cran release. gbm.auto offset param man text was cut off

CRAN-SUBMISSION

@@ -1,3 +1,3 @@
 Version: 2023.08.31
-Date: 2023-08-31 22:57:11 UTC
-SHA: 6bda7e8d110cbd641ce564230790cd5a975f7ebb
+Date: 2023-09-01 16:02:09 UTC
+SHA: ee6217a76f6ace8b250108daca5ed2ddc3cb59a1

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: gbm.auto
 Title: Automated Boosted Regression Tree Modelling and Mapping Suite
-Version: 2023.08.31
+Version: 2023.12.11
 Authors@R: person("Simon", "Dedman", , "simondedman@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-9108-972X"))
 Description: Automates delta log-normal boosted regression tree abundance
     prediction. Loops through parameters provided (LR (learning rate), TC

R/gbm.auto.R

@@ -35,8 +35,8 @@
 #' @param bf Permutations of bag fraction allowed, can be single number, vector
 #' or list, per tc and lr. Defaults to 0.5.
 #' @param offset Column number or quoted name in samples, containing offset values relating to the
-# samples. A numeric vector of length equal to the number of cases. Similar to weighting, see
-# https://towardsdatascience.com/offsetting-the-model-logic-to-implementation-7e333bc25798 .
+#' samples. A numeric vector of length equal to the number of cases. Similar to weighting, see
+#' https://towardsdatascience.com/offsetting-the-model-logic-to-implementation-7e333bc25798 .
 #' @param n.trees From gbm.step, number of initial trees to fit. Can be
 #' single or list but not vector i.e. list(fam1,fam2).
 #' @param ZI Are data zero-inflated? TRUE FALSE "CHECK". Choose one. TRUE:
@@ -1862,6 +1862,9 @@ gbm.auto <- function(
           # # byx, byy, mapmain, heatcol, mapback, landcol, lejback, legendloc, grdfun, zero, quantile, heatcolours, colournumber
           # dev.off()
 
+          # BUG: stamen autozoom####
+          # Error in if (zoom == "auto" && location_type == "bbox") { : missing value where TRUE/FALSE needed
+
           gbm.mapsf(predabund = grids[c(gridslat, gridslon, predabund)],
                     # predabundlon = 2, # Longitude column number.
                     # predabundlat = 1, # Latitude column number.

R/gbm.loop.R

@@ -54,6 +54,10 @@
 #' @return Returns a data frame of lat, long, 1 predicted abundance per loop,
 #' and a final variance score per cell.
 #'
+#' @details
+#' Thanks to a 2023 improvement to gbm.auto and gbm.loop,
+#'
+#'
 #' @export
 #' @importFrom beepr beep
 #' @importFrom grDevices dev.off grey.colors png

R/gbm.mapsf.R

@@ -325,12 +325,10 @@ gbm.mapsf <- function(
   if (mapsource == "gbm.basemap") {
     # if user provided location of .shp file, read in. If shape is already read with st_read, leave alone.
     if (is.character(shape)) shape = st_read(dsn = shape)
-
-
     # autoheight <- (6 / (attr(myMap, "bb")[[4]] - attr(myMap, "bb")[[2]])) * (attr(myMap, "bb")[[3]] - attr(myMap, "bb")[[1]]) * 1.2
     # if (googlemap) autoheight <- 6.4 # googlemap pulls tiles for a centre point hence will always be square. But needs a bit extra for title area.
     autoheight <- 6.4 # dummy
-    #autoheight####
+    #autoheight to build####
   } else { # mapsource ifelse
     myMap <- ggmap::get_map(
       location = myLocation, # -62.57564  28.64368  33.78889  63.68533 # stamen etc want a bounding box