Purge package of the evil camelCase

Robinlovelace · Oct 23, 2015 · 815afa2 · 815afa2
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -6,8 +6,8 @@ Date: 2015-10-18
 Authors@R: c(
     person("Robin", "Lovelace", email = "[email protected]", role = c("aut", "cre")),
     person("Richard", "Ellison", role = c("aut"), comment = "Author of various functions"),
-    person("Barry", "Rowlingson", role = c("aut"), comment = "Author of gOverline"),
-    person("Nick", "Bearman", role = c("aut"), comment = "Co-author of gClip")
+    person("Barry", "Rowlingson", role = c("aut"), comment = "Author of overline"),
+    person("Nick", "Bearman", role = c("aut"), comment = "Co-author of gclip")
     )
 Description: Functionality and data access tools for transport planning, including origin-destination analysis, route allocation and modelling travel patterns.
 License: MIT + file LICENSE

diff --git a/NAMESPACE b/NAMESPACE
@@ -10,12 +10,12 @@ export(dd_logcub)
 export(dd_loglin)
 export(dd_logsqrt)
 export(disab_recat)
-export(gClip)
-export(gMapshape)
-export(gOnewaygeo)
-export(gOnewayid)
-export(gOverline)
-export(gSection)
+export(gclip)
+export(mapshape)
+export(onewaygeo)
+export(onewayid)
+export(overline)
+export(gsection)
 export(islines)
 export(line2df)
 export(line2route)

diff --git a/R/geo-functions.R b/R/geo-functions.R
@@ -4,7 +4,7 @@
 #' \code{geojson_write} from the geojsonio package
 #' provides the same functionality \url{https://github.com/ropensci/geojsonio}.
 #'
-#' @inheritParams gClip
+#' @inheritParams gclip
 #' @param filename File name of the output geojson
 writeGeoJSON <- function(shp, filename){
   name <- nm <-deparse(substitute(shp))
@@ -16,7 +16,7 @@ writeGeoJSON <- function(shp, filename){
 #' Simplify geometry file of a shapfile.
 #'
 #' @section Details:
-#' This is a wrapper funtion for the open source JavaScript command-line GIS application mapshaper: \url{https://github.com/mbloch/mapshaper} . mapshaper which must be installed locally for gMapshaper to work. Writes \code{gMapshape} writes new file to disk. Thanks to Richard and Adrian Ellison for demonstrating this in R.
+#' This is a wrapper funtion for the open source JavaScript command-line GIS application mapshaper: \url{https://github.com/mbloch/mapshaper} . mapshaper which must be installed locally for mapshaper to work. Writes \code{mapshape} writes new file to disk. Thanks to Richard and Adrian Ellison for demonstrating this in R.
 #'
 #' @param dsn A character string providing the absolute path to the shapefile to simplify.
 #' @param percent A number between 0 and 100 stating how aggressively to simplify
@@ -27,9 +27,9 @@ writeGeoJSON <- function(shp, filename){
 #' @export
 #' @examples
 #' \dontrun{
-#' gMapshape("~/geodata/myShapefile.shp", 5)
+#' mapshape("~/geodata/myShapefile.shp", 5)
 #' }
-gMapshape <- function(dsn, percent){
+mapshape <- function(dsn, percent){
   from_layer <- gsub(".shp", replacement = "", dsn)
   to_layer <- paste0(from_layer, "mapshaped_", percent, "%.shp")
   cmd <- paste0("mapshaper ", dsn, " auto-snap -simplify keep-shapes ", percent, "% -o force ", to_layer)
@@ -56,12 +56,12 @@ gMapshape <- function(dsn, percent){
 #' cb <- rgeos::gBuffer(cents[8, ], width = 0.012, byid = TRUE)
 #' plot(cents)
 #' plot(cb, add = TRUE)
-#' clipped <- gClip(cents, cb)
+#' clipped <- gclip(cents, cb)
 #' row.names(clipped)
-#' clipped$avslope # gClip also returns the data attribute
+#' clipped$avslope # gclip also returns the data attribute
 #' points(clipped)
 #' points(cents[cb,], col = "red") # note difference
-gClip <- function(shp, bb){
+gclip <- function(shp, bb){
   if(class(bb) == "matrix"){
     b_poly <- as(raster::extent(as.vector(t(bb))), "SpatialPolygons")
   }
@@ -71,14 +71,14 @@ gClip <- function(shp, bb){
   clipped <- rgeos::gIntersection(shp, b_poly, byid = TRUE, id = row.names(shp))
   if(grepl("DataFrame", class(shp))){
     if(grepl("SpatialLines", class(shp)) & grepl("SpatialCollections",class(clipped))) {
-      geodata <- data.frame(gClip_id = row.names(clipped@lineobj))
+      geodata <- data.frame(gclip_id = row.names(clipped@lineobj))
     }
     else {
-      geodata <- data.frame(gClip_id = row.names(clipped))
+      geodata <- data.frame(gclip_id = row.names(clipped))
     }
-    joindata <- cbind(gClip_id = row.names(shp), shp@data)
+    joindata <- cbind(gclip_id = row.names(shp), shp@data)
     geodata <- dplyr::left_join(geodata, joindata)
-    row.names(geodata) <- geodata$gClip_id
+    row.names(geodata) <- geodata$gclip_id
     #if the data are SpatialPolygonsDataFrame (based on https://stat.ethz.ch/pipermail/r-sig-geo/2008-January/003052.html)
     if(grepl("SpatialPolygons", class(shp))){
       #then rebuild SpatialPolygonsDataFrame selecting relevant rows by row.names (row ID values)
@@ -91,15 +91,15 @@ gClip <- function(shp, bb){
       clipped <- sp::SpatialPointsDataFrame(clipped, geodata)
     }
   }
-  clipped@data$gClip_id <- NULL
+  clipped@data$gclip_id <- NULL
   clipped
 }
 
