// STATUS [ July 9, 2019 ] : this works
/// <summary>
/// Get list of Mlb player's Player Id, First Name, Last Name
/// </summary>
/// <param name="lastName">todo: describe lastName parameter on GetPlayerInfoForAllPlayersWithLastName</param>
/// <remarks>
/// See: 'playerInfo' section @ http://lahman.r-forge.r-project.org/doc/
/// See: https://analyticsrusers.blog/2018/05/31/leverage-r-code-within-net-environments-running-a-cvar-model-in-a-c-applications/
/// </remarks>
/// <example>
/// var playerInfoList = GetPlayerInfoForAllPlayersWithLastName("rizzo");
/// </example>
/// <returns>
/// List of LahmanPlayerInfo that includes: Lahman Id, First Name, Last Name
/// </returns>
public List <LahmanPlayerInfo> GetPlayerInfoForAllPlayersWithLastName(string lastName)
{
_h.StartMethod();
var engine = _r.CreateNewREngine();
engine.Evaluate("library(Lahman)");
CharacterVector lastNameVector = _r.CreateCharVect(engine, lastName);
engine.SetSymbol("lastNameVector", lastNameVector);
lastNameVector.Dispose();
SymbolicExpression lastEval = engine.Evaluate("playerInfo(lastNameVector)");
DataFrame dataFrame = lastEval.AsDataFrame();
var rowCount = dataFrame.RowCount;
List <LahmanPlayerInfo> playerinfoList = new List <LahmanPlayerInfo>();
for (var indexer = 0; indexer <= rowCount - 1; indexer++)
{
var playerInfo = CreateLahmanPlayerInfoInstance(dataFrame, indexer, lastName);
playerinfoList.Add(playerInfo);
}
_h.Dig(playerinfoList);
// engine.Evaluate("playerInfo(lastNameVector)");
return(playerinfoList);
}
private void button2_Click(object sender, EventArgs e)
{
string result;
string input;
REngine engine;
//init the R engine
REngine.SetEnvironmentVariables();
engine = REngine.GetInstance();
engine.Initialize();
//input
Console.WriteLine("Please enter the calculation");
input = Console.ReadLine();
//calculate
CharacterVector vector = engine.Evaluate(input).AsCharacter();
result = vector[0];
//clean up
engine.Dispose();
//output
Console.WriteLine("");
Console.WriteLine("Result: '{0}'", result);
Console.WriteLine("Press any key to exit");
Console.ReadKey();
}
private void MakePtfReport(string[] input_files, string path_out, string report_name)
{
// make sure we start in the correct directory with a clean environment
engine.Evaluate("rm(list=ls())");
engine.Evaluate("gc()");
engine.Evaluate("setwd('C:/Users/Keiran/Documents/Backtest_Source/R')");
// pass pnl files into R
CharacterVector r_input_files = engine.CreateCharacterVector(input_files);
engine.SetSymbol("filenames", r_input_files);
// output directory
CharacterVector r_path_out = engine.CreateCharacterVector(new string[] { path_out });
engine.SetSymbol("path.out", r_path_out);
// report name
CharacterVector r_filestem = engine.CreateCharacterVector(new string[] { report_name });
engine.SetSymbol("filestem", r_filestem);
// pass in dates and flags
LogicalVector r_relrtns = engine.CreateLogicalVector(new bool[] { relative_returns });
engine.SetSymbol("rel.rtns", r_relrtns);
CharacterVector r_startEndDate = engine.CreateCharacterVector(new string[] { date_start.ToShortDateString(), date_end.ToShortDateString() });
engine.SetSymbol("start.end.dates", r_startEndDate);
// 2. sanity checks
engine.Evaluate("print(rel.rtns)");
engine.Evaluate("print(start.end.dates)");
engine.Evaluate("print(filenames)");
engine.Evaluate("print(path.out)");
engine.Evaluate("print(filestem)");
// 3. run R script to make daily pnl
engine.Evaluate("source('PortfolioMakeReport.R')");
// 4. copy pdf report to output directory
string pdffile = report_name + ".pdf";
string pdffile_orig = System.IO.Path.Combine(@"C:\Temp\TeX_Tmp\", pdffile);
pdffile_dest = System.IO.Path.Combine(path_out, pdffile);
File.Copy(pdffile_orig, pdffile_dest, true);
// 5. copy daily and monthly pnl files to output directory
string daily_file = report_name + "_pnl_daily.csv";
string daily_file_orig = System.IO.Path.Combine(@"C:\Temp\TeX_Tmp\", daily_file);
string daily_file_dest = System.IO.Path.Combine(path_out, daily_file);
File.Copy(daily_file_orig, daily_file_dest, true);
string monthly_file = report_name + "_pnl_monthly.csv";
string monthly_file_orig = System.IO.Path.Combine(@"C:\Temp\TeX_Tmp\", monthly_file);
string monthly_file_dest = System.IO.Path.Combine(path_out, monthly_file);
File.Copy(monthly_file_orig, monthly_file_dest, true);
