utilisation de k-means au lieu de hierarchique dans initSmallEM - PB de dimensions...

[valse.git] / R / main.R

diff --git a/R/main.R b/R/main.R
index 00b1be9..9817b00 100644 (file)
--- a/R/main.R
+++ b/R/main.R
@@ -39,7 +39,7 @@ SelMix = setRefClass(
                # initialisation for the allocations probabilities in each component
                tauInit,
                # values for the regularization parameter grid
-               gridLambda = [];
+               gridLambda = c(),
                # je ne crois pas vraiment qu'il faille les mettre en sortie, d'autant plus qu'on construit
                # une matrice A1 et A2 pour chaque k, et elles sont grandes, donc ca coute un peu cher ...
                A1,
@@ -52,7 +52,7 @@ SelMix = setRefClass(
                Pi,
 
                #immutable
-               seuil = 1e-15;
+               seuil = 1e-15
        ),
 
        methods = list(
@@ -100,7 +100,7 @@ SelMix = setRefClass(
                        "computation of the regularization grid"
                        #(according to explicit formula given by EM algorithm)
 
-                       gridLambda <<- grillelambda(sx.phiInit,sx.rhoInit,sx.piInit,sx.tauInit,sx.X,sx.Y,
+                       gridLambda <<- gridLambda(sx.phiInit,sx.rhoInit,sx.piInit,sx.tauInit,sx.X,sx.Y,
                                sx.gamma,sx.mini,sx.maxi,sx.eps);
                },
 
@@ -163,19 +163,19 @@ SelMix = setRefClass(
                                                p = ncol(X)
                                                m = ncol(Y)
                                                if size(Phi2) == 0 #TODO: continue translation MATLAB --> R
-                                               sx.Phi(:,:,1:k,:) = r1$phi;
-                                               sx.Rho(:,:,1:k,:) = r1$rho;
-                                               sx.Pi(1:k,:) = r1$pi;
+                                               Phi(:,:,1:k,:) = r1$phi;
+                                               Rho(:,:,1:k,:) = r1$rho;
+                                               Pi(1:k,:) = r1$pi;
                                                else
-                                               sx.Phi = zeros(p,m,sx.kmax,size(Phi2,4)+size(r1$phi,4));
-                                               sx.Phi(:,:,1:size(Phi2,3),1:size(Phi2,4)) = Phi2;
-                                               sx.Phi(:,:,1:k,size(Phi2,4)+1:end) = r1$phi;
-                                               sx.Rho = zeros(m,m,sx.kmax,size(Rho2,4)+size(r1$rho,4));
-                                               sx.Rho(:,:,1:size(Rho2,3),1:size(Rho2,4)) = Rho2;
-                                               sx.Rho(:,:,1:k,size(Rho2,4)+1:end) = r1$rho;
-                                               sx.Pi = zeros(sx.kmax,size(Pi2,2)+size(r1$pi,2));
-                                               sx.Pi(1:size(Pi2,1),1:size(Pi2,2)) = Pi2;
-                                               sx.Pi(1:k,size(Pi2,2)+1:end) = r1$pi;
+                                               Phi = zeros(p,m,sx.kmax,size(Phi2,4)+size(r1$phi,4));
+                                               Phi(:,:,1:size(Phi2,3),1:size(Phi2,4)) = Phi2;
+                                               Phi(:,:,1:k,size(Phi2,4)+1:end) = r1$phi;
+                                               Rho = zeros(m,m,sx.kmax,size(Rho2,4)+size(r1$rho,4));
+                                               Rho(:,:,1:size(Rho2,3),1:size(Rho2,4)) = Rho2;
+                                               Rho(:,:,1:k,size(Rho2,4)+1:end) = r1$rho;
+                                               Pi = zeros(sx.kmax,size(Pi2,2)+size(r1$pi,2));
+                                               Pi(1:size(Pi2,1),1:size(Pi2,2)) = Pi2;
+                                               Pi(1:k,size(Pi2,2)+1:end) = r1$pi;
                                                end
                                else
                                                [phi] = runProcedure2(sx);