# R/toList.details.R In LearnClust: Learning Hierarchical Clustering Algorithms

#### Documented in toList.details

```#' @title To explain how to transform data into list
#' @description To explain how to transform \code{data} into list.
#' @param data could be a numeric vector, a matrix or a numeric data frame.
#' @details This function is part of the agglomerative hierarchical clusterization method. The function initializes
#' \code{data} content as a list.
#' @details In agglomerative algorithm, it adds a \code{TRUE} flag to each element, which indicates that the cluster is not grouped.
#' @author Roberto Alcántara \email{roberto.alcantara@@edu.uah.es}
#' @author Universidad de Alcalá de Henares
#' @return A list with cñlusters. Explanation.
#' @examples
#'
#' data <- c(1:10)
#'
#' matrix <- matrix(data,ncol=2)
#'
#' dataFrame <- data.frame(matrix)
#'
#' toList(data)
#'
#' toList(matrix)
#'
#' toList(dataFrame)
#'
#' @export

toList.details <- function(data){
message("  'toList' creates a list initializing datas by creating clusters with each one \n")
if (is.data.frame(data)){
# print('dataframe')
v <- dataFrameToVector(data)
} else if (is.matrix(data)){
# print('matrix')
v <- matrixToVector(data)
} else {
# print('vector')
v <- data
}
list <- c()
for (i in (1:(length(v)/2))) {
value1 <- v[2*i -1]
value2 <- v[2*i]
cluster <- matrix(c(value1,value2,TRUE),ncol=3)
list[[i]] <- cluster
}
list
}
```

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LearnClust documentation built on Nov. 30, 2020, 1:09 a.m.