Merge pull request #39 from gdauby/devel

Devel to master (version 2.1)

.gitignore

@@ -5,4 +5,5 @@ inst/doc
 *.Rproj
 *.Rhistory
 test_data.R
-data-raw/
+data-raw/
+data/data-raw

NAMESPACE

@@ -3,7 +3,6 @@
 export(AOH.estimation)
 export(AOO.computing)
 export(AOO.decline)
-export(AOO.estimation)
 export(EOO.comp)
 export(EOO.computing)
 export(EOO.sensitivity)
@@ -20,15 +19,16 @@ export(criterion_B)
 export(criterion_C)
 export(criterion_D)
 export(dummy_dist)
-export(frag_assess)
 export(locations.comp)
 export(map.res)
 export(near.threatened)
 export(over.valid.poly)
+export(pop.decline)
 export(pop.decline.fit)
 export(pop.decline.test)
 export(pop.fluctuation)
 export(proj_crs)
+export(severe_frag)
 export(subpop.comp)
 export(subpop.estimation)
 export(subpop.radius)
@@ -50,6 +50,8 @@ importFrom(foreach,foreach)
 importFrom(grDevices,chull)
 importFrom(grDevices,rgb)
 importFrom(graphics,axis)
+importFrom(graphics,box)
+importFrom(graphics,layout)
 importFrom(graphics,legend)
 importFrom(graphics,mtext)
 importFrom(graphics,par)
@@ -67,6 +69,7 @@ importFrom(sf,st_as_sf)
 importFrom(sf,st_coordinates)
 importFrom(sf,st_distance)
 importFrom(sf,st_geometry)
+importFrom(sf,st_intersects)
 importFrom(sf,st_linestring)
 importFrom(sf,st_multilinestring)
 importFrom(sf,st_sfc)

R/AOO.computing.R

@@ -1,7 +1,8 @@
 
 #' @title Area of occupancy
 #'
-#' @description Compute areas of occupancy (AOO) for multiple taxa in square kilometers
+#' @description Compute areas of occupancy (AOO) for multiple taxa in square
+#' kilometers
 #'
 #' @author Gilles Dauby \email{gilles.dauby@@ird.fr}
 #'
@@ -11,14 +12,12 @@
 #' @param nbe.rep.rast.AOO numeric, by default is 0. Indicate the number of
 #' raster with random starting position used for estimating the AOO. If 0 but
 #' some translation of the raster are still done.
-#' @param parallel logical, by default is FALSE. Whether running in parallel.
-#' @param NbeCores integer, by default is 2. Register the number of cores for
-#' parallel execution. Only used if parallel is TRUE.
-#' @param show_progress logical, by default is TRUE. Whether a progress bar
-#' during computation is shown.
+#' @inheritParams activate_parallel
+#' @param show_progress logical. Whether progress informations should displayed.
+#' TRUE by default
 #' @param export_shp logical, by default is FALSE. Whether a shapefile of
 #' occupied cells should be exported.
-#' @param proj_type character or numeric, by default is "cea", see Details.
+#' @inheritParams proj_crs
 #' 
 #' @details 
 #' # Input data
@@ -48,7 +47,7 @@
 #' See `proj_type`
 #' 
 #' 
-#' @references Gaston & Fuller 2009 The sizes of species'geographic ranges,
+#' @references Gaston & Fuller 2009 The sizes of species' geographic ranges,
 #' Journal of Applied Ecology, 49 1-9
 #'
 #' @return 
@@ -66,9 +65,9 @@
 #'
 #'
 #'# This would estimate AOO for all taxa by overlaying randomly a 
-#'# grid 10 times. For each taxa, the minimum value is kept
+#'# grid 3 times. For each taxa, the minimum value is kept
 #'
-#' AOO <- AOO.computing(dataset.ex, nbe.rep.rast.AO = 10)
+#' AOO <- AOO.computing(dataset.ex, nbe.rep.rast.AO = 3)
 #'
 #'
 #' @importFrom utils txtProgressBar setTxtProgressBar
@@ -153,7 +152,7 @@ AOO.computing <- function(XY,
 
  if(parallel) parallel::stopCluster(cl)
  if(show_progress) close(pb)
-
+ 
  res <- unlist(output[names(output) != "spatial"])
 
  res_df[res_df$tax %in% names(res), 2] <-
@@ -164,11 +163,11 @@ AOO.computing <- function(XY,
  "AOO could not computed because grid cells would overlap with antimeridian"
 
  if (export_shp) {
-
+ 
  shapes <- output[names(output) == "spatial"]
  shapes <- do.call('rbind', shapes)
  row.names(shapes) <- 1:nrow(shapes)
-
+ 
  }
 
