.98)").AsNumeric();
// Test difference of mean and get the P-value.
GenericVector testResult = engine.Evaluate("t.test(group1, group2)").AsList();
double p = testResult["p.value"].AsNumeric().First();
// you should always dispose of the REngine properly.
// After disposing of the engine, you cannot reinitialize nor reuse it
engine.Dispose();
}
private static double GetRecomendedQuntity(List <double> countList)
{
List <double> data = new List <double>();
for (int i = 0; i < countList.Count; i++)
{
data.Add(countList[i]);
}
REngine.SetEnvironmentVariables();
REngine engine = REngine.GetInstance();
engine.Initialize();
NumericVector dataVector = engine.CreateNumericVector(data.ToArray());
engine.SetSymbol("dataVector", dataVector);
engine.Evaluate("graphObj <- ts(dataVector, frequency=1, start=c(1, 1, 1))");
engine.Evaluate("library(\"forecast\")");
engine.Evaluate("arimaFit <- arima(graphObj,order=c(2,2,2))");
engine.Evaluate("fcast <- forecast(arimaFit, h=1)");
engine.Evaluate("result <- as.numeric(fcast$mean)");
NumericVector forecastResult = engine.GetSymbol("result").AsNumeric();
double result = forecastResult.First();
engine.Dispose();
return(result);
}
public static void TestMethod()
{
REngine.SetEnvironmentVariables();
// There are several options to initialize the engine, but by default the following suffice:
REngine engine = REngine.GetInstance();
// .NET Framework array to R vector.
NumericVector testTs = engine.CreateNumericVector(new double[] { 30.02, 29.99, 30.11, 29.97, 30.01, 29.99 });
engine.SetSymbol("testTs", testTs);
// Direct parsing from R script.
//NumericVector group2 = engine.Evaluate("group2 <- c(29.89, 29.93, 29.72, 29.98, 30.02, 29.98)").AsNumeric();
//auto arima for monthly
engine.Evaluate("tsValue <- ts(testTs, frequency=1, start=c(2010, 1, 1))");
engine.Evaluate("library(forecast)");
engine.Evaluate("arimaFit <- auto.arima(tsValue)");
engine.Evaluate("fcast <- forecast(tsValue, h=5)");
var a = engine.Evaluate("fcast <- forecast(tsValue, h=5)").AsCharacter();
NumericVector forecasts = engine.Evaluate("fcast$mean").AsNumeric();
foreach (var item in forecasts)
{
Console.WriteLine(item);
}
engine.Dispose();
}
public void OnData(TradeBars data)
{
if (IsWarmingUp)
{
return;
}
var logData = _window.Select(closingPrice => Math.Log10(closingPrice));
var diff = logData.Zip(logData.Skip(1), (x, y) => y - x);
var returns = _engine.CreateNumericVector(diff);
_engine.SetSymbol("roll.returns", returns);
_engine.Evaluate(@"source('C:\Users\M\Documents\Visual Studio 2015\Projects\Trading\Trading\arima_garch.r')");
var direction = _engine.GetSymbol("directions").AsInteger()[0];
var holdings = Portfolio[Symbol].Quantity;
if (holdings <= 0 && direction == 1)
{
Log("BUY >> " + Securities[Symbol].Price);
SetHoldings(Symbol, 1.0);
}
else if (holdings >= 0 && direction == -1)
{
Log("SELL >> " + Securities[Symbol].Price);
SetHoldings(Symbol, -1.0);
}
}
public static SymbolicExpression CreateDiffTimeVector(this REngine engine, IEnumerable <TimeSpan> data)
{
var numeric = data.ToArray().FromTimeSpan();
var sexp = engine.CreateNumericVector(numeric);
return(sexp.AddDiffTimeAttributes());
}
//
// GET: /Home/
public ActionResult Index()
{
REngine.SetEnvironmentVariables();
REngine engine = REngine.GetInstance();
engine.Initialize();
NumericVector group1 = engine.CreateNumericVector(new double[] { 30.02, 29.99, 30.11, 29.97, 30.01, 29.99 });
engine.SetSymbol("group1", group1);
// Direct parsing from R script.
