X-Git-Url: https://git.auder.net/?p=valse.git;a=blobdiff_plain;f=pkg%2FR%2FgenerateXY.R;h=064b54b2d083bb3bc9d9ddd26a8654962e5b93c2;hp=fe86045b1f08d3d21cf3161474d6992909b9f1de;hb=1b698c1619dbcf5b3a0608dc894d249945d2bce3;hpb=f7e157cdbcf2d60224c2d6773da9c698174e9aee

diff --git a/pkg/R/generateXY.R b/pkg/R/generateXY.R
index fe86045..064b54b 100644
--- a/pkg/R/generateXY.R
+++ b/pkg/R/generateXY.R
@@ -17,14 +17,14 @@ generateXY <- function(n, π, meanX, β, covX, covY)
   p <- dim(covX)[1]
   m <- dim(covY)[1]
   k <- dim(covY)[3]
-  
+
   X <- matrix(nrow = 0, ncol = p)
   Y <- matrix(nrow = 0, ncol = m)
-  
+
   # random generation of the size of each population in X~Y (unordered)
   sizePop <- rmultinom(1, n, π)
-  class <- c()  #map i in 1:n --> index of class in 1:k
-  
+  class <- c() #map i in 1:n --> index of class in 1:k
+
   for (i in 1:k)
   {
     class <- c(class, rep(i, sizePop[i]))
@@ -33,7 +33,7 @@ generateXY <- function(n, π, meanX, β, covX, covY)
     Y <- rbind(Y, t(apply(newBlockX, 1, function(row) MASS::mvrnorm(1, row %*% 
       β[, , i], covY[, , i]))))
   }
-  
+
   shuffle <- sample(n)
   list(X = X[shuffle, ], Y = Y[shuffle, ], class = class[shuffle])
 }