change of the cophenetic vector

R/treediff.R

@@ -48,12 +48,12 @@ treediff <- function(trees1, trees2, replicats){
     stop("The number of clusters is different between conditions or `replicats' is uncorrect")
   }
 
-  # Extract the number of pair of the trees
-  tree_order <- lapply(trees1, "[[", "order")
-  leaves <- sapply(tree_order, length)
-
-  # Get unique values of the number of leaves
-  leaves <- unique(leaves)
+  # # Extract the number of pair of the trees
+  # tree_order <- lapply(trees1, "[[", "order")
+  # leaves <- sapply(tree_order, length)
+  #
+  # # Get unique values of the number of leaves
+  # leaves <- unique(leaves)
 
   # Merge trees from both conditions
   trees <- c(trees1, trees2)
@@ -66,14 +66,15 @@ treediff <- function(trees1, trees2, replicats){
     adist <- as.matrix(adist)
     return(adist[upper.tri(adist)])
   })
-  # Fill the cophenetic vector with NA if the number of leaves is different from the max.
-  if (length(leaves) != 1){
-    len_max <- choose(max(leaves), 2)
 
-    coph_vect <- sapply(coph_vect, FUN = function(col) {
-      c(col, rep(NA, len_max - length(col)))
-    })
-  }
+  # # Fill the cophenetic vector with NA if the number of leaves is different from the max.
+  # if (length(leaves) != 1){
+  #   len_max <- choose(max(leaves), 2)
+  #
+  #   coph_vect <- sapply(coph_vect, FUN = function(col) {
+  #     c(col, rep(NA, len_max - length(col)))
+  #   })
+  # }
 
   # Compute squeeze factor
   outs <- compute_squeeze(coph_vect, replicats)
@@ -101,6 +102,13 @@ treediff <- function(trees1, trees2, replicats){
 
 compute_squeeze <- function(dist_coph, replicats){
 
+  if (class(dist_coph) == "list"){
+    max_pr <- as.numeric(max(summary(dist_coph)[,1]))
+    dist_coph <- sapply(dist_coph, FUN = function(col) {
+      c(col, rep(NA, max_pr - length(col)))
+    })
+  }
+
   # Calculate number of clusters
   nb_cluster <- ncol(dist_coph)/sum(replicats)
 
@@ -172,7 +180,7 @@ compute_pvalue <- function(average_coph, squeezed_var, replicats){
   # Calculate the t-statistic
   statistics <- numerator / sqrt(denominator)
 
-  # Extract the degrees of freedom for the t-distribution
+  # Extract the degrees of freedom
   d0 <- squeezed_var$df.prior
 
   # Calculate the p-value