cran fixes and snow rm

sylvainschmitt · Oct 24, 2023 · 58f669b · 58f669b
1 parent 8d7cdf6
commit 58f669b
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -43,8 +43,7 @@ Imports:
     parallel (>= 3.5.2),
     leaflet (>= 2.2.0),
     magrittr (>= 2.0.3),
-    sdm (>= 1.1.8),
-    snow (>= 0.4-4)
+    sdm (>= 1.1.8)
 Depends:
     R (>= 3.2.2)
 Collate:

diff --git a/NAMESPACE b/NAMESPACE
@@ -69,6 +69,8 @@ importFrom(mgcv,gam)
 importFrom(mgcv,gam.control)
 importFrom(nnet,nnet)
 importFrom(parallel,detectCores)
+importFrom(parallel,makeCluster)
+importFrom(parallel,stopCluster)
 importFrom(poibin,dpoibin)
 importFrom(randomForest,randomForest)
 importFrom(raster,"values<-")
@@ -149,8 +151,6 @@ importFrom(shinydashboard,sidebarMenuOutput)
 importFrom(shinydashboard,tabBox)
 importFrom(shinydashboard,tabItem)
 importFrom(shinydashboard,tabItems)
-importFrom(snow,makeCluster)
-importFrom(snow,stopCluster)
 importFrom(spThin,thin)
 importFrom(stats,aggregate.data.frame)
 importFrom(stats,cor)

diff --git a/R/ensemble_modelling.R b/R/ensemble_modelling.R
@@ -4,8 +4,7 @@
 #' @importFrom foreach foreach %dopar%
 #' @importFrom doParallel registerDoParallel
 #' @importFrom iterators icount
-#' @importFrom parallel detectCores
-#' @importFrom snow makeCluster stopCluster
+#' @importFrom parallel detectCores makeCluster stopCluster
 NULL
 
 #'Build an ensemble SDM that assembles multiple algorithms
@@ -181,7 +180,7 @@ NULL
 #'@section Maximum Entropy (\strong{MAXENT}) : Uses the \code{maxent} function
 #'  from the package 'dismo'. Make sure that you have correctly installed the
 #'  maxent.jar file in the folder ~\\R\\library\\version\\dismo\\java available
-#'  at \url{https://www.cs.princeton.edu/~schapire/maxent/}. As with the other algorithms, you can set parameters by supplying \code{maxent.args=list(arg1=val1,arg2=val2)}. Mind that arguments are passed from dismo to the MAXENT software again as an argument list  (see \code{\link[dismo]{maxent}} for more details).
+#'  at \url{https://biodiversityinformatics.amnh.org/open_source/maxent/}. As with the other algorithms, you can set parameters by supplying \code{maxent.args=list(arg1=val1,arg2=val2)}. Mind that arguments are passed from dismo to the MAXENT software again as an argument list  (see \code{\link[dismo]{maxent}} for more details).
 #'  No specific defaults are set with this method.
 #'
 #'@section Artificial Neural Network (\strong{ANN}) : Uses the \code{nnet}

diff --git a/R/mapDiversity.R b/R/mapDiversity.R
@@ -65,7 +65,7 @@ NULL
 #'  J.M. Calabrese, G. Certain, C.  Kraan, & C.F. Dormann (2014) "Stacking
 #'  species distribution  models  and  adjusting  bias  by linking them to
 #'  macroecological models." \emph{Global Ecology and Biogeography} 23:99-112
-#'  \url{http://portal.uni-freiburg.de/biometrie/mitarbeiter/dormann/calabrese2013globalecolbiogeogr.pdf}
+#'  \url{https://onlinelibrary.wiley.com/doi/full/10.1111/geb.12102}
 #'
 #' @name mapDiversity
 NULL

