version 0.8.1

Author: maraab23

DESCRIPTION

@@ -1,33 +1,34 @@
 Package: ggseqplot
 Title: Render Sequence Plots using 'ggplot2'
-Version: 0.8.0
+Version: 0.8.1
 Authors@R: 
   person("Marcel", "Raab", , "marcel.raab@gmail.com", role = c("aut", "cre"),
          comment = c(ORCID = "0000-0002-3097-1591"))
-Description: A set of wrapper functions that mainly re-produces some of the 
-  sequence plots rendered with TraMineR::seqplot() and 'TraMineRextras'. 
-  Whereas 'TraMineR' uses base R to produce the plots this library draws on 
-  'ggplot2'. The plots are produced on the basis of a sequence object defined  
+Description: A set of wrapper functions that mainly re-produces most of the 
+  sequence plots rendered with TraMineR::seqplot(). Whereas 'TraMineR' uses base 
+  R to produce the plots this library draws on 'ggplot2'. 
+  The plots are produced on the basis of a sequence object defined  
   with TraMineR::seqdef(). The package automates the reshaping and plotting 
   of sequence data. Resulting plots are of class 'ggplot', i.e. components 
   can be added and tweaked using '+' and regular 'ggplot2' functions. 
 URL: https://maraab23.github.io/ggseqplot/,
         https://github.com/maraab23/ggseqplot
 BugReports: https://github.com/maraab23/ggseqplot/issues
-Depends: R (>= 4.1.0), TraMineR (>= 2.2-5)
+Depends: R (>= 4.1.0)
 License: GPL (>= 3)
 Encoding: UTF-8
 RoxygenNote: 7.2.1
 RdMacros: Rdpack
 Imports: colorspace, dplyr, forcats, ggh4x, ggplot2, ggrepel, ggtext,
-        glue, patchwork, purrr, Rdpack, tidyr, usethis
+        glue, patchwork, purrr, Rdpack, tidyr, TraMineR (>= 2.2-5),
+        usethis
 Suggests: covr, ggthemes, hrbrthemes, knitr, rmarkdown, testthat (>=
-        3.0.0), TraMineRextras
+        3.0.0)
 VignetteBuilder: knitr
 Config/testthat/edition: 3
 NeedsCompilation: no
-Packaged: 2022-09-07 19:45:48 UTC; ba3gh6
+Packaged: 2022-10-11 09:58:49 UTC; ba3gh6
 Author: Marcel Raab [aut, cre] (<https://orcid.org/0000-0002-3097-1591>)
 Maintainer: Marcel Raab <marcel.raab@gmail.com>
 Repository: CRAN
-Date/Publication: 2022-09-07 20:00:02 UTC
+Date/Publication: 2022-10-11 10:32:33 UTC

