Resolve "Migrate from raster to terra"

.Rbuildignore

@@ -5,3 +5,4 @@
 ^\README.Rmd$
 ^dev_history\.R$
 ^\.github$
+^data-raw$

.gitignore

@@ -6,3 +6,4 @@ src/*.so
 src/*.dll
 README.html
 README.Rmd
+data-raw/*.RData

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: remote
 Title: Empirical Orthogonal Teleconnections in R
-Version: 1.2.3
-Authors@R:
+Version: 1.2.3.9009
+Authors@R: 
     c(person(given = "Tim",
              family = "Appelhans",
              role = c("cre", "aut"),
@@ -25,24 +25,29 @@ Description: Empirical orthogonal teleconnections in R.
     space and time, EOT analysis produces patterns that are orthogonal in
     either space or time.
 License: GPL (>= 3) | file LICENSE
-Depends:
+Depends: 
     Rcpp (>= 0.10.3),
     raster,
-    methods
-Imports:
+    methods,
+    R (>= 3.5)
+Imports: 
     grDevices,
     gridExtra,
     latticeExtra,
     mapdata,
     scales, 
     stats, 
+    terra,
     utils
-Suggests:
-    maps,
-    lattice,
+Suggests: 
+    checkmate,
     grid,
-    sp
+    lattice,
+    maps,
+    sp, 
+    tinytest
 LinkingTo: Rcpp
-RoxygenNote: 7.3.2
 Roxygen: list(markdown = TRUE)
 Encoding: UTF-8
+Config/roxygen2/version: 8.0.0
+LazyData: true

NAMESPACE

@@ -10,17 +10,17 @@ export(denoise)
 export(deseason)
 export(geoWeight)
 export(getWeights)
-export(lagalize)
-export(longtermMeans)
+export(nmodes)
 export(readEot)
 export(subset)
 exportClasses(EotMode)
 exportClasses(EotStack)
 exportMethods("names<-")
 exportMethods(eot)
+exportMethods(lagalize)
+exportMethods(longtermMeans)
 exportMethods(nXplain)
 exportMethods(names)
-exportMethods(nmodes)
 exportMethods(plot)
 exportMethods(predict)
 exportMethods(writeEot)
@@ -32,6 +32,7 @@ import(methods)
 import(parallel)
 import(raster)
 import(scales)
+import(terra)
 importFrom(grDevices,colorRampPalette)
 importFrom(grDevices,hcl)
 importFrom(stats,cov.wt)

NEWS.md

@@ -1,3 +1,18 @@
+# remote 1.2.3.9009 (2026-07-22)
+
+#### ✨ features and improvements
+
+  * `anomalize()` fails gracefully if 'reference' is not a raster object, and 
+    uses the 1st layer (with a warning) if a multi-layer object is supplied.
+  * `denoise()` fails gracefully if neither 'expl.var' nor 'k' are supplied.
+
+#### 🐛 bug fixes
+
+#### 💬 documentation etc
+
+#### 🍬 miscellaneous
+
+
 # remote 1.2.3 (2025-04-12)
 