diff --git a/R/modelling.R b/R/modelling.R
@@ -103,19 +103,19 @@ NULL
 #'  \item{'...'}{See algorithm in detail section} }
 #'
 #'@section Generalized linear model (\strong{GLM}) : Uses the \code{glm}
-#'  function from the package 'stats'. You can set parameters by supplying \code{glm.args=list(arg1=val1,arg2=val2)} (see \code{\link[stats]{glm}} for all settable arguments).  
+#'  function from the package 'stats'. You can set parameters by supplying \code{glm.args=list(arg1=val1,arg2=val2)} (see \code{\link[stats]{glm}} for all settable arguments).
 #'  The following parameters have defaults: \describe{
 #'  \item{test}{character. Test used to evaluate the SDM, default 'AIC'.}
 #'  \item{control}{list (created with \code{\link[stats]{glm.control}}).
-#'  Contains parameters for controlling the fitting process. Default is \code{glm.control(epsilon = 1e-08, maxit = 500)}. 
-#'  'epsilon' is a numeric and defines the positive convergence tolerance (eps). The iterations converge when \emph{|dev - dev_{old}|/(|dev| + 0.1) < eps}.
+#'  Contains parameters for controlling the fitting process. Default is \code{glm.control(epsilon = 1e-08, maxit = 500)}.
+#'  'epsilon' is a numeric and defines the positive convergence tolerance (eps).
 #'  'maxit' is an integer giving the maximal number of IWLS (Iterative Weighted Last Squares) iterations.} }
 #'
 #'@section Generalized additive model (\strong{GAM}) : Uses the \code{gam}
 #'  function from the package 'mgcv'. You can set parameters by supplying \code{gam.args=list(arg1=val1,arg2=val2)} (see \code{\link[mgcv]{gam}} for all settable arguments).
 #'  The following parameters have defaults: \describe{\item{test}{character.
 #'  Test used to evaluate the model, default 'AIC'.} \item{control}{list (created with \code{\link[mgcv]{gam.control}}).
-#'  Contains parameters for controlling the fitting process. Default is \code{gam.control(epsilon = 1e-08, maxit = 500)}. 
+#'  Contains parameters for controlling the fitting process. Default is \code{gam.control(epsilon = 1e-08, maxit = 500)}.
 #'  'epsilon' is a numeric used for judging the conversion of the GLM IRLS (Iteratively Reweighted Least Squares) loop. 'maxit' is an integer giving the maximum number of IRLS iterations to perform.} }
 #'
 #'@section Multivariate adaptive regression splines (\strong{MARS}) : Uses the
@@ -148,7 +148,7 @@ NULL
 #'  function from the package 'rpart'. You can set parameters by supplying \code{cta.args=list(arg1=val1,arg2=val2)} (see \code{\link[rpart]{rpart}} for all settable arguments).
 #'  The following parameters have defaults: \describe{
 #'  \item{control}{list (created with \code{\link[rpart]{rpart.control}}).
-#'  Contains parameters for controlling the rpart fit. The default is \code{rpart.control(minbucket=1, xval=3)}. 
+#'  Contains parameters for controlling the rpart fit. The default is \code{rpart.control(minbucket=1, xval=3)}.
 #'  'mibucket' is an integer giving the minimum number of observations in any
 #'  terminal node. 'xval' is an integer defining the number of
 #'  cross-validations.} }
@@ -164,7 +164,7 @@ NULL
 #'@section Maximum Entropy (\strong{MAXENT}) : Uses the \code{maxent} function
 #'  from the package 'dismo'. Make sure that you have correctly installed the
 #'  maxent.jar file in the folder ~\\R\\library\\version\\dismo\\java available
-#'  at \url{https://www.cs.princeton.edu/~schapire/maxent/}. As with the other algorithms, you can set parameters by supplying \code{maxent.args=list(arg1=val1,arg2=val2)}. Mind that arguments are passed from dismo to the MAXENT software again as an argument list  (see \code{\link[dismo]{maxent}} for more details).
+#'  at \url{https://biodiversityinformatics.amnh.org/open_source/maxent/}. As with the other algorithms, you can set parameters by supplying \code{maxent.args=list(arg1=val1,arg2=val2)}. Mind that arguments are passed from dismo to the MAXENT software again as an argument list  (see \code{\link[dismo]{maxent}} for more details).
 #'  No specific defaults are set with this method.
 #'
 #'@section Artificial Neural Network (\strong{ANN}) : Uses the \code{nnet}
@@ -372,7 +372,7 @@ modelling <- function(algorithm, Occurrences, Env, Xcol = "Longitude",
     if (GUI) {
       incProgress(1/5, detail = "SDM projected")
     }
-    
+
     # Axes evaluation
     if (verbose) {
       cat("Model axes contribution evaluation...\n")

diff --git a/R/stack_modelling.R b/R/stack_modelling.R
@@ -4,8 +4,7 @@
 #' @importFrom raster stack writeRaster
 #' @importFrom foreach foreach %dopar%
 #' @importFrom doParallel registerDoParallel
-#' @importFrom parallel detectCores
-#' @importFrom snow makeCluster stopCluster
+#' @importFrom parallel detectCores makeCluster stopCluster
 NULL
 
