Nothing
R/Tags.R
In archivist: Tools for Storing, Restoring and Searching for R Objects
## archivist package for R
##
#' @title Tags
#'
#' @description
#' \code{Tags} are attributes of an artifact, i.e., a class, a name, names of artifact's parts, etc...
#' The list of artifact tags vary across artifact's classes.
#' To learn more about artifacts visit \link[archivist]{archivist-package}.
#'
#' @details
#'
#' \code{Tags} are attributes of an artifact. They can be the artifact's \code{name},
#' \code{class} or \code{archiving date}. Furthermore, for various artifact's classes
#' more different \code{Tags} are available.
#'
#' A \code{Tag} is represented as a string and usually has the following structure
#' \code{"TagKey:TagValue"}, e.g., \code{"name:iris"}.
#'
#' \code{Tags} are stored in the \link{Repository}. If data is extracted from an artifact
#' then a special \code{Tag}, named \code{relationWith} is created.
#' It specifies with which artifact this data is related to.
#'
#' The list of supported artifacts which are divided thematically is presented below.
#' The newest list is also available on \pkg{archivist} \code{wiki} on
#' \href{https://github.com/pbiecek/archivist/wiki/archivist-package---Tags}{{Github}}.
#'
#' Regression Models
#'
#' \describe{
#' \item{\code{lm}}{
#' \itemize{
#' \item name
#' \item class
#' \item coefname
#' \item rank
#' \item df.residual
#' \item date
#' }
#' }
#' \item{\code{summary.lm}}{
#' \itemize{
#' \item name
#' \item class
#' \item sigma
#' \item df
#' \item r.squared
#' \item adj.r.squared
#' \item fstatistic
#' \item fstatistic.df
#' \item date
#' }
#' }
#' \item{\code{glmnet}}{
#' \itemize{
#' \item name
#' \item class
#' \item dim
#' \item nulldev
#' \item npasses
#' \item offset
#' \item nobs
#' \item date
#' }
#' }
#' \item{\code{survfit}}{
#' \itemize{
#' \item name
#' \item class
#' \item n
#' \item type
#' \item conf.type
#' \item conf.int
#' \item strata
#' \item date
#' }
#' }
#' }
#' Plots
#'
#' \describe{
#' \item{\code{ggplot}}{
#' \itemize{
#' \item name
#' \item class
#' \item date
#' \item labelx
#' \item labely
#' }
#' }
#' \item{\code{trellis}}{
#' \itemize{
#' \item date
#' \item name
#' \item class
#' }
#' }
#' }
#' Results of Agglomeration Methods
#'
#' \describe{
#' \item{\code{twins which is a result of agnes, diana or mona functions}}{
#' \itemize{
#' \item date
#' \item name
#' \item class
#' \item ac
#' }
#' }
#' \item{\code{partition which is a result of pam, clara or fanny functions}}{
#' \itemize{
#' \item name
#' \item class
#' \item memb.exp
#' \item dunn_coeff
#' \item normalized dunn_coeff
#' \item k.crisp
#' \item objective
#' \item tolerance
#' \item iterations
#' \item converged
#' \item maxit
#' \item clus.avg.widths
#' \item avg.width
#' \item date
#' }
#' }
#' \item{\code{lda}}{
#' \itemize{
#' \item name
#' \item class
#' \item N
#' \item lev
#' \item counts
#' \item prior
#' \item svd
#' \item date
#' }
#' }
#' \item{\code{qda}}{
#' \itemize{
#' \item name
#' \item class
#' \item N
#' \item lev
#' \item counts
#' \item prior
#' \item ldet
#' \item terms
#' \item date
#' }
#' }
#' }
#' Statistical Tests
#'
#' \describe{
#' \item{\code{htest}}{
#' \itemize{
#' \item name
#' \item class
#' \item method
#' \item data.name
#' \item null.value
#' \item alternative
#' \item statistic
#' \item parameter
#' \item p.value
#' \item conf.int.