  } else {
@@ -189,8 +188,8 @@ AOO.computing <- function(XY,
 
 
 #' @importFrom foreach %dopar% %do% foreach
-#' @keywords intenal
-#' @export
+#' @keywords internal
+#' 
 AOO.estimation <- function(coordEAC,
  cell_size = 2,
  nbe_rep = 0,

R/EOO.comp.R

@@ -15,7 +15,7 @@
 #' @param proj_type crs
 #' @param reproject logical FALSE whether the polygon should be converted to geographic coordinates if mode is `planar`
 #'
-#' @author Gilles Dauby & Renato A. Ferreira de LimaA
+#' @author Gilles Dauby & Renato A. Ferreira de Lima
 #' 
 #' @return A list
 #' \enumerate{

R/EOO.computing.R

@@ -20,13 +20,15 @@
 #' If `exclude.area` is TRUE and country_map is not provided, 
 #' the world country polygons used comes from the package [rnaturalearth](https://www.rdocumentation.org/packages/rnaturalearth/versions/0.1.0/topics/ne_countries)
 #' 
-#' By default (`mode = "spheroid"`),the area of the polygon is based 
-#' on a polygon in longitude/latitude coordinates considering the earth as an ellipsoid. 
+#' By default (`mode = "spheroid"`), the area of the polygon is based on a
+#' polygon in longitude/latitude coordinates considering the earth as an
+#' ellipsoid.
 #' 
 #' To make a polygon more accurate, the function use the function `st_segmentize` 
 #' from the [sf](https://CRAN.R-project.org/package=sf) package.
-#' This adds vertices on the great circles (in order to make shortest distances between points, see example below) 
-#' which can make difference for species with large distribution. 
+#' This adds vertices on the great circles (in order to make shortest distances
+#' between points, see example below) which can make difference for species with
+#' large distribution.
 #' 
 #' An estimation of EOO based on projected data is also possible (`mode = "planar"`).
 #' This allow the user to use its own projection.
@@ -52,8 +54,9 @@
 #' 
 #' **Limitation**\cr
 #' 
-#' For a species whose occurrences span more than 180 degrees, EOO should not be considered. 
-#' This is the case for example for species whose distribution span the 180th meridian.
+#' For a species whose occurrences span more than 180 degrees, EOO should not be
+#' considered. This is the case for example for species whose distribution span
+#' the 180th meridian.
 #' 
 #' @param XY `dataframe` see Details
 #' @param exclude.area a logical, if TRUE, areas outside of `country_map`
@@ -79,12 +82,14 @@
 #' @param method.less.than3 a character string. If equal to "arbitrary", will
 #' give a value to species with two unique occurrences, see Details. By default
 #' is "not comp"
-#' @param file.name a character string. Name file for exported results in csv file. By default is "EOO.results"
-#' @param parallel a logical. Whether running in parallel. By default, it is FALSE
-#' @param NbeCores an integer. Register the number of cores for parallel execution. By default, it is 2
-#' @param show_progress logical. Whether a progress bar should displayed. TRUE by default
-#' @param mode character string either 'spheroid' or 'planar'. By default 'spheroid'
+#' @param file.name a character string. Name file for exported results in csv
+#' file. By default is "EOO.results"
+#' @param show_progress logical. Whether progress informations should displayed.
+#' TRUE by default
+#' @param mode character string either 'spheroid' or 'planar'. By default
+#' 'spheroid'
 #' @inheritParams proj_crs
+#' @inheritParams activate_parallel
 #'
 #' @return
 #' If `export_shp` is FALSE, a `dataframe` with one field
@@ -103,7 +108,7 @@
 #' 
 #' <https://github.com/azizka/speciesgeocodeR>
 #' 
-#' @references Gaston & Fuller 2009 The sizes of species'geographic ranges,
+#' @references Gaston & Fuller 2009 The sizes of species' geographic ranges,
 #' Journal of Applied Ecology, 49 1-9
 #' 
 #' @examples

R/EOO.sensitivity.R

@@ -64,7 +64,7 @@
 #' 
 #' **Notes on computational time** The processing time depends on several
 #' factors, including the total number of occurrences, number of confidence
-#' levels rpovided and user's computer specifications. Using argument `parallel`
+#' levels provided and user's computer specifications. Using argument `parallel`
 #' equals `TRUE`, greatly increase the processing time, but the processing of
 #' large data sets (millions of occurrences) may take hours. On a Intel Core i5,
 #' CPU 1.70GHz, 64-bit OS and 16 GB RAM it took 20 min to process about 800