MD5

@@ -1,26 +1,26 @@
-a73605b45c0ef96bbe15c8003350b1f5 *DESCRIPTION
+9f793cacbb26e74abd6552f07f465025 *DESCRIPTION
 3a225b00b6b454cd7cc9982a22de5792 *NAMESPACE
-a1aa77054e7ab5cfb48bf8a6209d47b3 *NEWS.md
-cb3ad8305001ff158eb534634183890f *R/ggseqdplot.R
-5718499a91eade80422d1e040e84bbef *R/ggseqeplot.R
-392e407163d9e99645ee4d88d5415bfe *R/ggseqfplot.R
-4360337f6a6060ed5d31aa8b4af58582 *R/ggseqiplot.R
-c226da4f73415c37e164b056696d84af *R/ggseqmsplot.R
-3e5f0fc7fc8e9584a4b22062a1bb6e64 *R/ggseqmtplot.R
+31c5e6f7df7c7dbc4ddcdb25895fe259 *NEWS.md
+355695c5db7de1a8d7fbd2831553b8e2 *R/ggseqdplot.R
+0d41f3bb70d0170fb924842bed91741a *R/ggseqeplot.R
+644a2db1a57b7f7e3c2ef9abf958ab6c *R/ggseqfplot.R
+58053a1e07e548fedc31a2a8d8a1d080 *R/ggseqiplot.R
+996f614af557f14afc9e61833e08d459 *R/ggseqmsplot.R
+f767487a8f3d26ec469fdf7b3e31e97d *R/ggseqmtplot.R
 bee42aca8ac767a7de5732c8ff83eb97 *R/ggseqplot-package.R
-029fa7baba56aa1b5ddc072caa1e6d08 *R/ggseqrfplot.R
-11f8fa534ab078289d74774b3edd619b *R/ggseqrplot.R
-97c9aa77dc147159e8d3cb17af76acc0 *R/ggseqtrplot.R
+10c0581fdd36b5480d6de93772fb908f *R/ggseqrfplot.R
+234cf07c88e955b5ba47409ba5f2ff40 *R/ggseqrplot.R
+1677c4c5f8054d10f3ea3782321728ff *R/ggseqtrplot.R
 f3590a408dfcd78fcc58db1bd0574593 *R/internal_helpers.R
-655a94ea4bd67eda129b5520fb603e95 *R/zzz.R
-b594f437bd9788b2b686b2f3d23ebd6c *README.md
-349b7a4af047f94ca891988ac1fd50d9 *build/partial.rdb
+758a9bb682b1f55a5c188f2399245747 *R/zzz.R
+c8964244610ec8c6b6e17fd4fea268c7 *README.md
+ce38627d4a38a00cce7c1ce6c1185740 *build/partial.rdb
 3f4888d915d1e61bd3e4b47e46f5794b *build/vignette.rds
 e8c9fc7adf4763c9fb311e84c0480ad9 *inst/CITATION
 d975bd9930cfa30644934bb7359e30ba *inst/REFERENCES.bib
-f0f11a7c6f39f3a055312b48313487cf *inst/doc/ggseqplot.R
-38700f90d7b71ff7b906bc2eff81f5dd *inst/doc/ggseqplot.Rmd
-d0063786bc1e5397155e265c313e47c7 *inst/doc/ggseqplot.html
+0581ca6fb324a60879a4719f42ce754c *inst/doc/ggseqplot.R
+4dca36d1ecddcb57957ce43a17dd487f *inst/doc/ggseqplot.Rmd
+c2a36b34af9b34fcd41b08e30ff973d8 *inst/doc/ggseqplot.html
 441fb46be1612086d7ea49567c01fa0f *man/figures/README-ggseqdplot1-1.png
 fa6ecb6406f222a8c7f18832fda9ac59 *man/figures/README-ggseqdplot2-1.png
 2b4ccbde4e94508ecb42516330971d2d *man/figures/README-ggseqeplot1-1.png
@@ -36,26 +36,27 @@ e4bdee6ea6dc7db8b9c8e58043b8e5bc *man/figures/README-seqiplot2-1.png
 e4110e018e5be64b02a72c36eaad72c5 *man/figures/README-seqiplot3-1.png
 0e555a91e15ff18516b7f9bf2410f950 *man/figures/README-seqplot.rf1-1.png
 d4852713e6dd16952596233d7cb79262 *man/figures/logo.png
-c2a3ef62d374ea4fc7568606780b20ea *man/ggseqdplot.Rd
-1085ff80f1f7dcea9d8c2cefb02bc133 *man/ggseqeplot.Rd
-d808f979f177c720eeb1aed2f3c9c203 *man/ggseqfplot.Rd
-81dd6de92b6e94e420ba633c7be40c79 *man/ggseqiplot.Rd
-077694c4d057cf51ec5b291dd18abe81 *man/ggseqmsplot.Rd
-6a181ad240812d397661f1fe909e2944 *man/ggseqmtplot.Rd
-1bc50da44f62118718fe03a33ebe14c4 *man/ggseqplot-package.Rd
-cc902a8d8c3cf46e4c4f2c3c3f4df21d *man/ggseqrfplot.Rd
-8ddf7a89226f825e032aefabe592ff2c *man/ggseqrplot.Rd
-51b9fa5e7d5779fdc24ff6e239c0ef99 *man/ggseqtrplot.Rd
+b9274dfdfdecfbd570f7327b6fc0dca0 *man/ggseqdplot.Rd
+9e44b439f7c6e0a4440e5f1d03fbf3d5 *man/ggseqeplot.Rd
+4f5918af38c348e4b77acd9dc99929d5 *man/ggseqfplot.Rd
+541f306580ee3f46c484b861517146fb *man/ggseqiplot.Rd
+0461e17bb1624439fd755efdd53fe4e8 *man/ggseqmsplot.Rd
+ab9df37d2cc134e68e305446d1ba04f7 *man/ggseqmtplot.Rd
+175c60be86072261cff04c2814a5957d *man/ggseqplot-package.Rd
+5b16836ee5c89cc6b7a18a88ed03c1a0 *man/ggseqrfplot.Rd
+b6e41df2ed2744e34e859e80f764c768 *man/ggseqrplot.Rd
+534f36d5ab43019d5bb787e81d7f8f8a *man/ggseqtrplot.Rd
 3bc2a687a7d1df2f3288d53ad3b62a9e *tests/testthat.R
-b5d90965b80d859637ca94f31f99f807 *tests/testthat/test-ggseqdplot.R
-6bb16ff9ced511073eaca921fbabcc69 *tests/testthat/test-ggseqeplot.R
-65cab8175cc36f6d5ed0a50b634fbc66 *tests/testthat/test-ggseqfplot.R
-82e416b70167aaf609843b6f904c81fc *tests/testthat/test-ggseqiplot.R
-da195e84dca3b9bd4f7512f5d2bd0ca7 *tests/testthat/test-ggseqmsplot.R
-c8df0c866c725b36bd0de8c52cc7f01d *tests/testthat/test-ggseqmtplot.R
-7c1f59253b80c36adba331d2f9efdcce *tests/testthat/test-ggseqrfplot.R
-e160b0a4ee91add24d54b7d714a940c1 *tests/testthat/test-ggseqrplot.R
-8dfbc6ca4919157149176121a8edfa86 *tests/testthat/test-ggseqtrplot.R
+0e6d216e4c32c05c2052f4e9c8cd84bc *tests/testthat/test-ggseqdplot.R
+33bdb36141ee40ed0e424552b948115c *tests/testthat/test-ggseqeplot.R
+b22c2d5586ffccd1c1d4bbf91eec3ecc *tests/testthat/test-ggseqfplot.R
+4ea8ba616f00ce90fbaeb2169c92038f *tests/testthat/test-ggseqiplot.R
+9d34ed07d284c1afb7ba816fc0f1833f *tests/testthat/test-ggseqmsplot.R
+e05e27256db2f56f50ed52cefc570f38 *tests/testthat/test-ggseqmtplot.R
+a568b1cad477ce67178d2669f1c76842 *tests/testthat/test-ggseqrfplot.R
+0f459b5e95d0d4ec711111d3445fb088 *tests/testthat/test-ggseqrplot.R
+6ceba1964e4a1221c6efdc3c57c632e6 *tests/testthat/test-ggseqtrplot.R
 a4b5f30fd19f2de28f0cd30c893efbf2 *tests/testthat/test-internal_helper.R
-38700f90d7b71ff7b906bc2eff81f5dd *vignettes/ggseqplot.Rmd
+3163a0d1c73e1c77762ce0fea5020b02 *vignettes/apa.csl
+4dca36d1ecddcb57957ce43a17dd487f *vignettes/ggseqplot.Rmd
 f5dd7b005604e4fad4ba0d642598e54c *vignettes/references.bib

