50 dev version of od causing simodels to fail

DESCRIPTION

@@ -1,41 +1,47 @@
 Package: od
 Title: Manipulate and Map Origin-Destination Data
-Version: 0.5.0
+Version: 0.5.1
 Authors@R: c(
-    person("Robin", "Lovelace", email = "[email protected]", role = c("aut", "cre"),
-      comment = c(ORCID = "0000-0001-5679-6536")),
-    person("David", "Cooley", role = c("ctb"))
-    )
-Description: The aim of 'od' is to provide tools and example datasets for working with
-  origin-destination ('OD') datasets of the type used to describe aggregate
-  urban mobility patterns (Carey et al. 1981) <doi:10.1287/trsc.15.1.32>.
-  The package builds on functions for working with 'OD' data in the package 'stplanr',
-  (Lovelace and Ellison 2018) <doi:10.32614/RJ-2018-053> with a focus on computational
-  efficiency and support for  the 'sf' class system (Pebesma 2018) <doi:10.32614/RJ-2018-009>.
-  With few dependencies and a simple class system based on data frames,
-  the package is intended to facilitate efficient analysis of 'OD' datasets
-  and to provide a place for developing new functions.
-  The package enables the creation and analysis of geographic entities
-  representing large scale mobility patterns,
-  from daily travel between zones in cities to migration between countries.
+    person("Robin", "Lovelace", , "[email protected]", role = c("aut", "cre"),
+           comment = c(ORCID = "0000-0001-5679-6536")),
+    person("Malcolm", "Morgan", role = "aut",
+           comment = c(ORCID = "0000-0002-9488-9183")),
+    person("David", "Cooley", role = "ctb")
+  )
+Description: The aim of 'od' is to provide tools and example datasets for
+    working with origin-destination ('OD') datasets of the type used to
+    describe aggregate urban mobility patterns (Carey et al. 1981)
+    <doi:10.1287/trsc.15.1.32>.  The package builds on functions for
+    working with 'OD' data in the package 'stplanr', (Lovelace and Ellison
+    2018) <doi:10.32614/RJ-2018-053> with a focus on computational
+    efficiency and support for the 'sf' class system (Pebesma 2018)
+    <doi:10.32614/RJ-2018-009>.  With few dependencies and a simple class
+    system based on data frames, the package is intended to facilitate
+    efficient analysis of 'OD' datasets and to provide a place for
+    developing new functions.  The package enables the creation and
+    analysis of geographic entities representing large scale mobility
+    patterns, from daily travel between zones in cities to migration
+    between countries.
 License: GPL-3
 URL: https://github.com/itsleeds/od, https://itsleeds.github.io/od/
 BugReports: https://github.com/itsleeds/od/issues
-Encoding: UTF-8
-LazyData: true
-Depends: R (>= 3.4.0)
+Depends: 
+    R (>= 3.4.0)
 Imports: 
-    sfheaders,
     methods,
+    sfheaders,
     vctrs
 Suggests: 
-    sf,
-    knitr,
-    rmarkdown,
-    tinytest,
     covr,
+    knitr,
     lwgeom,
-    nngeo
-RoxygenNote: 7.3.2
-VignetteBuilder: knitr
+    nngeo,
+    rmarkdown,
+    sf,
+    tinytest
+VignetteBuilder: 
+    knitr
+Encoding: UTF-8
+LazyData: true
 Roxygen: list(markdown = TRUE)
+RoxygenNote: 7.3.2

NEWS.md

@@ -1,3 +1,7 @@
+# od 0.5.1 (2024-08)
+
+* Bug fix that was causing incorrect column names (#50)
+
 # od 0.5.0 (2024-08)
 
 * New `max_dist` argument in `points_to_od()` (also applicable to `points_to_odl()`) to limit the distance between origins and destinations. Credit to Malcolm Morgan @mem48 for this contribution, closing 4-year-old issue #18.

R/od-funs.R

@@ -351,3 +351,8 @@ od_filter_destinations = function(x, codes) {
   sel_d_in_codes = x[[2]] %in% codes
   x[sel_d_in_codes, ]
 }
+# See https://stackoverflow.com/a/67872362
+od_expand = function(ids) {
+  rev(expand.grid(rev(ids), stringsAsFactors = FALSE))
+}
+# od_expand(list(O = 1:3, D = 1:2))

R/points_to_od.R

@@ -29,7 +29,7 @@
 #' @export
 #' @examples
 #' library(sf)
-#' p = od_data_centroids[1:3, ]
+#' p = od_data_centroids[1:2, ]
 #' points_to_od(p)
 #' points_to_od(p, ids_only = TRUE)
 #' (l = points_to_odl(p, interzone_only = TRUE))
@@ -99,7 +99,8 @@ points_to_od.sf = function(p, pd = NULL, interzone_only = FALSE, ids_only = FALS
       D = pd[[1]][unlist(nn, use.names = FALSE)]
     )
   } else {
-    odf = data.frame(expand.grid(p[[1]], pd[[1]], stringsAsFactors = FALSE))
+    ids = list(O = p[[1]], D = pd[[1]])
+    odf = od_expand(ids)
   }
 
   if (interzone_only) {
@@ -148,7 +149,8 @@ points_to_odl = function(p, pd = NULL, crs = 4326, ...) {
 #' @export
 coords_to_od = function(p, interzone_only = FALSE, ids_only = FALSE) {
   id = seq(nrow(p))
-  odf = data.frame(expand.grid(id, id, stringsAsFactors = FALSE)[2:1])
+  ids = list(O = id, D = id)
+  odf = od_expand(ids)
   if (interzone_only) {
     odf = od_interzone(odf)
   }
@@ -184,3 +186,8 @@ od_interzone = function(x) {
 od_intrazone = function(x) {
   x[x[[1]] == x[[2]], ]
 }
+# See https://stackoverflow.com/a/67872362
+od_expand = function(ids) {
+  rev(expand.grid(rev(ids), stringsAsFactors = FALSE))
+}
+# od_expand(list(O = 1:3, D = 1:2))