R/ICtab.mod.select.R

@@ -27,7 +27,7 @@
 #' For the process of selecting the best model, we followed some basic steps.
 #' By default, if two or more models had delta-AIC smaller than the cutoff
 #' provided, the more parsimonious model (i.e. the model with less parameters)
-#' is selected. However, this decision can be changed (i.e. slect the model
+#' is selected. However, this decision can be changed (i.e. select the model
 #' with best fit) by setting the argument 'parsimony' to FALSE. Next, if more
 #' than one model is selected (i.e. both have the same number of parameters),
 #' the selection process give preference to models that are not linear or

R/Locations.estimation.R

@@ -7,7 +7,10 @@
 #' @param nbe_rep integer
 #' @param export_shp logical
 #' @param proj_type character string
-#' @param Rel_cell_size numeric, if `method ="sliding_scale"`, `Cell_size_locations` is ignored and the resolution is given by the maximum distance separating two occurrences multiplied by `Rel_cell_size`. By default, it is 0.05
+#' @param rel_cell_size numeric, if `method ="sliding_scale"`,
+#' `Cell_size_locations` is ignored and the resolution is given by the maximum
+#' distance separating two occurrences multiplied by `rel_cell_size`. By
+#' default, it is 0.05
 #' @param method character string
 #' 
 #' @return a list
@@ -21,7 +24,7 @@ locations.estimation <- function(coordEAC,
  export_shp = FALSE,
  proj_type = proj_type,
  method = "fixed_grid",
- Rel_cell_size = 0.05
+ rel_cell_size = 0.05
 
 ) {
 
@@ -33,7 +36,7 @@ locations.estimation <- function(coordEAC,
 
  pairwise_dist <- stats::dist(coordEAC[, 1:2], upper = F)
 
- cell_size <- max(pairwise_dist) * Rel_cell_size / 1000
+ cell_size <- max(pairwise_dist) * rel_cell_size / 1000
 
  } else{
 

R/activate_parallel.R

@@ -1,18 +1,22 @@
 #' @title Internal function
 #'
-#' @description Activate paralle processing
+#' @description Activate parallel processing
 #'
 #' @author Gilles Dauby, \email{gildauby@gmail.com}
 #' 
-#' @param XY data.frame
-#' @param mode character string either 'spheroid' or 'planar'. By default 'spheroid'
-#' @param proj_type crs
+#' @param parallel a logical. Whether running should be performed in parallel.
+#' FALSE by default.
+#' @param NbeCores an integer. Register the number of cores for parallel
+#' execution. Two by default.
 #' 
 #' @importFrom doSNOW registerDoSNOW
 #' @importFrom parallel makePSOCKcluster
 #' @importFrom foreach %dopar% %do% foreach
+#' 
 #' @keywords internal
+#' 
 #' @export
+#' 
 activate_parallel <- function(parallel = FALSE, NbeCores = 2) {
  if (parallel) {
  cl <- parallel::makePSOCKcluster(NbeCores)

R/ahull_to_SPLDF.R

@@ -5,8 +5,10 @@
 #' @param x ahull class object
 #'
 #' @details 
-#' The functions ahull_to_SPLDF and alpha.hull.poly were originally posted in the website https://casoilresource.lawr.ucdavis.edu/software/r-advanced-statistical-package/working-spatial-data/converting-alpha-shapes-sp-objects/
-#' in a now broken link. It is also used in functions written by David Bucklin, see https://github.com/dnbucklin/r_movement_homerange 
+#' The functions ahull_to_SPLDF and alpha.hull.poly were originally posted in
+#' the website https://casoilresource.lawr.ucdavis.edu/software/r-advanced-statistical-package/working-spatial-data/converting-alpha-shapes-sp-objects/
+#' in a now broken link. It is also used in functions written by David Bucklin,
+#' see https://github.com/dnbucklin/r_movement_homerange
 #'
 #' @importFrom sf st_linestring st_multilinestring st_as_sf st_sfc
 #' 

R/cat_downlist.R

@@ -1,13 +1,13 @@
 #' @title Downlist Threat Categories
 #'
 #' @description Perform the downlisting of threat categories which is often
-#' necessary for regional conservation assessmentes (IUCN 2012).
+#' necessary for regional conservation assessments (IUCN 2012).
 #'
 #' @param cats character. The vector containing the IUCN threat categories.
 #' @param down.by numerical. The number of steps to downlist the categories.
 #' Default to 1.
 #' @param dd logical. Should the Data Deficient (DD) category be included in the
-#' downlisting? Defaut to FALSE.
+#' downlisting? Default to FALSE.
 #' @param sign logical. Should the degrees sign be indicated in the downlisted
 #' category. Default to TRUE.
 #'
@@ -17,12 +17,12 @@
 #' thus to the possibility of a possible rescue effect (IUCN 2012).
 #'
 #' Although the IUCN (2012) considers the exceptional possibility of
-#' uplisting, the function only performs downliting of the categories of
+#' uplisting, the function only performs downlisting of the categories of
 #' threat. Downlisting normally is a one-step change in the category (i.e.
 #' from EN to VU), but this can be controlled by the argument ```down.by```
 #' (default to 1).
 #'
-#' By default, the Data Deficient category is excluded from the donwlisting.
+#' By default, the Data Deficient category is excluded from the downlisting.
 #' The Least Concern category remains unaltered as well.
 #'
 #' Note that "if it is unknown whether or not extra-regional populations

