R/seqQuickLook.R

In seqimpute: Imputation of Missing Data in Sequence Analysis

#' Numbering NAs and types of gaps among a dataset
#'
#' \code{seqQuickLook.R} is a function aimed at providing an overview of the
#' number and size of the different types of gaps
#' spread in the original dataset \code{OD}.
#'
#' @param OD either a data frame containing sequences of a multinomial variable with missing data (coded as \code{NA}) or
#' a state sequence object built with the TraMineR package
#' @param np number of previous observations in the imputation model of the internal gaps.
#' @param nf number of future observations in the imputation model of the internal gaps.
#' @author Andre Berchtold <andre.berchtold@@unil.ch>
#'
#' @return It returns a  \code{data.frame} object that summarizes for each type of gaps
#' (Internal Gaps, Initial Gaps, Terminal Gaps, LEFT-
#' hand side SLG, RIGHT-hand side SLG, Both-hand side SLG),
#' the minimum length, the maximum length, the total number of gaps and
#' the total number of NAs induced.
#'
#' @examples
#' data(OD)
#'
#' seqQuickLook(OD = OD, np = 1, nf = 0)
#'
#' @export


seqQuickLook <- function(OD, np = 1, nf = 1) {
  if (inherits(OD, "stslist")) {
    valuesNA <- c(attr(OD, "nr"), attr(OD, "void"))
    OD <- data.frame(OD)
    OD[OD == valuesNA[1] | OD == valuesNA[2]] <- NA
  }



  # 1. Initial tests on parameters --------------------------------------------------------------------------------------------------------------------


  # 1.1 Testing the class of the variables of the original dataset OD ---------------------------------------------------------------------------------
  ODClass <- class(OD[1, 1])
  if ((ODClass != "factor") & (ODClass != "numeric")) {
    stop("/!\\ The class of the variables contained in your original dataset
         should be either 'factor' or 'numeric'")
  }


  if (ODClass == "factor") {
    k <- length(sort(unique(as.vector(as.matrix(OD)))))
  } else {
    k <- max(OD)
  }

  dataOD <- list()
  dataOD[c("OD", "CO", "COt", "rowsNA")] <- deleteNaRows(OD, matrix(NA, nrow = 1, ncol = 1), matrix(NA, nrow = 1, ncol = 1))



  # Naming the number of rows and columns of the original dataset OD
  nr <- nrow(dataOD$OD)
  nc <- ncol(dataOD$OD)





  # 1. Analysis of OD and creation of matrices ORDER, ORDER2 and ORDER3 -----------------------------------------------------------------------------------------
  dataOD[c("MaxInitGapSize", "InitGapSize", "MaxTermGapSize", "TermGapSize", "MaxGap", "ORDER", "ORDER2", "ORDER3")] <- OrderCreation(dataOD$OD, nr, nc)



  # 2. Computation of the order of imputation of each MD (i.e. updating of matrix ORDER) --------------------------------------------------------------------
  if (max(dataOD$ORDER) != 0) {
    dataOD[c("ORDERSLGLeft", "ORDERSLGRight", "ORDERSLGBoth", "LongGap", "MaxGap", "REFORD_L", "ORDER")] <- ImputeOrderComputation(dataOD$ORDER, dataOD$ORDER3, dataOD$MaxGap, np, nf, nr, nc)
  } else {
    dataOD$ORDERSLGLeft <- matrix(nrow = dataOD$nr, ncol = dataOD$nc, 0)
    dataOD$ORDERSLGRight <- matrix(nrow = dataOD$nr, ncol = dataOD$nc, 0)
    dataOD$ORDERSLGBoth <- matrix(nrow = dataOD$nr, ncol = dataOD$nc, 0)
    dataOD$LongGap <- FALSE
  }


  MDGapsChart <- matrix(0, 6, 4)
  MDGapsChart <- as.data.frame(MDGapsChart)
  rownames(MDGapsChart) <- c("Internal Gaps", "Initial Gaps", "Terminal Gaps", "LEFT-hand side SLG", "RIGHT-hand side SLG", "BOTH-hand side SLG")
  colnames(MDGapsChart) <- c("MinGapSize", "MaxGapSize", "numbOfGaps", "sumNAGaps")

  if (max(dataOD$ORDER) > 0) {
    MDGapsChart[1, 1] <- min(dataOD$ORDER[dataOD$ORDER > 0])
    MDGapsChart[1, 2] <- max(dataOD$ORDER)
  }
  # Number of Internal Gaps
  # Transforming dataOD$ORDER in a single row vector
  dataOD$ORDERVect <- as.vector(t(dataOD$ORDER))
  # Transforming this single row vector into class character
  dataOD$ORDERVectChar <- paste(dataOD$ORDERVect, collapse = "")
  # Identifying the patterns "0 1" (this is the signature look of an internal gap
  # (it always indicates the beginning of an internal gap!))
  MDGapsChart[1, 3] <- str_count(dataOD$ORDERVectChar, pattern = "01")
  MDGapsChart[1, 4] <- sum(dataOD$ORDER > 0)


  if (max(dataOD$InitGapSize) > 0) {
    MDGapsChart[2, 1] <- min(dataOD$InitGapSize[dataOD$InitGapSize > 0])
    MDGapsChart[2, 2] <- max(dataOD$InitGapSize)
    MDGapsChart[2, 3] <- sum(table(dataOD$InitGapSize[dataOD$InitGapSize > 0]))
    MDGapsChart[2, 4] <- sum(dataOD$InitGapSize)
  }

  if (max(dataOD$TermGapSize) > 0) {
    MDGapsChart[3, 1] <- min(dataOD$TermGapSize[dataOD$TermGapSize > 0])
    MDGapsChart[3, 2] <- max(dataOD$TermGapSize)
    MDGapsChart[3, 3] <- sum(table(dataOD$TermGapSize[dataOD$TermGapSize > 0]))
    MDGapsChart[3, 4] <- sum(dataOD$TermGapSize)
  }

  LeftGap <- rowSums(dataOD$ORDERSLGLeft > 0)
  if (max(LeftGap) > 0) {
    MDGapsChart[4, 1] <- min(LeftGap[LeftGap > 0])
    MDGapsChart[4, 2] <- max(LeftGap)
    MDGapsChart[4, 3] <- sum(table(LeftGap[LeftGap > 0]))
    MDGapsChart[4, 4] <- sum(LeftGap)
  }

  RightGap <- rowSums(dataOD$ORDERSLGRight > 0)
  if (max(RightGap) > 0) {
    MDGapsChart[5, 1] <- min(RightGap[RightGap > 0])
    MDGapsChart[5, 2] <- max(RightGap)
    MDGapsChart[5, 3] <- sum(table(RightGap[RightGap > 0]))
    MDGapsChart[5, 4] <- sum(RightGap)
  }

  BothGap <- rowSums(dataOD$ORDERSLGBoth > 0)
  if (max(BothGap) > 0) {
    MDGapsChart[6, 1] <- min(BothGap[BothGap > 0])
    MDGapsChart[6, 2] <- max(BothGap)
    MDGapsChart[6, 3] <- sum(table(BothGap[BothGap > 0]))
    MDGapsChart[6, 4] <- sum(BothGap)
  }

  return(MDGapsChart)
}