 #'Build an SSDM that assembles multiple algorithms and species.
@@ -162,7 +161,7 @@ NULL
 #'  \item{test}{character. Test used to evaluate the SDM, default 'AIC'.}
 #'  \item{control}{list (created with \code{\link[stats]{glm.control}}).
 #'  Contains parameters for controlling the fitting process. Default is \code{glm.control(epsilon = 1e-08, maxit = 500)}.
-#'  'epsilon' is a numeric and defines the positive convergence tolerance (eps). The iterations converge when \emph{|dev - dev_{old}|/(|dev| + 0.1) < eps}.
+#'  'epsilon' is a numeric and defines the positive convergence tolerance (eps).
 #'  'maxit' is an integer giving the maximal number of IWLS (Iterative Weighted Last Squares) iterations.} }
 #'
 #'@section Generalized additive model (\strong{GAM}) : Uses the \code{gam}
@@ -218,7 +217,7 @@ NULL
 #'@section Maximum Entropy (\strong{MAXENT}) : Uses the \code{maxent} function
 #'  from the package 'dismo'. Make sure that you have correctly installed the
 #'  maxent.jar file in the folder ~\\R\\library\\version\\dismo\\java available
-#'  at \url{https://www.cs.princeton.edu/~schapire/maxent/}. As with the other algorithms, you can set parameters by supplying \code{maxent.args=list(arg1=val1,arg2=val2)}. Mind that arguments are passed from dismo to the MAXENT software again as an argument list  (see \code{\link[dismo]{maxent}} for more details).
+#'  at \url{https://biodiversityinformatics.amnh.org/open_source/maxent/}. As with the other algorithms, you can set parameters by supplying \code{maxent.args=list(arg1=val1,arg2=val2)}. Mind that arguments are passed from dismo to the MAXENT software again as an argument list  (see \code{\link[dismo]{maxent}} for more details).
 #'  No specific defaults are set with this method.
 #'
 #'@section Artificial Neural Network (\strong{ANN}) : Uses the \code{nnet}

diff --git a/cran-comments.md b/cran-comments.md
@@ -5,22 +5,13 @@
 
 ## R CMD check results
 
-There were no ERRORs or WARNINGs.
-
-There was one NOTE:
-
-  Imports includes 24 non-default packages.
-   Importing from so many packages makes the package vulnerable to any of
-   them becoming unavailable.  Move as many as possible to Suggests and
-   use conditionally.
-
-The fact that we quickly updated the package following several dependency
-changes shows that we are able to assume all the needed dependencies.
+There were no NOTEs, ERRORs or WARNINGs.
 
 ## Resubmission
 
 This is a resubmission. In this version I have:
 
+- removed superseded package snow
 - removed rgdal and sp from the package dependencies following r-spatial package archiving
 - updated invalid URLs
 - removed lost braces from documentation
diff --git a/man/ensemble_modelling.Rd b/man/ensemble_modelling.Rd
diff --git a/man/mapDiversity.Rd b/man/mapDiversity.Rd
diff --git a/man/modelling.Rd b/man/modelling.Rd
diff --git a/man/stack_modelling.Rd b/man/stack_modelling.Rd
diff --git a/tests/testthat/test_parallel_ESDM.R b/tests/testthat/test_parallel_ESDM.R
@@ -5,6 +5,6 @@ test_that('Ensemble parallelization', {
   ESDM <- ensemble_modelling(c('CTA', 'MARS'), Occurrences, Env, rep = 1,
                             Xcol = 'LONGITUDE', Ycol = 'LATITUDE',
                             ensemble.thresh = c(0), verbose = FALSE, cores = 2,
-                            minimal.memory = TRUE, tmp = TRUE)
+                            tmp = TRUE)
   expect_is(ESDM, 'Ensemble.SDM')
 })
diff --git a/tests/testthat/test_parallel_SSDM.R b/tests/testthat/test_parallel_SSDM.R
@@ -5,7 +5,7 @@ test_that('Stack parallelization', {
     SSDM <- stack_modelling(c('CTA', 'MARS'), Occurrences, Env, rep = 1,
                             Xcol = 'LONGITUDE', Ycol = 'LATITUDE', Spcol = 'SPECIES',
                             ensemble.thresh = c(0), method="pSSDM", uncertainty = TRUE,
-                            verbose = FALSE, cores = 2, parmode = i , minimal.memory = TRUE, tmp = FALSE)
+                            verbose = FALSE, cores = 2, parmode = i , tmp = FALSE)
     expect_is(SSDM, 'Stacked.SDM')
   }
 })