Add 'fast' argument to select C code or R code

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

diff --git a/test/generate_test_data/EMGrank.R b/test/generate_test_data/EMGrank.R
deleted file mode 100644 (file)
index c4576e4..0000000
--- a/test/generate_test_data/EMGrank.R
+++ /dev/null
@@ -1,85 +0,0 @@
-#helper to always have matrices as arg (TODO: put this elsewhere? improve?)
-# --> Yes, we should use by-columns storage everywhere... [later!]
-matricize <- function(X)
-{
-       if (!is.matrix(X))
-               return (t(as.matrix(X)))
-       return (X)
-}
-
-require(MASS)
-EMGrank_R = function(Pi, Rho, mini, maxi, X, Y, tau, rank)
-{
-  #matrix dimensions
-  n = dim(X)[1]
-  p = dim(X)[2]
-  m = dim(Rho)[2]
-  k = dim(Rho)[3]
-  
-  #init outputs
-  phi = array(0, dim=c(p,m,k))
-  Z = rep(1, n)
-  LLF = 0
-  
-  #local variables
-  Phi = array(0, dim=c(p,m,k))
-  deltaPhi = c()
-  sumDeltaPhi = 0.
-  deltaPhiBufferSize = 20
-  
-  #main loop
-  ite = 1
-  while (ite<=mini || (ite<=maxi && sumDeltaPhi>tau))
-       {
-    #M step: Mise à jour de Beta (et donc phi)
-    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
-      s = svd( ginv(crossprod(matricize(X[Z_indice,]))) %*%
-                               crossprod(matricize(X[Z_indice,]),matricize(Y[Z_indice,])) )
-      S = s$d
-      #Set m-rank(r) singular values to zero, and recompose
-      #best rank(r) approximation of the initial product
-      if(rank[r] < length(S))
-        S[(rank[r]+1):length(S)] = 0
-      phi[,,r] = s$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)
-               }
-  
-               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))
-}