 #' Scale a bounding box
 #'
 #' Takes a bounding box as an input and outputs a bounding box of a different size, centred at the same point.
 #'
-#' @inheritParams gClip
+#' @inheritParams gclip
 #' @param scale_factor Number determining how much the bounding box will grow or shrink. If the value is 1, the output size will be the same as the input.
 #' @export
 #' @examples

diff --git a/R/gFlow.R → R/od-funs.R b/R/gFlow.R → R/od-funs.R
diff --git a/R/gOverline.R → R/overline.R b/R/gOverline.R → R/overline.R
@@ -1,6 +1,6 @@
 #' Do the intersections between two geometries create lines?
 #'
-#' This is a function required in \code{\link{gOverline}}. It identifies
+#' This is a function required in \code{\link{overline}}. It identifies
 #' whether sets of lines overlap (beyond shared points) or
 #' not.
 #'
@@ -10,7 +10,7 @@
 #'
 #' @examples \dontrun{
 #' data(routes_fast)
-#' rnet <- gOverline(routes_fast[c(2, 3, 22),], attrib = "length")
+#' rnet <- overline(routes_fast[c(2, 3, 22),], attrib = "length")
 #' r1 <- routes_fast[2,]
 #' r2 <- routes_fast[3,]
 #' r3 <- routes_fast[22,]
@@ -37,15 +37,15 @@ islines <- function(g1, g2){
 #' @export
 #' @examples \dontrun{
 #' data(routes_fast)
-#' rsec <- gSection(routes_fast)
+#' rsec <- gsection(routes_fast)
 #' plot(routes_fast)
 #' lines(rsec, col = "red", lwd = 3)
 #' length(rsec)
 #' set.seed(5)
 #' sel <- sample(length(rsec), 20)
 #' plot(rsec[sel,], col = "blue", add = TRUE, lwd = 3) # overlapping lines
 #' }
-gSection <- function(sl){
+gsection <- function(sl){
   ## union and merge and disaggregate to make a
   ## set of non-overlapping line segments
   sp::disaggregate(rgeos::gLineMerge(rgeos::gUnion(sl, sl)))
@@ -91,16 +91,16 @@ lineLabels <- function(sldf, attrib){
 #' @examples \dontrun{
 #' data(routes_fast)
 #' data(cents)
-#' rnet <- gOverline(sldf = routes_fast[1:7,], attrib = "length")
+#' rnet <- overline(sldf = routes_fast[1:7,], attrib = "length")
 #' plot(rnet)
 #' points(cents)
 #' lineLabels(sldf = rnet, "length")
 #' sum(routes_fast$length[1:7], na.rm = TRUE) # verify highest flow
 #' data(flowlines)
 #' plot(flowlines)
-#' aggflow <- gOverline(flowlines, attrib = "All")
+#' aggflow <- overline(flowlines, attrib = "All")
 #' nrow(aggflow)
-#' aggflow2 <- gOverline(flowlines, attrib = "All", na.zero = TRUE)
+#' aggflow2 <- overline(flowlines, attrib = "All", na.zero = TRUE)
 #' plot(aggflow2) # 8 lines
 #' sel <- as.logical(colSums(gEquals(flowlines, aggflow2, byid = TRUE)))
 #' flowlines_sub <- flowlines[!sel,]
@@ -112,11 +112,11 @@ lineLabels <- function(sldf, attrib){
 #' overlaps <- over()
 #' nrow(overlaps)
 #' }
-gOverline <- function(sldf, attrib, fun = sum, na.zero = FALSE){
+overline <- function(sldf, attrib, fun = sum, na.zero = FALSE){
   ## simplify down to SpatialLines
   sl = as(sldf, "SpatialLines")