}
static void Main(string[] args)
{
string result;
string input;
REngine engine;
/* init the R engine */
REngine.SetEnvironmentVariables();
engine = REngine.GetInstance();
engine.Initialize();
/* input */
Console.WriteLine("Please enter the calculation");
input = Console.ReadLine();
/* calculate */
CharacterVector vector = engine.Evaluate(input).AsCharacter();
result = vector[0];
/* clean up */
engine.Dispose();
/* output */
Console.WriteLine("");
Console.WriteLine("Result: '{0}'", result);
Console.WriteLine("Press any key to exit");
Console.ReadKey();
}
public void Analyse(List <string> inputTweets)
{
REngine.SetEnvironmentVariables();
REngine engine = REngine.GetInstance();
try
{
inputTweets.ForEach(x => RCharVector.AddRange(x.Split(new char[] { '.' }, StringSplitOptions.RemoveEmptyEntries)));
inputTweets.ForEach(x => RCharVector.RemoveAll(y => string.IsNullOrEmpty(y.Trim())));
if (inputTweets.Count > 0)
{
engine.Evaluate("library('syuzhet')");
CharacterVector gp3 = engine.CreateCharacterVector(RCharVector);
engine.SetSymbol("grp3", gp3);
engine.Evaluate("grp3");
engine.Evaluate("g <- get_nrc_sentiment(grp3)");
engine.Evaluate("barplot(colSums(prop.table(g[, 3:8])))");
}
else
{
Console.WriteLine("No Tweets found with input data. Please change input data.");
}
}
finally
{
engine.Dispose();
}
}
private void frmSaveESFFull_Load(object sender, EventArgs e)
{
try
{
frmProgress pfrmProgress = new frmProgress();
pfrmProgress.lblStatus.Text = "Creating EVs:";
pfrmProgress.pgbProgress.Style = ProgressBarStyle.Marquee;
pfrmProgress.Show();
m_pEngine.Evaluate("sample.n <- length(sample.nb)");
m_pEngine.Evaluate("sample.listb <- nb2listw(sample.nb, style='B')");
m_pEngine.Evaluate("B <- listw2mat(sample.listb); M <- diag(sample.n) - matrix(1/sample.n, sample.n, sample.n); MBM <- M%*%B%*%M");
m_pEngine.Evaluate("eig <- eigen(MBM)");
nmEVs = m_pEngine.Evaluate("eig$vectors").AsNumericMatrix();
cvEVName = m_pEngine.Evaluate("paste('EV', 1:sample.n, sep='')").AsCharacter();
nvEValue = m_pEngine.Evaluate("eig$values").AsNumeric();
intNEVs = nmEVs.RowCount;
for (int i = 0; i < intNEVs; i++)
{
string strItemName = cvEVName[i] + " (" + Math.Round(nvEValue[i], 3).ToString() + ")";
clistFields.Items.Add(strItemName);
}
//m_pEngine.Evaluate("rm(list = ls(all = TRUE))"); //Remove all items from memory.
pfrmProgress.Close();
}
catch (Exception ex)
{
frmErrorLog pfrmErrorLog = new frmErrorLog(); pfrmErrorLog.ex = ex; pfrmErrorLog.ShowDialog();
return;
}
}
private void ClusteringMethKMean(List <int> activeVariables)
{
string clust_kmean = tmpFolder + "clust_kmean.png";
CharacterVector fileNameVector = engine.CreateCharacterVector(new[] { clust_kmean });
engine.SetSymbol("clust_kmean", fileNameVector);
engine.Evaluate("library(cluster)");
engine.Evaluate("library(ggplot2)");
string clusVar = "";
for (int k = 0; k < activeVariables.Count; k++)
{
clusVar += ((1 + activeVariables[k]).ToString()) + ",";
}
clusVar = clusVar.Substring(0, clusVar.Length - 1);
engine.Evaluate("corV <- c(" + clusVar + ")");
engine.Evaluate("kclust <- kmeans(as.matrix(dataset[, corV]), centers = 9)");
engine.Evaluate("png(filename=clust_kmean, width=6, height=6, units='in', res=100)");
engine.Evaluate("clusplot(dataset[,corV], kclust$cluster, main='K-Mean', xlab = \"\", ylab = \"Height\" , color=TRUE, shade=TRUE, labels=2, lines=0)");
engine.Evaluate("dev.off()");
worddoc.InlineShapes.AddPicture(clust_kmean, false, true, wrange);
latexText += "\n\\begin{frame}\\frametitle{K-Mean}" +
"\n \\begin{figure}" +
"\n \\centering" +
"\n \\includegraphics[scale=0.48]{clust_kmean.png}" +
"\n \\caption{K-Mean}" +
"\n \\end{figure}" +
"\n\\end{frame}";
}
// STATUS: this works
/// <summary> OPTION 3B --> Retrieve FanGraphs hitter leader board for: RANGE OF SEASON | ALL or AL or NL | players with PLATE APPEARANCES greater than defined # | display in AGGREGATE or by SEASON </summary>
/// <example> _r.GetFanGraphsHitterLeaderboard(2014, 2017, "all", 200, "aggregate"); </example>
/// <remarks>
/// See: https://billpetti.github.io/baseballr/data-acquisition-functions/
/// </remarks>
/// <param name="startYear"> The first year / season you want to get the leaders for </param>
/// <param name="endYear"> The last year / season you want to get the leaders for </param>
