R/print.factoextra.R

In factoextra: Extract and Visualize the Results of Multivariate Data Analyses

#' Print method for an object of class factoextra
#' 
#' @description
#' Print method for an object of class factoextra
#' @param x an object of class factoextra
#' @param ... further arguments to be passed to print method
#' @author Alboukadel Kassambara \email{alboukadel.kassambara@@gmail.com}
#' @examples
#'  data(iris)
#'  res.pca <- prcomp(iris[, -5],  scale = TRUE)
#'  ind <- get_pca_ind(res.pca)
#'  print(ind)
#'  
#' @export
print.factoextra<-function(x, ...){
  if(!inherits(x, "factoextra"))
    stop("Can't handle data of class ", paste(class(x), collapse = ", "))
  
  .factoextra_descriptions <- function(nms){
    desc_map <- c(
      coord = "Coordinates",
      cor = "Correlations between variables and dimensions",
      cos2 = "Cos2, quality of representation",
      contrib = "Contributions",
      inertia = "Inertia",
      correlation = "Correlation between groups and principal dimensions",
      canonical = "canonical correlation coefficient",
      `coord.partiel` = "Partial coordinates",
      `coord.partial` = "Partial coordinates",
      `within.inertia` = "Within inertia",
      `within.partial.inertia` = "Within partial inertia",
      `v.test` = "V-test"
    )
    desc <- unname(desc_map[nms])
    missing <- is.na(desc)
    if(any(missing)){
      desc[missing] <- tools::toTitleCase(gsub("[.]", " ", nms[missing]))
    }
    desc
  }
  
  if(inherits(x, "pca_ind")){
    cat("Principal Component Analysis Results for individuals\n",
        "===================================================\n")
    res <- array(data="", dim=c(3,2), dimnames=list(1:3, c("Name", "Description")))
    res[1, ] <- c("$coord", "Coordinates for the individuals")
    res[2, ] <- c("$cos2", "Cos2 for the individuals")
    res[3, ] <- c("$contrib", "contributions of the individuals")
    print(res[1:3,], ...)
  }
  
  else if(inherits(x, "pca_var")){
    cat("Principal Component Analysis Results for variables\n",
        "===================================================\n")
    nms <- names(x)
    nrows <- length(nms)
    res <- array(data = "", dim = c(nrows, 2),
                 dimnames = list(seq_len(nrows), c("Name", "Description")))
    res[, 1] <- paste0("$", nms)
    pca_var_descriptions <- c(
      coord = "Coordinates for the variables",
      cor = "Correlations between variables and dimensions",
      cos2 = "Cos2 for the variables",
      contrib = "contributions of the variables"
    )
    descriptions <- unname(pca_var_descriptions[nms])
    missing <- is.na(descriptions)
    if(any(missing))
      descriptions[missing] <- .factoextra_descriptions(nms[missing])
    res[, 2] <- descriptions
    print(res[seq_len(nrows), ], ...)
  }
  
  else if(inherits(x, "ca_row")){
    cat("Correspondence Analysis - Results for rows\n",
        "===================================================\n")
    res <- array(data="", dim=c(4,2), dimnames=list(1:4, c("Name", "Description")))
    res[1, ] <- c("$coord", "Coordinates for the rows")
    res[2, ] <- c("$cos2", "Cos2 for the rows")
    res[3, ] <- c("$contrib", "contributions of the rows")
    res[4, ] <- c("$inertia", "Inertia of the rows")
    print(res[1:4,])
  }
  
  else if(inherits(x, "ca_col")){
    cat("Correspondence Analysis - Results for columns\n",
        "===================================================\n")
    res <- array(data="", dim=c(4,2), dimnames=list(1:4, c("Name", "Description")))
    res[1, ] <- c("$coord", "Coordinates for the columns")
    res[2, ] <- c("$cos2", "Cos2 for the columns")
    res[3, ] <- c("$contrib", "contributions of the columns")
    res[4, ] <- c("$inertia", "Inertia of the columns")
    print(res[1:4,])
  }
  else if(inherits(x, "mca_ind")){
    cat("Multiple Correspondence Analysis Results for individuals\n",
        "===================================================\n")
    res <- array(data="", dim=c(3,2), dimnames=list(1:3, c("Name", "Description")))
    res[1, ] <- c("$coord", "Coordinates for the individuals")
    res[2, ] <- c("$cos2", "Cos2 for the individuals")
    res[3, ] <- c("$contrib", "contributions of the individuals")
    print(res[1:3,], ...)
  }
  else if(inherits(x, "mca_var")){
    cat("Multiple Correspondence Analysis Results for variables\n",
        "===================================================\n")
    res <- array(data="", dim=c(3,2), dimnames=list(1:3, c("Name", "Description")))
    res[1, ] <- c("$coord", "Coordinates for categories")
    res[2, ] <- c("$cos2", "Cos2 for categories")
    res[3, ] <- c("$contrib", "contributions of categories")
    print(res[1:3,])
  }
  else if(inherits(x, "famd")){
    element <- attr(x, "element") # description
    cat("FAMD results for", element, "\n",
        "===================================================\n")
    nms <- names(x)
    nrows <- length(nms)
    res <- array(data="", dim = c(nrows, 2), dimnames = list(seq_len(nrows), c("Name", "Description")))
    res[, 1] <- paste0("$", nms)
    res[, 2] <- .factoextra_descriptions(nms)
    print(res[seq_len(nrows),], ...)
  }
  else if(inherits(x, "mfa")){
    # Element
    element <- attr(x, "element") # description
    cat("Multiple Factor Analysis results for", element, "\n",
        "===================================================\n")
    nms <- names(x)
    nrows <- length(nms)
    res <- array(data="", dim = c(nrows, 2), dimnames=list(seq_len(nrows), c("Name", "Description")))
    res[, 1] <- paste0("$", nms)
    res[, 2] <- .factoextra_descriptions(nms)
    print(res[seq_len(nrows),], ...)
  }
  else if(inherits(x, c("hmfa_ind", "hmfa_quali_var", "hmfa_quanti_var"))){
    element <- attr(x, "element") # description
    cat("Hierarchical Multiple Factor Analysis results for", element, "\n",
        "===================================================\n")
    res <- array(data="", dim=c(3,2), dimnames=list(1:3, c("Name", "Description")))
    res[1, ] <- c("$coord", "Coordinates")
    res[2, ] <- c("$cos2", "Cos2, quality of representation")
    res[3, ] <- c("$contrib", "Contributions")
    print(res[1:3,], ...)
  }
  # canonical correlation coefficients added
  else if(inherits(x, "hmfa_group")){
    cat("Hierarchical Multiple Factor Analysis Results for groups\n",
        "===================================================\n")
    nms <- names(x)
    nrows <- length(nms)
    res <- array(data = "", dim = c(nrows, 2), dimnames = list(seq_len(nrows), c("Name", "Description")))
    res[, 1] <- paste0("$", nms)
    res[, 2] <- .factoextra_descriptions(nms)
    print(res[seq_len(nrows),], ...)
  }
  
}