   ## get the line sections that make the network
-  slu = gSection(sl)
+  slu = gsection(sl)
   ## overlay network with routes
   overs = sp::over(slu, sl, returnList=TRUE)
   ## overlay is true if end points overlay, so filter them out:
@@ -160,19 +160,19 @@ gOverline <- function(sldf, attrib, fun = sum, na.zero = FALSE){
 #' @param attrib A text string containing the name of the line's attribute to
 #' aggregate or a numeric vector of the columns to be aggregated
 #'
-#' @return \code{gOnewaygeo} outputs a SpatialLinesDataFrame with single lines
+#' @return \code{onewaygeo} outputs a SpatialLinesDataFrame with single lines
 #' and user-selected attribute values that have been aggregated. Only lines
 #' with a distance (i.e. not intra-zone flows) are included
 #' @export
 #' @examples
 #' data("flowlines")
 #' plot(flowlines)
-#' singlelines <- gOnewaygeo(flowlines, attrib = 3:14)
+#' singlelines <- onewaygeo(flowlines, attrib = 3:14)
 #' plot(singlelines, lwd = 3, col = "red")
 #' lines(singlelines) # check we've got the right lines
 #' sum(singlelines$All)
 #' nrow(singlelines)
-gOnewaygeo <- function(x, attrib){
+onewaygeo <- function(x, attrib){
   geq <- rgeos::gEquals(x, x, byid = T)
   sel1 <- !duplicated(geq) # repeated rows
   sel2 <- rowSums(geq) > 1 # all features with an overlap
@@ -223,7 +223,7 @@ gOnewaygeo <- function(x, attrib){
 #' @param id1 A text string referring to the name of the variable containing the unique id of the origin
 #' @param id2 A text string referring to the name of the variable containing the unique id of the destination
 #'
-#' @return \code{gOnewayid} outputs a SpatialLinesDataFrame with single lines
+#' @return \code{onewayid} outputs a SpatialLinesDataFrame with single lines
 #' and user-selected attribute values that have been aggregated. Only lines
 #' with a distance (i.e. not intra-zone flows) are included.
 #' @export
@@ -232,14 +232,14 @@ gOnewaygeo <- function(x, attrib){
 #' id1 <- names(flowlines)[1]
 #' id2 <- names(flowlines)[2]
 #' plot(flowlines)
-#' singlelines <- gOnewayid(flowlines, attrib = 3:14, id1, id2)
+#' singlelines <- onewayid(flowlines, attrib = 3:14, id1, id2)
 #' lines(singlelines) # check we've got the right lines
 #' sum(singlelines$All)
 #' nrow(singlelines)
-#' sl2 <- gOnewaygeo(flowlines, attrib = 3:14)
-#' # Demonstrate the results from gOnewayid and gOnewaygeo are identical
+#' sl2 <- onewaygeo(flowlines, attrib = 3:14)
+#' # Demonstrate the results from onewayid and onewaygeo are identical
 #` identical(singlelines, sl2)
-gOnewayid <- function(x, attrib, id1 = names(x)[1], id2 = names(x)[2]){
+onewayid <- function(x, attrib, id1 = names(x)[1], id2 = names(x)[2]){
   ids <- cbind(x[[id1]], x[[id2]])
   idsort <- t(apply(ids, 1, sort))
   # duplicate pairs - see http://stackoverflow.com/questions/9028369/