/// <param name="league"> You can get records for all of MLB ('all'), the National League ('nl'), or the American League ('al') </param>
/// <param name="minPlateAppearances"> Whether to include only batters that were qualified. Defaults to 'y'. Alternatively, you can pass a minimum number of plate appearances to restrict the data to. </param>
/// <param name="statDisplayType"> Whether to split the data by batter and individual season, or to simply aggregate by batter across the seasons selected. Defaults to aggregating (ind = 0). To split by season, use ind = 1 </param>
public void GetFanGraphsHitterLeaderboard(int startYear, int endYear, string league, int minPlateAppearances, string statDisplayType)
{
REngine engine = CreateNewREngine();
ImportBaseballR();
NumericVector startYearVector = CreateNumVect(engine, startYear);
NumericVector endYearVector = CreateNumVect(engine, endYear);
CharacterVector leagueVector = CreateCharVect(engine, league);
NumericVector minPlateAppearancesVector = CreateNumVect(engine, minPlateAppearances);
if (string.Equals(statDisplayType, "aggregate", StringComparison.Ordinal))
{
const int aggregateInt = 0;
NumericVector statDisplayVector = CreateNumVect(engine, aggregateInt);
engine.SetSymbol("statDisplayType", statDisplayVector);
}
if (string.Equals(statDisplayType, "season", StringComparison.Ordinal))
{
const int aggregateInt = 1;
NumericVector statDisplayVector = CreateNumVect(engine, aggregateInt);
engine.SetSymbol("statDisplayType", statDisplayVector);
}
engine.SetSymbol("startYearVector", startYearVector);
engine.SetSymbol("endYearVector", endYearVector);
engine.SetSymbol("leagueVector", leagueVector);
engine.SetSymbol("minPlateAppearancesVector", minPlateAppearancesVector);
engine.Evaluate("fgHittersLeaderBoard <- fg_bat_leaders(x = startYearVector, y = endYearVector, league = leagueVector, qual = minPlateAppearancesVector, ind = statDisplayType)");
}
//private void txtboxResults_TextChanged(object sender, EventArgs e)
//{
// if (String.IsNullOrEmpty(txtboxResults.Text))
// {
// btnClearResults.Enabled = false;
// }
// else
// {
// btnClearResults.Enabled = true;
// }
//}
private void btnSubmit_Click(object sender, EventArgs e)
{
try
{
SymbolicExpression expression = MyFunctions._engine.Evaluate(txtboxRCommands.Text.Trim());
if (expression == null)
{
return;
}
CharacterVector vector = expression.AsCharacter();
foreach (var sSubmitThis in vector)
{
//if (sSubmitThis is string)
{
Console.WriteLine(sSubmitThis);
}
}
}
catch
{
}
//catch (Exception ex)
//{
// MessageBox.Show(ex.StackTrace);
//}
}
public static List <string> CreateCharacterVar(string svarname, string svalue)
{
try
{
REngine.SetEnvironmentVariables();
REngine engine = REngine.GetInstance();
CharacterVector charVec = engine.CreateCharacter(svalue);
engine.SetSymbol(svarname, charVec);
List <string> lerrmsg = new List <string> {
"\nCreated R variable named " + svarname
};
return(lerrmsg);
}
catch (Exception e)
{
string errmsg = "\nException encountered while set R variable :" + svarname + "\n";
errmsg += "\nError message :\n" + e.Message + "\n" + e.StackTrace + "\n";
if (e.InnerException != null)
{
errmsg += "InnerException\n" + e.InnerException.Message + "\n" + e.InnerException.StackTrace + "\n";
}
List <string> lerrmsg = new List <string> {
errmsg
};
return(lerrmsg);
}
}
private List <string> groupSeparation(CharacterVector colNames, List <string> group1, List <string> group2)
{
List <string> result = new List <string>();
for (int i = 0; i < group1.Count; ++i)
{
group1[i] = group1[i].Replace('-', '.');
}
for (int i = 0; i < group2.Count; ++i)
{
group2[i] = group2[i].Replace('-', '.');
}
foreach (var name in colNames)
{
//Console.WriteLine(name);
if (group1.Contains(name.ToString()))
{
result.Add("G1");
}
else
{
result.Add("G2");
}
}
return(result);
}
//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)");
}
internal void RequireLibrary(string libraryName)
{
CharacterVector package = engine.CreateCharacter(libraryName);
engine.SetSymbol("package", package);
engine.Evaluate("if(libName %in% rownames(installed.packages())) do.call('library', list(package)) else { install.packages(package) do.call('library', list(package))");
}
public async Task <IActionResult> Get()
{