NEWS.md

@@ -1,3 +1,10 @@
+# ggseqplot 0.8.1
+
+* reverted TraMiner to Import 
+* removed unnecessary Suggests from TraMineRextras
+* revised vignette, tests, and documentation accordingly
+* harmonized example code
+
 # ggseqplot 0.8.0
 
 * complete revision of `ggseqrfplot` after `{TraMineR}` release 2.2-5 

R/ggseqdplot.R

@@ -63,15 +63,10 @@
 #'   \insertAllCited{}
 #'
 #' @examples
-#' # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-#'
-#' # Examples from TraMineR::seqplot
+#' # Use examples from TraMineR & load ggplot for fine-tuning the plot
+#' library(TraMineR)
 #' library(ggplot2)
 #'
-#' # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-#'
-#' # Examples from TraMineR::seqplot
-#'
 #' # actcal data set
 #' data(actcal)
 #'
@@ -81,8 +76,6 @@
 #' actcal.lab <- c("> 37 hours", "19-36 hours", "1-18 hours", "no work")
 #' actcal.seq <- seqdef(actcal, 13:24, labels = actcal.lab)
 #'
-#' # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-#'
 #' # state distribution plots; grouped by sex
 #' # with TraMineR::seqplot
 #' seqdplot(actcal.seq, group = actcal$sex)