NumericVector group2 = engine.Evaluate("group2 <- c(29.89, 29.93, 29.72, 29.98, 30.02, 29.98)").AsNumeric();
// Test difference of mean and get the P-value.
GenericVector testResult = engine.Evaluate("t.test(group1, group2)").AsList();
double p = testResult["p.value"].AsNumeric().First();
Console.WriteLine("Group1: [{0}]", string.Join(", ", group1));
Console.WriteLine("Group2: [{0}]", string.Join(", ", group2));
Console.WriteLine("P-value = {0:0.000}", p);
// you should always dispose of the REngine properly.
// After disposing of the engine, you cannot reinitialize nor reuse it
engine.Dispose();
return(View());
}
static void Main(string[] args)
{
// Set the folder in which R.dll locates.
var envPath = Environment.GetEnvironmentVariable("PATH");
var rBinPath = @"C:\Program Files (x86)\R\R-2.11.1\bin";
//var rBinPath = @"C:\Program Files\R\R-2.11.1-x64\bin"; // Doesn't work ("DLL was not found.")
Environment.SetEnvironmentVariable("PATH", envPath + Path.PathSeparator + rBinPath);
using (REngine engine = REngine.CreateInstance("RDotNet"))
{
// Initializes settings.
engine.Initialize();
// .NET Framework array to R vector.
NumericVector group1 = engine.CreateNumericVector(new double[] { 30.02, 29.99, 30.11, 29.97, 30.01, 29.99 });
engine.SetSymbol("group1", group1);
// Direct parsing from R script.
NumericVector group2 = engine.Evaluate("group2 <- c(29.89, 29.93, 29.72, 29.98, 30.02, 29.98)").AsNumeric();
// Test difference of mean and get the P-value.
GenericVector testResult = engine.Evaluate("t.test(group1, group2)").AsList();
double p = testResult["p.value"].AsNumeric().First();
Console.WriteLine("Group1: [{0}]", string.Join(", ", group1));
Console.WriteLine("Group2: [{0}]", string.Join(", ", group2));
Console.WriteLine("P-value = {0:0.000}", p);
}
}
static void RMain(string[] args)
{
REngine.SetEnvironmentVariables();
// There are several options to initialize the engine, but by default the following suffice:
using (REngine engine = REngine.GetInstance())
{
// .NET Framework array to R vector.
NumericVector group1 = engine.CreateNumericVector(new double[] { 30.02, 29.99, 30.11, 29.97, 30.01, 29.99 });
engine.SetSymbol("group1", group1);
// Direct parsing from R script.
NumericVector group2 = engine.Evaluate("group2 <- c(29.89, 29.93, 29.72, 29.98, 30.02, 29.98)").AsNumeric();
// Test difference of mean and get the P-value.
GenericVector testResult = engine.Evaluate("t.test(group1, group2)").AsList();
double p = testResult["p.value"].AsNumeric().First();
Console.WriteLine("Group1: [{0}]", string.Join(", ", group1));
Console.WriteLine("Group2: [{0}]", string.Join(", ", group2));
Console.WriteLine("P-value = {0:0.000}", p);
// you should always dispose of the REngine properly.