//_rEngine.Evaluate("install.packages('forecast', dependencies = TRUE)");
//_rEngine.Evaluate("install.packages('lmtest', dependencies = TRUE)");
_rEngine.Evaluate("library(forecast)");
_rEngine.Evaluate("library(lmtest)");
string fileName = "myplot.png";
CharacterVector fileNameVector = _rEngine.CreateCharacterVector(new[] { fileName });
_rEngine.SetSymbol("fileName", fileNameVector);
_rEngine.Evaluate("png(filename=fileName, width=6, height=6, units='in', res=100)");
_rEngine.Evaluate("vector <- as.numeric(AirPassengers)");
_rEngine.Evaluate("z <- ts(vector, frequency = 12, start = c(1949, 1))");
_rEngine.Evaluate("z_train <- ts(z[1:100], frequency = 12)");
_rEngine.Evaluate("z_validate <- ts(z[101:144], frequency = 12)");
_rEngine.Evaluate("fit <- Arima(y = z_train, order = c(1,1,0), seasonal = c(1,1,0), lambda = TRUE)");
_rEngine.Evaluate("predition <- forecast(fit, h = 44)");
//_rEngine.Evaluate("z_train <- ts(z[1:100], frequency = 12");
_rEngine.Evaluate("plot(predition)"); //plot and save file
//_rEngine.Evaluate("lines(fit$fitted, col = 'blue')");
_rEngine.Evaluate("dev.off()");
Byte[] b = System.IO.File.ReadAllBytes(@"C:\Users\admin\source\repos\DataAnalisysApi\DataAnalisysApi\myplot.png"); // You can use your own method over here.
return(File(b, "image/jpeg"));
}
static void Main(string[] args)
{
//intializing
setPath();
loadData();
using (REngine rengine = REngine.GetInstance())
{
rengine.Initialize();
//Importing libraries
rengine.Evaluate("library(ggplot2)");
rengine.Evaluate("library(ggthemes)");
rengine.Evaluate("library(dplyr)");
//Creating the dataframe
rengine.Evaluate("df <- setNames(data.frame(matrix(ncol=2, nrow=0)), c(\"year\",\"userCount\"))").AsDataFrame();
//Storing data from the class object into the dataframe
for (int i = 0; i < holder.year.Count; i++)
{
rengine.Evaluate("df[nrow(df)+1,] <- c(" + holder.year[i] + ", " + holder.userCount[i] + ")");
}
//Creating the time series chart
rengine.Evaluate("chart <- df %>% ggplot(aes(x=year, y=userCount)) + geom_smooth(size=2, aes(colour=\"red\", fill=\"black\"), show.legend=FALSE) + labs(x=\"Year\",y=\"User Count\") + theme_classic()");
//Saving the graph to a png file
string fileName = "C:/Users/{insert username here}/Desktop/plot0.png";
CharacterVector fileVector = rengine.CreateCharacterVector(new[] { fileName });
rengine.SetSymbol("fileName", fileVector);
rengine.Evaluate("png(filename=fileName, width=6, height=6, units='in',res=100)");
rengine.Evaluate("print(chart)");
//Cleaning up
rengine.Evaluate("dev.off()");
rengine.Dispose();
}
}
private void btnSubmit_Click(object sender, EventArgs e)
{
tabControl1.SelectedIndex = 1; // Sets focus to the log tab
try
{
SymbolicExpression expression = MyFunctions._engine.Evaluate(tbCode.Text.Trim());
if (expression == null)
{
return;
}
CharacterVector vector = expression.AsCharacter();
foreach (var sSubmitThis in vector)
{
{
Console.WriteLine(sSubmitThis);
tabControl1.SelectedIndex = 1;
}
}
}
catch (Exception ex)
{
Console.WriteLine("Problem running your R program: " + ex.Message);
}
}
public void Initialize(string[] tickers, string startDate)
{
CharacterVector tickerVector = _engine.CreateCharacterVector(tickers);
CharacterVector dateVector = _engine.CreateCharacterVector(new[] { startDate });
var appendedTickers = tickers.Select(ticker => $"NASDAQ:{ticker}").ToArray();
CharacterVector nasdaqCharacterVector = _engine.CreateCharacterVector(appendedTickers);
_engine.SetSymbol("nasdaqCharacterVector", nasdaqCharacterVector);
_engine.Evaluate("tickers.temp = spl(nasdaqCharacterVector)");
_engine.SetSymbol("dateVector", dateVector);
_engine.SetSymbol("tickerVector", tickerVector);
_engine.Evaluate("tickers = spl(tickerVector)");
_engine.Evaluate("data.fund <- new.env()");
_engine.Evaluate(
"for (i in 1:len(tickers)) {data.fund[[tickers[i]]] = fund.data(tickers.temp[i], 80, 'annual')};");
_engine.Evaluate("data <- new.env()");
_engine.Evaluate("getSymbols(tickers, src = 'yahoo', from = '1970-01-01', env = data, auto.assign = T)");
_engine.Evaluate("for (i in ls(data)) {data[[i]] = adjustOHLC(data[[i]], use.Adjusted = T)};");
_engine.Evaluate("portfolioPrices <- NULL");
_engine.Evaluate("for (Ticker in tickers) {" +
$"portfolioPrices <- cbind(portfolioPrices, getSymbols.yahoo(Ticker, from={startDate}, periodicity = \"daily\", auto.assign=FALSE)[,3])" +
