#' Comprehensive implementation of Dynamic Time Warping (DTW) algorithms in R.
#' 
#' The DTW algorithm computes the stretch of the time axis which optimally maps
#' one given timeseries (query) onto whole or part of another (reference). It
#' yields the remaining cumulative distance after the alignment and the
#' point-by-point correspondence (warping function). DTW is widely used e.g.
#' for classification and clustering tasks in econometrics, chemometrics and
#' general timeseries mining.
#' 
#' Please see documentation for function \code{\link{dtw}}, which is the main
#' entry point to the package.
#' 
#' The R implementation in dtw provides:
#' 
#' \itemize{ \item arbitrary windowing functions (global constraints), eg. the
#' Sakoe-Chiba band; see \code{\link{dtwWindowingFunctions}} \item arbitrary
#' transition types (also known as step patterns, slope constraints, local
#' constraints, or DP-recursion rules). This includes dozens of well-known
#' types; see \code{\link{stepPattern}}: \itemize{ \item all step patterns
#' classified by Rabiner-Juang, Sakoe-Chiba, and Rabiner-Myers; \item symmetric
#' and asymmetric; \item Rabiner's smoothed variants; \item arbitrary,
#' user-defined slope constraints } \item partial matches: open-begin,
#' open-end, substring matches \item proper, pattern-dependent, normalization
#' (exact average distance per step) \item the Minimum Variance Matching (MVM)
#' algorithm (Latecki et al.) }
#' 
#' Multivariate timeseries can be aligned with arbitrary local distance
#' definitions, leveraging the \code{\link[proxy]{dist}} function of package
#' \pkg{proxy}. DTW itself becomes a distance function with the dist semantics.
#' 
#' In addition to computing alignments, the package provides: \itemize{ \item
#' methods for plotting alignments and warping functions in several classic
#' styles (see plot gallery); \item graphical representation of step patterns;
#' \item functions for applying a warping function, either direct or inverse;
#' and more. }
#' 
#' If you use this software, please cite it according to
#' \code{citation("dtw")}.  The package home page is at
#' \url{http://dtw.r-forge.r-project.org}.
#' 
#' @name dtw-package
#' @docType package
#' @author Toni Giorgino
#'
#' 
#' @seealso \code{\link{dtw}} for the main entry point to the package;
#' \code{\link{dtwWindowingFunctions}} for global constraints;
#' \code{\link{stepPattern}} for local constraints;
#' \code{\link[analogue]{distance}}, \code{\link{outer}} for building a local
#' cost matrix with multivariate timeseries and custom distance functions.
#' @references Toni Giorgino. \emph{Computing and Visualizing Dynamic Time
#' Warping Alignments in R: The dtw Package.} Journal of Statistical Software,
#' 31(7), 1-24. \url{http://www.jstatsoft.org/v31/i07/} \cr \cr Tormene, P.;
#' Giorgino, T.; Quaglini, S. & Stefanelli, M. \emph{Matching incomplete time
#' series with dynamic time warping: an algorithm and an application to
#' post-stroke rehabilitation.} Artif Intell Med, 2009, 45, 11-34 \cr \cr
#' Rabiner, L. R., & Juang, B.-H. (1993). Chapter 4 in \emph{Fundamentals of
#' speech recognition.} Englewood Cliffs, NJ: Prentice Hall.
#' @keywords package ts
#' @import proxy
#' @examples
#' 
#'  library(dtw);
#'  ## demo(dtw);
#' 
NULL



.onAttach <- function(lib, pkg)  {
    
    packageStartupMessage(sprintf("Loaded dtw v%s. See ?dtw for help, citation(\"dtw\") for use in publication.\n",
                                  utils::packageDescription("dtw")$Version ) );
    
    ## Register DTW as a distance function into package proxy
    if(!proxy::pr_DB$entry_exists("DTW")) {
        proxy::pr_DB$set_entry(FUN=dtwpairdist, names=c("DTW","dtw"), 
                               loop=TRUE, type="metric",
                               description="Dynamic Time Warping",
                               reference="Giorgino T (2009). Computing and Visualizing Dynamic Time Warping Alignments in R: The dtw Package. Journal of Statistical Software, 31 (7), pp. 1--24. <URL: http://www.jstatsoft.org/v31/i07/>.",
                               formula="minimum of sum(x[xw[i]]-y[yw[i]]) over all monotonic xw, yw");
    }
    
    # invisible()
}