R/cat_mult_criteria.R

@@ -12,7 +12,7 @@
 #' category ('main.criteria'). It also returns the auxiliary category provided
 #' by other criteria ('aux.criteria'), separated by a ';'
 #' 
-#' @details The definiton of the main category of threat, follows the
+#' @details The definition of the main category of threat, follows the
 #' recommendations of IUCN (2019) that states "Only the criteria for the
 #' highest category of threat that the taxon qualifies for should be listed".
 #' Therefore, the consensus category is the highest category of threat among
@@ -40,10 +40,21 @@
 #' @export cat_mult_criteria
 cat_mult_criteria <- function(assess.df = NULL, evidence.df = NULL){
 
+ assess.df$tmp.order.plantr <- 1:dim(assess.df)[1]
  tmp <- assess.df
  tax <- names(tmp)[1]
- n.crits <- dim(tmp)[2]
- assess.df$order <- 1:dim(tmp)[1]
+
+ possible_crits <- c(LETTERS[1:5], paste0(LETTERS[1], 1:4),
+ paste0(rep(LETTERS[2:4], each = 2), 1:2),
+ paste0("category_", LETTERS[1:5]), "D2.Loc", "D.AOO")
+ if (!any(names(tmp) %in% possible_crits))
+ stop("Please provide a data frame with at least one of the following column names: ", 
+ paste0(possible_crits, collapse = ", "))
+ col.name.df <- names(tmp)[names(tmp) %in% possible_crits]
+ tmp0 <- tmp[, names(tmp) %in% possible_crits]
+ n.crits <- dim(tmp0)[2]
+
+ tmp <- cbind.data.frame(tax = tmp[[1]], tmp0)
 
  ## Establishing an hierarchy of data availability
  hier <- c("Observed","Estimated","Projected","Inferred","Suspected")
@@ -92,16 +103,20 @@ cat_mult_criteria <- function(assess.df = NULL, evidence.df = NULL){
  tmp$aux.criteria <- gsub(": \\+", ": ", tmp$aux.criteria, perl = TRUE)
  tmp$aux.criteria <- gsub("\\+$", "", tmp$aux.criteria, perl = TRUE)
  tmp$aux.criteria <- gsub("\\+;", ";", tmp$aux.criteria, perl = TRUE)
+ tmp$aux.criteria <- gsub("category_B", "B1+B2", tmp$aux.criteria, perl = TRUE)
+ tmp$aux.criteria <- gsub("category_C", "C1+C2", tmp$aux.criteria, perl = TRUE)
 
  tmp$main.criteria[is.infinite(as.double(tmp$category))] <- ""
  tmp$category[is.infinite(as.double(tmp$category))] <- ""
  tmp$category <- stringr::str_replace_all(tmp$category, rpl.cds)
+ tmp$category <- gsub("category_B", "B1+B2", tmp$category, perl = TRUE)
+ tmp$category <- gsub("category_C", "C1+C2", tmp$category, perl = TRUE)
 
  #Merging with the entry data.frame
  res <- merge(assess.df, tmp[,c(tax,"category","main.criteria","aux.criteria")], 
  by = tax)
- res <- res[order(res$order),]
- res <- res[,-which(names(res) %in% "order")]
+ res <- res[order(res$tmp.order.plantr),]
+ res <- res[,-which(names(res) %in% "tmp.order.plantr")]
 
  return(res)
 }

R/cell.occupied.R

@@ -214,7 +214,7 @@ cell.occupied <-
 
  r2_pol <-
  terra::as.polygons(
- r2_)
+ r2_, aggregate = FALSE)
 
  r2_pol_sf <- sf::st_as_sf(r2_pol)
 

R/coord.check.R

@@ -6,6 +6,7 @@
 #' @param listing logical, whether the dataset should be splitted in a list by taxa
 #' @param proj_type crs
 #' @param listing_by_valid logical
+#' @param cell_size numeric value
 #' @param check_eoo logical
 #' 
 #'