use md for man pages. CRAN release.

.Rbuildignore

@@ -4,6 +4,6 @@ proj$
 ^.*\.Rproj$
 ^LICENSE
 README.Rmd
-^Work/
+^Work
 ^_config\.yml
 ^\.github$

R/ggraph.R

@@ -39,8 +39,9 @@ graph_nodes_ggplot2 <- function(
     shading <- NULL
   }
 
-  # NULLify
+  # NULLify for checker
   label <- NULL
+  type <- NULL
 
   control <- c(control, list(...))
   control <- .get_parameters(

R/inspectDT.R

@@ -27,9 +27,9 @@
 #' @param ...  additional arguments are passed on to [`DT::datatable()`].
 #' @return A datatable htmlwidget.
 #' @author Michael Hahsler
-#' @seealso \code{\link[DT]{datatable}} in \pkg{DT}.
+#' @seealso [DT::datatable()] in \pkg{DT}.
 #' @references Hahsler M (2017). arulesViz: Interactive Visualization of
-#' Association Rules with R. \emph{R Journal,} 9(2):163-175. ISSN 2073-4859.
+#' Association Rules with R. *R Journal,* 9(2):163-175. ISSN 2073-4859.
 #' \doi{10.32614/RJ-2017-047}.
 #' @keywords print
 #' @examples

R/plot.R

@@ -30,14 +30,14 @@
 #' Most visualization techniques are described by Bruzzese and Davino (2008),
 #' however, we added more color shading, reordering and interactive features
 #' (see Hahsler, 2017). Many visualization methods take extra parameters as the
-#' \code{control} parameter list. Although, we have tried to keep control
+#' `control` parameter list. Although, we have tried to keep control
 #' parameters consistent, the available control parameters vary from
-#' visualization method to visualization method. You can specift \code{"help"}
-#' for \code{method}, \code{engine}, or \code{control} to get a list of
+#' visualization method to visualization method. You can specift `"help"`
+#' for `method`, `engine`, or `control` to get a list of
 #' available settings.
 #'
 #' Note on HTML widgets: HTML widgets tend to get very slow or unresponsive for
-#' too many rules. To prevent this situation, the control parameter \code{max}
+#' too many rules. To prevent this situation, the control parameter `max`
 #' sets a limit, and the user is warned if the limit is reached.
 #'
 #' The following visualization method are available:
@@ -53,10 +53,10 @@
 #' \item{"matrix"}{ Arranges the association rules as a matrix with the
 #' itemsets in the antecedents on one axis and the itemsets in the consequents
 #' on the other.  The measure of interestingness (first element of
-#' \code{measure}) is either visualized by a color (darker means a higher value
+#' `measure`) is either visualized by a color (darker means a higher value
 #' for the measure) or as the height of a bar (engine "3d").  The control
-#' parameter \code{reorder} takes the values \code{"none"}, \code{"measure"},
-#' \code{"support/confidence"}, or \code{"similarity"} and can be used to
+#' parameter `reorder` takes the values `"none"`, `"measure"`,
+#' `"support/confidence"`, or `"similarity"` and can be used to
 #' reorder LHS and RHS of the rules differntly. The default reordering average
 #' measure (typically lift) pushing the rules with the highest lift value to
 #' the top-left corner of the plot.  }
@@ -93,7 +93,7 @@
 #' pointing to the item. }
 #'
 #' \item{"doubledecker", "mosaic"}{ Represents a single rule as a doubledecker
-#' or mosaic plot. Parameter \code{data} has to be specified to compute the
+#' or mosaic plot. Parameter `data` has to be specified to compute the
 #' needed contingency table. No interactive version is available. }
 #'
 #' \item{"paracoord"}{ Represents the rules (or itemsets) as a parallel
@@ -114,13 +114,13 @@
 #' @param measure measure(s) of interestingness (e.g., "support", "confidence",
 #' "lift", "order") used in the visualization. Some visualization methods need
 #' one measure, others take a vector with two measures (e.g., scatterplot). In
-#' some plots (e.g., graphs) \code{NA} can be used to suppress using a measure.
+#' some plots (e.g., graphs) `NA` can be used to suppress using a measure.
 #' @param shading measure of interestingness used for the color of the
 #' points/arrows/nodes (e.g., "support", "confidence", "lift"). The default is
-#' "lift".  \code{NULL} can be often used to suppress shading.
+#' "lift".  `NULL` can be often used to suppress shading.
 #' @param limit A limit on the number of associations displayed. The top limit
 #' associations according to the measure specified in shading are chosen.
-#' @param interactive deprecated. See parameter \code{engine} below.
+#' @param interactive deprecated. See parameter `engine` below.
 #' @param engine a string indicating the plotting engine used to render the
 #' plot.  The "default" engine uses (mostly) \pkg{ggplot2}.  Other engines
 #' include "base" (base R plots), "grid", "interactive", "plotly",
@@ -135,7 +135,7 @@
 #' Specify "help" to get a complete list of available control parameters and
 #' their default values.
 #' @param \dots Further arguments are added for convenience to the
-#' \code{control} list.
+#' `control` list.
 #' @return Several interactive plots return a set of selected rules/itemsets.
 #' Other plots might return other data structures. For example, graph-based
 #' plots return the graph (invisibly). Engine "htmlwidget" always returns an

