R/s3_summary.R

In sharp: Stability-enHanced Approaches using Resampling Procedures

#' @export
summary.variable_selection <- function(object, ...) {
  cat(paste0(
    "Calibrated parameters: lambda = ",
    formatC(Argmax(object)[1, 1], format = "f", digits = 3),
    " and pi = ",
    formatC(Argmax(object)[1, 2], format = "f", digits = 3)
  ))
  cat("\n")
  cat("\n")
  cat(paste0(
    "Maximum stability score: ",
    formatC(max(object$S, na.rm = TRUE), format = "f", digits = 3)
  ))
  cat("\n")
  cat("\n")
  cat(paste0(
    "Number of selected variable(s): ",
    sum(SelectedVariables(object))
  ))
  cat("\n")
}


#' @export
summary.structural_model <- function(object, ...) {
  cat(paste0(
    "Calibrated parameters: lambda = ",
    formatC(Argmax(object)[1, 1], format = "f", digits = 3),
    " and pi = ",
    formatC(Argmax(object)[1, 2], format = "f", digits = 3)
  ))
  cat("\n")
  cat("\n")
  cat(paste0(
    "Maximum stability score: ",
    formatC(max(object$S, na.rm = TRUE), format = "f", digits = 3)
  ))
  cat("\n")
  cat("\n")
  cat(paste0(
    "Number of selected arrow(s): ",
    sum(SelectedVariables(object))
  ))
  cat("\n")
}


#' @export
summary.graphical_model <- function(object, ...) {
  if (ncol(object$S) > 1) {
    cat(paste0("Calibrated parameters:"))
    cat("\n")
    for (k in seq_len(ncol(object$S))) {
      cat(paste0(
        "Block ", k, ": lambda = ",
        formatC(Argmax(object)[k, 1], format = "f", digits = 3),
        " and pi = ",
        formatC(Argmax(object)[k, 2], format = "f", digits = 3)
      ))
      cat("\n")
    }
    cat("\n")
    cat("Maximum stability scores: ")
    cat("\n")
    for (k in seq_len(ncol(object$S))) {
      cat(paste0(
        "Block ", k, ": ",
        formatC(max(object$S[, k], na.rm = TRUE), format = "f", digits = 3)
      ))
      cat("\n")
    }
    cat("\n")
    cat("Number of selected edge(s): ")
    cat("\n")
    adjacency <- Adjacency(object)
    adjacency <- adjacency[upper.tri(adjacency)]
    bigblocks <- BlockMatrix(pk = object$params$pk)
    bigblocks <- bigblocks[upper.tri(bigblocks)]
    for (k in seq_len(ncol(object$S))) {
      cat(paste0(
        "Block ", k, ": ",
        round(sum(adjacency[bigblocks == k]))
      ))
      cat("\n")
    }
    cat(paste0(
      "Total: ",
      sum(Adjacency(object)) / 2
    ))
  } else {
    cat(paste0(
      "Calibrated parameters: lambda = ",
      formatC(Argmax(object)[1, 1], format = "f", digits = 3),
      " and pi = ",
      formatC(Argmax(object)[1, 2], format = "f", digits = 3)
    ))
    cat("\n")
    cat("\n")
    cat(paste0(
      "Maximum stability score: ",
      formatC(max(object$S[, 1], na.rm = TRUE), format = "f", digits = 3)
    ))
    cat("\n")
    cat("\n")
    cat(paste0(
      "Number of selected edge(s): ",
      sum(Adjacency(object)) / 2
    ))
  }
  cat("\n")
}


#' @export
summary.bi_selection <- function(object, ...) {
  cat(paste0("Calibrated parameters (X):"))
  cat("\n")
  for (k in seq_len(nrow(object$summary))) {
    if ("alphax" %in% colnames(object$summary)) {
      cat(paste0(
        "Component ", k, ": n = ",
        formatC(object$summary[k, "nx"], format = "f", digits = 3),
        ", alpha = ",
        formatC(object$summary[k, "alphax"], format = "f", digits = 3),
        " and pi = ",
        formatC(object$summary[k, "pix"], format = "f", digits = 3)
      ))
    } else {
      cat(paste0(
        "Component ", k, ": n = ",
        formatC(object$summary[k, "nx"], format = "f", digits = 3),
        " and pi = ",
        formatC(object$summary[k, "pix"], format = "f", digits = 3)
      ))
    }
    cat("\n")
  }
  if ("ny" %in% colnames(object$summary)) {
    cat("\n")
    cat(paste0("Calibrated parameters (Y):"))
    cat("\n")
    for (k in seq_len(nrow(object$summary))) {
      if ("alphay" %in% colnames(object$summary)) {
        cat(paste0(
          "Component ", k, ": n = ",
          formatC(object$summary[k, "ny"], format = "f", digits = 3),
          ", alpha = ",
          formatC(object$summary[k, "alphay"], format = "f", digits = 3),
          " and pi = ",
          formatC(object$summary[k, "piy"], format = "f", digits = 3)
        ))
      } else {
        cat(paste0(
          "Component ", k, ": n = ",
          formatC(object$summary[k, "ny"], format = "f", digits = 3),
          " and pi = ",
          formatC(object$summary[k, "piy"], format = "f", digits = 3)
        ))
      }
      cat("\n")
    }
  }
  cat("\n")
  if (nrow(object$summary) > 1) {
    cat("Maximum stability scores (X): ")
  } else {
    cat("Maximum stability score (X): ")
  }
  cat("\n")
  for (k in seq_len(nrow(object$summary))) {
    cat(paste0(
      "Component ", k, ": ",
      formatC(max(object$summary[k, "S"], na.rm = TRUE), format = "f", digits = 3)
    ))
    cat("\n")
  }
  cat("\n")
  cat("Number of selected variable(s) (X): ")
  cat("\n")
  for (k in seq_len(nrow(object$summary))) {
    cat(paste0(
      "Component ", k, ": ",
      round(sum(object$selectedX[, k]))
    ))
    cat("\n")
  }
  if ("ny" %in% colnames(object$summary)) {
    cat("\n")
    cat("Number of selected variable(s) (Y): ")
    cat("\n")
    for (k in seq_len(nrow(object$summary))) {
      cat(paste0(
        "Component ", k, ": ",
        round(sum(object$selectedY[, k]))
      ))
      cat("\n")
    }
  }
  cat("\n")
}


#' @export
summary.clustering <- function(object, ...) {
  cat(paste0(
    "Calibrated parameters: nc = ",
    formatC(Argmax(object)[1, 1], format = "f", digits = 3),
    ifelse(!is.na(Argmax(object)[1, 2]),
      yes = paste0(" and lambda = ", formatC(Argmax(object)[1, 2], format = "f", digits = 3)),
      no = ""
    )
  ))
  cat("\n")
  cat("\n")
  cat(paste0(
    "Maximum consensus score: ",
    formatC(max(object$S, na.rm = TRUE), format = "f", digits = 3)
  ))
  cat("\n")
}

#' @export
summary.incremental <- function(object, ...) {
  cat(paste0("Performances of refitted models:"))
  cat("\n")
  cat("\n")
  mat <- plot.incremental(object, output_data = TRUE, ...)
  for (i in seq_len(ncol(mat))) {
    cat(paste0(
      ifelse(i == 1, yes = "  ", no = "+ "),
      colnames(mat)[i],
      ": ",
      formatC(mat[1, i], format = "f", digits = 3)
    ))
    cat("\n")
  }
}