back compatibility for get_predictions with argument model.as.col

export function .transform_model.as.col for ecospat
biomodhub · Jan 16, 2023 · 954e33b · 954e33b
1 parent 014d1c8
commit 954e33b
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Showing 15 changed files with 315 additions and 46 deletions.
diff --git a/NAMESPACE b/NAMESPACE
@@ -2,6 +2,7 @@
 
 export(.transform.outputs.array)
 export(.transform.outputs.list)
+export(.transform_model.as.col)
 export(BIOMOD_ConvertOldRun)
 export(BIOMOD_CrossValidation)
 export(BIOMOD_EnsembleForecasting)

diff --git a/R/BIOMOD_RangeSize.R b/R/BIOMOD_RangeSize.R
@@ -160,9 +160,12 @@
 ##'                                               metric.binary = 'TSS')
 ##' 
 ##' # Load current and future binary projections
-##' CurrentProj <- get_predictions(myBiomodProj, metric.binary = "TSS")
-##' FutureProj <- get_predictions(myBiomodProjectionFuture, metric.binary = "TSS")
-##' 
+##' CurrentProj <- get_predictions(myBiomodProj,
+##'                                metric.binary = "TSS",
+##'                                model.as.col = TRUE)
+##' FutureProj <- get_predictions(myBiomodProjectionFuture,
+##'                                metric.binary = "TSS",
+##'                                model.as.col = TRUE)
 ##' # Compute differences
 ##' myBiomodRangeSize <- BIOMOD_RangeSize(proj.current = CurrentProj, proj.future = FutureProj)
 ##' 
@@ -301,17 +304,6 @@ setMethod('BIOMOD_RangeSize', signature(proj.current = 'SpatRaster', proj.future
 
 .BIOMOD_RangeSize.check.args <- function(proj.current, proj.future) {
 
-  ## Transformation of data.frame so that each column is a model
-  if (inherits(proj.current, "data.frame")) {
-     if (all(c("full.name","points","pred") %in% colnames(proj.current)) &&
-         all(c("full.name","points","pred") %in% colnames(proj.future))) {
-       proj.current <- .transform_df(proj.current)
-       proj.future <- .transform_df(proj.future)
-     } else {
-       stop("'proj.current' and 'proj.future' must have all columns 'full.name' (model name), 'points' (index of prediction) and 'pred' (binary prediction).")
-     }
-  }
-
   ## dimensions checking ------------------------
   if (inherits(proj.current, "data.frame")) {
     dim_current <- nrow(proj.current)
@@ -392,10 +384,3 @@ setMethod('BIOMOD_RangeSize', signature(proj.current = 'SpatRaster', proj.future
   }
 }
 
-# transform data.frame from long to wide for BIOMOD_RangeSize
-##' @importFrom stats reshape
-.transform_df <- function(df){
-  df <- reshape(df[,c("full.name","points","pred")], idvar = "points", timevar = "full.name", direction = "wide")[,-1, drop = FALSE] 
-  colnames(df) <- substring(colnames(df), 6)
-  df
-}
diff --git a/R/biomod2_classes_3.R b/R/biomod2_classes_3.R
@@ -87,6 +87,14 @@
 ##' \code{TSS}, \code{KAPPA}, \code{ACCURACY}, \code{BIAS}, \code{POD}, \code{FAR}, 
 ##' \code{POFD}, \code{SR}, \code{CSI}, \code{ETS}, \code{HK}, \code{HSS}, \code{OR}, \code{ORSS}
 ##' 
+##' @param model.as.col (\emph{optional, default} \code{FALSE}) \cr
+##' A \code{boolean} given to \code{\link{get_predictions}}. If \code{TRUE} 
+##' prediction are returned as a wide \code{data.frame} with each column containing
+##' predictions for a single model and corresponding to the old output given by
+##' \pkg{biomod2} in version < 4.2-2. If \code{FALSE} predictions are returned 
+##' as a long \code{data.frame} with many additional informations readily 
+##' available.
+##' 
 ##' 
 ##' @return 
 ##' 
@@ -468,7 +476,8 @@ setMethod("get_formal_data", "BIOMOD.models.out",
 
 setMethod("get_predictions", "BIOMOD.models.out",
           function(obj, evaluation = FALSE
-                   , full.name = NULL, PA = NULL, run = NULL, algo = NULL)
+                   , full.name = NULL, PA = NULL, run = NULL, algo = NULL,
+                   model.as.col = FALSE)
           {
             if (evaluation && (!obj@has.evaluation.data)) {
               warning("!   Calibration data returned because no evaluation data available")
@@ -486,6 +495,9 @@ setMethod("get_predictions", "BIOMOD.models.out",
             keep_lines <- .filter_outputs.df(out, subset.list = list(full.name =  full.name, PA = PA
                                                                      , run = run, algo = algo))
             out <- out[keep_lines, ]
+            if (model.as.col) {
+              out <- .transform_model.as.col(out)
+            }
             return(out)
           }
 )
@@ -971,7 +983,8 @@ setMethod("get_predictions", "BIOMOD.projection.out",
           function(obj, metric.binary = NULL, metric.filter = NULL
                    , full.name = NULL, PA = NULL, run = NULL, algo = NULL
                    , merged.by.algo = NULL, merged.by.run = NULL
-                   , merged.by.PA = NULL, filtered.by = NULL, ...) {
+                   , merged.by.PA = NULL, filtered.by = NULL, 
+                   model.as.col = FALSE, ...) {
 