R/ruleExplorer.R

@@ -36,10 +36,10 @@
 #' @author Tyler Giallanza and Michael Hahsler.  Adapted from functions
 #' originally created by Andrew Brooks. See
 #' [Rsenal](https://github.com/brooksandrew/Rsenal) for the original code.
-#' @seealso \code{\link{plot}} with \code{engine = "html"},
-#' \code{\link{inspectDT}}, \code{\link[arules]{apriori}}.
+#' @seealso [plot()] with `engine = "html"`,
+#' [inspectDT()], [arules::apriori()].
 #' @references Hahsler M (2017). arulesViz: Interactive Visualization of
-#' Association Rules with R. \emph{R Journal,} 9(2):163-175. ISSN 2073-4859.
+#' Association Rules with R. *R Journal,* 9(2):163-175. ISSN 2073-4859.
 #' \doi{10.32614/RJ-2017-047}.
 #' @examples
 #' \dontrun{

R/rules2matrix.R

@@ -35,16 +35,16 @@
 #' @param lhs_label_items number of top items used to name LHS itemset groups
 #' (columns).
 #' @param ...  passed on to [`arules::DATAFRAME()`].
-#' @return \code{rules2matrix} returns a matrix with quality values.
+#' @return `rules2matrix` returns a matrix with quality values.
 #'
-#' \code{rules2groupedMatrix} returns a list with elements
+#' `rules2groupedMatrix` returns a list with elements
 #' \item{m}{ the
 #' grouped matrix for measure. }
 #' \item{m2}{ the grouped matrix for measure2. }
 #' \item{clustering_rules}{ vector with group assignment for each rule. }
 #' @author Michael Hahsler
-#' @seealso \code{\link{plot}} for rules using \code{method = 'matrix'} and
-#' \code{method = 'grouped matrix'}.
+#' @seealso [plot()] for rules using `method = 'matrix'` and
+#' `method = 'grouped matrix'`.
 #' @references Michael Hahsler and Radoslaw Karpienko. Visualizing association
 #' rules in hierarchical groups. Journal of Business Economics, 87(3):317--335,
 #' May 2016. \doi{10.1007/s11573-016-0822-8}.

R/saveAsGraph.R

@@ -38,7 +38,7 @@
 #' @param format file format (e.g., "edgelist", "graphml", "dimacs", "gml",
 #' "dot"). See [`igraph::write_graph()`].
 #' @param ...  further arguments are passed on to `associations2igraph()`.
-#' @return \code{associations2igraph} returns an igraph object.
+#' @return `associations2igraph` returns an igraph object.
 #' @author Michael Hahsler
 #' @keywords file
 #' @examples