no need to generate random IO params: migrate in test. Add roxygen2 NAMESPACE-generat...

[valse.git] / test / generate_test_data / helper.R

diff --git a/pkg/R/generateSampleInputs.R b/test/generate_test_data/helper.R
similarity index 63%
rename from pkg/R/generateSampleInputs.R
rename to test/generate_test_data/helper.R
index c7aa3c6..49cd1b5 100644 (file)
--- a/pkg/R/generateSampleInputs.R
+++ b/test/generate_test_data/helper.R
@@ -1,34 +1,3 @@
-#' Generate a sample of (X,Y) of size n
-#' @param meanX matrix of group means for covariates (of size p)
-#' @param covX covariance for covariates (of size p*p)
-#' @param covY covariance for the response vector (of size m*m*K)
-#' @param pi    proportion for each cluster
-#' @param beta regression matrix, of size p*m*k
-#' @param n            sample size
-#'
-#' @return list with X and Y
-#' @export
-generateXY = function(meanX, covX, covY, pi, beta, n)
-{
-       p = dim(covX)[1]
-       m = dim(covY)[1]
-       k = dim(covY)[3]
-       
-       X = matrix(nrow=n,ncol=p)
-       Y = matrix(nrow=n,ncol=m)
-       class = matrix(nrow = n)
-       
-       require(MASS) #simulate from a multivariate normal distribution
-       for (i in 1:n)
-       {
-               class[i] = sample(1:k, 1, prob=pi)
-               X[i,] = mvrnorm(1, meanX, covX)
-               Y[i,] = mvrnorm(1, X[i,] %*% beta[,,class[i]], covY[,,class[i]])
-       }
-       
-       return (list(X=X,Y=Y, class = class))
-}
-
 #' Generate a sample of (X,Y) of size n with default values
 #' @param n sample size
 #' @param p number of covariates
@@ -42,9 +11,7 @@ generateXYdefault = function(n, p, m, k)
        covX = diag(p)
        covY = array(dim=c(m,m,k))
        for(r in 1:k)
-       {
                covY[,,r] = diag(m)
-       }
        pi = rep(1./k,k)
        #initialize beta to a random number of non-zero random value
        beta = array(0, dim=c(p,m,k))