"}");
}
public void test_NextItem_P(int numofItems, ModelNames.Models paramModel, ModelNames.CriterionTypes paramCriterion)
{
resultFlag = true;
REngine.SetEnvironmentVariables();
REngine engineObj = REngine.GetInstance();
// Loading a library from R
engineObj.Evaluate("library(catR)");
// Polytomous Items
CharacterVector modelName = engineObj.CreateCharacterVector(new string[] { paramModel.EnumToString() });
engineObj.SetSymbol("modelName", modelName);
DataFrame PolyItems = engineObj.Evaluate("PolyItems <- genPolyMatrix(" + numofItems + ", 5, model = modelName, same.nrCat = TRUE)").AsDataFrame();
engineObj.SetSymbol("PolyItems", PolyItems);
// Adapting with the existing "CAT-Items" type (Wrapper)
Console.WriteLine("*******************************************");
Console.WriteLine("Polytomous Items, Model : " + paramModel.EnumToString());
Console.WriteLine("*******************************************");
CATItems itemBank = new CATItems(PolyItems[0].Length, paramModel.EnumToString(), 5);
Tuple <CATItems.ColumnNames, int>[] cols = itemBank.GetKeys();
for (int i = 0; i < cols.Length; i++)
{
itemBank.SetItemParamter(cols[i], PolyItems[i].Select(y => (double)y).ToArray());
}
// Call "NextItem" function from R
GenericVector r_NextItem = engineObj.Evaluate("r_NextItem <- nextItem(PolyItems, model = modelName, theta = 0, criterion = \"" + paramCriterion.ToString() + "\")").AsList();
// Selected item
NumericVector item = r_NextItem[0].AsNumeric();
DataFrame par = r_NextItem[1].AsDataFrame();
// Value of "info"
NumericVector thStart = r_NextItem[2].AsNumeric();
// Criterion
CharacterVector startSelect = r_NextItem[3].AsCharacter();
// Call "NextItem" function from CS
NextItemModel cs_NextItem = CatRLib.NextItem(itemBank, model: paramModel.EnumToString(), theta: 0, criterion: (int)paramCriterion);
//Test passed for "MFI"
if (item[0] != cs_NextItem.item)
{
resultFlag = false;
}
Assert.IsTrue(resultFlag);
}
public TSAnalyze ()
{
InitializeComponent ();
// There are several options to initialize thengine, but by default the following suffice:
REngine engine = REngine.GetInstance();
//init the R engine
REngine.SetEnvironmentVariables ();
engine = REngine.GetInstance ();
engine.Initialize ();
//prepare data
List<int> size = new List<int>() { 29, 33, 51, 110, 357, 45, 338, 543, 132, 70, 103, 301, 146, 10, 56, 243, 238 };
List<int> population = new List<int>() { 3162, 11142, 3834, 7305, 81890, 1339, 5414, 65697, 11280, 4589, 320, 60918, 480, 1806, 4267, 63228, 21327 };
var docPath = Directory.GetCurrentDirectory();
//var myDir = $@"{docPath}\output";
var myDir = bingPathToAppDir ("output");
Directory.CreateDirectory (myDir);
Console.WriteLine (Directory.Exists (myDir));
Console.WriteLine (myDir);
Console.WriteLine (bingPathToAppDir ("output"));
Console.WriteLine ("my image location {0}", myDir);
fileName = myDir + "\\myplot.png";
//calculate
IntegerVector sizeVector = engine.CreateIntegerVector(size);
engine.SetSymbol ("size", sizeVector);
IntegerVector populationVector = engine.CreateIntegerVector(population);
engine.SetSymbol ("population", populationVector);
CharacterVector fileNameVector = engine.CreateCharacterVector(new[] { fileName });
engine.SetSymbol ("fileName", fileNameVector);
engine.Evaluate ("reg <- lm(population~size)");
engine.Evaluate ("png(filename=fileName, width=6, height=6, units='in', res=100)");
engine.Evaluate ("plot(population~size)");
engine.Evaluate ("abline(reg)");
engine.Evaluate ("dev.off()");
//clean up
engine.Dispose ();
//output
Console.WriteLine ("");
Console.WriteLine ("Press any key to exit");
Console.ReadKey ();
}
// GET api/values/5
public string Get(int id)
{
REngine engine = REngine.GetInstance();
CharacterVector charVec = engine.CreateCharacterVector(new[] { "Hello world" });
engine.SetSymbol("greetings", charVec);
engine.Evaluate("str(greetings)");
string[] a = engine.Evaluate("'Hi there .NET, from the R engine'").AsCharacter().ToArray();
return(a[0]);
}
public void RTest()
{
// 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");
}
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)");
}
// STATUS: this works
/// <summary> Search the Chadwich Bureau Register for a mlb player based on their last name </summary>
/// <remarks>