#' \item estimate
#' \item date
#' }
#' }
#' }
#'
#' When none of above is specified, Tags are assigned by default
#'
#' \describe{
#' \item{\code{default}}{
#' \itemize{
#' \item name
#' \item class
#' \item date
#' }
#' }
#' \item{\code{data.frame}}{
#' \itemize{
#' \item name
#' \item class
#' \item date
#' \item varname
#' }
#' }
#' }
#'
#' @seealso
#' Functions using \code{Tags} are:
#' \itemize{
#' \item \link{addTagsRepo}
#' \item \link{getTagsLocal}
#' \item \link{getTagsRemote}
#' \item \link{saveToLocalRepo}
#' \item \link{searchInLocalRepo},
#' \item \link{searchInRemoteRepo}.
#' }
#'
#' @template roxlate-references
#' @template roxlate-contact
#' @note
#' In the following way one can specify his own \code{Tags} for artifacts by
#' setting artifact's attribute before call of the \code{saveToLocalRepo} function:
#' \code{attr(x, "tags" ) = c( "name1", "name2" )}, where \code{x} is an artifact
#' and \code{name1, name2} are \code{Tags} specified by a user.
#' It can be also done in a new, simpler way by using \code{userTags} parameter like this:
#' \itemize{
#' \item \code{saveToLocalRepo(model, repoDir, userTags = c("my_model", "do not delete"))}.
#' }
#' Specifing additional \code{Tags} by attributes can be beneficial when one uses \link{addHooksToPrint}.
#'
#' @examples
#'
#' \dontrun{
#' # examples
#' # data.frame object
#' data(iris)
#' exampleRepoDir <- tempfile()
#' createLocalRepo(repoDir = exampleRepoDir)
#' saveToLocalRepo( iris, repoDir=exampleRepoDir )
#' showLocalRepo( exampleRepoDir, "tags" )
#' deleteLocalRepo( exampleRepoDir, deleteRoot=TRUE )
#'
#' # ggplot/gg object
#' library(ggplot2)
#' df <- data.frame(gp = factor(rep(letters[1:3], each = 10)),y = rnorm(30))
#' library(plyr)
#' ds <- ddply(df, .(gp), summarise, mean = mean(y), sd = sd(y))
#' myplot123 <- ggplot(df, aes(x = gp, y = y)) +
#' geom_point() + geom_point(data = ds, aes(y = mean),
#' colour = 'red', size = 3)
#' exampleRepoDir <- tempfile()
#' createLocalRepo( repoDir = exampleRepoDir )
#' saveToLocalRepo( myplot123, repoDir=exampleRepoDir )
#' showLocalRepo( exampleRepoDir, "tags" )
#' deleteLocalRepo( exampleRepoDir, deleteRoot=TRUE )
#'
#' # lm object
#' model <- lm(Sepal.Length~ Sepal.Width + Petal.Length + Petal.Width,
#' data= iris)
#' exampleRepoDir <- tempfile()
#' createLocalRepo( repoDir = exampleRepoDir )
#' asave( model, repoDir=exampleRepoDir )
#' showLocalRepo( exampleRepoDir, "tags" )
#' deleteLocalRepo( exampleRepoDir, TRUE )
#'
#' # agnes (twins) object
#' library(cluster)
#' data(votes.repub)
#' agn1 <- agnes(votes.repub, metric = "manhattan", stand = TRUE)
#' exampleRepoDir <- tempfile()
#' createLocalRepo( repoDir = exampleRepoDir )
#' saveToLocalRepo( agn1, repoDir=exampleRepoDir )
#' showLocalRepo( exampleRepoDir, "tags" )
#' deleteLocalRepo( exampleRepoDir, TRUE )
#'
#' # fanny (partition) object
#' x <- rbind(cbind(rnorm(10, 0, 0.5), rnorm(10, 0, 0.5)),
#' cbind(rnorm(15, 5, 0.5), rnorm(15, 5, 0.5)),
#' cbind(rnorm( 3,3.2,0.5), rnorm( 3,3.2,0.5)))
#' fannyx <- fanny(x, 2)
