updates

Cleaned up documentation

DESCRIPTION

@@ -2,7 +2,7 @@ Package: spatialEco
 Type: Package
 Title: Spatial Analysis and Modelling Utilities
 Version: 2.0-2
-Date: 2023-11-10
+Date: 2023-11-15
 Authors@R: c(
     person(family="Evans", given="Jeffrey S.", email = "jeffrey_evans@tnc.org", 
          role = c("aut", "cre"), comment = c(ORCID = "0000-0002-5533-7044")),
@@ -44,7 +44,8 @@ Suggests:
   units,
   sp,
   stringr,
-  lwgeom  
+  lwgeom,
+  geodata  
 Maintainer: Jeffrey S. Evans <jeffrey_evans@tnc.org>
 License: GPL-3
 URL: https://github.com/jeffreyevans/spatialEco, https://jeffreyevans.github.io/spatialEco/

NAMESPACE

@@ -19,7 +19,6 @@ export(breeding.density)
 export(built.index)
 export(cgls_urls)
 export(chae)
-export(class.comparison)
 export(classBreaks)
 export(collinear)
 export(combine)
@@ -38,14 +37,9 @@ export(daymet.tiles)
 export(dispersion)
 export(dissection)
 export(divergence)
-export(download.daymet)
-export(download.hansen)
-export(download.prism)
 export(effect.size)
 export(erase.point)
-export(explode)
 export(extract.vertices)
-export(focal.lmetrics)
 export(fuzzySum)
 export(gaussian.kernel)
 export(geo.buffer)
@@ -60,12 +54,10 @@ export(impute.loess)
 export(insert)
 export(insert.values)
 export(is.empty)
-export(kde.2D)
 export(kendall)
 export(kl.divergence)
 export(knn)
 export(lai)
-export(land.metrics)
 export(local.min.max)
 export(loess.boot)
 export(loess.ci)
@@ -74,7 +66,6 @@ export(max_extent)
 export(mean_angle)
 export(moments)
 export(morans.plot)
-export(mwCorr)
 export(nni)
 export(nth.values)
 export(o.ring)
@@ -86,11 +77,9 @@ export(overlap)
 export(parea.sample)
 export(parse.bits)
 export(partial.cor)
-export(point.in.poly)
 export(poly.regression)
 export(polyPerimeter)
 export(poly_trend)
-export(polygon_extract)
 export(pp.subsample)
 export(proximity.index)
 export(pseudo.absence)
@@ -117,11 +106,8 @@ export(rm.ext)
 export(rotate.polygon)
 export(sa.trans)
 export(sample.annulus)
-export(sample.line)
-export(sample.poly)
 export(sampleTransect)
 export(sar)
-export(se.news)
 export(separability)
 export(sf.kde)
 export(sf_dissolve)
@@ -133,8 +119,8 @@ export(similarity)
 export(smooth.time.series)
 export(sobal)
 export(sp.kde)
-export(sp.na.omit)
 export(spatial.select)
+export(spatialEcoNews)
 export(spectral.separability)
 export(spherical.sd)
 export(squareBuffer)
@@ -151,5 +137,4 @@ export(tri)
 export(vrm)
 export(winsorize)
 export(wt.centroid)
-export(zonal.stats)
 import(terra)

R/all_pairwise.R

@@ -2,14 +2,15 @@
 #' @description Creates all pairwise combinations list for iteration
 #'
 #' @param x A numeric or character vector 
-#'
-#' @return A list object with increasing all combination objects,
-#'         the first list element are the pairwise comparisons
 #' 
-#' @note This returns a list of vector combinations starting with
+#' @details 
+#' This returns a list of vector combinations starting with
 #' pairwise, as the first nested list element, then in groups of 
 #'  threes, fours, to length of the vector.  
 #'
+#' @return A list object with increasing all combination objects,
+#'         the first list element are the pairwise comparisons
+#'
 #' @author Jeffrey S. Evans    <jeffrey_evans<at>tnc.org>
 #'
 #' @examples

