fix generateRunTest for constructionModelesEMGrank; remove man pages (will be roxygen...

[valse.git] / src / test / generate_test_data / helpers / EMGrank.R

diff --git a/src/test/generate_test_data/helpers/EMGrank.R b/src/test/generate_test_data/helpers/EMGrank.R
index d419813..346916b 100644 (file)
--- a/src/test/generate_test_data/helpers/EMGrank.R
+++ b/src/test/generate_test_data/helpers/EMGrank.R
@@ -7,7 +7,8 @@ matricize <- function(X)
 }
 
 require(MASS)
-EMGrank = function(Pi, Rho, mini, maxi, X, Y, tau, rank){
+EMGrank = function(Pi, Rho, mini, maxi, X, Y, tau, rank)
+{
   #matrix dimensions
   n = dim(X)[1]
   p = dim(X)[2]
@@ -17,18 +18,17 @@ EMGrank = function(Pi, Rho, mini, maxi, X, Y, tau, rank){
   #init outputs
   phi = array(0, dim=c(p,m,k))
   Z = rep(1, n)
-#  Pi = piInit
   LLF = 0
   
   #local variables
   Phi = array(0, dim=c(p,m,k))
-  deltaPhi = c(0)
-  sumDeltaPhi = 0
+  deltaPhi = c()
+  sumDeltaPhi = 0.
   deltaPhiBufferSize = 20
   
   #main loop
   ite = 1
-  while(ite<=mini || (ite<=maxi && sumDeltaPhi>tau))
+  while (ite<=mini || (ite<=maxi && sumDeltaPhi>tau))
        {
     #M step: Mise à jour de Beta (et donc phi)
     for(r in 1:k)
@@ -40,46 +40,45 @@ EMGrank = function(Pi, Rho, mini, maxi, X, Y, tau, rank){
       s = svd( ginv(crossprod(matricize(X[Z_indice,]))) %*%
                                crossprod(matricize(X[Z_indice,]),matricize(Y[Z_indice,])) )
       S = s$d
-      U = s$u
-      V = s$v
       #Set m-rank(r) singular values to zero, and recompose
       #best rank(r) approximation of the initial product
       if(rank[r] < length(S))
         S[(rank[r]+1):length(S)] = 0
-      phi[,,r] = U %*% diag(S) %*% t(V) %*% Rho[,,r]
+      phi[,,r] = s$u %*% diag(S) %*% t(s$v) %*% Rho[,,r]
     }
-  
+
                #Etape E et calcul de LLF
                sumLogLLF2 = 0
-               for(i in 1:n){
+               for(i in seq_len(n))
+               {
                        sumLLF1 = 0
                        maxLogGamIR = -Inf
-                       for(r in 1:k){
+                       for (r in seq_len(k))
+                       {
                                dotProduct = tcrossprod(Y[i,]%*%Rho[,,r]-X[i,]%*%phi[,,r])
                                logGamIR = log(Pi[r]) + log(det(Rho[,,r])) - 0.5*dotProduct
                                #Z[i] = index of max (gam[i,])
-                               if(logGamIR > maxLogGamIR){
+                               if(logGamIR > maxLogGamIR)
+                               {
                                        Z[i] = r
                                        maxLogGamIR = logGamIR
                                }
-                       sumLLF1 = sumLLF1 + exp(logGamIR) / (2*pi)^(m/2)
+                               sumLLF1 = sumLLF1 + exp(logGamIR) / (2*pi)^(m/2)
                        }
                        sumLogLLF2 = sumLogLLF2 + log(sumLLF1)
                }
   
                LLF = -1/n * sumLogLLF2
-  
+
                #update distance parameter to check algorithm convergence (delta(phi, Phi))
-               deltaPhi = c(deltaPhi, max(max(max((abs(phi-Phi))/(1+abs(phi))))) )
-               if(length(deltaPhi) > deltaPhiBufferSize){
-                 l_1 = c(2:length(deltaPhi))
-                 deltaPhi = deltaPhi[l_1]
-               }
+               deltaPhi = c( deltaPhi, max( (abs(phi-Phi)) / (1+abs(phi)) ) ) #TODO: explain?
+               if (length(deltaPhi) > deltaPhiBufferSize)
+                 deltaPhi = deltaPhi[2:length(deltaPhi)]
                sumDeltaPhi = sum(abs(deltaPhi))
-  
+
                #update other local variables
                Phi = phi
                ite = ite+1
   }
-  return(list(phi=phi, LLF=LLF))
+  return(list("phi"=phi, "LLF"=LLF))
 }