R/concept_set.R

#' @title
#' R6 class for a set of concepts
#'
#' @description
#' This class implements the data structure and methods for concept sets.
#'
#' @examples
#' # Build a formal context
#' fc_planets <- FormalContext$new(planets)
#'
#' # Find the concepts
#' fc_planets$find_concepts()
#'
#' # Find join- and meet- irreducible elements
#' fc_planets$concepts$join_irreducibles()
#' fc_planets$concepts$meet_irreducibles()
#'
#'
#' @export
#' @import R6
#'
ConceptSet <- R6::R6Class(

  classname = "ConceptSet",

  public = list(

    #' @description
    #' Create a new \code{ConceptLattice} object.
    #'
    #' @param extents (\code{dgCMatrix}) The extents of all concepts
    #' @param intents (\code{dgCMatrix}) The intents of all concepts
    #' @param objects (character vector) Names of the objects in the formal context
    #' @param attributes (character vector) Names of the attributes in the formal context
    #' @param I (\code{dgCMatrix}) The matrix of the formal context
    #'
    #' @return
    #' A new \code{ConceptLattice} object.
    #'
    #' @export
    initialize = function(extents, intents,
                          objects, attributes,
                          I = NULL) {

      private$objects <- objects
      private$attributes <- attributes
      private$pr_extents <- extents
      private$pr_intents <- intents

      private$I <- I

    },

    #' @description
    #' Size of the Lattice
    #'
    #' @return
    #' The number of concepts in the lattice.
    #'
    #' @export
    size = function() {

      if (self$is_empty()) {

        return(0)

      }

      return(ncol(private$pr_extents))

    },

    #' @description
    #' Is the lattice empty?
    #'
    #' @return
    #' \code{TRUE} if the lattice has no concepts.
    #' @export
    is_empty = function() {

      return(is.null(private$pr_extents))

    },

    #' @description
    #' Concept Extents
    #'
    #' @return
    #' The extents of all concepts, as a \code{dgCMatrix}.
    #'
    #' @export
    extents = function() {

      return(private$pr_extents)

    },

    #' @description
    #' Concept Intents
    #'
    #' @return
    #' The intents of all concepts, as a \code{dgCMatrix}.
    #'
    #' @export
    intents = function() {

      return(private$pr_intents)

    },

    #' @description
    #' Print the Concept Set
    #'
    #' @return
    #' Nothing, just prints the concepts
    #'
    #' @export
    print = function() {

      if (self$is_empty()) {

        cat("An empty set of concepts.\n")

      } else {

        n <- ncol(private$pr_extents)

        cat("A set of", n, "concepts:\n")

        str <- sapply(seq(n), function(i) {

          vA <- Matrix::Matrix(private$pr_extents[, i], sparse = TRUE)
          vB <- Matrix::Matrix(private$pr_intents[, i], sparse = TRUE)

          paste0(i, ": ",
                 .concept_to_string(vA, vB,
                                    objects = private$objects,
                                    attributes = private$attributes))

        })

        cat(str, sep = "\n")

      }

    },

    #' @description
    #' Write in LaTeX
    #'
    #' @param print (logical) Print to output?
    #' @param ncols (integer) Number of columns of the output.
    #' @param numbered (logical) Number the concepts?
    #' @param align  (logical) Align objects and attributes independently?
    #'
    #' @return
    #' The \code{LaTeX} code to list all concepts.
    #'
    #' @export
    to_latex = function(print = TRUE,
                        ncols = 1,
                        numbered = TRUE,
                        align = TRUE) {

      if (!self$is_empty()) {

        output <- concepts_to_latex(private$pr_extents,
                                    private$pr_intents,
                                    private$objects,
                                    private$attributes,
                                    ncols = ncols,
                                    align = align,
                                    numbered = numbered)

        if (print) {

          cat(output)

        }

        return(invisible(output))

      }

    },

    #' @description
    #' Returns a list with all the concepts
    #'
    #' @return A list of concepts.
    #' @export
    to_list = function() {

      if (self$is_empty()) {

        return(list())

      }

      elements <- .matrix_to_concepts(
        M_ext = private$pr_extents,
        M_int = private$pr_intents,
        objects = private$objects,
        attributes = private$attributes)

      class(elements) <- c("list")

      return(elements)

    },

    #' @description
    #' Subsets a ConceptSet
    #'
    #' @param indices (numeric or logical vector) The indices of the concepts to return as a list of Concepts. It can be a vector of logicals where \code{TRUE} elements are to be retained.
    #'
    #' @return Another ConceptSet.
    #'
    #' @export
    `[` = function(indices) {

      if (!self$is_empty()) {

        if (is.logical(indices)) {

          indices <- which(indices)

        }

        indices <- indices[indices <= ncol(private$pr_extents)]

        return(ConceptSet$new(
          extents = Matrix::Matrix(private$pr_extents[, indices],
                                   sparse = TRUE),
          intents = Matrix::Matrix(private$pr_intents[, indices],
                                   sparse = TRUE),
          objects = private$objects,
          attributes = private$attributes,
          I = private$I))

      }

      return(ConceptSet$new(extents = NULL,
                            intents = NULL,
                            objects = private$objects,
                            attributes = private$attributes,
                            I = private$I))

    },

    #' @description
    #' Individual Concepts
    #'
    #' @param index (numeric) The index of the concept to return.
    #'
    #' @return The Concept.
    #'
    #' @export
    sub = function(index) {

      if (!self$is_empty()) {

        index <- index[index <= ncol(private$pr_extents)]

        if (length(index) > 0) {

          return(self[index]$to_list()[[1]])

        }

      }

      return(NULL)

    },

    #' @description
    #' Get support of each concept
    #'
    #' @return A vector with the support of each concept.
    #' @export
    support = function() {

      if (!is.null(private$concept_support)) {

        return(private$concept_support)

      }

      my_I <- private$I
      my_I@x <- as.numeric(my_I@x)

      subsets <- .subset(private$pr_intents, my_I)

      private$concept_support <- Matrix::rowMeans(subsets)

      return(private$concept_support)

    }

  ),

  private = list(

    pr_extents = NULL,
    pr_intents = NULL,
    objects = NULL,
    attributes = NULL,
    I = NULL,
    concept_support = NULL

  )

)

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fcaR documentation built on June 29, 2021, 1:06 a.m.