R/annulus.matrix.R

@@ -7,16 +7,16 @@
 #' @param outer.scale  Number of outer rings to set to null.value
 #' @param null.value   Value to set inner and outer scale(s) to
 #'
-#' @return A matrix object with defined null.value and 1, representing retained rings  
-#'
-#' @note 
+#' @details 
 #' This function will return a matrix of 1 and defined null.value based on a specification
 #' of the scale, inner scale and outer scale. The scale defines how many rings will be
 #' represented in the matrix based on (2 * scale - 1). So, a scale of 3 will result in a
 #' 5x5 matrix. The inner.scale and outer.scale arguments represent the > and < rings that
 #' will be set to the defined null.value (see examples). The resulting matrix can be used
 #' as the specified window in a focal function.      
 #'
+#' @return A matrix object with defined null.value and 1, representing retained rings  
+#'
 #' @author Jeffrey S. Evans  <jeffrey_evans@@tnc.org> 
 #'
 #' @examples

R/aspline.downscale.R

@@ -10,6 +10,15 @@
 #' @param plot         (FALSE/TRUE) Plot results
 #' @param ...          Additional arguments passed to earth 
 #'
+#' @details
+#' This function uses Multivariate Adaptive Regression Splines, to downscale a raster based 
+#' on higher-resolution or more detailed raster data specified as covariate(s). This is similar
+#' to the raster.downsample function which uses a robust regression and is a frequentest model for
+#' fitting linear asymptotic relationships whereas, this approach is for fitting nonparametric
+#' functions and should be used when the distributional relationship are complex/nonlinear.
+#' Using add.coords adds spatial coordinates to the model, including creating the associated 
+#' rasters for prediction.      
+#'
 #' @return A list object containing:  
 #' * downscale         Downscaled terra SpatRaster object
 #' * GCV Generalized   Cross Validation (GCV)
@@ -19,32 +28,24 @@
 #' * model             earth MARS model object (if keep.model = TRUE) 
 #' @md
 #'
-#' @note
-#' This function uses Multivariate Adaptive Regression Splines, to downscale a raster based 
-#' on higher-resolution or more detailed raster data specified as covariate(s). This is similar
-#' to the raster.downsample function which uses a robust regression and is a frequentest model for
-#' fitting linear asymptotic relationships whereas, this approach is for fitting nonparametric
-#' functions and should be used when the distributional relationship are complex/nonlinear.
-#' Using add.coords adds spatial coordinates to the model, including creating the associated 
-#' rasters for prediction.      
-#'
 #' @references
 #' Friedman (1991) Multivariate Adaptive Regression Splines (with discussion) 
 #'   Annals of Statistics 19(1):1–141
 #' 
 #' @author Jeffrey S. Evans  <jeffrey_evans@@tnc.org>
 #'
 #' @examples 
-#' \dontrun{
-#' library(geodata)
+#' \donttest{
+#' if (require(geodata, quietly = TRUE)) {
 #' library(terra)
+#' library(geodata)
 #' 
 #' # Download example data (requires geodata package)
-#'   elev <- geodata::elevation_30s(country="SWZ",  path=tempdir())
+#'   elev <- elevation_30s(country="SWZ",  path=tempdir())
 #'     slp <- terrain(elev, v="slope")
 #' 	  x <- c(elev,slp)
 #'         names(x) <- c("elev","slope")
-#'   tmax <- geodata::worldclim_country(country="SWZ", var="tmax", 
+#'   tmax <- worldclim_country(country="SWZ", var="tmax", 
 #'                                      path=tempdir())
 #'     tmax <- crop(tmax[[1]], ext(elev))
 #' 	  names(tmax) <- "tmax"
@@ -60,8 +61,12 @@
 #'       plot(x[[2]], main="slope")
 #'       plot(tmax.ds$downscale, main="Downscaled Temp max")
 #'   par(opar)
-#'  
+#'
+#' } else { 
+#'   cat("Please install geodata package to run example", "\n")
 #' }
+#' }
+#'
 #' @export
 aspline.downscale <- function(x, y, add.coords = TRUE, keep.model = FALSE, 
                               grid.search = FALSE, plot = FALSE, ...) {
@@ -75,7 +80,7 @@ aspline.downscale <- function(x, y, add.coords = TRUE, keep.model = FALSE,
           y <- y[[1]]
     }
     if(grid.search) {
-      if(!any(which(utils::installed.packages()[,1] %in% "caret")))
+      if(length(find.package("caret", quiet = TRUE)) == 0)
         stop("please install caret package to implement grid search")
     }	
   sub.samp.sp <- terra::as.points(x, na.rm=TRUE)
@@ -101,7 +106,7 @@ aspline.downscale <- function(x, y, add.coords = TRUE, keep.model = FALSE,
       names(x)[(nlyr(x)-1):nlyr(x)] <- c("xcoord", "ycoord")
   } 
     if(grid.search) {
-      if(!any(which(utils::installed.packages()[,1] %in% "caret")))
+      if(length(find.package("caret", quiet = TRUE)) == 0)
         stop("please install caret package to implement grid search")
       hyper_grid <- expand.grid(
       degree = 1:3, 

