Add print function for BIOMOD.options.dataset and BIOMOD.models.options

NAMESPACE

@@ -117,6 +117,7 @@ exportMethods(get_variables_importance)
 exportMethods(load_stored_object)
 exportMethods(plot)
 exportMethods(predict)
+exportMethods(print)
 exportMethods(show)
 exportMethods(summary)
 importFrom(PresenceAbsence,optimal.thresholds)

R/biomod2_classes_0.R

@@ -198,6 +198,9 @@ setMethod('BIOMOD.options.default', signature(mod = 'character', typ = 'characte
 ##' and validation datasets
 ##' 
 ##' @param object a \code{\link{BIOMOD.options.dataset}} object
+##' @param x a \code{\link{BIOMOD.options.dataset}} object
+##' @param dataset a \code{character} corresponding to the name of a dataset contained 
+##' in the \code{arg.values} slot
 ##' 
 ##' @slot model a \code{character} corresponding to the model
 ##' @slot type a \code{character} corresponding to the data type 
@@ -523,7 +526,7 @@ setMethod('BIOMOD.options.dataset', signature(strategy = 'character'),
 ##'
 
 
-## Attention ! print only values for _allData_allRun for now
+## Attention ! print only values for _allData_allRun
 setMethod('show', signature('BIOMOD.options.dataset'),
           function(object)
           {
@@ -532,6 +535,35 @@ setMethod('show', signature('BIOMOD.options.dataset'),
             dataset <- ifelse("_allData_allRun" %in% names(object@args.values)
                               , "_allData_allRun", names(object@args.values)[1])
             cat('\n\t   ( dataset', dataset, ')')
+
+            for (arg in names(object@args.values[[dataset]])) {
+              val.def = capture.output(object@args.default[[arg]])
+              val.used = capture.output(object@args.values[[dataset]][[arg]])
+
+              cat('\n\t\t- ', arg, "=", sub("\\[1\\] ", "", val.used))
+              if (!is.null(val.used) && !is.null(val.def) &&
+                  (length(val.used) != length(val.def) || any(val.used != val.def))) {
+                cat('   (default:', sub("\\[1\\] ", "", val.def), ')')
+              }
+            }
+            cat("\n")
+          }
+)
+
+##'
+##' @rdname BIOMOD.options.dataset
+##' @export
+##'
+
+setMethod('print', signature('BIOMOD.options.dataset'),
+          function(x, dataset = '_allData_allRun')
+          {
+            object = x
+            cat('\n\t> ', object@model, 'options (datatype:', object@type, ', package:', object@package, ', function:', object@func, ') :')
+            dataset <- ifelse(dataset %in% names(object@args.values)
+                              , dataset, ifelse("_allData_allRun" %in% names(object@args.values)
+                                                , "_allData_allRun", names(object@args.values)[1]))
+            cat('\n\t   ( dataset', dataset, ')')
 
             for (arg in names(object@args.values[[dataset]])) {
               val.def = capture.output(object@args.default[[arg]])
@@ -562,6 +594,10 @@ setMethod('show', signature('BIOMOD.options.dataset'),
 ##' \code{\link{BIOMOD_Modeling}}
 ##' 
 ##' @param object a \code{\link{BIOMOD.models.options}} object
+##' @param x a \code{\link{BIOMOD.models.options}} object
+##' @param dataset a \code{character} corresponding to the name of a dataset contained 
+##' in the \code{arg.values} slot of the \code{\link{BIOMOD.options.dataset}} object 
+##' for each model
 ##' 
 ##' @slot models a \code{vector} containing model names for which options have 
 ##' been retrieved and defined, must be \code{algo.datatype.package.function}
@@ -613,6 +649,23 @@ setMethod('show', signature('BIOMOD.models.options'),
           }
 )
 
+##'
+##' @rdname BIOMOD.models.options
+##' @export
+##'
+
+setMethod('print', signature('BIOMOD.models.options'),
+          function(x, dataset = '_allData_allRun')
+          {
+            object = x
+            .bm_cat("BIOMOD.models.options")
+            for (mod in object@models) {
+              print(object@options[[mod]], dataset = dataset)
+            }
+            .bm_cat()
+          }
+)
+
 # test <- .fun_testIfIn(test, "GLM$test", object@GLM$test, c("AIC", "BIC", "none"))
 # test <- .fun_testIfIn(test, "GBM$distribution", object@GBM$distribution, c("bernoulli", "huberized", "multinomial", "adaboost"))
 # test <- .fun_testIfIn(test, "CTA$method", object@CTA$method, c("anova", "poisson", "class", "exp"))

R/bm_Tuning.R

@@ -27,8 +27,9 @@
 ##' A \code{data.frame} object returned by \code{\link{get_calib_lines}} or 
 ##' \code{\link{bm_CrossValidation}} functions
 ##' @param metric.eval a \code{character} corresponding to the evaluation metric to be used, must 
-##' be either \code{ROC}, \code{TSS}, \code{KAPPA} for \code{SRE} only, and \code{auc.val.avg}, 
-##' \code{auc.diff.avg}, \code{or.mtp.avg}, \code{or.10p.avg}, \code{AICc} for \code{MAXENT} only
+##' be either \code{AUC}, \code{Kappa} or \code{TSS} for \code{SRE} only ; \code{auc.val.avg}, 
+##' \code{auc.diff.avg}, \code{or.mtp.avg}, \code{or.10p.avg}, \code{AICc} for \code{MAXENT} only ; 
+##' \code{ROC} or \code{TSS} for all other models
 ##' @param metric.AIC a \code{character} corresponding to the AIC metric to be used, must 
 ##' be either \code{AIC} or \code{BIC}
 ##' @param weights (\emph{optional, default} \code{NULL}) \cr