X-Git-Url: https://git.auder.net/?p=valse.git;a=blobdiff_plain;f=pkg%2FR%2Fplot_valse.R;h=2c74554899dfbeca72187047b7f6f1f393ae3fda;hp=05963c8af8c6d9d598caa0aed92ebc07c9f42e70;hb=a6b60f91ff8d798a3dcb7da6acbc03fba8a0459d;hpb=0e0fb59a6ea0a975d1a9059153aa27f54458bf95

diff --git a/pkg/R/plot_valse.R b/pkg/R/plot_valse.R
index 05963c8..2c74554 100644
--- a/pkg/R/plot_valse.R
+++ b/pkg/R/plot_valse.R
@@ -2,18 +2,21 @@
 #'
 #' It is a function which plots relevant parameters
 #'
-#'
+#' @param model the model constructed by valse procedure
+#' @param n sample size
 #' @return several plots
 #'
 #' @examples TODO
 #'
 #' @export
 #'
-plot_valse = function(){
+plot_valse = function(model,n){
   require("gridExtra")
   require("ggplot2")
   require("reshape2")
+  require("cowplot")
   
+  K = length(model$pi)
   ## regression matrices
   gReg = list()
   for (r in 1:K){
@@ -60,8 +63,8 @@ plot_valse = function(){
     gam2[i, ] = c(gam[i, affec[i]], affec[i])
   }
   bp <- ggplot(data.frame(gam2), aes(x=X2, y=X1, color=X2, group = X2)) +
-    geom_boxplot() + theme(legend.position = "none")
-  print(bp + background_grid(major = "xy", minor = "none"))
+    geom_boxplot() + theme(legend.position = "none")+ background_grid(major = "xy", minor = "none")
+  print(bp )
   
   ### Mean in each cluster
   XY = cbind(X,Y)