#' exampleRepoDir <- tempfile()
#' createLocalRepo( repoDir = exampleRepoDir )
#' saveToLocalRepo( fannyx, repoDir=exampleRepoDir )
#' showLocalRepo( exampleRepoDir, "tags" )
#' deleteLocalRepo( exampleRepoDir, TRUE )
#'
#' # lda object
#' library(MASS)
#'
#' Iris <- data.frame(rbind(iris3[,,1], iris3[,,2], iris3[,,3]),
#' Sp = rep(c("s","c","v"), rep(50,3)))
#' train <- c(8,83,115,118,146,82,76,9,70,139,85,59,78,143,68,
#' 134,148,12,141,101,144,114,41,95,61,128,2,42,37,
#' 29,77,20,44,98,74,32,27,11,49,52,111,55,48,33,38,
#' 113,126,24,104,3,66,81,31,39,26,123,18,108,73,50,
#' 56,54,65,135,84,112,131,60,102,14,120,117,53,138,5)
#' lda1 <- lda(Sp ~ ., Iris, prior = c(1,1,1)/3, subset = train)
#' exampleRepoDir <- tempfile()
#' createLocalRepo( repoDir = exampleRepoDir )
#' asave( lda1, repoDir=exampleRepoDir )
#' showLocalRepo( exampleRepoDir, "tags" )
#' deleteLocalRepo( exampleRepoDir, TRUE )
#'
#' # qda object
#' tr <- c(7,38,47,43,20,37,44,22,46,49,50,19,4,32,12,29,27,34,2,1,17,13,3,35,36)
#' train <- rbind(iris3[tr,,1], iris3[tr,,2], iris3[tr,,3])
#' cl <- factor(c(rep("s",25), rep("c",25), rep("v",25)))
#' qda1 <- qda(train, cl)
#' exampleRepoDir <- tempfile()
#' createLocalRepo( repoDir = exampleRepoDir )
#' saveToLocalRepo( qda1, repoDir=exampleRepoDir )
#' showLocalRepo( exampleRepoDir, "tags" )
#' deleteLocalRepo( exampleRepoDir, TRUE )
#'
#'
#' # glmnet object
#' library( glmnet )
#'
#' zk=matrix(rnorm(100*20),100,20)
#' bk=rnorm(100)
#' glmnet1=glmnet(zk,bk)
#' exampleRepoDir <- tempfile()
#' createLocalRepo( repoDir = exampleRepoDir )
#' saveToLocalRepo( glmnet1, repoDir=exampleRepoDir )
#' showLocalRepo( exampleRepoDir, "tags" )
#' deleteLocalRepo( exampleRepoDir, TRUE )
#'
#' # trellis object
#' require(stats)
#' library( lattice)
#' ## Tonga Trench Earthquakes
#'
#' Depth <- equal.count(quakes$depth, number=8, overlap=.1)
#' xyplot(lat ~ long | Depth, data = quakes)
#' update(trellis.last.object(),
#' strip = strip.custom(strip.names = TRUE, strip.levels = TRUE),
#' par.strip.text = list(cex = 0.75),
#' aspect = "iso")
#'
#' ## Examples with data from `Visualizing Data' (Cleveland, 1993) obtained
#' ## from http://cm.bell-labs.com/cm/ms/departments/sia/wsc/
#'
#' EE <- equal.count(ethanol$E, number=9, overlap=1/4)
#'
#' ## Constructing panel functions on the run; prepanel
#' trellis.plot <- xyplot(NOx ~ C | EE, data = ethanol,
#' prepanel = function(x, y) prepanel.loess(x, y, span = 1),
#' xlab = "Compression Ratio", ylab = "NOx (micrograms/J)",
#' panel = function(x, y) {
#' panel.grid(h = -1, v = 2)
#' panel.xyplot(x, y)
#' panel.loess(x, y, span=1)
#' },
#' aspect = "xy")
#' exampleRepoDir <- tempfile()
#' createLocalRepo( repoDir = exampleRepoDir )
#' saveToLocalRepo( trellis.plot, repoDir=exampleRepoDir )
#' showLocalRepo( exampleRepoDir, "tags" )
#' deleteLocalRepo( exampleRepoDir, TRUE )
#'
#' # htest object
#'
#' x <- c(1.83, 0.50, 1.62, 2.48, 1.68, 1.88, 1.55, 3.06, 1.30)
#' y <- c(0.878, 0.647, 0.598, 2.05, 1.06, 1.29, 1.06, 3.14, 1.29)
#' this.test <- wilcox.test(x, y, paired = TRUE, alternative = "greater")
