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 0ee2d1f..346916b 100644 (file)
--- a/src/test/generate_test_data/helpers/EMGrank.R
+++ b/src/test/generate_test_data/helpers/EMGrank.R
@@ -1,4 +1,14 @@
-EMGLLF = function(Pi, Rho, mini, maxi, X, Y, tau, rank){
+#helper to always have matrices as arg (TODO: put this elsewhere? improve?)
+matricize <- function(X)
+{
+       if (!is.matrix(X))
+               return (t(as.matrix(X)))
+       return (X)
+}
+
+require(MASS)
+EMGrank = function(Pi, Rho, mini, maxi, X, Y, tau, rank)
+{
   #matrix dimensions
   n = dim(X)[1]
   p = dim(X)[2]
@@ -8,65 +18,67 @@ EMGLLF = 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){
-      Z_bin = vec_bin(Z,r)
-      Z_vec = Z_bin$vec #vecteur 0 et 1 aux endroits o? Z==r
-      Z_indice = Z_bin$indice 
-      if(sum(Z_indice) == 0){
+    for(r in 1:k)
+               {
+      Z_indice = seq_len(n)[Z==r] #indices où Z == r
+      if (length(Z_indice) == 0)
         next
-      }
       #U,S,V = SVD of (t(Xr)Xr)^{-1} * t(Xr) * Yr
-      [U,S,V] = svd(ginv(crossprod(X[Z_indice,]))%*% (X[Z_indice,])%*%Y[Z_indice,]      )
+      s = svd( ginv(crossprod(matricize(X[Z_indice,]))) %*%
+                               crossprod(matricize(X[Z_indice,]),matricize(Y[Z_indice,])) )
+      S = s$d
       #Set m-rank(r) singular values to zero, and recompose
       #best rank(r) approximation of the initial product
-      S[rank(r)+1:end,] = 0
-      phi[,,r] = U %*%S%*%t(V)%*%Rho[,,r]
+      if(rank[r] < length(S))
+        S[(rank[r]+1):length(S)] = 0
+      phi[,,r] = s$u %*% diag(S) %*% t(s$v) %*% Rho[,,r]
     }
+
+               #Etape E et calcul de LLF
+               sumLogLLF2 = 0
+               for(i in seq_len(n))
+               {
+                       sumLLF1 = 0
+                       maxLogGamIR = -Inf
+                       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)
+                               {
+                                       Z[i] = r
+                                       maxLogGamIR = logGamIR
+                               }
+                               sumLLF1 = sumLLF1 + exp(logGamIR) / (2*pi)^(m/2)
+                       }
+                       sumLogLLF2 = sumLogLLF2 + log(sumLLF1)
+               }
   
-  #Etape E et calcul de LLF
-  sumLogLLF2 = 0
-  for(i in 1:n){
-    sumLLF1 = 0
-    maxLogGamIR = -Inf
-    for(r in 1: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){
-        Z[i] = r
-        maxLogGamIR = logGamIR
-      }
-    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){
-    deltaPhi = deltaPhi[2:length(deltaPhi)]
-  }
-  sumDeltaPhi = sum(abs(deltaPhi))
-  
-  #update other local variables
-  Phi = phi
-  ite = ite+1
-  
+               LLF = -1/n * sumLogLLF2
+
+               #update distance parameter to check algorithm convergence (delta(phi, Phi))
+               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))
-}
\ No newline at end of file
+  return(list("phi"=phi, "LLF"=LLF))
+}