Nothing
#' @include distance.r
#' @include origin_methods.r
NULL
#' Public transportation network datasets from LinTim software (Integrated Optimization in Public Transportation)
#'
#' @name ptn-data
#' @rdname ptn-data
#' @docType data
#' @keywords data
#' @author Juliane Manitz and Jonas Harbering
#' @seealso \code{\link{delay-data}}
#'
#' @source Public transportation network datasets are extracted from LinTim software (Integrated Optimization in Public Transportation; \url{https://lintim.net/}). Special thanks to Anita Schoebel for making the data available.
NULL
#' \code{ptnAth} The data of the Athens Metro, consisting of 51 nodes and 52 edges.
#' \itemize{
#' \item Vertex attributes: station name, additonal station info.
#' \item Edge attributes: track length (in meter), minimal and maximal time required to pass the track (in minutes).
#' }
#'
#' @name ptnAth
#' @rdname ptn-data
#' @docType data
#' @keywords data
#' @source The Athens Metro data was collected by Konstantinos Gkoumas.
#'
#' @examples
#' # Athens metro system
#' data(ptnAth)
#' plot_ptn(ptnAth)
#'
NULL
#' \code{ptnGoe} The data of the Goettingen bus network, consisting of 257 nodes and 548 edges. \itemize{
#' \item Vertex attributes: station name.
#' \item Edge attributes: track length (in meter), minimal and maximal time required to pass the track (in minutes).
#' }
#'
#' @name ptnGoe
#' @rdname ptn-data
#' @docType data
#' @keywords data
#' @source The Goettingen bus network data was collected by Barbara Michalski.
#'
#' @examples
#' # Goettingen bus system
#' data(ptnGoe)
#' plot_ptn(ptnGoe)
#'
NULL
#' Delay propagation data examples simulated by LinTim software
#'
#' @name delay-data
#' @rdname delay-data
#' @docType data
#' @keywords data
#' @author Jonas Harbering
#' @seealso \code{\link{ptn-data}}
#'
#' @references Manitz, J., J. Harbering, M. Schmidt, T. Kneib, and A. Schoebel (2017): Source Estimation for Propagation Processes on Complex Networks with an Application to Delays in Public Transportation Systems. Journal of Royal Statistical Society C (Applied Statistics), 66: 521-536.
#'
#' @source Public transportation network datasets are generated by LinTim software (Integrated Optimization in Public Transportation; \url{https://lintim.net/}).
NULL
#' \code{delayAth} Delay propagation data generated on the Athens metro network by LinTim software
#'
#' @name delayAth
#' @rdname delay-data
#' @docType data
#' @keywords data
#'
#' @details \code{delayAth} Delay data on the Athens metro network. Propagation simulation under consideration of secruity distances and fixed-waiting time delay management. 'data.frame' with 510 observations (10 sequential time pictures for delay spreading pattern from 51 stations) of 53 variables (\code{k0} true source, \code{time}, delays at 51 stations).
#'
#' @import igraph
#'
#' @examples
#' \dontrun{
#' # compute effective distance
#' data(ptnAth)
#' athnet <- igraph::as_adjacency_matrix(ptnAth, sparse=FALSE)
#' p <- athnet/rowSums(athnet)
#' eff <- eff_dist(p)
#' # apply source estimation
# if (requireNamespace("plyr", quietly = TRUE)) {
#' data(delayAth)
#' res <- plyr::alply(.data=delayAth[,-c(1:2)], .margins=1, .fun=origin_edm, distance=eff,
#' silent=TRUE, .progress='text')
#' perfAth <- plyr::ldply(Map(performance, x = res, start = as.list(delayAth$k0),
#' list(graph = ptnAth)))
#' }
# }
NULL
#' \code{delayGoe} Delay propagation data generated on the Goettingen bus system by LinTim software
#'
#' @name delayGoe
#' @rdname delay-data
#' @docType data
#' @keywords data
#'
#' @details \code{delayGoe} Delay data on the directed Goettingen bus system. Progation simulation under consideration of secruity distances and fixed-waiting time delay management. 'data.frame' with 2570 observations (10 sequential time pictures for delay spreading pattern from 257 stations) of 259 variables (\code{k0} true source, \code{time}, delays at 257 stations).
#'
#' @import igraph plyr
#'
#' @examples
#' \dontrun{
#' # compute effective distance
#' data(ptnGoe)
#' goenet <- igraph::as_adjacency_matrix(ptnGoe, sparse=FALSE)
#' p <- goenet/rowSums(goenet)
#' eff <- eff_dist(p)
#' # apply source estimation
# if (requireNamespace("plyr", quietly = TRUE)) {
#' data(delayGoe)
#' res <- plyr::alply(.data=delayGoe[,-c(1:2)], .margins=1, .fun=origin_edm, distance=eff,
#' silent=TRUE, .progress='text')
#' perfGoe <- plyr::ldply(Map(performance, x = res, start = as.list(delayGoe$k0),
#' list(graph = ptnGoe)))
#' }
# }
NULL
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.