#' exampleRepoDir <- tempfile()
#' createLocalRepo( repoDir = exampleRepoDir )
#' saveToLocalRepo( this.test, repoDir=exampleRepoDir )
#' showLocalRepo( exampleRepoDir, "tags" )
#' deleteLocalRepo( exampleRepoDir, TRUE )
#'
#' # survfit object
#' library( survival )
#' # Create the simplest test data set
#' test1 <- list(time=c(4,3,1,1,2,2,3),
#' status=c(1,1,1,0,1,1,0),
#' x=c(0,2,1,1,1,0,0),
#' sex=c(0,0,0,0,1,1,1))
#' # Fit a stratified model
#' myFit <- survfit( coxph(Surv(time, status) ~ x + strata(sex), test1), data = test1 )
#' exampleRepoDir <- tempfile()
#' createLocalRepo( repoDir = exampleRepoDir )
#' saveToLocalRepo( myFit , repoDir=exampleRepoDir )
#' showLocalRepo( exampleRepoDir, "tags" )[,-3]
#' deleteLocalRepo( exampleRepoDir, TRUE)
#'
#' # origin of the artifacts stored as a name - chaining code
#' library(dplyr)
#' exampleRepoDir <- tempfile()
#' createLocalRepo( repoDir = exampleRepoDir )
#' data("hflights", package = "hflights")
#' hflights %>%
#' group_by(Year, Month, DayofMonth) %>%
#' select(Year:DayofMonth, ArrDelay, DepDelay) %>%
#' saveToLocalRepo( exampleRepoDir, value = TRUE ) %>%
#' # here the artifact is stored but chaining is not finished
#' summarise(
#' arr = mean(ArrDelay, na.rm = TRUE),
#' dep = mean(DepDelay, na.rm = TRUE)
#' ) %>%
#' filter(arr > 30 | dep > 30) %>%
#' saveToLocalRepo( exampleRepoDir )
#' # chaining code is finished and after last operation the
#' # artifact is stored
#' showLocalRepo( exampleRepoDir, "tags" )[,-3]
#' showLocalRepo( exampleRepoDir )
#' deleteLocalRepo( exampleRepoDir, TRUE)
#'
#' rm( exampleRepoDir )
#' }
#' @family archivist
#' @name Tags
#' @docType class
invisible(NULL)
Try the archivist package in your browser
Any scripts or data that you put into this service are public.
archivist documentation built on May 20, 2021, 5:08 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
## archivist package for R
##
#' @title Tags
#'
#' @description
#' \code{Tags} are attributes of an artifact, i.e., a class, a name, names of artifact's parts, etc...
#' The list of artifact tags vary across artifact's classes.
#' To learn more about artifacts visit \link[archivist]{archivist-package}.
#'
#' @details
#'
#' \code{Tags} are attributes of an artifact. They can be the artifact's \code{name},
#' \code{class} or \code{archiving date}. Furthermore, for various artifact's classes
#' more different \code{Tags} are available.
#'
#' A \code{Tag} is represented as a string and usually has the following structure
#' \code{"TagKey:TagValue"}, e.g., \code{"name:iris"}.
#'
#' \code{Tags} are stored in the \link{Repository}. If data is extracted from an artifact
#' then a special \code{Tag}, named \code{relationWith} is created.
#' It specifies with which artifact this data is related to.
#'
#' The list of supported artifacts which are divided thematically is presented below.
#' The newest list is also available on \pkg{archivist} \code{wiki} on
#' \href{https://github.com/pbiecek/archivist/wiki/archivist-package---Tags}{{Github}}.