R/background.R

@@ -9,16 +9,16 @@
 #' @param d      Threshold distance for known proximity 
 #' @param type   Type of sample c("systematic", "random", "hexagon", "nonaligned")
 #'
-#' @return A sf POINT feature class or data.frame with x,y coordinates
-#'
-#' @note 
+#' @details 
 #' This function creates a background point sample based on an extent 
 #' or polygon sampling region. The known argument can be used with d 
 #' to remove sample points based on distance-based proximity to existing  
 #' locations (eg., known species locations). The size (p) of the resulting 
 #' sample will be dependent on the known locations and the influence of 
 #' the distance threshold (d). As such, if the know and d arguments are
 #' provided the exact value provided in p will not be returned. 
+#'
+#' @return A sf POINT feature class or data.frame with x,y coordinates
 #' 
 #' @author Jeffrey S. Evans  <jeffrey_evans@@tnc.org> 
 #'
@@ -66,7 +66,7 @@ background <- function(x, p=1000, known=NULL, d=NULL,
 	  if(as.character(unique(sf::st_geometry_type(x))) != "POLYGON")
         stop(deparse(substitute(x)), " x must be an sf POLYGON object")	
     }
-  if(!any(which(utils::installed.packages()[,1] %in% "lwgeom")))
+  if(length(find.package("lwgeom", quiet = TRUE)) == 0)
       stop("please install lwgeom package before running this function")
   if(!is.null(known)){
     if(!inherits(known, c("sf", "sfc")))  

R/bbox_poly.R

@@ -1,50 +1,49 @@
 #' @title Bounding box polygon
+#'
 #' @description Creates a polygon from a vector or raster extent
 #' 
 #' @param x    An sf or terra object or vector of bounding coordinates 
 #'
-#' @return A single feature sf class polygon object
-#'
-#' @note
+#' @details 
 #' If not a spatial object, expected order of input for x is: xmin, ymin, 
 #' xmax, ymax. Where; xmin, ymin and the coordinates of top left corner of the 
 #' bounding box and xmax, ymax represent the bottom right corner. The maximum 
 #' value of xmax is width of the extent while maximum value of ymax is the height 
 #' of the extent.
 #' 
+#' @return A single feature sf class polygon object
+#'
 #' @author Jeffrey S. Evans  <jeffrey_evans@@tnc.org>
 #'
 #' @examples
-#' p = c("sf", "sp", "terra")
-#'   if(any(!unlist(lapply(p, requireNamespace, quietly=TRUE)))) { 
-#'     m = which(!unlist(lapply(p, requireNamespace, quietly=TRUE)))
-#'     message("Can't run examples, please install ", paste(p[m], collapse = " "))
-#'   } else {
-#'   invisible(lapply(p, require, character.only=TRUE))
-#' 
+#' if(require(sp, quietly = TRUE)) {
+#' library(terra)
+#' library(sf)
 #'   data(meuse, package = "sp")
 #'   meuse <- st_as_sf(meuse, coords = c("x", "y"), crs = 28992, 
 #'                     agr = "constant")
 #' 
+#' # raster (terra)
+#' r <- rast(ext(meuse))
+#'   r[] <- runif(ncell(r))
+#'  crs(r) <- "epsg:28992"
+#' e <- bbox_poly(r)
+#' 
+#' plot(r)
+#'   plot(st_geometry(e), border="red", add=TRUE)
+#' 
+#' # extent vector
+#' e <- bbox_poly(c(178605, 329714, 181390, 333611)) 
+#'   plot(e)
+#' 
 #' # vector bounding box
 #' e <- bbox_poly(meuse)
 #' 
 #' plot(st_geometry(meuse), pch=20)
 #'   plot(st_geometry(e), add=TRUE)
 #' 
-#' # raster (terra)
-#'   r <- rast(ext(meuse))
-#'     r[] <- runif(ncell(r))
-#'	   crs(r) <- "epsg:28992"
-#'   e <- bbox_poly(r)
-#'   
-#'   plot(r)
-#'     plot(st_geometry(e), border="red", add=TRUE)
-#' 
-#' # extent vector
-#' e <- bbox_poly(c(178605, 329714, 181390, 333611)) 
-#' plot(e)
-#' 
+#' } else { 
+#'   cat("Please install sp package to run this example", "\n")
 #' }
 #'
 #' @export bbox_poly