// After disposing of the engine, you cannot reinitialize nor reuse it
// engine.Dispose();
} // End Using engine
} // End Sub RMain
// C:\Program Files\R\R-3.2.4revised
public double[] ForeCast(double[] serie, int numberOfPredictions)
{
// source: http://stackoverflow.com/questions/14879697/retrieve-results-from-r-evaluation-using-r-net
engine.Initialize();
// code below to run the first time, choose yes to install in personal directory
// engine.Evaluate("install.packages(\"forecast\")");
NumericVector testGroup = engine.CreateNumericVector(serie);
engine.SetSymbol("testGroup", testGroup);
engine.Evaluate("testTs <- c(testGroup)");
NumericVector ts = engine.GetSymbol("testTs").AsNumeric();
engine.Evaluate("tsValue <- ts(testTs, frequency=1, start=c(2016, 4, 9))");
engine.Evaluate("library(forecast)");
engine.Evaluate("arimaFit <- auto.arima(tsValue)");
engine.Evaluate("fcast <- forecast(tsValue, h=" + numberOfPredictions + ")");
engine.Evaluate("results <- fcast$mean");
//engine.Evaluate("plot(fcast)");
var fcast = engine.GetSymbol("results").AsNumeric().Select(d => Math.Round(d, 2)).ToArray();
//var nv = ts.AsNumeric().ToArray().Select(a => ""+ a).Aggregate((a,b) => a + "," + b);
//var rstring = fcast.Select(a => "" + a).Aggregate((a, b) => a + "," + b);
////var result = nv.ToArray<double>();
return(fcast);
}
private void button1_Click(object sender, EventArgs e)
{
engine.Evaluate("library('ks')");
engine.Evaluate("library(ggplot2)");
//engine.Evaluate("library(sm)");
for (int i = 0; i < values.Length; i++)
{
Random r = new Random(3);
//r.NextDouble();
values[i] += 1000 * r.NextDouble();
}
data = engine.CreateNumericVector(values);
engine.SetSymbol("group1", data);
engine.Evaluate("fhat <- kde(group1, h = hpi(group1))");
engine.Evaluate("X <- rkde(fhat = fhat, n = length(group1))");
//engine.Evaluate("p1 <- plot(density(group1))");
// engine.Evaluate("p2 <- plot(density(X))");
string TempImagePath = @"C:\Users\Tom\Desktop\test.png";
engine.Evaluate(string.Format("png('{0}', {1}, {2})", TempImagePath.Replace('\\', '/'), pictureBox1.Width, this.pictureBox1.Height));
engine.Evaluate("par(mfrow=c(1,2))");
engine.Evaluate("plot(density(group1))");
engine.Evaluate("plot(density(X))");
engine.Evaluate("dev.off()");
this.pictureBox1.ImageLocation = TempImagePath;
//engine.Evaluate("hist(group1)");
//engine.Evaluate("d <- density(group1)");
//engine.Evaluate("sm.density(group1, PANEL =\"TRUE\")");
}
public static SymbolicExpression CreatePosixctVector(this REngine engine, DateTime[] data)
{
var numeric = data.ToTicks(out var tzone);
var sexp = engine.CreateNumericVector(numeric);
return(sexp.AddPosixctAttributes(tzone));
}
static void TestOptimCsharp(REngine engine)
{
var rand = new Random(0);
int n = 10000;
double x, y, r, xb, yb, rb;
rb = double.MaxValue; xb = yb = double.MaxValue;
engine.Evaluate("rosen <- function(x, y) { (1-x)**2 + 100*(y-x*x)**2 }");
Console.WriteLine("*** Try a basic way to call the function in R ***");
for (int i = 0; i < n; i++)
{
x = -1 + rand.NextDouble() * (3 - (-1));
y = -1 + rand.NextDouble() * (3 - (-1));
r = engine.Evaluate(string.Format("rosen({0}, {1})", x, y)).AsNumeric().ToArray()[0];
if (r < rb)
{
rb = r;
xb = x;
yb = y;
}
}
Console.WriteLine("The best score r={0} is for x={1}, y={2}", rb, xb, yb);
Console.WriteLine("*** Try an R function 'pointer' with a vectorized function call. Faster, if you can do it this way***");
var f = engine.GetSymbol("rosen").AsFunction();
double[] xa = new double[n], ya = new double[n];
rand = new Random(0);
for (int i = 0; i < n; i++)
{
xa[i] = -1 + rand.NextDouble() * (3 - (-1));
ya[i] = -1 + rand.NextDouble() * (3 - (-1));
}
double[] ra = f.Invoke(new[] { engine.CreateNumericVector(xa), engine.CreateNumericVector(ya) })
.AsNumeric().ToArray();
rb = ra.Min();
int indBest = -1;
for (int i = 0; i < ra.Length; i++)
{ // no which.min in C#. Should call R here too...