R/ggseqeplot.R

@@ -5,8 +5,7 @@
 #' instead of base R's \code{\link[base]{plot}} function that is used by
 #' \code{\link[TraMineR:seqplot]{TraMineR::seqplot}} \insertCite{gabadinho2011}{ggseqplot}.
 #' Other than in \code{\link[TraMineR:seqHtplot]{TraMineR::seqHtplot}} group-specific entropy
-#' lines are displayed in a common plot (just like in
-#' \code{\link[TraMineRextras:seqplot.tentrop]{TraMineRextras::seqplot.tentrop}}).
+#' lines are displayed in a common plot.
 #'
 #' @param seqdata State sequence object (class \code{stslist}) created with the \code{\link[TraMineR:seqdef]{TraMineR::seqdef}} function.
 #' @param group If grouping variable is specified plot shows one line for each group
@@ -41,9 +40,8 @@
 #'   \insertAllCited{}
 #'
 #' @examples
-#' # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-#'
-#' # Examples from TraMineR::seqplot
+#' # Use examples from TraMineR
+#' library('TraMineR')
 #'
 #' # actcal data set
 #' data(actcal)
@@ -54,17 +52,14 @@
 #' actcal.lab <- c("> 37 hours", "19-36 hours", "1-18 hours", "no work")
 #' actcal.seq <- seqdef(actcal, 13:24, labels = actcal.lab)
 #'
-#' # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-#'
-#'
 #' # sequences sorted by age in 2000 and grouped by sex
 #' # with TraMineR::seqplot (entropies shown in two separate plots)
 #' seqHtplot(actcal.seq, group = actcal$sex)
 #' # with ggseqplot (entropies shown in one plot)
 #' ggseqeplot(actcal.seq, group = actcal$sex)
 #' ggseqeplot(actcal.seq, group = actcal$sex, gr.linetype = TRUE)
 #'
-#' #manual color specification
+#' # manual color specification
 #' ggseqeplot(actcal.seq, linecolor = "darkgreen")
 #' ggseqeplot(actcal.seq, group = actcal$sex,
 #'            linecolor = c("#3D98D3FF", "#FF363CFF"))

R/ggseqfplot.R

@@ -47,16 +47,10 @@
 #' \code{\link[ggseqplot:ggseqiplot]{ggseqiplot}}
 #'
 #' @examples
-#' # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-#'
-#' # Examples from TraMineR::seqplot
-#'
+#' # Use examples from TraMineR & load ggplot for fine-tuning the plot
+#' library(TraMineR)
 #' library(ggplot2)
 #'
-#' # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-#'
-#' # Examples from TraMineR::seqplot
-#'
 #' # actcal data set
 #' data(actcal)
 #'
@@ -66,8 +60,6 @@
 #' actcal.lab <- c("> 37 hours", "19-36 hours", "1-18 hours", "no work")
 #' actcal.seq <- seqdef(actcal, 13:24, labels = actcal.lab)
 #'
-#' # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-#'
 #' # sequence frequency plot
 #' # with TraMineR::seqplot
 #' seqfplot(actcal.seq)

R/ggseqiplot.R

@@ -70,9 +70,8 @@
 #'   \insertAllCited{}
 #'
 #' @examples
-#' # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-#'
-#' # Examples from TraMineR::seqplot
+#' # Use examples from TraMineR
+#' library(TraMineR)
 #'
 #' # actcal data set
 #' data(actcal)
@@ -87,9 +86,6 @@
 #' data(ex1)
 #' ex1.seq <- seqdef(ex1, 1:13, weights = ex1$weights)
 #'
-#' # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-#'
-#'
 #' # sequences sorted by age in 2000 and grouped by sex
 #' # with TraMineR::seqplot
 #' seqIplot(actcal.seq, group = actcal$sex, sortv = actcal$age00)

R/ggseqmsplot.R

@@ -35,15 +35,8 @@
 #'   \insertAllCited{}
 #'
 #' @examples
-#' # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-#'
-#' # Examples from TraMineR::seqplot
-#'
-#' library(ggplot2)
-#'
-#' # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-#'
-#' # Examples from TraMineR::seqplot
+#' # Use examples from TraMineR
+#' library(TraMineR)
 #'
 #' # actcal data set
 #' data(actcal)
@@ -54,8 +47,6 @@
 #' actcal.lab <- c("> 37 hours", "19-36 hours", "1-18 hours", "no work")
 #' actcal.seq <- seqdef(actcal, 13:24, labels = actcal.lab)
 #'
-#' # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-#'
 #' # modal state sequence plot; grouped by sex
 #' # with TraMineR::seqplot
 #' seqmsplot(actcal.seq, group = actcal$sex)

