Small fix with weighted mean and multi-band rasters

R/ensemble.R

@@ -43,7 +43,7 @@ NULL
 #' is a fitted [`DistributionModel`] object. Take care not to create an ensemble
 #' of models constructed with different link functions, e.g. logistic vs [log].
 #' In this case the \code{"normalize"} parameter has to be set.
-#' @param ... Provided [`DistributionModel`] objects.
+#' @param ... Provided [`DistributionModel`] or [`SpatRaster`] objects.
 #' @param method Approach on how the ensemble is to be created. See details for
 #'   available options (Default: \code{'mean'}).
 #' @param weights (*Optional*) weights provided to the ensemble function if
@@ -133,14 +133,6 @@ methods::setMethod(
     # Uncertainty calculation
     uncertainty <- match.arg(uncertainty, c('none','sd', 'cv', 'range', 'pca'), several.ok = FALSE)
 
-    # Check that weight lengths is equal to provided distribution objects
-    if(!is.null(weights)) assertthat::assert_that(length(weights) == length(mods))
-    # If weights vector is numeric, standardize the weights
-    if(is.numeric(weights)) {
-      if(any(weights < 0)) weights[weights < 0] <- 0 # Assume those contribute anything
-      weights <- weights / sum(weights)
-    }
-
     # For Distribution model ensembles
     if( all( sapply(mods, function(z) inherits(z, "DistributionModel")) ) ){
       assertthat::assert_that(length(mods)>=2, # Need at least 2 otherwise this does not make sense
@@ -288,6 +280,14 @@ methods::setMethod(
       # If normalize before running an ensemble if parameter set
       if(normalize) ras <- predictor_transform(ras, option = "norm")
 
+      # Check that weight lengths is equal to provided distribution objects
+      if(!is.null(weights) && !is.numeric(layer)) assertthat::assert_that(length(weights) == length(mods))
+      # If weights vector is numeric, standardize the weights
+      if(is.numeric(weights)) {
+        if(any(weights < 0)) weights[weights < 0] <- 0 # Assume those contribute anything
+        weights <- weights / sum(weights)
+      }
+
       # Now ensemble per layer entry
       out <- terra::rast()
       for(lyr in layer){

tests/testthat/test_functions.R

@@ -126,6 +126,11 @@ test_that('Custom functions - Test gridded transformations and ensembles', {
     pp <- ensemble(ras, method = "mean", layer = "mean")
   )
   expect_s4_class(pp, "SpatRaster")
+  # Also test weighted mean
+  expect_no_error(
+    pp <- ensemble(ras, method = "weighted.mean", weights = runif(3, 0.5,1))
+  )
+
 
   # Check centroid calculation
   expect_s3_class(raster_centroid(r1), "sf")