if (ra[i] <= rb)
{
indBest = i;
}
}
Console.WriteLine("The best score r={0} is for x={1}, y={2}", rb, xa[indBest], ya[indBest]);
}
static double calcSDev(REngine engine, double[] arr)
{
// Note: only one quick and slightly dirty way to do it
NumericVector rVector = engine.CreateNumericVector(arr);
engine.SetSymbol("x", rVector);
return(engine.Evaluate("sd(x)").AsNumeric() [0]);
}
// STATUS: this works
/// <summary> Get a single pitcher's winning percentage </summary>
/// <remarks> Calculating Baseball Data with R </remarks>
public void CalculatePitcherWinningPercentage()
{
REngine engine = CreateNewREngine();
// PITCHER WINS --> each number represents number of wins for a single season
NumericVector pitcherWins = engine.CreateNumericVector(new double[] { 8, 21, 15, 21, 21, 22, 14 });
engine.SetSymbol("pitcherWins", pitcherWins);
// PITCHER LOSSES --> each number represents number of losses for a single season
NumericVector pitcherLosses = engine.CreateNumericVector(new double[] { 5, 10, 12, 14, 17, 14, 19 });
engine.SetSymbol("pitcherLosses", pitcherLosses);
// WINNING PERCENTAGE --> calculate the winning percentage for each single season
NumericVector winningPercentage = engine.Evaluate("winningPercentage <- 100 * pitcherWins / (pitcherWins + pitcherLosses)").AsNumeric();
}
public static List <double> GetLinearRegression(REngine engine, double[] xdata, double[] ydata)
{
if (engine == null)
{
throw new Exception("REngine not instantiated.");
}
double a = 0, b = 0, c = 0;
if (xdata.Length > 1 && xdata.Length == ydata.Length)
{
NumericVector group1 = engine.CreateNumericVector(xdata);
NumericVector group2 = engine.CreateNumericVector(ydata);
engine.SetSymbol("group1", group1);
engine.SetSymbol("group2", group2);
GenericVector t;
t = engine.Evaluate("lm.r <- lm (group2 ~ group1)").AsList();
t = engine.Evaluate("coef(summary(lm.r))").AsList();
NumericVector r0 = t[0].AsNumeric(); //intercept estimate
NumericVector r1 = t[1].AsNumeric(); //slope estimate
NumericVector r2 = t[2].AsNumeric(); //intercept se
NumericVector r3 = t[3].AsNumeric(); //slope se
NumericVector r4 = t[4].AsNumeric(); //intercept tvalue
NumericVector r5 = t[5].AsNumeric(); //slope t value
NumericVector r6 = t[6].AsNumeric(); //intercept P>t
NumericVector r7 = t[7].AsNumeric(); //slope P>t
a = r1.First();
b = r3.First();
c = r0.First() + xdata[0] * r1.First();
}
List <double> ld = new List <double> {
};
ld.Add(a);
ld.Add(b);
ld.Add(c);
return(ld);
}
protected override double calculateComposite(double[][] objValues)
{
for (int i = 0; i < VariableNames.Length; i++)
{
rEngine.SetSymbol(VariableNames[i], rEngine.CreateNumericVector(objValues[i]));
}
Log.InfoFormat("Objective expression: {0}", ObjectiveExpression);
return(rEngine.Evaluate(ObjectiveExpression).AsNumeric()[0]);
}
private void BtR_OnClick(object sender, RoutedEventArgs e)
{
if (Open)
{
try
{
REngine.SetEnvironmentVariables();
REngine engine = REngine.GetInstance();
engine.Initialize();
engine.SetSymbol("x", engine.CreateNumericVector(X));
engine.SetSymbol("y", engine.CreateNumericVector(Y));
engine.Evaluate("plot(x, y, type = 'l', main = 'Дискретный вариационный ряд')");
}
catch
{
MessageBox.Show("RGUI.exe не найден!", "Ошибка");
}
}
}
public void Run()
{
if (_targetInstrumentName == null ||
_matchInstrumentName == null ||
_targetSampleList == null ||
_matchSampleList == null)
{
throw new ArgumentNullException("参数未设置");
}
engine.SetSymbol("target", engine.CreateCharacter(_targetInstrumentName));
