Few more tweaks

R/linefuns.R

@@ -171,11 +171,13 @@ line_midpoint <- function(l, tolerance = NULL) {
 #' l_seg_multi <- line_segment(l, segment_length = 1000, use_rsgeo = FALSE)
 #' # Number of subsegments
 #' table(l_seg_multi$ID)
-#' plot(l_seg_multi, col = seq_along(l_seg_multi), lwd = 5)
+#' plot(l_seg_multi["ID"])
+#' plot(l_seg_multi$geometry, col = seq_along(l_seg_multi), lwd = 5)
 #' round(st_length(l_seg_multi))
 #' # rsgeo implementation:
 #' rsmulti = line_segment(l, segment_length = 1000, use_rsgeo = TRUE)
-#' # plot(rsmulti, col = seq_along(l_seg_multi), lwd = 5)
+#' plot(rsmulti["ID"])
+#' plot(rsmulti$geometry, col = seq_along(l_seg_multi), lwd = 5)
 #' # round(st_length(rsmulti))
 #' # waldo::compare(l_seg_multi, rsmulti)
 line_segment <- function(

docs/articles/stplanr-paper.tex

@@ -980,10 +980,7 @@ \section{Future directions of travel}\label{future-directions-of-travel}
 planning a more open and democratic process. Other developments in this
 movement include the increasing availability of open data
 \citep{naumova_building_2016} and the rise of open source products for
-transport modelling, such as
-\href{http://www.dlr.de/ts/en/desktopdefault.aspx/tabid-9883/16931_read-41000/}{SUMO},
-\href{http://www.matsim.org/}{MATSim} and
-\href{https://its.mit.edu/software/mitsimlab}{MITSIMLAB}
+transport modelling, such as SUMO, MATSim and MITSIMLAB
 \citep{saidallah_comparative_2016}. \textbf{stplanr}, with its focus on
 GIS operations rather than microscopic vehicle-level behaviour, can
 complement such software and help make better use of new open data

vignettes/stplanr-paper.Rmd

@@ -697,7 +697,7 @@ Furthermore, with the development of online application frameworks such as **shi
 
 This paper has demonstrated the great potential for R to be used for transport planning. R's flexibility, powerful GIS capabilities \citep{bivand_applied_2013} and free accessibility makes it well-suited to the needs of transport planners and researchers, especially those wanting to avoid the high costs of market-leading products. Rather than 'reinvent the wheel' (e.g. with a new class system), **stplanr** builds on existing packages and \CRANpkg{sp} classes to work with common transport data formats.
 
-It is useful to see **stplanr**, and R for transport planning in general, as an addition tool in the transport planner's cabinet. It can be understood as one part of a wider movement that is making transport planning a more open and democratic process. Other developments in this movement include the increasing availability of open data \citep{naumova_building_2016} and the rise of open source products for transport modelling, such as [SUMO](https://www.dlr.de/ts/en/desktopdefault.aspx/tabid-9883/16931_read-41000/), [MATSim](https://www.matsim.org/) and MITSIMLAB \citep{saidallah_comparative_2016}.
+It is useful to see **stplanr**, and R for transport planning in general, as an addition tool in the transport planner's cabinet. It can be understood as one part of a wider movement that is making transport planning a more open and democratic process. Other developments in this movement include the increasing availability of open data \citep{naumova_building_2016} and the rise of open source products for transport modelling, such as SUMO, [MATSim](https://www.matsim.org/) and MITSIMLAB \citep{saidallah_comparative_2016}.
 **stplanr**, with its focus on GIS operations rather than microscopic vehicle-level behaviour, can complement such software and help make better use of new open data sources.
 
 Because transport planning is an inherently spatial activity, **stplanr** occupies an important niche in the transport planning software landscape, with its focus on spatial transport data. There is great potential for development of **stplanr** in many directions.