R/cobiclustering.R

In cobiclust: Biclustering via Latent Block Model Adapted to Overdispersed Count Data

# cobiclust R package Copyright INRAE 2024 Universite Paris-Saclay,
# AgroParisTech, INRAE, UMR MIA Paris-Saclay, 91120, Palaiseau, France
#' Creation of the cobiclustering class.
#' @export cobiclustering
#' @keywords internal


cobiclustering <- function(data = matrix(nrow = 3, ncol = 3, NA),
    K = 2, G = 2, classification = list(length = 2), strategy = list(),
    parameters = list(), info = list()) {
    object <- list(data = "matrix", K = "numeric", G = "numeric",
        classification = "list", strategy = "list", parameters = "list",
        info = "list")
    # UseMethod('new',object) Set the name for the class
    class(object) <- "cobiclustering"
    return(object)
}

#' Is an object of class cobiclustering ?
#'
#' @param object an object of class cobiclustering.
#' @export is.cobiclustering
#' @keywords internal
is.cobiclustering <- function(object) {
    return(class(object) == "cobiclustering")
}

#' Summary of an object of class Cobiclust
#'
#' @param object an object of class cobiclustering.
#' @param ... ignored
#' @keywords internal
#' @method summary cobiclustering
#' @export
summary.cobiclustering <- function(object, ...) {
    cat("-----------------------------------------------------------\n")
    cat("Number of biclusters: K = ", object$K, "* G = ",
        object$G, "\n")
    cat("Row proportions:", round(object$parameters$pi,
        3), "\n")
    cat("Column proportions:", round(object$parameters$rho,
        3), "\n")
    cat("-----------------------------------------------------------\n")
    cat("Matrix of alpha_kg interactions terms: \n")
    print(matrix(nrow = object$K, ncol = object$G,
        round(object$parameters$alpha, 3)))
    cat("-----------------------------------------------------------\n")
    cat("Frequencies of MAP classification \n")
    cat("Rows")
    print(table(object$classification$rowclass))
    cat("Columns")
    print(table(object$classification$colclass))
    cat(" \n")
    NextMethod("summary", object)
    cat("-----------------------------------------------------------\n")
}