#'
#' Regression Models
#'
#' \describe{
#' \item{\code{lm}}{
#' \itemize{
#' \item name
#' \item class
#' \item coefname
#' \item rank
#' \item df.residual
#' \item date
#' }
#' }
#' \item{\code{summary.lm}}{
#' \itemize{
#' \item name
#' \item class
#' \item sigma
#' \item df
#' \item r.squared
#' \item adj.r.squared
#' \item fstatistic
#' \item fstatistic.df
#' \item date
#' }
#' }
#' \item{\code{glmnet}}{
#' \itemize{
#' \item name
#' \item class
#' \item dim
#' \item nulldev
#' \item npasses
#' \item offset
#' \item nobs
#' \item date
#' }
#' }
#' \item{\code{survfit}}{
#' \itemize{
#' \item name
#' \item class
#' \item n
#' \item type
#' \item conf.type
#' \item conf.int
#' \item strata
#' \item date
#' }
#' }
#' }
#' Plots
#'
#' \describe{
#' \item{\code{ggplot}}{
#' \itemize{
#' \item name
#' \item class
#' \item date
#' \item labelx
#' \item labely
#' }
#' }
#' \item{\code{trellis}}{
#' \itemize{
#' \item date
#' \item name
#' \item class
#' }
#' }
#' }
#' Results of Agglomeration Methods
#'
#' \describe{
#' \item{\code{twins which is a result of agnes, diana or mona functions}}{
#' \itemize{
#' \item date
#' \item name
#' \item class
#' \item ac
#' }
#' }
#' \item{\code{partition which is a result of pam, clara or fanny functions}}{
#' \itemize{
#' \item name
#' \item class
#' \item memb.exp
#' \item dunn_coeff
#' \item normalized dunn_coeff
#' \item k.crisp
#' \item objective
#' \item tolerance
#' \item iterations
#' \item converged
#' \item maxit
#' \item clus.avg.widths
#' \item avg.width
#' \item date
#' }
#' }
#' \item{\code{lda}}{
#' \itemize{
#' \item name
#' \item class
#' \item N
#' \item lev
#' \item counts
#' \item prior
#' \item svd
#' \item date
#' }
#' }
#' \item{\code{qda}}{
#' \itemize{
#' \item name
#' \item class
#' \item N
#' \item lev
#' \item counts
#' \item prior
#' \item ldet
#' \item terms
#' \item date
#' }
#' }
#' }
#' Statistical Tests
#'
#' \describe{
#' \item{\code{htest}}{
#' \itemize{
#' \item name
#' \item class
#' \item method
#' \item data.name
#' \item null.value
#' \item alternative
#' \item statistic
#' \item parameter
#' \item p.value
#' \item conf.int.
#' \item estimate
#' \item date
#' }
#' }
#' }
#'
#' When none of above is specified, Tags are assigned by default
#'
#' \describe{
#' \item{\code{default}}{
#' \itemize{
#' \item name
#' \item class
#' \item date
#' }
#' }
#' \item{\code{data.frame}}{
#' \itemize{
#' \item name
#' \item class
#' \item date
#' \item varname
#' }
#' }
#' }
#'
#' @seealso
#' Functions using \code{Tags} are:
#' \itemize{
#' \item \link{addTagsRepo}
#' \item \link{getTagsLocal}
#' \item \link{getTagsRemote}
#' \item \link{saveToLocalRepo}
#' \item \link{searchInLocalRepo},
#' \item \link{searchInRemoteRepo}.
#' }
#'
#' @template roxlate-references
#' @template roxlate-contact
#' @note
#' In the following way one can specify his own \code{Tags} for artifacts by
#' setting artifact's attribute before call of the \code{saveToLocalRepo} function:
#' \code{attr(x, "tags" ) = c( "name1", "name2" )}, where \code{x} is an artifact
#' and \code{name1, name2} are \code{Tags} specified by a user.
#' It can be also done in a new, simpler way by using \code{userTags} parameter like this:
#' \itemize{
#' \item \code{saveToLocalRepo(model, repoDir, userTags = c("my_model", "do not delete"))}.
#' }
#' Specifing additional \code{Tags} by attributes can be beneficial when one uses \link{addHooksToPrint}.
