Example update using climate4R.datasets

SantanderMetGroup · May 23, 2020 · 8a2759e · 8a2759e
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,7 +1,7 @@
 Package: downscaleR
 Depends:
-    R(>= 3.1.0),
-    transformeR(>= 1.5.0)
+    R(>= 3.5.0),
+    transformeR(>= 2.0.0)
 Imports:
     reticulate,
     lubridate,
@@ -21,17 +21,18 @@ Imports:
     magrittr,
     sp,
     gridGraphics,
-    gridExtra
+    gridExtra,
+    visualizeR
 Suggests:
+    climate4R.datasets,
     loadeR,
     loadeR.ECOMS,
-    visualizeR,
     knitr,
     rmarkdown
 Type: Package
 Title: A climate4R package for statistical downscaling <http://meteo.unican.es/climate4r>
 Version: 3.2.0
-Date: 2020-04-23
+Date: 2020-05-23
 Authors@R: as.person(c(
     "Santander Meteorology Group <http://meteo.unican.es> [cph]",
     "Joaquín Bedia <bediaj@unican.es> [aut, cre]",
@@ -46,7 +47,7 @@ Authors@R: as.person(c(
     "Jorge B. Medina <bmedina@ifca.unican.es> [aut]",
     "Beata Szabo-Takacs <szabo.b@czechglobe.cz> [ctb]",
     "Max Tuni <max@predictia.es> [ctb]",
-    "Ana Casanueva <ana.casanueva@unican.es> [ctb]"))
+    "Ana Casanueva <ana.casanueva@unican.es> [aut]"))
 BugReports: https://github.com/SantanderMetGroup/downscaleR/issues
 URL: http://www.meteo.unican.es/climate4r
 Encoding: UTF-8

diff --git a/NAMESPACE b/NAMESPACE
@@ -77,7 +77,6 @@ importFrom(transformeR,binaryGrid)
 importFrom(transformeR,bindGrid)
 importFrom(transformeR,climatology)
 importFrom(transformeR,dataSplit)
-importFrom(transformeR,draw.world.lines)
 importFrom(transformeR,fillGridDates)
 importFrom(transformeR,getCoordinates)
 importFrom(transformeR,getDim)
@@ -97,11 +96,11 @@ importFrom(transformeR,isRegular)
 importFrom(transformeR,makeMultiGrid)
 importFrom(transformeR,mat2Dto3Darray)
 importFrom(transformeR,parallelCheck)
-importFrom(transformeR,plotClimatology)
 importFrom(transformeR,redim)
 importFrom(transformeR,scaleGrid)
 importFrom(transformeR,selectPar.pplyFun)
 importFrom(transformeR,subsetDimension)
 importFrom(transformeR,subsetGrid)
 importFrom(transformeR,typeofGrid)
 importFrom(utils,packageDescription)
+importFrom(visualizeR,spatialPlot)
diff --git a/R/biasCorrection.R b/R/biasCorrection.R
@@ -194,6 +194,7 @@
 #' @author S. Herrera, M. Iturbide, J. Bedia
 #' @export
 #' @examples \donttest{
+#' require(climate4R.datasets)
 #' data("EOBS_Iberia_pr")
 #' data("CORDEX_Iberia_pr")
 #' y <- EOBS_Iberia_pr

diff --git a/R/downscale.R b/R/downscale.R
@@ -48,38 +48,44 @@
 #' @export 
 #' @family downscaling.functions
 #' @importFrom transformeR scaleGrid
-#' @examples
+#' @examples \donttest{
+#' require(transformeR)
+#' require(climate4R.datasets)
+#' data("NCEP_Iberia_hus850")
+#' data("NCEP_Iberia_ta850")
 #' x <- makeMultiGrid(NCEP_Iberia_hus850, NCEP_Iberia_ta850)
 #' newdata <- subsetGrid(x, years = 1994:1995)
 #' x <- subsetGrid(x, years = 1985:1993)
 #' # Loading predictands
+#' data("VALUE_Iberia_pr")
 #' y <- VALUE_Iberia_pr
 #' y <- getTemporalIntersection(obs = y,prd = x, "obs" )
 #' x <- getTemporalIntersection(obs = y,prd = x, "prd" )
 #' ### Analogs ###
 #' # None
-#' yp <- downscale(y,x,method = "analogs")
-#' yp <- downscale(y,x,newdata,method = "analogs")
+#' yp <- downscale(y, x, method = "analogs")
+#' yp <- downscale(y, x, newdata, method = "analogs")
 #' # kfold
-#' yp <- downscale(y,x,method = "analogs", n.pcs = 15,
-#'                 cross.val = "kfold", folds = list(c(1985,1986,1987),
-#'                                                   c(1988,1989,1990),
-#'                                                   c(1991,1992,1993)))
+#' yp <- downscale(y, x, method = "analogs", n.pcs = 15,
+#'                 cross.val = "kfold", folds = list(c(1985, 1986, 1987),
+#'                                                   c(1988, 1989, 1990),
+#'                                                   c(1991, 1992, 1993)))
 #' # Leave-one-year-out
-#' yp <- downscale(y,x,method = "analogs", n.pcs = 15,
+#' yp <- downscale(y, x, method = "analogs", n.pcs = 15,
 #'                 cross.val = "loocv")
 #' 
 #' ### GLM ###
 #' # None
-#' yp <- downscale(y,x,method = "glm", simulate = FALSE,  n.pcs = 10,
+#' yp <- downscale(y, x, method = "glm", simulate = FALSE, n.pcs = 10,
 #'                 wet.threshold = 1)
-#' yp <- downscale(y,x,method = "glm", simulate = TRUE, n.pcs = 10,
+#' yp <- downscale(y, x, method = "glm", simulate = TRUE, n.pcs = 10,
 #'                 wet.threshold = 1)
 #' # kfold
-#' yp <- downscale(y,x,method = "glm", simulate = FALSE, n.pcs = 10,
-#'                 cross.val = "kfold", folds = list(c(1985,1986,1987),
-#'                                                   c(1988,1989,1990),
-#'                                                   c(1991,1992,1993)))
+#' yp <- downscale(y, x, method = "glm", simulate = FALSE, n.pcs = 10,
+#'                 cross.val = "kfold", folds = list(c(1985, 1986, 1987),
+#'                                                   c(1988, 1989, 1990),
+#'                                                   c(1991, 1992, 1993)))
+#' }
 
