Make mkinpredict consistently return a dataframe

1 files changed, 16 insertions, 16 deletions

diff --git a/R/mkinpredict.R b/R/mkinpredict.R
index df51dbe3..8c76ca05 100644
--- a/R/mkinpredict.R
+++ b/R/mkinpredict.R
@@ -37,7 +37,7 @@
 #'   solver is used.
 #' @import deSolve
 #' @importFrom inline getDynLib
-#' @return A matrix in the same format as the output of \code{\link{ode}}.
+#' @return A data frame with the solution in wide format
 #' @author Johannes Ranke
 #' @examples
 #'
@@ -72,27 +72,27 @@
 #'
 #' # Check compiled model versions - they are faster than the eigenvalue based solutions!
 #' SFO_SFO = mkinmod(parent = list(type = "SFO", to = "m1"),
-#'                   m1 = list(type = "SFO"), use_of_ff = "min")
+#'                   m1 = list(type = "SFO"), use_of_ff = "max")
 #' if(require(rbenchmark)) {
-#'   benchmark(
-#'     eigen = mkinpredict(SFO_SFO, c(k_parent_m1 = 0.05, k_parent_sink = 0.1, k_m1_sink = 0.01),
+#'   benchmark(replications = 10, order = "relative", columns = c("test", "relative", "elapsed"),
+#'     eigen = mkinpredict(SFO_SFO,
+#'       c(k_parent = 0.15, f_parent_to_m1 = 0.5, k_m1 = 0.01),
 #'       c(parent = 100, m1 = 0), seq(0, 20, by = 0.1),
 #'       solution_type = "eigen")[201,],
-#'     deSolve_compiled = mkinpredict(SFO_SFO, 
-#'       c(k_parent_m1 = 0.05, k_parent_sink = 0.1, k_m1_sink = 0.01),
+#'     deSolve_compiled = mkinpredict(SFO_SFO,
+#'       c(k_parent = 0.15, f_parent_to_m1 = 0.5, k_m1 = 0.01),
 #'       c(parent = 100, m1 = 0), seq(0, 20, by = 0.1),
 #'       solution_type = "deSolve")[201,],
-#'     deSolve = mkinpredict(SFO_SFO, c(k_parent_m1 = 0.05, k_parent_sink = 0.1, k_m1_sink = 0.01),
-#'      c(parent = 100, m1 = 0), seq(0, 20, by = 0.1),
-#'      solution_type = "deSolve", use_compiled = FALSE)[201,],
-#'     replications = 10)
+#'     deSolve = mkinpredict(SFO_SFO,
+#'       c(k_parent = 0.15, f_parent_to_m1 = 0.5, k_m1 = 0.01),
+#'       c(parent = 100, m1 = 0), seq(0, 20, by = 0.1),
+#'       solution_type = "deSolve", use_compiled = FALSE)[201,],
+#'     analytical = mkinpredict(SFO_SFO,
+#'       c(k_parent = 0.15, f_parent_to_m1 = 0.5, k_m1 = 0.01),
+#'       c(parent = 100, m1 = 0), seq(0, 20, by = 0.1),
+#'       solution_type = "analytical", use_compiled = FALSE)[201,])
 #' }
 #'
-#' # Since mkin 0.9.49.11 we also have analytical solutions for some models, including SFO-SFO
-#' #    deSolve = mkinpredict(SFO_SFO, c(k_parent_m1 = 0.05, k_parent_sink = 0.1, k_m1_sink = 0.01),
-#' #     c(parent = 100, m1 = 0), seq(0, 20, by = 0.1),
-#' #     solution_type = "analytical", use_compiled = FALSE)[201,],
-#'
 #' \dontrun{
 #'   # Predict from a fitted model
 #'   f <- mkinfit(SFO_SFO, FOCUS_2006_C, quiet = TRUE)
@@ -209,7 +209,7 @@ mkinpredict.mkinmod <- function(x,
     }
     return(out_mapped)
   } else {
-    return(out)
+    return(as.data.frame(out))
   }
 }