/// See: https://billpetti.github.io/baseballr/data-acquisition-functions/
/// </remarks>
/// <example> _r.SearchForPlayer("Seager"); </example>
/// <param name="lastName"> Mlb player's last name </param>
/// <returns> first_name, last_name, given_name, name_suffix, nick_name, birth_year, mlb_played_first, mlbam_id, retrosheet_id, retrosheet_id, bbref_id, fangraphs_id </returns>
public void SearchForPlayer(string lastName)
{
REngine engine = CreateNewREngine();
ImportBaseballR();
CharacterVector cvLastName = CreateCharVect(engine, lastName);
engine.SetSymbol("lastName", cvLastName);
engine.Evaluate("player <- playerid_lookup(lastName)");
}
private void a_calistir_Click(object sender, EventArgs e)
{
SayfaAdi = sayfaAdiBox.Text;
if (!check(DosyaYolu) && !check(SayfaAdi))
{
yukleme.Visible = true;
new Thread(() =>
{
//calculate
asso_cikis = a_cikissayfasi.Text;
asso_sutun = Convert.ToInt32(a_sutun.Value);
asso_satir = Convert.ToInt32(a_satir.Value);
asso_harici = Convert.ToInt32(a_haricietken.Value);
DosyaYolu = DosyaYolu.Replace(@"\", "/");
string akod = "using <- function(...) {libs <- unlist(list(...));req <- unlist(lapply(libs,require,character.only=TRUE));need <- libs[req==FALSE];if(length(need)>0){;install.packages(need);lapply(need,require,character.only=TRUE);};};using('forecast', 'openxlsx');Sales <- read.xlsx('" + DosyaYolu + "',sheet='" + SayfaAdi + "');wb <- loadWorkbook('" + DosyaYolu + "');counter <- 1;rowindex <- " + asso_satir + "; colindex <- " + asso_sutun + "; m <- " + asso_harici + "/100; maxid <- length(Sales[,1]);n <- Sales[,1];tSales <- as.data.frame(t(Sales[,-1]));colnames(tSales) <- n;tSales$myfactor <- factor(row.names(tSales));tSales$myfactor <- NULL;tsSales <- ts(tSales);forecastop <- tryCatch({;while(counter <= maxid){;forecast <- as.data.frame(thetaf(tsSales[,counter],level=80,h=1));fc <- forecast[,1];fc[fc < 0] <- 0;fc <- fc+fc*m;forecastvalues <- round(fc,0);writeData(wb,sheet='" + asso_cikis + "',forecastvalues,startRow=rowindex,startCol = colindex);counter <- counter+1;rowindex <- rowindex+1;};print('Forecast values for assortment are generated. Now writing data to Excel file.');},error = function(e){print('Error. Problem in the R code. Check the error message:');stop(e);},warning = function(w){print('Warning. There may be a problem within the data. Check the warning message:');stop(w);});writingop <- tryCatch({saveWorkbook(wb, '" + DosyaYolu + "', overwrite = TRUE);print('Done');},error = function(e){;print('Error. Please check the error message:');stop(e);},warning = function(w){;stop('Access denied. Make sure that the Excel file is closed and not protected.');});openXL('" + DosyaYolu + "');print('Done')";
try
{
CharacterVector vector = engine.Evaluate(akod).AsCharacter();
result = vector[0];
if (result == "Done")
{
MessageBox.Show("İşlem başarıyla tamamlandı");
}
else
{
MessageBox.Show(result);
}
}
catch (RDotNet.EvaluationException a)
{
MessageBox.Show(" " + a);
}
yukleme.Visible = false;
//clean up
//engine.Dispose();
}).Start();
}
else
{
MessageBox.Show("Dosya yolu veya sayfa adı girilmedi !" + check(DosyaYolu) + " - " + check(SayfaAdi));
}
}
// moved to LahmanPlayerInfoController
// STATUS: this works
// <summary> Get Mlb player's Player Id, First Name, Last Name</summary>
// <reference> http://lahman.r-forge.r-project.org/doc/ </reference>
// public void GetLahmanPlayerInfo(string lastName)
// {
// // for testing
// // string mookieBettsId = "bettsmo01";
// REngine engine = CreateNewREngine();
// engine.Evaluate("library(Lahman)");
// CharacterVector lastNameVector = CreateCharVect(engine, lastName);
// engine.SetSymbol("lastNameVector", lastNameVector);
// // CharacterVector playerIdVector = CreateCharVect(engine, mookieBettsId);
// // engine.SetSymbol("playerIdVector", playerIdVector);
// engine.Evaluate("playerInfo(lastNameVector)");
// }
public void GetLahmanTeamInfo(string lastName)
{
REngine engine = CreateNewREngine();
engine.Evaluate("library(Lahman)");
CharacterVector lastNameVector = CreateCharVect(engine, lastName);
engine.SetSymbol("lastNameVector", lastNameVector);
engine.Evaluate("teamInfo('CH', extra='park')");
// engine.Evaluate("playerInfo(lastNameVector)");
}
/// <summary>
/// Executes the function. Match the function arguments by name.