#'
#' @examples
#'
#' \dontrun{
#' # examples
#' # data.frame object
#' data(iris)
#' exampleRepoDir <- tempfile()
#' createLocalRepo(repoDir = exampleRepoDir)
#' saveToLocalRepo( iris, repoDir=exampleRepoDir )
#' showLocalRepo( exampleRepoDir, "tags" )
#' deleteLocalRepo( exampleRepoDir, deleteRoot=TRUE )
#'
#' # ggplot/gg object
#' library(ggplot2)
#' df <- data.frame(gp = factor(rep(letters[1:3], each = 10)),y = rnorm(30))
#' library(plyr)
#' ds <- ddply(df, .(gp), summarise, mean = mean(y), sd = sd(y))
#' myplot123 <- ggplot(df, aes(x = gp, y = y)) +
#' geom_point() + geom_point(data = ds, aes(y = mean),
#' colour = 'red', size = 3)
#' exampleRepoDir <- tempfile()
#' createLocalRepo( repoDir = exampleRepoDir )
#' saveToLocalRepo( myplot123, repoDir=exampleRepoDir )
#' showLocalRepo( exampleRepoDir, "tags" )
#' deleteLocalRepo( exampleRepoDir, deleteRoot=TRUE )
#'
#' # lm object
#' model <- lm(Sepal.Length~ Sepal.Width + Petal.Length + Petal.Width,
#' data= iris)
#' exampleRepoDir <- tempfile()
#' createLocalRepo( repoDir = exampleRepoDir )
#' asave( model, repoDir=exampleRepoDir )
#' showLocalRepo( exampleRepoDir, "tags" )
#' deleteLocalRepo( exampleRepoDir, TRUE )
#'
#' # agnes (twins) object
#' library(cluster)
#' data(votes.repub)
#' agn1 <- agnes(votes.repub, metric = "manhattan", stand = TRUE)
#' exampleRepoDir <- tempfile()
#' createLocalRepo( repoDir = exampleRepoDir )
#' saveToLocalRepo( agn1, repoDir=exampleRepoDir )
#' showLocalRepo( exampleRepoDir, "tags" )
#' deleteLocalRepo( exampleRepoDir, TRUE )
#'
#' # fanny (partition) object
#' x <- rbind(cbind(rnorm(10, 0, 0.5), rnorm(10, 0, 0.5)),
#' cbind(rnorm(15, 5, 0.5), rnorm(15, 5, 0.5)),
#' cbind(rnorm( 3,3.2,0.5), rnorm( 3,3.2,0.5)))
#' fannyx <- fanny(x, 2)
#' exampleRepoDir <- tempfile()
#' createLocalRepo( repoDir = exampleRepoDir )
#' saveToLocalRepo( fannyx, repoDir=exampleRepoDir )
#' showLocalRepo( exampleRepoDir, "tags" )
#' deleteLocalRepo( exampleRepoDir, TRUE )
#'
#' # lda object
#' library(MASS)
#'
#' Iris <- data.frame(rbind(iris3[,,1], iris3[,,2], iris3[,,3]),
#' Sp = rep(c("s","c","v"), rep(50,3)))
#' train <- c(8,83,115,118,146,82,76,9,70,139,85,59,78,143,68,
#' 134,148,12,141,101,144,114,41,95,61,128,2,42,37,
#' 29,77,20,44,98,74,32,27,11,49,52,111,55,48,33,38,
#' 113,126,24,104,3,66,81,31,39,26,123,18,108,73,50,
#' 56,54,65,135,84,112,131,60,102,14,120,117,53,138,5)
#' lda1 <- lda(Sp ~ ., Iris, prior = c(1,1,1)/3, subset = train)
#' exampleRepoDir <- tempfile()
#' createLocalRepo( repoDir = exampleRepoDir )
#' asave( lda1, repoDir=exampleRepoDir )
#' showLocalRepo( exampleRepoDir, "tags" )
#' deleteLocalRepo( exampleRepoDir, TRUE )
#'
#' # qda object
#' tr <- c(7,38,47,43,20,37,44,22,46,49,50,19,4,32,12,29,27,34,2,1,17,13,3,35,36)
#' train <- rbind(iris3[tr,,1], iris3[tr,,2], iris3[tr,,3])
#' cl <- factor(c(rep("s",25), rep("c",25), rep("v",25)))
#' qda1 <- qda(train, cl)
#' exampleRepoDir <- tempfile()
#' createLocalRepo( repoDir = exampleRepoDir )
#' saveToLocalRepo( qda1, repoDir=exampleRepoDir )
#' showLocalRepo( exampleRepoDir, "tags" )
#' deleteLocalRepo( exampleRepoDir, TRUE )
#'
#'
#' # glmnet object
#' library( glmnet )
#'
#' zk=matrix(rnorm(100*20),100,20)
#' bk=rnorm(100)
#' glmnet1=glmnet(zk,bk)
#' exampleRepoDir <- tempfile()
#' createLocalRepo( repoDir = exampleRepoDir )
