Finish adapting to upcoming deSolve

2 files changed, 8 insertions, 11 deletions

diff --git a/man/mkinpredict.Rd b/man/mkinpredict.Rd
index d93c0753..ad749fa4 100644
--- a/man/mkinpredict.Rd
+++ b/man/mkinpredict.Rd
@@ -21,7 +21,6 @@ mkinpredict(x, odeparms, odeini, outtimes, ...)
   maxsteps = 20000L,
   map_output = TRUE,
   na_stop = TRUE,
-  call_lsoda = NULL,
   ...
 )
 
@@ -69,7 +68,8 @@ parent compound.}
 \link{mkinmod} model is used, even if is present.}
 
 \item{method.ode}{The solution method passed via \link{mkinpredict} to \link{ode}] in
-case the solution type is "deSolve" and we are not using compiled code.}
+case the solution type is "deSolve" and we are not using compiled code.
+When using compiled code, only lsoda is supported.}
 
 \item{atol}{Absolute error tolerance, passed to the ode solver.}
 
@@ -83,8 +83,6 @@ FALSE). Setting this to FALSE has no effect for analytical solutions,
 as these always return mapped output.}
 
 \item{na_stop}{Should it be an error if \link{ode} returns NaN values}
-
-\item{call_lsoda}{The address of the compiled function "call_lsoda"}
 }
 \value{
 A matrix with the numeric solution in wide format
@@ -111,11 +109,11 @@ mkinpredict(SFO, c(k_degradinol = 0.3), c(degradinol = 100), 0:20,
 mkinpredict(SFO, c(k_degradinol = 0.3), c(degradinol = 100), 0:20,
       solution_type = "analytical")[21,]
 mkinpredict(SFO, c(k_degradinol = 0.3), c(degradinol = 100), 0:20,
-      method = "lsoda")[21,]
+      method = "lsoda", use_compiled = FALSE)[21,]
 mkinpredict(SFO, c(k_degradinol = 0.3), c(degradinol = 100), 0:20,
-      method = "ode45")[21,]
+      method = "ode45", use_compiled = FALSE)[21,]
 mkinpredict(SFO, c(k_degradinol = 0.3), c(degradinol = 100), 0:20,
-      method = "rk4")[21,]
+      method = "rk4", use_compiled = FALSE)[21,]
 # rk4 is not as precise here
 
 # The number of output times used to make a lot of difference until the
diff --git a/man/mmkin.Rd b/man/mmkin.Rd
index 309761dd..438a237b 100644
--- a/man/mmkin.Rd
+++ b/man/mmkin.Rd
@@ -83,16 +83,15 @@ plot_sep(fits.0[[1, 1]])
 # allow to plot the observed variables separately
 plot(fits.0[1, 1])
 
-# On Windows, we can use multiple cores by making a cluster using the parallel
-# package, which gets loaded with mkin, and passing it to mmkin, e.g.
-cl <- makePSOCKcluster(12)
+# On Windows, we can use multiple cores by making a cluster first
+cl <- parallel::makePSOCKcluster(12)
 f <- mmkin(c("SFO", "FOMC", "DFOP"),
   list(A = FOCUS_2006_A, B = FOCUS_2006_B, C = FOCUS_2006_C, D = FOCUS_2006_D),
   cluster = cl, quiet = TRUE)
 print(f)
 # We get false convergence for the FOMC fit to FOCUS_2006_A because this
 # dataset is really SFO, and the FOMC fit is overparameterised
-stopCluster(cl)
+parallel::stopCluster(cl)
 }
 
 }