/// </summary>
/// <param name="argNames">The names of the arguments. These can be empty strings for unnamed function arguments</param>
/// <param name="args">The arguments passed to the function</param>
/// <returns></returns>
protected SymbolicExpression InvokeViaPairlist(string[] argNames, SymbolicExpression[] args)
{
var names = new CharacterVector(Engine, argNames);
var arguments = new GenericVector(Engine, args);
arguments.SetNames(names);
var argPairList = arguments.ToPairlist();
//IntPtr newEnvironment = Engine.GetFunction<Rf_allocSExp>()(SymbolicExpressionType.Environment);
//IntPtr result = Engine.GetFunction<Rf_applyClosure>()(Body.DangerousGetHandle(), handle,
// argPairList.DangerousGetHandle(),
// Environment.DangerousGetHandle(), newEnvironment);
return createCallAndEvaluate(argPairList.DangerousGetHandle());
}
public string run_ruvseq(List <string> group1, List <string> group2)
{
try
{
engine = REngine.GetInstance();
engine.Initialize();
engine.Evaluate(string.Format("Sys.setenv(PATH = paste('{0}', ';', Sys.getenv('PATH'), sep=''))", this.rPath));
engine.Evaluate("Sys.getenv()");
engine.Evaluate("library('RUVSeq')");
engine.Evaluate("library('DESeq2')");
engine.Evaluate("library('RColorBrewer')");
engine.Evaluate("matrix <- read.table('" + inputFile + "', header=TRUE, sep=',', fill=TRUE, row.names=1)");
engine.Evaluate("matrix <- matrix + 1;" +
"matrix <- round(matrix, 0);" +
"filter <- apply(matrix, 1, function(x) length(x[x > 5]) >= 2);" +
"filtered <- matrix[filter,];" +
"genes <- rownames(filtered)[grep('^ENS', rownames(filtered))];" +
"spikes <- rownames(filtered)[grep('^ERCC', rownames(filtered))];");
CharacterVector colnames = engine.Evaluate("colnames(filtered)").AsCharacter();
var x = engine.CreateCharacterVector(this.groupSeparation(colnames, group1, group2));
engine.SetSymbol("x", x);
engine.Evaluate("print(x)");
engine.Evaluate("print(colnames(filtered))");
engine.Evaluate("colors <- brewer.pal(4, 'Set1');" +
"set <- newSeqExpressionSet(as.matrix(filtered), phenoData = data.frame(x, row.names=colnames(filtered)));" +
"set <- betweenLaneNormalization(set, which='upper');" +
"set1 <- RUVg(set, spikes, k=1);" +
"write.csv(normCounts(set1), paste('" + outputFileDirectory + "\\\\" + outputFile + "','_normalizedCounts.csv', sep=''));" +
"write.csv(counts(set1), paste('" + outputFileDirectory + "\\\\" + outputFile + "', '_counts.csv', sep = ''));" +
"write.csv(pData(set1), paste('" + outputFileDirectory + "\\\\" + outputFile + "','_colData.csv', sep = ''));");
engine.Evaluate(@"png(file = paste('" + outputFileDirectory + "\\\\" + outputFile + "','_graphRLE_RUV.png', sep = ''), height = 720, width = 1280);" +
"plotRLE(set1, outline = FALSE, ylim = c(-4, 4), col = colors[x], xaxt = 'n', ann = FALSE);" +
"text(x = seq(1, length(colnames(filtered))) - .2, par('usr')[3] - .4, labels = colnames(filtered), adj = c(1.5, 1.5), srt = 60, pos = 1, xpd = TRUE, cex = 1);" +
"axis(1, at = seq(1, length(colnames(filtered)), by = 1), labels = FALSE);" +
"dev.off();");
engine.Evaluate("png(file = paste('" + outputFileDirectory + "\\\\" + outputFile + "', '_graphPCA_RUV.png', sep = '), height = 720, width = 1280);" +
"plotPCA(set1, col = colors[x], cex = 1.2);" +
"dev.off();");
return("Success");
}
catch (RDotNet.EvaluationException e)
{
return(e.ToString());
}
finally
{
engine.Evaluate("rm(list = ls())");
engine.Evaluate(@"detach(); detach(); detach();");
}
}
private float CalculateLeveneValue(LeveneTestDTO leveneTestDTO)
{
CharacterVector namesV = leveneTestDTO.Names;
NumericVector valuesV = leveneTestDTO.Values;
_engine.Evaluate("library(car)");
_engine.SetSymbol("namesV", namesV);
_engine.SetSymbol("valuesV", valuesV);
GenericVector testResult = _engine.Evaluate("levene.test(valuesV, namesV, center=mean)").AsList();
float p = (float)testResult[2].AsNumeric().First();
return(p);
}
// TO-DO: continue working through available functions within the PitchRx package
