Avoid the call to merge for analytical solutions

This increases performance up to a factor of five!

4 files changed, 22 insertions, 22 deletions

diff --git a/man/mkinfit.Rd b/man/mkinfit.Rd
index b728aded..db3f5f3e 100644
--- a/man/mkinfit.Rd
+++ b/man/mkinfit.Rd
@@ -26,7 +26,6 @@ mkinfit(
   quiet = FALSE,
   atol = 1e-08,
   rtol = 1e-10,
-  n.outtimes = 10,
   error_model = c("const", "obs", "tc"),
   error_model_algorithm = c("auto", "d_3", "direct", "twostep", "threestep",
     "fourstep", "IRLS", "OLS"),
@@ -141,11 +140,6 @@ is 1e-8, lower than in \code{\link{lsoda}}.}
 \item{rtol}{Absolute error tolerance, passed to \code{\link{ode}}. Default
 is 1e-10, much lower than in \code{\link{lsoda}}.}
 
-\item{n.outtimes}{The length of the dataseries that is produced by the model
-prediction function \code{\link{mkinpredict}}. This impacts the accuracy
-of the numerical solver if that is used (see \code{solution_type}
-argument.}
-
 \item{error_model}{If the error model is "const", a constant standard
   deviation is assumed.
 
diff --git a/man/mkinmod.Rd b/man/mkinmod.Rd
index 2ba917d6..a5736be7 100644
--- a/man/mkinmod.Rd
+++ b/man/mkinmod.Rd
@@ -82,7 +82,7 @@ The IORE submodel is not well tested for metabolites. When using this
 \examples{
 
 # Specify the SFO model (this is not needed any more, as we can now mkinfit("SFO", ...)
-SFO <- mkinmod(parent = list(type = "SFO"))
+SFO <- mkinmod(parent = mkinsub("SFO"))
 
 # One parent compound, one metabolite, both single first order
 SFO_SFO <- mkinmod(
diff --git a/man/mkinpredict.Rd b/man/mkinpredict.Rd
index f7e4acfc..1ba5b5f8 100644
--- a/man/mkinpredict.Rd
+++ b/man/mkinpredict.Rd
@@ -91,7 +91,7 @@ FALSE).}
 solver is used.}
 }
 \value{
-A matrix in the same format as the output of \code{\link{ode}}.
+A data frame with the solution in wide format
 }
 \description{
 This function produces a time series for all the observed variables in a
@@ -131,30 +131,35 @@ mkinpredict(SFO, c(k_degradinol = 0.3), c(degradinol = 100),
 
 # 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,],
+    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,]
 
 \dontrun{
   # Predict from a fitted model
   f <- mkinfit(SFO_SFO, FOCUS_2006_C, quiet = TRUE)
+  f <- mkinfit(SFO_SFO, FOCUS_2006_C, quiet = TRUE, solution_type = "analytical")
   head(mkinpredict(f))
 }
 
diff --git a/man/plot.mkinfit.Rd b/man/plot.mkinfit.Rd
index c3f3134a..4235557e 100644
--- a/man/plot.mkinfit.Rd
+++ b/man/plot.mkinfit.Rd
@@ -144,6 +144,7 @@ latex is being used for the formatting of the chi2 error level, if
 \dontrun{
 SFO_SFO <- mkinmod(parent = mkinsub("SFO", "m1", full = "Parent"),
                    m1 = mkinsub("SFO", full = "Metabolite M1" ))
+fit <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE)
 fit <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE, error_model = "tc")
 plot(fit)
 plot_res(fit)