public void test_MWI_D(int NumOfItems)
{
resultFlag = true;
REngine.SetEnvironmentVariables();
REngine engineObj = REngine.GetInstance();
// Loading a library from R
engineObj.Evaluate("library(catR)");
// Dichotomous Items
DataFrame DichoItems = engineObj.Evaluate("DichoItems <- genDichoMatrix(items = " + NumOfItems + ")").AsDataFrame();
engineObj.SetSymbol("DichoItems", DichoItems);
// Adapting with the existing "CAT-Items" type (Wrapper)
CATItems itemBank = new CATItems(DichoItems[0].Length, false);
// New Dictionary
itemBank.SetItemParamter(CATItems.ColumnNames.a, DichoItems[0].Select(y => (double)y).ToArray());
itemBank.SetItemParamter(CATItems.ColumnNames.b, DichoItems[1].Select(y => (double)y).ToArray());
itemBank.SetItemParamter(CATItems.ColumnNames.c, DichoItems[2].Select(y => (double)y).ToArray());
itemBank.SetItemParamter(CATItems.ColumnNames.d, DichoItems[3].Select(y => (double)y).ToArray());
// Dichotomous Items
DataFrame it_given_R = engineObj.Evaluate("it_given_R <- DichoItems[c(4, 8),]").AsDataFrame();
engineObj.SetSymbol("it_given_R", it_given_R);
//Creation of a response pattern for theta value
engineObj.Evaluate("set.seed(1)");
NumericVector x_val = engineObj.Evaluate("x_val <- genPattern(0, it_given_R)").AsNumeric();
engineObj.SetSymbol("x_val", x_val);
int[] x = x_val.Select(y => (int)y).ToArray();
CATItems it_given = itemBank.FindItem(new int[] { 4, 8 });
// Call "MWI" function from R
NumericVector r_mwi = engineObj.Evaluate("r_mei <- MWI(DichoItems, 1, x_val, it_given_R, type = \"MPWI\")").AsNumeric();
// Call "MWI" function from CatRCS
double cs_mwi = CatRLib.MWI(itemBank, 1, x, it_given, "", 2);
if (r_mwi[0] - cs_mwi > testEpsilon)
{
resultFlag = false;
}
Assert.IsTrue(resultFlag);
}
public void test_MWI_P(int NumOfItems, ModelNames.Models paramModel)
{
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());
}
// Dichotomous Items
DataFrame it_given_R = engineObj.Evaluate("it_given_R <- DichoItems[c(4, 8),]").AsDataFrame();
engineObj.SetSymbol("it_given_R", it_given_R);
//Creation of a response pattern for theta value
engineObj.Evaluate("set.seed(1)");
NumericVector x_val = engineObj.Evaluate("x_val <- genPattern(0, it_given_R)").AsNumeric();
engineObj.SetSymbol("x_val", x_val);
int[] x = x_val.Select(y => (int)y).ToArray();
CATItems it_given = itemBank.FindItem(new int[] { 4, 8 });
// Call "MWI" function from R
NumericVector r_mwi = engineObj.Evaluate("r_mei <- MWI(DichoItems, 1, x_val, it_given_R, type = \"MPWI\")").AsNumeric();
// Call "MWI" function from CatRCS
double cs_mwi = CatRLib.MWI(itemBank, 1, x, it_given, "", 2);
if (r_mwi[0] - cs_mwi > testEpsilon)
{
resultFlag = false;
}
Assert.IsTrue(resultFlag);
}