 downscale <- function(y,
                        x,
@@ -179,4 +185,4 @@ downscale <- function(y,
     }
   }
   return(yp)
-}
+}
diff --git a/R/downscaleCV.R b/R/downscaleCV.R
@@ -74,8 +74,9 @@
 #' @family downscaling.functions
 #' @author J. Bano-Medina
 #' @export
-#' @examples 
+#' @examples \donttest{
 #' require(transformeR)
+#' require(climate4R.datasets)
 #' data(NCEP_Iberia_hus850, NCEP_Iberia_ta850)
 #' x <- makeMultiGrid(NCEP_Iberia_hus850, NCEP_Iberia_ta850)
 #' x <- subsetGrid(x, years = 1985:1995)
@@ -105,6 +106,7 @@
 #'                      scaleGrid.args = list(type = "standardize"),
 #'                      method = "GLM", condition = "GT", threshold = 0,
 #'                      prepareData.args = list("local.predictors" = list(vars = "hus@850", n = 4)))
+#' }
 
 downscaleCV <- function(x, y, method,
                         sampling.strategy = "kfold.chronological", folds = 4, 

diff --git a/R/downscalePredict.R b/R/downscalePredict.R
@@ -33,9 +33,10 @@
 #' @importFrom transformeR gridArithmetics
 #' @importFrom sticky sticky
 #' @export
-#' @examples 
+#' @examples \donttest{
 #' # Loading data
-#' library(downscaleR)
+#' require(transformeR)
+#' require(climate4R.datasets)
 #' data("VALUE_Iberia_tas")
 #' y <- VALUE_Iberia_tas
 #' data("NCEP_Iberia_hus850", "NCEP_Iberia_psl", "NCEP_Iberia_ta850")
@@ -59,6 +60,7 @@
 #' pred  <- downscalePredict(newdata, model.analogs)  # predicting
 #' # Plotting the results for station 5
 #' plot(yt$Data[,5],pred$Data[,5])
+#' }
 
 downscalePredict <- function(newdata, model) {
   n <- length(newdata$x.global) # number of members
@@ -175,4 +177,4 @@ downs.predict <- function(x, method, atomic_model){
          analogs = pred <- analogs.test(x, atomic_model$dataset_x, atomic_model$dataset_y, atomic_model$dates, atomic_model$info),
          GLM     = pred <- glm.predict(x, atomic_model$weights, atomic_model$info),
          NN      = pred <- nn.predict(atomic_model, x)) 
-  return(pred)}
+  return(pred)}
diff --git a/R/downscaleTrain.R b/R/downscaleTrain.R
@@ -117,6 +117,7 @@
 #' @examples \donttest{
 #' # Loading data
 #' require(transformeR)
+#' require(climate4R.datasets)
 #' data("VALUE_Iberia_tas")
 #' y <- VALUE_Iberia_tas
 #' data("NCEP_Iberia_hus850", "NCEP_Iberia_psl", "NCEP_Iberia_ta850")