#region PITCH RX ------------------------------------------------------------
// STATUS: this works to a point, returns a lot of stuff but then breaks; seems to be an issue with some of the data being returned
// TO-DO: test this with more dates to figure out why it breaks; figure out of if there are more things returned if it doesnt' break
/// <summary> Scrapes and returns a significant amount of data about each individual at bat within a given date range </summary>
/// <example> _r.GetPitchRxData("2013-06-01", "2013-06-01"); </example>
/// <param name="startDate"> First date of the range you are looking for (e.g, "2016-04-06") </param>
/// <param name="endDate"> Last date of the range you are looking for (e.g, "2016-06-21") </param>
/// <returns>
/// <list>
/// <item> AT BAT: pitcher (id), batter (id), num (pitch number?), b, s, o, start_tfs, start_tfs_zulu, stand, b_height, p_throws, atbat_des, home_team_runs, away_team_runs, url (for XML), inning_side(top OR bottom), inning, next_, event2, batter_name, pitcher_name, gameday_link, date </item>
/// <item> ACTION: b, s, o, des, event, tfs_zulu, player (id), pitch (number), event_num, home_team_runs, away_team_runs, url (for XML), inning_side (top OR bottom), inning, next_, num, score, event2, gameday_link </item>
/// <item> PITCH: des, id, type (B, S, X), tfs, tfs_zulu, x, y, event_num, sv_id, play_guid, start_speed, end_speed, sz_top, sz_top, pfx_x, pfx_z, px, pz, x0, y0, z0, vx0, vy0, vz0, ax, ay, az, break_y </item>
/// </list>
/// </returns>
/// <reference> https://pitchrx.cpsievert.me </reference>
public void GetPitchRxData(string startDate, string endDate)
{
REngine engine = CreateNewREngine();
ImportPitchRx();
CharacterVector startDateVector = CreateCharVect(engine, startDate);
CharacterVector endDateVector = CreateCharVect(engine, endDate);
engine.SetSymbol("startDateVector", startDateVector);
engine.SetSymbol("endDateVector", endDateVector);
engine.Evaluate("dat <- scrape(start = startDateVector, end = endDateVector)");
}
// STATUS: this works
/// <summary>
/// OPTION 1A --> Retrieve FanGraphs hitter leader board for: SINGLE SEASON | ALL MLB | QUALIFIED or UNQUALIFIED
/// </summary>
/// <remarks>
/// See: https://billpetti.github.io/baseballr/data-acquisition-functions/
/// </remarks>
/// <example> _r.GetFanGraphsHitterLeaderboard(2017, "y");
/// </example>
/// <param name="year">
/// The year of the season you want to get the leaders for
/// </param>
/// <param name="qual">
/// Whether to include only batters that were qualified. Defaults to 'y'. Alternatively, you can pass a minimum number of plate appearances to restrict the data to.
/// </param>
public void GetFanGraphsHitterLeaderboard(int year, string qual)
{
REngine engine = CreateNewREngine();
ImportBaseballR();
NumericVector yearVector = CreateNumVect(engine, year);
CharacterVector qualifyingVector = CreateCharVect(engine, qual);
engine.SetSymbol("yearVector", yearVector);
engine.SetSymbol("qualifyingVector", qualifyingVector);
engine.Evaluate("fgHittersLeaderBoard <- fg_bat_leaders(x = yearVector, y = yearVector, league = 'all', qual = qualifyingVector, ind = 0)");
}
private void button1_Click(object sender, EventArgs e)
{
REngine.SetEnvironmentVariables(); // <-- 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");
engine.Dispose();
}
/// <summary>
/// Gets the symbol names defined in this environment.
/// </summary>
/// <param name="all">Including special functions or not.</param>
/// <returns>Symbol names.</returns>
public string[] GetSymbolNames(bool all = false)
{
var symbolNames = new CharacterVector(Engine, this.GetFunction<R_lsInternal>()(handle, all));
int length = symbolNames.Length;
var copy = new string[length];
symbolNames.CopyTo(copy, length);
return copy;
}
public PlotWindowViewModel(REngine engine)
{
_engine = engine;
_response = _engine.Evaluate("require(quantmod)").AsCharacter(); // load quantmod
}
