Merge pull request #8 from abfleishman/Vignettes

Vignettes

NAMESPACE

@@ -28,7 +28,7 @@ importFrom(dplyr,lag)
 importFrom(dplyr,lead)
 importFrom(dplyr,mutate)
 importFrom(geosphere,bearing)
-importFrom(ggplot2,aes)
+importFrom(ggplot2,aes_string)
 importFrom(ggplot2,facet_wrap)
 importFrom(ggplot2,fortify)
 importFrom(ggplot2,geom_polygon)

R/kernalOverlapBA_p.R

@@ -30,15 +30,16 @@
 #'
 #' @importFrom sp SpatialPointsDataFrame CRS spTransform
 #' @importFrom adehabitatHR kernelUD getverticeshr kerneloverlaphr
-#' @importFrom ggplot2 fortify ggplot geom_polygon aes facet_wrap labs
+#' @importFrom ggplot2 fortify ggplot geom_polygon aes_string facet_wrap labs
 #' @importFrom dplyr bind_rows mutate
 #' @importFrom utils head
 #' @importFrom stats sd
 #' @export
+
 kernalOverlapBA_p<-function (tracks, tripid="tripID", groupid = "Sex",
-                       lon="Longitude",lat="Latitude",
-                       colonyLon=-113.244555,colonyLat=31.015513,
-                       its=1000, h=1.4809524, ud.grid,Plot=F){
+                             lon="Longitude",lat="Latitude",
+                             colonyLon=-113.244555, colonyLat=31.015513,
+                             its=10, h=1.4809524, ud.grid, Plot=F){
 
   # get unique trips
   UniTripID<-unique(tracks[[tripid]]) #unique trips
@@ -80,15 +81,25 @@ kernalOverlapBA_p<-function (tracks, tripid="tripID", groupid = "Sex",
   ud <- kernelUD(tracks.spdf.t, h = h,grid=ud.grid)
 
   # Plot the actual overlap
-  if(Plot==T){
-  uds<-suppressWarnings(bind_rows(
-      mutate(suppressWarnings(fortify(getverticeshr(ud, percent=95, standardize=T))), ud="95"),
-      mutate(suppressWarnings(fortify(getverticeshr(ud, percent=50, standardize=T))), ud="50")))
+    # make empty df to solve cmd check issue unbound var
+    # uds<-data.frame(long = numeric(0),
+    #                 lat = numeric(0),
+    #                 order = integer(0),
+    #                 hole = logical(0),
+    #                 piece = character(0),
+    #                 id = character(0),
+    #                 group = character(0),
+    #                 ud = character(0))
+
+uds<-suppressWarnings(bind_rows(
+      mutate(suppressMessages(fortify(getverticeshr(ud, percent=95, standardize=T))), ud="95"),
+      mutate(suppressMessages(fortify(getverticeshr(ud, percent=50, standardize=T))), ud="50")))
+
     print(ggplot(data=uds)+
-            geom_polygon(aes(x=long,y=lat,group=group,fill=id),alpha=.5)+
+            geom_polygon(aes_string(x="long",y="lat",group="group",fill="id"),alpha=.5)+
             facet_wrap(~ud)+
             labs(fill=groupid))
-}
+
 
   # 50% overlap
   BA_o50<-kerneloverlaphr(ud , method="BA", percent=50, conditional=TRUE)
@@ -125,24 +136,35 @@ kernalOverlapBA_p<-function (tracks, tripid="tripID", groupid = "Sex",
 
     # Make SPDF with the random grouping as the ID column
     tracks.spdf <- SpatialPointsDataFrame(coords=cbind(tracks[[lon]],tracks[[lat]]),
-                                                 data=data.frame(id=tracks$groupRan),
-                                                 proj4string = CRS("+proj=longlat +ellps=WGS84
+                                          data=data.frame(id=tracks$groupRan),
+                                          proj4string = CRS("+proj=longlat +ellps=WGS84
                                                             +datum=WGS84 +no_defs"))
     # Project data into laea
     tracks.spdf.t <- spTransform(tracks.spdf,
-                                        CRS(paste("+proj=laea +units=km +lon_0=", colonyLon,
-                                                  " +lat_0=", colonyLat	, sep="")))
+                                 CRS(paste("+proj=laea +units=km +lon_0=", colonyLon,
+                                           " +lat_0=", colonyLat	, sep="")))
 
     # make the kernelUD
     ud1 <- kernelUD(tracks.spdf.t, h = h,grid=ud.grid)
 
     # Plot each if desired (only for diagnostics?)
     if(Plot==T){
+      # make empty df to solve cmd check issue unbound var
+      # uds<-data.frame(long = numeric(0),
+      #                 lat = numeric(0),
+      #                 order = integer(0),
+      #                 hole = logical(0),
+      #                 piece = character(0),
+      #                 id = character(0),
+      #                 group = character(0),
+      #                 ud = character(0))
       uds<-bind_rows(
         mutate(fortify(getverticeshr(ud1, percent=95, standardize=T)), ud="95"),
         mutate(fortify(getverticeshr(ud1, percent=50, standardize=T)), ud="50"))
       head(uds)
-      print(ggplot(data=uds)+geom_polygon(aes(x=long,y=lat,group=group,fill=id),alpha=.5)+facet_wrap(~ud))
+      print(ggplot(data=uds)+
+              geom_polygon(aes_string(x="long",y="lat",group="group",fill="id"),alpha=.5)+
+              facet_wrap(~ud))
     }
 
     # Calculate BA

vignettes/split_trips.Rmd

@@ -42,7 +42,7 @@ tracks$Dist2Col<-trakR::Dist2Colony(tracks = tracks,
                                     ColonyLong = -169.6760)
 ```
 
-## segment trips
+## Split Trips
 
 The `makeTrip` function finds the points where a animal moves some treshold distance `DistCutOff` away from the colony and the points where the animal returns within that threshold and annotates the data.frame with two new column, one indicating those "In" and "Out" points and another with trip numbers.  
 ```{r make trips}