 #### 💬 documentation etc

R/AAAremoteClasses.R

@@ -6,54 +6,58 @@
 #' @slot coords_bp the coordinates of the identified base point
 #' @slot cell_bp the cell number of the indeified base point
 #' @slot cum_exp_var the cumulative explained variance of the considered EOT mode
-#' @slot r_predictor the RasterLayer of the correlation coefficients between the base point and each pixel of the predictor domain
+#' @slot r_predictor `SpatRaster` of the correlation coefficients between the base point and each pixel of the predictor domain
 #' @slot rsq_predictor as above but for the coefficient of determination of the predictor domain
 #' @slot rsq_sums_predictor as above but for the sums of coefficient of determination of the predictor domain
-#' @slot int_predictor the RasterLayer of the intercept of the regression equation for each pixel of the predictor domain
-#' @slot slp_predictor same as above but for the slope of the regression equation for each pixel of the predictor domain
-#' @slot p_predictor the RasterLayer of the significance (p-value) of the the regression equation for each pixel of the predictor domain
-#' @slot resid_predictor the RasterBrick of the reduced data for the predictor domain 
-#' @slot r_response the RasterLayer of the correlation coefficients between the base point and each pixel of the response domain
+#' @slot int_predictor `SpatRaster` of the intercept of the regression equation for each pixel of the predictor domain
+#' @slot slp_predictor as above but for the slope of the regression equation for each pixel of the predictor domain
+#' @slot p_predictor `SpatRaster` of the significance (p-value) of the regression equation for each pixel of the predictor domain
+#' @slot resid_predictor `SpatRaster` of the reduced data for the predictor domain
+#' @slot r_response `SpatRaster` of the correlation coefficients between the base point and each pixel of the response domain
 #' @slot rsq_response as above but for the coefficient of determination of the response domain
-#' @slot int_response the RasterLayer of the intercept of the regression equation for each pixel of the response domain
+#' @slot int_response `SpatRaster` of the intercept of the regression equation for each pixel of the response domain
 #' @slot slp_response as above but for the slope of the regression equation for each pixel of the response domain
-#' @slot p_response same the RasterLayer of the significance (p-value) of the the regression equation for each pixel of the response domain
-#' @slot resid_response the RasterBrick of the reduced data for the response domain 
+#' @slot p_response `SpatRaster` of the significance (p-value) of the regression equation for each pixel of the response domain
+#' @slot resid_response `SpatRaster` of the reduced data for the response domain
 #' 
 #' @exportClass EotMode
 #' @rdname EotMode-class
 
-setClass('EotMode',
-         slots = c(mode = 'integer',
-                   name = 'character',
-                   eot = 'numeric',
-                   coords_bp = 'matrix',
-                   cell_bp = 'integer',
-                   cum_exp_var = 'numeric',
-                   r_predictor = 'RasterLayer',
-                   rsq_predictor = 'RasterLayer',
-                   rsq_sums_predictor = 'RasterLayer',
-                   int_predictor = 'RasterLayer', 
-                   slp_predictor = 'RasterLayer',
-                   p_predictor = 'RasterLayer',
-                   resid_predictor = 'RasterBrick',
-                   r_response = 'RasterLayer',
-                   rsq_response = 'RasterLayer',
-                   int_response = 'RasterLayer', 
-                   slp_response = 'RasterLayer',
-                   p_response = 'RasterLayer',
-                   resid_response = 'RasterBrick'))
+methods::setClass(
+  'EotMode'
+  , slots = c(mode = 'integer'
+    , name = 'character'
+    , eot = 'numeric'
+    , coords_bp = 'matrix'
+    , cell_bp = 'integer'
+    , cum_exp_var = 'numeric'
+    , r_predictor = 'SpatRaster'
+    , rsq_predictor = 'SpatRaster'
+    , rsq_sums_predictor = 'SpatRaster'
+    , int_predictor = 'SpatRaster'
+    , slp_predictor = 'SpatRaster'
+    , p_predictor = 'SpatRaster'
+    , resid_predictor = 'SpatRaster'
+    , r_response = 'SpatRaster'
+    , rsq_response = 'SpatRaster'
+    , int_response = 'SpatRaster'
+    , slp_response = 'SpatRaster'
+    , p_response = 'SpatRaster'
+    , resid_response = 'SpatRaster'
+  )
+)
 
 NULL
 
 #' Class EotStack
+#' 
 #' @slot modes a list containing the individual 'EotMode's of the 'EotStack'
 #' @slot names the names of the modes
 #' 
 #' @exportClass EotStack
 #' @rdname EotStack-class
 
-setClass('EotStack',
+methods::setClass('EotStack',
          slots = c(modes = 'list',
                    names = 'character'))