R/bearing.distance.R

@@ -8,9 +8,9 @@
 #' @param azimuth       Azimuth to new point
 #' @param EastOfNorth   Specified surveying convention
 #'
-#' @return a new point representing location of baring and distance 
+#' @details East of north is a surveying convention and defaults to true. 
 #'
-#' @note East of north is a surveying convention and defaults to true. 
+#' @return a new point representing location of baring and distance 
 #'
 #' @author Jeffrey S. Evans  <jeffrey_evans@@tnc.org> 
 #'

R/breeding.density.R

@@ -10,6 +10,13 @@
 #' @param self     (TRUE/FALSE) Should source observations be included in 
 #'                 density (default TRUE)
 #'
+#' @details
+#' The breeding density areas model identifies the Nth-percent population exhibiting 
+#' the highest spatial density and counts/frequency. It then buffers these points by 
+#' a specified distance to produce breeding area polygons. If you would like to recreate 
+#' the results in Doherty et al., (2010), then define bw = 6400m and b[if p < 0.75 
+#' b = 6400m, | p >= 0.75 b = 8500m]  
+#'
 #' @return A list object with:
 #' \itemize{ 
 #' \item pop.pts   sf POINT object with points identified within the specified p
@@ -19,13 +26,6 @@
 #' \item p         Specified population percent
 #' }
 #'
-#' @note 
-#' The breeding density areas model identifies the Nth-percent population exhibiting 
-#' the highest spatial density and counts/frequency. It then buffers these points by 
-#' a specified distance to produce breeding area polygons. If you would like to recreate 
-#' the results in Doherty et al., (2010), then define bw = 6400m and b[if p < 0.75 
-#' b = 6400m, | p >= 0.75 b = 8500m]  
-#'
 #' @author Jeffrey S. Evans  <jeffrey_evans@@tnc.org>
 #'
 #' @references
@@ -34,7 +34,7 @@
 #'   Bureau of Land Management. Number L10PG00911
 #'                                                              
 #' @examples 
-#' if(require(sf, quietly = TRUE)) { 
+#' library(sf)
 #' 
 #' n=1500
 #' bb <- rbind(c(-1281299,-761876.5),c(1915337,2566433.5))
@@ -53,8 +53,6 @@
 #'          plot(st_geometry(bd75$pop.pts), pch=20, col='red', add=TRUE)
 #'       legend("bottomright", legend=c("selected areas","selected sites", "all sites"),
 #'              bg="white", fill=c("grey","red", "black"), pt.cex = 2) 
-#' 
-#' }
 #'
 #' @export
 breeding.density <- function(x, pop, p = 0.75, bw = 6400,