R/ChlorineConcentration.R

In moviedo5/fda.tsc: Functional Data Sets for Time Series Classification

#' @title Chlorine concentration data set
#'
#' @description The data set consists of 166 nodes (pipe junctions) and measurement of the Chlorine concentration level at all these nodes during 15 days (one measurement for every 5 minutes, a total of 4310 time ticks).
#' @details  This dataset was defined in a PhD thesis by Lei Li (Carnegie Mellon University). It was produced by EPANET that models the hydraulic and water quality behavior of water distribution piping systems. EPANET can track, in a given water network, the water level and pressure in each tank, the water flow in the pipes and the concentration of a chemical species (Chlorine in this case) throughout the network within a simulated duration.
#' @format 
#' \describe{
#' The variables are as follows:
#' \itemize{
#' \item{\code{df}:}{ \code{data.frame} with the following variables:}
#' \itemize{
#' \item{\code{class}:}{ Corresponding class level of ``ChlorineConcentration'' curves with 3 classes with 1000, 1000 and 2307 observations per class respectively.}
#' \item{\code{sample}:}{Factor variable. In TSC database, the first 467 values (\code{sample=train}) are used for training sample and the rest of 3840 (\code{sample=test}) for testing.}
#' }
#' \item{\code{x}:}{ \code{fdata} class object with with n=930 curves (per row) in 930 discretization points (per column).}
#' }
#'   
#' }
#' 
#' @docType data
#' @keywords datasets
#' @name ChlorineConcentration
#' @usage data(ChlorineConcentration)
#' @source \url{http://timeseriesclassification.com/description.php?Dataset=ChlorineConcentration}
#' @references 
#' Li, L. (2011). Fast algorithms for mining co-evolving time series (No. CMU-CS-11-127). CARNEGIE INST OF TECH PITTSBURGH PA DEPT OF COMPUTER SCIENCE.
#' \url{http://www.cs.cmu.edu/~leili/pubs/leili-thesis.pdf}
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