             # extract layers from [email protected]@link concerned by metric.filter 
             # or metric.binary
@@ -1009,7 +1022,11 @@ setMethod("get_predictions", "BIOMOD.projection.out",
                                                                          , run = run, algo = algo))
               }
               out <- out[keep_lines, ]
+              if (model.as.col) {
+                out <- .transform_model.as.col(out)
+              }
             }
+
             return(out)
           }
 )
@@ -1256,7 +1273,8 @@ setMethod("get_kept_models", "BIOMOD.ensemble.models.out", function(obj) { retur
 
 setMethod("get_predictions", "BIOMOD.ensemble.models.out",
           function(obj, evaluation = FALSE, full.name = NULL, merged.by.algo = NULL, merged.by.run = NULL
-                   , merged.by.PA = NULL, filtered.by = NULL, algo = NULL)
+                   , merged.by.PA = NULL, filtered.by = NULL, algo = NULL,
+                   model.as.col = FALSE)
           {
             # check evaluation data availability
             if (evaluation && (!get_formal_data(obj)@has.evaluation.data)) {
@@ -1279,6 +1297,9 @@ setMethod("get_predictions", "BIOMOD.ensemble.models.out",
                                                                      , filtered.by = filtered.by
                                                                      , algo = algo))
             out <- out[keep_lines, ]
+            if (model.as.col) {
+              out <- .transform_model.as.col(out)
+            }
             return(out)
           }
 )

diff --git a/R/biomod2_internal.R b/R/biomod2_internal.R
@@ -360,7 +360,7 @@ get_var_range <- function(data)
   }
   proj
 }
-## TRANSFORM models outputs getting specific slot -------------------------------------------------
+## TRANSFORM models outputs getting specific slot --------------------
 ## used in BIOMOD_Modeling.R, BIOMOD_EnsembleModeling.R
 
 .transform_outputs_list = function(obj.type, obj.out, out = 'evaluation')
@@ -430,6 +430,33 @@ get_var_range <- function(data)
   return(output)
 }
 
+## transform predictions data.frame from long to wide with models as columns ----------------
+## used in BIOMOD_RangeSize.R
+##' @name .transform_model.as.col
+##' @author Remi Patin
+##' 
+##' @title Transform predictions data.frame from long to wide with models as columns
+##' 
+##' @description This function is used internally in \code{\link{get_predictions}}
+##' to ensure back-compatibility with former output of \code{\link{get_predictions}}
+##' (i.e. for \pkg{biomod2} version < 4.2-2). It transform a long \code{data.frame}
+##' into a wide \code{data.frame} with each column corresponding to a single model.
+##' 
+##' \emph{Note that the function is intended for internal use but have been 
+##' made available for compatibility with \pkg{ecospat}} 
+##'
+##' @param df a long \code{data.frame}, generally a standard output of 
+##' \code{\link{get_predictions}}
+##' 
+##' @return a wide \code{data.frame}
+##' @importFrom stats reshape
+##' @export
+##' @keywords internal
+.transform_model.as.col <- function(df){
+  df <- reshape(df[,c("full.name","points","pred")], idvar = "points", timevar = "full.name", direction = "wide")[,-1, drop = FALSE] 
+  colnames(df) <- substring(colnames(df), 6)
+  df
+}
 
 ## EXTRACT model names according to specific infos ------------------------------------------------
 ## used in biomod2_classes_3.R, BIOMOD_LoadModels, BIOMOD_Projection, BIOMOD_EnsembleModeling, bm_PlotRangeSize

diff --git a/R/bm_PlotRangeSize.R b/R/bm_PlotRangeSize.R
@@ -136,8 +136,12 @@
 ##'                                               metric.binary = 'TSS')
 ##' 
 ##' # Load current and future binary projections
-##' CurrentProj <- get_predictions(myBiomodProj, metric.binary = "TSS")
-##' FutureProj <- get_predictions(myBiomodProjectionFuture, metric.binary = "TSS")
+##' CurrentProj <- get_predictions(myBiomodProj,
+##'                                metric.binary = "TSS",
+##'                                model.as.col = TRUE)
+##' FutureProj <- get_predictions(myBiomodProjectionFuture,
+##'                                metric.binary = "TSS",
+##'                                model.as.col = TRUE)
 ##' 
 ##' # Compute differences
 ##' myBiomodRangeSize <- BIOMOD_RangeSize(proj.current = CurrentProj, proj.future = FutureProj)

diff --git a/docs/articles/news.html b/docs/articles/news.html
diff --git a/docs/reference/BIOMOD_RangeSize.html b/docs/reference/BIOMOD_RangeSize.html
diff --git a/docs/reference/bm_PlotRangeSize.html b/docs/reference/bm_PlotRangeSize.html