#' saveToLocalRepo( glmnet1, repoDir=exampleRepoDir )
#' showLocalRepo( exampleRepoDir, "tags" )
#' deleteLocalRepo( exampleRepoDir, TRUE )
#'
#' # trellis object
#' require(stats)
#' library( lattice)
#' ## Tonga Trench Earthquakes
#'
#' Depth <- equal.count(quakes$depth, number=8, overlap=.1)
#' xyplot(lat ~ long | Depth, data = quakes)
#' update(trellis.last.object(),
#' strip = strip.custom(strip.names = TRUE, strip.levels = TRUE),
#' par.strip.text = list(cex = 0.75),
#' aspect = "iso")
#'
#' ## Examples with data from `Visualizing Data' (Cleveland, 1993) obtained
#' ## from http://cm.bell-labs.com/cm/ms/departments/sia/wsc/
#'
#' EE <- equal.count(ethanol$E, number=9, overlap=1/4)
#'
#' ## Constructing panel functions on the run; prepanel
#' trellis.plot <- xyplot(NOx ~ C | EE, data = ethanol,
#' prepanel = function(x, y) prepanel.loess(x, y, span = 1),
#' xlab = "Compression Ratio", ylab = "NOx (micrograms/J)",
#' panel = function(x, y) {
#' panel.grid(h = -1, v = 2)
#' panel.xyplot(x, y)
#' panel.loess(x, y, span=1)
#' },
#' aspect = "xy")
#' exampleRepoDir <- tempfile()
#' createLocalRepo( repoDir = exampleRepoDir )
#' saveToLocalRepo( trellis.plot, repoDir=exampleRepoDir )
#' showLocalRepo( exampleRepoDir, "tags" )
#' deleteLocalRepo( exampleRepoDir, TRUE )
#'
#' # htest object
#'
#' x <- c(1.83, 0.50, 1.62, 2.48, 1.68, 1.88, 1.55, 3.06, 1.30)
#' y <- c(0.878, 0.647, 0.598, 2.05, 1.06, 1.29, 1.06, 3.14, 1.29)
#' this.test <- wilcox.test(x, y, paired = TRUE, alternative = "greater")
#' exampleRepoDir <- tempfile()
#' createLocalRepo( repoDir = exampleRepoDir )
#' saveToLocalRepo( this.test, repoDir=exampleRepoDir )
#' showLocalRepo( exampleRepoDir, "tags" )
#' deleteLocalRepo( exampleRepoDir, TRUE )
#'
#' # survfit object
#' library( survival )
#' # Create the simplest test data set
#' test1 <- list(time=c(4,3,1,1,2,2,3),
#' status=c(1,1,1,0,1,1,0),
#' x=c(0,2,1,1,1,0,0),
#' sex=c(0,0,0,0,1,1,1))
#' # Fit a stratified model
#' myFit <- survfit( coxph(Surv(time, status) ~ x + strata(sex), test1), data = test1 )
#' exampleRepoDir <- tempfile()
#' createLocalRepo( repoDir = exampleRepoDir )
#' saveToLocalRepo( myFit , repoDir=exampleRepoDir )
#' showLocalRepo( exampleRepoDir, "tags" )[,-3]
#' deleteLocalRepo( exampleRepoDir, TRUE)
#'
#' # origin of the artifacts stored as a name - chaining code
#' library(dplyr)
#' exampleRepoDir <- tempfile()
#' createLocalRepo( repoDir = exampleRepoDir )
#' data("hflights", package = "hflights")
#' hflights %>%
#' group_by(Year, Month, DayofMonth) %>%
#' select(Year:DayofMonth, ArrDelay, DepDelay) %>%
#' saveToLocalRepo( exampleRepoDir, value = TRUE ) %>%
#' # here the artifact is stored but chaining is not finished
#' summarise(
#' arr = mean(ArrDelay, na.rm = TRUE),
#' dep = mean(DepDelay, na.rm = TRUE)
#' ) %>%
#' filter(arr > 30 | dep > 30) %>%
#' saveToLocalRepo( exampleRepoDir )
#' # chaining code is finished and after last operation the
#' # artifact is stored
#' showLocalRepo( exampleRepoDir, "tags" )[,-3]
#' showLocalRepo( exampleRepoDir )
#' deleteLocalRepo( exampleRepoDir, TRUE)
#'
#' rm( exampleRepoDir )
#' }
#' @family archivist
#' @name Tags
#' @docType class
invisible(NULL)
Try the archivist package in your browser
Any scripts or data that you put into this service are public.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.