R/ggseqmtplot.R

@@ -45,16 +45,10 @@
 #'   \insertAllCited{}
 #'
 #' @examples
-#' # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-#'
-#' # Examples from TraMineR::seqplot
-#'
+#' # Use examples from TraMineR & load ggplot for fine-tuning the plot
+#' library(TraMineR)
 #' library(ggplot2)
 #'
-#' # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-#'
-#' # Examples from TraMineR::seqplot
-#'
 #' # actcal data set
 #' data(actcal)
 #'
@@ -64,8 +58,6 @@
 #' actcal.lab <- c("> 37 hours", "19-36 hours", "1-18 hours", "no work")
 #' actcal.seq <- seqdef(actcal, 13:24, labels = actcal.lab)
 #'
-#' # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-#'
 #' # modal state sequence plot; grouped by sex
 #' # with TraMineR::seqplot
 #' seqmtplot(actcal.seq, group = actcal$sex)

R/ggseqrfplot.R

@@ -103,47 +103,48 @@
 #'   \insertAllCited{}
 #'
 #' @examples
-#' ## Load additional libraries
+#' # Use examples from TraMineR & load additional libraries for fine-tuning the plots
+#' library(TraMineR)
 #' library(patchwork)
 #' library(ggplot2)
 #'
-#' ## From TraMineR::seqprf
-#' ## Defining a sequence object with the data in columns 10 to 25
-#' ## (family status from age 15 to 30) in the biofam data set
+#' # From TraMineR::seqprf
+#' # Defining a sequence object with the data in columns 10 to 25
+#' # (family status from age 15 to 30) in the biofam data set
 #' data(biofam)
 #' biofam.lab <- c("Parent", "Left", "Married", "Left+Marr",
 #'   "Child", "Left+Child", "Left+Marr+Child", "Divorced")
 #'
-#' ## Here, we use only 100 cases selected such that all elements
-#' ## of the alphabet be present.
-#' ## (More cases and a larger k would be necessary to get a meaningful example.)
+#' # Here, we use only 100 cases selected such that all elements
+#' # of the alphabet be present.
+#' # (More cases and a larger k would be necessary to get a meaningful example.)
 #' biofam.seq <- seqdef(biofam[501:600, 10:25], labels=biofam.lab,
 #'                      weights=biofam[501:600,"wp00tbgs"])
 #' diss <- seqdist(biofam.seq, method = "LCS")
 #'
 #'
-#' ## Using 12 groups and default MDS sorting
-#' ## and original method by Fasang and Liao (2014)
+#' # Using 12 groups and default MDS sorting
+#' # and original method by Fasang and Liao (2014)
 #'
-#' ## ... with TraMineR::seqrfplot (weights have to be turned off)
+#' # ... with TraMineR::seqrfplot (weights have to be turned off)
 #' seqrfplot(biofam.seq, weighted = FALSE, diss = diss, k = 12,
 #'           grp.meth="first", which.plot = "both")
 #'
-#' ## ... with ggseqrfplot
-#' ggseqrfplot(biofam.seq, weighted = FALSE, diss = diss, k = 12)
+#' # ... with ggseqrfplot
+#' ggseqrfplot(biofam.seq, weighted = FALSE, diss = diss, k = 12, grp.meth="first")
 #'
-#'## With a user specified sorting variable
-#'## Here time spent in parental home, which has ties
-#'parentTime <- seqistatd(biofam.seq)[, 1]
-#'b.srf <- seqrf(biofam.seq, diss=diss, k=12, sortv=parentTime)
+#' # With a user specified sorting variable
+#' # Here time spent in parental home, which has ties
+#' parentTime <- seqistatd(biofam.seq)[, 1]
+#' b.srf <- seqrf(biofam.seq, diss=diss, k=12, sortv=parentTime)
 #'
-#'## ... with TraMineR
-#'plot(b.srf, which.plot="both")
+#' # ... with TraMineR
+#' plot(b.srf, which.plot="both")
 #'
-#'## ... with ggseqrfplot (and some extra annotation using patchwork)
-#'ggseqrfplot(seqrfobject = b.srf) +
-#'  plot_annotation(title = "Sorted by time spent in parental home",
-#'                  theme = theme(plot.title = element_text(hjust = 0.5, size = 18)))
+#' # ... with ggseqrfplot (and some extra annotation using patchwork)
+#' ggseqrfplot(seqrfobject = b.srf) +
+#'   plot_annotation(title = "Sorted by time spent in parental home",
+#'                   theme = theme(plot.title = element_text(hjust = 0.5, size = 18)))
 ggseqrfplot <- function(seqdata = NULL,
                         diss = NULL,
                         k = NULL,