engine.SetSymbol("match", engine.CreateCharacter(_matchInstrumentName));
engine.SetSymbol("filename", engine.CreateCharacter(_imagePath));
engine.SetSymbol("检测系统A结果", engine.CreateNumericVector(_targetSampleList));
engine.SetSymbol("检测系统B结果", engine.CreateNumericVector(_matchSampleList));
engine.Evaluate("source('" + _scriptPath + "')");
}
private async Task <TTestGroupsDTO> CreateGroupsForTTest(BusinessKey businessKey)
{
var rawData = await _oppeDBService.GetRawDataFactList(businessKey);
if (!rawData.Any())
{
return(null);
}
var grp1 = Array.ConvertAll(rawData.Where(r => r.Name == "Peers").Select(r => r.Value).ToArray(), x => (double)x);
var grp2 = Array.ConvertAll(rawData.Where(r => r.Name != "Peers").Select(r => r.Value).ToArray(), x => (double)x);
var tTestGroupsDto = new TTestGroupsDTO
{
Group1 = _engine.CreateNumericVector(grp1),
Group2 = _engine.CreateNumericVector(grp2)
};
return(tTestGroupsDto);
}
public static void Start(REngine engine)
{
Console.WriteLine("\n\nExporting Objects\n\n");
string RCodeString = string.Empty;
//R character vector -- R.NET RDotNet.RDotNet.CharacterVector
Console.WriteLine("\nR character vector\n");
string[] myStringArray = new string[] { "PIDataLink", "PIProcessBook", "PIWebParts" };
CharacterVector myCharacterVector = engine.CreateCharacterVector(myStringArray.AsEnumerable());
engine.SetSymbol("mycharvector", myCharacterVector);
engine.Evaluate("print(mycharvector)");
//R integer vector -- R.NET RDotNet.NumericVector
Console.WriteLine("\nR int vector\n");
int[] myIntegerArray = new int[] { 4, 6, 10, 140, 54, 25 };
IntegerVector myIntegerVector = engine.CreateIntegerVector(myIntegerArray);
engine.SetSymbol("myintvector", myIntegerVector);
engine.Evaluate("print(myintvector)");
//R real vector -- R.NET RDotNet.NumericVector
Console.WriteLine("\nR real vector\n");
NumericVector myNumericVector = engine.CreateNumericVector(new double[] { 30.02, 29.99, 30.11, 29.97, 30.01, 29.99 });
engine.SetSymbol("mynumvector", myNumericVector);
engine.Evaluate("print(mynumvector)");
//R complex vector -- R.NET RDotNet.ComplexVector
Console.WriteLine("\nR complex vector\n");
Complex[] myComplexArray = new Complex[] { Complex.FromPolarCoordinates(10, 0.524), new Complex(12, 6), new Complex(14, 3), (Complex)12.3m, Complex.One + Complex.One };
ComplexVector myComplexVector = engine.CreateComplexVector(myComplexArray);
engine.SetSymbol("mycomplexvector", myComplexVector);
engine.Evaluate("print(mycomplexvector)");
//R raw vector -- R.NET RDotNet.RawVector
Console.WriteLine("\nR raw vector\n");
byte[] myByteArray = System.Text.Encoding.ASCII.GetBytes("u03a0");
RawVector myRawVector = engine.CreateRawVector(myByteArray);
engine.SetSymbol("myrawvector", myRawVector);
engine.Evaluate("print(myrawvector)");
//R logical vector -- R.NET RDotNet.LogicalVector
Console.WriteLine("\nR logical vector\n");
LogicalVector myLogicalVector = engine.CreateLogicalVector(new Boolean[] { true, false, false, false, true });
engine.SetSymbol("mylogicalvector", myLogicalVector);
engine.Evaluate("print(mylogicalvector)");
}
public static void Birth_of_age(this REngine engine)
{
var numVer = engine.CreateNumericVector(new double[] { 11, 30, 39, 20 });
var charVer = engine.CreateCharacterVector(new string[] { "70后", "80后", "90后", "00后" });
engine.SetSymbol("x", numVer);
engine.SetSymbol("labels", charVer);
engine.Evaluate("png(file = 'birth_of_age.jpg')");
engine.Evaluate("pie(x,labels)");
engine.Evaluate("dev.off()");
}