diff --git a/R/routes.R b/R/routes.R
@@ -43,8 +43,6 @@
 #' Sys.setenv(CYCLESTREET = mytoken)
 #' }
 #'
-#'
-#'
 #' \code{
 #' cckey <- Sys.getenv('CYCLESTREET')
 #' }

diff --git a/R/stplanr-package.R b/R/stplanr-package.R
@@ -12,7 +12,7 @@
 #'
 #' @section Interesting functions:
 #' \itemize{
-#'  \item \code{\link{gOverline}} - Aggregate overlaying route lines and data intelligently
+#'  \item \code{\link{overline}} - Aggregate overlaying route lines and data intelligently
 #'  \item \code{\link{calc_catchment}} - Create a 'catchment area' to show the areas serving a destination
 #'  \item \code{\link{route_cyclestreet}} - Finds the fastest routes for cyclists between two places.
 #' }

diff --git a/README.Rmd b/README.Rmd
@@ -77,7 +77,7 @@ plot(routes)
 
 For more examples, `example("line2route")`.
 
-`gOverline` is a function which takes a series of route-allocated lines,
+`overline` is a function which takes a series of route-allocated lines,
 splits them into unique segmentes and aggregates
 the values of overlapping lines. This can represent where there will be
 most traffic on the transport system, as illustrated
@@ -87,7 +87,7 @@ with the plotting using [tmap](https://github.com/mtennekes/tmap).]
 
 ```{r rnet}
 routes$All <- travel_network$All
-rnet <- gOverline(sldf = routes, attrib = "All", fun = sum)
+rnet <- overline(sldf = routes, attrib = "All", fun = sum)
 
 osm_tiles <- read_osm(bb(rnet, ext = 1.05))
 rnet$lwd <- rnet$All / mean(rnet$All)

diff --git a/README.md b/README.md
@@ -110,7 +110,7 @@ plot(routes)
 
 For more examples, `example("line2route")`.
 
-`gOverline` is a function which takes a series of route-allocated lines,
+`overline` is a function which takes a series of route-allocated lines,
 splits them into unique segmentes and aggregates
 the values of overlapping lines. This can represent where there will be
 most traffic on the transport system, as illustrated
@@ -121,7 +121,7 @@ with the plotting using [tmap](https://github.com/mtennekes/tmap).]
 
 ```r
 routes$All <- travel_network$All
-rnet <- gOverline(sldf = routes, attrib = "All", fun = sum)
+rnet <- overline(sldf = routes, attrib = "All", fun = sum)
 
 osm_tiles <- read_osm(bb(rnet, ext = 1.05))
 rnet$lwd <- rnet$All / mean(rnet$All)
@@ -190,12 +190,12 @@ lsf.str("package:stplanr", all = TRUE)
 ## dd_loglin : function (x, a = 0.3, b1 = -0.2)  
 ## dd_logsqrt : function (x, a, b1, b2)  
 ## disab_recat : function (a)  
-## gClip : function (shp, bb)  
-## gMapshape : function (dsn, percent)  
-## gOnewaygeo : function (x, attrib)  
-## gOnewayid : function (x, attrib, id1 = names(x)[1], id2 = names(x)[2])  
-## gOverline : function (sldf, attrib, fun = sum, na.zero = FALSE)  
-## gSection : function (sl)  
+## gclip : function (shp, bb)  
+## mapshape : function (dsn, percent)  
+## onewaygeo : function (x, attrib)  
+## onewayid : function (x, attrib, id1 = names(x)[1], id2 = names(x)[2])  
+## overline : function (sldf, attrib, fun = sum, na.zero = FALSE)  
+## gsection : function (sl)  
 ## islines : function (g1, g2)  
 ## line2df : function (l)  
 ## line2route : function (ldf, ...)