prepare EMGLLF / EMGrank wrappers, simplify folder generateTestData

[valse.git] / R / initSmallEM.R

diff --git a/R/initSmallEM.R b/R/initSmallEM.R
index d519766..e2157b2 100644 (file)
--- a/R/initSmallEM.R
+++ b/R/initSmallEM.R
@@ -1,31 +1,24 @@
-vec_bin = function(X,r)
-{
-       Z = c()
-       indice = c()
-       j = 1
-       for (i in 1:length(X))
-       {
-               if(X[i] == r)
-               {
-                       Z[i] = 1
-                       indice[j] = i
-                       j=j+1
-               } else
-                       Z[i] = 0
-       }
-       return (list(Z=Z,indice=indice))
-}
-
+#' initialization of the EM algorithm
+#'
+#' @param k number of components
+#' @param X matrix of covariates (of size n*p)
+#' @param Y matrix of responses (of size n*m)
+#' @param tau threshold to stop EM algorithm
+#'
+#' @return a list with phiInit, rhoInit, piInit, gamInit
+#' @export
 initSmallEM = function(k,X,Y,tau)
 {
        n = nrow(Y)
        m = ncol(Y)
        p = ncol(X)
-
+  
+       Zinit1 = array(0, dim=c(n,20))
        betaInit1 = array(0, dim=c(p,m,k,20))
        sigmaInit1 = array(0, dim = c(m,m,k,20))
        phiInit1 = array(0, dim = c(p,m,k,20))
        rhoInit1 = array(0, dim = c(m,m,k,20))
+       Gam = matrix(0, n, k)
        piInit1 = matrix(0,20,k)
        gamInit1 = array(0, dim=c(n,k,20))
        LLFinit1 = list()
@@ -33,43 +26,39 @@ initSmallEM = function(k,X,Y,tau)
        require(MASS) #Moore-Penrose generalized inverse of matrix
        for(repet in 1:20)
        {
-               clusters = hclust(dist(y)) #default distance : euclidean
-               #cutree retourne les indices (à quel cluster indiv_i appartient) d'un clustering hierarchique
-               clusterCut = cutree(clusters,k)
-               Zinit1[,repet] = clusterCut
+         distance_clus = dist(X)
+         tree_hier = hclust(distance_clus)
+         Zinit1[,repet] = cutree(tree_hier, k)
 
                for(r in 1:k)
                {
                        Z = Zinit1[,repet]
-                       Z_bin = vec_bin(Z,r)
-                       Z_vec = Z_bin$Z #vecteur 0 et 1 aux endroits où Z==r
-                       Z_indice = Z_bin$indice #renvoit les indices où Z==r
-
-                       betaInit1[,,r,repet] =
-                               ginv(t(x[Z_indice,])%*%x[Z_indice,])%*%t(x[Z_indice,])%*%y[Z_indice,]
+                       Z_indice = seq_len(n)[Z == r] #renvoit les indices où Z==r
+                       
+                       betaInit1[,,r,repet] = ginv(crossprod(X[Z_indice,])) %*%
+                               crossprod(X[Z_indice,], Y[Z_indice,])
                        sigmaInit1[,,r,repet] = diag(m)
-                       phiInit1[,,r,repet] = betaInit1[,,r,repet]/sigmaInit1[,,r,repet]
+                       phiInit1[,,r,repet] = betaInit1[,,r,repet] #/ sigmaInit1[,,r,repet]
                        rhoInit1[,,r,repet] = solve(sigmaInit1[,,r,repet])
-                       piInit1[repet,r] = sum(Z_vec)/n
+                       piInit1[repet,r] = mean(Z == r)
                }
-
+               
                for(i in 1:n)
                {
                        for(r in 1:k)
                        {
-                               dotProduct = (y[i,]%*%rhoInit1[,,r,repet]-x[i,]%*%phiInit1[,,r,repet]) %*%
-                                       (y[i,]%*%rhoInit1[,,r,repet]-x[i,]%*%phiInit1[,,r,repet])
+                               dotProduct = tcrossprod(Y[i,]%*%rhoInit1[,,r,repet]-X[i,]%*%phiInit1[,,r,repet])
                                Gam[i,r] = piInit1[repet,r]*det(rhoInit1[,,r,repet])*exp(-0.5*dotProduct)
                        }
-                       sumGamI = sum(gam[i,])
+                       sumGamI = sum(Gam[i,])
                        gamInit1[i,,repet]= Gam[i,] / sumGamI
                }
-
+               
                miniInit = 10
                maxiInit = 11
-
-               new_EMG = .Call("EMGLLF",phiInit1[,,,repet],rhoInit1[,,,repet],piInit1[repet,],
-                       gamInit1[,,repet],miniInit,maxiInit,1,0,x,y,tau)
+               
+               new_EMG = .Call("EMGLLF_core",phiInit1[,,,repet],rhoInit1[,,,repet],piInit1[repet,],
+                       gamInit1[,,repet],miniInit,maxiInit,1,0,X,Y,tau)
                LLFEessai = new_EMG$LLF
                LLFinit1[repet] = LLFEessai[length(LLFEessai)]
        }