add news, plot docu, update vignette

NEWS.md

@@ -1,8 +1,12 @@
 # fmeffects 0.1.3
 
 -   `fme` and `ame` automatically extract the name of the model's target variable from the model.
--   Added support for `"lm"`-type models, such as `stats::glm` and `mgcv::gam`.
+-    Added support for `"lm"`-type models, such as `stats::glm` and `mgcv::gam`.
 -   `fme` now computes NLMs via parallel processing with `future` and displays a progress bar while doing so.
+-    Multivariate effects for more than two features can be computed and visualized.
+-    Improved visualizations (especially for larger data sets) via hexagon plots.
+-    Better error communication with `cli`.
+-    Feature interactions for categorical features are supported.
 
 # fmeffects 0.1.0
 

R/FME.R

@@ -124,9 +124,9 @@ ForwardMarginalEffect = R6::R6Class("ForwardMarginalEffect",
     #' @description
     #' Plots results, i.e., FME (and NLMs) for non-extrapolation points, for an `FME` object.
     #' @param with.nlm Plots NLMs if computed, defaults to `FALSE`.
-    #' @param bins Numeric vector giving number of bins in both vertical and horizontal directions.
+    #' @param bins Numeric vector giving number of bins in both vertical and horizontal directions.  Applies only to univariate or bivariate numeric effects.
     #'   See [ggplot2::stat_summary_hex()] for details.
-    #' @param binwidth Numeric vector giving bin width in both vertical and horizontal directions. Overrides bins if both set.
+    #' @param binwidth Numeric vector giving bin width in both vertical and horizontal directions. Overrides bins if both set. Applies only to univariate or bivariate numeric effects.
     #'   See [ggplot2::stat_summary_hex()] for details.
     #' @examples
     #' # Compute results:

R/FMEPlot.R

@@ -16,8 +16,9 @@ FMEPlot = R6::R6Class("FMEPlot",
 
     initializeSubclass = function(results, data, feature, step.size) {
 
-      # Check if results is a data.table with a minimum of one observation
-      checkmate::assertDataTable(results, min.rows = 1)
+      if (!checkmate::test_true(unique(results$fme) == 1)) {
+        cli::cli_abort(paste("Cannot plot effects if they all have the same value."))
+      }
 
       self$feature = feature
       self$step.size = step.size

vignettes/fmeffects.Rmd

@@ -92,7 +92,7 @@ effects2 = fme(model = forest,
                ep.method = "envelope")
 ```
 
-For bivariate effects, we can plot the effects (we cannot for more than two features):
+For bivariate effects, we can plot the effects in a way similar to univariate effects (for more than two features, we can plot only the histogram of effects):
 
 ```{r, message=FALSE}
 plot(effects2)