diff --git a/R/prepareData.R b/R/prepareData.R
@@ -70,8 +70,10 @@
 #' @export
 #'  
 #' @author J. Bedia, D. San-Martín and J.M. Gutiérrez 
-#' @examples
+#' @examples \donttest{
+#' require(transformeR)
 #' # Loading data
+#' require(climate4R.datasets)
 #' data("VALUE_Iberia_tas")
 #' y <- VALUE_Iberia_tas 
 #' data("NCEP_Iberia_hus850", "NCEP_Iberia_psl", "NCEP_Iberia_ta850")
@@ -88,6 +90,7 @@
 #' # Using joined PCs and local predictors: the 4 closest gridboxes
 #' data <- prepareData(x = x, y = y,local.predictors = list(n=4, vars = getVarNames(x)),
 #' spatial.predictors = list(v.exp = 0.95, which.combine =getVarNames(x)))
+#' }
 
 prepareData <- function(x, y, global.vars = NULL, combined.only = TRUE, spatial.predictors = NULL, local.predictors = NULL, extended.predictors = NULL) {
     y <- getTemporalIntersection(obs = y, prd = x, which.return = "obs")

diff --git a/R/prepareNewData.R b/R/prepareNewData.R
@@ -26,7 +26,9 @@
 #' @family downscaling.helpers
 #' @importFrom transformeR getVarNames subsetGrid redim getShape getCoordinates grid2PCs getRefDates array3Dto2Dmat grid2PCs
 #' @importFrom magrittr %>% extract2 
-#' @examples
+#' @examples \donttest{
+#' require(transformeR)
+#' require(climate4R.datasets)
 #' # Loading data
 #' data("VALUE_Iberia_tas")
 #' y <- VALUE_Iberia_tas 
@@ -36,6 +38,7 @@
 #' data <- prepareData(x = x, y = y, spatial.predictors = list(v.exp = 0.95))
 #' # Projecting a new dataset to the calculated EOFs
 #' newdata <- prepareNewData(x,data)
+#' }
 
 prepareNewData <- function(newdata, data.structure) {
   x.varnames <- attr(data.structure, "predictor.vars")

diff --git a/R/quickDiagnostics.R b/R/quickDiagnostics.R
@@ -17,7 +17,8 @@
 #' @return Two diagnostic plots with observed, simulated and (possibly) downscaled time series, and a QQ-plot by percentlies.
 #' @author M. Iturbide 
 #' @export
-#' @examples {
+#' @examples \donttest{
+#' require(climate4R.datasets)
 #' data("VALUE_Iberia_pr")
 #' data("NCEP_Iberia_pr")
 #' y <- VALUE_Iberia_pr
@@ -83,7 +84,8 @@ quickDiagnostics <- function(obs,
 #' @importFrom stats sd cor
 #' @importFrom grDevices rgb
 #' @keywords internal
-#' @importFrom transformeR subsetGrid getCoordinates getYearsAsINDEX draw.world.lines aggregateGrid climatology plotClimatology interpGrid getGrid
+#' @importFrom transformeR subsetGrid getCoordinates getYearsAsINDEX aggregateGrid climatology interpGrid getGrid
+#' @importFrom visualizeR spatialPlot
 #' @importFrom sp SpatialPoints
 
 interannualOutlook <- function(obs, raw, downscaled = NULL, location = c(-42.5, -3), na.tolerance = .3, ylim = NULL, main = NULL){
@@ -189,11 +191,11 @@ interannualOutlook <- function(obs, raw, downscaled = NULL, location = c(-42.5,
              }
        }
        plcor <- 
-             plotClimatology(corgrid, backdrop.theme = "countries", cuts = seq(-1,1,0.25),
-                                key.space = "bottom", scales=list(draw = TRUE),
-                             auto.key = T,par.settings=list(fontsize=list(text= 8)),
-                       sp.layout = list(list(SpatialPoints(matrix(location,ncol = 2)), 
-                                             first = FALSE, pch = 2, cex = 1.8, col = "black")))
+          visualizeR::spatialPlot(corgrid, backdrop.theme = "countries", cuts = seq(-1,1,0.25),
+                                  key.space = "bottom", scales = list(draw = TRUE),
+                                  auto.key = TRUE, par.settings = list(fontsize = list(text = 8)),
+                                  sp.layout = list(list(SpatialPoints(matrix(location, ncol = 2)), 
+                                                        first = FALSE, pch = 2, cex = 1.8, col = "black")))
        grid.arrange(pl, plcor, nrow = 1, ncol = 2, widths = c(1.4,1))
 }
 #end
@@ -293,4 +295,4 @@ dailyOutlook <- function(obs, raw, downscaled = NULL, location = c(-42.5, -3), y
 grabGrob <- function(){
       grid.echo()
       grid.grab()
-}
+}
diff --git a/man/biasCorrection.Rd b/man/biasCorrection.Rd
diff --git a/man/downscale.Rd b/man/downscale.Rd
diff --git a/man/downscaleCV.Rd b/man/downscaleCV.Rd
diff --git a/man/downscalePredict.Rd b/man/downscalePredict.Rd
diff --git a/man/downscaleTrain.Rd b/man/downscaleTrain.Rd