R/repr_matrix.R

In PetoLau/TSrepr: Time Series Representations

# Computation of matrix of representations from matrix of time series

#' @rdname repr_matrix
#' @name repr_matrix
#' @title Computation of matrix of representations from matrix of time series
#'
#' @description The \code{repr_matrix} computes matrix of representations from matrix of time series
#'
#' @return the numeric matrix of representations of time series
#'
#' @param x the matrix, data.frame or data.table of time series, where time series are in rows of the table
#' @param func the function that computes representation
#' @param args the list of additional (or required) parameters of func (function that computes representation)
#' @param normalise normalise (scale) time series before representations computation? (default is FALSE)
#' @param func_norm the normalisation function (default is \code{norm_z})
#' @param windowing perform windowing? (default is FALSE)
#' @param win_size the size of the window
#'
#' @details This function computes representation to an every row of a matrix of time series and returns matrix of time series representations.
#' It can be combined with windowing (see \code{\link{repr_windowing}}) and normalisation of time series.
#'
#' @author Peter Laurinec, <tsreprpackage@gmail.com>
#'
#' @seealso \code{\link[TSrepr]{repr_windowing}, \link[TSrepr]{repr_list}}
#'
#' @examples
#' # Create random matrix of time series
#' mat_ts <- matrix(rnorm(100), ncol = 10)
#' repr_matrix(mat_ts, func = repr_paa,
#'  args = list(q = 5, func = meanC))
#'
#' # return normalised representations, and normalise time series by min-max normalisation
#' repr_matrix(mat_ts, func = repr_paa,
#'  args = list(q = 2, func = meanC), normalise = TRUE, func_norm = norm_min_max)
#'
#' # with windowing
#' repr_matrix(mat_ts, func = repr_feaclip, windowing = TRUE, win_size = 5)
#'
#' @export repr_matrix
repr_matrix <- function(x, func = NULL, args = NULL, normalise = FALSE, func_norm = norm_z, windowing = FALSE, win_size = NULL) {

  if (is.null(func)) {

    stop("func must be specified!")

  }

  x <- data.matrix(x)

  if (normalise == TRUE) {

    x <- t(apply(x, 1, func_norm))

  }

  if (windowing) {

    if (is.null(win_size)) {

      stop("win_size must be specified!")

    }

    repr <- t(sapply(1:nrow(x), function(i) repr_windowing(x[i,],
                                                           win_size = win_size,
                                                           func = func,
                                                           args = args
                                                           )
                     )
              )

  } else {

    repr <- t(sapply(1:nrow(x), function(i) do.call(func, args = c(list(x = x[i,]),
                                                                   args
                                                                   )
                                                    )
                     )
              )

  }

  return(repr)

}